It is a challenge to accurately quantify short-term dynamic human impact on the environment, which is the key to ecosystem and biodiversity conservation. Human's digital footprints are widely used as a proxy of dynamic human impact. This study developed a method to accurately and objectively map the dynamic human's digital footprints in the Tibetan Plateau using the geospatial big datasets, including the numbers of smartphone location request, microblog check-ins, and geo-tagged flicker photos. We developed a method to calculate the fused digital footprint intensity (FDFI) by integrating the location information in the three datasets. The magnitude of the FDFI was converted to a footprint intensity score (FIS), which was then used to infer the human impact. Results show that the average FIS values in Qinghai and Tibet are low (0.12 and 0.04, respectively). The grids with a positive FIS only account for 5.99% of the Tibetan Plateau and are mainly found in the cities and along the transportation networks. The FIS is also strongly correlated to land use and the positive values are mainly found in the built-up and agricultural lands. All other land use categories tend to have near zero FIS values. We concluded that human activities overall show very limited impact on the Tibetan Plateau and most of the impact is found in the built-up and agricultural lands.
Keywords: Digital footprint; Geospatial big data; Human impact; Nature conservation; Tibetan Plateau.
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