GeoAI

Spatiotemporal patterns of air pollutants over the epidemic course: a national study in China

Air pollution has been standing as one of the most pressing global challenges. The changing patterns of air pollutants at different spatial and temporal scales have been substantially studied all over the world, which, however, were intricately …

Health geography studies based on spatial lifecourse epidemiology framework

To introduce some cases of my health geography studies.

Assessing spatiotemporal bikeability using multi-source geospatial big data: A case study of Xiamen, China

we develop a bikeability evaluation framework by combining the collected multi-source spatio-temporal big data.

Seeking your interest and going ahead will contribute to success

We just want to talk about how to become a academic scholar.

Improving the accuracy of forest biomass estimate using source analysis and machine learning

Improving the accuracy of forest biomass estimate using source analysis and machine learning. CN111814397A

A biomass estimation method by fusing plot data and forest inventory data

A biomass estimation method by fusing plot data and forest inventory data. CN110162872A.

Assessing bicycle-sharing riding friendliness by fusing multi-source heterogeneous spatio-temporal big data

With the rapid development of mobile Internet and IoT, shared-bike use has surged, especially since 2020 when COVID-19 caused public transport suspension in many cities. Shared bikes have become a greener and healthier travel option. However, there …

Assessing riding friendliness by fusing multi-source heterogeneous spatio-temporal big data

With the rapid development of mobile Internet and IoT, shared-bike use has surged, especially since 2020 when COVID-19 caused public transport suspension in many cities. Shared bikes have become a greener and healthier travel option. However, there …

Improving Plot-Level Model of Forest Biomass: A Combined Approach Using Machine Learning with Spatial Statistics

Estimating the aboveground biomass (AGB) at the plot level plays a major role in connecting accurate single-tree AGB measurements to relatively difficult regional AGB estimates. The goal of this study is to determine whether combining machine learning with spatial statistics reduces the uncertainty of plot-level AGB estimates.

New Approaches to Anticipate the Risk of Reverse Zoonosis

The coronavirus disease 2019 (COVID-19) pandemic can cause reverse zoonoses (i.e., human–animal transmission of COVID-19). It is vital to utilize up-to-date methods to improve the control, management, and prevention of reverse zoonoses. Awareness of …