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1990-2020年长江源地区生态环境质量动态变化及驱动力分析

王天宏 蒋馥根 龙依 邓目丽 孙华

南京林业大学学报(自然科学版)2025,Vol.49Issue(3):110-118,9.
南京林业大学学报(自然科学版)2025,Vol.49Issue(3):110-118,9.DOI:10.12302/j.issn.1000-2006.202301017

1990-2020年长江源地区生态环境质量动态变化及驱动力分析

Dynamic changes and driving forces of ecological environment quality in the source region of the Yangtze River from 1990 to 2020

王天宏 1蒋馥根 1龙依 1邓目丽 1孙华1

作者信息

  • 1. 中南林业科技大学林业遥感信息工程研究中心,林业遥感大数据与生态安全湖南省重点实验室,南方森林资源经营与监测国家林业和草原局重点实验室,湖南 长沙 410004
  • 折叠

摘要

Abstract

[Objective]Accurately and efficiently monitoring the spatio-temporal distribution characteristics of the ecological environment quality and its evolving trends in the source area of the Yangtze River is of great significance for maintaining the high-standard protection of the ecological environment.It also serves as a fundamental basis for formulating long-term and effective ecological protection and restoration strategies in the Sanjiangyuan region.The remote sensing ecological index(RSEI)has distinct advantages over traditional evaluation methods relying on single monitoring indices.It boasts rapid assessment capabilities,objectivity,high efficiency,strong visual interpretability,and reliable predictability.Nevertheless,the spatial resolution constraints and the complexity of data acquisition and processing in remote sensing images still present challenges to the large-scale and accurate evaluation of the RSEI.[Method]In this study,the Google Earth Engine(GEE)platform was utilized,with Landsat series images as the data source.Remote sensing images of the Yangtze River source area during the vegetation-growing season(from June to September)from 1990 to 2020 were obtained.Subsequently,long-time-series RSEI data were calculated.To comprehensively analyze the RSEI in the Yangtze River source area from 1990 to 2020,the coefficient of variation was applied to measure its stability,the Sen+Mann-Kendall(Sen+MK)trend analysis was used to explore the spatio-temporal change trends,the Hurst index was employed to predict future evolution,and the trend analysis method was adopted to identify the driving forces behind these changes.[Result](1)From 1990 to 2020,the RSEI values in the Yangtze River source region were predominantly distributed within the range of 0.4-0.6.Geographically,the region exhibited a clear pattern where the RSEI values were higher in the eastern and southern parts and lower in the western and northern parts.(2)The average coefficient of variation of the RSEI in the source region was 6.52%.This indicates that the ecological environment in the eastern and western regions underwent relatively more pronounced fluctuations,while the central region remained relatively stable.Overall,the RSEI showed a slow oscillating trend,with an average annual growth rate of 0.004 7.Spatially,the RSEI presented an overall upward trend,and the area with improved ecological conditions accounted for 83.63%of the total study area.(3)The average Hurst index value of the RSEI in the source region was 0.53,implying that the future changes of the RSEI were more likely to be continuous rather than show anti-sustainability.The future ecological environment quality in the Yangtze River source region was expected to experience continuous improvement,yet the overall trend was relatively mild,and there still existed an underlying risk of degradation.(4)In the Yangtze River source region,the RSEI was positively correlated with air temperature,night-light index,and potential evapotranspiration.This reveals that both natural factors and human activities had a certain degree of influence on the enhancement of the ecological environment quality.[Conclusion]The integration of using GEE for remote sensing data acquisition and time-series data analysis has significant potential for rapidly and comprehensively monitoring the ecological environment quality on a large scale.This approach can offer valuable references and technical support for ecological monitoring and protection efforts in the Sanjiangyuan area,thereby contributing to the sustainable development of the regional ecological environment.

关键词

长江源地区/遥感生态指数(RSEI)/生态环境质量/Google Earth Engine(GEE)/Hurst指数

Key words

Yangtze River source region/remote sensing ecological index (RSEI)/ecological environment quality/Google Earth Engine(GEE)/Hurst index

分类

农业科技

引用本文复制引用

王天宏,蒋馥根,龙依,邓目丽,孙华..1990-2020年长江源地区生态环境质量动态变化及驱动力分析[J].南京林业大学学报(自然科学版),2025,49(3):110-118,9.

基金项目

国家重点研发计划(2017YFC0506502) (2017YFC0506502)

国家林业局荒漠化监测专项(101-9899) (101-9899)

湖南省教育厅科学研究重点项目(17A225). (17A225)

南京林业大学学报(自然科学版)

OA北大核心

1000-2006

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