首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于MODIS和NOAA/AVHRR的荒漠化遥感监测方法
引用本文:刘爱霞,王长耀,王静,邵晓梅.基于MODIS和NOAA/AVHRR的荒漠化遥感监测方法[J].农业工程学报,2007,23(10):145-150.
作者姓名:刘爱霞  王长耀  王静  邵晓梅
作者单位:1. 国土资源部土地利用重点实验室中国土地勘测规划院,北京,100035
2. 中国科学院遥感应用研究所,北京,100101
基金项目:科技部社会公益研究项目;数字制图与国土应用工程国家测绘局重点实验室开放研究基金
摘    要:土地荒漠化是中国西部最严重的生态环境问题,荒漠化遥感监测技术是掌握荒漠化发展趋势的重要手段。基于空间分辨率为1 km的NOAA/AVHRR和MODIS遥感数据,首先依据湿润指数法确定了荒漠化范围和气候分区。然后选取出了可以反映不同荒漠化特征,并且能够通过中低分辨率的NOAA/AVHRR和MODIS遥感影像反演出来的5个荒漠化遥感监测指标,通过精度评价分析,确定了最佳指标组合。由于MODIS和NOAA/AVHRR数据的影像特征存在较大差异,针对每一气候分区, 建立了分别适用于MODIS和NOAA/AVHRR数据的两套遥感指标分类体系。通过不同分类方法的比较,确定了最佳分类方法-决策树分类法。通过对中国1995年和2001年的荒漠化动态变化状况进行了分析,结果表明,本文提出的荒漠化遥感监测方法,不仅能够成功地进行大尺度的荒漠化遥感监测,而且能够取得较好的监测效果。

关 键 词:MODIS数据  NOAA/AVHRR数据  荒漠化  遥感监测
文章编号:1002-6819(2007)10-0145-06
收稿时间:2006/9/14 0:00:00
修稿时间:2006-09-142007-08-25

Method for remote sensing monitoring of desertification based on MODIS and NOAA/AVHRR data
Liu Aixi,Wang Changyao,Wang Jing and Shao Xiaomei.Method for remote sensing monitoring of desertification based on MODIS and NOAA/AVHRR data[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(10):145-150.
Authors:Liu Aixi  Wang Changyao  Wang Jing and Shao Xiaomei
Institution:Key Laboratory of Land Use, China Land Surveying and Planning Institute, Beijing 100035, China;Key Laboratory of Land Use, China Land Surveying and Planning Institute, Beijing 100035, China;Institute of Remote Sensing Applications, Chinse Academy of Sciences, Beijing 100101, China;Key Laboratory of Land Use, China Land Surveying and Planning Institute, Beijing 100035, China
Abstract:Desertification is one of the most serious ecological and environmental problems in the west of China. Understanding the distribution and development trend of desertification provides researchers important scientific basis for desertification control and rehabilitation. In this paper the authors proposed a method suitable for large-scale desertification monitoring using remote sensing techniques. First, five desertification indexes(MSAVI, FVC, Albedo, LST and TVDI) suitable for large-scale desertification monitoring using remote sensing technique were selected. In terms of the desertification climate types, the potential extent of desertification in China was respectively divided into four categories: dry sub-humid areas, semi-arid areas, arid areas, high and cold areas. Second, different desertification index systems were built for each area. Then based on analysis and comparison of current retrieval algorithms, the authors utilized a suitable algorithm on large scale to retrieve five desertification indexes with ten-day NOAA/AVHRR data set in 1995 and 16-day MODIS data set in 2001 in China. By assessing the classification accuracies of three types of classifiers, the authors selected decision tree classifier for desertification monitoring. Supported by desertification index system and the database of desertification indexes, the desertification status in China in 1995 and 2001 was classified by decision tree classifier, and analysis of desertification changes from 1995 to 2001 was also completed. Statistical result showed that the speed of desertification development was faster than that of rehabilitation, there was a trend of development as a whole and improvement locally in desertificated areas in China. The desertification monitoring results confirmed the practicability of the method founded in this paper for desertification monitoring.
Keywords:MODIS data  NOAA/AVHRR data  desertification  remote sensing monitoring
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《农业工程学报》浏览原始摘要信息
点击此处可从《农业工程学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号