Spatiotemporal Patterns and Driving Factors of Ecological Vulnerability on the Qinghai-Tibet Plateau Based on the Google Earth Engine

Abstract

With the background of climate change and intensified human activities, environmental problems are becoming increasingly prominent on the Qinghai-Tibet Plateau (QTP). For the development of efficient environmental policies and protection measures, quick and accurate assessments of the spatiotemporal patterns in ecological vulnerability are crucial. Based on the Google Earth Engine (GEE) platform, we used Moderate Resolution Imaging Spectroradiometer (MODIS), Shuttle Radar Topography Mission (SRTM), and human footprint (HFP) datasets to analyze the spatiotemporal distributions and main driving factors of the remote sensing ecological vulnerability index (RSEVI) for the QTP. Moreover, spatial autocorrelation analysis and the standard deviational ellipse (SDE) were used to analyze the spatiotemporal characteristics. Our results showed that the RSEVI gradually increased from the southeast to the northwest of the QTP. From 2000 to 2018, the potential vulnerability area increased by 6.59 × 104 km2, while the extreme vulnerability area decreased by 1.84 × 104 km2. Moran’s I value of the RSEVI was greater than 0 and increased, indicating that the aggregation degree was increasing. The gravity center was located in Nagqu, Tibet, and shifted to the northwest from 2000 to 2015 and to the southeast from 2015 to 2018. The SDE rotated in a counterclockwise direction. The three most important driving factors of ecological vulnerability were wetness, land surface temperature (LST), and the normalized difference vegetation index (NDVI), indicating that climate and vegetation were the dominant factors. Moreover, this study developed a promising method for the ecological vulnerability assessment of large-scale and long time series datasets, and it provides theoretical support for the ecological conservation and sustainable development of the QTP under global change.

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