摘要
利用ETM遥感数据提取反映生态环境的植被、土壤亮度、湿度、热度指数,结合气象和其它地学辅助信息,经过对因子进行相关性分析从每类因子中选取与遥感本底值相关系数最大的指数作为评价指标。以遥感本底值为因变量和所筛选的评价指标为自变量建立多元线性回归方程。利用该模型对福建省2001年生态环境质量进行评价,结果表明福建省生态环境质量总体较好,在空间分布上内陆山区优于沿海地区,西部和北部山区生态环境质量较好,城市、裸露山地、遭砍伐的林地及海岸带地区次之。同时,借鉴中国环境监测总站环境质量优劣度评价方法对福建省生态环境质量进行评价,将两种方法的评价结果进行比较,结果显示,两种方法评价结果大体吻合。
In the present study, the vegetation, soil brightness, moisture and heat indices are extracted from multi-band enhanced thematic mapper remote sensing image to describe ecosystem status. Pearson correlation analysis was applied to find the relationship between the background value of remote sensing and these indices, climate data, and olher geographical auxiliary information. In each index type, there was an index was selected as the evaluation index for its correlation variables was the biggest. These indices were considered as independent variables, the background value of remote sensing was considered as dependent variable, and a regression equation of ecological environment background value was built using multilinear regression analysis. Then the ecological environment background value of the whole Fujian province was calculated using this regression equation. The result was compared with the result assessed by the eco-environment quality evaluation, which was used by the China national environmental monitoring center. The tendency of ecological environment quality assess by the two method was uniform. The general ecological environment qualily of Fujian province was good. The ecological environment quality of mountain region in west and north was better, followed by the town, eroded/deforested hill, and coastland.
出处
《遥感技术与应用》
CSCD
2006年第1期49-54,共6页
Remote Sensing Technology and Application
关键词
生态环境
遥感本底值
指标体系
多元线性回归
Ecological environment, Background vahle of remote sensing, Indices system, Multilinear regression
