基于GF-1卫星影像的改进SWI水体提取方法

发布时间：2018-05-29 12:51

本文选题：GF- + 水体信息提取　；参考：《国土资源遥感》2017年01期

【摘要】：大尺度高精度山区河流信息提取是我国干旱区水资源开发利用的关键技术,而利用遥感影像提取水资源信息存在水体与山区阴影难以区分的瓶颈。以GF-1号卫星2 m分辨率全色波段影像和8 m分辨率多光谱影像为数据源,选取新疆特克斯河流域巴喀勒克水库为研究区,提出改进的阴影水体指数法(modified shade water index,MSWI)进行水体信息提取;同时运用单波段阈值法、NDWI法、单波段法与阴影水体指数法(shade water indes,SWI)相结合的决策树分类法(简称SWI)以及单波段法与MSWI相结合的决策树分类法(简称MSWI)分别对研究区水体信息进行提取,并进行了对比分析。研究结果表明,前2种方法与SWI和MSWI法相比,效果稍差;而SWI和MSWI法分类效果较好,其中MSWI比SWI法分类总精度高0.94%,提高了高分辨率遥感影像的解译精度,可为国产高分系列卫星影像在干旱区水资源信息提取中的应用提供技术支持。
[Abstract]:The large scale and high precision mountain river information extraction is the key technology of water resources development and utilization in the arid area of our country. While using remote sensing image to extract water resources information is difficult to distinguish between water body and mountain shadow. Taking GF-1 2 m resolution panchromatic image and 8 m resolution multi spectral image as data source, Xinjiang Turks are selected. The bakklek reservoir in the river domain is the research area, and the improved shadow water index method (modified shade water index, MSWI) is used to extract the water information. At the same time, the single band threshold method, NDWI method, the single band method and the shadow water index method (shade water indes, SWI) are combined with the decision tree classification method (SWI) and the single band method and MSWI. The decision tree classification method (MSWI) is used to extract the water information of the study area, and the results are compared. The results show that the first 2 methods are less effective than the SWI and MSWI methods, while the SWI and MSWI methods have better classification effect, and the total accuracy of MSWI is higher than that of the SWI method, and the interpretation of high resolution remote sensing images is improved. The accuracy can provide technical support for the application of domestic high score satellite images in the extraction of water resources information in arid areas.
【作者单位】：新疆大学资源与环境科学学院绿洲生态教育部重点实验室;新疆交通职业技术学院;
【基金】：国防科技工业局高分辨率对地观测重大专项(民用部分)项目“中亚地区跨境河流水资源利用开发遥感监测系统”(编号:95-Y40B02-9001-13/15-03-01) 教育部新世纪优秀人才支持计划项目“区域水盐遥感监测与模拟方法研究”(编号:NCET-12-1075) 2014年新疆研究生科研创新项目“基于国产高分卫星影像的水资源开发利用遥感监测系统”(编号:XJGRI2014022)共同资助
【分类号】：TP751

【相似文献】