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探索了一种基于自组织特征映射神经网络算法识别区域尺度生态系统服务功能分区的新方法。在此基础上,依据新千年生态系统评估框架构建了生态服务功能评价指标体系,并运用自组织特征映射神经网络算法开展了生态服务功能空间聚类分析,在1km栅格上识别并排定了各类生态服务功能的重要性。在案例区锡林郭勒盟的研究表明,利用基于自组织特征映射神经网络算法划分出的该区6个生态服务功能分区比较科学、合理,所形成的分区结论为案例区生态系统的可持续管理提供有时空针对性的决策参考信息。
This paper explores a new method to identify service-functional zoning of regional scale ecosystem based on self-organizing feature mapping neural network algorithm. On this basis, the evaluation index system of ecological service function was constructed according to the framework of the New Millennium Ecosystem Assessment. The self-organizing feature mapping neural network algorithm was used to carry out the spatial clustering analysis of ecological service function, identified and scheduled on the 1km grid The importance of various types of ecosystem services. The research on Xilin Gol League in the case area shows that the partitioning of six ecological service functions in the district, which is based on the self-organizing feature mapping neural network algorithm, is more scientific and reasonable. The conclusion of the district is provided for the sustainable management of the ecosystem in the case area Time-space-oriented decision-making reference information.