小型水坝:确定使用Sentinel-1 SAR图像可以成功探测到的最小水体表面积

IF 0.3 Q4 REMOTE SENSING South African Journal of Geomatics Pub Date : 2022-09-02 DOI:10.4314/sajg.v11i2.9
M. von Fintel, J. Kemp
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引用次数: 0

摘要

水在南非是一种稀缺资源,南非约62%的用水用于灌溉。这些水储存在分散在全国各地的许多小水坝中。如果管理不当,它们可能会对集水区和水的可用性产生负面影响。因此,需要开发一个新的监测和管理系统。这项研究确定了在Sentinel-1合成孔径雷达图像上探测到水体所需的最小表面积。随机森林分类器用于检测Sentinel-1图像上的水体,该图像是根据三个月内拍摄的一系列图像计算得出的。陡入射角优于浅入射角,分类的总体准确率为80%。一公顷及以上水体的检测率几乎为90%,没有假阳性,假阴性率为10%。这些发现为开发一个检测和监测系统奠定了基础,该系统将有助于更好地管理南非的水资源。
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Small dams: determining the minimum waterbody surface area that can be successfully detected using Sentinel-1 SAR imagery
Water is a scarce resource in South Africa, and approximately 62% of the water used in South Africa is for irrigation. This water is stored in many small dams scattered across the country. If not managed correctly, they could have a negative effect on catchment areas and on the availability of water. As such, there is a need for a new monitoring and management system to be developed. This study determined the minimum surface area that would be required for a waterbody to be detected on Sentinel-1 Synthetic Aperture Radar imagery. A Random Forest classifier was used to detect waterbodies on a Sentinel-1 image calculated from a time series of imagery taken over a period of three months. Steep incidence angles outperformed shallow incidence angles, with the classification having an overall accuracy of 80%. Detection rates were almost 90% for waterbodies of one hectare and greater, with no false positives, and a 10% false negative rate. These findings provide the foundation for developing a detection and monitoring system, which would allow for the better management of water resources in South Africa.
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