Remote sensing and GIS tool application for tracing the water body of Bangalore area

Abstract

To comprehend the function of the water bodies at various sizes, such as regional and global, for example, in biogeochemical cycles, it is necessary to more correctly estimate the size, form, and extent of the water bodies. Excluding the few areas with precise maps, scaling upward to vast area regions relies on statistical estimates of the number and size of lakes, rivers, and other water bodies, which explains why estimates are wrong. In comparison to the currently available conventional and frequently used methods of mapping land surface water (LSW), remote sensing offers several extra advantages since it is a more accurate, efficient, and reliable information source with the ability to make multiple high-frequency and repeatable quantities of observations. This project describes the development and technological evolution of the Water Body Map (WBM), which employs an automated algorithm to interpret multi-temporal Landsat images from the USGS database. In this project, we used Landsat 5 band photographs to define a water body map without any cloud cover. Permanent water bodies were separated from temporary water-covered areas by estimating the frequency of water bodies in overlapping, multi-temporal Landsat images. In contrast to past studies, the WBM now makes a more precise distinction between rivers and floodplains by looking at the frequency of water bodies. As a result, it is clear that using multi-temporal images from sources is equally as important for mapping global water bodies as analysis at a higher resolution. The classification's accuracy was confirmed in Hokkaido (Japan) and the United States of America using databases of actual water bodies. Around 70% of lakes N1 km2 have relative water area errors of b25%, and the commission error was diminishing and nearly nonexistent. The Water Body Mapping's overall accuracy should be helpful for much larger scale research projects in hydrology, biogeochemistry, and climate systems, among other things. It can also include a quantification of the kinds of water bodies that are currently present around. Some smaller water bodies were overlooked, primarily because shoreline pixels were not included. The primary goal of this project was to estimate the accuracy of mapping water bodies using Landsat 5 TM data by employing straightforward digital image processing techniques.