Spatial Statistics

Exploring the impact factors of uncertainties for urban carbon dioxide, a case of Jinjiang, Quanzhou, China

To introduce the how to explore the impact factors of uncertainties for urban carbon dioxide.

Improving obesogenic environmental assessments with advanced geospatial methods

This thesis explores the intricate connections between the envir- onment and obesity. It develops and applies advanced geospatial methods to enhance the assessment of obesogenic environments and obesity risks. Its primary objective is to evaluate …

Bridging environment and human health, from earth observation to human-center observation

To introduce my research interest and some research on health geography.

Assessment of physical activity opportunities based on multi-source geospatial data

To introduce our published paper in 'Remote Sensing, Geoinformatics and Social Geographical Computing' session.

Health geography studies based on spatial lifecourse epidemiology framework

To introduce some cases of my health geography studies.

Local carbon emission zone construction in the highly urbanized regions: Application of residential and transport CO$_2$ emissions in Shanghai, China

Optimizing urban morphology can help city managers deploy internal carbon reduction strategies. However, due to the numerous factors that influence urban carbon emissions and the complex paths of their effects, existing research findings are diverse …

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.

A predition method of subtropical forest biomass

A predition method of subtropical forest biomass. CN108959705A

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