Applications of Artificial Intelligence and Machine Learning in Geospatial Data

Abstract

With rapid development in new technologies our intelligence and expertise in artificial intelligence (AI) have increased significantly. Intelligent machines are preferred, which motivates us to incorporate highly sophisticated technologies. Geographic analysis for environmental applications has advanced recently, owing to the vast explosion of geospatial data, the accessibility of powerful computing resources, and advancement in AI. Geospatial analytics at a high-resolution scale is now possible because AI reshapes our research environment. High-resolution satellite imaginaries used in geospatial analysis always include bigdata; thus, alternative methods other than traditional data-processing applications are needed to deal with these large datasets. AI has become an alternative method to handle big data in recent decades. Geospatial information from high-resolution remote sensing and other environmental sensors generates enormous data. AI makes the process more effective and makes it possible to derive deep understandings and information from the data.