地理空间人工智能 (GeoAI) 为利用地球、环境和地理空间数据相关的智慧和可持续决策创造了新的机会。GeoAI 改变了我们研究地球系统和城市的特征、模式和预测问题的方式。当前研究人员希望将 GeoAI 与传统方法进行比较和整合，并开发创新模型来表征地理空间对象、量化空间关联和优化决策。在最近的研究中，GeoAI 极大地加强了对区域和全球自然环境以及社会和建筑环境的研究。本期专刊旨在收集有关 GeoAI 在不同领域研究前沿、面临的机遇和挑战的高水平研究论文和综述。
Scope/Keywords:
Geospatial Artificial Intelligence (GeoAI);
Earth, environmental, and geospatial data;
Characteristics, patterns, and prediction of Earth’s systems and cities;
Compare and integrate GeoAI with traditional methods and develop innovative models;
Characterize geospatial objects, quantify spatial association, and optimize decision-making;
GeoAI enhances studies of natural environment, social and built environments, regionally and globally;
Advances, opportunities, and challenges facing GeoAI in diverse fields.
欧洲电力系统时空模式
Principal spatiotemporal mismatch and electricity price patterns in a highly decarbonized networked European power system
水技术进步影响中国用水量
Dual effects of technology change: How does water technological progress affect China’s water consumption?
全球收缩城市卫星监测
Satellite monitoring of shrinking cities on the globe and containment solutions
