2019
DOI: 10.3390/ijgi8120528
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A Method of Watershed Delineation for Flat Terrain Using Sentinel-2A Imagery and DEM: A Case Study of the Taihu Basin

Abstract: Accurate watershed delineation is a precondition for runoff and water quality simulation. Traditional digital elevation model (DEM) may not generate realistic drainage networks due to large depressions and subtle elevation differences in local-scale plains. In this study, we propose a new method for solving the problem of watershed delineation, using the Taihu Basin as a case study. Rivers, lakes, and reservoirs were obtained from Sentinel-2A images with the Canny algorithm on Google Earth Engine (GEE), rather… Show more

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Cited by 28 publications
(18 citation statements)
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References 52 publications
(50 reference statements)
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“…S2A images have great usage for studying lake ecology and also for retrieving the water quality indicators at a fine scale (Bresciani et al 2018). S2A images available in GEE are considered to be Level 2 products (Li et al 2019). The revisit time of S2A is ten days, but it decreases to five days when both the imagers are operational as compared to LANDSAT-8 satellite, Gorji et al 2020).…”
Section: Data Usedmentioning
confidence: 99%
“…S2A images have great usage for studying lake ecology and also for retrieving the water quality indicators at a fine scale (Bresciani et al 2018). S2A images available in GEE are considered to be Level 2 products (Li et al 2019). The revisit time of S2A is ten days, but it decreases to five days when both the imagers are operational as compared to LANDSAT-8 satellite, Gorji et al 2020).…”
Section: Data Usedmentioning
confidence: 99%
“…The second group of studies focused on using geo-spatial technique to improve the accuracy of extraction of basin characteristics. Li et al [24] proposed a new method of watershed delineation for flat terrain based on Sentinel-2A images with the Canny algorithm on Google Earth Engine (GEE). Using the traditional DEM for water delineation in local-scale plains may not obtain realistic drainage networks primarily because of large depressions and subtle elevation differences.…”
Section: Content Of the Special Issuementioning
confidence: 99%
“…Phân định lưu vực sông là bước xác định bề mặt đất trong tự nhiên nơi mà lượng nước mưa khi rơi xuống sẽ tập trung và thoát ra một cửa xả. Các dữ liệu về tích lũy dòng chảy, hướng dòng chảy, mạng lưới dòng chảy, ranh giới lưu vực và lưu vực con sẽ được tạo ra trong quá trình phân định lưu vực trên GIS (Leilei, 2019). Diện tích toàn bộ lưu vực của khu vực nghiên cứu được xác định là 9982,5 km 2 .…”
Section: Bước 2: Phân địNh Lưu Vựcunclassified