GIS-based suitability assessment of stone crushing site selection using AHP, Fuzzy-AHP, and Fuzzy-TOPSIS models: Navigating towards sustainable environmental management in Brahmani-Dwarka interfluve

The primary objective of this present study is to carry out the suitability assessment for establishing prospective and existing stone-crushing units in Brahmani-Dwarka Interfluve, which has 764 operational units. The significance of this present study lies in its pioneering effort to identify appropriate locations for such a polluting industry that has not been explored in existing literature. The study utilized the AHP and Fuzzy-AHP to determine the weight of various criteria and sub-criteria. Fuzzy-TOPSIS was employed to identify suitable alternatives for new units, while a sensitivity analysis examined how changes in criteria weight affected those alternatives. The ROC-AUC curve was used to validate the robustness of the models. Results indicated that 144.22 km 2 and 154.44 km 2 areas were classified as low to very low suitable according to AHP and FAHP, respectively, while 144.45 km 2 and 113.36 km 2 areas were deemed very highly suitable. The assessment of existing units revealed that 577 units (AHP) and 493 units (FAHP) were located in low to very low suitable zones, with 12 (AHP) and 24 (FAHP) units in highly suitable areas. FTOPSIS identified 10 potential sites, with Site 1 being the most suitable. Sensitivity analysis indicated Site 5 was most responsive to changes in criteria weight. The AHP and FAHP models achieved AUC values of 0.719 and 0.815, respectively, demonstrating good prediction accuracy and confirming the model's robustness. The findings of the study will help policymakers, planners, and stakeholders develop environmentally friendly site selection strategies and policies in the study region or analogous region. • 29.49% (AHP) and 31.48% (FAHP) of areas were low to very low suitable for stone-crushing. • 29.54% (AHP) and 23.18% (FAHP) of areas were highly suitable for stone-crushing. • 75.5% (AHP) and 65.5% (FAHP) of current crushing sites were located in low-very low suitable zones. • 1.57% (AHP) and 3.14% (FAHP) of current crushing sites were located in highly to very highly suitable zones. • F-AHP performed better than AHP, with an AUC of 0.815 against 0.789.

Authors

Institutions

Publication Details

Journal
Environmental and Sustainability Indicators
Published
2025-05-08
DOI
https://doi.org/10.1016/j.indic.2025.100704
Citations
6
Primary Topic
Soil and Land Suitability Analysis
Type
article
Field-Weighted Citation Impact
14.53

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GIS-based suitability assessment of stone crushing site selection using AHP, Fuzzy-AHP, and Fuzzy-TOPSIS models: Navigating towards sustainable environmental management in Brahmani-Dwarka interfluve

Kaushalendra Prakash Goswami, Bhaskar Mandal, Sharmistha Mondal
6 citations
Environmental and Sustainability Indicators
Soil and Land Suitability Analysis
14.53
article

GIS-based suitability assessment of stone crushing site selection using AHP, Fuzzy-AHP, and Fuzzy-TOPSIS models: Navigating towards sustainable environmental management in Brahmani-Dwarka interfluve

Kaushalendra Prakash Goswami, Bhaskar Mandal, Sharmistha Mondal
article en
6 citations

Abstract

The primary objective of this present study is to carry out the suitability assessment for establishing prospective and existing stone-crushing units in Brahmani-Dwarka Interfluve, which has 764 operational units. The significance of this present study lies in its pioneering effort to identify appropriate locations for such a polluting industry that has not been explored in existing literature. The study utilized the AHP and Fuzzy-AHP to determine the weight of various criteria and sub-criteria. Fuzzy-TOPSIS was employed to identify suitable alternatives for new units, while a sensitivity analysis examined how changes in criteria weight affected those alternatives. The ROC-AUC curve was used to validate the robustness of the models. Results indicated that 144.22 km 2 and 154.44 km 2 areas were classified as low to very low suitable according to AHP and FAHP, respectively, while 144.45 km 2 and 113.36 km 2 areas were deemed very highly suitable. The assessment of existing units revealed that 577 units (AHP) and 493 units (FAHP) were located in low to very low suitable zones, with 12 (AHP) and 24 (FAHP) units in highly suitable areas. FTOPSIS identified 10 potential sites, with Site 1 being the most suitable. Sensitivity analysis indicated Site 5 was most responsive to changes in criteria weight. The AHP and FAHP models achieved AUC values of 0.719 and 0.815, respectively, demonstrating good prediction accuracy and confirming the model's robustness. The findings of the study will help policymakers, planners, and stakeholders develop environmentally friendly site selection strategies and policies in the study region or analogous region. • 29.49% (AHP) and 31.48% (FAHP) of areas were low to very low suitable for stone-crushing. • 29.54% (AHP) and 23.18% (FAHP) of areas were highly suitable for stone-crushing. • 75.5% (AHP) and 65.5% (FAHP) of current crushing sites were located in low-very low suitable zones. • 1.57% (AHP) and 3.14% (FAHP) of current crushing sites were located in highly to very highly suitable zones. • F-AHP performed better than AHP, with an AUC of 0.815 against 0.789.

Environmental and Sustainability IndicatorsVol. 26
Banaras Hindu University (IN)
University Grants Commission
Life in Land
Openalex Percentile: Top 1%
Soil and Land Suitability Analysis
14.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.