Institut für Geographie und Geologie
Refine
Has Fulltext
- yes (363)
Year of publication
Document Type
- Journal article (208)
- Doctoral Thesis (100)
- Book (35)
- Book article / Book chapter (6)
- Master Thesis (6)
- Report (5)
- Working Paper (2)
- Habilitation (1)
Keywords
- remote sensing (39)
- Einzelhandel (30)
- Fernerkundung (23)
- climate change (18)
- Deutschland (15)
- MODIS (14)
- Sentinel-2 (14)
- time series (14)
- Germany (12)
- Nachhaltigkeit (12)
Institute
- Institut für Geographie und Geologie (363)
- Theodor-Boveri-Institut für Biowissenschaften (9)
- Institut für Altertumswissenschaften (4)
- Graduate School of Science and Technology (3)
- Institut für Informatik (2)
- Frauenklinik und Poliklinik (1)
- Institut für Klinische Epidemiologie und Biometrie (1)
- Julius-von-Sachs-Institut für Biowissenschaften (1)
- Medizinische Klinik und Poliklinik I (1)
- Neuphilologisches Institut - Moderne Fremdsprachen (1)
Schriftenreihe
Sonstige beteiligte Institutionen
- The Italian Federation of Parks and Nature Reserves (3)
- ALPARC - The Alpine Network of Protected Areas (2)
- Eurac research (2)
- Salzburg Institute for Regional Planning and Housing (2)
- Urban Planning Institute of the Republic of Slovenia (2)
- ALPARC - Das Netzwerk Alpiner Schutzgebiete (1)
- Albert-Ludwigs-Universität Freiburg (1)
- Deutsches Klimaservice Zentrum (GERICS) (1)
- Deutsches Zentrum für Luft & Raumfahrt (DLR) (1)
- Deutsches Zentrum für Luft- und Raumfahrt (1)
ResearcherID
- I-5818-2014 (1)
EU-Project number / Contract (GA) number
- 308377 (2)
- 20-3044-2-11 (1)
- 227159 (1)
- 243964 (1)
- 714087 (1)
- 776019 (1)
- 818182 (1)
- 834709 (1)
- LIFE12 BIO/AT/000143 (1)
- LIFE20 NAT/AT/000049 (1)
Der demographische Wandel stellt in den meisten entwickelten Ländern einen externen Treiber dar, der die Entwicklung in und um Nationalparke in Zukunft maßgeblich mitbestimmen wird. Die Alterung der Besucher, die in den nächsten beiden Jahrzehnten die dominante Komponente des demographischen Wandels in Deutschland darstellen dürfte, erfordert von Seiten der Nationalparke eine Anpassung ihrer Besuchermanagementaktivitäten auch im Bereich der Infrastruktur. Hierfür muss jedoch zunächst grundlegendes Wissen über die Altersabhängigkeit raumzeitlichen Verhaltens vorhanden sein. Die zentrale forschungsleitende Frage der vorliegenden Arbeit ist in diesem Kontext angesiedelt und versucht herauszuarbeiten, in welcher Art auftretende Alterseffekte bei der körperlichen Leistungsfähigkeit sowohl die Tourenoptionen im Raum als auch das tatsächliche raumzeitliche Verhalten beeinflussen. Als Untersuchungsgebiet wurde mit dem Nationalpark Berchtesgaden der einzige alpine Nationalpark Deutschlands gewählt. Dieser besitzt aufgrund seiner Topographie ein breites Spektrum an Tourenmöglichkeiten mit unterschiedlichsten Anforderungen an die körperliche Leistungsfähigkeit. Aufbauend auf den theoretischen Erklärungszugängen der Time-Geography und des Constraints-Konzeptes der Freizeitforschung wurde zur Beantwortung der Forschungsfragen ein Methodenmix aus standardisierter Befragung und GPS-Logging zur Aufnahme des Tourenwahlverhaltens eingesetzt. Die gewonnenen Trajektorien wurden mit weiteren Informationen zur Ausstattung des Raumes versehen, um eine detailliertere Beschreibung des raumzeitlichen Verhaltens zu ermöglichen.
Die Analysen zeigen, dass im Nationalpark Berchtesgaden vier Aktivitätstypen mit abweichendem raumzeitlichem Verhalten unterschieden werden können. Nur eine Minderheit von ca. einem Drittel der Besucher wählt dabei Touren, die mit größerer körperlicher Anstrengung verbunden sind. Die restlichen Besucher wandern nur halbtags oder kürzer im Gebiet und überwinden dabei nur wenige Höhenmeter. Im Altersverlauf konnten klare Brüche im raumzeitlichen Verhalten identifiziert werden. So verliert der Aktivitätstypus des Bergsteigers, der sich durch die Begehung alpiner Wege mit Absturzgefahr auszeichnet, bereits ab einem Alter von 50 Jahren stark an Bedeutung. Ab 60 Jahren steigt der Anteil sehr kurzer Touren sprunghaft. Ursachen dieser Veränderungen liegen primär in der Wahrnehmung von eingeschränkter körperlicher Leistungsfähigkeit, sowie einer veränderten Motivationsstruktur.
Diese abweichenden Muster raumzeitlichen Verhaltens sind jedoch auch das Resultat divergierender Tourenoptionen. So konnte gezeigt werden, dass ältere Besucher aufgrund der niedrigen Fortbewegungsgeschwindigkeit nur einen geringeren Anteil der Wege im Nationalpark innerhalb eines bestimmten Zeitbudgets erreichen können.
Wird die Verteilung der Aktivitätstypen unter der Annahme eines ausschließlich wirkenden Alterseffektes in die Zukunft übertragen, bedeutet dies eine Steigerung der Besucherkonzentration in der Managementzone des Nationalparks und eine Bedeutungszunahme von stationären Aktivitäten.
Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012
(2016)
This study is aimed at a better understanding of how upstream runoff formation affected the cropping intensity (CI: number of harvests) in the Aral Sea Basin (ASB) between 2000 and 2012. MODIS 250 m NDVI time series and knowledge-based pixel masking that included settlement layers and topography features enabled to map the irrigated cropland extent (iCE). Random forest models supported the classification of cropland vegetation phenology (CVP: winter/summer crops, double cropping, etc.). CI and the percentage of fallow cropland (PF) were derived from CVP. Spearman’s rho was selected for assessing the statistical relation of CI and PF to runoff formation in the Amu Darya and Syr Darya catchments per hydrological year. Validation in 12 reference sites using multi-annual Landsat-7 ETM+ images revealed an average overall accuracy of 0.85 for the iCE maps. MODIS maps overestimated that based on Landsat by an average factor of ~1.15 (MODIS iCE/Landsat iCE). Exceptional overestimations occurred in case of inaccurate settlement layers. The CVP and CI maps achieved overall accuracies of 0.91 and 0.96, respectively. The Amu Darya catchment disclosed significant positive (negative) relations between upstream runoff with CI (PF) and a high pressure on the river water resources in 2000–2012. Along the Syr Darya, reduced dependencies could be observed, which is potentially linked to the high number of water constructions in that catchment. Intensified double cropping after drought years occurred in Uzbekistan. However, a 10 km × 10 km grid of Spearman’s rho (CI and PF vs. upstream runoff) emphasized locations at different CI levels that are directly affected by runoff fluctuations in both river systems. The resulting maps may thus be supportive on the way to achieve long-term sustainability of crop production and to simultaneously protect the severely threatened environment in the ASB. The gained knowledge can be further used for investigating climatic impacts of irrigation in the region.
This study analyzed the spatiotemporal pattern of settlement expansion in Abuja, Nigeria, one of West Africa’s fastest developing cities, using geoinformation and ancillary datasets. Three epochs of Land-use Land-cover (LULC) maps for 1986, 2001 and 2014 were derived from Landsat images using support vector machines (SVM). Accuracy assessment (AA) of the LULC maps based on the pixel count resulted in overall accuracy of 82%, 92% and 92%, while the AA derived from the error adjusted area (EAA) method stood at 69%, 91% and 91% for 1986, 2001 and 2014, respectively. Two major techniques for detecting changes in the LULC epochs involved the use of binary maps as well as a post-classification comparison approach. Quantitative spatiotemporal analysis was conducted to detect LULC changes with specific focus on the settlement development pattern of Abuja, the federal capital city (FCC) of Nigeria. Logical transitions to the urban category were modelled for predicting future scenarios for the year 2050 using the embedded land change modeler (LCM) in the IDRISI package. Based on the EAA, the result showed that urban areas increased by more than 11% between 1986 and 2001. In contrast, this value rose to 17% between 2001 and 2014. The LCM model projected LULC changes that showed a growing trend in settlement expansion, which might take over allotted spaces for green areas and agricultural land if stringent development policies and enforcement measures are not implemented. In conclusion, integrating geospatial technologies with ancillary datasets offered improved understanding of how urbanization processes such as increased imperviousness of such a magnitude could influence the urban microclimate through the alteration of natural land surface temperature. Urban expansion could also lead to increased surface runoff as well as changes in drainage geography leading to urban floods.
Schutzgebiete und insbesondere Nationalparke haben nach den Richtlinien der IUCN ein Doppelmandat bzw. eine doppelte Funktion: Sie sollen zum einen Räume für Natur- und Artenschutz und zum anderen für Erholung, Umweltbildung und Tourismus bieten und durch letztgenanntes zur Stärkung der Regionalökonomie beitragen. Um diesen Spagat zu meistern, sollten sich Schutzgebiete bzw. deren Verwaltungen und kooperierende Destinationsmarketingorganisationen darüber im Klaren sein, welche Besuchersegmente bzw. Tourismusprodukte im Schutzgebiet anzutreffen sind, bzw. angeboten werden und welchen Einfluss diese auf die Erfüllung des Doppelmandates haben. Die deduktiv entworfene Product-based Typology for Nature-based Tourism von ARNEGGER et al. (2010) bietet hierfür einen zweidimensionalen Analyserahmen, der die Angebots- und Nachfrageperspektive auf den Tourismus und dessen Produkte vereint und bisher noch nicht empirisch angewendet wurde, was das vorrangige Ziel dieser Studie ist.
Hierfür wurde von Theorien und empirischen Studien aus dem Kontext von Natur- und Ökotourismus eine Operationalisierung der Typologie abgeleitet, die am Beispiel des Nationalparks Berchtesgaden eingesetzt wurde. Dabei wurden zwei Ansätze verfolgt, eine angebotsseitige und eine nachfrageseitige Abgrenzung von Tourismusprodukten. Zur empirischen Erfassung von Tourismusprodukten wurde eine umfassende Besucherbefragung in der Sommersaison 2014 durchgeführt, bei der Informationen von rund 1.400 Besuchern des Nationalparks gesammelt werden konnten.
Aus Sicht der Nachfrager wurden sechs Produkt-Cluster identifiziert, die sich bezüglich Reiseaktivitäten und Motiven unterscheiden. Das mit der höchsten Naturaffinität ist das Produkt-Cluster der „Naturbildungsurlauber“ bzw. der „Ökotouristen“. Auf der anderen Seite des Spektrums stehen die „Passiven Erholungsurlauber“ mit einer geringen Nationalparkaffinität. Des Weiteren wurden spezifische Tourismusprodukte aus der Angebotsperspektive, wie Exkursionen der Nationalparkverwaltung oder mehrtägige geführte Wanderungen von spezialisierten Nischenreiseveranstaltern, identifiziert.
Nach der empirischen Abgrenzung der Produkte wurden diese dahingehend überprüft, ob sie sich bezüglich ökonomischer und ökologischer Indikatoren unterscheiden, um zu eruieren, inwieweit die Segmente aus Sicht einer nachhaltigen Regionalentwicklung bzw. aus Sicht des Doppelmandats zu beurteilen sind. Auch hier schneiden etwa die Naturbildungsurlauber relativ gut ab, da sie Muster von structured ecotourism aufweisen und sich durch eine hohe Naturaffinität, positive Einstellungen zu nachhaltigem Tourismus und relativ hohe Reiseausgaben auszeichnen. Bei drei Clustern zeigt sich ein gewisser trade-off: Während die Bergsteiger aus ökologischer jedoch nicht aus ökonomischer Perspektive interessant sind, ist dies bei den allgemeinen Vergnügungs- und Naturerlebnisurlaubern und den passiven Erholungsurlaubern genau umgekehrt.
Basierend auf den Ergebnissen werden mögliche Adaptionen der Typologie diskutiert und darauf aufbauend ein Analyserahmen für eine „Typologie für Nachhaltige Park-Tourismus Produkte“ erarbeitet. Zudem werden theoretische und erste praktische Implikationen für das Management von Schutzgebiets-Destinationen diskutiert, um unter Berücksichtigung der trade-offs das Produktportfolio weiterzuentwickeln, das eine Destination auf den Pfad des sogenannten enlightened mass tourism bringen kann.
The 2007 flood in the Sahel: causes, characteristics and its presentation in the media and FEWS NET
(2012)
During the rainy season in 2007, reports about exceptional rains and floodings in the Sahel were published in the media, especially in August and September. Institutions and organizations like the World Food Programme (WFP) and FEWS NET put the events on the agenda and released alerts and requested help. The partly controversial picture was that most of the Sahel faced a crisis caused by widespread floodings. Our study shows that the rainy season in 2007 was exceptional with regard to rainfall amount and return periods. In many areas the event had a return period between 1 and 50 yr with high spatial heterogeneity, with the exception of the Upper Volta basin, which yielded return periods of up to 1200 yr. Despite the strong rainfall, the interpretation of satellite images show that the floods were mainly confined to lakes and river beds. However, the study also proves the difficulties in assessing the meteorological processes and the demarcation of flooded areas in satellite images without ground truthing. These facts and the somewhat vague and controversial reports in the media and FEWS NET demonstrate that it is crucial to thoroughly analyze such events at a regional and local scale involving the local population.
Objective: The objective of this study was to investigate the applicability of microanalytical methods with high spatial resolution to the characterization of the composition and corrosion behavior of two bracket systems.
Material and methods: The surfaces of six nickel-free brackets and six nickel-containing brackets were examined for signs of corrosion and qualitative surface analysis using an electron probe microanalyzer (EPMA), prior to bonding to patient's tooth surfaces and four months after clinical use. The surfaces were characterized qualitatively by secondary electron (SE) images and back scattered electron (BSE) images in both compositional and topographical mode. Qualitative and quantitative wavelength-dispersive analyses were performed for different elements, and by utilizing qualitative analysis the relative concentration of selected elements was mapped two-dimensionally. The absolute concentration of the elements was determined in specially prepared brackets by quantitative analysis using pure element standards for calibration and calculating correction-factors (ZAF).
Results: Clear differences were observed between the different bracket types. The nickel-containing stainless steel brackets consist of two separate pieces joined by a brazing alloy. Compositional analysis revealed two different alloy compositions, and reaction zones on both sides of the brazing alloy. The nickel-free bracket was a single piece with only slight variation in element concentration, but had a significantly rougher surface. After clinical use, no corrosive phenomena were detectable with the methods applied. Traces of intraoral wear at the contact areas between the bracket slot and the arch wire were verified. Conclusion: Electron probe microanalysis is a valuable tool for the characterization of element distribution and quantitative analysis for corrosion studies.
Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.
Diese Arbeit widmet sich detaillierten stratigraphischen und paläopedologischen Studien an Löss-Paläoboden Sequenzen (LPS) im kontinentalen Nordosten Österreichs, im Lee der Böhmischen Masse relativ zur Westwindzone. Neben methodischen Erkenntnissen ergeben sich allgemeine Schlussfolgerungen über die Klima- und Landschaftsentwicklung während der letzten Million Jahre.
Die untersuchten Aufschlüsse liegen in der Region um Krems (Krems-Schießstätte, Paudorf, Stiefern) und in Stillfried. Einige sind weithin bekannt als ehemalige Typuslokalitäten der Quartärstratigraphie, aber nach fundamentalen Revisionen in den 1970er Jahren schwand das Interesse an diesen merklich. Die LPS befinden sich in Hanglage, so sind polygenetische Einheiten und Erosionslücken üblich. Als Archive einer komplexen geomorphologischen Entwicklung sind sie nicht geeignet für die Anwendung üblicher paläoklimatischer Proxies.
Um die Entstehung der untersuchten LPS zu verstehen, wurde ein multimethodischer Ansatz entwickelt, der detaillierte Untersuchungen von der Landschafts- bis auf die Mikroebene umfasst. Innovativ ist die Verwendung quantitativer Farbmessungen in hoher Auflösung zum Zwecke einer standardisierten Klassifikation von Profileinheiten. Detaillierte mikromorphologische Untersuchungen sind Basis für die Rekonstruktion des Wechselspiels aus äolischer Sedimentation, Pedogenese und Hangprozessen.
Die Korrelation der LPS basiert auf mehreren geochronologischen Ankerpunkten und ist zugleich Hinweis auf tiefgreifende morphologische Veränderungen in der Region Krems während des Pleistozäns. Im chronologischen Rahmen ergeben sich unter Anwendung des Konzepts der klimaphytomorphen Böden qualitative paläoklimatische Schlussfolgerungen:
Kräftig verwitterte Bodenhorizonte sind polygenetisch und nicht das Resultat feuchterer Klimabedingungen während dezidierter Entwicklungsphasen. Die Kontinentalität des Untersuchungsgebiets blieb währenden der letzten Million Jahre weitgehend bestehen, teils mit erhöhtem mediterranem Einfluss. Eine Dominanz atlantischer Feuchte beschränkt(e) sich auf die Regionen westlich der Böhmischen Masse. Die Paläoklimate des Untersuchungs-gebiets waren eher vergleichbar mit jenen des Pannonischen Beckens, obgleich die untersuchten Sequenzen keinen Hinweis auf den dort vermuteten Gradienten zunehmender Aridität zeigen. Interessant sind ferner zahlreiche gebleichte Horizonte innerhalb der Lösssedimente, die als Reste von Tundragleyen interpretiert werden. Diese sind im Löss des Pannonischen Becken nicht nachweisbar. Hieraus wird ein mitteleuropäischer Charakter kaltzeitlichen Klimas innerhalb des untersuchten Zeitrahmens gefolgert.
Massenbewegungen zählen zu den am häufigsten auftretenden Naturgefahren in Deutschland. Dabei wird die von instabilen Hängen ausgehende Gefährdung speziell in den Regionen der Mittelgebirge regelmäßig unterschätzt. In Bezug auf die Verbreitung von Massenbewegungen in Mittelgebirgen stellt das süddeutsche Schichtstufenland einen besonderen Schwerpunkt dar.
Die Disposition der Schichtstufenhänge beruht dabei in erster Linie auf einer Wechsellagerung wasserdurchlässiger und wasserstauender geologischer Schichten. Zu Hanginstabilitäten kommt es bevorzugt in Verbindung mit synthetischem Schichtfallen, steilen Hängen und erhöhten Niederschlägen. Rezente Massenbewegungen treten verstärkt in alten Rutsch- und/oder Hangschuttgebieten auf, da sich dort unkonsolidierte Rutschmassen leicht remobilisieren lassen.
Das Ziel der vorliegenden Arbeit ist es, ein fundiertes Verständnis über Ursachen, Ablauf, Ausprägung und Prozesse von charakteristischen Massenbewegungen sowie dem aktuellen Aufbau der damit verbundenen Schichtstufenhänge in Nordbayern zu erlangen, um daraus grundlegende Einschätzungen zur Stabilität der Rutschgebiete treffen zu können. Neben den rutschungsrelevanten geologischen Schichten sind in diesem Zusammenhang insbesondere der Aufbau, die Eigenschaften und Charakteristika der Rutschmassen von besonderer Wichtigkeit, da besonders die bodenmechanischen und bodenphysikalischen Eigenschaften einen entscheidenden Faktor in Bezug auf die Hangstabilität darstellen. Entsprechend steht die umfassende Analyse dieser Sedimente im Fokus der Studien.
Die Arbeiten betrachten dabei drei Hänge im fränkischen Schichtstufenland, an denen in der jüngeren Vergangenheit Massenbewegungen auftraten. Ein weiteres zentrales Auswahlkriterium war die Lage der Gebiete in den Schichtstufen der Fränkischen Alb und der westlich vorgelagerten Keuperstufe, wobei hinsichtlich Typ und Verbreitung möglichst charakteristische Massenbewegungen für die jeweilige Region ausgewählt wurden. Bei Ebermannstadt stand demnach die sog. Werkkalkstufe der Weißjura-Kalke im Fokus, nahe Wüstendorf die Sandsteine des Braunjura und bei Gailnau an der Frankenhöhe die Sandsteine des mittleren (Gips-) Keupers.
Die Untersuchungen der Rutschungen und ihrer Sedimentcharakteristika erfolgte anhand eines speziell konzipierten Multimethodenansatzes mit zahlreichen, multiskaligen Gelände- und Laboranalysen. Neben klassischen, geomorphologischen Kartierungen an der Oberfläche wurden die sedimentologisch-morphologischen Verhältnisse des oberflächennahen Untergrundes in der Vertikalen durch geophysikalische Sondierungen analysiert. Eine Einschätzung der hydrologischen Verhältnisse der Rutschmassen erfolgte auf Basis von Messdaten aus Bodenfeuchtemonitoringsystemen, die an allen Untersuchungsstandorten installiert wurden. Für die bodenphysikalischen und -mechanischen Eigenschaften der Sedimente wurden Korngrößen, Konsistenzgrenzen, Plastizität, Gefüge und Lagerungsdichte untersucht und durch Tonmineralanalysen ergänzt. Die mikromorphologische Analyse von Dünnschliffen aus Rutschungssedimenten und den darin enthaltenen Deformationsstrukturen erweiterten den Gesamtansatz, ermöglichten neuartige Einblicke in die innere Architektur von Rutschmassen und erlaubten die Rekonstruktion von Bewegungsabläufen.
Durch die Arbeiten konnten an den Standorten Ebermannstadt und Gailnau komplexe, vielschichtige Massenbewegungen nachgewiesen werden. In der Rutschung bei Wüstendorf wurden nahezu ausschließlich unkonsolidierte Sedimente feinerer Korngrößen in einem Fließprozess verlagert. Primär erfolgte bei allen Rutschungen nachweislich die Remobilisierung alter Hangsedimente, wobei darüber hinaus auch stets bisher stabile Areale mit in die Bewegung einbezogen wurden.
Der sedimentologische Aufbau der Rutschmassen ist speziell im Falle großer und komplexer Rutschungen mitunter extrem heterogen. Im Zuge der Arbeiten konnten interne Makrostrukturen der Sedimentablagerungen, wie beispielsweise Rotationsflächen oder die Lage von Schollen detektiert werden. Trotz geophysikalisch und visuell auffälliger Beimischungen von Grobschutt, entfallen die größten Mengenanteile aber stets auf die veränderlich feste Feinmaterialfraktion. Im Rahmen der mikromorphologischen Untersuchungen der Sedimentdünnschliffe konnten auch in diesen Sedimenten zahlreiche Deformationsstrukturen nachgewiesen werden.
Die Arbeit unterstreicht insgesamt die Bedeutung dieser bindigen Bestandteile für die (Re)Mobilisierung von Sedimentablagerungen. Die Stabilität des Feinmaterials steht dabei in engem Zusammenhang mit der hydraulischen Leitfähigkeit und dem Eintrag von Wasser, welches zu wechselnden Steifigkeiten der Sedimente führt. Im Falle erhöhter Bodenwassergehalte konnte eine Plastifizierung der Feinkornfraktion ermittelt werden. Kommt es zu einer starken Durchnässung des Untergrundes, führt dies zu einer Plastifizierung der tonigen Lagen und einer entsprechenden Reduktion der Scherfestigkeit, was letztlich zum Auslösen von Massenbewegungen führt. Neben den geologisch-sedimentologischen Voraussetzungen impliziert dies auch eine hohe Bedeutung der Niederschlagscharakteristika in Bezug auf das Auslösen rezenter Massenbewegungen.
Die Bodenwassergehalte unterliegen im Jahresverlauf einer deutlichen saisonalen Variabilität. Während der Sommermonate wurden einheitlich niedrige Feuchtigkeitswerte im oberflächennahen Untergrund verzeichnet, was in erster Linie auf den Einfluss der Vegetation zurückzuführen ist. Auch sommerliche Starkregenereignisse besitzen unter diesen Bedingungen lediglich eine reduzierte Wirkung auf die Durchfeuchtung des Bodens. Demgegenüber erfolgt während der kalten Jahreszeit ein signifikanter Anstieg der Bodenwassergehalte. Neben den Regenfällen kommt vor allem der Schneeschmelze eine essentielle Bedeutung zu, da sie für eine zusätzliche und anhaltende Durchfeuchtung der Schichten besonders im Spätwinter bzw. Frühjahr sorgt. Entsprechend besteht vor allem während der Monate Februar bis April eine erhöhte Disposition für Rutschungen in Nordbayern. Im Hinblick auf die Niederschlagssummen gingen den Rutschungen in den Untersuchungsgebieten zwar keine besonders extremen Ereignisse, aber durchaus deutlich überdurchschnittliche Niederschlagssummen voraus, weshalb unter Berücksichtigung der im Zuge des Klimawandels ansteigenden Winterniederschläge von einer generell verstärkten Rutschungsaktivität auszugehen ist.
Vergleiche mit den Daten aus zahlreichen Übersichtskartierungen von Rutschungen aus den fränkischen Schichtstufengebieten verdeutlichen, dass die ermittelten Ergebnisse auf eine Vielzahl der verzeichneten Rutschungen übertragbar sind.
The 2010 eruption of Eyjafjallajokull volcano was characterized by pulsating activity. Discrete ash bursts merged at higher altitude and formed a sustained quasi-continuous eruption column. High-resolution near-field videos were recorded on 8-10 May, during the second explosive phase of the eruption, and supplemented by contemporary aerial observations. In the observed period, pulses occurred at intervals of 0.8 to 23.4 s (average, 4.2 s). On the basis of video analysis, the pulse volume and the velocity of the reversely buoyant jets that initiated each pulse were determined. The expansion history of jets was tracked until the pulses reached the height of transition from a negatively buoyant jet to a convective buoyant plume about 100 m above the vent. Based on the assumption that the density of the gas-solid mixture making up the pulse approximates that of the surrounding air at the level of transition from the jet to the plume, a mass flux ranging between 2.2 and 3.5 . 10\(^4\) kg/s was calculated. This mass eruption rate is in good agreement with results obtained with simple models relating plume height with mass discharge at the vent. Our findings indicate that near-field measurements of eruption source parameters in a pulsating eruption may prove to be an effective monitoring tool. A comparison of the observed pulses with those generated in calibrated large-scale experiments reveals very similar characteristics and suggests that the analysis of near-field sensors could in the future help to constrain the triggering mechanism of explosive eruptions.
Cu- and Mn-bearing tourmalines from Brazil and Mozambique were characterised chemically (EMPA and LA-ICP-MS) and by X-ray single-crystal structure refinement. All these samples are rich in Al, Li and F (fluor-elbaite) and contain significant amounts of CuO (up to ~1.8 wt%) and MnO (up to ~3.5 wt%). Structurally investigated samples show a pronounced positive correlation between the <Y-O> distances and the (Li + Mn\(^{2+}\) + Cu + Fe\(^{2+}\)) content (apfu) at this site with R\(^2\) = 0.90. An excellent negative correlation exists between the <Y-O> distances and the Al\(_2\)O\(_3\) content (R\(^2\) = 0.94). The samples at each locality generally show a strong negative correlation between the X-site vacancies and the (MnO + FeO) content. The Mn content in these tourmalines depends on the availability of Mn, on the formation temperature, as well as on stereochemical constraints. Because of a very weak correlation between MnO and CuO we believe that the Cu content in tourmaline is essentially dependent on the availability of Cu and on stereochemical constraints.
Rice is the most important food crop in Asia, and the timely mapping and monitoring of paddy rice fields subsequently emerged as an important task in the context of food security and modelling of greenhouse gas emissions. Rice growth has a distinct influence on Synthetic Aperture Radar (SAR) backscatter images, and time-series analysis of C-band images has been successfully employed to map rice fields. The poor data availability on regional scales is a major drawback of this method. We devised an approach to classify paddy rice with the use of all available Envisat ASAR WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) data for our study area, the Mekong Delta in Vietnam. We used regression-based incidence angle normalization and temporal averaging to combine acquisitions from multiple tracks and years. A crop phenology-based classifier has been applied to this time series to detect single-, double- and triple-cropped rice areas (one to three harvests per year), as well as dates and lengths of growing seasons. Our classification has an overall accuracy of 85.3% and a kappa coefficient of 0.74 compared to a reference dataset and correlates highly with official rice area statistics at the provincial level (R-2 of 0.98). SAR-based time-series analysis allows accurate mapping and monitoring of rice areas even under adverse atmospheric conditions.
An Overview of the Regional Experiments for Land-atmosphere Exchanges 2012 (REFLEX 2012) Campaign
(2015)
The REFLEX 2012 campaign was initiated as part of a training course on the organization of an airborne campaign to support advancement of the understanding of land-atmosphere interaction processes. This article describes the campaign, its objectives and observations, remote as well as in situ. The observations took place at the experimental Las Tiesas farm in an agricultural area in the south of Spain. During the period of ten days, measurements were made to capture the main processes controlling the local and regional land-atmosphere exchanges. Apart from multi-temporal, multi-directional and multi-spatial space-borne and airborne observations, measurements of the local meteorology, energy fluxes, soil temperature profiles, soil moisture profiles, surface temperature, canopy structure as well as leaf-level measurements were carried out. Additional thermo-dynamical monitoring took place at selected sites. After presenting the different types of measurements, some examples are given to illustrate the potential of the observations made.
This study aimed to optimise the application, efficiency and interpretability of quasi-3D resistivity imaging for investigating the heterogeneous permafrost distribution at mountain sites by a systematic forward modelling approach. A three dimensional geocryologic model, representative for most mountain permafrost settings, was developed. Based on this geocryologic model quasi-3D models were generated by collating synthetic orthogonal 2D arrays, demonstrating the effects of array types and electrode spacing on resolution and interpretability of the inversion results. The effects of minimising the number of 2D arrays per quasi-3D grid were tested by enlarging the spacing between adjacent lines and by reducing the number of perpendicular tie lines with regard to model resolution and loss of information value. Synthetic and measured quasi-3D models were investigated with regard to the lateral and vertical resolution, reliability of inverted resistivity values, the possibility of a quantitative interpretation of resistivities and the response of the inversion process on the validity of quasi-3D models. Results show that setups using orthogonal 2D arrays with electrode spacings of 2 m and 3 m are capable of delineating lateral heterogeneity with high accuracy and also deliver reliable data on active layer thickness. Detection of permafrost thickness, especially if the permafrost base is close to the penetration depth of the setups, and the reliability of absolute resistivity values emerged to be a weakness of the method. Quasi-3D imaging has proven to be a promising tool for investigating permafrost in mountain environments especially for delineating the often small-scale permafrost heterogeneity, and therefore provides an enhanced possibility for aligning permafrost distribution with site specific surface properties and morphological settings.
11 Conclusion
11.1 Glaze compositions
Glazes from tiles of imposing Islamic buildings and some tableware glazes of the medieval epoch in Central Asia, the Middle East, Asia Minor, and North Africa are analysed regarding their main composition and colouring agents. Three major production recipes can be distinguished, i.e. alkali glazes, alkali lead glazes, and lead glazes. In the work of Tite (2011), Islamic glazes from Egypt, Iran, Iraq, and Syria are subdivided into four groups of composition, being partly consistent with those of this work. The alkali lime glazes with <2 wt% PbO correspond to the alkali glazes, but with higher content of CaO. The second and third group of low lead alkali and lead alkali glazes (2-10 wt% PbO and 10-35 wt% PbO) can be subsumed to the alkali lead group described here. Tite´s high lead group has PbO contents >35 wt% and is comparable to the lead glazes (>30 wt% PbO) of this study. The lead and the alkali oxides serve as a flux for the lowering the melting point.
In the interaction of ceramic body and glaze, primarily an influence from Si, Al, and K is observed in the line scans from the cross section of ceramic and glaze. However, the input of ceramic material doesn’t seem to be critical for the classification of glazes according to their alkali and alkali lead compositions.
In every epoch and locality, except of the Ilkhanate dynasty in Iran, lead glaze samples can be verified. This is also observed in previous investigations e.g. from medieval Iraq, Jordan and Iran (McCarthy, 1996; Al-Saad, 2002; Holakooei et al., 2014). In the Moroccan and Bulgarian glazes, lead seems to be the only important flux. In part, the lead flux is supplemented by additional alkali contents. The lack of alkali and alkali lead glazes in Bulgarian and Moroccan glazes (assuming that the Ottoman alkali lead glazes are imported tableware) seems to affect the regions with Roman-influenced history and with geographical distance to the Near East alkali flux tradition.
For the alkali lead glazes and alkali glazes, the overall characteristic is sodium dominated, although the absolute soda values are in part surprisingly low. Samples from Bukhara, Takht-i-Suleiman and the Turkish localities have the highest, but still moderate Na2O values up to 15 wt%, compared to other analyses from e.g. India (Gill & Rehren, 2011).
The source of the alkali flux is either mineral natron or plant ash. The source can be determined regarding the MgO values, limited to 1.3 wt% in mineral natron and exceeding 2.0 wt% in the case of plant ashes. In the samples of the present study, the K2O component is not suitable for the indication of the flux-relevant alkali source due to its broad scattering. The P2O5 contents are also enhanced in the plant ash compositions but the data set is not sufficient for statistical evaluation. An influence of the ceramic body on the glaze composition is observed only for SiO2, Al2O3, and K2O in quartz frit ceramics with slight K-feldspar content.
The earliest Uzbek tableware glazes from the 10th-11th century (Seljuq period) were generally produced using a lead flux. The same applies to part of the Uzbek tile glazes which were produced between the 13th and 16th century. In Iran, glazes from the 12th century (Khwarezmid period) are lead glazes, but also alkali-fluxed glazes with mineral natron characteristics can be found. Although the production of lead-rich glazes was established from the 8th-9th century on in Iraq, Syria, and Egypt (Henshaw, 2010; Tite et al., 2011), alkali glazes are found in almost all regions except of Bulgaria and Morocco.
Plant ash-fluxed alkali glazes are found in 13th century glazes from Takht-i-Suleiman. The plant ash flux technology is assumed to be continuously used in Mesopotamia, Iran, and Central Asia (Sayre & Smith, 1974; Henderson, 2009), but it could be shown that a parallel use of mineral natron parallel existed in the alkali glaze production from the 12th-15th century from Uzbekistan to Afghanistan. Mineral natron characteristics are also reported by Mason (2004) for Syrian and Iranian alkali glazes on lustre ware of the 8th-14th century. Tile glazes with partly mineral natron compositions are found in the Mughal architectural glazes from the 14th- 17th century from India (Gill et al., 2014).
Alkali and alkali lead tile glazes from Samarkand from the 13th century (Mongolian period) have mineral natron flux characteristics, but samples from the 15th century (Timurid period) show plant ash signature. Alkali fluxed Uzbek glazes from Bukhara from the 16th century (Sheibanid dynasty) are also made by plant ash flux and are subdivided into two groups with high and low sodium oxide content. The Afghan alkali glazes have sodium oxide contents similar to the sodium-poor Uzbek subgroup, which points to a possible exchange of glaze makers or glaze making technology from Uzbekistan and Afghanistan in the 15th-17th century. Regarding the extensive exchange of Timurid craftsmen in Central Asia, this option seems to be even more likely (Golombek, 1996). One sample from the 15th century from Afghanistan with mineral natron reveals that this material was parallel used in these centuries.
Concerning the colouring of the glazes, it has to be distinguished between pigments and colouring ions which are incorporated in the glassy matrix. The colouring agents for translucent glazes are cations of various transition metals. As ions, Co2+ (blue), Cu2+ (green in a lead rich matrix), Fe3+ (brown/black), Mn4+ (brown/black) and Mn3+ (violet) are determined by EPMA. For opaque yellow, white, and turquoise glazes, different pigments were used. The crystalline pigments are investigated by a µ XRD2 device with the result of SnO2, SiO2, and PbSiO4 as whitening agents. PbSiO4 and Pb2Sn2O6 are found in the yellow glaze, from which only the lead tin oxide causes the yellow colour. In the black glazes, different Cr-rich pigments, Cu-Cr-Mn-oxides and iron containing clinopyroxenes are found, even in samples of the same period and region. Cr-rich particles are also detected in two turquoise Afghan glazes from the 15th and 16th century. The use of the ions of Fe, Cu, Co, Cr, and Mn seems to be widely common in the Islamic glazes and corresponds to the described colouring agents in e.g. the study of Tite (2011). The use of opacifying SnO2 particles is widespread as it is reported from different Islamic glazes from Iraq, Iran, Egypt, and Syria (Henshaw, 2010; O´Kane, 2011; Tite, 2011). The colouring agents are known already from former, e.g. Egyptian, Roman and pre-islamic periods, but especially SnO2 pigments became increasingly widespread in the Islamic glazing tradition. The use of yellow and black pigments instead varies already within the buildings from Bukhara from Cr crystals and clino-pyroxenes in the mosque Khoja Zainuddin to a Cu-Cr-Mn-oxide in the madrassa Mir-i Arab of the same epoch.
Regarding the matrix compositions connected with the colouring, a certain assignment within the different locations and epochs can be seen. It is noticeable that e.g. the content of lead in turquoise glazes in Uzbekistan is in the range of 0.0-9.2 wt% Pb, whereas blue glazes are mostly alkali ones with PbO contents <2.0 wt%. The turquoise glazes show, that this restriction is not influenced by any defaults of availability and processability. The assumption of common addition of lead and tin to the glaze, which is already described for Iranian glazes of the 13th century (Allan et al., 1973) cannot be confirmed by correlations of tin and lead oxide in the compositions.
11.2 Portable XRF measurement
With the p-XRF, semi-quantitative information about the major element compositions is generated. The depth of the detectable signals depends on the analysed sample setup. The p-XRF data are collected with the XL3 Hybrid device of the company Analyticon Instruments. In the comparison of p-XRF results of the “mining” program from Uzbek glazes with EPMA results, the same major composition groups can be distinguished. The Moroccan glazes, all lead rich, are measured with the “mining” as well as with the “soil” program, revealing a better performance in the “mining” measurements. The deviations are nevertheless high, because of the high lead contents, which make the calculation of matrix correction difficult.
The measurement of the colouring oxides MnO2, CoO, and CuO is satisfying with the internal calibration of the device and even improved with the “mining” program measurement, if compared to the results of the “soil” program. The measurements of glaze imitations lead to better results than that of bulk glass. This can be attributed to the smoother surface texture.
In spite of the accuracy limits in the measurements of particular elements in glazes, the classification of flux composition into three groups could be confirmed with the p XRF analysis. The measurement precision is therefore sufficient for the semi-quantitative analysis of the flux characteristic of glazes. Especially for the on-site measurement of large sample quantities on historical buildings, the device is a suitable tool.
11.3 Restoration material
The ORMOCER® fulfils the requirements of stability, reversibility, and transparency, which are imposed to a modern restoration material. As pigments, historically coloured glass, cobalt blue, Egyptian blue, lead tin yellow, manganese violet, iron oxide, copper oxide, and cassiterite were used. The metal compounds have higher colour intensities than the pigments of coloured glass. It has to be considered that the proportion of ORMOCER® in the batch must be high enough (70 vol%) to guarantee the ORMOCER® properties of weathering and mechanical stability. The adhesion properties of the ORMOCER® and the homogeneity of the mixture are the best in a fraction of max. 30 vol% particles per ORMOCER®.
With integrated particles, the ORMOCER® G materials show homogeneous coatings, whereas the particles in the ORMCOER® E show more agglomeration. In the sedimentation and weathering experiments, the use of an ultrasonic finger in combination with a roller mill is favourable compared to the treatment with bead grinding mill. The treatments with ultrasonic finger and roller mill result in less sedimentation and better adhesion of the dispersions. The treatment of the dispersions in the bead grinding mill does not result in sufficient adhesion, certainly due to the sedimentation behaviour and a congregation of particles on the bottom of the coating.
The modification of dispersed nano-particles by 3-methacryl-oxypropyltrimethoxysilan leads to a further homogenization in the sedimentation tests. It is therefore approved for the use in coloured glaze supplements. In weathered coatings of nano-particle compounds, the surface modification shows certainly no enhancement of stability.
The treatment of pigmented coatings with an additional layer of pure ORMOCER® results in a bright and transparent appearing, which is closer to the original optical appearance of the glaze. A long-time test application on a historical building will be the next step to validate the suitability of the restoration material.
The natural environment and livelihoods in the Lower Mekong Basin (LMB) are significantly affected by the annual hydrological cycle. Monitoring of soil moisture as a key variable in the hydrological cycle is of great interest in a number of Hydrological and agricultural applications. In this study we evaluated the quality and spatiotemporal variability of the soil moisture product retrieved from C-band scatterometers data across the LMB sub-catchments. The soil moisture retrieval algorithm showed reasonable performance in most areas of the LMB with the exception of a few sub-catchments in the eastern parts of Laos, where the land cover is characterized by dense vegetation. The best performance of the retrieval algorithm was obtained in agricultural regions. Comparison of the available in situ evaporation data in the LMB and the Basin Water Index (BWI), an indicator of the basin soil moisture condition, showed significant negative correlations up to R = −0.85. The inter-annual variation of the calculated BWI was also found corresponding to the reported extreme hydro-meteorological events in the Mekong region. The retrieved soil moisture data show high correlation (up to R = 0.92) with monthly anomalies of precipitation in non-irrigated regions. In general, the seasonal variability of soil moisture in the LMB was well captured by the retrieval method. The results of analysis also showed significant correlation between El Niño events and the monthly BWI anomaly measurements particularly for the month May with the maximum correlation of R = 0.88.
The global-local sustainable development and climate change adaptation policy, and the emerging political discourse on the value of local Adaptation, have positioned the local institutions and their governance space within the strategic enclaves of multilevel governance system. Such shifts have transformed the context for sustainable Nature Based Tourism (NBT) development and adaptation in Nepal in general, and its protected areas, in particular. The emerging institutional adaptation discourse suggests on the need to link tourism development, adaptation and governance within the sustainability concept, and also to recognize the justice and inclusive dimensions of local adaptation. However, sociological investigation of institutional adaptation, particularly at the interface between sustainability, justice and inclusive local adaptation is an undertheorized research topic.
This exploratory study examined the sociological process of the institutional adaptation, especially the social resilience and adaptive governance capacities of the NBT institutions, in 7 Village Development Committees of the Mustang district, a popular destination in the Annapurna Conservation Area, Nepal. Using the sphere (a dynamic social space concept) and quality of governance as the analytical framework, the integrative adaptation as the methodological approach and the case study action research method, the study investigated and generated a holistic picture on the state of the social resilience and adaptive governance capacities of the NBT institutions.
The findings show institutional social resilience capacities to be contingent on socio-political construction of adaptation knowledge and power. Factors influencing such constructions among NBT institutions include: the site and institutions specific political, economic and environmental dispositions; the associated socio-political processes of knowledge constructions and volition action; and the social relationships and interaction, operating within the spheres and at multiple governance levels. The adaptive governance capacities hinge on the institutional arrangements, the procedural aspects of adaptation governance and the governmentality. These are reflective of the diverse legal frameworks, the interiority perspective of the decision making and governance practices of the NBT institutions.
In conclusion, it is argued that effective local adaptation in the Mustang district is contingent on the adaptation and institutional dynamics of the NBT institutions, consisting of the cognitive, subjective, process and procedural aspects of the adaptation knowledge production and its use.
Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices
(2013)
Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions in Iran. Results indicated that by consideration of the advantages and disadvantages of the mentioned drought predictors in Iran, the Z-Score, CZI and MCZI could be used as a good meteorological drought predictor. Depending on the month, the length of drought and climatic conditions of the region, they are an alternative to the SPI that has limitations both because of only a few available long term data series in Iran and its complex structure.
A modified setup featuring high speed high resolution data and video recording was developed to obtain detailed information on trigger and heat transfer times during explosive molten fuel-coolant-interaction (MFCI). MFCI occurs predominantly in configurations where water is entrapped by hot melt. The setup was modified to allow direct observation of the trigger and explosion onset. In addition the influences of experimental control and data acquisition can now be more clearly distinguished from the pure phenomena. More precise experimental studies will facilitate the description of MFCI thermodynamics.
Les sécheresses des années 1970 et 1980 ont occasionné des changements remarquables dans les paysages et écosystèmes sahéliens. Au Niger, les milieux dunaires sont les plus affectés par la dégradation des paysages aux conséquences parfois irréversibles. Cette étude tente de montrer que, malgré les modifications climatiques et les pressions anthropiques, une régénération des sols dunaires serait possible, dans cette dynamique complexe. Cela a été démontré à travers l’analyse micromorphologique des matériaux des parties superficielles des sols (0-20 cm). L’étude des caractéristiques particulières des croûtes (organisations pelliculaires de surface des sols) offre des pistes de recherches pouvant proposer des moyens et méthodes de fixation des dunes dégradées. Elle propose également des alternatives de lutte contre l’érosion éolienne et hydrique dans les écosystèmes sahéliens. Ceci cadre parfaitement avec la situation au Niger, où les phénomènes de désertification et d’ensablement des cuvettes interdunaires constituent une préoccupation majeure en matière de protection de l’environnement.
Les sécheresses des années 1970 et 1980 ont occasionné des changements remarquables dans les paysages et écosystèmes sahéliens. Au Niger, les milieux dunaires sont les plus affectés par la dégradation des paysages aux conséquences parfois irréversibles. Cette étude tente de montrer que, malgré les modifications climatiques et les pressions anthropiques, une régénération des sols dunaires serait possible, dans cette dynamique complexe. Cela a été démontré à travers l’analyse micromorphologique des matériaux des parties superficielles des sols (0-20 cm). L’étude des caractéristiques particulières des croûtes (organisations pelliculaires de surface des sols) offre des pistes de recherches pouvant proposer des moyens et méthodes de fixation des dunes dégradées. Elle propose également des alternatives de lutte contre l’érosion éolienne et hydrique dans les écosystèmes sahéliens. Ceci cadre parfaitement avec la situation au Niger, où les phénomènes de désertification et d’ensablement des cuvettes interdunaires constituent une préoccupation majeure en matière de protection de l’environnement.
Background
Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.
Methodology
We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d’Ivoire and validated against readily available survey data from school-aged children.
Principal Findings
Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d’Ivoire.
Conclusions/Significance
A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.
Accurate quantification of land use/cover change (LULCC) is important for efficient environmental management, especially in regions that are extremely affected by climate variability and continuous population growth such as West Africa. In this context, accurate LULC classification and statistically sound change area estimates are essential for a better understanding of LULCC processes. This study aimed at comparing mono-temporal and multi-temporal LULC classifications as well as their combination with ancillary data and to determine LULCC across the heterogeneous landscape of southwest Burkina Faso using accurate classification results. Landsat data (1999, 2006 and 2011) and ancillary data served as input features for the random forest classifier algorithm. Five LULC classes were identified: woodland, mixed vegetation, bare surface, water and agricultural area. A reference database was established using different sources including high-resolution images, aerial photo and field data. LULCC and LULC classification accuracies, area and area uncertainty were computed based on the method of adjusted error matrices. The results revealed that multi-temporal classification significantly outperformed those solely based on mono-temporal data in the study area. However, combining mono-temporal imagery and ancillary data for LULC classification had the same accuracy level as multi-temporal classification which is an indication that this combination is an efficient alternative to multi-temporal classification in the study region, where cloud free images are rare. The LULCC map obtained had an overall accuracy of 92%. Natural vegetation loss was estimated to be 17.9% ± 2.5% between 1999 and 2011. The study area experienced an increase in agricultural area and bare surface at the expense of woodland and mixed vegetation, which attests to the ongoing deforestation. These results can serve as means of regional and global land cover products validation, as they provide a new validated data set with uncertainty estimates in heterogeneous ecosystems prone to classification errors.
Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.
Remote sensing for disease risk profiling: a spatial analysis of schistosomiasis in West Africa
(2014)
Global environmental change leads to the emergence of new human health risks. As a consequence, transmission opportunities of environment-related diseases are transformed and human infection with new emerging pathogens increase. The main motivation for this study is the considerable demand for disease surveillance and monitoring in relation to dynamic environmental drivers. Remote sensing (RS) data belong to the key data sources for environmental modelling due to their capabilities to deliver spatially continuous information repeatedly for large areas with an ecologically adequate spatial resolution.
A major research gap as identified by this study is the disregard of the spatial mismatch inherent in current modelling approaches of profiling disease risk using remote sensing data. Typically, epidemiological data are aggregated at school or village level. However, these point data do neither represent the spatial distribution of habitats, where disease-related species find their suitable environmental conditions, nor the place, where infection has occurred. As a consequence, the prevalence data and remotely sensed environmental variables, which aim to characterise the habitat of disease-related species, are spatially disjunct.
The main objective of this study is to improve RS-based disease risk models by incorporating the ecological and spatial context of disease transmission. Exemplified by the analysis of the human schistosomiasis disease in West Africa, this objective includes the quantification of the impact of scales and ecological regions on model performance.
In this study, the conditions that modify the transmission of schistosomiasis are reviewed in detail. A conceptual underpinning of the linkages between geographical RS measures, disease transmission ecology, and epidemiological survey data is developed. During a field-based analysis, environmental suitability for schistosomiasis transmission was assessed on the ground, which is then quantified by a habitat suitability index (HSI) and applied to RS data. This conceptual model of environmental suitability is refined by the development of a hierarchical model approach that statistically links school-based disease prevalence with the ecologically relevant measurements of RS data. The statistical models of schistosomiasis risk are derived from two different algorithms; the Random Forest and the partial least squares regression (PLSR). Scale impact is analysed based on different spatial resolutions of RS data. Furthermore, varying buffer extents are analysed around school-based measurements. Three distinctive sites of Burkina Faso and Côte d’Ivoire are specifically modelled to represent a gradient of ecozones from dry savannah to tropical rainforest including flat and mountainous regions.
The model results reveal the applicability of RS data to spatially delineate and quantitatively evaluate environmental suitability for the transmission of schistosomiasis. In specific, the multi-temporal derivation of water bodies and the assessment of their riparian vegetation coverage based on high-resolution RapidEye and Landsat data proofed relevant. In contrast, elevation data and water surface temperature are constraint in their ability to characterise habitat conditions for disease-related parasites and freshwater snail species. With increasing buffer extent observed around the school location, the performance of statistical models increases, improving the prediction of transmission risk. The most important RS variables identified to model schistosomiasis risk are the measure of distance to water bodies, topographic variables, and land surface temperature (LST). However, each ecological region requires a different set of RS variables to optimise the modelling of schistosomiasis risk. A key result of the hierarchical model approach is its superior performance to explain the spatial risk of schistosomiasis.
Overall, this study stresses the key importance of considering the ecological and spatial context for disease risk profiling and demonstrates the potential of RS data. The methodological approach of this study contributes substantially to provide more accurate and relevant geoinformation, which supports an efficient planning and decision-making within the public health sector.
Purpose – The purpose of this dissertation is to reveal the status quo of development of the grocery retailers’ internationalization process in China as well as to model future trends, opportunities and challenges within a very competitive market. Using several, geographically distant cities as case studies, this paper focuses on the development and outlook of different store formats, along with the development of competition in this respect by explicitly treating China not as a single market. The study thereby analyses historical and geographical diffusion in regard to store formats. The impacts of the main factors of change are discussed.
Design/methodology/approach – The dissertation reviews extensively the literature of grocery retail internationalization with special focus on China. In addition, it draws on primary research in the form of a wide range of expert interviews. As China´s ‘supermarket revolution’ is underway, an understanding of the local and foreign competition and the development of different store formats within different regions of China as well as their prospects, will be crucial to companies expanding into this area.
Findings – The study explains how grocery retailers have already entered the Chinese market with different store formats and how competition has and will further develop. In addition, the study reveals challenges and obstacles in regard to future market strategies, especially in regard to store formats and geographical regions.
Research limitations/implications – The study reveals the current landscape of the Chinese grocery retailing market and emphasizes important strategic pillars, modelling future implications and challenges for food retailers operating in China. Because China is a vast country this dissertation forms only a small part of the geographical evolution process in regard to store formats and competition.
Practical implications – Explores current understanding of the internationalization process in China by considering different format choices. Supplementary, the dissertation proposes an outlook of competition enlargement, prospects of format development and therewith strategic implications within different regions as well as a future research agenda.
Originality / value – Contributes to the understanding of the Chinese grocery retailing market. Furthermore, it is among the first to critically explore possible future developments in regard to store formats and competition within a geographical context in China
Regionalvermarktung ist in deutschen Biosphärenreservaten ein wichtiges Instrument zur Umsetzung des Leitbilds der nachhaltigen Entwicklung. Die Dachmarke Rhön im Biosphärenreservat Rhön hat in den vergangenen Jahren einen Vorbildcharakter in diesem Kontext entwickelt. Doch nur wenige quantitative Untersuchungen befassen sich bis jetzt mit der Frage, welche regionalökonomischen Effekte diese Initiativen haben. In der Arbeit werden die internen Wirtschaftsstrukturen, wie z.B. die Vorleistungen, der Dachmarkenmitglieder mit einer zufälligen Kontrollgruppe von regionalen Betrieben verglichen. Die wirtschaftlichen Differenzen zwischen den Untersuchungsgruppen stellen sich deutlicher dar, wenn die Dachmarke Rhön nicht als eine Einheit gesehen wird, sondern in drei Untergruppen geteilt wird.
Die Betriebe der Dachmarke Rhön haben aufgrund von tendenziell höheren Vorleistungsausgaben geringere Wertschöpfungsquoten auf der ersten Stufe des regionalökonomischen Modells. Die Analyse der Einkaufsbeziehungen und Investitionen macht aber deutlich, dass die Betriebe der Dachmarke Rhön dennoch einen Beitrag zur nachhaltigen Regionalentwicklung in der Rhön leisten können. Zur Erreichung dieses Ziels handeln die Betriebe der Dachmarke in vielerlei Hinsicht aus idealistischen Motiven.
Das Tibetplateau (TP) ist das höchste Gebirgsplateau der Erde und bildete sich im Verlauf der letzten 50 Millionen Jahre. Durch seine Ausmaße veränderte das TP nicht nur das Klima im heutigen Asien, sondern bewirkte Veränderungen weltweit. Heute stellt das TP einen Hotspot des Klimawandels dar und ist als Quellgebiet vieler großer Flüsse in Asien für die Wasserversorgung von Milliarden von Menschen von zentraler Bedeutung. Vor diesem Hintergrund ist es wichtig, die Prozesse, die das Klima in der Region steuern, besser zu verstehen und die Variabilität des Klimas auf unterschiedlichen Zeitskalen abschätzen zu können.
Grundlegendes Ziel der vorliegenden Arbeit ist es, räumlich hochaufgelöste quantitative Informationen über die Veränderung der klimatischen Verhältnisse in Asien während der Bildungsphase des TP und unter warm- und kaltzeitlichen Randbedingungen zur Verfügung zu stellen und dadurch eine Verbindung zwischen den verschiedenen Zeitskalen herzustellen. Hierfür werden das heutige Klima und das Paläoklima der Region mit Hilfe von Klimamodellen simuliert. Da frühere Studien zeigen konnten, dass die Ergebnisse von hochaufgelösten Modellen besser mit Paläoklimarekonstruktionen übereinstimmen, als die von vergleichsweise niedrig aufgelösten Globalmodellen, erfolgt ein dynamisches Downscaling des globalen Klimamodells ECHAM5 mit dem regionalen Klimamodell REMO.
Die Heraushebung des TP wird durch eine Serie von fünf Simulationen (Topogra- phieexperimente) approximiert, in denen die Höhe des TP in 25%-Schritten von 0% bis 100% der heutigen Höhe verändert wird. Die Schwankungen des Klimas im spä- ten Quartär sind durch Simulationen für das mittlere Holozän und den Hochstand der letzten Vereisung, das Last-Glacial-Maximum, repräsentiert (Quartärexperi- mente). In den Quartärexperimenten wurden die Treibhausgaskonzentrationen, Orbitalparameter, Landbedeckung und verschiedene Vegetationsparameter an die Bedingungen der jeweiligen Zeitscheibe angepasst. Die Auswertung der Simulati- onsergebnisse konzentriert sich auf jährliche und jahreszeitliche Veränderungen der bodennahen Temperatur und des Niederschlags. Außerdem werden die sich erge- benden Änderungen in der Intensität des indischen Monsuns anhand verschiedener Monsunindizes analysiert. Für das TP und die sich unmittelbar anschließenden Ge- biete wird zusätzlich eine Clusteranalyse durchgeführt, um die dort vorkommenden regionalen Klimatypen identifizieren und charakterisieren zu können.
In den Topographieexperimenten zeigt sich, dass die 2m-Temperatur im Bereich des TP im Jahresmittel mit abnehmender Höhe des Plateaus um bis zu 30◦C zunimmt, während es in den übrigen Teilen des Modellgebiets nahezu überall kälter wird. Die Jahressumme des Niederschlags nimmt mit abnehmender Höhe des TP westlich und nördlich davon zu. Im Bereich des TP sowie südlich und östlich davon gehen die Niederschläge zurück. Die starke Niederschlagszunahme nördlich des TP kann durch die Ausbildung eines Höhentrogs statt eines Höhenrückens in diesem Bereich erklärt werden. Das grundsätzliche räumliche Muster der Veränderungen besteht dabei bereits bei einer Plateauhöhe von 75% des Ausgangswertes und ändert sich bei weiterer Verringerung der Höhe nicht wesentlich. Lediglich der Betrag der Veränderungen nimmt zu. Dies gilt für die 2m-Temperatur und den Niederschlag und sowohl im Jahresmittel als auch für die einzelnen Jahreszeiten. Bezüglich der Intensität des indischen Sommermonsuns zeigt sich, dass zwischen 25% und 75% der heutigen Höhe des TP die stärkste Intensivierung stattfindet. Eine mit heute vergleichbare Monsunintensität tritt erst auf, wenn das TP die Hälfte seiner jetzigen Höhe erreicht hat.
Im mittleren Holozän ist es im Jahresmittel in den meisten Teilen des Modellge- biets kälter und feuchter als heute. Die Unterschiede sind jedoch größtenteils gering und nicht signifikant. Hinsichtlich der Temperatur zeigen die Modelldaten nur vereinzelt eine gute Übereinstimmung mit den rekonstruierten Werten. Allerdings weisen die Rekonstruktionen eine hohe räumliche Variabilität auf, wodurch die in diesem Datensatz vorhandenen Unsicherheiten widergespiegelt werden. Hinsicht- lich des Niederschlags ist die Übereinstimmung besser. Hier deuten sowohl die simulierten als auch die rekonstruierten Daten auf feuchtere Bedingungen hin.
In der Simulation für das Last-Glacial-Maximum liegen die Temperaturen überall im Modellgebiet im Jahresmittel und in allen Jahreszeiten um bis zu 8◦C unter den heutigen Werten. Es besteht eine gute Übereinstimmung mit den rekonstruierten Temperaturwerten für diese Zeitscheibe. Zu einer signifikanten Abnahme der jährlichen Niederschlagsmenge kommt es westlich und nordwestlich des TP, in Indien, Südostasien und entlang der Ostküste Chinas. Für die Bereiche, für die Niederschlagsrekonstruktionen verfügbar sind, stimmen die Modellergebnisse gut mit diesen überein. Zu einer signifikanten Niederschlagszunahme kommt es nur zwischen der Nordküste des Golfs von Bengalen und dem Himalaya, wobei dies möglicherweise ein Modellartefakt darstellt.
Hinsichtlich der Monsunintensität bestehen große Unterschiede zwischen den Indizes. Während der Extended Indian Monsoon Rainfall Index eine starke Ab- schwächung des indischen Sommermonsuns anzeigt, ist der Wert des Webster and Yang Monsoon Index verglichen mit heute nahezu unverändert. Ein Vergleich der Monsunintensität in den Topographie- und den Quartärexperimenten macht deut- lich, dass der indische Monsun durch den Wechsel von warm- und kaltzeitlichen Randbedingungen mindestens so stark beeinflusst wird wie durch die Hebung des TP.
Der vielschichtige Begriff Entwicklung stellt die Basis für die multidisziplinäre Entwicklungsforschung, aber auch die Entwicklungspolitik und Entwicklungszusammenarbeit dar und wird demzufolge auf verschiedenste Art und Weise verwendet. Insbesondere zu den Auswirkungen regionaler Entwicklungsprozesse auf lokaler Ebene existieren innerhalb der entwicklungstheoretischen Ideengeschichte eine Vielzahl unterschiedlicher Zugänge, über die die vorliegende Arbeit einen kurzen Überblick gibt. Unter Berücksichtigung anthropogeographischer Ansätze zur Erforschung des Verhältnisses von Entwicklung und Raum werden im ersten (theoretischen) Teil die Konzepte der lokalen Partizipation sowie der Politischen Ökologie als geeignete Analyseinstrumente für das Verständnis konkreter lokaler Entwicklungsprozesse erarbeitet; Entwicklung wird hierbei akteurs- und kontextorientiert als Ergebnis von Mensch-Umwelt-Interaktionen angesehen.
Im Rahmen eines case study research wird im zweiten Teil der Arbeit die Praxistauglichkeit dieser Analyseinstrumente überprüft. Hierfür werden in zwei Untersuchungsregionen regionale Entwicklungsdynamiken beschrieben und analysiert, um deren räumliche und soziale Auswirkungen zu verstehen. In beiden Gebieten (Mampu/Mbankana in der Demokratischen Republik Kongo sowie Wasini Island in Kenia) hat in den vergangenen Jahren eine durch unterschiedliche Prozesse verursachte rasante Regionalentwicklung stattgefunden, die die Gebiete jeweils deutlich von ihrem Umland abhebt. Im Fallbeispiel Wasini Island wurde die Entwicklung durch den (internationalen) Tourismus bedingt, in Mampu/Mbankana durch ein Entwicklungsprojekt der Hanns-Seidel-Stiftung (HSS). Für beide Gebiete wird zuerst der naturräumliche, politische und historische Kontext aufgezeigt, welcher die Rahmenbedingungen für die Analyse der einzelnen Akteure und Akteursgruppen darstellt. Sowohl für Wasini Island als auch für Mampu/Mbankana können während des Untersuchungszeitraums Ereignisse identifiziert werden, die von der einheimischen Bevölkerung (bzw. Teilen dieser) als stark situationsverändernd und zudem nicht endogen verursacht wahrgenommen werden (externe Krisen): in Wasini der drastische Einbruch der Touristenzahlen nach den Unruhen im Nachgang der Präsidentschaftswahlen (2007/08 Kenyan Crisis), im kongolesischen Untersuchungsgebiet der schrittweise Rückzug der HSS aus dem operativen Projekt ab 2009 und die damit einhergehende Übertragung von Verantwortung auf lokale Gremien und Organisationen.
Durch die Zusammenführung der Ergebnisse aus beiden Fallbeispielen wird konstatiert, dass Entwicklung auf regionaler Ebene als ein kontext- und akteursabhängiger dynamischer Prozess anzusehen ist, der aus den kumulierten, in beide Richtungen wirksamen Mensch-Umwelt-Interaktionen in der betrachteten Region resultiert, und damit in der Tradition geopossibilistischer Perspektiven steht, in denen die natürliche bzw. geographische ebenso wie die gesellschaftliche Umwelt die Rahmenbedingungen für menschliches Handeln und damit Entwicklung vorgibt, jedoch nicht determiniert.
Mapping threatened dry deciduous dipterocarp forest in South-east Asia for conservation management
(2014)
Habitat loss is the primary reason for species extinction, making habitat conservation a critical strategy for maintaining global biodiversity. Major habitat types, such as lowland tropical evergreen forests or mangrove forests, are already well represented in many conservation priorities, while others are underrepresented. This is particularly true for dry deciduous dipterocarp forests (DDF), a key forest type in Asia that extends from the tropical to the subtropical regions in South-east Asia (SE Asia), where high temperatures and pronounced seasonal precipitation patterns are predominant. DDF are a unique forest ecosystem type harboring a wide range of important and endemic species and need to be adequately represented in global biodiversity conservation strategies. One of the greatest challenges in DDF conservation is the lack of detailed and accurate maps of their distribution due to inaccurate open-canopy seasonal forest mapping methods. Conventional land cover maps therefore tend to perform inadequately with DDF. Our study accurately delineates DDF on a continental scale based on remote sensing approaches by integrating the strong, characteristic seasonality of DDF. We also determine the current conservation status of DDF throughout SE Asia. We chose SE Asia for our research because its remaining DDF are extensive in some areas but are currently degrading and under increasing pressure from significant socio-economic changes throughout the region. Phenological indices, derived from MODIS vegetation index time series, served as input variables for a Random Forest classifier and were used to predict the spatial distribution of DDF. The resulting continuous fields maps of DDF had accuracies ranging from R-2 = 0.56 to 0.78. We identified three hotspots in SE Asia with a total area of 156,000 km(2), and found Myanmar to have more remaining DDF than the countries in SE Asia. Our approach proved to be a reliable method for mapping DDF and other seasonally influenced ecosystems on continental and regional scales, and is very valuable for conservation management in this region.
Spätestens mit der Erstauflage der deutschen Nachhaltigkeitsstrategie 2002 wurde die Notwendigkeit einer Reduzierung der Flächeninanspruchnahme politisch anerkannt. Die damit verbundene Einführung des „30-ha-Ziels“, definiert als eine Reduktion der täglichen Flächeninanspruchnahme im Bundesgebiet von 120 ha/Tag auf 30 ha/Tag im Jahr 2020, soll den negativen Auswirkungen wie z.B. Zersiedelung oder sozialer Segregation Einhalt gebieten. Trotz intensiver Bemühungen konnte jedoch keine deutliche Reduzierung der Flächeninanspruchnahme erreicht werden. 2007 betrug die tägliche Neuinanspruchnahme von Flächen immer noch 96 ha .
An diesem Punkt knüpft die Arbeit an und versucht mittels eines akteurszentrierten Ansatzes einen Erkenntnisgewinn zur Ursachenforschung der Flächeninanspruchnahme zu liefern. Ziel ist die Untersuchung der Raumrelevanz planerischer und politischer Entscheidungsprozesse vor dem Hintergrund einer nachhaltigen Siedlungsentwicklung und Flächeninanspruchnahme. Dabei erfolgt eine schwerpunktmäßige Betrachtung der Regional- und Bauleitplanung im Rahmen einer Flächennutzung durch Wohnen. Denn diese Akteure stellen nicht nur zentrale „Flächennutzungsentscheider“ dar, sondern sind auch Anknüpfungspunkt zahlreicher Handlungsstrategien/-maßnahmen. Die Arbeit fokussiert dabei die Entscheidungsfindung der Planung und der politischen Gremien bei der Aufstellung von Regional- und Flächennutzungsplänen und den ihr immanenten Entscheidungen, nämlich der Abwägung und dem Beschluss, sowie deren Wechselwirkungen untereinander. Die Fragestellung wird dabei anhand von Fallstudien in Städten, die in der Vergangenheit von Schrumpfungsprozessen betroffen waren, konkret die Städte Dresden und Leipzig, und in Regionen, welche mit einer wachsenden Bevölkerung konfrontiert sind, hier die Regionen München und Rhein-Neckar, eruiert. Hierzu kamen verschiedene Methoden zum Einsatz, in deren Zentrum die Anwendung des Analytical Hierarchy Process (AHP) und qualitativer Experteninterviews stehen.
Im Ergebnis kann ausgesagt werden, dass weniger raumstrukturelle Ausgangssituationen, als vielmehr kommunalspezifische Handlungsorientierungen das Maß einer Reduzierung der Flächeninanspruchnahme bestimmen. Um deren Beweggründe eruieren zu können, ist es sowohl auf regionaler als auch auf kommunaler Ebene wichtig, die Interaktionsbeziehungen zwischen planerischen und politischen Akteuren und den ihnen zugrunde liegenden Handlungsorientierungen zu beleuchten. Denn diese spezielle Inter-aktionsbeziehung spielt eine bedeutende Rolle zum Verständnis planerischer und politischer Entscheidungen vor dem Hintergrund des Flächensparziels, da das Thema Flächenverbrauch als ein fachliches und sehr komplexes Thema wahrgenommen wird, welches sich in seiner Gesamtheit den politischen Akteuren aufgrund deren begrenzter Zeit oftmals nicht erschließt.
Planerischen Entscheidungen können dabei immer flächensparende Bestrebungen konstatiert werden, politischen Entscheidungen eingeschränkt dadurch, ob es der Planung gelingt, das Flächensparziel der Politik nahe zu bringen, es nicht anderen Anliegen entgegensteht und ein dahingehendes Verhalten nicht zu Nachteilen im Konkurrenzkampf mit den anderen Kommunen führt. Jedoch kann auch aus den Ergebnissen abgeleitet werden, dass nach außen gelebtes Flächensparen oftmals nicht auf ein Bewusstseins des Wertes der Fläche per se zurückzuführen ist. Es hängt vielmehr davon ab, wie hoch der Problemdruck auf Basis alter Flächenausweisungen ist und inwieweit es sich als Nebenprodukt aus den planerischen und politischen Entscheidungen ergibt. Oftmals verhindern aber auch u.a. Eigentumsstrukturen und rechtliche Rahmenbedingungen, wie die bis dato noch kaum diskutierten Eingemeindungsverträge, dass eine Reduzierung der Flächeninanspruchnahme vollzogen wird. Resultat hieraus ist, dass es keinen allgemeingültigen Maßnahmen- oder Instrumentarienkatalog geben kann, um eine Flächeninanspruchnahme voranzutreiben. Vielmehr gilt es infolge der Analyse von Akteuren, Akteurskonstellationen und institutionellen Rahmenbedingungen diese entsprechend einzusetzen bzw. zu generieren.
The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass.
This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure.
The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.
The ecosystem of the high northern latitudes is affected by the recently changing environmental conditions. The Arctic has undergone a significant climatic change over the last decades. The land coverage is changing and a phenological response to the warming is apparent. Remotely sensed data can assist the monitoring and quantification of these changes. The remote sensing of the Arctic was predominantly carried out by the usage of optical sensors but these encounter problems in the Arctic environment, e.g. the frequent cloud cover or the solar geometry. In contrast, the imaging of Synthetic Aperture Radar is not affected by the cloud cover and the acquisition of radar imagery is independent of the solar illumination. The objective of this work was to explore how polarimetric Synthetic Aperture Radar (PolSAR) data of TerraSAR-X, TanDEM-X, Radarsat-2 and ALOS PALSAR and interferometric-derived digital elevation model data of the TanDEM-X Mission can contribute to collect meaningful information on the actual state of the Arctic Environment. The study was conducted for Canadian sites of the Mackenzie Delta Region and Banks Island and in situ reference data were available for the assessment. The up-to-date analysis of the PolSAR data made the application of the Non-Local Means filtering and of the decomposition of co-polarized data necessary.
The Non-Local Means filter showed a high capability to preserve the image values, to keep the edges and to reduce the speckle. This supported not only the suitability for the interpretation but also for the classification. The classification accuracies of Non-Local Means filtered data were in average +10% higher compared to unfiltered images. The correlation of the co- and quad-polarized decomposition features was high for classes with distinct surface or double bounce scattering and a usage of the co-polarized data is beneficial for regions of natural land coverage and for low vegetation formations with little volume scattering. The evaluation further revealed that the X- and C-Band were most sensitive to the generalized land cover classes. It was found that the X-Band data were sensitive to low vegetation formations with low shrub density, the C-Band data were sensitive to the shrub density and the shrub dominated tundra. In contrast, the L-Band data were less sensitive to the land cover. Among the different dual-polarized data the HH/VV-polarized data were identified to be most meaningful for the characterization and classification, followed by the HH/HV-polarized and the VV/VH-polarized data. The quad-polarized data showed highest sensitivity to the land cover but differences to the co-polarized data were small. The accuracy assessment showed that spectral information was required for accurate land cover classification. The best results were obtained when spectral and radar information was combined. The benefit of including radar data in the classification was up to +15% accuracy and most significant for the classes wetland and sparse vegetated tundra. The best classifications were realized with quad-polarized C-Band and multispectral data and with co-polarized X-Band and multispectral data. The overall accuracy was up to 80% for unsupervised and up to 90% for supervised classifications. The results indicated that the shortwave co-polarized data show promise for the classification of tundra land cover since the polarimetric information is sensitive to low vegetation and the wetlands. Furthermore, co-polarized data provide a higher spatial resolution than the quad-polarized data.
The analysis of the intermediate digital elevation model data of the TanDEM-X showed a high potential for the characterization of the surface morphology. The basic and relative topographic features were shown to be of high relevance for the quantification of the surface morphology and an area-wide application is feasible. In addition, these data were of value for the classification and delineation of landforms. Such classifications will assist the delineation of geomorphological units and have potential to identify locations of actual and future morphologic activity.
Agriculture is mankind’s primary source of food production and plays the key role for cereal supply to humanity. One of the future challenges will be to feed a constantly growing population, which is expected to reach more than nine billion by 2050. The potential to expand cropland is limited, and enhancing agricultural production efficiency is one important means to meet the future food demand. Hence, there is an increasing demand for dependable, accurate and comprehensive agricultural intelligence on crop production. The value of satellite earth observation (EO) data for agricultural monitoring is well recognized. One fundamental requirement for agricultural monitoring is routinely updated information on crop acreage and the spatial distribution of crops. With the technical advancement of satellite sensor systems, imagery with higher temporal and finer spatial resolution became available. The classification of such multi-temporal data sets is an effective and accurate means to produce crop maps, but methods must be developed that can handle such large and complex data sets. Furthermore, to properly use satellite EO for agricultural production monitoring a high temporal revisit frequency over vast geographic areas is often necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g. over heterogeneous landscapes where individual fields are often smaller than individual pixels.
The main purposes of the presented study were (i) to assess the influence of input dimensionality and feature selection on classification accuracy and uncertainty in object-based crop classification, (ii) to evaluate if combining classifier algorithms can improve the quality of crop maps (e.g. classification accuracy), (iii) to assess the spatial resolution requirements for crop identification via image classification.
Reporting on the map quality is traditionally done with measures that stem from the confusion matrix based on the hard classification result. Yet, these measures do not consider the spatial variation of errors in maps. Measures of classification uncertainty can be used for this purpose, but they have attained only little attention in remote sensing studies. Classifier algorithms like the support vector machine (SVM) can estimate class memberships (the so called soft output) for each classified pixel or object. Based on these estimations, measures of classification uncertainty can be calculated, but it has not been analysed in detail, yet, if these are reliable in predicting the spatial distribution of errors in maps. In this study, SVM was applied for the classification of agricultural crops in irrigated landscapes in Middle Asia at the object-level. Five different categories of features were calculated from RapidEye time series data as classification input. The reliability of classification uncertainty measures like entropy, derived from the soft output of SVM, with regard to predicting the spatial distribution of error was evaluated. Further, the impact of the type and dimensionality of the input data on classification uncertainty was analysed. The results revealed that SMVs applied to the five feature categories separately performed different in classifying different types of crops. Incorporating all five categories of features by concatenating them into one stacked vector did not lead to an increase in accuracy, and partly reduced the model performance most obviously because of the Hughes phenomena. Yet, applying the random forest (RF) algorithm to select a subset of features led to an increase of classification accuracy of the SVM. The feature group with red edge-based indices was the most important for general crop classification, and the red edge NDVI had an outstanding importance for classifying crops. Two measures of uncertainty were calculated based on the soft output from SVM: maximum a-posteriori probability and alpha quadratic entropy. Irrespective of the measure used, the results indicate a decline in classification uncertainty when a dimensionality reduction was performed. The two uncertainty measures were found to be reliable indicators to predict errors in maps. Correctly classified test cases were associated with low uncertainty, whilst incorrectly test cases tended to be associated with higher uncertainty.
The issue of combining the results of different classifier algorithms in order to increase classification accuracy was addressed. First, the SVM was compared with two other non-parametric classifier algorithms: multilayer perceptron neural network (MLP) and RF. Despite their comparatively high classification performance, each of the tested classifier algorithms tended to make errors in different parts of the input space, e.g. performed different in classifying crops. Hence, a combination of the complementary outputs was envisaged. To this end, a classifier combination scheme was proposed, which is based on existing algebraic operators. It combines the outputs of different classifier algorithms at the per-case (e.g. pixel or object) basis. The per-case class membership estimations of each classifier algorithm were compared, and the reliability of each classifier algorithm with respect to classifying a specific crop class was assessed based on the confusion matrix. In doing so, less reliable classifier algorithms were excluded at the per-class basis before the final combination. Emphasis was put on evaluating the selected classification algorithms under limiting conditions by applying them to small input datasets and to reduced training sample sets, respectively. Further, the applicability to datasets from another year was demonstrated to assess temporal transferability. Although the single classifier algorithms performed well in all test sites, the classifier combination scheme provided consistently higher classification accuracies over all test sites and in different years, respectively. This makes this approach distinct from the single classifier algorithms, which performed different and showed a higher variability in class-wise accuracies. Further, the proposed classifier combination scheme performed better when using small training set sizes or when applied to small input datasets, respectively.
A framework was proposed to quantitatively define pixel size requirements for crop identification via image classification. That framework is based on simulating how agricultural landscapes, and more specifically the fields covered by one crop of interest, are seen by instruments with increasingly coarser resolving power. The concept of crop specific pixel purity, defined as the degree of homogeneity of the signal encoded in a pixel with respect to the target crop type, is used to analyse how mixed the pixels can be (as they become coarser) without undermining their capacity to describe the desired surface properties (e.g. to distinguish crop classes via supervised or unsupervised image classification). This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Inputs to the experiments were eight multi-temporal images from the RapidEye sensor. Simulated pixel sizes ranged from 13 m to 747.5 m, in increments of 6.5 m. Constraining parameters for crop identification were defined by setting thresholds for classification accuracy and uncertainty. Results over irrigated agricultural landscapes in Middle Asia demonstrate that the task of finding the optimum pixel size did not have a “one-size-fits-all” solution. The resulting values for pixel size and purity that were suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the investigated crops were growing in. Results further indicate that map quality (e.g. classification accuracy) was not homogeneously distributed in a landscape, but that it depended on the spatial structures and the pixel size, respectively. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types.
Regarding the operationalization of EO-based techniques for agricultural monitoring and its application to a broader range of agricultural landscapes, it can be noted that, despite the high performance of existing methods (e.g. classifier algorithms), transferability and stability of such methods remain one important research issue. This means that methods developed and tested in one place might not necessarily be portable to another place or over several years, respectively. Specifically in Middle Asia, which was selected as study region in this thesis, classifier combination makes sense due to its easy implementation and because it enhanced classification accuracy for classes with insufficient training samples. This observation makes it interesting for operational contexts and when field reference data availability is limited. Similar to the transferability of methods, the application of only one certain kind of EO data (e.g. with one specific pixel size) over different landscapes needs to be revisited and the synergistic use of multi-scale data, e.g. combining remote sensing imagery of both fine and coarse spatial resolution, should be fostered. The necessity to predict and control the effects of spatial and temporal scale on crop classification is recognized here as a major goal to achieve in EO-based agricultural monitoring.
Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.
Defining the Spatial Resolution Requirements for Crop Identification Using Optical Remote Sensing
(2014)
The past decades have seen an increasing demand for operational monitoring of crop conditions and food production at local to global scales. To properly use satellite Earth observation for such agricultural monitoring, high temporal revisit frequency over vast geographic areas is necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g., over heterogeneous landscapes where individual fields are often smaller than individual pixels. The question of determining the optimal pixel sizes for an application such as crop identification is therefore naturally inclined towards finding the coarsest acceptable pixel sizes, so as to potentially benefit from what instruments with coarser pixels can offer. To answer this question, this study builds upon and extends a conceptual framework to quantitatively define pixel size requirements for crop identification via image classification. This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Results over contrasting landscapes in Central Asia demonstrate that the task of finding the optimum pixel size does not have a “one-size-fits-all” solution. The resulting values for pixel size and purity that are suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the crops are growing in. Results indicate that sensors like MODIS (250 m) could be suitable for identifying major crop classes in the study sites, whilst sensors like Landsat (30 m) should be considered for object-based classification. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types.
Irrigated agriculture in the Khorezm region in the arid inner Aral Sea Basin faces enormous challenges due to a legacy of cotton monoculture and non-sustainable water use. Regional crop growth monitoring and yield estimation continuously gain in importance, especially with regard to climate change and food security issues. Remote sensing is the ideal tool for regional-scale analysis, especially in regions where ground-truth data collection is difficult and data availability is scarce. New satellite systems promise higher spatial and temporal resolutions. So-called light use efficiency (LUE) models are based on the fraction of photosynthetic active radiation absorbed by vegetation (FPAR), a biophysical parameter that can be derived from satellite measurements. The general objective of this thesis was to use satellite data, in conjunction with an adapted LUE model, for inferring crop yield of cotton and rice at field (6.5 m) and regional (250 m) scale for multiple years (2003-2009), in order to assess crop yield variations in the study area. Intensive field measurements of FPAR were conducted in the Khorezm region during the growing season 2009. RapidEye imagery was acquired approximately bi-weekly during this time. The normalized difference vegetation index (NDVI) was calculated for all images. Linear regression between image-based NDVI and field-based FPAR was conducted. The analyses resulted in high correlations, and the resulting regression equations were used to generate time series of FPAR at the RapidEye level. RapidEye-based FPAR was subsequently aggregated to the MODIS scale and used to validate the existing MODIS FPAR product. This step was carried out to evaluate the applicability of MODIS FPAR for regional vegetation monitoring. The validation revealed that the MODIS product generally overestimates RapidEye FPAR by about 6 to 15 %. Mixture of crop types was found to be a problem at the 1 km scale, but less severe at the 250 m scale. Consequently, high resolution FPAR was used to calibrate 8-day, 250 m MODIS NDVI data, this time by linear regression of RapidEye-based FPAR against MODIS-based NDVI. The established FPAR datasets, for both RapidEye and MODIS, were subsequently assimilated into a LUE model as the driving variable. This model operated at both satellite scales, and both required an estimation of further parameters like the photosynthetic active radiation (PAR) or the actual light use efficiency (LUEact). The latter is influenced by crop stress factors like temperature or water stress, which were taken account of in the model. Water stress was especially important, and calculated via the ratio of the actual (ETact) to the potential, crop-specific evapotranspiration (ETc). Results showed that water stress typically occurred between the beginning of May and mid-September and beginning of May and end of July for cotton and rice crops, respectively. The mean water stress showed only minor differences between years. Exceptions occurred in 2008 and 2009, where the mean water stress was higher and lower, respectively. In 2008, this was likely caused by generally reduced water availability in the whole region. Model estimations were evaluated using field-based harvest information (RapidEye) and statistical information at district level (MODIS). The results showed that the model at both the RapidEye and the MODIS scale can estimate regional crop yield with acceptable accuracy. The RMSE for the RapidEye scale amounted to 29.1 % for cotton and 30.4 % for rice, respectively. At the MODIS scale, depending on the year and evaluated at Oblast level, the RMSE ranged from 10.5 % to 23.8 % for cotton and from -0.4 % to -19.4 % for rice. Altogether, the RapidEye scale model slightly underestimated cotton (bias = 0.22) and rice yield (bias = 0.11). The MODIS-scale model, on the other hand, also underestimated official rice yield (bias from 0.01 to 0.87), but overestimated official cotton yield (bias from -0.28 to -0.6). Evaluation of the MODIS scale revealed that predictions were very accurate for some districts, but less for others. The produced crop yield maps indicated that crop yield generally decreases with distance to the river. The lowest yields can be found in the southern districts, close to the desert. From a temporal point of view, there were areas characterized by low crop yields over the span of the seven years investigated. The study at hand showed that light use efficiency-based modeling, based on remote sensing data, is a viable way for regional crop yield prediction. The found accuracies were good within the boundaries of related research. From a methodological viewpoint, the work carried out made several improvements to the existing LUE models reported in the literature, e.g. the calibration of FPAR for the study region using in situ and high resolution RapidEye imagery and the incorporation of crop-specific water stress in the calculation.
In this work the potential of polarimetric Synthetic Aperture Radar (PolSAR) data of dual-polarized TerraSAR-X (HH/VV) and quad-polarized Radarsat-2 was examined in combination with multispectral Landsat 8 data for unsupervised and supervised classification of tundra land cover types of Richards Island, Canada. The classification accuracies as well as the backscatter and reflectance characteristics were analyzed using reference data collected during three field work campaigns and include in situ data and high resolution airborne photography. The optical data offered an acceptable initial accuracy for the land cover classification. The overall accuracy was increased by the combination of PolSAR and optical data and was up to 71% for unsupervised (Landsat 8 and TerraSAR-X) and up to 87% for supervised classification (Landsat 8 and Radarsat-2) for five tundra land cover types. The decomposition features of the dual and quad-polarized data showed a high sensitivity for the non-vegetated substrate (dominant surface scattering) and wetland vegetation (dominant double bounce and volume scattering). These classes had high potential to be automatically detected with unsupervised classification techniques.
Crop mapping in West Africa is challenging, due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. To address this challenge, we integrated high spatial resolution multi-temporal optical (RapidEye) and dual polarized (VV/VH) SAR (TerraSAR-X) data to map crops and crop groups in northwestern Benin using the random forest classification algorithm. The overall goal was to ascertain the contribution of the SAR data to crop mapping in the region. A per-pixel classification result was overlaid with vector field boundaries derived from image segmentation, and a crop type was determined for each field based on the modal class within the field. A per-field accuracy assessment was conducted by comparing the final classification result with reference data derived from a field campaign. Results indicate that the integration of RapidEye and TerraSAR-X data improved classification accuracy by 10%–15% over the use of RapidEye only. The VV polarization was found to better discriminate crop types than the VH polarization. The research has shown that if optical and SAR data are available for the whole cropping season, classification accuracies of up to 75% are achievable.
Rapid population growth in West Africa has led to expansion in croplands due to the need to grow more food to meet the rising food demand of the burgeoning population. These expansions negatively impact the sub-region's ecosystem, with implications for water and soil quality, biodiversity and climate. In order to appropriately monitor the changes in croplands and assess its impact on the ecosystem and other environmental processes, accurate and up-to-date information on agricultural land use is required. But agricultural land use mapping (i.e. mapping the spatial distribution of crops and croplands) in West Africa has been challenging due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. This study, therefore, investigated the possibilities of improving agricultural land use mapping by utilizing optical satellite images with higher spatial and temporal resolution as well as images from Synthetic Aperture Radar (SAR) systems which are near-independent of weather conditions. The study was conducted at both watershed and regional scales.
At watershed scale, classification of different crop types in three watersheds in Ghana, Burkina Faso and Benin was conducted using multi-temporal: (1) only optical images (RapidEye) and (2) optical plus dual polarimetric (VV/VH) SAR images (TerraSAR-X). In addition, inter-annual or short term (2-3 years) changes in cropland area in the past ten years were investigated using historical Landsat images. Results obtained indicate that the use of only optical images to map different crop types in West Africa can achieve moderate classification accuracies (57% to 71%). Overlaps between the cropping calendars of most crops types and certain inter-croppings pose a challenge to optical images in achieving an adequate separation between those crop classes. Integration of SAR images, however, can improve classification accuracies by between 8 and 15%, depending on the number of available images and their acquisition dates. The sensitivity of SAR systems to different crop canopy architectures and land surface characteristics improved the separation between certain crop types. The VV polarization of TerraSAR-X was found to better discrimination between crop types than the VH. Images acquired between August and October were found to be very useful for crop mapping in the sub-region due to structural differences in some crop types during this period.
At the regional scale, inter-annual or short term changes in cropland area in the Sudanian Savanna agro-ecological zone in West Africa were assessed by upscaling historical cropland information derived at the watershed scale (using Landsat imagery) unto a coarse spatial resolution, but geographically large, satellite imagery (MODIS) using regression based modeling. The possibility of using such regional scale cropland information to improve government-derived agricultural statistics was investigated by comparing extracted cropland area from the fractional cover maps with district-level agricultural statistics from Ghana The accuracy of the fractional cover maps (MAE between 14.2% and 19.1%) indicate that the heterogeneous agricultural landscape of West Africa can be suitably represented at the regional or continental scales by estimating fractional cropland cover on low resolution Analysis of the results revealed that cropland area in the Sudanian Savanna zone has experienced inter-annual or short term fluctuations in the past ten years due to a variety of factors including climate factors (e.g. floods and droughts), declining soil fertility, population increases and agricultural policies such as fertilizer subsidies. Comparison of extracted cropland area from the fractional cover maps with government's agricultural statistics (MoFA) for seventeen districts (second administrative units) in Ghana revealed high inconsistencies in the government statistics, and highlighted the potential of satellite derived cropland information at regional scales to improve national/sub-national agricultural statistics in West Africa.
The results obtained in this study is promising for West Africa, considering the recent launch of optical (Landsat 8) and SAR sensors (Sentinel-1) that will provide free data for crop mapping in the sub-region. This will improve chances of obtaining adequate satellite images acquired during the cropping season for agricultural land use mapping and bolster opportunities of operationalizing agricultural land use mapping in West Africa. This can benefit a wide range of biophysical and economic models and improve decision making based on their results.
Information on the state of the terrestrial vegetation cover is important for several ecological, economical, and planning issues. In this regard, vegetation properties such as the type, vitality, or density can be described by means of continuous biophysical parameters. One of these parameters is the leaf area index (LAI), which is defined as half the total leaf area per unit ground surface area. As leaves constitute the interface between the biosphere and the atmosphere, the LAI is used to model exchange processes between plants and their environment. However, to account for the variability of ecosystems, spatially and temporally explicit information on LAI is needed both for monitoring and modeling applications.
Remote sensing aims at providing such information. LAI is commonly derived from remote sensing data by empirical-statistical or physical models. In the first approach, an empirical relationship between LAI measured in situ and the corresponding canopy spectral signature is established. Although this method achieves accurate LAI estimates, these relationships are only valid for the place and time at which the field data were sampled, which hampers automated LAI derivation. The physical approach uses a radiation transfer model to simulate canopy reflectance as a function of the scene’s geometry and of leaf and canopy parameters, from which LAI is derived through model inversion based on remote sensing data. However, this model inversion is not stable, as it is an under-determined and ill-posed problem.
Until now, LAI research focused either on the use of coarse resolution remote sensing data for global applications, or on LAI modeling over a confined area, mostly in forest and crop ecosystems, using medium to high spatial resolution data. This is why to date no study is available in which high spatial resolution data are used for LAI mapping in a heterogeneous, natural landscape such as alpine grasslands, although a growing amount of high spatial and temporal resolution remote sensing data would allow for an improved environmental monitoring. Therefore, issues related to model parameterization and inversion regularization techniques improving its stability have not yet been investigated for this ecosystem.
This research gap was taken up by this thesis, in which the potential of high spatial resolution remote sensing data for grassland LAI estimation based on statistical and radiation transfer modeling is analyzed, and the achieved accuracy and robustness of the two approaches is compared. The objectives were an ecosystem-adapted radiation transfer model set-up and an optimized LAI derivation in mountainous grassland areas. Multi-temporal LAI in situ measurements as well as time series of RapidEye data from 2011 and 2012 over the catchment of the River Ammer in the Bavarian alpine upland were used. In order to obtain accurate in situ data, a comparison of the LAI derivation algorithms implemented in the LAI-2000 PCA instrument with destructively measured LAI was performed first. For optimizing the empirical-statistical approach, it was then analyzed how the selection of vegetation indices and regression models impacts LAI modeling, and how well these models can be transferred to other dates. It was shown that LAI can be derived
with a mean accuracy of 80 % using contemporaneous field data, but that the accuracy decreases to on average 51 % when using these models on remote sensing data from other dates. The combined use of several data sets to create a regression which is used for LAI derivation at different points in time increased the LAI estimation accuracy to on average 65 %. Thus, reduced field measurement labor comes at the cost of LAI error rates being increased by 10 - 30 % as long as at least two campaigns are conducted. Further, it was shown that the use of RapidEye’s red edge channel improves the LAI derivation by on average 5.4 %.
With regard to physical LAI modeling, special interest lay in assessing the accuracy improvements that can be achieved through model set-up and inversion regularization techniques. First, a global sensitivity analysis was applied to the radiation transfer model in order to identify the most important model parameters and most sensitive spectral features. After model parameterization, several inversion regularizations, namely the use of a multiple sample solution, the additional use of vegetation indices, and the addition of noise, were analyzed. Further, an approach to include the local scene’s geometry in the retrieval process was introduced to account for the mountainous topography. LAI modeling accuracies of in average 70 % were achieved using the best combination of regularization techniques, which is in the upper range of accuracies that were achieved in the few existing other grassland studies based on in situ or air-borne measured hyperspectral data. Finally, further physically derived vegetation parameters and inversion uncertainty measures were evaluated in detail to identify challenging modeling conditions, which was mostly neglected in other studies. An increased modeling uncertainty for extremely high and low LAI values was observed. This indicates an insufficiently wide model parameterization and a canopy deviation from model assumptions on some fields. Further, the LAI modeling accuracies varied strongly between the different scenes. From this observation it can be deduced that the radiometric quality of the remote sensing data, which might be reduced by atmospheric effects or unexpected surface reflectances, exerts a high influence on the LAI modeling accuracy.
The major findings of the comparison between the empirical-statistical and physical LAI modeling approaches are the higher accuracies achieved by the empirical-statistical approach as long as contemporaneous field data are available, and the computationally efficiency of the statistical approach. However, when no or temporally unfitting in situ measurements are available, the physical approach achieves comparable or even higher accuracies. Furthermore, radiation transfer modeling enables the derivation of other leaf and canopy variables useful for ecological monitoring and modeling applications, as well as of pixel-wise uncertainty measures indicating the robustness and reliability of the model inversion and LAI derivation procedure. The established look-up tables can be used for further LAI derivation in Central European grassland also in other years.
The use of high spatial resolution remote sensing data for LAI derivation enables a reliable land cover classification and thus a reduced LAI mapping error due to misclassifications. Furthermore, the RapidEye pixels being smaller than individual fields allow for a radiation transfer model inversion over homogeneous canopies in most cases, as canopy gaps or field parcels can be clearly distinguished. However, in case of unexpected local surface conditions such as blooming, litter, or canopy gaps, high spatial resolution data show corresponding strong deviations in reflectance values and hence LAI estimation, which would be reduced using coarser resolution data through the balancing effect of the surrounding surface reflectances. An optimal pixel size with regard to modeling accuracy hence depends on the canopy and landscape structure. Furthermore, a reduced spatial resolution would enable a considerable acceleration of the LAI map derivation.
This illustration of the potential of RapidEye data and of the challenges associated to LAI derivation in heterogeneous grassland areas contributes to the development of robust LAI estimation procedures based on new and upcoming, spatially and temporally high resolution remote sensing imagery such as Landsat 8 and Sentinel-2.
Die Entwicklung von Clustern ist in den vergangenen zwei Dekaden zu einem äußerst beliebten Ziel der regionalen Wirtschaftsförderung geworden. Dieser Trend wird seitens der Wissenschaft recht kritisch betrachtet. Sie befürchtet, dass die Clusterförderung den jeweiligen Kontext zu wenig beachtet und sich zudem auf wenige Instrumente beschränkt, ohne alle Anknüpfungspunkte, die ihr die Clustertheorie bietet, auszuschöpfen. Allerdings muss sich die Wissenschaft eingestehen, dass sie den Anschluss an die Förderung verloren hat und sich daher mit einer fundierten Beratung schwer tut.
Die vorliegende Arbeit hat das Ziel diese Wissenslücke zu verkleinern, indem sie Clusterplattformen untersucht, die häufig die zentralen Umsetzungsorganisationen der clusterorientierten Wirtschaftsförderung sind. Im Zentrum stehen dabei die Fragen, wie diese Plattformen arbeiten und welche Möglichkeiten und Begrenzungen sie haben, um eine den Clustertheorien entsprechende Förderung zu betreiben. Untersuchungsgegenstand sind die Clusterplattformen des bayerischen Förderprogramms Cluster-Offensive Bayern.
Als theoretische Grundlage zur Analyse der Clusterplattformen wurde der Neo-Institutionalismus gewählt. Dieser soziologischen Theorie zufolge werden die Handlungen von Organisationen durch die Akteure in ihrem Umfeld bestimmt, auf deren Legitimitätszuweisungen sie angewiesen sind. Für den vorliegenden Fall heißt das, dass sich die Clusterplattformen in ihren Handlungen an die Erwartungen der zu fördernden Unternehmen und der politischen Auftraggeber anpassen müssen. Das wird dazu führen, dass die Plattformen keine theoretisch optimale Förderung betreiben können. Die Frage ist schließlich, welche Elemente der Clustertheorien sie gut und welche sie weniger gut fördern können. Um das zu beantworten, werden die Erwartungen der einzelnen Akteure auf der Basis von qualitativen Experten Interviews identifiziert und ihre Auswirkungen auf ausgewählte Elemente der Clustertheorien untersucht und diskutiert.
Die Untersuchung zeigt, dass die Anpassungen der Clusterplattformen an die Erwartungen der Akteure in ihrem Umfeld in der Tat sehr stark sind, was generell zu einer sehr kontextspezifischen Förderung führt. Allerdings wird von Maßnahmen Abstand genommen, die den partikularen Erwartungen widersprechen, obwohl sie für den Gesamtcluster bedeutsam sein können. Andere Aspekte der Clustertheorien, die von den Akteuren allgemein als sehr bedeutsam angesehen werden, sind hingegen im Werkzeugkasten der Plattformen überrepräsentiert. Bei vielen weiteren Elementen beeinflussen jedoch ganz praktische Umstände die Handlungsmöglichkeiten der Clusterplattformen. Grundsätzlich schöpfen die Clusterplattformen ihre Möglichkeiten dennoch weitestgehend aus. Für eine umfassende clustertheoretisch orientierte Wirtschaftsförderung ist daher vor allem für die Einbeziehung von weiteren Akteuren oder Programmen zu plädieren, welche die Handlungsdefizite der Clusterplattformen ausgleichen können.
Nature-based tourism and ecotourism experienced a dynamic development over the past decade. While originally often described as specialized post-Fordist niche markets for ecologically aware and affluent target groups, in many regions they are nowadays characterized by a heterogeneous structure and the presence of a wide product range, from individual travels to package tours.
The present dissertation analyzes the structure and economic importance of tourism in two highly frequented protected areas in middle income countries, the Sian Ka’an Biosphere Reserve (SKBR) in Mexico and the Souss-Massa National Park (SMNP) in Morocco. Both areas are situated in close proximity to the most important package tour destinations Cancún (Mexico) and Agadir (Morocco) and are subject to high touristic use and development pressure. So far, the planning of a more sustainable tourism development is hampered by the lack of reliable data.
Based on demand-side surveys and income multipliers calculated with the help of regionalized input-output models, the visitor structure and economic impact of tourism in both protected areas are described. With regional income effects of approximately 1 million USD (SKBR) and approximately 1.9 million USD (SMNP), and resulting income equivalents of 1,348 and 5,218 persons, both the SKBR and the SMNP play an important—and often undervalued—role for the regional economies in underdeveloped rural peripheral regions of the countries.
Detailed analyses of the visitor structures show marked differences with regard to criteria such as travel organization, nature/protected area affinity and expenditures. With regard to planning and marketing of nature-based tourism, protected area managers and political decision-takers are advised to focus on ecologically and economically attractive visitor groups. Based on the results of the two case studies as well as existing tourism typologies from the literature, a classification scheme is presented that may be used for a more target-oriented development and marketing of nature-based tourism products.
Klimawandelbedingte bzw. potenziell klimawandelbedingte Umweltmigration ist ein sehr komplexes und breites Feld. Es existiert eine Fülle von Studien, die sich in ihrer Herangehensweise unterscheiden, weshalb hier ein Systematisierungsvorschlag aufgezeigt wird. Mittels einer an den Richtlinien der Grounded Theory orientierten Analyse wurden Studien auf zentrale gemeinsame Kategorien hin untersucht und als Modell präsentiert. Dieses stellt jedoch kein abgeschlossenes System dar, sondern dient durch seine Offenheit als Gerüst, das mit Ergebnissen aus weiteren Fallstudien gefestigt werden kann.
Bewertung und Auswirkungen der Simulationsgüte führender Klimamoden in einem Multi-Modell Ensemble
(2013)
Der rezente und zukünftige Anstieg der atmosphärischen Treibhausgaskonzentration bedeutet für das terrestrische Klimasystem einen grundlegenden Wandel, der für die globale Gesellschaft schwer zu bewältigende Aufgaben und Herausforderungen bereit hält. Eine effektive, rühzeitige Anpassung an diesen Klimawandel profitiert dabei enorm von möglichst genauen Abschätzungen künftiger Klimaänderungen.
Das geeignete Werkzeug hierfür sind Gekoppelte Atmosphäre Ozean Modelle (AOGCMs). Für solche Fragestellungen müssen allerdings weitreichende Annahmen über die zukünftigen klimarelevanten Randbedingungen getroffen werden. Individuelle Fehler dieser Klimamodelle, die aus der nicht perfekten Abbildung der realen Verhältnisse und Prozesse resultieren, erhöhen die Unsicherheit langfristiger Klimaprojektionen. So unterscheiden sich die Aussagen verschiedener AOGCMs im Hinblick auf den zukünftigen Klimawandel insbesondere bei regionaler Betrachtung, deutlich. Als Absicherung gegen Modellfehler werden üblicherweise die Ergebnisse mehrerer AOGCMs, eines Ensembles an Modellen, kombiniert. Um die Abschätzung des Klimawandels zu präzisieren, wird in der vorliegenden Arbeit der Versuch unternommen, eine Bewertung der Modellperformance der 24 AOGCMs, die an der dritten Phase des Vergleichsprojekts für gekoppelte Modelle (CMIP3) teilgenommen haben, zu erstellen. Auf dieser Basis wird dann eine nummerische Gewichtung für die Kombination des Ensembles erstellt. Zunächst werden die von den AOGCMs simulierten Klimatologien für einige
grundlegende Klimaelemente mit den betreffenden klimatologien verschiedener Beobachtungsdatensätze quantitativ abgeglichen. Ein wichtiger methodischer Aspekt
hierbei ist, dass auch die Unsicherheit der Beobachtungen, konkret Unterschiede zwischen verschiedenen Datensätzen, berücksichtigt werden. So zeigt sich, dass die Aussagen, die aus solchen Ansätzen resultieren, von zu vielen Unsicherheiten in den Referenzdaten beeinträchtigt werden, um generelle Aussagen zur Qualität von AOGCMs zu treffen. Die Nutzung der Köppen-Geiger Klassifikation offenbart jedoch, dass die prinzipielle Verteilung der bekannten Klimatypen im kompletten CMIP3 in vergleichbar guter Qualität reproduziert wird. Als Bewertungskriterium wird daher hier die Fähigkeit der AOGCMs die großskalige natürliche Klimavariabilität, konkret die hochkomplexe gekoppelte
El Niño-Southern Oscillation (ENSO), realistisch abzubilden herangezogen. Es kann anhand verschiedener Aspekte des ENSO-Phänomens gezeigt werden, dass nicht alle AOGCMs hierzu mit gleicher Realitätsnähe in der Lage sind. Dies steht im Gegensatz zu den dominierenden Klimamoden der Außertropen, die modellübergreifend überzeugend repräsentiert werden. Die wichtigsten Moden werden, in globaler Betrachtung, in verschiedenen Beobachtungsdaten über einen neuen Ansatz identifiziert. So können für einige bekannte Zirkulationsmuster neue Indexdefinitionen gewonnen werden, die sich sowohl als äquivalent zu den Standardverfahren erweisen und im Vergleich zu diesen zudem eine deutliche Reduzierung
des Rechenaufwandes bedeuten. Andere bekannte Moden werden dagegen als weniger bedeutsame, regionale Zirkulationsmuster eingestuft. Die hier vorgestellte
Methode zur Beurteilung der Simulation von ENSO ist in guter Übereinstimmung mit anderen Ansätzen, ebenso die daraus folgende Bewertung der gesamten Performance
der AOGCMs. Das Spektrum des Southern Oscillation-Index (SOI) stellt somit eine aussagekräftige Kenngröße der Modellqualität dar.
Die Unterschiede in der Fähigkeit, das ENSO-System abzubilden, erweisen sich als signifikante Unsicherheitsquelle im Hinblick auf die zukünftige Entwicklung einiger fundamentaler und bedeutsamer Klimagrößen, konkret der globalen Mitteltemperatur,
des SOIs selbst, sowie des indischen Monsuns. Ebenso zeigen sich signifikante Unterschiede für regionale Klimaänderungen zwischen zwei Teilensembles des CMIP3, die auf Grundlage der entwickelten Bewertungsfunktion eingeteilt werden. Jedoch sind diese Effekte im Allgemeinen nicht mit den Auswirkungen der
anthropogenen Klimaänderungssignale im Multi-Modell Ensemble vergleichbar, die für die meisten Klimagrößen in einem robusten multivariaten Ansatz detektiert und
quantifiziert werden können. Entsprechend sind die effektiven Klimaänderungen, die sich bei der Kombination aller Simulationen als grundlegende Aussage des
CMIP3 unter den speziellen Randbedingungen ergeben nahezu unabhängig davon, ob alle Läufe mit dem gleichen Einfluss berücksichtigt werden, oder ob die erstellte nummerische Gewichtung verwendet wird. Als eine wesentliche Begründung hierfür kann die Spannbreite der Entwicklung des ENSO-Systems identifiziert werden. Dies
bedeutet größere Schwankungen in den Ergebnissen der Modelle mit funktionierendem ENSO, was den Stellenwert der natürlichen Variabilität als Unsicherheitsquelle
in Fragen des Klimawandels unterstreicht. Sowohl bei Betrachtung der Teilensembles als auch der Gewichtung wirken sich dadurch gegenläufige Trends im SOI
ausgleichend auf die Entwicklung anderer Klimagrößen aus, was insbesondere bei letzterem Vorgehen signifikante mittlere Effekte des Ansatzes, verglichen mit der
Verwendung des üblichen arithmetischen Multi-Modell Mittelwert, verhindert.
Increasing urbanisation is one of the biggest pressures to vegetation in the City of Cape Town. The growth of the city dramatically reduced the area under indigenous Fynbos vegetation, which remains in isolated fragments. These are subject to a number of threats including atmospheric deposition, atypical fire cycles and invasion by exotic plant and animal species. Especially the Port Jackson willow (Acacia saligna) extensively suppresses the indigenous Fynbos vegetation with its rapid growth.
The main objective of this study was to investigate indicators for a quick and early prediction of the health of the remaining Fynbos fragments in the City of Cape Town with help of remote sensing.
First, the productivity of the vegetation in response to rainfall was determined. For this purpose, the Enhanced Vegetation Index (EVI), derived from Terra MODIS data with a spatial resolution of 250m, and precipitation data of 19 rainfall stations for the period from 2000 till 2008 were used. Within the scope of a flexible regression between the EVI data and the precipitation data, different lags of the vegetation response to rainfall were analysed. Furthermore, residual trends (RESTREND) were calculated, which result from the difference between observed EVI and the one predicted by precipitation. Negative trends may suggest a degradation of the habitats. In addition, the so-called Rain-use Efficiency (RUE) was tested in this context. It is defined as the ratio between net primary production (NPP) – represented by the annual sum of EVI – and the annual rainfall sum. These indicators were analysed for their suitability to determine the health of the indigenous Fynbos vegetation.
Furthermore, the degree of dispersal of invasive species especially the Acacia saligna was investigated. With the specific characteristics of the tested indicators and the spectral signature of Acacia saligna, i.e. its unique reflectance over the course of the year, the dispersal was estimated. Since the growth of invasive species dramatically reduces the biodiversity of the fragments, their presence is an important factor for the condition of ecosystem health.
This work focused on 11 test sites with an average size of 200ha, distributed over the whole area of the City of Cape Town. Five of these fragments are under conservation and the others shall be protected in the near future, too, which makes them of special interest. In January 2010, fieldwork was undertaken in order to investigate the state and composition of the local vegetation.
The results show promising indicators for the assessment of ecosystem health. The coefficients of determination of the EVI-rainfall regression for Fynbos are minor, because the reaction of this vegetation type to rainfall is considerably lower than the one of the invasive species. Thus, a good distinction between indigenous and alien vegetation is possible on the basis of this regression. On the other hand, the RESTREND method, for which the regression forms the basis, is only of limited use, since the significance of these trends is not given for Fynbos vegetation. Furthermore, the RUE has considerable potential for the assessment of ecosystem health in the study area. The Port Jackson willow has an explicitly higher EVI than the Fynbos vegetation and thus its RUE is more efficient for a similar amount of rainfall. However, it has to be used with caution, because local and temporal variability cannot be extinguished in the study area over the rather short MODIS time series.
These results display that the interpretation of the indicators has to be conducted differently from the literature, because the element of invasive species was not considered in most of the previous papers. An increase in productivity is not necessarily equivalent with an improvement in health of the fragment, but can indicate a dispersal of Acacia saligna. This shows the general problem of the term ‘degradation’ which in most publications so far is only measured by productivity and other factors like invasive species are disregarded.
On the basis of the EVI-rainfall regression and statistical measures of the EVI, the distribution of invasive species could be delineated. Generally, a strong invasion of the Port Jackson willow was discovered on the test sites. The results display that a reasoned and sustainable management of the fragments is essential in order to prevent the suppression of the indigenous Fynbos vegetation by Acacia saligna. For this purpose, remote sensing can give an indication which areas changed so that specific field surveys can be undertaken and subsequent management measures can be determined.
The Mediterranean area reveals a strong vulnerability to future climate change due to a high exposure to projected impacts and a low capacity for adaptation highlighting the need for robust regional or local climate change projections, especially for extreme events strongly affecting the Mediterranean environment. The prevailing study investigates two major topics of the Mediterranean climate variability: the analysis of dynamical downscaling of present-day and future temperature and precipitation means and extremes from global to regional scale and the comprehensive investigation of temperature and rainfall extremes including the estimation of uncertainties and the comparison of different statistical methods for precipitation extremes. For these investigations, several observational datasets of CRU, E-OBS and original stations are used as well as ensemble simulations of the regional climate model REMO driven by the coupled global general circulation model ECHAM5/MPI-OM and applying future greenhouse gas (GHG) emission and land degradation scenarios.
The overarching goal of this research was to explore accurate methods of mapping irrigated crops, where digital cadastre information is unavailable: (a) Boundary separation by object-oriented image segmentation using very high spatial resolution (2.5–5 m) data was followed by (b) identification of crops and crop rotations by means of phenology, tasselled cap, and rule-based classification using high resolution (15–30 m) bi-temporal data. The extensive irrigated cotton production system of the Khorezm province in Uzbekistan, Central Asia, was selected as a study region. Image segmentation was carried out on pan-sharpened SPOT data. Varying combinations of segmentation parameters (shape, compactness, and color) were tested for optimized boundary separation. The resulting geometry was validated against polygons digitized from the data and cadastre maps, analysing similarity (size, shape) and congruence. The parameters shape and compactness were decisive for segmentation accuracy. Differences between crop phenologies were analyzed at field level using bi-temporal ASTER data. A rule set based on the tasselled cap indices greenness and brightness allowed for classifying crop rotations of cotton, winter-wheat and rice, resulting in an overall accuracy of 80 %. The proposed field-based crop classification method can be an important tool for use in water demand estimations, crop yield simulations, or economic models in agricultural systems similar to Khorezm.
Wetlands in West Africa are among the most vulnerable ecosystems to climate change. West African wetlands are often freshwater transfer mechanisms from wetter climate regions to dryer areas, providing an array of ecosystem services and functions. Often wetland-specific data in Africa is only available on a per country basis or as point data. Since wetlands are challenging to map, their accuracies are not well considered in global land cover products. In this paper we describe a methodology to map wetlands using well-corrected 250-meter MODIS time-series data for the year 2002 and over a 360,000 km2 large study area in western Burkina Faso and southern Mali (West Africa). A MODIS-based spectral index table is used to map basic wetland morphology classes. The index uses the wet season near infrared (NIR) metrics as a surrogate for flooding, as a function of the dry season chlorophyll activity metrics (as NDVI). Topographic features such as sinks and streamline areas were used to mask areas where wetlands can potentially occur, and minimize spectral confusion. 30-m Landsat trajectories from the same year, over two reference sites, were used for accuracy assessment, which considered the area-proportion of each class mapped in Landsat for every MODIS cell. We were able to map a total of five wetland categories. Aerial extend of all mapped wetlands (class “Wetland”) is 9,350 km2, corresponding to 4.3% of the total study area size. The classes “No wetland”/“Wetland” could be separated with very high certainty; the overall agreement (KHAT) was 84.2% (0.67) and 97.9% (0.59) for the two reference sites, respectively. The methodology described herein can be employed to render wide area base line information on wetland distributions in semi-arid West Africa, as a data-scarce region. The results can provide (spatially) interoperable information feeds for inter-zonal as well as local scale water assessments.
Understanding the mechanisms of fragmentation within silicate melts is of great interest not only for material science, but also for volcanology, particularly regarding molten fuel coolant-interactions (MFCIs). Therefore edge-on hammer impact experiments (HIEs) have been carried out in order to analyze the fracture dynamics in well defined targets by applying a Cranz-Schardin highspeed camera technique. This thesis presents the corresponding results and provides a thorough insight into the dynamics of fragmentation, particularly focussing on the processes of energy dissipation. In HIEs two main classes of cracks can be identified, characterized by completely different fracture mechanisms: Shock wave induced “damage cracks” and “normal cracks”, which are exclusively caused by shear-stresses. This dual fracture situation is taken into account by introducing a new concept, according to which the crack class-specific fracture energies are linearly correlated with the corresponding fracture areas. The respective proportionality constants - denoted “fracture surface energy densities” (FSEDs) - have been quantified for all studied targets under various constraints. By analyzing the corresponding high speed image sequences and introducing useful dynamic parameters it has been possible to specify and describe in detail the evolution of fractures and, moreover, to quantify the energy dissipation rates during the fragmentation. Additionally, comprehensive multivariate statistical analyses have been carried out which have revealed general dependencies of all relevant fracture parameters as well as characteristics of the resulting particles. As a result, an important principle of fracture dynamics has been found, referred to as the “local anisotropy effect”: According to this principle, the fracture dynamics in a material is significantly affected by the location of directed stresses. High local stress gradients cause a more stable crack propagation and consequently a reduction of the energy dissipation rates. As a final step, this thesis focusses on the volcanological conclusions which can be drawn on the basis of the presented HIE results. Therefore fragments stemming from HIEs have been compared with natural and experimental volcanic ash particles of basaltic Grimsvötn and rhyolitic Tepexitl melts. The results of these comparative particle analyses substantiate HIEs to be a very suitable method for reproducing the MFCI loading conditions in silicate melts and prove the FSED concept to be a model which is well transferable to volcanic fragmentation processes.