@phdthesis{Breitkreuz2008,
  author    = {Breitkreuz, Hanne-Katarin},
  title     = {Solare Strahlungsprognosen f{\"u}r energiewirtschaftliche Anwendungen - Der Einfluss von Aerosolen auf das sichtbare Strahlungsangebot},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-28200},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2008},
  abstract  = {F{\"u}r eine dauerhaft gesicherte und umweltgerechte Energieerzeugung kommt den erneuerbaren Energien in Zukunft eine immer gr{\"o}ßere Bedeutung zu. Dies stellt eine große Herausforderung f{\"u}r die Entwicklung zuk{\"u}nftiger Energiesysteme dar, da erneuerbare Energietr{\"a}ger zeitlich und r{\"a}umlich zumeist hoch variabel zur Verf{\"u}gung stehen. Eine effiziente Integration solar erzeugter Energie in das bestehende Energieversorgungsnetz ist daher nur m{\"o}glich, wenn verl{\"a}ssliche Nahe-Echtzeit-Vorhersagen der am Erdboden verf{\"u}gbaren Einstrahlung und ein- bis dreit{\"a}gige Vorhersagen von Energieproduktion und -nachfrage zur Verf{\"u}gung stehen. Die vorliegende Arbeit besch{\"a}ftigt sich mit der Vorhersage der solaren Strahlung f{\"u}r die n{\"a}chsten Tage und Stunden im Hinblick auf Anwendungen in der Energiewirtschaft. Der dominante Atmosph{\"a}renparameter f{\"u}r die Abschw{\"a}chung der solaren Einstrahlung ist die Bew{\"o}lkung. Das gr{\"o}ßte wirtschaftliche Potential der Solarenergie liegt jedoch in Zeitr{\"a}umen und Regionen, in denen wenig Bew{\"o}lkung auftritt. Im wolkenlosen Fall beeinflussen vor allem Aerosole, feste und fl{\"u}ssige Partikel in der Atmosph{\"a}re, die direkte und diffuse Strahlung am Erdboden. Aerosole sind durch eine hohe zeitliche und r{\"a}umliche Variabilit{\"a}t gekennzeichnet, die die Bestimmung ihrer raumzeitlichen Verteilung und damit ihres Einflusses auf die Strahlung erschwert und einen hohen Aufwand zu ihrer Prognose erforderlich macht. Am Beispiel eines f{\"u}nfmonatigen europ{\"a}ischen Datensatzes (Juli-November 2003) werden Prognosen der aerosoloptischen Tiefe bei 550 nm (AOT550) untersucht, die aus Aerosolvorhersagen eines Chemie-Transport-Modells stammen. Es zeigt sich, dass im Vergleich mit Bodenmessungen die Aerosolprognosen mit einer mittleren Untersch{\"a}tzung von -0,11 und einem RMSE von 0,20 die geforderte Genauigkeit nicht ganz erreichen. Dabei stellen insbesondere die unregelm{\"a}ßig auftretenden Saharastaubausbr{\"u}che {\"u}ber dem zentralen Mittelmeer eine im Modell bisher nicht erfassbare Quelle großer Ungenauigkeiten in der AOT- und damit auch in der Strahlungsvorhersage dar. Entsprechend der hohen regionalen Aerosol-Variabilit{\"a}t finden sich zudem signifikante Unterschiede zwischen den Regionen, zum Beispiel eine deutliche Untersch{\"a}tzung des Aerosolaufkommens in der stark industriell belasteten Po-Ebene Norditaliens sowie gute Entsprechungen in abgelegenen Gegenden Nordeuropas. Basierend auf dieser Aerosol-Prognose und unter Einbeziehung weiterer Fernerkundungsdaten (Bodenalbedo, Ozon) und Parametern aus der numerischen Wetterprognose (Wasserdampf, Wolken) wird ein Prototyp f{\"u}r ein Vorhersagesystem der Solarstrahlung konzipiert und vorgestellt: das AFSOL-System (Aerosol-based Forecasts of Solar Irradiance for Energy Applications). An Hand der f{\"u}nfmonatigen Testepisode wird das AFSOL-System mit Vorhersagen des Europ{\"a}ischen Zentrums f{\"u}r Mittelfrist-Wettervorhersage (ECMWF), mit satellitenbasierten Beobachtungen der Solarstrahlung (Meteosat-7) und mit Bodenmessungen der Solarstrahlung verglichen. F{\"u}r den wolkenlosen Fall erzielt das AFSOL-Modellsystem eine deutliche Verbesserung der Direktstrahlungsprognosen gegen{\"u}ber den ECMWF-Vorhersagen, mit einer Reduktion des relativen Bias von -26\% auf +11\% und des relativen RMSE von 31\% auf 19\%. Dies kann auf die verbesserte Beschreibung des atmosph{\"a}rischen Aerosols zur{\"u}ckgef{\"u}hrt werden, die sich im Vergleich zu den am ECMWF genutzten AOT-Klimatologien ergibt, auch wenn insbesondere bei der Behandlung von W{\"u}stenstaubepisoden weiterhin Probleme auftreten. Auch die Globalstrahlungsprognosen erreichen im wolkenlosen Fall eine h{\"o}here Genauigkeit als die operationell verf{\"u}gbaren ECMWF-Vorhersagen, was sich in einer Verringerung des relativen Bias von -10\% zu +5\% sowie des relativen RMSE von 12\% zu 7\% zeigt. Im bew{\"o}lkten Fall jedoch k{\"o}nnen die Vorhersagen des AFSOL-Systems erhebliche Ungenauigkeiten aufweisen, die sich auf Grund von Problemen bei der Wolkenprognose des zu Grunde liegenden numerischen Wettervorhersagemodells ergeben. Abschließend wird in einer Fallstudie zur Verwendung der Vorhersagen f{\"u}r die optimale Betriebsf{\"u}hrung eines solarthermischen Kraftwerks in Spanien beispielhaft gezeigt, dass die Nutzung der AFSOL-Prognose im wolkenlosen Fall eine deutliche Gewinnsteigerung bei der Einspeisung ins {\"o}ffentliche Stromnetz durch den Handel an der spanischen Stromb{\"o}rse erm{\"o}glicht.},
  subject      = {Aerosol},
  language  = {de}
}
@phdthesis{Kirschke2008,
  author    = {Kirschke, Stefanie},
  title     = {Bilanzierung des Methanaustauschs zwischen Biosph{\"a}re und Atmosph{\"a}re in Periglazialr{\"a}umen mit Hilfe von Fernerkundung und Modellen am Beispiel des Lena Deltas},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-29024},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2008},
  abstract  = {Verbleibende Unsicherheiten im Kohlenstoffhaushalt in {\"O}kosystemen der hohen n{\"o}rdlichen Breiten k{\"o}nnen teilweise auf die Schwierigkeiten bei der Erfassung der r{\"a}umlich und zeitlich hoch variablen Methanemissionsraten von Permafrostb{\"o}den zur{\"u}ckgef{\"u}hrt werden. Methan ist ein global abundantes atmosph{\"a}risches Spurengas, welches signifikant zur Erw{\"a}rmung der Atmosph{\"a}re beitr{\"a}gt. Aufgrund der hohen Sensibilit{\"a}t des arktischen Bodenkohlenstoffreservoirs sowie der großen von Permafrost unterlagerten Landfl{\"a}chen sind arktische Gebiete am kritischsten von einem globalen Klimawandel betroffen. Diese Dissertation adressiert den Bedarf an Modellierungsans{\"a}tzen f{\"u}r die Bestimmung der Quellst{\"a}rke nordsibirischer permafrostbeeinflusster {\"O}kosysteme der nassen polygonalen Tundra mit Hinblick auf die Methanemissionen auf regionalem Maßstab. Die Arbeit pr{\"a}sentiert eine methodische Struktur in welcher zwei prozessbasierte Modelle herangezogen werden, um die komplexen Wechselwirkungen zwischen den Kompartimenten Pedosph{\"a}re, Biosph{\"a}re und Atmosph{\"a}re, welche zu Methanemissionen aus Permafrostb{\"o}den f{\"u}hren, zu erfassen. Es wird ein Upscaling der Gesamtmethanfl{\"u}sse auf ein gr{\"o}ßeres, von Permafrost unterlagertes Untersuchungsgebiet auf Basis eines prozessbasierten Modells durchgef{\"u}hrt. Das prozessbasierte Vegetationsmodell Biosphere Energy Hydrology Transfer Model (BETHY/DLR) wird f{\"u}r die Berechnung der Nettoprim{\"a}rproduktion (NPP) arktischer Tundravegetation herangezogen. Die NPP ist ein Maß f{\"u}r die Substratverf{\"u}gbarkeit der Methanproduktion und daher ein wichtiger Eingangsparameter f{\"u}r das zweite Modell: Das prozessbasierte Methanemissionsmodell wird anschließend verwendet, um die Methanfl{\"u}sse einer gegebenen Bodens{\"a}ule explizit zu berechnen. Dabei werden die Prozesse der Methanogenese, Methanotrophie sowie drei verschiedene Transportmechanismen - molekulare Diffusion, Gasblasenbildung und pflanzengebundener Transport durch vaskul{\"a}re Pflanzen - ber{\"u}cksichtigt. Das Methanemissionsmodell ist f{\"u}r Permafrostbedingungen modifiziert, indem das t{\"a}gliche Auftauen des Permafrostbodens in der kurzen arktischen Vegetationsperiode ber{\"u}cksichtigt wird. Der Modellantrieb besteht aus meteorologischen Datens{\"a}tzen des European Center for Medium-Range Weather Forecasts (ECMWF). Die Eingangsdatens{\"a}tze werden mit Hilfe von in situ Messdaten validiert. Zus{\"a}tzliche Eingangsdaten f{\"u}r beide Modelle werden aus Fernerkundungsdaten abgeleitet, welche mit Feldspektralmessungen validiert werden. Eine modifizierte Landklassifikation auf der Basis von Landsat-7 Enhanced Thematic Mapper Plus (ETM+) Daten wird f{\"u}r die Ableitung von Informationen zu Feuchtgebietsverteilung und Vegetationsbedeckung herangezogen. Zeitserien der Auftautiefe werden zur Beschreibung des Auftauens bzw. R{\"u}ckfrierens des Bodens verwendet. Diese Faktoren sind die Haupteinflussgr{\"o}ßen f{\"u}r die Modellierung von Methanemissionen aus permafrostbeeinflussten Tundra{\"o}kosystemen. Die vorgestellten Modellergebnisse werden mittels Eddy-Kovarianz-Messungen der Methanfl{\"u}sse validiert, welche w{\"a}hrend der Vegetationsperioden der Jahre 2003-2006 im s{\"u}dlichen Teil des Lena Deltas (72°N, 126°E) vom Alfred Wegener Institut f{\"u}r Polar- und Meeresforschung (AWI) durchgef{\"u}hrt wurden. Das Untersuchungsgebiet Lena Delta liegt an der Laptewsee in Nordostsibirien und ist durch {\"O}kosysteme der arktischen nassen polygonalen Tundra sowie kalten kontinuierlichen Permafrost charakterisiert. Zeitlich integrierte Werte der modellierten Methanfl{\"u}sse sowie der in situ Messungen zeigen gute {\"U}bereinstimmungen und weisen auf eine leichte Modelluntersch{\"a}tzung von etwa 10\%.},
  subject      = {Methanemission},
  language  = {de}
}
@phdthesis{Asam2014,
  author    = {Asam, Sarah},
  title     = {Potential of high resolution remote sensing data for leaf area index derivation using statistical and physical models},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-108399},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {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.},
  subject      = {Optische Fernerkundung},
  language  = {en}
}
@phdthesis{Forkuor2014,
  author    = {Forkuor, Gerald},
  title     = {Agricultural Land Use Mapping in West Africa Using Multi-sensor Satellite Imagery},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-108687},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {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.},
  subject      = {Westafrika},
  language  = {en}
}
@phdthesis{Pollinger2013,
  author    = {Pollinger, Felix},
  title     = {Bewertung und Auswirkungen der Simulationsg{\"u}te f{\"u}hrender Klimamoden in einem Multi-Modell Ensemble},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-97982},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Der rezente und zuk{\"u}nftige Anstieg der atmosph{\"a}rischen Treibhausgaskonzentration bedeutet f{\"u}r das terrestrische Klimasystem einen grundlegenden Wandel, der f{\"u}r die globale Gesellschaft schwer zu bew{\"a}ltigende Aufgaben und Herausforderungen bereit h{\"a}lt. Eine effektive, r{\"u}hzeitige Anpassung an diesen Klimawandel profitiert dabei enorm von m{\"o}glichst genauen Absch{\"a}tzungen k{\"u}nftiger Klima{\"a}nderungen. Das geeignete Werkzeug hierf{\"u}r sind Gekoppelte Atmosph{\"a}re Ozean Modelle (AOGCMs). F{\"u}r solche Fragestellungen m{\"u}ssen allerdings weitreichende Annahmen {\"u}ber die zuk{\"u}nftigen klimarelevanten Randbedingungen getroffen werden. Individuelle Fehler dieser Klimamodelle, die aus der nicht perfekten Abbildung der realen Verh{\"a}ltnisse und Prozesse resultieren, erh{\"o}hen die Unsicherheit langfristiger Klimaprojektionen. So unterscheiden sich die Aussagen verschiedener AOGCMs im Hinblick auf den zuk{\"u}nftigen Klimawandel insbesondere bei regionaler Betrachtung, deutlich. Als Absicherung gegen Modellfehler werden {\"u}blicherweise die Ergebnisse mehrerer AOGCMs, eines Ensembles an Modellen, kombiniert. Um die Absch{\"a}tzung des Klimawandels zu pr{\"a}zisieren, wird in der vorliegenden Arbeit der Versuch unternommen, eine Bewertung der Modellperformance der 24 AOGCMs, die an der dritten Phase des Vergleichsprojekts f{\"u}r gekoppelte Modelle (CMIP3) teilgenommen haben, zu erstellen. Auf dieser Basis wird dann eine nummerische Gewichtung f{\"u}r die Kombination des Ensembles erstellt. Zun{\"a}chst werden die von den AOGCMs simulierten Klimatologien f{\"u}r einige grundlegende Klimaelemente mit den betreffenden klimatologien verschiedener Beobachtungsdatens{\"a}tze quantitativ abgeglichen. Ein wichtiger methodischer Aspekt hierbei ist, dass auch die Unsicherheit der Beobachtungen, konkret Unterschiede zwischen verschiedenen Datens{\"a}tzen, ber{\"u}cksichtigt werden. So zeigt sich, dass die Aussagen, die aus solchen Ans{\"a}tzen resultieren, von zu vielen Unsicherheiten in den Referenzdaten beeintr{\"a}chtigt werden, um generelle Aussagen zur Qualit{\"a}t von AOGCMs zu treffen. Die Nutzung der K{\"o}ppen-Geiger Klassifikation offenbart jedoch, dass die prinzipielle Verteilung der bekannten Klimatypen im kompletten CMIP3 in vergleichbar guter Qualit{\"a}t reproduziert wird. Als Bewertungskriterium wird daher hier die F{\"a}higkeit der AOGCMs die großskalige nat{\"u}rliche Klimavariabilit{\"a}t, konkret die hochkomplexe gekoppelte El Ni{\~n}o-Southern Oscillation (ENSO), realistisch abzubilden herangezogen. Es kann anhand verschiedener Aspekte des ENSO-Ph{\"a}nomens gezeigt werden, dass nicht alle AOGCMs hierzu mit gleicher Realit{\"a}tsn{\"a}he in der Lage sind. Dies steht im Gegensatz zu den dominierenden Klimamoden der Außertropen, die modell{\"u}bergreifend {\"u}berzeugend repr{\"a}sentiert werden. Die wichtigsten Moden werden, in globaler Betrachtung, in verschiedenen Beobachtungsdaten {\"u}ber einen neuen Ansatz identifiziert. So k{\"o}nnen f{\"u}r einige bekannte Zirkulationsmuster neue Indexdefinitionen gewonnen werden, die sich sowohl als {\"a}quivalent 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 {\"U}bereinstimmung mit anderen Ans{\"a}tzen, ebenso die daraus folgende Bewertung der gesamten Performance der AOGCMs. Das Spektrum des Southern Oscillation-Index (SOI) stellt somit eine aussagekr{\"a}ftige Kenngr{\"o}ße der Modellqualit{\"a}t dar. Die Unterschiede in der F{\"a}higkeit, das ENSO-System abzubilden, erweisen sich als signifikante Unsicherheitsquelle im Hinblick auf die zuk{\"u}nftige Entwicklung einiger fundamentaler und bedeutsamer Klimagr{\"o}ßen, konkret der globalen Mitteltemperatur, des SOIs selbst, sowie des indischen Monsuns. Ebenso zeigen sich signifikante Unterschiede f{\"u}r regionale Klima{\"a}nderungen 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 Klima{\"a}nderungssignale im Multi-Modell Ensemble vergleichbar, die f{\"u}r die meisten Klimagr{\"o}ßen in einem robusten multivariaten Ansatz detektiert und quantifiziert werden k{\"o}nnen. Entsprechend sind die effektiven Klima{\"a}nderungen, die sich bei der Kombination aller Simulationen als grundlegende Aussage des CMIP3 unter den speziellen Randbedingungen ergeben nahezu unabh{\"a}ngig davon, ob alle L{\"a}ufe mit dem gleichen Einfluss ber{\"u}cksichtigt werden, oder ob die erstellte nummerische Gewichtung verwendet wird. Als eine wesentliche Begr{\"u}ndung hierf{\"u}r kann die Spannbreite der Entwicklung des ENSO-Systems identifiziert werden. Dies bedeutet gr{\"o}ßere Schwankungen in den Ergebnissen der Modelle mit funktionierendem ENSO, was den Stellenwert der nat{\"u}rlichen Variabilit{\"a}t als Unsicherheitsquelle in Fragen des Klimawandels unterstreicht. Sowohl bei Betrachtung der Teilensembles als auch der Gewichtung wirken sich dadurch gegenl{\"a}ufige Trends im SOI ausgleichend auf die Entwicklung anderer Klimagr{\"o}ßen aus, was insbesondere bei letzterem Vorgehen signifikante mittlere Effekte des Ansatzes, verglichen mit der Verwendung des {\"u}blichen arithmetischen Multi-Modell Mittelwert, verhindert.},
  subject      = {Modell},
  language  = {de}
}
@phdthesis{Loew2013,
  author    = {L{\"o}w, Fabian},
  title     = {Agricultural crop mapping from multi-scale remote sensing data - Concepts and applications in heterogeneous Middle Asian agricultural landscapes},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-102093},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {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.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Paxian2012,
  author    = {Paxian, Andreas},
  title     = {Future changes in climate means and extremes in the Mediterranean region deduced from a regional climate model},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72155},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {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.},
  subject      = {Mittelmeerraum},
  language  = {en}
}
@phdthesis{Fritsch2013,
  author    = {Fritsch, Sebastian},
  title     = {Spatial and temporal patterns of crop yield and marginal land in the Aral Sea Basin: derivation by combining multi-scale and multi-temporal remote sensing data with alight use efficiency model},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87939},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {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.},
  subject      = {Fernerkundung},
  language  = {en}
}
@misc{Knauer2011,
  type      = {Master Thesis},
  author    = {Knauer, Kim},
  title     = {Monitoring ecosystem health of Fynbos remnant vegetation in the City of Cape Town using remote sensing},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-92495},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {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.},
  subject      = {remote sensing},
  language  = {en}
}
@phdthesis{Wegmann2009,
  author    = {Wegmann, Martin},
  title     = {Analyse von r{\"a}umlichen Landschaftsmustern und deren Determinanten mittels Fernerkundungsdaten : am Beispiel von Regenwaldfragmenten in Westafrika},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-36532},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {In den letzten Jahrzehnten ist eine verst{\"a}rkte Ver{\"a}nderung der Landoberfl{\"a}che beobachtet worden. Diese Prozesse sind direkten und indirekten anthropogenen Einfl{\"u}ssen zuzuschreiben, wie Deforestation oder Klimawandel. Mit dieser Entwicklung geht der Verlust und die Fragmentation von naturnahen Fl{\"a}chen einher. F{\"u}r das Fortbestehen von Populationen verschiedenster Organismen in einer derartig geformten Landschaft ist entscheidend, inwieweit die Migration zwischen bestehenden Fragmenten gew{\"a}hrleistet ist. Diese wird von der Eignung der umgebenden Landschaft beeinflusst. Im Kontext einer klimatischen Ver{\"a}nderung und verst{\"a}rkter anthropogener Landnutzung ist die Analyse der r{\"a}umlichen Anordnung von Habitatfragmenten und der Qualit{\"a}t der umgebenden Landschaft besonders f{\"u}r die globale Aufrechterhaltung der Biodiversit{\"a}t wichtig. Großr{\"a}umige Muster der Landschaftsver{\"a}nderung k{\"o}nnen mit Hilfe von Satellitendaten analysiert werden, da es nur diese erm{\"o}glichen die Landbedeckung fl{\"a}chendeckend, reproduzierbar und auf einer ad{\"a}quaten r{\"a}umlichen Aufl{\"o}sung zu kartieren. Besonders zeitlich hochaufgel{\"o}ste Daten liefern wertvolle Informationen bez{\"u}glich der Dynamik der Landbedeckung. Diese Arbeit besch{\"a}ftigt sich mit der Analyse der Fragmentation in Westafrika und der potentiellen Bedeutung von singul{\"a}ren Fragmenten und deren potentiellen Auswirkungen auf die Biodiversit{\"a}t. Daf{\"u}r wurden zeitlich hoch- und r{\"a}umlich mittelaufgel{\"o}ste Daten des Aufnahmesystems MODIS verwendet, mit denen f{\"u}r das Untersuchungsgebiet Westafrika die Landbedeckung klassifziert wurde. F{\"u}r die darauf folgenden Analysen der r{\"a}umlichen Konfiguration der Fragmente wurde der Fokus auf Regenwaldgebiete gelegt. Die Analyse von r{\"a}umlichen Mustern der Regenwaldfragmente liefert weiterf{\"u}hrende qualitative Informationen der individuellen Teilbereiche. Die r{\"a}umliche Anordnung wurde sowohl mit etablierten Maßen als auch mittels in dieser Arbeit erstellter robuster und {\"u}bertragbarer Indizes quantifiziert. Es konnte gezeigt werden, dass die Verwendung von aussagekr{\"a}ftigen Indizes, besonders, wenn sie alle benachbarten Fragmente und die Qualit{\"a}t der umgebenden Matrix ber{\"u}cksichtigen, die r{\"a}umliche Differenzierung von Fragmenten verbessert. Jedoch ist die Anwendung dieser Maße abh{\"a}ngig von den Anspr{\"u}chen einer Art. Daher muss die artspezifische Perzeptionen der Landschaft auf der Basis der Indizes implementiert werden, da die {\"U}bertragung der Ergebnisse einzelner Indizes auf andere r{\"a}umliche Aufl{\"o}sungen und andere Regionen nur begrenzt m{\"o}glich war. Des Weiteren wurden potentielle Einflussfaktoren auf die r{\"a}umlichen Muster mittels Neutraler Landschaftsmodelle untersucht. Hierbei ergaben sich je nach Region und Index unterschiedliche Ergebnisse, allerdings konnte der Einfluss anthropogen induzierter Ver{\"a}nderungen auf die Landbedeckung postuliert werden. Die große Bedeutung der r{\"a}umlichen Attribution von Landbedeckungsklassen konnte in dieser Arbeit aufgezeigt werden. Der alleinige Fokus auf die Kartierung von z. B. Waldfragmenten ohne deren r{\"a}umliche Anordnung zu ber{\"u}cksichtigen, kann zu falschen Schl{\"u}ssen bez{\"u}glich deren {\"o}kologischen, hydrologischen und klimatologischen Bedeutung f{\"u}hren.},
  subject      = {Fragmentierung},
  language  = {de}
}
@misc{Cammerer2009,
  type      = {Master Thesis},
  author    = {Cammerer, Holger},
  title     = {Minderung von Hochwassersch{\"a}den durch Fr{\"u}hwarnung und Eigenvorsorge - Eine statistische Analyse von Befragungen in Privathaushalten in Deutschland und {\"O}sterreich},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-47314},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {Ziel der vorliegenden Arbeit war es, anhand von aktuellen Hochwasserschadensdaten aus Telefonbefragungen in Privathaushalten in Deutschland und {\"O}sterreich die Minderung von Hochwassersch{\"a}den durch Fr{\"u}hwarnung und privater Eigenvorsorge zu quantifizieren. Im ersten Schritt wurden die Datens{\"a}tze aus den vier zugrunde liegenden Befragungen zu den Hochwasserereignissen der Jahre 2002, 2005 und 2006 zusammengef{\"u}hrt und die Hochwassersch{\"a}den auf das Referenzjahr 2007 angepasst. Um das Schadensminderungspotenzial von Fr{\"u}hwarnung und diversen Vorsorge-/ Notmaßnahmen beurteilen zu k{\"o}nnen, wurde der konsistente Datensatz nach verschiedenen schadensbestimmenden Faktoren (Wasserstand, Hochwassertyp, Kontaminationsart und Hochwassererfahrung) aufgeteilt. Dabei stellte sich heraus, dass eine Hochwasserwarnung z.B. durch Beh{\"o}rden den Schaden am Geb{\"a}ude und Hausrat nur dann reduzieren kann, wenn der Fr{\"u}hwarnungsinhalt klar verst{\"a}ndlich oder das Wissen der Betroffenen ausreichend ist, wie man sich und seinen Haushalt vor dem Hochwasser sch{\"u}tzen kann (durch das Ergreifen von Notmaßnahmen). Der Nutzen einer langfristigen Vorsorge, insbesondere von baulichen Maßnahmen, wurde in dieser Studie sehr deutlich. Vor allem die geringwertige Nutzung der hochwassergef{\"a}hrdeten Stockwerke und die hochwasserangepasste Inneneinrichtung konnten die Sch{\"a}den am Geb{\"a}ude und Inventar erheblich reduzieren.},
  subject      = {Hochwasser},
  language  = {de}
}
@phdthesis{Nagm2009,
  author    = {Nagm, Emad Hamdy Mahmoud},
  title     = {Integrated stratigraphy, palaeontology and facies analysis of the Cenomanian - Turonian (Upper Cretaceous) Galala and Maghra El Hadida formations of the western Wadi Araba, Eastern Desert, Egypt},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-39881},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {Four sections of the Galala and Maghra El Hadida formations on the footwalls of the slopes of the northern and southern Galala plateaus in Wadi Araba (Eastern Desert) have been measured and sampled in great detail. The Galala Formation is ranging in thickness from 55 to 95 meters. It unconformably overlies the Malha Formation which forms the base of the studied sections. The upper boundary of the Galala Formation is characterized by a major unconformity which separates it from the overlying the Maghra El Hadida Formation. The Galala Formation can be subdivided into five shallowing-upward cycles, each cycle starting with deep-lagoonal, marly-silty deposits at the base and grading into highly fossiliferous shallow-lagoonal limestones at the top. Only the basal part of the Galala Formation consists of unfossiliferous, greenish sandy siltstones intercalated with thin cross-bedded, bioturbated, fine- to medium-grained sandstones. Despite the lack of biostratigraphic markers in that lower part, its age can be assigned to the late Middle Cenomanian, since the conformably overlying strata contain the ammonite Neolobites vibrayeanus (D'ORBIGNY), the index marker of the early Upper Cenomanian which extends into the top of the formation. The measured thickness of the overlying Maghra El Hadida Formation is ranging from 59 to 118 meters. This formation starts with the Ghonima Member, introduced in this work to distinguish a brown, fine- to medium-grained calcareous sandstone unit in its lower part. The Ghonima Member is erosionally incised into the Galala Formation, explaining its strong lateral variability in thickness, ranging from 3 to 21 meters. It is mostly unfossiliferous except for irregular bioturbation in its upper part. The Ghonima Member is assigned to the middle Upper Cenomanian, based on its stratigraphic position between the lower Upper Cenomanian Neolobites vibrayeanus Zone and the overlying upper Upper Cenomanian Metoicoceras geslinianum and Vascoceras cauvini zones. This means that the lower part of the Maghra El Hadida Formation, about 20 - 30 m thick, accumulated during the latest Cenomanian and that the base of the formation does not coincide with the base of the Turonian as commonly believed. The overlying succession of the Maghra El Hadida Formation is characterized by an increase of carbonate content, represented by yellow, soft marls intercalated with fine-grained wacke- to packstones containing a highly fossiliferous ammonite assemblage of the upper Upper Cenomanian and Lower Turonian (zones of Vascoceras proprium, Choffaticeras spp., and Wrightoceras munieri). The Middle Turonian part of the Maghra El Hadida Formation consists of poorly fossiliferous, thick-bedded yellowish marls with upward-increasing silt content, showing occasional intercalations of medium- to coarse-grained sandstones with hummocky cross-stratification. The topmost part of the Maghra El Hadida Formation consists of brownish, medium-grained sandstones topped by fossiliferous marly limestones yielding the Upper Turonian zonal ammonite Coilopoceras requienianum (D'ORBIGNY). Based on sequence stratigraphic analyses, four complete 3rd order depositional sequences and the lower part of a fifth one, each bounded by major unconformities, can be recognized: depositional sequence DS WA 1 (upper Middle - lower Upper Cenomanian) includes the entire Galala Formation, while the Maghra El Hadida Formation comprises all the overlying depositional sequences: DS WA 2 (upper Upper Cenomanian - Lower Turonian) reaches from the base of the Metoicoceras geslinianum Zone to the top of Wrightoceras munieri Zone, DS WA 3 and DS WA 4 comprise the Middle Turonian, while Upper Turonian sequence DS WA 5 is not complete. The stratigraphic positions of the recognized sequence 2 boundaries SB WA 1 to SB WA 5 match well with contemporaneous sequence boundaries known from Europe and elsewhere. The stacking pattern of the basic cycles and bundles of the Galala Formation (5:1) and the Maghra El Hadida Formation (4:1) strongly suggest an orbital forcing by MILANKOVITCH periodicities. The Galala Formation is composed of five 5th-order bundles which equal to ~500 kyr, each bundle equals to ~100 kyr (short eccentricity). Every bundle has five basic (6th-order) cycles, each one representing ~20 kyr (precession). Based on this precession-short eccentricity syndrome, the accumulation rate of the Galala Formation therefore accounts for about 19 cm/kyr. The rate of sea-level fall at sequence boundary SB WA 2 (equivalent to the quasi-global mid-Late Cenomanian SB Ce V) estimated is with 35 cm/kyr which can be explained only by glacio-eustasy. The Upper Cenomanian and Lower Turonian part of the Maghra El Hadida Formation is considered to equal to ~1200 kyr, based on the existence of three 4th-order bundles with an inferred duration of ~400 kyr for each bundle (long eccentricity of the MILANKOVITCH Band). Every bundle consists of four basic cycles with a duration of ~100 kyr. This means that the upper Cenomanian part of the Maghra El Hadida Formation is equivalent to ~400 kyr, while the Lower Turonian (consisting of the two upper bundles) lasted 800 kyr. This matches well with the recently proposed 785 kyr duration of the Early Turonian (SAGEMAN et al., 2006; VOIGT et al., 2008) and contradicts the 1300 kyr according to the standard time scale of GRADSTEIN et al. (2004). According to this temporal constrains, the accumulation rate of the Maghra El Hadida Formation is about 4.25 cm/kyr. In addition, based on the cyclostratigraphic analysis, the range of the Early Turonian genus Choffaticeras (HYATT) is equivalent to ~325 kyr and morphological changes within its lineage can be quantified. The macrobenthos (bivalves, gastropods, echinoids) and cephalopods of the Galala and Maghra El Hadida formations were identified and illustrated in 24 figures. The ammonite taxonomy and palaeobiogeographic distribution is discussed in detail. Four genera and eight ammonite species are recorded from Egypt for the first time. The microfloral and -faunal assemblage identified in thin sections revealed two species of dasycladalean algae, two species of udoteacean algae, five species of benthic foraminifera, and two species of crustacean microcoprolites. The six facies types of the upper Middle - Upper Cenomanian Galala Formation document largely open-lagoonal, warm water conditions, while the depositional environment of the Upper Cenomanian - Turonian Maghra El Hadida Formation (16 facies types) is suggested to range from a deep-subtidal to intertidal.},
  subject      = {Oberkreide},
  language  = {en}
}
@phdthesis{Baumann2009,
  author    = {Baumann, Sabine Christine},
  title     = {Mapping, analysis, and interpretation of the glacier inventory data from Jotunheimen, South Norway, since the maximum of the 'Little Ice Age'},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-46320},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2009},
  abstract  = {Glacier outlines during the 'Little Ice Age' maximum in Jotunheimen were mapped by using remote sensing techniques (vertical aerial photos and satellite imagery), glacier outlines from the 1980s and 2003, a digital terrain model (DTM), geomorphological maps of individual glaciers, and field-GPS measurements. The related inventory data (surface area, minimum and maximum altitude) and several other variables (e.g. slope, range) were calculated automatically by using a geographical information system. The length of the glacier flowline was mapped manually based on the glacier outlines at the maximum of the 'Little Ice Age' and the DTM. The glacier data during the maximum of the 'Little Ice Age' were compared with the Norwegian glacier inventory of 2003. Based on the glacier inventories during the maximum of the 'Little Ice Age', the 1980s and 2003, a simple parameterization after HAEBERLI \& HOELZLE (1995) was performed to estimate unmeasured glacier variables, as e.g. surface velocity or mean net mass balance. Input data were composed of surface glacier area, minimum and maximum elevation, and glacier length. The results of the parameterization were compared with the results of previous parameterizations in the European Alps and the Southern Alps of New Zealand (HAEBERLI \& HOELZLE 1995; HOELZLE et al. 2007). A relationship between these results of the inventories and of the parameterization and climate and climate changes was made.},
  subject      = {Gletscher},
  language  = {en}
}
@article{UereyenBachoferKuenzer2022,
  author    = {Uereyen, Soner and Bachofer, Felix and Kuenzer, Claudia},
  title     = {A framework for multivariate analysis of land surface dynamics and driving variables — a case study for Indo-Gangetic river basins},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {1},
  issn      = {2072-4292},
  doi       = {10.3390/rs14010197},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-255295},
  year      = {2022},
  abstract  = {The analysis of the Earth system and interactions among its spheres is increasingly important to improve the understanding of global environmental change. In this regard, Earth observation (EO) is a valuable tool for monitoring of long term changes over the land surface and its features. Although investigations commonly study environmental change by means of a single EO-based land surface variable, a joint exploitation of multivariate land surface variables covering several spheres is still rarely performed. In this regard, we present a novel methodological framework for both, the automated processing of multisource time series to generate a unified multivariate feature space, as well as the application of statistical time series analysis techniques to quantify land surface change and driving variables. In particular, we unify multivariate time series over the last two decades including vegetation greenness, surface water area, snow cover area, and climatic, as well as hydrological variables. Furthermore, the statistical time series analyses include quantification of trends, changes in seasonality, and evaluation of drivers using the recently proposed causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI). We demonstrate the functionality of our methodological framework using Indo-Gangetic river basins in South Asia as a case study. The time series analyses reveal increasing trends in vegetation greenness being largely dependent on water availability, decreasing trends in snow cover area being mostly negatively coupled to temperature, and trends of surface water area to be spatially heterogeneous and linked to various driving variables. Overall, the obtained results highlight the value and suitability of this methodological framework with respect to global climate change research, enabling multivariate time series preparation, derivation of detailed information on significant trends and seasonality, as well as detection of causal links with minimal user intervention. This study is the first to use multivariate time series including several EO-based variables to analyze land surface dynamics over the last two decades using the causal discovery algorithm PCMCI.},
  language  = {en}
}
@phdthesis{Hoeser2022,
  author    = {H{\"o}ser, Thorsten},
  title     = {Global Dynamics of the Offshore Wind Energy Sector Derived from Earth Observation Data - Deep Learning Based Object Detection Optimised with Synthetic Training Data for Offshore Wind Energy Infrastructure Extraction from Sentinel-1 Imagery},
  doi       = {10.25972/OPUS-29285},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-292857},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {The expansion of renewable energies is being driven by the gradual phaseout of fossil fuels in order to reduce greenhouse gas emissions, the steadily increasing demand for energy and, more recently, by geopolitical events. The offshore wind energy sector is on the verge of a massive expansion in Europe, the United Kingdom, China, but also in the USA, South Korea and Vietnam. Accordingly, the largest marine infrastructure projects to date will be carried out in the upcoming decades, with thousands of offshore wind turbines being installed. In order to accompany this process globally and to provide a database for research, development and monitoring, this dissertation presents a deep learning-based approach for object detection that enables the derivation of spatiotemporal developments of offshore wind energy infrastructures from satellite-based radar data of the Sentinel-1 mission. For training the deep learning models for offshore wind energy infrastructure detection, an approach is presented that makes it possible to synthetically generate remote sensing data and the necessary annotation for the supervised deep learning process. In this synthetic data generation process, expert knowledge about image content and sensor acquisition techniques is made machine-readable. Finally, extensive and highly variable training data sets are generated from this knowledge representation, with which deep learning models can learn to detect objects in real-world satellite data. The method for the synthetic generation of training data based on expert knowledge offers great potential for deep learning in Earth observation. Applications of deep learning based methods can be developed and tested faster with this procedure. Furthermore, the synthetically generated and thus controllable training data offer the possibility to interpret the learning process of the optimised deep learning models. The method developed in this dissertation to create synthetic remote sensing training data was finally used to optimise deep learning models for the global detection of offshore wind energy infrastructure. For this purpose, images of the entire global coastline from ESA's Sentinel-1 radar mission were evaluated. The derived data set includes over 9,941 objects, which distinguish offshore wind turbines, transformer stations and offshore wind energy infrastructures under construction from each other. In addition to this spatial detection, a quarterly time series from July 2016 to June 2021 was derived for all objects. This time series reveals the start of construction, the construction phase and the time of completion with subsequent operation for each object. The derived offshore wind energy infrastructure data set provides the basis for an analysis of the development of the offshore wind energy sector from July 2016 to June 2021. For this analysis, further attributes of the detected offshore wind turbines were derived. The most important of these are the height and installed capacity of a turbine. The turbine height was calculated by a radargrammetric analysis of the previously detected Sentinel-1 signal and then used to statistically model the installed capacity. The results show that in June 2021, 8,885 offshore wind turbines with a total capacity of 40.6 GW were installed worldwide. The largest installed capacities are in the EU (15.2 GW), China (14.1 GW) and the United Kingdom (10.7 GW). From July 2016 to June 2021, China has expanded 13 GW of offshore wind energy infrastructure. The EU has installed 8 GW and the UK 5.8 GW of offshore wind energy infrastructure in the same period. This temporal analysis shows that China was the main driver of the expansion of the offshore wind energy sector in the period under investigation. The derived data set for the description of the offshore wind energy sector was made publicly available. It is thus freely accessible to all decision-makers and stakeholders involved in the development of offshore wind energy projects. Especially in the scientific context, it serves as a database that enables a wide range of investigations. Research questions regarding offshore wind turbines themselves as well as the influence of the expansion in the coming decades can be investigated. This supports the imminent and urgently needed expansion of offshore wind energy in order to promote sustainable expansion in addition to the expansion targets that have been set.},
  language  = {en}
}
@book{Brauneck2010,
  author    = {Brauneck, Jens},
  title     = {Late Quaternary climate changes in the Central Sahara : new evidence from palaeoenvironmental research in NE-Niger},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235146},
  publisher      = {Universit{\"a}t W{\"u}rzburg},
  pages     = {XI, 158},
  year      = {2010},
  abstract  = {Surveys by the Universities of Wuerzburg and Berlin, starting in the 1970´s have revealed the existence of palaeolakes in remote areas in Niger. Initial research has shown that the sediments found are suitable for reconstructing its late quaternary palaeoenvironment. Although a high number of investigations focused on the succession of climatological conditions in the Central Sahara, some uncertainties still exist as the results show discontinuities and mostly are of low temporal and spatial resolution. Two expeditions in 2005 and 2006 headed to the northeastern parts of Niger to investigate the known remains of palaeolakes and search some new and undetected ones. Samples were taken at several study sites in order to receive a complete picture of the Late Quaternary environmental settings and to produce high-resolution proxies for palaeoclimate modelling. The most valuable and best-investigated study site is the sebkha of Seggedim, where a core of 15 meters length could be extracted which revealed a composition of high-resolution sections. Stratigraphical, structural and geochemical investigations as well as the analysis of thin sections allow the characterization of different environmental conditions from Early to Mid Holocene. Driven by climate and hydrogeological influence, the water body developed from a water pond of several metres depth within a stable, grass and shrub vegetated landscape, to an alternating freshwater lake in a more dynamic environmental setting. Radiocarbon dates set the beginning of the stage at about 10.6 ka cal BP, with an exceptionally stable regime to 6.6 ka cal BP (at 12.6 metres' depth), when a major change in the sedimentation regime of the basin is recorded in the core. Increased erosion, likely due to decreased vegetation cover within the basin, led to the siltation/filling of the lake within a few hundred years and the subsequent development of a sebkha/salt pan due to massive evaporation. Due to the lack of dateable material in the upper core section, the termination of the lake stage and the onset of the subsequent sebkha stage cannot be determined precisely but can be narrowed to a period around 6 ka BP. The results obtained from the core are compared with those from terrestrial and lacustrine sediments from outside the depression, situated a few hundred kilometres further to the north. These supplementary study sites are required to validate the information obtained from the coring. Within the plateau landscape of Djado, Mangueni and Tchigai, two depressions and a valley containing lacustrine deposits, were investigated for palaeoenvironmental reconstruction. Depending on modifying local factors, these sediment archives were of shorter existence than IX the lake, but reveal additional information about the landscape dynamics from Early to Mid Holocene. A damming situation within a small tributary at Enneri Achelouma led to lacustrine sedimentation conditions at Early Holocene in the upper reaches of the valley. The remnants of the lacustrine accumulations show distinct changes in the environmental conditions within the small catchment, as the archive immediately responded to local climate-induced changes of precipitation. Radiocarbon dating of the deposited sediments revealed ages from 8780 ± 260 cal a BP to 9480 ± 80 cal a BP. The sites of Yoo Ango and Fab{\´e}rg{\´e} show a completely different sedimentation milieu as they consist of basins within the foothills of the Tchigai. The study sites show increased catchment sizes, probably extending towards the Tchigai massif and are most likely influenced by groundwater charge. The widespread occurrence of wind shaped relicts and the limited amount of lacustrine remnants indicate a generally high aeolian activity in both areas. Only in wind sheltered spots, parts of the lacustrine sequences were preserved, that show ages spanning from Early to Mid Holocene (9440 ± 140 cal a BP - 6810 ±140 cal a BP) and give additional evidence of fires from pre-LGM periods. Although intensively weathered, all profiles indicate distinct changes in the sedimentation conditions by alternating geochemical values and the mineralogical composition. The information obtained from the records investigated in this work confirms the heterogeneity of reconstructed environmental succession in the Central Sahara. The Mid Holocene rapid (within decades) and uniform development from more humid to extremely arid environmental conditions cannot be confirmed for the Central Sahara. In addition, a division of Early and Mid Holocene wet periods cannot be confirmed, either. Actually, the evidences obtained from the palaeoenvironmental reconstructions revealed major variations in the timing and extend of lacustrine and aeolian periods. Evidently, a transitional time has existed between 7 to 5 ka BP where alternating influences prevailed. This is indicated by the varying sedimentation conditions in the Seggedim depression as well as the evidence of soil properties on a fossil dune, with a time of deposition dated to 6200 ± 400 cal a BP and the removal of lacustrine Sediments at the Seeterrassental at Mid Holocene. In respect to provide a complete picture of landscape succession and to avoid misinterpretation, the investigation of several dissimilar spots within a designated study area is prerequisite for further investigations.},
  subject      = {Pal{\"a}oklimatologie},
  language  = {en}
}
@book{OPUS4-24885,
  title     = {Innenst{\"a}dte, Einzelhandel und Corona in Deutschland},
  editor    = {Appel, Alexandra and Hardaker, Sina},
  isbn      = {978-3-95826-176-1},
  issn      = {2196-5811},
  doi       = {10.25972/WUP-978-3-95826-177-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248851},
  publisher      = {W{\"u}rzburg University Press},
  pages     = {238},
  year      = {2022},
  abstract  = {"Die Innenstadt braucht den Handel, der Handel aber nicht die Innenstadt", lautet eine oft formulierte These bez{\"u}glich des Verh{\"a}ltnisses von Handel und Innenstadt - nicht erst seit der Covid-19-Pandemie. Die Krise hat die Herausforderungen des Strukturwandels im Einzelhandel erneut offengelegt und teils Entwicklungen beschleunigt. Besonders hervorzuheben sind zum einen Handlungsbedarfe im Bereich der Digitalisierung sowie die dringende Notwendigkeit einer {\"u}berdachten Auseinandersetzung {\"u}ber das Verh{\"a}ltnis von Innenstadt und Einzelhandel. Neben Fragen zur zuk{\"u}nftigen Gestaltung des Einzelhandels und seiner Bedeutung f{\"u}r Innenst{\"a}dte, sind auch Fragen zur Bedeutung anderer Branchen/Einrichtungen/Angebote (z.B. Gastronomie, Handwerk, Kultureinrichtungen, Kitas, Sport- und Bildungseinrichtungen, aber auch Freir{\"a}ume, Gr{\"u}nfl{\"a}chen, verkehrsberuhigte Bereiche oder lokale Kurierdienste) f{\"u}r den Einzelhandel vermehrt aus Perspektive der geographischen Handelsforschung zu beantworten. Mit der Krise wurden Defizite und Handlungsfelder in den Blick ger{\"u}ckt, deren Bearbeitung schon lange ansteht. Die Chance liegt darin, diesen Aufmerksamkeitsschub konstruktiv zu nutzen und realistische fall- und standortspezifische Perspektiven f{\"u}r Innenst{\"a}dte und ihre Akteur*innen jetzt zu verhandeln und nicht weiter auf die lange Bank zu schieben. Der vorliegende Band vereint neun handelsgeographische Beitr{\"a}ge von Wissenschaftler*innen und Praktiker*innen, die die Auswirkungen der Covid-19-Pandemie er{\"o}rtern und damit einen wichtigen Beitrag f{\"u}r die notwendige Diskussion der Zukunft von Innenst{\"a}dten und Handel leisten.},
  subject      = {Einzelhandel},
  language  = {de}
}
@article{Rauch2022,
  author    = {Rauch, Sebastian},
  title     = {Analysing Long Term Spatial Mobility Patterns of Individuals and Large Groups Using 3D-GIS: A Sport Geographic Approach},
  series = {Tijdschrift voor Economische en Sociale Geografie},
  volume    = {113},
  journal   = {Tijdschrift voor Economische en Sociale Geografie},
  number    = {3},
  issn      = {0040-747X},
  doi       = {10.1111/tesg.12513},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-318551},
  pages     = {257 -- 272},
  year      = {2022},
  abstract  = {Individual mobility and human patterns analyses is receiving increasing attention in numerous interdisciplinary studies and publications using the concept of time-geography but is largely unknown to the subdiscipline of sports geography. Meanwhile the visualization and evaluation of large data of individual patterns are still a major challenge. While a qualitative, microscale view on spatial-temporal topics is more common in today's pattern research using mostly 24h time intervals, this work examines a quantitative approach focusing on an extended period of life. This paper presents a combination of time-geographic approaches with 3D-geoinformation systems and demonstrates their value for analysing individual mobility by implementing a path-homogeneity factor (HPA). Using the example of professional athletes, it is shown which groups display greater similarities in their career paths. While a high homogeneity suggests that groups make similar decisions through socially influenced processes, low values allow the assumption that external processes provide stronger, independent individual structures.},
  language  = {en}
}
@article{KumarKhamzinaKnoefeletal.2021,
  author    = {Kumar, Navneet and Khamzina, Asia and Kn{\"o}fel, Patrick and Lamers, John P. A. and Tischbein, Bernhard},
  title     = {Afforestation of degraded croplands as a water-saving option in irrigated region of the Aral Sea Basin},
  series = {Water},
  volume    = {13},
  journal   = {Water},
  number    = {10},
  issn      = {2073-4441},
  doi       = {10.3390/w13101433},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-239626},
  year      = {2021},
  abstract  = {Climate change is likely to decrease surface water availability in Central Asia, thereby necessitating land use adaptations in irrigated regions. The introduction of trees to marginally productive croplands with shallow groundwater was suggested for irrigation water-saving and improving the land's productivity. Considering the possible trade-offs with water availability in large-scale afforestation, our study predicted the impacts on water balance components in the lower reaches of the Amudarya River to facilitate afforestation planning using the Soil and Water Assessment Tool (SWAT). The land-use scenarios used for modeling analysis considered the afforestation of 62\% and 100\% of marginally productive croplands under average and low irrigation water supply identified from historical land-use maps. The results indicate a dramatic decrease in the examined water balance components in all afforestation scenarios based largely on the reduced irrigation demand of trees compared to the main crops. Specifically, replacing current crops (mostly cotton) with trees on all marginal land (approximately 663 km\(^2\)) in the study region with an average water availability would save 1037 mln m\(^3\) of gross irrigation input within the study region and lower the annual drainage discharge by 504 mln m\(^3\). These effects have a considerable potential to support irrigation water management and enhance drainage functions in adapting to future water supply limitations.},
  language  = {en}
}
@phdthesis{Knoefel2018,
  author    = {Kn{\"o}fel, Patrick},
  title     = {Energiebilanzmodellierung zur Ableitung der Evapotranspiration - Beispielregion Khorezm},
  edition   = {1. Auflage},
  publisher = {W{\"u}rzburg University Press},
  address   = {W{\"u}rzburg},
  isbn      = {978-3-95826-042-9 (Print)},
  issn      = {0510-9833},
  doi       = {10.25972/WUP-978-3-95826-043-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-135669},
  school      = {W{\"u}rzburg University Press},
  pages     = {276},
  year      = {2018},
  abstract  = {Zum Verst{\"a}ndnis der komplexen Wechselwirkungen innerhalb des Klimasystems der Erde sind Kenntnisse {\"u}ber den hydrologischen Zyklus und den Energiekreislauf essentiell. Eine besondere Rolle obliegt hierbei der Evapotranspiration (ET), da sie eine wesentliche Teilkomponente beider oben erw{\"a}hnter Kreisl{\"a}ufe ist. Die exakte Quantifizierung der regionalen, tats{\"a}chlichen Evapotranspiration innerhalb der Wasser- und Energiekreisl{\"a}ufe der Erdoberfl{\"a}che auf unterschiedlichen zeitlichen und r{\"a}umlichen Skalen ist f{\"u}r hydrologische, klimatologische und agronomische Fragestellungen von großer Bedeutung. Dabei ist eine realistische Absch{\"a}tzung der regionalen tats{\"a}chlichen Evapotranspiration die wichtigste Herausforderung der hydrologischen Modellierung. Besonders die unterschiedlichen r{\"a}umlichen und zeitlichen Aufl{\"o}sungen von Satelliteninformationen machen die Fernerkundung sowohl f{\"u}r globale als auch regionale hydrologischen Fragestellungen interessant. Zus{\"a}tzlich zur Notwendigkeit des Prozessverst{\"a}ndnisses des Wasserkreislaufs auf globaler Ebene kommt dessen regionale Bedeutung f{\"u}r die Landwirtschaft, insbesondere in Bew{\"a}sserungssystemen arider Regionen. In ariden Klimazonen {\"u}bersteigt die Menge der Verdunstung oft bei weitem die Niederschlagsmengen. Aufgrund der geringen Niederschlagsmenge muss in ariden agrarischen Regionen das zum Pflanzenwachstum ben{\"o}tigte Wasser mit Hilfe k{\"u}nstlicher Bew{\"a}sserung aufgebracht werden. Der jeweilige lokale Bew{\"a}sserungsbedarf h{\"a}ngt von der Feldfrucht und deren Wachstumsphase, den Klimabedingungen, den Bodeneigenschaften und der Ausdehnung der Wurzelzone ab. Die Evapotranspiration ist als Komponente der regionalen Wasserbilanz eine wichtige Steuerungsgr{\"o}ße und Effizienzindikator f{\"u}r das lokale Bew{\"a}sserungsmanagement. Die Bew{\"a}sse-rungslandwirtschaft verbraucht weltweit etwa 70 \% der verf{\"u}gbaren S{\"u}ßwasservorkom-men. Dies wird als einer der Hauptgr{\"u}nde f{\"u}r die weltweit steigende Wasserknappheit identifiziert. Dabei liegt die Wasserentnahme des landwirtschaftlichen Sektors in den OECD Staaten im Mittel bei etwa 44 \%, in den Staaten Mittelasiens bei {\"u}ber 90 \%. Bei der Erstellung der vorliegenden Arbeit kam die Methode der residualen Bestimmung der Energiebilanz zum Einsatz. Eines der weltweit am h{\"a}ufigsten eingesetzten und vali-dierten fernerkundlichen Residualmodelle zur ET Ableitung ist das SEBAL-Modell (Surface Energy Balance Algorithm for Land, mit {\"u}ber 40 ver{\"o}ffentlichten Studien. SEBAL eignet sich zur Quantifizierung der Verdunstung großfl{\"a}chiger Gebiete und wurde bisher {\"u}ber-wiegend in der Bew{\"a}sserungslandwirtschaft eingesetzt. Aus diesen Gr{\"u}nden wurde es f{\"u}r die Bearbeitung der Fragestellungen in dieser Arbeit ausgew{\"a}hlt. SEBAL verwendet physikalische und empirische Beziehungen zur Berechnung der Energiebilanzkomponenten basierend auf Fernerkundungsdaten, bei gleichzeitig minimalem Einsatz bodengest{\"u}tzter Daten. Als Eingangsdaten werden u.a. Informationen {\"u}ber Strahlung, Bodenoberfl{\"a}chentemperatur, NDVI, LAI und Albedo verwendet. Zus{\"a}tzlich zu SEBAL wurden einige Komponenten der SEBAL Weiterentwicklung METRIC (Mapping Evapotranspiration with Internalized Calibration) verwendet, um die Modellierung der ET vorzunehmen. METRIC {\"u}berwindet einige Limitierungen des SEBAL Verfahrens und kann beispielsweise auch in st{\"a}rker reliefierten Regionen angewendet werden. Außerdem erm{\"o}glicht die Integration einer gebietsspezifischen Referenz-ET sowie einer Landnutzungsklassifikation eine bessere regionale Anpassung des Residualverfahrens. Unter der Annahme der Bedingungen zum Zeitpunkt der Fernerkundungsaufnahme ergibt sich die Energiebilanz an der Erdoberfl{\"a}che RN = LvE + H + G. Demnach teilt sich die verf{\"u}gbare Strahlungsenergie RN in die Komponenten latenter W{\"a}rme (LVE), f{\"u}hlbarer W{\"a}rme (H) und Bodenw{\"a}rme (G) auf. Durch Umstellen der Gleichung kann auf die latente W{\"a}rme geschlossen werden. Das wesentliche Ziel der vorliegenden Arbeit ist die Optimierung, Erweiterung und Validierung des ausgew{\"a}hlten SEBAL Verfahrens zur regionalen Modellierung der Energiebilanzkomponenten und der daraus abgeleiteten tats{\"a}chlichen Evapotranspiration. Die validierten Modellergebnisse der Gebietsverdunstung der Jahre 2009-2011 sollen anschließend als Grundlage dienen, das Gesamtverst{\"a}ndnis der regionalen Prozesse des Wasserkreislaufs zu verbessern. Die Arbeit basiert auf der Datengrundlage von MODIS Daten mit 1 km r{\"a}umlicher Aufl{\"o}sung. W{\"a}hrend die Komponenten verf{\"u}gbare Strahlungsenergie und f{\"u}hlbarer W{\"a}rmestrom physikalisch basiert ermittelt werden, beruht die Berechnung des Bodenw{\"a}rmestroms ausschließlich auf empirischen Absch{\"a}tzungen. Ein großer Nachteil des empirischen Ansatzes ist die Vernachl{\"a}ssigung des zeitlichen Versatzes zwischen Strahlungsbilanz und Bodenw{\"a}rmestrom in Abh{\"a}ngigkeit der aktuellen Bodenfeuchtesituation. Ein besonderer Schwerpunkt der vorliegenden Arbeit liegt auf der Bewertung und Verbesserung der Modellg{\"u}te des Bodenw{\"a}rmestroms durch Verwendung eines neuen Ansatzes zur Integration von Bodenfeuchteinformationen. Daher wird in der Arbeit ein physikalischer Ansatz entwickelt der auf dem Ansatz der periodischen Temperaturver{\"a}nderung basiert. Hierbei wurde neben dem ENVISAT ASAR SSM Produkt der TU Wien das operationelle Oberfl{\"a}chenbodenfeuchteprodukt ASCAT SSM als Fernerkundungseingangsdaten ausgew{\"a}hlt. Die mit SEBAL modellierten Energiebilanzkomponenten werden durch eine intensive Validierung mit bodengest{\"u}tzten Messungen bewertet, die Messungen stammen von Bodensensoren und Daten einer Eddy-Kovarianz-Station aus den Jahren 2009 bis 2011. Die Region Khorezm gilt als charakteristisch f{\"u}r die wasserbezogene Problematik der Bew{\"a}sserungslandwirtschaft Mittelasiens und wurde als Untersuchungsgebiet f{\"u}r diese Arbeit ausgew{\"a}hlt. Die wesentlichen Probleme dieser Region entstehen durch die nach wie vor nicht nachhaltige Land- und Wassernutzung, das marode Bew{\"a}sserungsnetz mit einer Verlustrate von bis zu 40 \% und der Bodenversalzung aufgrund hoher Grundwasserspiegel. Im Untersuchungsgebiet wurden in den Jahren 2010 und 2011 umfangreiche Feldarbeiten zur Erhebung lokaler bodengest{\"u}tzter Informationen durchgef{\"u}hrt. Bei der Evaluierung der modellierten Einzelkomponenten ergab sich f{\"u}r die Strahlungsbi-lanz eine hohe Modellg{\"u}te (R² > 0,9; rRMSE < 0,2 und NSE > 0,5). Diese Komponente bildet die Grundlage bei der Bezifferung der f{\"u}r die Prozesse an der Erdoberfl{\"a}che zur Verf{\"u}gung stehenden Energie. F{\"u}r die f{\"u}hlbaren W{\"a}rmestr{\"o}me wurden ebenfalls gute Ergebnisse erzielt, mit NSE von 0,31 und rRMSE von ca. 0,21. F{\"u}r die residual bestimmte Gr{\"o}ße der latenten W{\"a}rmestr{\"o}mung konnte eine insgesamt gute Modellg{\"u}te festgestellt werden (R² > 0,6; rRMSE < 0,2 und NSE > 0,5). Dementsprechend gut wurde die t{\"a}gliche Evapotranspiration modelliert. Hier ergab sich, nach der Interpolation t{\"a}glicher Werte, eine insgesamt ausreichend gute Modellg{\"u}te (R² > 0,5; rRMSE < 0,2 und NSE > 0,4). Dies best{\"a}tigt die Ergebnisse vieler Energiebilanzstudien, die lediglich den f{\"u}r die Ableitung der Evapotranspiration maßgebenden W{\"a}rmestrom untersuchten. Die Modellergebnisse f{\"u}r den Bodenw{\"a}rmestrom konnten durch die Entwicklung und Verwendung des neu entwickelten physikalischen Ansatzes von NSE < 0 und rRMSE von ca. 0,57 auf NSE von 0,19 und rRMSE von 0,35 verbessert werden. Dies f{\"u}hrt zu einer insgesamt positiven Einsch{\"a}tzung des Verbesserungspotenzials des neu entwickelten Bodenw{\"a}rmestromansatzes bei der Berechnung der Energiebilanz mit Hilfe von Fernerkundung.},
  subject      = {Evapotranspiration},
  language  = {de}
}