Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices

被引：62
作者：
Yang, Xiucheng [1 ]
Chen, Li [2 ]
机构：
[1] Univ Strasbourg, ICube Lab, Strasbourg, France
[2] China Aero Geophys Survey & Remote Sensing Ctr La, Beijing, Peoples R China
来源：
JOURNAL OF APPLIED REMOTE SENSING | 2017年 / 11卷
关键词：
urban surface; water body; Sentinel-2; Landsat; 8; water index; LANDSAT IMAGERY; RESOLUTION; FEATURES; NDWI;
D O I：
10.1117/1.JRS.11.026016
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
Urban surface water is characterized by complex surface continents and small size of water bodies, and the mapping of urban surface water is currently a challenging task. The moderate-resolution remote sensing satellites provide effective ways of monitoring surface water. This study conducts an exploratory evaluation on the performance of the newly available Sentinel-2A multispectral instrument (MSI) imagery for detecting urban surface water. An automatic framework that integrates pixel-level threshold adjustment and object-oriented segmentation is proposed. Based on the automated workflow, different combinations of visible, near infrared, and short-wave infrared bands in Sentinel-2 image via different water indices are first compared. Results show that object-level modified normalized difference water index (MNDWI with band 11) and automated water extraction index are feasible in urban surface water mapping for Sentinel-2 MSI imagery. Moreover, comparative results are obtained utilizing optimal MNDWI from Sentinel-2 and Landsat 8 images, respectively. Consequently, Sentinel-2 MSI achieves the kappa coefficient of 0.92, compared with that of 0.83 from Landsat 8 operational land imager. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
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页数：11
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