基于自组织特征映射模型(SOFM)网络的中国自然资源生态安全区划  

Ecological security regionalization of natural resources in China based on Self-Organizing Feature Map neural network

作　　者：邹易 蒙吉军[1] 吴英迪 魏婵娟 程浩然 马宇翔 ZOU Yi;MENG Jijun;WU Yingdi;WEI Chanjuan;CHENG Haoran;MA Yuxiang(Key Laboratory of Earth Surface Processes of Ministry of Education,College of Urban and Environmental Sciences,Peking University,Beijing 100871,China;Department of Geography,Geomatics and Environment,University of Toronto,3359 Mississauga Road,Mississauga ON L5L 1C6,Canada)

机构地区：[1]北京大学城市与环境学院,地表过程分析与模拟教育部重点实验室,北京100871 [2]多伦多大学地理、地理信息与环境系,加拿大安大略省密西沙加市L5L 1C6

出　　处：《生态学报》2024年第1期171-182,共12页Acta Ecologica Sinica

基　　金：教育部哲学社会科学研究重大课题攻关项目(19JZD023);国家社会科学基金重大项目(20ZDA085)。

摘　　要：自然资源生态安全是国家安全的重要组成部分,自然资源生态安全区划对保障区域可持续发展提供了重要途径。基于自然资源数据、生态环境数据和相关区划资料,从生态敏感性与生态服务重要性角度构建了自然资源生态安全评价指标体系,进而揭示了中国自然资源生态安全的空间格局;通过建立区划的原则和指标,按照一级区主要反映自然资源空间分布格局,二级区主要揭示自然资源生态安全水平的差异,采用SOFM网络制订了中国自然资源生态安全区划方案。结果显示:(1)中国自然资源生态安全水平整体偏低,以中警与重警状态区域为主,安全和较安全状态的区域仅占24.22%,其中低安全等级区多分布于400mm等降水量线以西的干旱、半干旱区,高安全等级区则集中分布于水热资源与生物资源较为丰富的东南部地区;(2)中国自然资源生态安全区划方案包括8个一级区与27个二级区,总结归纳各大区自然资源的特征和威胁生态安全的问题,并针对二级区自然资源生态安全状况提出了对策建议。研究结果可为分区、分类推进全国自然资源可持续利用和国土空间优化提供理论支持与决策依据。Ecological security of natural resource is an important component of national security,and the regionalization of natural resource ecological security provides an essential approach to ensure regional sustainable development.Based on the natural resource data,ecological environment data,and relevant regionalization materials,this article constructs a natural resource ecological security evaluation index system from the perspectives of ecological sensitivity and ecological service importance,then reveals the spatial pattern of China′s natural resource ecological security.By establishing the principles and indicators of regionalization,according to the fact that the first-level area mainly reflects the spatial distribution pattern of natural resources,and the second-level area mainly reveals the difference in natural resource ecological security level,the Self-Organizing Feature Map(SOFM)neural network is used to formulate a regionalization scheme for the natural resource ecological security in China.The results show that:(1)The overall level of ecological security of natural resource in China is relatively low,with most of the areas being classified as having moderate to high levels of warning.Only 24.22%of the regions have a safe or relatively safe state.The areas with low-security levels are primarily located in the arid and semi-arid regions west of the 400mm precipitation line.On the other hand,the areas with high-security levels are concentrated in the southeastern parts of the country,where water,heat,and biological resources are relatively abundant.(2)The natural resource ecological security regionalization scheme for China includes 8 first-level zones and 27 second-level zones.We summarize a comprehensive summary and analysis of the unique features and ecological security threats of natural resources in each major region.Moreover,we present practical recommendations to address the challenges faced by natural resources in the secondary regions to enhance their ecological security status.The research resul

关 键 词：自然资源生态安全 自组织特征映射模型(SOFM)网络 区划方案 

分 类 号：F32[经济管理—产业经济]