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基于物元模型的汾河流域土地生态安全评价

郭利刚1,冯珍珍2,刘庚3*,石瑛4,王捷4,林菲3,马小红3   

  1. 1太原师范学院管理系, 山西晋中 030619;2郑州大学旅游管理学院, 郑州 450001; 3太原师范学院汾河流域科学发展研究中心, 山西晋中 030619;4太原师范学院生物系, 山西晋中 030619)
  • 出版日期:2020-06-10 发布日期:2020-06-10

Evaluation of land eco-security in Fenhe River Basin based on matter-element model.

GUO Li-gang1, FENG Zhen-zhen2, LIU Geng3*, SHI Ying4, WANG Jie4, LIN Fei3, MA Xiao-hong3   

  1. (1Department of Management, Taiyuan Normal University, Jinzhong 030619, Shanxi, China; 2School of Tourism Management, Zhengzhou University, Zhengzhou 450001, China; 3Research Center for Scientific Development in Fenhe River Valley, Taiyuan Normal University, Jinzhong 030619, Shanxi, China; 4Department of Biology, Taiyuan Normal University, Jinzhong 030619, Shanxi, China).
  • Online:2020-06-10 Published:2020-06-10

摘要: 土地生态安全关乎人类生存与发展,是土地资源可持续利用的核心。研究土地生态安全对于揭示区域内土地利用安全特征,促进人口、资源与环境的协调发展具有重要意义。本文以汾河流域为研究区域,根据“压力-状态-响应(PSR)”模型,构建土地生态安全评价指标体系,采用层次分析法和熵值法确定指标权重,运用物元模型对汾河流域土地生态安全状况进行评价。结果表明:2006年汾河流域土地生态安全状况处于“向安全转化”状态,2012和2017年均处于“向较安全转化”状态,整体发展状况较稳定;2006—2017年,景观破碎度、人均水资源量和河网密度是制约区域土地生态安全水平的主要因素;2017年处于“安全”状态的县(市/区)占15%,多数集中在上游,上游土地生态安全水平整体高于中下游地区。

关键词: BP神经网络, 主成分分析, 高光谱, 植被指数, 叶绿素含量, 红边参数

Abstract: Land ecological security, the core of sustainable utilization of land resource, is relevant to human well-being. The study of land ecological security is of great significance to reveal the characteristics of land use security and promote the coordinated regional development of population, resources and environment. Using the “PressureState-Response (PSR)” model, we constructed an evaluation index system of land ecological security in Fenhe River Basin. The index weight was determined by AHP and entropy method, while the matter-element model was used to evaluate land ecological security. In 2006, the land ecological security of Fenhe River Basin was at the state of “transforming to safe status”. In 2012 and 2017, it was at the state of “transforming to moderately safe status”, with overall situation being stable. From 2006 to 2017, landscape fragmentation, per capita water resource and river network density were the main factors restricting land ecological security. In 2017, 15% of the counties (cities/districts) were at the “safe” state, with most of which being concentrated in the upstream area. Land ecological security in the upstream area was generally higher than that in the middle and downstream areas.

Key words: hyperspectral, red edge parameters, vegetation index, principal component analysis, BP neural network., chlorophyll content