基于改进型遥感生态指数(MRSEI)模型的滇中地区生态环境质量研究

doi:10.19741/j.issn.1673-4831.2020.0821

摘要/Abstract

摘要： 以云南省滇中地区为研究区，以MODIS、DEM、社会经济数据等为数据源，构建改进型遥感生态指数（MRSEI）模型探究滇中地区生态环境质量变化情况，采用变异系数、Theil-Sen Median趋势度、空间自相关等方法分析生态环境质量的时空变化特征，利用地理探测器分析生态环境质量差异的主导因素。结果表明：（1）整体上，2000-2018年滇中生态环境质量有所改善，但程度不明显，生态环境质量变化稳定，楚雄州生态环境质量状况最佳；（2）滇中县域生态环境质量呈现正相关性空间聚集特征。从滇中地区西部到东部表现出高高聚集-低低聚集-无显著性的经度地带性空间格局，西部生态环境质量优于东部地区；（3）在地形分布上，海拔3 000 m以上、坡度>20°~30°的区域生态环境质量较佳，生态环境质量较差的区域与人口聚集区分布特征一致；（4）绿度（NDVI）、湿度（WET）与生态环境质量之间呈正相关，而干度（NDBSI）、热度（LST）、人口、GDP等与生态环境质量之间呈负相关。多因子间的交互作用对生态环境质量影响明显，其中NDVI等受人类活动影响较大的自然因子与社会经济因子间的交互作用对生态环境质量造成的影响较大。

关键词: 遥感生态模型, 生态环境质量, 时空变化, 变异系数, 空间自相关, 地理探测器

Abstract: This study adopted Central Yunnan as the study area. Data sources used include the Moderate Resolution Imaging Spectroradiometer (MODIS), a digital elevation model (DEM), and socio-economic data. A modified remote sensing ecological model was used to monitor the eco-environmental quality of Central Yunnan. In addition, the spatiotemporal variation in eco-environmental quality was analyzed by means of the variation coefficient, Theil-Sen median degree, and spatial autocorrelation. Finally, a geographical detector was used to isolate influencing factors. The results show that:(1) The eco-environmental quality of Central Yunnan improved insignificantly from 2000 to 2018 and stabilized. Among the four cities in Central Yunnan, Chuxiong Prefecture showed the most stable eco-environmental quality. (2) Spatial aggregation in eco-environmental quality occurred in counties in Central Yunnan. A longitudinal zonal spatial pattern of "High-High aggregation"-"Low-Low aggregation"-"No significance" occurred from the western to eastern parts of Central Yunnan and the eco-environmental quality in the west exceeded that in the east. (3) Improved eco-environmental quality was observed at an altitude exceeding 3 000 m and at a slope ranging from 20° to 30°. The distribution of the areas with poor eco-environmental quality was consistent with that of high population density. (4) The normalized difference vegetation index (NDVI) and WET were positively correlated with eco-environmental quality, whereas the normalized difference built-up and bare-soil index (NDBSI), Land surface temperature (LST), population, and gross domestic product (GDP) were negatively correlated. The interactions between multiple factors showed a greater impact on eco-environmental quality in comparison to that of any single factor. Among these interactions, that between natural factors and socioeconomic factors, such as the NDVI which was affected by anthropogenic activities to a larger extent, had a greater impact on eco-environmental quality.

Key words: remote sensing ecological index, eco-environmental quality, spatial and temporal variation, coefficient of variation, spatial autocorrelation, geographic detector

中图分类号:

X826
X835

农兰萍, 王金亮, 玉院和. 基于改进型遥感生态指数(MRSEI)模型的滇中地区生态环境质量研究[J]. 生态与农村环境学报, 2021, 37(8): 972-982.

NONG Lan-ping, WANG Jin-liang, YU Yuan-he. Research on Ecological Environment Quality in Central Yunnan Based on MRSEI Model[J]. Journal of Ecology and Rural Environment, 2021, 37(8): 972-982.

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