A global map of human presence in 2017

Understanding global patterns of human presence is crucial for monitoring anthropogenic pressures on ecological integrity, optimizing tourism management, and informing decision-making in various domains. However, existing datasets on human presence are insufficient and primarily limited to local scales.

We combined massive geotagged microblogs and multi-covariates to infer the global human presence in 2017 at a fine spatial resolution of 0.01 degrees. Specifically, we proposed a Human Presence Indicator (HPI) to quantify human presence. It categorizes the intensity of human presence at a location in four levels based on year-long statistics of geotagged data. HPI-0, HPI-1, HPI-2, and HPI-3 represent no human presence, occasional/frequent/sustained human presence, respectively.

The model achieved a macro-F1 score of 0.72 on a test set comprising over 1.9 million grids in China and 0.84 on manually labeled samples worldwide. Cross-validation with external datasets, including geotagged social media data from X and global human settlement and population data, corroborated the model's effectiveness.

The related article is currently under review.