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

Assessment of the fuzzy ARTMAP neural network method performance in geological mapping using... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Environmental Science and Technology Springer Journals

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

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Islamic Azad University (IAU)
Subject
Environment; Environment, general; Environmental Science and Engineering; Environmental Chemistry; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution; Soil Science & Conservation; Ecotoxicology
ISSN
1735-1472
eISSN
1735-2630
DOI
10.1007/s13762-018-1795-7
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Environmental Science and Technology – Springer Journals

Published: May 31, 2018

References

  • Remote sensing for porphyry copper deposits in Southern Arizona
    Abrams, MJ; Brown, L; Lepley, R; Sadowski, P
  • Geology, alteration and geochemical studies in Kalateh Teymour area North-North East of Iran
    Alami Nia, Z; Karimpour, MH; Heidarian Shahri, MR
  • Application of remote sensing in the Earth sciences (Soil Science)
    Alavi Panah, K
  • ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network
    Carpenter, GA; Grossberg, S; Reynolds, JH
  • Statistical method for selecting Landsat MSS ratios
    Chavez, PS; Berlin, GL; Sowers, LB
  • Intelligent estimation of flood hydrographs using an adaptive neuro–fuzzy inference system (ANFIS)
    Dehghani, AA; Bahremand, AR; Shojaei, S
  • Artificial neural networks (Fuzzy ARTMAP) analysis of the data obtained with an electronic tongue applied to a ham-curing process with different salt formulations
    Gil-Sáncheza, L; Garriguesa, J; Garcia-Breijoa, E; Graub, R; Marta, A; Baigtsb, D; Baratb, JM
  • The application of different image processing methods of ETM data to explore porphyry and vein copper deposits in Mamzar Mountain in Kerman province
    Honarmand, MV; Ranjbar, H
  • Change detection techniques
    Lu, D; Mausel, P; Brondizio, E; Moran, E
  • Mineralogical and structural characterization of alteration zones detected by orbital remote sensing at Shalatein District, SEDesert, Egypt
    Ramadan, MT; Kontny, A
  • Iron-oxide and hydroxyl enhancement using the Crosta method: a case study from the Zagros Belt, Fars Province, Iran
    Tangestani, MH; Moore, F
  • The effects of geological formations on groundwater quality with application of Boulian logic, case study: bajestan watershed plain
    Zare Shooraki, P; Ekhtesasi, MR; Golkarian, A; Hosseini, Z