生态与环境

基于RS和PCA的荒漠化现状综合评价

  • 梁文琼 ,
  • 田淑芳 ,
  • 周家晶
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  • 1.海口市土地测绘院,海南 海口 570125;
    2.中国地质大学(北京)地球科学与资源学院,北京 100083
梁文琼(1987-),女,硕士研究生,研究方向为遥感与地理信息系统.E-mail: liangwenqiong@sina.com

收稿日期: 2013-04-22

  修回日期: 2013-05-27

  网络出版日期: 2015-04-16

基金资助

国土资源部地质调查局华北地区基础地质调查及数据更新项目(1212010811001);黄河流域基础地质环境变迁遥感调查项目(1212010510511)

Comprehensive Assessment of Desertification Status Based on Remote Sensing and Principle Component Analysis

  • LIANG Wen-qiong ,
  • TIAN Shu-fang ,
  • ZHOU Jia-jing
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  • 1. Haikou Land Surveying and Mapping Institute, Haikou 570125, Hainan, China;
    2. School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China

Received date: 2013-04-22

  Revised date: 2013-05-27

  Online published: 2015-04-16

摘要

针对一些荒漠化评价指标无法通过遥感手段直接获取,且简单目视判读或直接分类等评价方法主观性强等问题,提出一种基于遥感与主成分分析相结合的荒漠化现状综合评价方法。研究遵循代表性、综合性、主导性及遥感手段可操作性原则,选取5个荒漠化评价指标,由ETM+数据直接反演得到;并基于先验数据进行主成分分析,确定指标权重,建立综合评价模型,对整个研究区荒漠化现状进行综合评价。研究认为,该方法体现了遥感在大面积环境评价中的优势,且基于统计结果的评价方法更客观,更适用于区域尺度荒漠化评价。

本文引用格式

梁文琼 , 田淑芳 , 周家晶 . 基于RS和PCA的荒漠化现状综合评价[J]. 干旱区研究, 2015 , 32(2) : 342 -346 . DOI: 10.13866/j.azr.2015.02.19

Abstract

Because some of the desertification evaluation indices cannot be directly obtained by remote sensing, and simple visual interpretation or direct classification evaluation methods have strong subjectivity, a comprehensive evaluation method of the desertification status based on remote sensing in combination with principal component analysis was put forward. Five desertification evaluation indices were selected following the representative, comprehensive, predominant and operable principles. These indices were directly obtained from inversed ETM+ data. Comprehensive evaluation model was set up based on principal component analysis of priori data and the determination of indices weight. The present desertification status of the whole study area was evaluated by the model. Results indicate that the model is more objective than that method of analysis and is more suitable for the desertification evaluation at regional scale. And the evaluation effects of the model reflected the superiority of the remote sensing method at large environmental scale.

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