Identifying the spatio-temporal variability of human activity intensity and associated drivers: a case study on the Tibetan Plateau

Abstract

Human activities have significantly degraded ecosystems and their associated services. By understanding the spatio-temporal variability and drivers of human activity intensity (HAI), we can better evaluate the interactions between human and terrestrial ecosystems, which is essential for land-use related decision making and eco-environmental construction. As the “third pole,” the Tibetan Plateau (TP) plays a strong role in shaping the global environment, and acts as an important ecological security barrier for China. Based on land-use/cover change data, environmental geographic data, and socioeconomic data, we adopted a method for converting different land use/cover types into construction land equivalent to calculate the HAI value and applied the Getis–Ord Gi* statistic to analyze the spatio-temporal dynamics associated with HAI since 1980 on the TP. Thereafter, we explored the forces driving the HAI changes using GeoDetector software and a correlation analysis. The main conclusions are as follows: It was observed that HAI increased slowly from 3.52% to 3.65% during the 1980–2020 period, with notable increases in the western part of the Qaidam Basin and Hehuang Valley. Spatially, HAI was associated with a significant agglomeration effect, which was mainly concentrated in the regions of the Yarlung Zangbo and Yellow–Huangshui rivers. Both natural and anthropogenic factors were identified as important driving forces behind the spatial changes in HAI, of which soil type, gross domestic product, and population density had the greatest influence. Meanwhile, the temporal changes in HAI were largely driven by economic development. This information provides crucial guidance for territory development planning and ecological-protection policy decisions.

Graphical abstract

Keywords

Tibetan Plateau / human activity intensity / GeoDetector / spatio-temporal variability / driving factors

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Acknowledgments

This work was supported by the Key Laboratory of Airborne Geophysics and Remote Sensing Geology Foundation (No. 2020YFL20), China Postdoctoral Science Foundation (No. 2019M650820).

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