张成, 黄芳芳, 尚国琲. 土地生态安全预警系统设计与实现[J]. 中国生态农业学报(中英文), 2020, 28(6): 931-944. DOI: 10.13930/j.cnki.cjea.190782
引用本文: 张成, 黄芳芳, 尚国琲. 土地生态安全预警系统设计与实现[J]. 中国生态农业学报(中英文), 2020, 28(6): 931-944. DOI: 10.13930/j.cnki.cjea.190782
ZHANG Cheng, HUANG Fangfang, SHANG Guobei. Design and implementation of the land ecological security warning system[J]. Chinese Journal of Eco-Agriculture, 2020, 28(6): 931-944. DOI: 10.13930/j.cnki.cjea.190782
Citation: ZHANG Cheng, HUANG Fangfang, SHANG Guobei. Design and implementation of the land ecological security warning system[J]. Chinese Journal of Eco-Agriculture, 2020, 28(6): 931-944. DOI: 10.13930/j.cnki.cjea.190782

土地生态安全预警系统设计与实现

Design and implementation of the land ecological security warning system

  • 摘要: 土地生态安全问题是区域生态安全的核心问题之一。定量化、可视化、自动化的评价和预测土地生态安全状况并进行实时预警,对土地资源的可持续利用具有重要意义。本文以河北省为研究实例,基于PSR(压力、状态、响应)模型构建了土地生态安全评价指标体系,采用投影寻踪模型对土地生态安全状况进行评价,采用主成分相关分析法诊断土地生态安全的主要影响因子,采用空间差异系数模型分析了土地生态安全的时空格局,采用马尔科夫预测模型对土地生态安全水平进行预测,通过划分土地生态安全预警等级建立了预警机制,并利用MATLAB的图形用户界面(GUI)开发了土地生态安全预警系统。结果表明:1)2010-2018年,河北省土地生态安全指数呈不断增长态势,由0.300上升到0.611,年均增长率为12.92%,土地生态安全状态由"恶化级"转变为"敏感级",预警等级由"巨警"转变为"中警",土地生态安全总体水平仍然较低。2)土地生态安全主要限制因子是人口密度、工业化率、单位播种面积农药负荷、单位土地工业三废负荷、城市建设用地比重、工业用地比重和GDP能耗等。3)河北省各地级市土地生态安全区域差异性不断缩小,近年趋于平稳,至2018年,空间差异系数为32.54%,各市之间的差异性仍然不容忽视,大部分地级市土地生态安全状态处于"敏感级",预警等级为"中警",土地生态安全水平有待进一步提高。4)2019-2025年,河北省土地生态安全指数呈稳步上升趋势,到2025年为0.834,达到"较安全级",预警等级为"轻警",土地生态朝着良性方向发展的潜力较大。

     

    Abstract: Land ecological security is one of the core issues in regional ecological security. Quantitative, visual, and automatic evaluation and prediction of land ecological security status and real-time warning are of great significance for the sustainable use of land resources. Taking Hebei Province as an example, an index system of land ecological security was constructed based on the pressure-state-response (PSR) model. In addition, a projection tracking model was used to evaluate the land ecological status, a principal component correlation analysis model was used to identify the main influencing factors of land ecological security, and the spatial difference coefficient model was used to analyze the spatial and temporal pattern of land ecological security. The Markov prediction model was adopted to predict the land ecological security level, an early warning mechanism was established by dividing the early warning levels of land ecological security, and the land ecological security warning system was developed by using the graphical user interface (GUI) of MATLAB. The results showed that:1) From 2010 to 2018, the land ecological security index of Hebei showed an overall increasing trend, shifting from 0.300 to 0.611, with an average annual growth rate of 12.92%. The status of the land ecological security had changed from "deteriorating grade" to "sensitive grade". The warning level had changed from "super-severe warning" to "moderate warning". However, the overall level of land ecological security was still low. 2) The main limiting factors of land ecological security were population density, industrialization rate, pesticide input per unit area of cultivated land, load of industrial wastes per unit area of land, proportion of urban construction land, proportion of industrial land, and energy consumption per 10 000 ¥ GDP. 3) The regional differences in land ecological security in different prefecture-level cities of Hebei Province had been decreasing continuously and became stable in recent years. By 2018, the coefficient of spatial difference was 32.54%, and the differences between cities still cannot be ignored. The state of land ecological security in most prefecture-level cities was at "sensitive level", and the warning level was "moderate warning". The level of land ecological security needs to be further improved. 4) From 2019 to 2025, the land ecological security index of Hebei Province is predicted to show a steady upward trend, and by 2025, it predicted to be 0.834, reaching the "less security level, " with a warning level of "slight warning." There is now greater potential for land ecology to develop in a benign direction.

     

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