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Sonstige beteiligte Institutionen
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- ALPARC - The Alpine Network of Protected Areas (2)
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- 243964 (1)
- 776019 (1)
- 818182 (1)
- 834709 (1)
- LIFE12 BIO/AT/000143 (1)
- LIFE20 NAT/AT/000049 (1)
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.