Istanbul Technical University, Faculty of Mines, Geological Engineering Department, Istanbul, Turkey.
J Environ Manage. 2021 Nov 15;298:113481. doi: 10.1016/j.jenvman.2021.113481. Epub 2021 Aug 12.
Lake Salda's extreme environment is geologically similar to Jezero Crater paleolake on Mars due to the formation of stromatolites and its extremely alkaline and cold water. It is critical to accurately determine the shoreline in the littoral zone where stromatolite formation occurs, in alkaline clean lakes like Salda, which contain traces of life on Mars, and in monitoring the change that occurs with climate and anthropogenic effect. The performance of global automatic thresholding algorithms on shoreline determination from NDWI and mNDWI water indices is compared in this study using Sentinel-2 and Landsat-8 images atmospherically corrected by different algorithms. Satellite images data acquired on August 12, 2020 for Sentinel-2 and August 11, 2020 for Landsat-8 on Lake Salda were used to determining the shoreline. The shoreline data measured in situ concurrently with the Sentinel-2 satellite acquisition was used as reference data. In the accuracy analysis, ground control points created inside and outside the lake at a distance of 1 pixel and 0.5 pixel to the reference shoreline for each satellite image were used. The performance of the optimal threshold values determined by each thresholding algorithm in the water index images was assessed using Kappa coefficient, Overall Accuracy (OA), %OA of Inside (%OA) and %OA of Outside (%OA) statistics metrics. The optimal threshold values vary depending on the image and the atmospheric correction algorithm applied to the image. The NDWI index produces more accurate results in both Sentinel-2 and Landsat-8 satellite images. While atmospheric correction algorithms do not affect the results in Landsat-8 images, the Sen2Cor algorithm outperforms iCOR in Sentinel-2 images. For thresholding algorithms to be used in different water index and satellite images, Intermode, Isodata, IJ_Isodata, Minimum and Otsu algorithms in Landsat-8_LaSRC_NDWI and Landsat-8_iCOR_NDWI images, and Intermode, Minimum and Huang algorithms in Sentinel-2_Sen2Cor_NDWI images produce the best results. Because the Minimum algorithm causes significant gaps in the lake surface, the Huang and Intermode algorithms should be used for Sentinel-2_Sen2Cor_NDWI images. The 0 (zero) threshold value in the water indices images has a high accuracy only in the NDWI water indices generated from the Landsat-8 image.
萨尔达湖的极端环境与火星上杰泽罗陨石坑古湖泊在地质学上相似,因为那里形成了叠层石,而且水呈极强碱性、低温。在萨尔达这样的碱性清洁湖中,准确确定叠层石形成的滨海带的海岸线至关重要,因为这里有火星生命的痕迹,并且还需要监测气候和人为影响引起的变化。本研究比较了使用不同大气校正算法校正后的 Sentinel-2 和 Landsat-8 卫星图像的归一化水指数(NDWI)和修正归一化水指数(mNDWI)的水指数图像中全局自动阈值算法对海岸线的测定性能。使用 2020 年 8 月 12 日获取的 Sentinel-2 卫星图像和 2020 年 8 月 11 日获取的 Landsat-8 卫星图像,在大气校正后对萨尔达湖的海岸线进行了测定。同时,还使用了与 Sentinel-2 卫星采集同步进行的现场测量的海岸线数据作为参考数据。在精度分析中,为每个卫星图像在湖内和湖外距离参考海岸线 1 像素和 0.5 像素处创建了地面控制点。使用 Kappa 系数、总体精度(OA)、内部 OA(%OA)和外部 OA(%OA)统计量评估了每个阈值算法在水指数图像中确定的最佳阈值的性能。最佳阈值值取决于图像和应用于图像的大气校正算法。NDWI 指数在 Sentinel-2 和 Landsat-8 卫星图像中都能产生更准确的结果。虽然大气校正算法不会影响 Landsat-8 图像的结果,但 Sen2Cor 算法在 Sentinel-2 图像中的表现优于 iCOR。对于要在不同的水指数和卫星图像中使用的阈值算法,Landsat-8_LaSRC_NDWI 和 Landsat-8_iCOR_NDWI 图像中的 Intermode、Isodata、IJ_Isodata、Minimum 和 Otsu 算法,以及 Sentinel-2_Sen2Cor_NDWI 图像中的 Intermode、Minimum 和 Huang 算法,产生了最佳的结果。由于最小算法会在湖面上产生很大的间隙,因此应该在 Sentinel-2_Sen2Cor_NDWI 图像中使用 Huang 和 Intermode 算法。水指数图像中的 0(零)阈值值仅在 Landsat-8 图像生成的 NDWI 水指数中具有很高的精度。