Abstract:
The surface water is any water body that is above the surface like streams, rivers, lakes, wetland reservoirs. Together they cover approximately 3% of the global land mass. They provide water sources for various human uses and supports high levels of biodiversity and provides important ecosystem services. Satellite remote sensing provides unique capabilities for mapping the location, extend and changes of surface water bodies through high resolution raster images. But in these traditional water body extraction methods, it is difficult to extract the water bodies due to the shadows of buildings and other ground objects are in the same spectrum as water bodies. This study is about understanding the application of Artificial intelligence which combines the geo spatial data and GIS data to form a new technology based on image processing technology which helps to identify the water body boundaries from the satellite images. Artificial intelligence has been extensively used in many areas such as geo spatial engineering.
Geo-Ai also called as Geospatial Ai is a subset of Artificial Intelligence that combines the GIS technology with high accuracy for analysis and solution-based approach AI. It is a new form of deep learning with the help of neutral engines based on geospatial data. The Geo-Ai will help in improvised planning, resource allocation and decision making – perdition with high accuracy, precision, and efficiency. The objective of the study is to create an enhanced surface water detection tool which have a huge potential on modern planning field related to water resource mapping as well as monitoring and response to natural disaster emergency and its application in modern planning field.
Keywords: Surface water body, Artificial intelligence, Geo Ai, GIS, Image processing, high resolution satellite imagery.
