Assessment of the fuzzy ARTMAP neural network method performance in geological mapping using satellite images and Boolean logic

Abstract

Currently, in executive comparative studies and even in the research studies of natural resources, the use of maps produced by the geological survey forms the basis of geological studies. However, in recent years, remote sensing technology has been introduced as a new and efficient tool for geological studies which in addition to the accuracy has other benefits such as access to the arduous mountainous areas or inaccessible that can help us to prepare geological maps with more accuracy. The purpose of this study is to compare geological survey geological maps with a scale of 1: 100,000, and produced and modified by Google Earth maps by using fuzzy ARTMAP artificial neural network method. For this purpose, the geological map of a part of Yazd-Shirkooh watershed prepared by using Landsat 7 image by fuzzy ARTMAP artificial neural network method with Kappa coefficient of 89%. Also, geological survey and Google Earth map prepared. Graphic map obtained from the visual interpretation of Google Earth images with the ground control was considered as the base map and comparing it with other maps evaluated by using Boolean logic. By using the sampling network created 100 points which 62 points were in the study area and 56 cases in the fuzzy ARTMAP map and 52 cases in the geological survey map were consistent with the base map. Due to reduced cost and time and no limits of time and space, fuzzy ARTMAP is a suitable method for the preparation of geological maps.