A comprehensive GeoAI review: Progress, Challenges and Outlooks
Anasse Boutayeb, Iyad Lahsen-cherif, Ahmed El Khadimi
TL;DR
GeoAI addresses the challenge of leveraging AI techniques on geospatial data to handle large-scale, multi-source spatial information. The paper presents a comprehensive review that combines methodological framing, motivation, application domains, and both statistical and semantic analyses to map progress, challenges, and future prospects. It clarifies the relationship between GeoAI, GIS, and big geodata, and synthesizes directions to guide future research and practice. The work provides researchers and practitioners with a consolidated state-of-the-art reference to inform strategy, standardization, and deployment in GeoAI-driven geospatial tasks.
Abstract
In recent years, Geospatial Artificial Intelligence (GeoAI) has gained traction in the most relevant research works and industrial applications, while also becoming involved in various fields of use. This paper offers a comprehensive review of GeoAI as a synergistic concept applying Artificial Intelligence (AI) methods and models to geospatial data. A preliminary study is carried out, identifying the methodology of the work, the research motivations, the issues and the directions to be tracked, followed by exploring how GeoAI can be used in various interesting fields of application, such as precision agriculture, environmental monitoring, disaster management and urban planning. Next, a statistical and semantic analysis is carried out, followed by a clear and precise presentation of the challenges facing GeoAI. Then, a concrete exploration of the future prospects is provided, based on several informations gathered during the census. To sum up, this paper provides a complete overview of the correlation between AI and the geospatial domain, while mentioning the researches conducted in this context, and emphasizing the close relationship linking GeoAI with other advanced concepts such as geographic information systems (GIS) and large-scale geospatial data, known as big geodata. This will enable researchers and scientific community to assess the state of progress in this promising field, and will help other interested parties to gain a better understanding of the issues involved.