首页|期刊导航|西南林业大学学报|基于RSEI模型的泰顺县生态环境质量评价及驱动力分析

基于RSEI模型的泰顺县生态环境质量评价及驱动力分析OA

Research on the Assessment and Motivating Factors of Ecological Environment Quality in Taishun County Based on the RSEI Model

中文摘要英文摘要

基于2016-2020年Landsat8遥感影像、DEM与森林资源一张图数据,构建遥感生态指数,结合主成分分析与回归模型,定量评估生态环境质量的动态变化及驱动机制.结果表明:RSEI指数呈先升后降趋势,2018年达到峰值0.711,2020年回落至0.697,总体增幅1.2%.生态环境质量等级以"优""良"为主(年均占比71%),但"较差""差"等级面积占比由11.5%增至13.1%,退化风险显著.生态环境质量变化集中于坡度5°~30°与海拔500~1000m区域,南坡退化面积显著高于北坡.建设用地扩张与气候干热化是主要负向驱动因子,植被覆盖与湿度为正向调控因素.泰顺县生态环境质量呈现"整体稳定、局部退化"特征,需加强建设用地管控与生态修复工程,重点关注南坡及高海拔区域.

Based on Landsat 8 remote sensing imagery,Digital Elevation Model(DEM),and Integrated Forest Resources Map data from 2016 to 2020,this study constructed the Remote Sensing Ecological Index(RSEI).Combining Principal Component Analysis and regression modeling,we quantitatively assessed the spati-otemporal dynamics of eco-environmental quality and its driving mechanisms.The results indicate that the RSEI exhibited a trend of increasing initially and then decreasing,peaking at 0.711 in 2018 before declining to 0.697 in 2020,with an overall increase of 1.2%.Eco-environmental quality grades were predominantly"Excellent"and"Good"(annual average proportion:71%).However,the area proportion of"Poor"and"Very Poor"grades in-creased from 11.5%to 13.1%,indicating significant degradation risks.Changes in eco-environmental quality were concentrated in areas with slopes of 5°-30° and elevations of 500-1000 m.Degraded areas were significantly more extensive on south-facing slopes than on north-facing slopes.Expansion of construction land and a regional drying-warming climate trend were identified as the primary negative driving factors,while vegetation coverage and humidity acted as positive regulators.This study concludes that Taishun County exhibits a pattern of"overall stability with localized degradation"in eco-environmental quality.To address this,enhanced management of con-struction land and implementation of ecological restoration projects are recommended,with particular focus on south-facing slopes and high-elevation areas.

邬枭楠;方婷轩;孟森;伊力塔;王剑武

浙江省森林资源监测中心,浙江 杭州 310020||浙江农林大学林业与生物技术学院,浙江 杭州 311300浙江省生态环境监测中心,浙江 杭州 310012泰顺县自然资源和规划局,浙江温州 325500浙江农林大学林业与生物技术学院,浙江 杭州 311300浙江省森林资源监测中心,浙江 杭州 310020

资源环境

生态环境遥感生态指数时空分异地形效应驱动因素

ecological environmentremote sensing ecological indexspatiotemporal differentiationterrain effectmotivating factor

《西南林业大学学报》 2026 (3)

100-107,8

浙江省"尖兵""领雁"研发攻关计划项目(2022C02019)资助.

10.11929/j.swfu.202503033

评论