The Interaction of Human-Centric and Artificial Intelligence for Geospatial Chaining Method

AI has benefited a human that may also harm humans not appropriately developed. Transitioning from traditional human contact with non-AI computer systems to interaction with AI systems is the main goal of HCI work. We have reviewed the relevant literature at a high level and thoroughly examined the state of the art in AI system development from an HCI standpoint. Our evaluation and analysis shed light on the latest developments brought about by AI technology as well as the fresh difficulties that HCI specialists now have when using the human-centered AI (HCAI) method to design AI systems. The use of geospatial artificial intelligence (GeoAI) in quantitative human geography studies is reviewed in detail in this paper, covering the subdomains of latitude, longitude, area temperature, soil type, appropriate plants, trees, water sources, land type, animal behaviour, and the area's current state. The current state of GeoAI applications within each subdomain of human geography is elaborated upon by geospatial methodology, which also highlights the problems and obstacles and suggests future research directions and opportunities for the application of GeoAI in human geography studies within the framework of open and sustainable science, generative AI, and the quantum revolution. AI and human-centric analysis of the present state of geospatial data allowed for the easy prediction of natural catastrophes as well as the identification and prediction of specific area suitable for human habitation.