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基于NDVI-Albedo特征空间的沙漠化动态变化研究——以准格尔盆地南缘为例
引用本文:任艳群,刘海隆,唐立新,姜亮亮,安小艳.基于NDVI-Albedo特征空间的沙漠化动态变化研究——以准格尔盆地南缘为例[J].水土保持通报,2014(2):267-271.
作者姓名:任艳群  刘海隆  唐立新  姜亮亮  安小艳
作者单位:石河子大学水利建筑工程学院, 新疆石河子 832000;石河子大学水利建筑工程学院, 新疆石河子 832000;兵团建设交通有限公司, 新疆石河子 832000;石河子大学水利建筑工程学院, 新疆石河子 832000;石河子大学水利建筑工程学院, 新疆石河子 832000
基金项目:国家重点基础科学研究发展计划(973)项目"气候变化对西北干旱期水循环影响机理与水资源安全研究"(2010CB951003);国家科技支撑计划课题(2012BAH27B03;STSN-05-32);新疆研究生科技创新项目(XJGRI2013056)
摘    要:土地沙漠化是干旱区主要生态环境问题之一,也是干旱区农业发展的重要制约因子。以新疆农八师石河子垦区150团为研究区域,基于TM遥感影像,计算了归一化植被指数(NDVI)、地表反照率(Albedo)等指标,通过建立NDVI—Albedo特征空间,对研究区沙漠化的等级进行划分。将研究区的沙化土地分为极重度、重度、中度、轻度沙漠化土地,并通过地面调查验证,对其精度进行了评价。对2000,2005和2010年3期数据进行分类处理,并对这3期的沙漠化信息进行了分析。结果表明,利用该方法的分析精度满足研究要求;研究区通过10a的发展变化,其沙漠化状况得到了有效改善。

关 键 词:遥感  沙漠化  植被覆盖度  干旱区
收稿时间:2013/4/23 0:00:00
修稿时间:2013/5/27 0:00:00

A Study on Dynamic Changes of Desertification in South Edge of Junggar Basin Based on NDVI-Albedo Features
REN Yan-qun,LIU Hai-long,TANG Li-xin,JANG Liang-liang and AN Xiao-yan.A Study on Dynamic Changes of Desertification in South Edge of Junggar Basin Based on NDVI-Albedo Features[J].Bulletin of Soil and Water Conservation,2014(2):267-271.
Authors:REN Yan-qun  LIU Hai-long  TANG Li-xin  JANG Liang-liang and AN Xiao-yan
Institution:College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi, Xinjiang 832000, China;College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi, Xinjiang 832000, China;Xinjiang Construction Transportation Limited Company, Shihezi, Xinjiang 832000, China;College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi, Xinjiang 832000, China;College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi, Xinjiang 832000, China
Abstract:Desertification is not only one of the most serious ecological environment problems but also the limiting factor of the development of agriculture in arid areas. This paper took the area of 150 regiment in Shihezi City of Xinjiang Uyghur Autonomous Region as the study area, and used TM images to derived the normalized difference vegetation index(NDVI) and surface Albedo, and to classify desertification grade of study area by establishing NDVI-Albedo feature space. Desertified land in the study area can be divided into very severely desertified, severely desertified, moderately desertified, and mild desertified. The accuracy of the monitoring was tested with the ground investigation, and the result showed that the accuracy meet the requirement of the study. With the same method, we classified desertification area in 2000, 2005 and 2010, and analyzed the dynamic changes of desertification three periods. The analysis showed that the development of desertification has been effectively controlled after 10 years.
Keywords:remote sensing  desertification  vegetation coverage  arid area
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