Description

• Title:
  Mapping Groundwater Resource using Multispectral Sentinel 2 and Fuzzy Logic method, Case Study: Salafchegan, Qom, Iran
• Creator:
  Shahsavari, Hamideh;
  Arefi, Hossein;
  Davoodabdi Farahani, Meysam;
  alizadeh Pirbasti, Mehran;
  Shobairi, Seyed Omid Reza
• Description:
  Groundwater is one of the essential freshwater sources for human consumption, with the highest reserves of fresh water on earth after glaciers and glaciers. Conservation and maintenance of groundwater quality in a large area require an overview of the status and potential of groundwater resources in that area, which can be applied to potential areas using remote sensing technology. In this study, after extracting the factors influencing the formation of groundwater aquifers from the Sentinel satellite image, appropriate information layers were prepared and integrated into the ArcGIS using different fuzzy operators and potential maps prepared with the location of groundwater wells. The area was validated. The results of combining slope layers, slope direction, lithology, drainage length density, lineament length density, lineament buffer, drainage buffer, and vegetation in the area showed that fuzzy multiplication and gamma operators could be used as suitable operators for Introducing information layers to identify groundwater potential in the area. Also, using the gamma numbers 0.1 gave better results than larger gamma numbers. The research results showed that 15.9% of the studied area has good and very good potential for the presence of underground water in the production map using the fuzzy gamma with gamma 0.1 method. Also, this map was validated by 70.1% of water wells in the region. The normalized ratio of accuracy to validity in the final production model with this method was estimated to be 54%, which is entirely acceptable compared to other methods.
• Object availability:
  free access
• Rights:
  Prawa autorskie (c) 2023 Hamideh Shahsavari, Hossein Arefi, Meysam Davoodabdi Farahani, Mehran alizadeh Pirbasti, Seyed Omid Reza Shobairi;
  https://creativecommons.org/licenses/by-nd/4.0
• Date:
  2023.12.05
• Type:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Language:
  English
• Source:
  Ecological Questions; Vol. 35 No. 2 (2024); 33-48;
  Ecological Questions; Tom 35 Nr 2 (2024); 33-48;
  1644-7298
• Format:
  application/pdf
• Publisher:
  Uniwersytet Mikołaja Kopernika w Toruniu
• Relation: https://apcz.umk.pl/EQ/article/view/41933/36991
• Subject:
  Remote Sensing;
  groundwater;
  potential detection;
  multispectral imagery;
  fuzzy algebra
• Identifier: https://apcz.umk.pl/EQ/article/view/41933
• Data provider:
  Akademicka Platforma Czasopism
• Can I use it?:
  seek permission
• Type:
  text