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Interferometric SAR for characterization of ravines as a function of their density, depth, and surface cover

机译:干涉SAR来表征山沟的密度,深度和表面覆盖率

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摘要

In recent years, the problem of ravine erosion with consequent loss of usable land has received much attention worldwide. The Chambal ravine zone in India is well known for being an extremely intricate, deeply incised network of ravines in a 10 km wide zone on the flanks of the Chambal River. It occupies an area of ~0.5 million hectares at the expense of fertile agricultural land of the Chambal Valley. The broad grouping of the ravines considering their reclamation potential, as carried out by previous workers based on visual interpretation of optical remote sensing data, is mostly descriptive in nature. In the present study, characterization of the ravines as a function of their erosion potential expressed through ravine density, ravine depth, and ravine surface cover was made in quantitative terms exploiting the preferential characteristics of side-looking, long-wavelength, coherent SAR signal and precision measurements associated with the InSAR technique.rnThe outlines of ravines appear remarkably prominent in SAR backscattered amplitude images due to the high sensitivity of the SAR signal to terrain ruggedness. Using local statistics-based meso and macro textural information of SAR backscattered amplitude images in 7 x 7 pixel windows (the pixel size being 20 m × 20 m), the ravine-affected area has been classified into three density classes, namely low, moderate, and high density ravine classes.rnC-band InSAR digital elevation models (DEMs) of sparsely vegetated ravine areas essentially give the terrain height. From the pixel-by-pixel terrain height, the ravine depth was calculated by differencing the maximum and minimum terrain heights of the pixels in a 100 m distance range. Considering the vertical precision of the ERS InSAR DEMs of ~5 m and ravine depth classification by previous workers [Sharma, H.S., 1968. Genesis and pattern of ravines of the Lower Chambal Valley, India. Special Issue. 21st International Geographical Union Congress 30(4), 14-24; Seth, S.P., Bhatnagar, R.K., Chauhan, S.S., 1969. Reclamability classification and nature of ravines of Chambal Command Areas. Journal of Soil and Water Conservation in India 17 (3-4), 39-44.], three depth classes, namely shallow (<5 m), moderately deep (5-20 m), and deep (>20 m) ravines, were made.rnUsing the temporal decorrelation property of the close time interval InSAR data pair, namely the ERS SAR tandem pair, four ravine surface cover classes, namely barren land, grass/scrub/crop land, sparse vegetation, and wet land/dense vegetation, could be delineated, which was corroborated by the spectral signatures in the optical range and selective ground truths.
机译:近年来,沟壑侵蚀问题以及随之而来的可用土地流失问题在全世界引起了广泛关注。印度的尚巴尔河谷地带因其在尚巴拉河侧翼10公里宽的区域中极为复杂,深度切割的山沟网而闻名。它占地约50万公顷,以钱伯尔香巴拉谷肥沃的农业土地为代价。以前的工作人员基于对光学遥感数据的视觉解释,将谷类动物考虑其填海潜力,将其大致分为几类。在本研究中,通过利用侧视,长波长,相干SAR信号和SAR信号的优先特征,定量地描述了沟壑作为通过沟壑密度,沟壑深度和沟壑表面覆盖表示的其侵蚀潜力的函数。与SAR技术相关的精确测量。由于SAR信号对地形崎ness性非常敏感,因此在SAR反向散射振幅图像中,沟壑的轮廓显得非常突出。利用基于本地统计的7 x 7像素窗口(像素大小为20 m×20 m)中SAR背向散射振幅图像的宏观和宏观纹理信息,将受沟壑影响的区域分为三个密度类别,即低,中稀疏的沟壑区的rnC波段InSAR数字高程模型(DEM)本质上给出了地形高度。根据每个像素的地形高度,通过对100 m距离范围内的像素的最大和最小地形高度求差来计算沟壑深度。考虑到约5 m的ERS InSAR DEM的垂直精度和以前的工作人员对山沟深度的分类[Sharma,H.S.,1968.印度下香巴拉谷地的山沟的成因和样式。特刊。第21届国际地理联盟大会30(4),14-24;塞思,S.P.,Bhatnagar,R.K。,南卡罗来纳州乔汉,1969。印度水土保持学报17(3-4),39-44。],三个深度类别,即浅层(<5 m),中深层(5-20​​ m)和深层(> 20 m)山沟利用短时间间隔InSAR数据对的时间去相关特性(即ERS SAR串联对),四个沟壑地表覆盖类别,即贫瘠土地,草丛/灌木丛/作物地,稀疏植被和湿地/茂密地可以描绘出植被,这被光学范围内的光谱特征和选择性的地面真相所证实。

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  • 作者单位

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

    Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, 4-Kalidas Road, Dehradun-248001, India;

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  • 正文语种 eng
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  • 关键词

    ravines; InSAR; characterization; chambal; India;

    机译:沟壑InSAR;表征;尚巴尔印度;

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