[Spatio-temporal Correlation Between Human Activity Intensity and Remote Sensing Ecological Index in the Guanzhong Plain Urban Agglomeration].

Résumé fourni par la source

Human activity intensity （HAI） is a critical metric for assessing the extent of human activities impacting the ecological environment. The remote sensing ecological index （RSEI）, as a comprehensive indicator of ecological environmental quality, is particularly sensitive to changes driven by human activities. Investigating the spatiotemporal differentiation and correlation between HAI and RSEI provides valuable insights for maintaining environmental stability, managing human activities, and balancing human-land relationships. Taking the Guanzhong Plain Urban Agglomeration as the study area, this research quantified HAI using nighttime lighting, population density, and land-use data. The Google Earth Engine （GEE） platform was employed to obtain MODIS data for constructing RSEI, and the spatiotemporal differentiation and correlation of HAI and RSEI from 2001 to 2023 were analyzed. The results showed that： ① From 2001 to 2023, the overall variation in HAI across the Guanzhong Plain Urban Agglomeration was relatively slow, with an average annual growth rate of 0.41%. The spatial distribution followed an "eight-point, one circle, and one belt" pattern, with high-intensity areas increasingly concentrated in the central region. ② Between 2001 and 2015, areas rated as "excellent" in RSEI increased significantly （from 6.43% to 19.41%）, but the growth slowed between 2015 and 2023 （rising from 19.41% to 20.87%）. The RSEI distribution was higher in the southeast and lower in the northwest, with the Qinling Mountains serving as a boundary. Changes in RSEI frequency showed a decreasing trend from east to west. ③ The relationship between HAI and RSEI exhibited significant spatial differentiation, with clear spatial clustering observed in the Guanzhong Plain and Qingyang City. Human activities had a bidirectional impact on ecological quality： High-intensity activities led to ecological degradation, whereas restoration efforts, such as the "Grain for Green" program and grassland conservation, effectively mitigated these effects. These results provide a theoretical basis and reference framework for accurately quantifying human activity intensity, spatial land-use planning in the Guanzhong Plain Urban Agglomeration, and efforts to restore and stabilize ecological environmental quality.

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