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Urban land suitability analysis using geospatial techniques and combined weighting approach in Gabes zone, Southeastern Tunisia

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submitted on 2024-08-19, 12:52 and posted on 2024-08-19, 12:53 authored by Dhekra Souissi, Lahcen Zouhri, Abdelaziz Sebei, Adel Zghibi, Mahmoud Dlala, Mohamed Ghanmi

Urban Land Suitability analysis is necessary in any development project in order to ensure rational urban planning and sustainable development. In this study, a novel approach based on GIS and Combined Weighting method were used to construct a reasonable assessment model and calculate the Urban Land Suitability Index (ULSI) of Gabes area (Southeastern Tunisia). Seven conditional factors were selected: flooding susceptibility, Lithology, Topography, Seismotectonic, Water table depth, Swelling soils, Soils Aggressivity and the thematic layers were prepared in ArcMap_GIS. The resultant model following combination of the geo-spatial (GIS) and geostatistical (CRITIC-ANP) modeling show that this region is subdivided into four analyzed zones in terms of geo-hazard susceptibility and foundation excavation: flooding risk area; settlement risk zone; collapse risk area and subsidence risk zone. The ULSI is equal to 3.5. The accuracy degree of the achieved model was validated by ROC-AUC curve, it’s is around 78.4%. The ULS model developed enable assured a the assessed thorough and can well reflect an urban land suitability. The results achieved in this study assured planners, engineers, decision-makers and authorities assured a good risk prediction and management plan, could, thus, be facilitate decision-making and can serve as a guideline for all future urban planning projects in this region.

Other Information

Published in: Geomatics, Natural Hazards and Risk
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1080/19475705.2023.2278278

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Taylor & Francis

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU

Geographic coverage

Tunisia

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