基于Landsat 8 OLI影像的常用水体指数法分类精度对比

李龙杰; 杨永辉

doi:10.7523/j.ucas.2023.088

中国科学院大学学报 >

2024 , Vol. 41 >Issue 6: 755 - 765

DOI: https://doi.org/10.7523/j.ucas.2023.088

环境科学与地理学

基于Landsat 8 OLI影像的常用水体指数法分类精度对比

李龙杰 ,
杨永辉

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中国科学院遗传与发育生物学研究所农业资源研究中心/中国科学院农业水资源重点实验室/河北省节水农业重点实验室, 石家庄 050022;中国科学院大学, 北京 100049

收稿日期: 2023-06-25

修回日期: 2023-11-13

网络出版日期: 2023-11-13

基金资助

国家自然科学基金(42171046)资助

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Comparison study on classification accuracy of 11 common water indices based on Landsat 8 OLI images

LI Longjie ,
YANG Yonghui

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Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences/CAS Key Laboratory of Agricultural Water Resources/Hebei Key Laboratory of Water-saving Agriculture, Shijiazhuang 050022, China;University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2023-06-25

Revised date: 2023-11-13

Online published: 2023-11-13

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摘要

以南水北调受水区的石家庄为对象，以同期Sentinel-2 MSI影像的目视结果作为标准水体，使用11种常见水体指数，从Landsat 8 OLI影像中提取水体分布信息，基于转移矩阵的面积精度检验法、抽样精度检验法，对提取结果进行精度验证。结果表明，各水体指数法提取宽阔水面(如大型水库、湖泊)的区别不大，城区小水系、小型河道更能检验水体指数的提取能力，WI2019在对比的水体指数中表现最佳。分析表明，南水北调通水后，石家庄市除去大型水库后地表水体面积显著增加，从2014年42.0 km²增长到2020年62.5 km²。南水北调通水后受水区地表水体面积增长较快，鉴于大部分新增水体底部存在人工衬砌，地下水补给功能较差、无效蒸发较多，建议适当控制水体规模，以便有效减少外调水资源的浪费。

关键词： 水体指数; 精度验证; Landsat 8 OLI; GEE; 南水北调工程

本文引用格式

李龙杰 , 杨永辉 . 基于Landsat 8 OLI影像的常用水体指数法分类精度对比[J]. 中国科学院大学学报, 2024 , 41(6) : 755 -765 . DOI: 10.7523/j.ucas.2023.088

Abstract

Water index is one of the most effective methods to extract water bodies from remote sensing images. There are many kinds of water index, each with its own characteristics. It is, therefore, necessary to select the index with best classification accuracy. Taking Shijiazhuang City as the research area, 11 common water indices were used to extract water bodies from Landsat 8 OLI images. The accuracy of the water index extraction results is validated by using the visual interpretation (VI) result as the standard classification map from Sentinel-2 MSI based on the area test method in combination with transition matrix and sampling test method. Results show little difference in the extraction of large water bodies among different water indices. Small ponds and rivers can better check the extraction ability of water index. It is proved that Water Index 2019 (WI2019) has the best water classification. WI2019 is then used to find out the recent expansion of water bodies after the start of South-to-North Water Diversion Project for water transfer. It was found that the area of surface water body in Shijiazhuang excluding large reservoirs increased significantly, from 42 km² in 2014 to 62 km² in 2020, an increase of 20 km². In view of the canal seepage control treatment at the bottom of most newly added water bodies, with poor groundwater recharge function, and more ineffective evaporation, it is recommended to properly control the scale of water bodies in order to effectively reduce the waste of water transferred from outside.

Key words： water index; accuracy validation; Landsat 8 OLI; GEE; South-to-North Water Diversion Project

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