Urban Road Change Detection using Morphological Processing

The primary point of this research is to design a road extraction algorithm for processing National Aeronautics and Space Administration satellite pictures. Roadway network detection is one of the important appointments for calamity emergency response, smart shipping structures, and real-time modify roadway network. Everyone is trying to detect road; this system is useful for urban or rural developing schedule. The development of a town / village depends not only on the building and population density of the town or village, but also in the systematic development of roads. The research focused on finding ways to use morphological image processing primarily. As an application area, we use National Aeronautics and Space Administration imagery obtained from 2009-2020 in Monywa, Upper Myanmar to find out how the roads have been developed and how the city has been developed. Extraction road from planet pictures is hard matter with many realistic application programs. The primary points in the model are the advancement of the picture, the segmentation of that picture, the application of the morphological operators, and finally the detection of the roadway network. Use Google Earth Pro to get the necessary data photos and search for road improvements. After collecting images from different seasons and years, we can find precise answers by combining them with precise algorithms. In addition to significant, benefits of Google Earth Pro, this research demonstrates the ability to make good use of satellite imagery and to integrate it with outside experts to save money, save time, and provide accurate answers. It is simulated with MATLAB programming language.