Project Details
Projekt
Characterization of different landscape surfaces in arid environments by the use of Sentinel-1 SAR data
Subject Area
Physical Geography
Term
from 2019 to 2020
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 430973477
The arid regions of the earth were and are particularly susceptible to climatic changes. At the same time, they are the habitat of more than 2 billion people. Due to the size of the areas, the poor infrastructure in many parts and the often adverse environmental conditions, there are still large gaps in the state of research on the rates of landscape change. For several decades, optical remote sensing data have been used intensively to monitor arid areas. However, optical remote sensing methods often face problems to identify geomorphological processes and process rates due to their coarse resolution and the low spectral diversity. Within the framework of this project, the suitability of Synthetic Aperture Radar (SAR) data for the characterization of surfaces will be investigated. With the Sentinel-1 mission of the ESA (European Space Agency), a modern SAR system, offering spatial resolution of less than 15 m per pixel, is operating. It delivers remote sensing imagery free of charge and suited to build temporal dense time series. Due to the sparse vegetation cover, arid regions are particularly suitable for the use of radar remote sensing because the influence of vegetation, leading to volume scattering and thus unwanted distortion, is low. The project will investigate the SAR intensities and the interferometric coherences in order to evaluate the capacities of Sentinel-1 for the spatial-temporal characterization of the land surface. The Orog-Nuur Basin in southern Mongolia was selected as a suited study area. The region is characterized by a variety of different land surfaces and geomorphological processes. These include former lake sediments modified by periglacial processes, dunes, large gravelly beach ridges and, in particular, a large number of different alluvial fan surfaces of various ages. The different surfaces will be geomorphologically recorded and described in detail during the fieldwork. Special emphasis during the field work will be put on the creation of high-precision orthophotos and digital terrain models from drone imagery. Since surface roughness strongly influences the backscatter of the SAR system, roughness analyses on different spatial scales will be carried out on these terrain models. Additionally, these models will be suited for the characterization of micro- and mesoscale landform elements. Finally, the results from the field work and the morphometric analyses will be compared with the SAR data in order to achieve an accurate characterization of the different surfaces and landforms on different scales. If the suitability of the SAR data for a detailed characterisation of the surfaces in arid environment is successfully determined, a new method for a detailed monitoring of these sensitive landscapes is offered for future research. Especially in areas with a high variability, detailed and temporally frequent observations are of high relevance.
DFG Programme
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