Deep Learning in GeoSpatial Artificial Intelligence.

Abstract

Geospatial artificial intelligence sometimes referred to as geoAI is recently receiving so much attention. From large-scale projects to smaller projects. GeoAI can be referred to as using artificial intelligence with Geographical information system to analyse and produce solution-based predictions. GeoAI is improving geospatial diversity in a lot of ways. With a case study such as predicting particulate matter air pollution in Los Angeles, geo AI has used openStreetMap to improve the prediction between roads pollution with other human efforts based on time, past behavioral pattern and particle concentration. This help to intelligently forecast dangerous levels of air pollution level before it gets out of hand. The application of Geospartial AI is endless as it affects, resource allocation, improvise planning and decision making with regards to supply chain efficiency.