GeoAI

An MLLM-powered visual-semantic indicator system coupled with geographically weighted XGBoost for precise, spatially explicit urban fire-risk governance in Wuhan.

A multimodal, multi-output framework that estimates complete sex and age structures on 100 m grid cells from census data, remote sensing imagery, and geotagged social media data.

Editorial to the Research Topic on machine learning for advanced remote sensing, connecting methodological advances with trustworthy, scalable, and societally valuable applications.

To introduce our published studies in sensing healthy city from multimodal geographic data, GeoAI to causal inference.

To introduce our published studies in sensing healthy city from multimodal geographic data, GeoAI to causal inference.

We proposed the Geographical Cross Mapping Cardinality (GCMC) model to reliably quantify causal strengths from spatial cross-sectional data with low false positive rates.

To introduce our published research in sensing obesogenic environments based on multimodal data and GeoAI.

We proposed GeoIdentity-Sat2Street, a geographic identity preserving satellite-to-street-view generation framework that expands street view coverage in data-scarce regions.

Human mobility during the Spring Festival is a large-scale annual human mobility across China. This paper evaluated the human health risks of short-term exposure to PM2.5 in the Yangtze River Delta through a combination of the daily-level high …

To introduce our published paper in sensing health city using multimodal data and GeoAI.