基于大数据分析框架的生态脆弱型人地系统模式研究

Study on the Model of Ecological Vulnerable Human-land System based on Big Data Analysis Framework

针对生态脆弱型人地系统模式研究中存在的数据处理繁杂、模式识别偏主观、内在机理复杂等问题,提出了基于云平台及大数据方法的模式分析框架。通过遥感及社会经济云平台实现数据的云上收集及处理,利用自组织映射神经网络聚类(Self-Organizing Map,SOM)方法实现无先验知识的模式识别;同时利用知觉图从社会经济发展与生态友好性两个角度分析变化轨迹,利用关联规则方法筛选社会经济与生态环境之间的潜在规律。以“一带一路”65国进行实验分析,实验结果将“一带一路”65个国家有效划分为10类模式,并分析了10类模式的变化轨迹及关系规律。结果表明:该分析框架能够快速实现数据获取及处理、人地系统多模式识别、变化轨迹可视化和规律探测等功能,有效弥补了人地系统多模式研究中的不足。

To solve the problems of complex data processing,subjective model recognition and complex internal mechanism in the study of ecological vulnerable human-land system,a model analysis framework based on cloud platform and big data methods was proposed.Remote sensing and socio-economic cloud platform are used to collect and process data.Self-organizing mapping neural network clustering(SOM)method is used to recognize model without prior knowledge.The trajectories was analyzed from the perspective of social-economic development and ecological friendliness by using perceptual map,and the laws between social economy and ecological environment was selected by using association rules.The experimental analysis was carried out in 65 Belt and Road countries.The experimental results effectively divided 65 countries into 10 models,and analyzed the trajectories and relationship rules of 10 models.The results show that the framework can perform the functions of data acquisition and processing,multi-model recognition of human-land system,trajectories visualization and rules detection.It effectively makes up for the deficiencies in the multi-model study of human-land system.