Tag: TanDEM-X
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Use of TanDEM-X and Sentinel products to derive gully activity maps in Kunene Region (Namibia) based on automatic iterative Random Forest approach
Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1 and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micro-mapping simulation as training data, to map gullies in the northwestern of Namibia. A Random Forest Classifier examines pixels with similar characteristics in a…
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PermaSAR project concluded with publication of final report
With the publication of the final report, the PermaSAR project is concluded. In the blink of an eye regarding timescales of permafrost monitoring, research within the project period covered diverse methods and analyses around the topic of permafrost and related thaw subsidence in Arctic tundra landscapes. The report (in German) provides all details on the…
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Estimating tree height from TanDEM-X data at the northwestern Canadian treeline
A new paper on tree height estimation from TanDEM-X data has just been published in Remote Sensing of Environment. The article finds that tree height can be predicted using TanDEM-X metrics (backscatter, bistatic coherence, and interferometric height) in the sparse forest patches of the Arctic treeline zone at the transition from forest to tundra. Taking…
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Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia)
Namibia is a dry and low populated country highly dependent on agriculture, with many areas experiencing land degradation accelerated by climate change. One of the most obvious and damaging manifestations of these degradation processes are gullies, which lead to great economic losses while accelerating desertification. The development of standardized methods to detect and monitor the…