基于GEE和RSEI的长三角一体化示范区生态环境质量动态评估

doi:10.13292/j.1000-4890.202302.017

生态学杂志 ›› 2023, Vol. 42 ›› Issue (2): 436-444.doi: 10.13292/j.1000-4890.202302.017

基于GEE和RSEI的长三角一体化示范区生态环境质量动态评估

何天星¹,田宁¹,周锐^1,2,3*,马群^1,3,张洁¹,高峻^1,3

（¹上海师范大学环境与地理科学学院，上海 200234； ²北京大学城市与环境学院，北京 100871； ³上海长三角城市湿地生态系统国家野外科学观测研究站，上海 200234）

出版日期:2023-02-10 发布日期:2023-07-10

Dynamic assessment of ecoenvironmental quality in Yangtze River Delta integration demonstration area based on GEE and RSEI.

HE Tian-xing¹, TIAN Ning¹, ZHOU Rui^1,2,3*, MA Qun^1,3, ZHANG Jie¹, GAO Jun^1,3

(¹School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; ²College of Urban and Environmental Sciences, Peking University, Beijing 100871, China; ³Yangtze River Delta Urban Wetland Ecosystem National Field Observation and Research Station, Shanghai 200234, China).

Online:2023-02-10 Published:2023-07-10

摘要/Abstract

摘要： 生态环境质量变化的及时监测与定量评估，可为区域生态环境协同治理与管控政策制定提供决策支持。本研究基于Landsat5/TM和Landsat8/OLI影像，利用Google Earth Engine（GEE）平台和遥感生态指数（RSEI），综合考虑湿度、绿度、干度和热度等多种生态环境要素，对长三角一体化示范区2000—2020年生态环境质量变化进行了评估，并结合GDP和人口数据分析了社会经济因子对生态环境质量的影响。结果表明：绿度是对研究区生态环境质量贡献率最大的指标，且具有正面效应，而热度指标是引起生态环境质量退化的主要因素；研究区生态环境质量总体上处于中等水平，且呈现平稳上升趋势，其中，青浦区生态环境质量上升趋势明显，而吴江区和嘉善县的生态环境质量略有下降；2000—2020年，研究区生态环境质量提高区域面积占比（30.45%）略高于下降区域（28.35%），良好和优等级区域占比由27.34%增至29.79%，在不同时段，区县间和街镇间差异较为显著；人口增长对生态环境质量具有明显的负面影响，而经济发展并未以牺牲生态环境为代价，二者之间表现为脱钩关系。

关键词: 生态环境质量, 遥感生态指数, Google Earth Engine, 长三角一体化示范区

Abstract: The rapid monitoring and quantitative evaluation of eco-environmental quality change can provide decision support for regional ecological environment collaborative governance and management policy formulation. Based on Landsat5/TM and Landsat8/OLI images, using Google Earth Engine (GEE) platform and Remote Sensing Ecological Index (RSEI), comprehensively considering various eco-environmental factors such as humidity, greenness, dryness, and heat, we quantitatively evaluated the changes of eco-environmental quality in the Yangtze River Delta integration demonstration area from 2000 to 2020. We analyzed the effects of social and economic factors on eco-environmental quality by combining GDP and population data. The results showed that greenness contributed most and positively to the eco-environmental quality of the study area. Thermal index was the main factor resulting in the degradation of regional eco-environmental quality. The eco-environmental quality of the study area was generally at a medium level, which showed a steady upward trend during 2000-2020. Specifically, the eco-environmental quality of Qingpu District increased obviously, while that of Wujiang District and Jiashan County decreased slightly. From 2000 to 2020, the proportion of areas with improved eco-environmental quality (30.45%) was slightly higher than that of degraded area (28.35%), and the proportion of areas with good and excellent grades increased from 27.34% to 29.79%. There were significant differences in eco-environment quality among districts/counties and towns in different periods. Population growth had a significant negative impact on eco-environment quality. Economic development was not at the cost of eco-environment, and the relationship between economic development and eco-environment quality was decoupled.

Key words: eco-environmental quality, remote sensing based ecological index, Google Earth Engine, Yangtze River Delta integration demonstration area.

何天星, 田宁, 周锐, 马群, 张洁, 高峻. 基于GEE和RSEI的长三角一体化示范区生态环境质量动态评估[J]. 生态学杂志, 2023, 42(2): 436-444.

HE Tian-xing, TIAN Ning, ZHOU Rui, MA Qun, ZHANG Jie, GAO Jun. Dynamic assessment of ecoenvironmental quality in Yangtze River Delta integration demonstration area based on GEE and RSEI.[J]. Chinese Journal of Ecology, 2023, 42(2): 436-444.

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基于GEE和RSEI的长三角一体化示范区生态环境质量动态评估

Dynamic assessment of ecoenvironmental quality in Yangtze River Delta integration demonstration area based on GEE and RSEI.

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