Spatial Change Recognition Model Using Image Processing and Fuzzy Inference System to Remote Sensing

Abstract

After the advent of satellites whose job is to image the surface of the earth, a huge database of imaging data of the surface of the earth was made available to researchers in various sciences to exploit a large data set in their field of work, and the subject of remote sensing gradually came to the attention of researchers in various sciences. For example, geography, environmental science, civil engineering, etc., each analyzed the visual data of the earth’s surface from the perspective of their field. According to this research, the issue of spatial change recognition and their location and calculating the percentage of changes at the ground level has been considered, and the model presented is based on machine vision, image processing, and a fuzzy interface system to reveal features. This research is in the category of applied research and finally, an application will be presented that can lead to the development of software such as Google Earth and can be added to that as an option. Another of the advantages of this model is its easy use compared to specialized software such as Arc GIS, and this is the novelty of this research.