{"title":"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","authors":"M. von Fintel, J. Kemp","doi":"10.4314/sajg.v11i2.9","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Small dams: determining the minimum waterbody surface area that can be successfully detected using Sentinel-1 SAR imagery\",\"authors\":\"M. von Fintel, J. Kemp\",\"doi\":\"10.4314/sajg.v11i2.9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":43854,\"journal\":{\"name\":\"South African Journal of Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2022-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/sajg.v11i2.9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v11i2.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
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.