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作 者:卢远[1] 林年丰[1] 汤洁[1] 王娟[1] 杜崇[1]
机构地区:[1]吉林大学环境与资源学院,吉林长春130026
出 处:《地理与地理信息科学》2003年第2期24-27,共4页Geography and Geo-Information Science
基 金:国家自然科学基金资助项目(40072093)
摘 要:以松嫩平原西部土地退化典型地区———吉林省通榆县为例,在RS和GIS集成技术支持下,利用不同时相的TM数据,采用线性光谱混合模型方法,选用植被、盐碱地、裸沙地、沼泽地、苇地作为最终光谱单元进行线性光谱分解,依据盐碱地和沙地加权和分量,将试点区的土地退化划分为未退化、轻度退化、中度退化和重度退化四个等级进行动态监测,并分析土地退化的数量、空间分布与动态过程。In this paper,the authors used two temporal Landsat TM/ETM+ data of 1989 and 2001 to evaluate the land degradation in Tongyu County of Jilin Province,a typical area of land degradation in the west of Songnen Plain. Spectral mixture model (SMM) was adopted to separate the end-members of land degradation from the image results of Minimum Noise Fraction(MNF). SMM is an image-processing technique used for the analysis of airborne hyperspectral remote-sensing data which consist of a large number of spectral bands,typically over 100. Five end-members were derived from the image analysis,including vegetation,salina,desert,marsh, reed swarm. The authors graded land degradation into four levels according to the weight sum of salina and desert. With the support of ENVI and ARC/INFO,The authors also analyzed the amount,spatial distribution and dynamic change of land degradation in the study area.
分 类 号:TP79[自动化与计算机技术—检测技术与自动化装置]
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