{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T22:11:47Z","timestamp":1783980707521,"version":"3.55.0"},"reference-count":72,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,3,23]],"date-time":"2020-03-23T00:00:00Z","timestamp":1584921600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Investigating the causes of the spatial heterogeneity of glacial changes offers vital information about glacial behavior and provides forecasting ability to define where glacier retreat may occur in the future. This study was designed to determine the spatial distribution of A\u011fr\u0131 Mountain glacier vulnerability. The main goal of the current study was to assess the forecasting capabilities of Geographical Information System (GIS)-based Multi-Criteria Decision Analysis (MCDA) for determining the location of the mountain glacier retreat. To estimate the glacier retreat, the following criteria were selected: elevation, aspect, slope, direction, and glacier surface temperature anomaly (GSTA). The entropy method was used for weighting the criteria for the evaluation of the vulnerable areas of the glacier. The results of this method clearly indicate a strong relationship between GSTA, direction, and elevation criteria and glacier retreat. The glacier vulnerability map was created by synthesizing criteria layers with their weights. The vulnerability map provided a consistency of 77.8% in the short term and 92.1% in the long term. In the study, the priority melting zones were determined and glacial retreat locations were forecasted in 10-year periods.<\/jats:p>","DOI":"10.3390\/ijgi9030180","type":"journal-article","created":{"date-parts":[[2020,3,24]],"date-time":"2020-03-24T07:16:08Z","timestamp":1585034168000},"page":"180","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A GIS-Based Multi-Criteria Decision Analysis Model for Determining Glacier Vulnerability"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6402-5651","authenticated-orcid":false,"given":"Mustafa","family":"Yalcin","sequence":"first","affiliation":[{"name":"Department of Geomatics Engineering, Afyon Kocatepe University, 03200 Afyonkarahisar Merkez\/Afyonkarahisar, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.rse.2013.06.010","article-title":"Characterization of recent glacier decline in the Cordillera Real by LANDSAT, ALOS, and ASTER data","volume":"137","author":"Liu","year":"2013","journal-title":"Remote Sens. 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