GeoAI Research

GeoAI, or geospatial artificial intelligence, integrates AI techniques with geospatial data to solve complex problems across various domains. Current research emphasizes developing robust spatial representation learning frameworks, including novel location encoding methods and benchmark datasets for evaluating model performance and mitigating geographic bias, often employing deep learning architectures like convolutional neural networks and vision transformers. This interdisciplinary field is crucial for advancing geographic knowledge discovery and improving applications ranging from flood inundation mapping and species distribution modeling to cartography and social science research, while also addressing critical ethical considerations like data privacy and algorithmic fairness.