期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 140, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2021.105030
关键词
Satellite water mapping; Spectral index; MNDWI; AWEI; WI; Landsat
类别
资金
- CUAHSI
- National Science Foundation (NSF) [EAR-1849458]
- U.S. Geological Survey's Land Change Science Program
- U.S. Geological Survey
This study provides a critical review of satellite remote sensing water indices and introduces a novel Augmented Normalized Difference Water Index (ANDWI) that utilizes an expanded set of spectral bands and dynamic thresholding. The ANDWI with Otsu-thresholding outperformed other indices in terms of overall accuracy. Additionally, a new cloud filtering algorithm and a Google Earth Engine App were developed to improve the accuracy and efficiency of water body delineation.
We present a comprehensive critical review of well-established satellite remote sensing water indices and offer a novel, robust Augmented Normalized Difference Water Index (ANDWI). ANDWI employs an expanded set of spectral bands, RGB, NIR, and SWIR1-2, to maximize the contrast between water and non-water pixels. Further, we implement a dynamic thresholding method, the Otsu algorithm, to enhance ANDWI?s performance. Applied to a variety of environmental conditions, ANDWI with Otsu-thresholding offered the highest overall accuracy (accuracy = 0.98, F1 = 0.98, and Kappa = 0.96) compared to other indices (NDWI, MNDWI, AWEI, WI). We also propose a novel cloud filtering algorithm that substantially increases the number of useable images compared to the conventional cloud-free composites (124% increased observations in the studied area) and resolves inappropriate masking of water bodies and hot sands as clouds by conventional methods. Finally, we develop a Google Earth Engine App to readily delineate 16-day surface water bodies across the globe.
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