基于多源数据的自然生态空间分类体系构建及其识别

研究目的:探讨市县尺度下自然生态空间分类体系和多源数据下自然生态空间识别方法。研究方法:采用归纳比较法构建自然生态空间分类体系,通过综合分析法建立多分类体系转换机制,运用GIS空间分析法识别自然生态空间。研究结果:(1)市县级自然生态空间是指生产性空间和承载性空间以外,以发挥土地生态系统服务功能为主导,以提供生态产品为主,对维护区域生态系统稳定性,保障区域生态安全格局具有重要作用的用地空间;(2)自然生态空间可分为基础生态空间和人工生态空间两个一级类,10个二级类,26个三级类;(3)2015年鹤壁市自然生态空间总量606.08 km~2,其中基础生态空间554.41 km~2,人工生态空间51.67 km~2。研究结论:依据市县尺度自然生态空间分类体系,运用多源数据融合转换识别方法能快速准确识别自然生态空间数量和空间分布。

Construction of Classification System and Identification of Ecological Spatial based on Multi-sources Data

The purpose of this paper is to explore the classification system of ecological space at municipality and county levels as well as the identification method of ecological space with multi-sources data, to provide reference for pilot work of ecological space use control, and to further promote the modernization of national governance systems and governance capabilities in ecological field. Taking Hebi City as a study area, the research employed the method of inductive comparison to construct the classification system of ecological space, the method of comprehensive analysis to establish conversion mechanism of classification system, and the method of GIS spatial analysis to identify ecological space. The results show that ecological space refers to the land space, apart from the productive and carrying space, that plays an important role in maintaining the ecosystem stability of the region and ensuring the regional ecological security pattern, has ecosystem service functions, and provides ecological products. The ecological space can be divided into two primary types: basic ecological space and artificial ecological space, including 10 secondary types and 26 tertiary types. The total area of ecological space in Hebi was 606.08 km2 in 2015, of which the basic ecological space was 554.41 km2 and the artificial ecological space was 51.67 km2. In conclusion, the quantity and spatial distribution of ecological space can be identified promptly and accurately by using the identification method of converting and fusing multi-sources data according to the ecological space classification system at municipality and county scale.