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- La rete di aree protette alpine (ALPARC) (1)
- Lehrstuhl für Fernerkundung der Uni Würzburg, in Kooperation mit dem Deutschen Fernerkundungsdatenzentrum (DFD) des Deutschen Zentrums für Luft- und Raumfahrt (DLR) (1)
- Leuphana Universität Lüneburg (1)
- Salzburger Institut für Raumordnung und Wohnen (1)
- Sonderforschungsbereich Re-Figuration von Räumen (Technische Universität Berlin) (1)
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- 227159 (1)
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- LIFE20 NAT/AT/000049 (1)
Das Ziel dieser Arbeit war neue Eingangsdaten für die Landoberflächenbeschreibung des regionalen Klimamodells REMO zu finden und ins Modell zu integrieren, um die Vorhersagequalität des Modells zu verbessern. Die neuen Daten wurden so in das Modell eingebaut, dass die bisherigen Daten weiterhin als Option verfügbar sind. Dadurch kann überprüft werden, ob und in welchem Umfang sich die von jedem Klimamodell benötigten Rahmendaten auf Modellergebnisse auswirken. Im Zuge der Arbeit wurden viele unterschiedliche Daten und Methoden zur Generierung neuer Parameter miteinander verglichen, denn neben dem Ersetzen der konstanten Eingangswerte für verschiedene Oberflächenparameter und den damit verbundenen Änderungen wurden als zusätzliche Verbesserung auch Veränderungen an der Parametrisierung des Bodens speziell in Hinblick auf die Bodentemperaturen in REMO vorgenommen. Im Rahmen dieser Arbeit wurden die durch die verschiedenen Änderungen ausgelösten Auswirkungen für das CORDEX-Gebiet EUR-44 mit einer Auflösung von ca. 50km und für das in dem darin eingebetteten neu definierten Deutschlandgebiet GER-11 mit einer Auflösung von ca. 12km getestet sowie alle Änderungen anhand von verschiedenen Beobachtungsdatensätzen validiert.
Die vorgenommenen Arbeiten gliederten sich in drei Hauptteile. Der erste Teil bestand in dem vom eigentlichen Klimamodell unabhängigen Vergleich der verschiedenen Eingangsdaten auf unterschiedlichen Auflösungen und deren Performanz in allen Teilen der Erde, wobei ein besonderer Fokus auf der Qualität in den späteren Modellgebieten lag. Unter Berücksichtigung der Faktoren, wie einer globalen Verfügbarkeit der Daten, einer verbesserten räumlichen Auflösung und einer kostenlosen Nutzung der Daten sowie verschiedener Validationsergebnissen von anderen Studien, wurden in dieser Arbeit vier neue Topographiedatensätze (SRTM, ALOS, TANDEM und ASTER) und drei neue Bodendatensätze (FAOn, Soilgrid und HWSD) für die Verwendung im Präprozess von REMO aufbereitet und miteinander sowie mit den bisher in REMO verwendeten Daten verglichen. Auf Grundlage dieser Vergleichsstudien schieden bei den Topographiedaten die verwendeten Datensatz-Versionen von SRTM, ALOS und TANDEM für die in dieser Arbeit durchgeführten REMO-Läufe aus. Bei den neuen Bodendatensätzen wurde ausgenutzt, dass diese verschiedenen Bodeneigenschaften für unterschiedliche Tiefen als Karten zur Verfügung stellen. In REMO wurden bisher alle benötigten Bodenparameter abhängig von fünf verschiedenen Bodentexturklassen und einer zusätzlichen Torfklasse ausgewiesen und als konstant über die gesamte Modellbodensäule (bis ca. 10m) angenommen. Im zweiten Teil wurden auf Basis der im ersten Teil ausgewählten neuen Datensätze und den neu verfügbaren Bodenvariablen verschiedene Sensitivitätsstudien über das Beispieljahr 2000 durchgeführt. Dabei wurden verschiedene neue Parametrisierungen für die bisher aus der Textur abgeleiteten Bodenvariablen und die Parametrisierung von weiteren hydrologischen und thermalen Bodeneigenschaften verglichen. Ferner wurde aufgrund der neuen nicht über die Tiefe konstanten Bodeneigenschaften eine neue numerische Methode zur Berechnung der Bodentemperaturen der fünf Schichten in REMO getestet, welche wiederum andere Anpassungen erforderte. Der Test und die Auswahl der verschiedenen Datensatz- und Parametrisierungsversionen auf die Modellperformanz wurde in drei Experimentpläne unterteilt. Im ersten Plan wurden die Auswirkungen der ausgewählten Topographie- und Bodendatensätze überprüft. Der zweite Plan behandelte die Unterschiede der verschiedenen Parametrisierungsarten der Bodenvariablen hinsichtlich der verwendeten Variablen zur Berechnung der Bodeneigenschaften, der über die Tiefe variablen oder konstanten Eigenschaften und der verwendeten Berechnungsmethode der Bodentemperaturänderungen. Durch die Erkenntnisse aus diesen beiden Experimentplänen, die für beide Untersuchungsgebiete durchgeführt wurden, ergaben sich im dritten Plan weitere Parametrisierungsänderungen. Alle Änderungen dieses dritten Experimentplans wurden sukzessiv getestet, sodass der paarweise Vergleich von zwei aufeinanderfolgenden Modellläufen die Auswirkungen der Neuerung im jeweils zweiten Lauf widerspiegelt. Der letzte Teil der Arbeit bestand aus der Analyse von fünf längeren Modellläufen (2000-2018), die zur Überprüfung der Ergebnisse aus den Sensitivitätsstudien sowie zur Einschätzung der Performanz in weiteren teilweise extremen atmosphärischen Bedingungen durchgeführt wurden. Hierfür wurden die bisherige Modellversion von REMO (id01) für die beiden Untersuchungsgebiete EUR-44 und GER-11 als Referenzläufe, zwei aufgrund der Vergleichsergebnisse von Experimentplan 3 selektierte Modellversionen (id06 und id15a für GER-11) sowie die finale Version (id18a für GER-11), die alle vorgenommenen Änderungen dieser Arbeit enthält, ausgewählt.
Es stellte sich heraus, dass sowohl die neuen Topographiedaten als auch die neuen Bodendaten große Differenzen zu den bisherigen Daten in REMO haben. Zudem änderten sich die von diesen konstanten Eingangsdaten abgeleiteten Hilfsvariablen je nach verwendeter Parametrisierung sehr deutlich. Dies war besonders gut anhand der Bodenparameter zu erkennen. Sowohl die räumliche Verteilung als auch der Wertebereich der verschiedenen Modellversionen unterschieden sich stark. Eine Einschätzung der Qualität der resultierenden Parameter wurde jedoch dadurch erschwert, dass auch die verschiedenen zur Validierung herangezogenen Bodendatensätze für diese Parameter deutlich voneinander abweichen. Die finale Modellversion id18a ähnelte trotz der umfassenden Änderungen in den meisten Variablen den Ergebnissen der bisherigen REMO-Version. Je nach zeitlicher und räumlicher Aggregation sowie unterschiedlichen Regionen und Jahreszeiten wurden leichte Verbesserungen, aber auch leichte Verschlechterungen im Vergleich zu den klimatologischen Validationsdaten festgestellt. Größere Veränderungen im Vergleich zur bisherigen Modellversion konnten in den tieferen Bodenschichten aufgezeigt werden, welche allerdings aufgrund von fehlenden Validationsdaten nicht beurteilt werden konnten. Für alle 2m-Temperaturen konnte eine tendenzielle leichte Erwärmung im Vergleich zum bisherigen Modelllauf beobachtet werden, was sich einerseits negativ auf die ohnehin durchschnittlich zu hohe Minimumtemperatur, aber andererseits positiv auf die bisher zu niedrige Maximumtemperatur des Modells in den betrachteten Gebieten auswirkte. Im Niederschlagssignal und in den 10m-Windvariablen konnten keine signifikanten Änderungen nachgewiesen werden, obwohl die neue Topographie an manchen Stellen im Modellgebiet deutlich von der bisherigen abweicht. Des Weiteren variierte das Ranking der verschiedenen Modellversionen jeweils nach dem angewendeten Qualitätsindex.
Um diese Ergebnisse besser einordnen zu können, muss berücksichtigt werden, dass die neuen Daten für Modellgebiete mit 50 bzw. 12km räumlicher Auflösung und der damit verbundenen hydrostatischen Modellversion getestet wurden. Zudem sind vor allem in Fall der Topographie die bisher enthaltenen GTOPO-Daten (1km Auflösung) für die Aggregation auf diese gröbere Modellauflösung geeignet. Die bisherigen Bodendaten stoßen jedoch mit 50km Auflösung bereits an ihre Grenzen. Zusätzlich ist zu beachten, dass nicht nur die Mittelwerte dieser Daten, sondern auch deren Subgrid-Variabilität als Variablen im Modell für verschiedene Parametrisierungen verwendet werden. Daher ist es essentiell, dass die Eingangsdaten eine deutlich höhere Auflösung bereitstellen als die zur Modellierung definierte Auflösung. Für lokale Klimasimulationen mit Auflösungen im niedrigen Kilometerbereich spielen auch die Vertikalbewegungen (nicht-hydrostatische Modellversion) eine wichtige Rolle, die stark von der Topographie sowie deren horizontaler und vertikaler Änderungsrate beeinflusst werden, was die in dieser Arbeit eingebauten wesentlich höher aufgelösten Daten für die zukünftige Weiterentwicklung von REMO wertvoll machen kann.
Open Spaces in Alpine Countries: Analytical Concepts and Preservation Strategies in Spatial Planning
(2020)
Open spaces in the Alps are becoming noticeably scarcer, and the long-term consequences for humans and the environment are often overlooked. Open spaces preserve ecosystem services but are under pressure in many Alpine valleys due to demographic and economic development as well as corresponding technical and tourism infrastructure. This article conceptualizes and measures open spaces in Alpine environments. In addition to analyzing existing spatial planning instruments and the open spaces resulting from 2 of them-the Bavarian Alpenplan in Germany and the Tyrolean Ruhegebiete in Austria-we identify open spaces in Switzerland using a geographic information system. More generally, we discuss how spatial planning deals with open spaces. Results show that both the Alpenplan and the Ruhegebiete have contributed significantly to the protection of open spaces in the Bavarian and Tyrolean Alps since the 1970s. Indeed, both approaches prevented several development projects. In the Swiss Alps, open spaces cover 41.9% of the Alpine Convention area. A share of 40.3% vegetation-free open spaces shows that they are concentrated in high alpine areas. Of the open spaces identified, 64.6% are covered by protected areas. Hence, about one third of the open spaces still existing in the Swiss Alps need preservation, not only for ecological connectivity reasons but also to preserve them for generations to come. We conclude that different sectoral approaches for the conservation of open spaces for people and natural heritage in the Alps and other high mountain ranges should be better coordinated. In addition, much more intensive crossborder cooperation in spatial development and planning is needed to preserve open spaces throughout the Alpine arc.
Episodic low oxygenated conditions on the sea-floor are likely responsible for exceptional preservation of animal remains in the upper Amouslek Formation (lower Cambrian, Stage 3) on the northern slope of the western Anti-Atlas, Morocco. This stratigraphic interval has yielded trilobite, brachiopod, and hyolith fossils with preserved soft parts, including some of the oldest known trilobite guts. The "Souss fossil lagerstatte" (newly proposed designation) represents the first Cambrian fossil lagerstatte in Cambrian strata known from Africa and is one of the oldest trilobite-bearing fossil lagerstatten on Earth. Inter-regional correlation of the Souss fossil lagerstatte in West Gondwana suggests its development during an interval of high eustatic levels recorded by dark shales that occur in informal upper Cambrian Series 2 in Siberia, South China, and East Gondwana.
Reliable near-surface soil moisture (θ) information is crucial for supporting risk assessment of future water usage, particularly considering the vulnerability of agroforestry systems of Mediterranean environments to climate change. We propose a simple empirical model by integrating dual-polarimetric Sentinel-1 (S1) Synthetic Aperture Radar (SAR) C-band single-look complex data and topographic information together with in-situ measurements of θ into a random forest (RF) regression approach (10-fold cross-validation). Firstly, we compare two RF models' estimation performances using either 43 SAR parameters (θNov\(^{SAR}\)) or the combination of 43 SAR and 10 terrain parameters (θNov\(^{SAR+Terrain}\)). Secondly, we analyze the essential parameters in estimating and mapping θ for S1 overpasses twice a day (at 5 a.m. and 5 p.m.) in a high spatiotemporal (17 × 17 m; 6 days) resolution. The developed site-specific calibration-dependent model was tested for a short period in November 2018 in a field-scale agroforestry environment belonging to the “Alento” hydrological observatory in southern Italy. Our results show that the combined SAR + terrain model slightly outperforms the SAR-based model (θNov\(^{SAR+Terrain}\) with 0.025 and 0.020 m3 m\(^{−3}\), and 89% compared to θNov\(^{SAR}\) with 0.028 and 0.022 m\(^3\) m\(^{−3}\, and 86% in terms of RMSE, MAE, and R2). The higher explanatory power for θNov\(^{SAR+Terrain}\) is assessed with time-variant SAR phase information-dependent elements of the C2 covariance and Kennaugh matrix (i.e., K1, K6, and K1S) and with local (e.g., altitude above channel network) and compound topographic attributes (e.g., wetness index). Our proposed methodological approach constitutes a simple empirical model aiming at estimating θ for rapid surveys with high accuracy. It emphasizes potentials for further improvement (e.g., higher spatiotemporal coverage of ground-truthing) by identifying differences of SAR measurements between S1 overpasses in the morning and afternoon.
Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients.
Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales.
Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5–10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements.
The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.
Impacts of climate variability and change on Maize (\(Zea\) \(mays\)) production in tropical Africa
(2022)
Climate change is undeniable and constitutes one of the major threats of the 21st century. It impacts sectors of our society, usually negatively, and is likely to worsen towards the middle and end of the century. The agricultural sector is of particular concern, for it is the primary source of food and is strongly dependent on the weather. Considerable attention has been given to the impact of climate change on African agriculture because of the continent’s high vulnerability, which is mainly due to its low adaptation capac- ity. Several studies have been implemented to evaluate the impact of climate change on this continent. The results are sometimes controversial since the studies are based on different approaches, climate models and crop yield datasets. This study attempts to contribute substantially to this large topic by suggesting specific types of climate pre- dictors. The study focuses on tropical Africa and its maize yield. Maize is considered to be the most important crop in this region. To estimate the effect of climate change on maize yield, the study began by developing a robust cross-validated multiple linear regression model, which related climate predictors and maize yield. This statistical trans- fer function is reputed to be less prone to overfitting and multicollinearity problems. It is capable of selecting robust predictors, which have a physical meaning. Therefore, the study combined: large-scale predictors, which were derived from the principal component analysis of the monthly precipitation and temperature; traditional local-scale predictors, mainly, the mean precipitation, mean temperature, maximum temperature and minimum temperature; and the Water Requirement Satisfaction Index (WRSI), derived from the specific crop (maize) water balance model. The projected maize-yield change is forced by a regional climate model (RCM) REMO under two emission scenarios: high emission scenario (RCP8.5) and mid-range emission scenario (RCP4.5). The different effects of these groups of predictors in projecting the future maize-yield changes were also assessed. Furthermore, the study analysed the impact of climate change on the global WRSI. The results indicate that almost 27 % of the interannual variability of maize production of the entire region is explained by climate variables. The influence of climate predictors on maize-yield production is more pronounced in West Africa, reaching 55 % in some areas. The model projection indicates that the maize yield in the entire region is expected to decrease by the middle of the century under an RCP8.5 emission scenario, and from the middle of the century to the end of the century, the production will slightly recover but will remain negative (around -10 %). However, in some regions of East Africa, a slight increase in maize yield is expected. The maize-yield projection under RCP4.5 remains relatively unchanged compared to the baseline period (1982-2016). The results further indicate that large-scale predictors are the most critical drivers of the global year-to-year maize-yield variability, and ENSO – which is highly correlated with the most important predictor (PC2) – seems to be the physical process underlying this variability. The effects of local predictors are more pronounced in the eastern parts of the region. The impact of the future climate change on WRSI reveals that the availability of maize water is expected to decrease everywhere, except in some parts of eastern Africa.
Die imperiale Lebensweise westlicher Industrienationen, die sich durch ein permanentes Streben nach Wirtschaftswachstum ausdrückt, bringt den Planeten an die Grenzen seiner Tragfähigkeit. In den letzten Jahren wurden jedoch – bestärkt durch die Weltwirtschaftskrise 2007/08 – Alternativen zum Modell des permanenten Wachstums immer populärer, die sich anstatt auf ökonomischen Wohlstand vermehrt auf soziale und ökologische Belange des gesellschaftlichen Zusammenlebens fokussierten. Unter dem Begriff der Postwachstumsbewegung sammelten sich Ansätze, Ideen und Akteure, die gemeinsam für eine Zukunft fernab jeglicher Wachstumszwänge und innerhalb der planetaren Grenzen kämpfen.
Vor dem Hintergrund der zunehmenden sozialen und ökologischen Herausforderungen wurden nun erstmals sozial-ökologische Nischenakteure aus drei unterschiedlichen Bereichen der Postwachstumsbewegung gemeinsam in einem Forschungsvorhaben – unter besonderer Berücksichtigung gesellschaftlicher, organisatorischer und territorialer Einbettungsprozesse – untersucht. Eingebettet ist diese Untersuchung in den theoretisch-konzeptionellen Ansatz der sozial-ökologischen Transformation, deren inkrementeller Wandel mithilfe der Multi-Level-Perspektive beschrieben werden kann. Die Kombination dieses spezifischen theoretisch-konzeptionellen Ansatzes und der empirischen Erhebung ist das Alleinstellungsmerkmal der vorliegenden Untersuchung.
Es zeigte sich, dass alle untersuchten Nischenakteure eine deutlich progressive Unternehmungsphilosophie vertreten, die häufig in einer Unternehmungsorganisation mit flachen Hierarchien und konsensbasierten Entscheidungsfindungen mündet. Besonders gesellschaftliche Einbettungsprozesse bedingen den Erfolg oder Misserfolg der Nischenentwicklung. Organisatorische Einbettung kommt derweil vor allem im Aufbau weitreichender Netzwerkstrukturen zum Tragen, die die Innovationsfähigkeit und Stabilität der Nische unterstützen. Eine starke territoriale Einbettung steigert den lokal-regionalen Einfluss der Nischeninnovationen und generiert Rückhalt in der Bevölkerung.
Forest systems provide crucial ecosystem functions to our environment, such as balancing carbon stocks and influencing the local, regional and global climate. A trend towards an increasing frequency of climate change induced extreme weather events, including drought, is hereby a major challenge for forest management. Within this context, the application of remote sensing data provides a powerful means for fast, operational and inexpensive investigations over large spatial scales and time. This study was dedicated to explore the potential of satellite data in combination with harmonic analyses for quantifying the vegetation response to drought events in German forests. The harmonic modelling method was compared with a z-score standardization approach and correlated against both, meteorological and topographical data. Optical satellite imagery from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used in combination with three commonly applied vegetation indices. Highest correlation scores based on the harmonic modelling technique were computed for the 6th harmonic degree. MODIS imagery in combination with the Normalized Difference Vegetation Index (NDVI) generated hereby best results for measuring spectral response to drought conditions. Strongest correlation between remote sensing data and meteorological measures were observed for soil moisture and the self-calibrated Palmer Drought Severity Index (scPDSI). Furthermore, forests regions over sandy soils with pine as the dominant tree type were identified to be particularly vulnerable to drought. In addition, topographical analyses suggested mitigated drought affects along hill slopes. While the proposed approaches provide valuable information about vegetation dynamics as a response to meteorological weather conditions, standardized in-situ measurements over larger spatial scales and related to drought quantification are required for further in-depth quality assessment of the used methods and data.
"Die Innenstadt braucht den Handel, der Handel aber nicht die Innenstadt", lautet eine oft formulierte These bezüglich des Verhältnisses 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 überdachten Auseinandersetzung über das Verhältnis von Innenstadt und Einzelhandel. Neben Fragen zur zukünftigen Gestaltung des Einzelhandels und seiner Bedeutung für Innenstädte, sind auch Fragen zur Bedeutung anderer Branchen/Einrichtungen/Angebote (z.B. Gastronomie, Handwerk, Kultureinrichtungen, Kitas, Sport- und Bildungseinrichtungen, aber auch Freiräume, Grünflächen, verkehrsberuhigte Bereiche oder lokale Kurierdienste) für den Einzelhandel vermehrt aus Perspektive der geographischen Handelsforschung zu beantworten. Mit der Krise wurden Defizite und Handlungsfelder in den Blick gerückt, deren Bearbeitung schon lange ansteht. Die Chance liegt darin, diesen Aufmerksamkeitsschub konstruktiv zu nutzen und realistische fall- und standortspezifische Perspektiven für Innenstädte und ihre Akteur*innen jetzt zu verhandeln und nicht weiter auf die lange Bank zu schieben. Der vorliegende Band vereint neun handelsgeographische Beiträge von Wissenschaftler*innen und Praktiker*innen, die die Auswirkungen der Covid-19-Pandemie erörtern und damit einen wichtigen Beitrag für die notwendige Diskussion der Zukunft von Innenstädten und Handel leisten.
This study examines the relationship between variations of the Southern Annular Mode (SAM) and black carbon (BC) at 550 nm aerosol optical depth (AOD) in the Western Cape province (WC). Variations of the positive (negative) phase of the SAM are found to be related to regional circulation types (CTs) in southern Africa, associated with suppressed (enhanced) westerly wind over the WC through the southward (northward) migration of Southern Hemisphere mid-latitude cyclones. The CTs related to positive (negative) SAM anomalies induce stable (unstable) atmospheric conditions over the southwestern regions of the WC, especially during the austral winter and autumn seasons. Through the control of CTs, positive (negative) SAM phases tend to contribute to the build-up (dispersion and dilution) of BC in the study region because they imply dry (wet) conditions which favor the build-up (washing out) of pollutant particles in the atmosphere. Indeed, recent years with an above-average frequency of CTs related to positive (negative) SAM anomalies are associated with a high (low) BC AOD over southwesternmost Africa.
Sacred water canals or lakes, which provided water for all kinds of purification rites and other activities, were very specific and important features of temples in ancient Egypt. In addition to the longer-known textual record, preliminary geoarchaeological surveys have recently provided evidence of a sacred canal at the Temple of Bastet at Bubastis. In order to further explore the location, shape, and course of this canal and to find evidence of the existence of a second waterway, also described by Herodotus, 34 drillings and five 2D geoelectrical measurements were carried out in 2019 and 2020 near the temple. The drillings and 2D ERT surveying revealed loamy to clayey deposits with a thickness of up to five meters, most likely deposited in a very low energy fluvial system (i.e., a canal), allowing the reconstruction of two separate sacred canals both north and south of the Temple of Bastet. In addition to the course of the canals, the width of about 30 m fits Herodotus’ description of the sacred waterways. The presence of numerous artefacts proved the anthropogenic use of the ancient canals, which were presumably connected to the Nile via a tributary or canal located west or northwest of Bubastis.
Background
Breast cancer (BC), which is most common in elderly women, requires a multidisciplinary and continuous approach to care. With demographic changes, the number of patients with chronic diseases such as BC will increase. This trend will especially hit rural areas, where the majority of the elderly live, in terms of comprehensive health care.
Methods
Accessibility to several cancer facilities in Bavaria, Germany, was analyzed with a geographic information system. Facilities were identified from the national BC guideline and from 31 participants in a proof‐of‐concept study from the Breast Cancer Care for Patients With Metastatic Disease registry. The timeframe for accessibility was defined as 30 or 60 minutes for all population points. The collection of address information was performed with different sources (eg, a physician registry). Routine data from the German Census 2011 and the population‐based Cancer Registry of Bavaria were linked at the district level.
Results
Females from urban areas (n = 2,938,991 [ie, total of females living in urban areas]) had a higher chance for predefined accessibility to the majority of analyzed facilities in comparison with females from rural areas (n = 3,385,813 [ie, total number of females living in rural areas]) with an odds ratio (OR) of 9.0 for cancer information counselling, an OR of 17.2 for a university hospital, and an OR of 7.2 for a psycho‐oncologist. For (inpatient) rehabilitation centers (OR, 0.2) and genetic counselling (OR, 0.3), women from urban areas had lower odds of accessibility within 30 or 60 minutes.
Conclusions
Disparities in accessibility between rural and urban areas exist in Bavaria. The identification of underserved areas can help to inform policymakers about disparities in comprehensive health care. Future strategies are needed to deliver high‐quality health care to all inhabitants, regardless of residence.
Park−People Relationships: The Socioeconomic Monitoring of National Parks in Bavaria, Germany
(2021)
Questions about park–people relationships and the understanding and handling of the conflicts that may result from the creation and management of national parks in the surrounding area are prerequisites for both successful park management and sustainable rural tourism development. This paper analyzes the roles that research may play in relation to park–people relationships in the context of the two oldest German national parks located in Bavaria. The different fields of action of national parks are used to identify the potential for conflict, using detailed case studies from the Bavarian Forest and Berchtesgaden National Parks using quantitative population surveys carried out in 2018. The overall attitude towards both national parks is overwhelmingly positive, with trust towards park administrations and the perceived economic benefits from rural tourism being the attitudes most strongly correlated to the overall level of park–people relationships. Nevertheless, some points of contention still exist, like the ecological integrity approach towards strict nature conservation and related landscape changes (e.g., deadwood cover). A comparison over time shows in both cases that the spatial proximity to the protected area negatively influences people’s attitudes towards the parks, but less so than in the past. Recommendations for national park management include communicating proactively and with greater transparency with locals and decision-makers, to identify conflicts earlier and, where possible, to eliminate them. Furthermore, developing a standardized method to monitor park–people relationships in Germany is a must and would benefit integrated approaches in research and management based on conservation social science.
Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands.
This study investigates circulation types (CTs) in Africa, south of the equator, that are related to wet and dry conditions in the Western Cape, the statistical relationship between the selected CTs and the Southern Annular Mode (SAM), and changes in the frequency of occurrence of the CTs related to the SAM under the ssp585 scenario. Obliquely rotated principal component analysis applied to sea level pressure (SLP) was used to classify CTs in Africa, south of the equator. Three CTs were found to have a high probability of being associated with wet days in the Western Cape, and four CTs were equally found to have a high probability of being associated with dry days in the Western Cape. Generally, the dry/wet CTs feature the southward/northward track of the mid-latitude cyclone, adjacent to South Africa; anti-cyclonic/cyclonic relative vorticity, and poleward/equatorward track of westerlies, south of South Africa. One of the selected wet CTs was significantly related to variations of the SAM. Years with an above-average SAM index correlated with the below-average frequency of occurrences of the wet CT. The results suggest that through the dynamics of the CT, the SAM might control the rainfall variability of the Western Cape. Under the ssp585 scenario, the analyzed climate models indicated a possible decrease in the frequency of occurrence of the aforementioned wet CT associated with cyclonic activity in the mid-latitudes, and an increase in the frequency of the occurrence of CT associated with enhanced SLP at mid-latitudes.
Strategies in Times of Pandemic Crisis — Retailers and Regional Resilience in Würzburg, Germany
(2021)
Research on the COVID-19 crisis and its implications on regional resilience is still in its infancy. To understand resilience on its aggregate level it is important to identify (non)resilient actions of individual actors who comprise regions. As the retail sector among others represents an important factor in an urban regions recovery, we focus on the resilience of (textile) retailers within the city of Würzburg in Germany to the COVID-19 pandemic. To address the identified research gap, this paper applies the concept of resilience. Firstly, conducting expert interviews, the individual (textile) retailers’ level and their strategies in coping with the crisis is considered. Secondly, conducting a contextual analysis of the German city of Würzburg, we wish to contribute to the discussion of how the resilience of a region is influenced inter alia by actors. Our study finds three main strategies on the individual level, with retailers: (1) intending to “bounce back” to a pre-crisis state, (2) reorganising existing practices, as well as (3) closing stores and winding up business. As at the time of research, no conclusions regarding long-term impacts and resilience are possible, the results are limited. Nevertheless, detailed analysis of retailers’ strategies contributes to a better understanding of regional resilience.
Grasslands cover one third of the earth’s terrestrial surface and are mainly used for livestock production. The usage type, use intensity and condition of grasslands are often unclear. Remote sensing enables the analysis of grassland production and management on large spatial scales and with high temporal resolution. Despite growing numbers of studies in the field, remote sensing applications in grassland biomes are underrepresented in literature and less streamlined compared to other vegetation types. By reviewing articles within research on satellite-based remote sensing of grassland production traits and management, we describe and evaluate methods and results and reveal spatial and temporal patterns of existing work. In addition, we highlight research gaps and suggest research opportunities. The focus is on managed grasslands and pastures and special emphasize is given to the assessment of studies on grazing intensity and mowing detection based on earth observation data. Grazing and mowing highly influence the production and ecology of grassland and are major grassland management types. In total, 253 research articles were reviewed. The majority of these studies focused on grassland production traits and only 80 articles were about grassland management and use intensity. While the remote sensing-based analysis of grassland production heavily relied on empirical relationships between ground-truth and satellite data or radiation transfer models, the used methods to detect and investigate grassland management differed. In addition, this review identified that studies on grassland production traits with satellite data often lacked including spatial management information into the analyses. Studies focusing on grassland management and use intensity mostly investigated rather small study areas with homogeneous intensity levels among the grassland parcels. Combining grassland production estimations with management information, while accounting for the variability among grasslands, is recommended to facilitate the development of large-scale continuous monitoring and remote sensing grassland products, which have been rare thus far.
This study compares the performance of the five widely used crop growth models (CGMs): World Food Studies (WOFOST), Coalition for Environmentally Responsible Economies (CERES)-Wheat, AquaCrop, cropping systems simulation model (CropSyst), and the semi-empiric light use efficiency approach (LUE) for the prediction of winter wheat biomass on the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site, Germany. The study focuses on the use of remote sensing (RS) data, acquired in 2015, in CGMs, as they offer spatial information on the actual conditions of the vegetation. Along with this, the study investigates the data fusion of Landsat (30 m) and Moderate Resolution Imaging Spectroradiometer (MODIS) (500 m) data using the spatial and temporal reflectance adaptive reflectance fusion model (STARFM) fusion algorithm. These synthetic RS data offer a 30-m spatial and one-day temporal resolution. The dataset therefore provides the necessary information to run CGMs and it is possible to examine the fine-scale spatial and temporal changes in crop phenology for specific fields, or sub sections of them, and to monitor crop growth daily, considering the impact of daily climate variability. The analysis includes a detailed comparison of the simulated and measured crop biomass. The modelled crop biomass using synthetic RS data is compared to the model outputs using the original MODIS time series as well. On comparison with the MODIS product, the study finds the performance of CGMs more reliable, precise, and significant with synthetic time series. Using synthetic RS data, the models AquaCrop and LUE, in contrast to other models, simulate the winter wheat biomass best, with an output of high R2 (>0.82), low RMSE (<600 g/m\(^2\)) and significant p-value (<0.05) during the study period. However, inputting MODIS data makes the models underperform, with low R2 (<0.68) and high RMSE (>600 g/m\(^2\)). The study shows that the models requiring fewer input parameters (AquaCrop and LUE) to simulate crop biomass are highly applicable and precise. At the same time, they are easier to implement than models, which need more input parameters (WOFOST and CERES-Wheat).
The detrimental impacts of climate variability on water, agriculture, and food resources in East Africa underscore the importance of reliable seasonal climate prediction. To overcome this difficulty RARIMAE method were evolved. Applications RARIMAE in the literature shows that amalgamating different methods can be an efficient and effective way to improve the forecasts of time series under consideration. With these motivations, attempt have been made to develop a multiple linear regression model (MLR) and a RARIMAE models for forecasting seasonal rainfall in east Africa under the following objectives:
1. To develop MLR model for seasonal rainfall prediction in East Africa.
2. To develop a RARIMAE model for seasonal rainfall prediction in East Africa.
3. Comparison of model's efficiency under consideration
In order to achieve the above objectives, the monthly precipitation data covering the period from 1949 to 2000 was obtained from Climate Research Unit (CRU). Next to that, the first differenced climate indices were used as predictors.
In the first part of this study, the analyses of the rainfall fluctuation in whole Central- East Africa region which span over a longitude of 15 degrees East to 55 degrees East and a latitude of 15 degrees South to 15 degrees North was done by the help of maps. For models’ comparison, the R-squared values for the MLR model are subtracted from the R-squared values of RARIMAE model. The results show positive values which indicates that R-squared is improved by RARIMAE model. On the other side, the root mean square errors (RMSE) values of the RARIMAE model are subtracted from the RMSE values of the MLR model and the results show negative value which indicates that RMSE is reduced by RARIMAE model for training and testing datasets.
For the second part of this study, the area which is considered covers a longitude of 31.5 degrees East to 41 degrees East and a latitude of 3.5 degrees South to 0.5 degrees South. This region covers Central-East of the Democratic Republic of Congo (DRC), north of Burundi, south of Uganda, Rwanda, north of Tanzania and south of Kenya. Considering a model constructed based on the average rainfall time series in this region, the long rainfall season counts the nine months lead of the first principal component of Indian sea level pressure (SLP_PC19) and the nine months lead of Dipole Mode Index (DMI_LR9) as selected predictors for both statistical and predictive model. On the other side, the short rainfall season counts the three months lead of the first principal component of Indian sea surface temperature (SST_PC13) and the three months lead of Southern Oscillation Index (SOI_SR3) as predictors for predictive model. For short rainfall season statistical model SAOD current time series (SAOD_SR0) was added on the two predictors in predictive model. By applying a MLR model it is shown that the forecast can explain 27.4% of the total variation and has a RMSE of 74.2mm/season for long rainfall season while for the RARIMAE the forecast explains 53.6% of the total variation and has a RMSE of 59.4mm/season. By applying a MLR model it is shown that the forecast can explain 22.8% of the total variation and has a RMSE of 106.1 mm/season for short rainfall season predictive model while for the RARIMAE the forecast explains 55.1% of the total variation and has a RMSE of 81.1 mm/season.
From such comparison, a significant rise in R-squared, a decrease of RMSE values were observed in RARIMAE models for both short rainfall and long rainfall season averaged time series. In terms of reliability, RARIMAE outperformed its MLR counterparts with better efficiency and accuracy. Therefore, whenever the data suffer from autocorrelation, we can go for MLR with ARIMA error, the ARIMA error part is more to correct the autocorrelation thereby improving the variance and productiveness of the model.
The natural cyclical development of palsas makes it difficult to use visible signs of decay as reference points for environmental change. Thus, to determine the actual development stage of a palsa, investigations of the internal structure are crucial. Our study presents 2‐D and 3‐D electrical resistivity imaging (ERI) and 2‐D ground‐penetrating radar (GPR) results, measurements of surface and subsurface temperatures, and of the soil matric potential from Orravatnsrústir Palsa Site in Central Iceland. By a joint interpretation of the results, we deduce the internal structure (i.e., thickness of thaw zone and permafrost, ice/water content) of five palsas of different size and shape. The results differentiate between initial and mature development stages and show that palsas of different development stages can exist in close proximity. While internal characteristics indicate undisturbed development of four palsas, one palsa shows indications of environmental change. Our study shows the value of the multimethod geophysical approach and introduces measurements of the soil matric potential as a promising method to assess the current state of the subsurface.
In vielen mediterranen Küstenniederungen entstand seit 1950 infolge von Gebirgsentvölkerung, Infrastrukturausbau, neuer Gewerbe sowie illegaler Bautätigkeit ein fast lückenloses Verstädterungsband. Am Golf von Neapel konnte dieser Landschaftswandel über eine lange Zeit beobachtet und durch zahlreiche Vergleichsfotos, Kartierungen, Luft- und Satellitenbilder und Interviews dokumentiert werden. Horst-Günter Wagner zeigt in diesem Band die Veränderungen der Küstenebene und erläutert ihre Ursachen.
In den letzten drei Jahrzehnten expandierten Supermarktketten aus dem Globalen Norden in Länder des Globalen Südens. Insbesondere Länder mit einem raschen wirtschaftlichen Wachstum und damit neuen Marktpotentialen waren dabei Expansionsziele. Zugleich zeigt sich innerhalb der Länder des Globalen Südens eine Ausbreitung von regionalen Supermarktketten. Mittlerweile gehört frisches Obst und Gemüse fast immer zum Sortiment dieser Einzelhandelsunternehmen.
Bisher untersuchte eine Reihe von Studien die Auswirkungen der Kooperation mit den Einzelhändlern auf die landwirtschaftlichen Produzierenden. Weniger ist dagegen bekannt, welche Liefersysteme und Intermediäre für die Verbindung zwischen landwirtschaftlichen Produzierenden und Supermarktketten in Ländern des Globalen Südens bestehen und sich entwickeln. Insbesondere für leicht verderbliche Frischeprodukte (Obst und Gemüse) ist die Herausbildung dieser Intermediäre eine große Herausforderung. Die vorliegende Studie betrachtet den Zusammenhang zwischen der räumlichen und zeitlichen Ausbreitung von Supermärkten und der Etablierung von Liefersystemen sowie Intermediären am Beispiel von Kenia und Tansania.
The Antarctic Ice Sheet stores ~91% of the global ice volume which is equivalent to a sea-level rise of 58.3 meters. Recent disintegration events of ice shelves and retreating glaciers along the Antarctic Peninsula and West Antarctica indicate the current vulnerable state of the Antarctic Ice Sheet. Glacier tongues and ice shelves create a safety band around Antarctica with buttressing effects on ice discharge. Current decreases in glacier and ice shelf extent reduce the effective buttressing forces and increase ice discharge of grounded ice. The consequence is a higher contribution to sea-level rise from the Antarctic Ice Sheet. So far, it is unresolved which proportion of Antarctic glacier retreat can be attributed to climate change and which part to the natural cycle of growth and decay in the lifetime of a glacier. The quantitative assessment of the magnitude, spatial extent, distribution, and dynamics of circum-Antarctic glacier and ice shelf retreat is of utmost importance to monitor Antarctica’s weakening safety band. In remote areas like Antarctica, earth observation provides optimal properties for large-scale mapping and monitoring of glaciers and ice shelves. Nowadays, the variety of available satellite sensors, technical advancements regarding spatial resolution and revisit times, as well as open satellite data archives create an ideal basis for monitoring calving front change. A systematic review conducted within this thesis revealed major gaps in the availability of glacier and ice shelf front position measurements despite the improved satellite data availability. The previously limited availability of satellite imagery and the time-consuming manual delineation of calving fronts did neither allow a circum-Antarctic assessment of glacier retreat nor the assessment of intra-annual changes in glacier front position. To advance the understanding of Antarctic glacier front change, this thesis presents a novel automated approach for calving front extraction and explores drivers of glacier retreat.
A comprehensive review of existing methods for glacier front extraction ascertained the lack of a fully automatic approach for large-scale monitoring of Antarctic calving fronts using radar imagery. Similar backscatter characteristics of different ice types, seasonally changing backscatter values, multi-year sea ice, and mélange made it challenging to implement an automated approach with traditional image processing techniques. Therefore, the present abundance of satellite data is best exploited by integrating recent developments in big data and artificial intelligence (AI) research to derive circum-Antarctic calving front dynamics. In the context of this thesis, the novel AI-based framework “AntarcticLINES” (Antarctic Glacier and Ice Shelf Front Time Series) was created which provides a fully automated processing chain for calving front extraction from Sentinel-1 imagery. Open access Sentinel-1 radar imagery is an ideal data source for monitoring current and future changes in the Antarctic coastline with revisit times of less than six days and all-weather imaging capabilities. The developed processing chain includes the pre-processing of dual-polarized Sentinel-1 imagery for machine learning applications. 38 Sentinel-1 scenes were used to train the deep learning architecture U-Net for image segmentation. The trained weights of the neural network can be used to segment Sentinel-1 scenes into land ice and ocean. Additional post-processing ensures even more accurate results by including morphological filtering before extracting the final coastline. A comprehensive accuracy assessment has proven the correct extraction of the coastline. On average, the automatically extracted coastline deviates by 2-3 pixels (93 m) from a manual delineation. This accuracy is in range with deviations between manually delineated coastlines from different experts.
For the first time, the fully automated framework AntarcticLINES enabled the extraction of intra-annual glacier front fluctuations to assess seasonal variations in calving front change. Thereby, for example, an increased calving frequency of Pine Island Glacier and a beginning disintegration of Glenzer Glacier were revealed. Besides, the extraction of the entire Antarctic coastline for 2018 highlighted the large-scale applicability of the developed approach. Accurate results for entire Antarctica were derived except for the Western Antarctic Peninsula where training imagery was not sufficient and should be included in future studies.
Furthermore, this dissertation presents an unprecedented record of circum-Antarctic calving front change over the last two decades. The newly extracted coastline for 2018 was compared to previous coastline products from 2009 and 1997. This revealed that the Antarctic Ice Sheet shrank 29,618±1193 km2 in extent between 1997-2008 and gained an area of 7,108±1029 km2 between 2009-2018. Glacier retreat concentrated along the Antarctic Peninsula and West Antarctica. The only East Antarctic coastal sector primarily experiencing calving front retreat was Wilkes Land in 2009-2018. Finally, potential drivers of circum-Antarctic glacier retreat were identified by combining data on glacier front change with changes in climate variables. It was found that strengthening westerlies, snowmelt, rising sea surface temperatures, and decreasing sea ice cover forced glacier retreat over the last two decades. Relative changes in mean air temperature could not be identified as a driver for glacier retreat and further investigations on extreme events in air temperature are necessary to assess the effect of atmospheric forcing on frontal retreat. The strengthening of all identified drivers was closely connected to positive phases of the Southern Annular Mode (SAM). With increasing greenhouse gases and ozone depletion, positive phases of SAM will occur more often and force glacier retreat even further in the future.
Within this thesis, a comprehensive review on existing Antarctic glacier and ice shelf front studies was conducted revealing major gaps in Antarctic calving front records. Therefore, a fully automated processing chain for glacier and ice shelf front extraction was implemented to track circum-Antarctic calving front fluctuations on an intra-annual basis. The large-scale applicability was certified by presenting two decades of circum-Antarctic calving front change. In combination with climate variables, drivers of recent glacier retreat were identified. In the future, the presented framework AntarcticLINES will greatly contribute to the constant monitoring of the Antarctic coastline under the pressure of a changing climate.
Pre‐Klondikean oxidation prepared the ground for Broken Hill‐type mineralization in South Africa
(2021)
New Cu isotope data obtained on chalcopyrite from the Black Mountain and the Broken Hill deposits in the medium‐ to high‐grade metamorphic Aggeneys‐Gamsberg ore district (South Africa) require a revision of our understanding of the genesis of metamorphic Broken Hill‐type massive sulphide deposits. Chalcopyrite from both deposits revealed unusually wide ranges in δ\(^{65}\)Cu (−2.41 to 2.84‰ NIST 976 standard) in combination with distinctly positive mean values (0.27 and 0.94‰, respectively). This is interpreted to reflect derivation from various silicate and oxide precursor minerals in which Cu occurred in higher oxidation states. Together with the observation of a typical supergene base metal distribution within the deposits and their spatial association with an unconformity only meters above the ore horizon, our new data are best explained by supergene oxidation of originally possibly SEDEX deposits prior to metamorphic sulphide formation, between the Okiepian (1,210–1,180 Ma) and Klondikean (1,040–1,020 Ma) orogenic events.
Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-
temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total
number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented.
New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.)and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet)will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.
Maize cropping systems mapping using RapidEye observations in agro-ecological landscapes in Kenya
(2017)
Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer’s accuracy and UA: user’s accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10–20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.
Statistical modeling of phenology in Bavaria based on past and future meteorological information
(2020)
Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961–1990).
The new ellipsocephaloid trilobite species Kingaspidoides spinirecurvatus has a spectacular morphology because of a unique set of two long and anteriorly recurved spines on the occipital ring and the axial ring of thoracic segment 8. Together with the long genal spines this whimsical dorsally directed spine arrangement is thought to act as a non-standard protective device against predators. This is illustrated by the body posture during different stages of enrolment, contrasting with the more sophisticated spinosities seen in later trilobites, which are discussed in brief. Kingaspidoides spinirecurvatus from the lower–middle Cambrian boundary interval of the eastern Anti-Atlas in Morocco has been known for about two decades, with specimens handled as precious objects on the fossil market. Similar, but far less spectacular, spine arrangements on the thoracic axial rings are known from other ellipsocephaloid trilobites from the Anti-Atlas of Morocco and the Franconian Forest region of Germany. This suggests that an experimental phase of spine development took place within the Kingaspi-doides clade during the early–middle Cambrian boundary interval.
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.
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 Fabérgé 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.
Mapping buried paleogeographical features of the Nile Delta (Egypt) using the Landsat archive
(2020)
The contribution highlights the use of Landsat spectral-temporal metrics (STMs) for the detection of surface anomalies that are potentially related to buried near-surface paleogeomorphological deposits in the Nile Delta (Egypt), in particular for a buried river branch close to Buto. The processing was completed in the Google Earth Engine (GEE) for the entire Nile Delta and for selected seasons of the year (summer/winter) using Landsat data from 1985 to 2019. We derived the STMs of the tasseled cap transformation (TC), the Normalized Difference Wetness Index (NDWI), and the Normalized Difference Vegetation Index (NDVI). These features were compared to historical topographic maps of the Survey of Egypt, CORONA imagery, the digital elevation model of the TanDEM-X mission, and modern high-resolution satellite imagery. The results suggest that the extent of channels is best revealed when differencing the median NDWI between summer (July/August) and winter (January/February) seasons (ΔNDWI). The observed difference is likely due to lower soil/plant moisture during summer, which is potentially caused by coarser-grained deposits and the morphology of the former levee. Similar anomalies were found in the immediate surroundings of several Pleistocene sand hills (“geziras”) and settlement mounds (“tells”) of the eastern delta, which allowed some mapping of the potential near-surface continuation. Such anomalies were not observed for the surroundings of tells of the western Nile Delta. Additional linear and meandering ΔNDWI anomalies were found in the eastern Nile Delta in the immediate surroundings of the ancient site of Bubastis (Tell Basta), as well as several kilometers north of Zagazig. These anomalies might indicate former courses of Nile river branches. However, the ΔNDWI does not provide an unambiguous delineation.
Visualizing movement data is challenging: While traditional spatial data can be sufficiently displayed as two‐dimensional plots or maps, movement trajectories require the representation of time in a third dimension. To address this, we present moveVis, an R package, which provides tools to animate movement trajectories, overlaying simultaneous uni‐ or multi‐temporal raster imagery or vector data.
moveVis automates the processing of movement and environmental data to turn such into an animation. This includes (a) the regularization of movement trajectories enforcing uniform time instances and intervals across all trajectories, (b) the frame‐wise mapping of movement trajectories onto temporally static or dynamic environmental layers, (c) the addition of customizations, for example, map elements or colour scales and (d) the rendering of frames into an animation encoded as GIF or video file.
moveVis is designed to display interactions and concurrencies of animal movement and environmental data. We present examples and use cases, ranging from data exploration to visualizing scientific findings.
Static spatial plots of movement data disregard the temporal dimension that distinguishes movement from other spatial data. In contrast, animations allow to display relocation in both time and space. We deem animations a powerful way to visually explore movement data, frame analytical findings and display potential interactions with spatially continuous and temporally dynamic environmental covariates.
Städte sehen sich in der Entwicklung ihres Einzelhandelsangebots zunehmend Konkurrenzsituationen zwischen traditionellen Innenstadt- und neu entstehenden Stadtrandlagen ausgesetzt, die einerseits die gestiegenen Flächen- und Produktivitätsansprüche der Unternehmen eher erfüllen, während andererseits Bürger, Politik und etablierter Handel ein ‚Aussterben’ der Innenstädte befürchten. Die Konsequenzen planerischer Entscheidungen in dieser Hinsicht abzuschätzen, wird zunehmend komplexer. Dafür sind ebenso eine stärkere Individualisierung des Konsumverhaltens verantwortlich, wie eine gestiegene Sensibilität gegenüber Verkehrs- und Emissionsbelastungen. Modellierungen und Simulationen können einen Beitrag zu fundierter Entscheidungsfindung leisten, indem sie durch Prognosen von Szenarien mit unterschiedlichen Rahmenbedingungen solche Auswirkungen aufzeigen.
In der Vergangenheit wurden Kaufkraftströme durch Modelle abgebildet, die auf aggregierten Ausgangsdaten und Analogieschlüssen zu Naturgesetzen (Gravitations-, Potenzialansatz) oder nutzentheoretischen Annahmen (Diskreter Entscheidungsansatz) beruhten. In dieser Arbeit wird dafür erstmals ein agentenbasierter Ansatz angewendet, da sich so individuelle Ausdifferenzierungen des Konsumentenhandelns wesentlich leichter integrieren und Ergebnisse anschaulicher präsentieren lassen. Ursprünglich entstammt die Idee zur Agententechnologie einem Forschungsfeld der Informatik, der Künstlichen Intelligenz. Ziel war hier, Algorithmen zu entwickeln, die aus einer Menge von kleinen Softwarebausteinen bestehen, die zur Lösung eines Problems miteinander in Kommunikation treten und sich selbst zielbezogen anordnen. Somit schreibt sich der Algorithmus im Grunde selbst. Dieses Konzept kann in den Sozialwissenschaften als Modellierungsparadigma genutzt werden, insofern als dass sie der Idee der Selbstorganisation von Gesellschaften recht nahe kommt. Insbesondere zeichnen sich Multiagentensysteme durch eine dezentrale Kontrolle und Datenvorhaltung aus, die es darüber hinaus ermöglichen, auch komplexe Systeme von Entscheidungsprozessen mit wenigen Spezifikationen darzustellen. Damit begegnet der Agentenansatz vielen Einwänden gegen Analogie- und Entscheidungsmodelle. Durch die konsequente Einnahme einer individuenbezogenen Sichtweise ist die individuelle Ausdifferenzierung von Entscheidungsprozessen viel eher abbildbar.
Für das Forschungsprojekt konnten für einenm ntersuchungsraum in Nordschweden (Funktionalregion Umeå, ca. 140.000 Einwohner) individuenbezogene Einwohnerdaten verfügbar gemacht werden. Diese enthielten u.a. Lagekoordinaten des Wohn- und Arbeitsorts, Alter, Geschlecht, verfügbares Einkommen und Angaben zur Haushaltsstruktur. Verbunden mit Erkenntnissen aus empirischen Untersuchungen (Konsumentenbefragung, Geschäftskartierung) stellten sie die Eingabegrößen für ein agentenbasiertes Modell der Einkaufsstättenwahl bei der Lebensmittelversorgung dar. Die Konsumentenbefragung stellte regressionsanalytische Abhängigkeiten zwischen sozioökonomischen Daten und Konsumpräferenzen bezüglich einzelner Geschäftsattribute (Preisniveau, Produktqualität, Sortimentsbreite, Service etc.) her, die gleichen Attribute wurden für die Geschäfte erhoben. Somit können Kaufkraftströme zwischen Einzelelementen der Nachfrage (individuelle Konsumenten) und des Angebots (einzelne Geschäftsstandorte) als individuell variierende Bewertung der Geschäfte durch die Agenten dargestellt werden, gemäß derer die Agenten ihre lebensmittelrelevante Kaufkraft auf die Geschäfte verteilen.
Für die Geschäfte der gesamten Region konnten Gütemaßwerte bis 0,7 erreicht werden, für einzelne Betriebsformate auch über 0,9. Dies zeigt, dass auch bei der Verwendung individuenbezogener Modelle, die mit einer deutlich höheren Anzahl Freiheitsgraden behaftet sind als ihre aggregierten Gegenstücke, hohe Prognosequalitäten für Umsatzschätzungen von Standorten erreicht werden können. Gleichzeitig bietet der Agentenansatz die Möglichkeit, einzelne Simulationsobjekte bei ihrer Entscheidungsfindung und ihren Aktivitäten zu verfolgen. Dabei konnten ebenfalls plausible Einkaufsmuster abgebildet werden.
Da die Distanz vom Wohn- bzw. Arbeitsort zum Geschäft Bestandteil des Modells ist, können auch die von den Einwohnern zum Zweck der Grundversorgung zu leistenden Distanzaufwände in verschiedenen Angebotssituationen analysiert werden. Als Fallstudie wurde ein Vergleich von zwei Situationen 1997 und 2004 vorgenommen. Während dieses Zeitraums haben im Untersuchungsgebiet grundlegende Veränderungen der Einzelhandelsstruktur stattgefunden, die zu einem weitgehenden Rückzug des Angebots aus den peripheren ländlichen Gebieten geführt haben. Die Ergebnisse zeigteneine hohe Übereinstimmung mit den auf nationaler Ebene erhobenen Mobilitätsdaten, ließen aber auch einen differenzierten Blick auf die unterschiedliche Betroffenheit der Einwohner der Region zu.
An agentenbasierte Simulationen werden in den Sozialwissenschaften große Erwartungen geknüpft, da sie erstmals ermöglichen, gesellschaftliche Phänomene auf der Ebene ihres Zustandekommens, dem Individuum, zu erfassen, sowie komplexe mentale Vorgänge des Handelns, Lernens und Kommunizierens auf einfache Weise in ein Modell zu integrieren. Mit der vorliegenden Arbeit wurde im Bereich der Konsumentenforschung erstmals ein solcher Ansatz auf regionaler Ebene angewendet, um zu planungsrelevanten Aussagen zu gelangen. In Kombination mit anderen Anwendungen im Bereich der Bevölkerungsprognose, des Verkehrs und der innerstädtischen Migration haben Agentensimulationen alle Voraussetzungen zu einem zukunftsweisenden Paradigma für die Raum- und Fachplanung.
Das Erbe der deutschen Kolonialzeit in Namibia im Fokus des "Tourist Gaze" deutscher Touristen
(2009)
Die Studie beschäftigt sich mit der Wahrnehmung des deutschen Kolonialerbes in Namibia aus Sicht deutscher Touristen. Namibia ist das Land in Afrika welches die stärkste Durchdringung mit Elementen der deutschen Kolonialzeit aufweist. Darüber hinaus zeichnet sich dieses Land durch eine sehr hohe touristische Bedeutung des deutschen Quellmarktes aus. Weiterhin ist die gemeinsame koloniale Vergangenheit weder bilateral noch innerhalb Namibias aufgearbeitet, was der Thematik eine gesellschaftspolitische Komponente verleiht.
Die Analyse der touristischen Wahrnehmung basiert auf 103 qualitativen Interviews mit deutschen Touristen in Namibia. Neben der Perspektive der Reisenden werden Akteure untersucht, welche den ‚Blick‘ der Touristen lenken und beeinflussen. Dabei kommen eine Inhaltsanalyse von deutschsprachiger Reiseliteratur sowie teilnehmende Beobachtungen bei Stadtführungen mit lokalen Reiseleitern in der Stadt zum Einsatz.
Die Resultate zeigen, dass die Touristen das Erbe der deutschen Kolonialzeit als sehr heterogenes Phänomen interpretieren. Durch das Aufsummieren der vielfältigen Erfahrungen mit gelebtem und gebautem Kolonialerbe wird die Wahrnehmung geographisch wirksam, da die Eindrücke auf Räume und Menschen übertragen werden und nicht auf punktuellen Elementen verharren. Aufgrund von Unterdrückung und Verbrechen in der Kolonialzeit sehen die befragten Touristen das deutsche Erbe in Namibia als ein ‚schwieriges’ an, das kaum nostalgische Gefühle auslöst, sondern eher zu einer kritischen Auseinandersetzung mit der Geschichte anregt. Der Grad dieser Dissonanz ist stark davon abhängig, in wie weit die koloniale Thematik nach Ansicht der Touristen in aktuellem Bezug steht oder aber als nicht mehr relevante Vergangenheit interpretiert wird.
Neben der ‚Dissonanz’ können die Touristen anhand der beiden weiteren Indikatoren ‚Interesse’ – im Sinne einer Auseinandersetzung und Informiertheit – sowie ‚Attraktion‘ – als touristische Bedeutung – typologisiert werden. Die entscheidende Determinante für die Charakterisierung der Befragten stellt das Maß der empfundenen Dissonanz dar. Weiterhin lässt sich eine Differenzierung in Touristen mit einer vorbereiteten und organisierten und solche mit einer unvorbereiteten und spontanen Konfrontation mit dem deutschen Erbe vornehmen. Insgesamt können fünf Typen – ‚klassische Heritage-Touristen’, ‚spontane Heritage-Touristen, ‚Kritiker’, ‚historische motivierte Touristen’ und ‚Sightseeing-Touristen’ – identifiziert werden, wobei den drei erstgenannten eine Wahrnehmung als ‚schwieriges’, dissonantes Erbe immanent ist.
Mit der vorliegenden Arbeit werden konventionelle thermische Kraftwerke an deutschen Flüssen identifiziert, bei denen aufgrund hoher Flusswassertemperaturen im Zusammenhang mit wasserrechtlichen Grenzwerten Leistungseinschränkungen auftraten. Weiterhin wird aufgezeigt, wie sich die Wassertemperaturen der Flüsse in der Vergangenheit (rezent) entwickelt haben und wie sie sich zukünftig im Kontext des Klimawandels entwickeln könnten.
Mittels Literaturrecherche, Medienanalyse und schriftlicher Befragung wurden konventionelle thermische Kraftwerke identifiziert, welche wassertemperaturbedingte Leistungseinschränkungen verzeichneten. Die meisten dieser Leistungseinschränkungen zwischen 1976 und 2007 zeigen sich bei großen Kraftwerken mit einer elektrischen Bruttoleistung über 300 Megawatt, bei Steinkohle- und Kernkraftwerken, bei Kraftwerken mit Durchlaufkühlung und bei solchen, die zwischen 1960 und 1990 in Betrieb gingen.
Trendanalysen interpolierter und homogenisierter, rezenter Wassertemperaturzeitreihen deutscher Flüsse ergeben positive Trends v. a. im Frühjahr und Sommer. Die Zählstatistik zeigt in den Jahren 1994, 2003 und 2006 die meisten Tage mit sehr hohen und extrem hohen Wassertemperaturen in den Sommermonaten. In diesen Jahren traten gleichzeitig 63 % aller identifizierter wassertemperaturbedingter Leistungseinschränkungen bei Kraftwerken, meist zwischen Juni und August, auf.
Für die Trendanalysen und den Mittelwertvergleich simulierter zukünftiger Wassertemperaturzeitreihen wurden drei Szenarien – B1, A1B und A2 sowie drei Zukunftsperioden 2011-2040, 2011/2041-2070, 2011/2071-2100 betrachtet. Es ergeben sich für die Zukunftsperiode 2011-2040 des A1B- oder A2-Szenarios in mindestens einem der Sommermonate eine Erwärmung und für das B1-Szenario negative oder keine Trends. Die mittleren Wassertemperaturen der Zukunftsperiode 2011-2040 zeigen in allen drei Szenarien gegenüber denen der Klimanormalperiode 1961-1990 positive Unterschiede in mindestens einem der Sommermonate. Für die beiden späteren Zukunftsperioden bis 2070 bzw. bis 2100 liegen in allen Wassertemperaturzeitreihen der drei Szenarien im Sommer positive Trends bzw. Differenzen gegenüber den mittleren Wassertemperaturen der Klimanormalperiode vor.
Durch die Synthese der drei Analysen ist erkennbar, dass Isar, Rhein, Neckar, Saar, Elbe und Weser die meisten Kraftwerksstandorte mit wassertemperaturbedingten Leistungseinschränkungen verzeichnen. Es zeigen sich hier positive Trends sowohl in den rezenten als auch zukünftigen Wassertemperaturen für die Zukunftsperiode 2011-2040 des A1B- und A2-Szenarios in jeweils mindestens einem der Sommermonate. Gegenüber den mittleren Wassertemperaturen der Klimanormalperiode liegen für alle drei Szenarien positive Unterschiede der Wassertemperaturen vor.
Bei einer Kraftwerkslaufzeit von 40-50 Jahren und einem Kernenergieausstieg 2022 bzw. 2034, werden 48-64 % bzw. 67-91 % der Kraftwerke mit wassertemperaturbedingten Leistungseinschränkungen bis 2022 bzw. 2034 außer Betrieb gehen. Bei einer Laufzeitverlängerung würden nach 2022 fünf der elf betroffenen Kernkraftwerke weiter am Netz bleiben. Somit kann es wieder zu wassertemperaturbedingten Leistungseinschränkungen kommen. In Deutschland sind nach wie vor große Kraftwerke an Flüssen geplant. Deren Kühlsysteme müssen entsprechend ausgewählt und konstruiert werden, um der zu erwartenden Erhöhung der Flusstemperaturen Rechnung zu tragen.
Detailed information on the land cover types present and the horizontal position of the land–water interface is needed for sensitive coastal ecosystems throughout the Arctic, both to establish baselines against which the impacts of climate change can be assessed and to inform response operations in the event of environmental emergencies such as oil spills. Previous work has demonstrated potential for accurate classification via fusion of optical and SAR data, though what contribution either makes to model accuracy is not well established, nor is it clear what shorelines can be classified using optical or SAR data alone. In this research, we evaluate the relative value of quad pol RADARSAT-2 and Landsat 5 data for shoreline mapping by individually excluding both datasets from Random Forest models used to classify images acquired over Nunavut, Canada. In anticipation of the RADARSAT Constellation Mission (RCM), we also simulate and evaluate dual and compact polarimetric imagery for shoreline mapping. Results show that SAR data is needed for accurate discrimination of substrates as user’s and producer’s accuracies were 5–24% higher for models constructed with quad pol RADARSAT-2 and DEM data than models constructed with Landsat 5 and DEM data. Models based on simulated RCM and DEM data achieved significantly lower overall accuracies (71–77%) than models based on quad pol RADARSAT-2 and DEM data (80%), with Wetland and Tundra being most adversely affected. When classified together with Landsat 5 and DEM data, however, model accuracy was less affected by the SAR data type, with multiple polarizations and modes achieving independent overall accuracies within a range acceptable for operational mapping, at 89–91%. RCM is expected to contribute positively to ongoing efforts to monitor change and improve emergency preparedness throughout the Arctic.
Monitoring the spatio-temporal development of vegetation is a challenging task in heterogeneous and cloud-prone landscapes. No single satellite sensor has thus far been able to provide consistent time series of high temporal and spatial resolution for such areas. In order to overcome this problem, data fusion algorithms such as the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) have been established and frequently used in recent years to generate high-resolution time series. In order to make it applicable to larger scales and to increase the input data availability especially in cloud-prone areas, an ESTARFM framework was developed in this study introducing several enhancements. An automatic filling of cloud gaps was included in the framework to make best use of available, even partly cloud-covered Landsat images. Furthermore, the ESTARFM algorithm was enhanced to automatically account for regional differences in the heterogeneity of the study area. The generation of time series was automated and the processing speed was accelerated significantly by parallelization. To test the performance of the developed ESTARFM framework, MODIS and Landsat-8 data were fused for generating an 8-day NDVI time series for a study area of approximately 98,000 km\(^{2}\) in West Africa. The results show that the ESTARFM framework can accurately produce high temporal resolution time series (average MAE (mean absolute error) of 0.02 for the dry season and 0.05 for the vegetative season) while keeping the spatial detail in such a heterogeneous, cloud-prone region. The developments introduced within the ESTARFM framework establish the basis for large-scale research on various geoscientific questions related to land degradation, changes in land surface phenology or agriculture
The internal structures of a moraine complex mostly provide information about the manner in which they develop and thus they can transmit details about several processes long after they have taken place. While the occurrence of glacier–permafrost interactions during the formation of large thrust moraine complexes at polar and subpolar glaciers as well as at marginal positions of former ice sheets has been well understood, their role in the formation of moraines on comparatively small alpine glaciers is still very poorly investigated. Therefore, the question arises as to whether evidence of former glacier–permafrost interactions can still be found in glacier forefields of small alpine glaciers and to what extent these differ from the processes in finer materials at larger polar or subpolar glaciers. To investigate this, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) surveys were carried out in the area of a presumed alpine thrust moraine complex in order to investigate internal moraine structures. The ERT data confirmed the presence of a massive ice core within the central and proximal parts of the moraine complex. Using GPR, linear internal structures were detected, which were interpreted as internal shear planes due to their extent and orientation. These shear planes lead to the assumption that the moraine complex is of glaciotectonic origin. Based on the detected internal structures and the high electrical resistivity values, it must also be assumed that the massive ice core is of sedimentary or polygenetic origin. The combined approach of the two methods enabled the authors of this study to detect different internal structures and to deduce a conceptual model of the thrust moraine formation.
West African summer monsoon precipitation is characterized by distinct decadal variability. Due to its welldocumented link to oceanic boundary conditions in various ocean basins it represents a paradigm for decadal predictability. In this study, we reappraise this hypothesis for several sub-regions of sub-Saharan West Africa using the new German contribution to the coupled model intercomparison project phase 5 (CMIP5) near-term prediction system.
In addition, we assume that dynamical downscaling of the global decadal predictions leads to an enhanced predictive skill because enhanced resolution improves the atmospheric response to oceanic forcing and landsurface feedbacks. Based on three regional climate models, a heterogeneous picture is drawn: none of the regional climate models outperforms the global decadal predictions or all other regional climate models in every region nor decade. However, for every test case at least one regional climate model was identified which outperforms the global predictions. The highest predictive skill is found in the western and central Sahel Zone with correlation coefficients and mean-square skill scores exceeding 0.9 and 0.8, respectively.
Burkina Faso ranges amongst the fastest growing countries in the world with an annual population growth rate of more than three percent. This trend has consequences for food security since agricultural productivity is still on a comparatively low level in Burkina Faso. In order to compensate for the low productivity, the agricultural areas are expanding quickly. The mapping and monitoring of this expansion is difficult, even on the basis of remote sensing imagery, since the extensive farming practices and frequent cloud coverage in the area make the delineation of cultivated land from other land cover and land use types a challenging task. However, as the rapidly increasing population could have considerable effects on the natural resources and on the regional development of the country, methods for improved mapping of LULCC (land use and land cover change) are needed. For this study, we applied the newly developed ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) framework to generate high temporal (8-day) and high spatial (30 m) resolution NDVI time series for all of Burkina Faso for the years 2001, 2007, and 2014. For this purpose, more than 500 Landsat scenes and 3000 MODIS scenes were processed with this automated framework. The generated ESTARFM NDVI time series enabled extraction of per-pixel phenological features that all together served as input for the delineation of agricultural areas via random forest classification at 30 m spatial resolution for entire Burkina Faso and the three years. For training and validation, a randomly sampled reference dataset was generated from Google Earth images and based on expert knowledge. The overall accuracies of 92% (2001), 91% (2007), and 91% (2014) indicate the well-functioning of the applied methodology. The results show an expansion of agricultural area of 91% between 2001 and 2014 to a total of 116,900 km\(^2\). While rainfed agricultural areas account for the major part of this trend, irrigated areas and plantations also increased considerably, primarily promoted by specific development projects. This expansion goes in line with the rapid population growth in most provinces of Burkina Faso where land was still available for an expansion of agricultural area. The analysis of agricultural encroachment into protected areas and their surroundings highlights the increased human pressure on these areas and the challenges of environmental protection for the future.
Rice is an important food crop and a large producer of green-house relevant methane. Accurate and timely maps of paddy fields are most important in the context of food security and greenhouse gas emission modelling. During their life-cycle, rice plants undergo a phenological development that influences their interaction with waves in the visible light and infrared spectrum. Rice growth has a distinctive signature in time series of remotely-sensed data. We used time series of MODIS (Moderate Resolution Imaging Spectroradiometer) products MOD13Q1 and MYD13Q1 and a one-class support vector machine to detect these signatures and classify paddy rice areas in continental China. Based on these classifications, we present a novel product for continental China that shows rice areas for the years 2002, 2005, 2010 and 2014 at 250-m resolution. Our classification has an overall accuracy of 0.90 and a kappa coefficient of 0.77 compared to our own reference dataset for 2014 and correlates highly with rice area statistics from China’s Statistical Yearbooks (R2 of 0.92 for 2010, 0.92 for 2005 and 0.90 for 2002). Moderate resolution time series analysis allows accurate and timely mapping of rice paddies over large areas with diverse cropping schemes.
Availability of water and desiccation of important water reservoirs is a vital challenge in semi-arid to arid climates with growing economy and population. Low quantities of precipitation and high evaporation rates leave the water supply vulnerable to human activity and climatic variations. Endorheic basins of Northern Iran were hydrologically landlocked within geological timescales and thus bear evidence of past variations of water resources in generations of water related landforms, like abandoned lake level shorelines, alluvial fans and stream terraces. Understanding the development of these landforms reveals crucial information about past water reservoirs and landscape history.
This study offers a comprehensive approach on understanding the geomorphological development of the landscape throughout Late Pleistocene and Holocene times. It integrates remote sensing and geographic information system analysis, with geomorphological and stratigraphical mapping fieldwork and detailed sedimentological investigations.
The work shows the importance of analytical geomorphological mapping for delineating stratigraphic units of the Iranian Quaternary. Thus, several phases of drying and lake level retreat were identified in parallel geoarchives and could be dated to a time span from today to Late Pleistocene. The findings link the fate of the citizens of the ancient city of "Tepe Hissar" to their access to water and to the power of geomorphological processes, which started changing their environment.
In recent years, the midlatitudes are characterized by more intense heatwaves in summer and sometimes severe cold spells in winter that might emanate from changes in atmospheric circulation, including synoptic‐scale and planetary wave activity in the midlatitudes. In this study, we investigate the heat and momentum exchange between the mean flow and atmospheric waves in the North Atlantic sector and adjacent continents by means of the physically consistent Eliassen–Palm flux diagnostics applied to reanalysis and forced climate model data. In the long‐term mean, momentum is transferred from the mean flow to atmospheric waves in the northwest Atlantic region, where cyclogenesis prevails. Further downstream over Europe, eddy fluxes return momentum to the mean flow, sustaining the jet stream against friction. A global climate model is able to reproduce this pattern with high accuracy. Atmospheric variability related to atmospheric wave activity is much more expressed at the intraseasonal rather than the interannual time‐scale. Over the last 40 years, reanalyses reveal a northward shift of the jet stream and a weakening of intraseasonal weather variability related to synoptic‐scale and planetary wave activity. This pertains to the winter and summer seasons, especially over central Europe, and correlates with changes in the North Atlantic Oscillation as well as regional temperature and precipitation. A very similar phenomenon is found in a climate model simulation with business‐as‐usual scenario, suggesting an anthropogenic trigger in the weakening of intraseasonal weather variability in the midlatitudes.
Nach aktuellem Stand der Forschung ist die Dachbegrünung eine geeignete Klimaanpassungsmaßnahme, mit der die Folgen des rezenten Klimawandels in verdichteten und versiegelten Stadtgebieten abgeschwächt werden können. Vor dem Hintergrund schrumpfender Flächenreserven und wachsender Flächenkonkurrenz können auf Dächern alternative Flächenressourcen zur Expansion urbanen Grüns erschlossen werden. Zudem besitzt diese Begrünungsart vielfältige ökologische und ökonomische Vorteile (Kühlwirkung, Biodiversität, Wasserrückhaltung, Gebäudedämmung und -schutz). Mit Bebauungsplänen und Innenbereichssatzungen sowie Förderprogrammen und indirekter Förderung (gesplittete Abwassergebühren) stehen den Kommunen harte und weiche Instrumente zur Verfügung, um Gebäudeeigentümer für Dachbegrünungsmaßnahmen im Neubau, aber auch im Bestandsbau zu mobilisieren. Für eine Aktivierung bereits bestehender Dachflächen eignet sich besonders die Extensivbegrünung dank ihrer anspruchslosen Vegetation, des minimalen Pflegeaufwands sowie den geringeren statischen und formspezifischen Anforderungen an die Dachkonstruktion gegenüber der Intensivbegrünung. Auf Basis von Untersuchungen mit Fernerkundungsdaten und amtlichen Geodaten konnten für deutsche Groß- und Mittelstädte enorme Flächenpotentiale für die nachträgliche Dachbegrünung festgestellt werden. Zur Stadt Würzburg, in der als Hotspot des Klimawandels eine hohe Dringlichkeit für Klimaanpassungsmaßnahmen besteht, lagen bis dato keine Daten zu diesem Potential vor. Im Rahmen dieser Arbeit wurden Luftbilder, Höhendaten (LiDAR) und amtliche Gebäudeumriss-Daten in einem Geoinformationssystem (GIS) zu einer dreidimensionalen Dachlandschaft verarbeitet, hinsichtlich relevanter Begrünungskriterien (Neigung, Homogenität, Größe, Funktion) analysiert und in Form von Karten, Bildern und Statistiken ausgegeben. Für das konkrete Untersuchungsgebiet der stadtklimatisch besonders kritischen Stadtbezirke Altstadt und Sanderau konnte eine empirische Grundlage zur Quantifizierung der Potentialfläche geschaffen werden. Rund ein Drittel der über 5.000 untersuchten innerstädtischen Dächer kommen mit einer Fläche von über 300.000 m² für eine nachträgliche Begrünung in Betracht. Zudem wurden Aussagen zur städtebaulichen Qualifizierung (Denkmalschutz) dieser Flächen getroffen und die Aktivierbarkeit mit dem einschlägigen stadtplanerischem Begrünungsinstrumentarium (Förderprogramm, Satzung bzw. Bebauungsplan) bewertet. So konnten die für die Umsetzung der geeigneten Dachflächen nötigen Förderkosten auf Basis der geltenden Förderrichtlinie approximiert werden. Zudem wurde unter Verwendung amtlicher Baustatistik und einschlägiger Bebauungspläne ein zeitlicher Horizont geschätzt, bis zu welchem sich Eigentümer an die Vorgaben einer hypothetischen Dachbegrünungssatzung anpassen würden. Die Arbeit bietet Anreize für die Methodik geoinformatischer Analysen sowie für städteplanerische Analyse- und Handlungsmöglichkeiten. Natürlich kann die fernerkundliche Messung keine bautechnische Begutachtung vor Ort ersetzen, sie kann aber im Vorfeld einen Eindruck der teils versteckten Flächenreserven kostengünstig und flächendeckend verschaffen und zudem die Möglichkeit darauf aufbauender Untersuchungen der ökologischen oder städtebaulichen Wirkung eröffnen.
Sea level rise contribution from the Antarctic ice sheet is influenced by changes in glacier and ice shelf front position. Still, little is known about seasonal glacier and ice shelf front fluctuations as the manual delineation of calving fronts from remote sensing imagery is very time-consuming. The major challenge of automatic calving front extraction is the low contrast between floating glacier and ice shelf fronts and the surrounding sea ice. Additionally, in previous decades, remote sensing imagery over the often cloud-covered Antarctic coastline was limited. Nowadays, an abundance of Sentinel-1 imagery over the Antarctic coastline exists and could be used for tracking glacier and ice shelf front movement. To exploit the available Sentinel-1 data, we developed a processing chain allowing automatic extraction of the Antarctic coastline from Seninel-1 imagery and the creation of dense time series to assess calving front change. The core of the proposed workflow is a modified version of the deep learning architecture U-Net. This convolutional neural network (CNN) performs a semantic segmentation on dual-pol Sentinel-1 data and the Antarctic TanDEM-X digital elevation model (DEM). The proposed method is tested for four training and test areas along the Antarctic coastline. The automatically extracted fronts deviate on average 78 m in training and 108 m test areas. Spatial and temporal transferability is demonstrated on an automatically extracted 15-month time series along the Getz Ice Shelf. Between May 2017 and July 2018, the fronts along the Getz Ice Shelf show mostly an advancing tendency with the fastest moving front of DeVicq Glacier with 726 ± 20 m/yr.
This study investigates synthetic aperture radar (SAR) time series of the Sentinel-1 mission acquired over the Atacama Desert, Chile, between March 2015 and December 2018. The contribution analyzes temporal and spatial variations of Sentinel-1 interferometric SAR (InSAR) coherence and exemplarily illustrates factors that are responsible for observed signal differences. The analyses are based on long temporal baselines (365–1090 days) and temporally dense time series constructed with short temporal baselines (12–24 days). Results are compared to multispectral data of Sentinel-2, morphometric features of the digital elevation model (DEM) TanDEM-X WorldDEM™, and to a detailed governmental geographic information system (GIS) dataset of the local hydrography. Sentinel-1 datasets are suited for generating extensive, nearly seamless InSAR coherence mosaics covering the entire Atacama Desert (>450 × 1100 km) at a spatial resolution of 20 × 20 meter per pixel. Temporal baselines over several years lead only to very minor decorrelation, indicating a very high signal stability of C-Band in this region, especially in the hyperarid uplands between the Coastal Cordillera and the Central Depression. Signal decorrelation was associated with certain types of surface cover (e.g., water or aeolian deposits) or with actual surface dynamics (e.g., anthropogenic disturbance (mining) or fluvial activity and overland flow). Strong rainfall events and fluvial activity in the periods 2015 to 2016 and 2017 to 2018 caused spatial patterns with significant signal decorrelation; observed linear coherence anomalies matched the reference channel network and indicated actual episodic and sporadic discharge events. In the period 2015–2016, area-wide loss of coherence appeared as strip-like patterns of more than 80 km length that matched the prevailing wind direction. These anomalies, and others observed in that period and in the period 2017–2018, were interpreted to be caused by overland flow of high magnitude, as their spatial location matched well with documented heavy rainfall events that showed cumulative precipitation amounts of more than 20 mm.
Air temperatures in the Arctic have increased substantially over the last decades, which has extensively altered the properties of the land surface. Capturing the state and dynamics of Land Surface Temperatures (LSTs) at high spatial detail is of high interest as LST is dependent on a variety of surficial properties and characterizes the land–atmosphere exchange of energy. Accordingly, this study analyses the influence of different physical surface properties on the long-term mean of the summer LST in the Arctic Mackenzie Delta Region (MDR) using Landsat 30 m-resolution imagery between 1985 and 2018 by taking advantage of the cloud computing capabilities of the Google Earth Engine. Multispectral indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Tasseled Cap greenness (TCG), brightness (TCB), and wetness (TCW) as well as topographic features derived from the TanDEM-X digital elevation model are used in correlation and multiple linear regression analyses to reveal their influence on the LST. Furthermore, surface alteration trends of the LST, NDVI, and NDWI are revealed using the Theil-Sen (T-S) regression method. The results indicate that the mean summer LST appears to be mostly influenced by the topographic exposition as well as the prevalent moisture regime where higher evapotranspiration rates increase the latent heat flux and cause a cooling of the surface, as the variance is best explained by the TCW and northness of the terrain. However, fairly diverse model outcomes for different regions of the MDR (R2 from 0.31 to 0.74 and RMSE from 0.51 °C to 1.73 °C) highlight the heterogeneity of the landscape in terms of influential factors and suggests accounting for a broad spectrum of different factors when modeling mean LSTs. The T-S analysis revealed large-scale wetting and greening trends with a mean decadal increase of the NDVI/NDWI of approximately +0.03 between 1985 and 2018, which was mostly accompanied by a cooling of the land surface given the inverse relationship between mean LSTs and vegetation and moisture conditions. Disturbance through wildfires intensifies the surface alterations locally and lead to significantly cooler LSTs in the long-term compared to the undisturbed surroundings.
Periglacial environments are facing dramatic changes. Warming air temperatures and strong snow cover variations fundamentally affect landforming processes in this hotspot region of Climate Change. But before we can assess the response of landform development to a changing climate, we need to enhance our understanding of the internal structure of those landforms. Within this study, a broad scope of landform types from alpine and subarctic regions is investigated: rock glaciers, solifluction lobes, palsas and patterned ground. By using the geophysical methods 2-D and 3-D ERI, as well as GPR surveying, structural differences and similarities between landform units of different or the same landform types are highlighted. This enables a reconstruction of their past and a projection of their future development.
We analyze the processing of cereals and its role at Early Neolithic Göbekli Tepe, southeastern Anatolia (10th / 9th millennium BC), a site that has aroused much debate in archaeological discourse. To date, only zooarchaeological evidence has been discussed in regard to the subsistence of its builders. Göbekli Tepe consists of monumental round to oval buildings, erected in an earlier phase, and smaller rectangular buildings, built around them in a partially contemporaneous and later phase. The monumental buildings are best known as they were in the focus of research. They are around 20 m in diameter and have stone pillars that are up to 5.5 m high and often richly decorated. The rectangular buildings are smaller and–in some cases–have up to 2 m high, mostly undecorated, pillars. Especially striking is the number of tools related to food processing, including grinding slabs/bowls, handstones, pestles, and mortars, which have not been studied before. We analyzed more than 7000 artifacts for the present contribution. The high frequency of artifacts is unusual for contemporary sites in the region. Using an integrated approach of formal, experimental, and macro- / microscopical use-wear analyses we show that Neolithic people at Göbekli Tepe have produced standardized and efficient grinding tools, most of which have been used for the processing of cereals. Additional phytolith analysis confirms the massive presence of cereals at the site, filling the gap left by the weakly preserved charred macro-rests. The organization of work and food supply has always been a central question of research into Göbekli Tepe, as the construction and maintenance of the monumental architecture would have necessitated a considerable work force. Contextual analyses of the distribution of the elements of the grinding kit on site highlight a clear link between plant food preparation and the rectangular buildings and indicate clear delimitations of working areas for food production on the terraces the structures lie on, surrounding the circular buildings. There is evidence for extensive plant food processing and archaeozoological data hint at large-scale hunting of gazelle between midsummer and autumn. As no large storage facilities have been identified, we argue for a production of food for immediate use and interpret these seasonal peaks in activity at the site as evidence for the organization of large work feasts.
The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.