文献类型：期刊文献

中文题名：面向对象的沙化土地信息提取

英文题名：Desertification Land Information Extraction Based on Object-Oriented Classification Method

作者：冯益明[1] 郑冬梅[2] 智长贵[2] 姚爱冬[1] 高志海[3]

第一作者：冯益明

机构：[1]中国林业科学研究院荒漠化研究所;[2]国家林业局调查规划设计院;[3]中国林业科学研究院资源信息研究所

年份：2013

期号：1

起止页码：126-133

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

基金："沙化土地类型高分遥感识别与精确分类技术"(E0305/1112/03);"中国干旱区生态系统碳储量估算技术合作研究"(2011-4-78)

语种：中文

中文关键词：SPOT5影像;面向对象;沙化土地;信息提取;遥感

外文关键词：SPOT5 image; object-oriented classification method; desertification land; information extraction;remote sensing

分类号：S757

摘要：以沙化土地典型分布区——甘肃省民勤县为研究对象,以高空间分辨率影像SPOT5与30mDEM为主要数据源,采用面向对象的影像分析方法,对影像进行多尺度、多层次的分割、合并,在此基础上,通过构建多重规则集,对影像进行基于知识的模糊分类,可较为准确地实现沙化土地信息的识别与提取。本文为解决基于高空间分辨率影像进行沙化土地信息准确提取提供一个有效途径,为防沙治沙决策提供科学依据。
Desertification of land was the significant environmental issue threatening human existence. Desertification land area was 1 731 100 km2 in 2009, occupying 18.03% of China＇ s total land area. Remote sensing is an effective method monitoring the desertification land. With the development of remote sensing technology, high spatial resolution remote sensing image gradually becomes main data source of resolving the desertification land information extraction. The traditional remote sensing image classification method based on pixel has some difficulties in treating the high spatial resolution remote sensing images, however, the object-oriented classification method might overcame the limit of using the pixel as basic treatment unit. Minqin County, a typical desertification land distribution region, was used as studied object in this paper, the high spatial resolution remote sensing images SPOT5 and 30 m DEM were used as date sources, the multi-scale and multi-level segmentation of remote sensing images was conducted by using the object-oriented classification method. Based on these results, the remote sensing images were subjected to fuzzy image classification based on knowledge by constructing multiset, and thus relatively accurately realize the recognition and extraction of desertification land information. This paper would provide an effective path for resolving the accurate extraction of desertifieation land information based on the high spatial resolution remote sensing images and also provide scientific proofs for sand prevention and control.