基于多源空间数据的中国生态环境综合评价与分析

Comprehensive Assessment and Analysis of China Eco-environment Based on Spatial Data

利用多种来源的不同专题空间数据 ,通过建立生态环境背景指标体系 ,采用空间叠加分析方法 ,实现了大范围的生态环境状况的综合评价。通过计算生态环境背景指数 ,以数值方式比较全面、系统地反映了我国生态环境背景的整体特点以及区域差异 ,可以直接进行全国生态环境背景状况的区域对比研究和主要影响因素分析 ,而且为进一步开展时间序列动态变化监测 ,以及开展针对区域特点的深入研究提供支持。

The paper builds the multi-subject spatial database and the numerical analytical method because regional difference of Chinese ecological environment background is prominent. The ecological environment background condition is synthetically appraised and the index is used to reflect the general characteristics and the regional difference by the 9 kinds of spatial raster database i.e.precipitation, accumulative temperature, temperature, slope,aspect,elevation, NDVI,the building of the national appraisal index system of ecological environment background and the combined function of the GIS. The ecological environment index in divided into 10 grades. The higher the grade, the better the ecological environment is. The results will be beneficial to compare the regional difference of the ecological environment and to study the dynamic change in time series since it reflects objectively the natural characteristics and regional difference of China. The average index of Chinese ecological environment is 5 726. The ecological environment index increases and represents the better condition from Northwest to Southeast. Using the index, the numerical method is built to reflect the ecological environment background and to compare the regional ecological environment background that builds the foundation for future dynamic monitoring. The feature value of the subject index of every cell by the GRID module of ARC/INFO can be calculated to analyze the regional law and dynamic change and to study the main factors that have the effect on the background. The ancillary information can be supplied to help make decision on the resource exploitation and environmental protection pertinently and simultaneously by overlaying the data with the especially spatial data such as land use data.