基于Hyperion数据的滇西北高寒山区高山松典型森林生态系统健康分级研究

The Health Classification of Pinus densata Typical Forest Ecosystem in Alpine Region of Northwestern Yunnan Based on Hyperion Data

选取香格里拉高寒山区典型森林生态系统高山松纯林为研究对象,以Hyperion影像为数据源,在利用敏感性分析法筛选高山松林健康评价指标体系基础上,建立研究区基于像元的森林健康指数综合评判模型（FHI）,运用层次分析法和德尔菲法确定FHI模型中的各项指标权重,并结合地面样地调查数据,将研究区森林健康指数划分为健康、 亚健康、 中等健康和不健康4个等级.结果表明：研究区遥感影像的森林健康指数为-0.25-75.34,平均值为33.23,研究区森林整体处于亚健康状态;其中不健康森林面积约占森林总面积的16.24%,中度健康面积约为31.60%,亚健康森林面约为25.80%,健康面积约为26.36%.

The pure Pinus densata forest of the typical forest ecosystem in the alpine region of Shangri-La is selected as the research subject and Hyperion images are taken as the data source. Based on using the sensitivity a-nalysis method to screen out the Pinus densata forest′s health evaluation index system, the forest health index com-prehensive evaluation model of the research zone is set up based on image elements. By using the analytic hierarchy process method and the Delphi method, this paper determines various indexes′ weighted values and combines the investigated data of the ground surface to classify the research zone′s forest health indexes into four levels, including healthy, sub-healthy, moderately healthy and unhealthy. Results have shown that the forest health index of the research zone′s remote images is in the range of -0. 25-75. 34, and the average value is 33. 23, the research zone′s forest is generally in the sub-healthy state. The unhealthy area, moderately healthy area, sub-healthy area and healthy area occupies of the forest′s total area is 16. 24%, 31. 60%, 25. 80% and 26. 36%, re-spectively.