The Power of Geo-Spatial Data Mining and Geo-Ai: A Comprehensive Review and Concise Guide For New Developers

Geo-spatial data refers to information that describes the location, shape, and relationships of geographic features and phenomena. This type of data is crucial for various applications, including mapping, urban planning, environmental monitoring, and navigation systems. GeoSpatial Artificial Intelligence (Geo-AI) is a fascinating topic, particularly in its development and application in our lives. Many key applications play a crucial role in the economic and social development of regions and countries. Geo-AI is a cutting-edge field that merges Geo-Spatial science with artificial intelligence to generate insights, make predictions, and automate decision-making based on geo-spatial data. This paper delves into the power of geo-spatial data mining and main Geo-AI applied techniques. The objective is to give, for new Geo-AI developers, a comprehensive Review and guide on collecting and processing geo-spatial data and main used AI algorithms and Python libraries to develop Geo-AI based solutions. A case study of Deep-Learning (ResUNet) based Land Use Land Cover Segmentation is implemented and interpreted.