Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices
Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices
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DOI：
10.1117/1.jrs.11.026016
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发表时间：
2017-04
影响因子：
1.7
通讯作者：
Xiucheng Yang;Li Chen
中科院分区：
文献类型：
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作者：
Xiucheng Yang;Li Chen
抽象。城市地表水具有地表复杂、水体规模小的特点，城市地表水制图是当前一项具有挑战性的任务。中分辨率遥感卫星提供了监测地表水的有效方法。本研究进行了探索性的性能评价的最新可用的哨兵-2A多光谱仪器（MSI）图像检测城市地表水。提出了一种集成像素级阈值调整和面向对象分割的自动化框架。基于自动化工作流程，首先通过不同的水指数比较了Sentinel-2图像中可见光、近红外和短波红外波段的不同组合。结果表明，对象级修正的归一化差异水指数（MNDWI与波段11）和自动水提取指数是可行的城市地表水制图哨兵-2 MSI图像。此外，利用最佳MNDWI哨兵-2和Landsat 8图像，分别获得比较结果。因此，Sentinel-2 MSI实现了0.92的kappa系数，而Landsat 8业务陆地成像仪的kappa系数为0.83。
Abstract. 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.