首页|期刊导航|西南林业大学学报|基于改进遥感生态指数的曲靖市生态环境评价及驱动力分析

基于改进遥感生态指数的曲靖市生态环境评价及驱动力分析OA

Ecological Environment Evaluation and Driving Force Analysis of Qujing Based on an Improved Remote Sensing Ecological Index Model

中文摘要英文摘要

以2000年、2005年、2010年、2015年、2020年的Landsat TM/OLI遥感影像为主要数据源,构建改进的喀斯特遥感生态指数.采用Sen斜率估计和Mann-Kendall趋势检验相结合的方法,对曲靖市2000-2020年的生态环境质量进行时空变化分析;同时,采用最优参数地理探测器模型优化空间数据的分区效应,研究不同因素对生态环境质量空间异质性的影响.结果表明:2000-2020年,曲靖市生态环境质量整体改善,具有显著的空间异质性.在空间上呈现"西北低东南高"的分布格局,且"优"和"良"级别的面积逐步增加.根据Sen斜率和Mann-Kendall检验趋势分析,生态环境质量改善的区域面积占比超过60%,但仍有部分区域出现退化现象.最优参数地理探测器模型的结果显示,生态环境质量受多因素影响,其中NPP、土地利用类型、DEM和气温影响显著,且各驱动因子的交互作用进一步加深了对生态质量的影响.研究结果可为喀斯特地区的生态环境质量遥感评价提供方法参考,有助于推进喀斯特地区的生态环境保护和区域社会经济可持续发展.

This study uses Landsat TM/OLI remote sensing images from 2000,2005,2010,2015,and 2020 to construct an improved karst remote sensing ecological index.The temporal and spatial changes in the quality of the ecological environment in Qujing City from 2000 to 2020 were analyzed using Sen's slope estimator and the Mann-Kendall trend test.The optimal parameter geographic detector model was further used to optimize the zon-ing effect of spatial data and quantify the impact of different factors on the spatial heterogeneity of ecological en-vironment quality.The results show that from 2000 to 2020,the overall quality of the ecological environment in Qujing City has improved,with significant spatial heterogeneity.In terms of space,it presents a distribution pat-tern of"low in the northwest and high in the southeast",and the area of"excellent"and"good"levels has gradu-ally increased.According to the trend analysis using the Sen slope and MK tests,the area with improved ecologic-al environment quality accounts for more than 60%,although some areas still show degradation.The results of the optimal parameter geodetector model show that ecological environment quality is influenced by multiple factors,among which NPP,land use type,DEM,and temperature have significant effects,and the interactions among these driving factors further amplify their impact on ecological quality.These findings provide a methodological reference for the remote-sensing evaluation of ecological environment quality in karst areas and offer insights that promote ecological environment protection and the sustainable development of the regional social and economic in karst areas.

毛青文;张超;周礼;王彤

西南林业大学林学院,云南 昆明 650233西南林业大学林学院,云南 昆明 650233||西南林业大学云南省山地农村生态环境演变与污染治理重点实验室,云南 昆明 650233西南林业大学林学院,云南 昆明 650233西南林业大学林学院,云南 昆明 650233

资源环境

遥感生态指数生态环境质量喀斯特地理探测器

RSEIecological environment qualitykarstgeographic detector

《西南林业大学学报》 2026 (7)

104-111,8

国家自然科学基金项目(32160405)资助.

10.11929/j.swfu.202503010

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