水土保持通报2024,Vol.44Issue(3) :159-170.DOI:10.13961/j.cnki.stbctb.20240528.002

基于RSEI改进模型的生态环境质量评价及驱动机制研究——以湖南省桃江县为例

Evaluation and Driving Mechanism of Eco-environmental Quality Based on Improved RSEI Model—A Case Study at Taojiang County,Hunan Province

陈创 聂平静 黄凤寸 樊东 向莉 曾剑 陈方伟 胡庚辛
水土保持通报2024,Vol.44Issue(3) :159-170.DOI:10.13961/j.cnki.stbctb.20240528.002

基于RSEI改进模型的生态环境质量评价及驱动机制研究——以湖南省桃江县为例

Evaluation and Driving Mechanism of Eco-environmental Quality Based on Improved RSEI Model—A Case Study at Taojiang County,Hunan Province

陈创 1聂平静 2黄凤寸 2樊东 3向莉 2曾剑 2陈方伟 2胡庚辛2
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作者信息

  • 1. 中国地质调查局长沙自然资源综合调查中心,湖南长沙 410600;中国地质大学(北京),北京 100083
  • 2. 中国地质调查局长沙自然资源综合调查中心,湖南长沙 410600
  • 3. 昆明理工大学国土资源工程学院,云南昆明 650031
  • 折叠

摘要

[目的]为了更好地对丘陵地区生态质量进行监测和评价,构建适用于高植被区的改进型遥感生态指数模型,并探索生态质量的影响因素,为湖南省益阳市桃江县兼顾发展与生态的发展提供科学支撑.[方法]针对植被指数(NDVI)在植被茂密区的饱和性缺陷,借助改进型遥感生态指数(MRSEI)量化了桃江县2000-2021年生态环境质量时序变化,并利用最优化参数的地理探测器模型对植被覆盖度、降水、气温、土地利用、海拔、人口密度等6个影响因子进行了驱动力分析.[结果]①与遥感生态指数相比,改进的遥感生态指数模型能够避免高植被覆盖区NDVI饱和性缺陷问题,可以更准确地监测桃江县生态环境.②研究区2000-2021年5期的MRSEI均值分别为0.77,0.84,0.83,0.75和0.79,生态环境质量整体表现良好,具有转好—转差—转好的变化特征.③从生态环境质量成因分析来看,土地利用是影响研究区生态环境质量的关键因子,交互式探测中,土地利用和海拔交互作用最强.[结论]改进的RSEI模型能对高植被地区生态环境质量进行准确的评价.桃江县2000-2021年生态环境质量总体处于良好水平且呈上升趋势.生态环境质量变化主要受到自然和人为因素双重影响.

Abstract

[Objective]An improved remote sensing ecological index model suitable for high vegetation area was constructed to better monitor and evaluate the ecological quality of hilly areas,and the influencing factors of ecological quality were explored,in order to provide scientific support for the balance between development and ecology at Taojiang County,Yiyang City,Hunan Province.[Methods]To address the saturation limitations of the normalized difference vegetation index(NDVI)in densely vegetated areas,the improved remote sensing ecological index(MRSEI)was used to quantify the temporal variation in the ecological environment quality of Taojiang County from 2000 to 2021.Additionally,a geographic detector model with optimized parameters was utilized to analyze the driving forces behind six influencing factors,including vegetation coverage,precipitation,temperature,land use,elevation,and population density.[Results]① Compared with the RSEI model,the MRSEI model more effectively addressed the issue of NDVI saturation in areas with high vegetation cover,enabling a more precise monitoring of the ecological environment in Taojiang County.② The average RSEI values for the five periods from 2000 to 2021 in the study area were 0.77,0.84,0.83,0.75,and 0.79,respectively,indicating a satisfactory performance in ecological environmental quality with a trend of improvement-deterioration-improvement.③ From the analysis of the factors influencing ecological environmental quality,land use emerged as a key determining factor in the study area.In the interactive factor detection analysis,the interaction between land use and elevation was the strongest.[Conclusion]The improved RSEI model could accurately evaluate the eco-environmental quality in high-vegetation areas.The eco-environmental quality of Taojiang County was generally at a good level and showed an upward trend from 2000 to 2021.The change of eco-environmental quality was mainly affected by both natural and human factors.

关键词

核归一化植被指数(kNDVI)/生态环境质量/改进型遥感生态指数(MRSEI)/GEE/地理探测器/驱动机制

Key words

kernel normalized diference vegetation index/ecological environmental quality/modified remote sensing ecology index/google earth engine/geographical detector/driving mechanism

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基金项目

中国地质调查局项目(DD20230478)

湖南省重点研发计划项目(2023SK2066)

出版年

2024
水土保持通报
中国科学院水利部水土保持研究所 水利部水土保持监测中心

水土保持通报

CSTPCDCSCD北大核心
影响因子:0.658
ISSN:1000-288X
参考文献量23
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