面向Sentinel-2影像的亚像元级水体提取方法

doi:10.13474/j.cnki.11-2246.2023.0339

测绘通报 ›› 2023, Vol. 0 ›› Issue (11): 122-127.doi: 10.13474/j.cnki.11-2246.2023.0339

面向Sentinel-2影像的亚像元级水体提取方法

熊龙海^1,2, 何颖清^1,2, 刘茉默^1,2, 李俊^1,2

1. 水利部珠江河口治理与保护重点实验室, 广东广州 510611;
2. 珠江水利委员会珠江水利科学研究院, 广东广州 510611

收稿日期:2023-08-08 出版日期:2023-11-25 发布日期:2023-12-07
通讯作者: 何颖清。E-mail:heyingqing@foxmail.com
作者简介:熊龙海(1990—),男,博士,工程师,主要从事水利遥感工作。E-mail:xiaoyi111.good@163.com
基金资助:
水利部重大科技项目(SKR-2022037);广州市科技计划(2023A04J0942)

Subpixel water extraction method for Sentinel-2 image

XIONG Longhai^1,2, HE Yingqing^1,2, LIU Momo^1,2, LI Jun^1,2

1. Key Laboratory of the Pearl River Estuary Regulation and Protection of Ministry of Water Resources, Guangzhou 51061 l, China;
2. Pearl River Water Resources Research Institute, Pearl River Water Resources Commission, Guangzhou 510611, China

Received:2023-08-08 Online:2023-11-25 Published:2023-12-07

摘要/Abstract

摘要： 结合Sentinel-2影像及其他高分辨率卫星数据进行长序列、高频次、大范围的水面率、蓄水量、生态流量等水资源要素监测具有重要意义。为了提高水体提取精度,解决利用多源中高分辨率卫星数据提取水体时的空间尺度效应问题,本文提出了一种面向Sentinel-2影像的亚像元级水体提取方法(简称SWES)。首先利用RWI提取纯水体像元,然后利用膨胀算法提取水陆边界混合像元,最后为解决地物的类内光谱变化问题,采用考虑空间信息的多端元光谱混合分析算法(MESMA)求解水陆混合像元中的水体丰度。3个试验区的结果均表明,SWES取得了较好效果,平均RMSE为0.147,水体提取效果均优于自动亚像元水体提取方法(简称ASWM),尤其在水陆混合像元较多的坑塘养殖区。SWES在试验区获取的水体面积也有较高精度,平均相对误差为8.03%,低于ASWM的20.23%,结果表明SWES能够有效提升水域面积提取精度。

关键词: 亚像元, 水体提取, 水陆混合像元, 多端元光谱混合分析, Sentinel-2影像

Abstract: Combining Sentinel-2 image and other high-resolution satellite data, it is of great significance to monitor water resources factors such as water surface rate, water storage and ecological flow in long series, high frequency and large range. In order to improve the accuracy of water extraction and solve the problem of spatial scale effect when extracting water from multi-source moderate-and high-resolution satellite data, a subpixel water extraction method for Sentinel-2 image(SWES) is proposed in this paper. First, RWI is used to extract pure water pixel, then the expansion algorithm is used to extract the mixed water pixel. Finally, in order to solve the problem of intra-class spectral changes of surface objects, MESMA considering spatial information is used to solve the water abundance in the mixed water pixel. The results of the three experimental areas all showed that SWES achieved a good effect, the average RMSE was 0.147, and the water extraction effect is better than automatic subpixel water mapping method(ASWM), especially in the pond aquaculture area with more mixed pixels of water and land. The water area obtained by SWES in experimental area also has high accuracy, with the average relative error of 8.03%, which is lower than the 20.23% of ASWM. The results show that SWES can effectively improve the accuracy of water area extraction.

Key words: subpixel, water extraction, mixed pixels of water and land, multiple endmember spectral mixture analysis, Sentinel-2 image

中图分类号:

P237

熊龙海, 何颖清, 刘茉默, 李俊. 面向Sentinel-2影像的亚像元级水体提取方法[J]. 测绘通报, 2023, 0(11): 122-127.

XIONG Longhai, HE Yingqing, LIU Momo, LI Jun. Subpixel water extraction method for Sentinel-2 image[J]. Bulletin of Surveying and Mapping, 2023, 0(11): 122-127.

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面向Sentinel-2影像的亚像元级水体提取方法

Subpixel water extraction method for Sentinel-2 image

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