路虽远行则将至，事虽难做则必成。漫漫长路，必见曙光。《荀子•修身》
CoCA: Spatial cooperative simulation and prediction of land-population-economy in city cluster
Title: CoCA: Spatial cooperative simulation and future prediction of “land-population-economy” in urban agglomerations
在研课题 | 面向网约车场景的多层次时空划分与表征驱动的供需预测方法研究
在研课题 | 面向网约车场景的多层次时空划分与表征驱动的供需预测方法研究
A framework for synthesizing mobility data and evaluating predictive neural networks.
Title: A causal intervention framework for synthesizing mobility data and evaluating predictive neural networks
CoCA v2.1.0：基于元胞自动机模型的“土地-人口-经济”空间协同模拟平台
CoCA v2.1.0：基于元胞自动机模型的“土地-人口-经济”空间协同模拟平台
CoCA v2.1.0: Spatial Cooperation Development Simulation Platform for "Land-Population-Economy" based on Cellular Automaton Model
会议通知 | Geoinformatics 2025暨CPGIS年会
第三十二届国际地理信息学大会（Geoinformatics 2025）暨CPGIS年会将于2025年6月16日至18日在中国河南焦作黄河交通学院举办。
Book Chapter | Urban mobility prediction with attention and geo-info
Title: Prediction and Analysis of Urban Mobility Based on Attention Mechanism and Geographic Information Embedding
Perceiving rural China via deep learning, from street views to countryside.
Title: From Street View Imagery to the Countryside: Large-Scale Perception of Rural China Using Deep Learning
Exploring the nonlinear effects of greenery on active travel among the ageing population
Title: Exploring the nonlinear effects of greenery on active travel among the ageing population
活动通知 | 第五届国产地理分析模型培训班（2025年）（一号通知）
地理分析模型是对地理系统要素及其作用关系、演化规律的抽象与表达。通过构建地理分析模型开展地理模拟可以反演过去、预测未来、模拟过程、揭示规律，从而增进对复杂、多样地理系统的认知与理解。近年来，随着观测手段与建模技术的更新与发展，已经涌现了大量地理分析模型，有效推动了人们对地理系统要素作用机制、演化规律、演变过程的认知，提高了对地理环境变化的预估与适应能力。由此可见，地理分析模型的构建与应用已经成为探索地理过程、人地关系，乃至应对全球变化、可持续发展等重大科学议题的重要方法。
在研课题 | Crowd Prediction and Simulation in Disaster Scenarios
This project aims to develop a geographical model-based intelligent prediction system for crowd flow simulation and emergency decision support in disasters, effectively leveraging Digital Twin data. To accurately predict crowd flow changes, we will construct a sophisticated prediction model that integrates comprehensive data from geographical environment, disaster dynamics, and crowd movement trajectories. Digital Twin technology will be strategically utilized as a rich data source and a powerful virtual simulation platform.
