TY - JOUR A1 - Uereyen, Soner A1 - Kuenzer, Claudia T1 - A review of earth observation-based analyses for major river basins JF - Remote Sensing N2 - Regardless of political boundaries, river basins are a functional unit of the Earth’s land surface and provide an abundance of resources for the environment and humans. They supply livelihoods supported by the typical characteristics of large river basins, such as the provision of freshwater, irrigation water, and transport opportunities. At the same time, they are impacted i.e., by human-induced environmental changes, boundary conflicts, and upstream–downstream inequalities. In the framework of water resource management, monitoring of river basins is therefore of high importance, in particular for researchers, stake-holders and decision-makers. However, land surface and surface water properties of many major river basins remain largely unmonitored at basin scale. Several inventories exist, yet consistent spatial databases describing the status of major river basins at global scale are lacking. Here, Earth observation (EO) is a potential source of spatial information providing large-scale data on the status of land surface properties. This review provides a comprehensive overview of existing research articles analyzing major river basins primarily using EO. Furthermore, this review proposes to exploit EO data together with relevant open global-scale geodata to establish a database and to enable consistent spatial analyses and evaluate past and current states of major river basins. KW - major river basins KW - catchment KW - watershed KW - Earth observation KW - remote sensing KW - spatial analyses KW - land surface KW - surface water Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193849 SN - 2072-4292 VL - 11 IS - 24 ER - TY - JOUR A1 - Nill, Leon A1 - Ullmann, Tobias A1 - Kneisel, Christof A1 - Sobiech-Wolf, Jennifer A1 - Baumhauer, Roland T1 - Assessing Spatiotemporal Variations of Landsat Land Surface Temperature and Multispectral Indices in the Arctic Mackenzie Delta Region between 1985 and 2018 JF - Remote Sensing N2 - 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. KW - LST KW - thermal remote sensing KW - Landsat time series KW - arctic greening KW - Google Earth Engine Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193301 SN - 2072-4292 VL - 11 IS - 19 ER - TY - JOUR A1 - Ullmann, Tobias A1 - Sauerbrey, Julia A1 - Hoffmeister, Dirk A1 - May, Simon Matthias A1 - Baumhauer, Roland A1 - Bubenzer, Olaf T1 - Assessing Spatiotemporal Variations of Sentinel-1 InSAR Coherence at Different Time Scales over the Atacama Desert (Chile) between 2015 and 2018 JF - Remote Sensing N2 - 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. KW - Chile KW - Atacama KW - Sentinel-1 KW - InSAR KW - coherence KW - geomorphology Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193836 SN - 2072-4292 VL - 11 IS - 24 ER - TY - JOUR A1 - Baumhoer, Celia A. A1 - Dietz, Andreas J. A1 - Kneisel, C. A1 - Kuenzer, C. T1 - Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning JF - Remote Sensing N2 - 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. KW - Antarctica KW - coastline KW - deep learning KW - semantic segmentation KW - Getz Ice Shelf KW - calving front KW - glacier front KW - U-Net KW - convolutional neural network KW - glacier terminus Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193150 SN - 2072-4292 VL - 11 IS - 21 ER - TY - JOUR A1 - Dietrich, Laura A1 - Meister, Julia A1 - Dietrich, Oliver A1 - Notroff, Jens A1 - Kiep, Janika A1 - Heeb, Julia A1 - Beuger, André A1 - Schütt, Brigitta T1 - Cereal processing at Early Neolithic Göbekli Tepe, southeastern Turkey JF - PLoS ONE N2 - 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. KW - Specimen grinding KW - Archaeology KW - Neolithic period KW - Sediment KW - Equipment KW - Stratigraphy KW - Limestone KW - Meat Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-201504 VL - 14 IS - 5 ER - TY - JOUR A1 - Paeth, Heiko A1 - Pollinger, Felix T1 - Changes in mean flow and atmospheric wave activity in the North Atlantic sector JF - Quarterly Journal of the Royal Meteorological Society N2 - 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. KW - atmospheric waves KW - climate change KW - Elissen-Palm flux KW - jet stream Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-208079 VL - 145 IS - 725 ER - TY - JOUR A1 - Latifi, Hooman A1 - Valbuena, Ruben T1 - Current trends in forest ecological applications of three-dimensional remote sensing: Transition from experimental to operational solutions? JF - Forests N2 - The alarming increase in the magnitude and spatiotemporal patterns of changes in composition, structure and function of forest ecosystems during recent years calls for enhanced cross-border mitigation and adaption measures, which strongly entail intensified research to understand the underlying processes in the ecosystems as well as their dynamics. Remote sensing data and methods are nowadays the main complementary sources of synoptic, up-to-date and objective information to support field observations in forest ecology. In particular, analysis of three-dimensional (3D) remote sensing data is regarded as an appropriate complement, since they are hypothesized to resemble the 3D character of most forest attributes. Following their use in various small-scale forest structural analyses over the past two decades, these sources of data are now on their way to be integrated in novel applications in fields like citizen science, environmental impact assessment, forest fire analysis, and biodiversity assessment in remote areas. These and a number of other novel applications provide valuable material for the Forests special issue “3D Remote Sensing Applications in Forest Ecology: Composition, Structure and Function”, which shows the promising future of these technologies and improves our understanding of the potentials and challenges of 3D remote sensing in practical forest ecology worldwide. KW - 3D remote sensing KW - composition KW - forest ecology KW - function KW - structure Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193282 SN - 1999-4907 VL - 10 IS - 10 ER - TY - JOUR A1 - Abdullahi, Sahra A1 - Wessel, Birgit A1 - Huber, Martin A1 - Wendleder, Anna A1 - Roth, Achim A1 - Kuenzer, Claudia T1 - Estimating penetration-related X-band InSAR elevation bias: a study over the Greenland ice sheet JF - Remote Sensing N2 - Accelerating melt on the Greenland ice sheet leads to dramatic changes at a global scale. Especially in the last decades, not only the monitoring, but also the quantification of these changes has gained considerably in importance. In this context, Interferometric Synthetic Aperture Radar (InSAR) systems complement existing data sources by their capability to acquire 3D information at high spatial resolution over large areas independent of weather conditions and illumination. However, penetration of the SAR signals into the snow and ice surface leads to a bias in measured height, which has to be corrected to obtain accurate elevation data. Therefore, this study purposes an easy transferable pixel-based approach for X-band penetration-related elevation bias estimation based on single-pass interferometric coherence and backscatter intensity which was performed at two test sites on the Northern Greenland ice sheet. In particular, the penetration bias was estimated using a multiple linear regression model based on TanDEM-X InSAR data and IceBridge laser-altimeter measurements to correct TanDEM-X Digital Elevation Model (DEM) scenes. Validation efforts yielded good agreement between observations and estimations with a coefficient of determination of R\(^2\) = 68% and an RMSE of 0.68 m. Furthermore, the study demonstrates the benefits of X-band penetration bias estimation within the application context of ice sheet elevation change detection. KW - InSAR height KW - penetration bias KW - cryosphere KW - TanDEM-X KW - Greenland ice sheet KW - DEM Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193902 SN - 2072-4292 VL - 11 IS - 24 ER - TY - JOUR A1 - Philipp, Marius B. A1 - Levick, Shaun R. T1 - Exploring the potential of C-Band SAR in contributing to burn severity mapping in tropical savanna JF - Remote Sensing N2 - The ability to map burn severity and to understand how it varies as a function of time of year and return frequency is an important tool for landscape management and carbon accounting in tropical savannas. Different indices based on optical satellite imagery are typically used for mapping fire scars and for estimating burn severity. However, cloud cover is a major limitation for analyses using optical data over tropical landscapes. To address this pitfall, we explored the suitability of C-band Synthetic Aperture Radar (SAR) data for detecting vegetation response to fire, using experimental fires in northern Australia. Pre- and post-fire results from Sentinel-1 C-band backscatter intensity data were compared to those of optical satellite imagery and were corroborated against structural changes on the ground that we documented through terrestrial laser scanning (TLS). Sentinel-1 C-band backscatter (VH) proved sensitive to the structural changes imparted by fire and was correlated with the Normalised Burn Ratio (NBR) derived from Sentinel-2 optical data. Our results suggest that C-band SAR holds potential to inform the mapping of burn severity in savannas, but further research is required over larger spatial scales and across a broader spectrum of fire regime conditions before automated products can be developed. Combining both Sentinel-1 SAR and Sentinel-2 multi-spectral data will likely yield the best results for mapping burn severity under a range of weather conditions. KW - burn severity KW - Sentinel-1 KW - Sentinel-2 KW - terrestrial LiDAR Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193789 SN - 2072-4292 VL - 12 IS - 1 ER - TY - JOUR A1 - Khare, Siddhartha A1 - Latifi, Hooman A1 - Rossi, Sergio A1 - Ghosh, Sanjay Kumar T1 - Fractional cover mapping of invasive plant species by combining very high-resolution stereo and multi-sensor multispectral imageries JF - Forests N2 - Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5 m to quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38% (for SPOT-6), and 85.27% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8% (for RapidEye) and 7.22% (for SPOT-6), and R\(^2\) values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37%, whereas it decreased by up to 37.96% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions. KW - Lantana camara KW - SPOT-6 KW - RapidEye KW - 3D KW - DSM KW - Fractional cover analysis Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-197250 SN - 1999-4907 VL - 10 IS - 7 ER -