Characterization of different landscape surfaces in arid environments by the use of Sentinel-1 SAR data

地球上的干旱地区过去和现在都特别容易受到气候变化的影响。与此同时，它们是20多亿人的栖息地。由于面积小，许多地方基础设施差，环境条件往往不利，在景观变化率的研究方面仍有很大的差距。几十年来，光学遥感数据一直被广泛用于监测干旱地区。然而，光学遥感方法往往面临的问题，以确定地貌过程和过程速率，由于其粗分辨率和低光谱多样性。在本项目的框架内，将研究合成孔径雷达数据是否适合于表面特征的确定。随着欧空局的哨兵-1使命，一个现代化的合成孔径雷达系统正在运作，其空间分辨率低于每像素15米。它免费提供遥感图像，适合建立时间密集的时间序列。由于植被稀疏，干旱地区特别适合使用雷达遥感，因为植被的影响很小，导致体积散射，从而产生不必要的失真。该项目将调查合成孔径雷达的强度和干涉测量相干性，以评价哨兵-1号确定陆地表面时空特征的能力。蒙古南部的Orog-Nuur盆地被选为合适的研究区域。该区域的特点是各种不同的陆地表面和地貌过程。这些包括受冰缘过程、沙丘、大砾石海滩山脊以及特别是大量不同年代的冲积扇表面所改变的前湖泊沉积物。在实地考察期间，将对不同的表面进行地貌记录和详细描述。在实地工作期间，将特别强调利用无人机图像制作高精度正射影像和数字地形模型。由于表面粗糙度强烈影响SAR系统的后向散射，将对这些地形模型进行不同空间尺度的粗糙度分析。此外，这些模式将适合于表征微观和中尺度地形要素。最后，将把实地工作和形态测量分析的结果与合成孔径雷达数据进行比较，以便在不同尺度上准确描述不同表面和地貌的特征。如果成功地确定了SAR数据对干旱环境中表面的详细表征的适用性，则为今后的研究提供了一种详细监测这些敏感景观的新方法。特别是在具有高度可变性的区域，详细和时间上频繁的观察具有高度相关性。

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.