HashGAT-VCA: A VCA model with hash function and graph attention network for land-use simulation
Title: HashGAT-VCA: A vector cellular automata model with hash function and graph attention network for urban land-use change simulation
Title: HashGAT-VCA: A vector cellular automata model with hash function and graph attention network for urban land-use change simulation
Title: A multimodal data fusion model for accurate and interpretable urban land use mapping with uncertainty analysis
Title: Temporal-VCA: Simulating urban land use change using coupled temporal data and vector cellular automata
Graph convolutional networks for street network analysis with a case study of urban polycentricity in Chinese cities
Title:Predicting short-term PM2.5 concentrations at fine temporal resolutions using a multi-branch temporal graph convolutional neural networkAbstract
Title:Predicting the locations of missing persons in China by using NGO data and deep learning techniquesAbstractMissing person crimes can seriously a
Fine-grained regional economic forecasting for a megacity using vector-based cellular automata
Title: Evaluating geospatial context information for travel mode detection
Title: Extracting the pickpocketing information implied in the built environment by treating it as the anomaliesAbstractThe practice of crime risk map
Unsupervised land-use change detection using multi-temporal POI embedding