Identification of sustainable urban settlement sites using interrelationship based multi-influencing factor technique and GIS

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Abstract

Evaluation of a site suitability for sustainable urban settlement growth is crucial. A system for evaluating an interaction between the factors must be established to assure that critical site selection interrelationships are not neglected. To solve this problem, the proposed methodology was evaluated to identify a suitable site for sustainable residential development in Nashik, India. The Geographic information system (GIS)-based multi-influence factor (MIF) approach is used in this study to find ideal locations for future urban settlement. The assessment was based on 11 factors including vegetation, elevation, land use, industry, drainage network, slope, water bodies, road, health services, railway station and population density. The sustainable site suitability was delineated by aggregating all considered factors and their associated MIF weights using the interrelationship between the factors. The results showed that 27.26% of research area was not ideal for settlement development, 16.82% was low suitable, 30.65% was moderately suitable, 16.48% was highly suitable and 8.77% was very highly suitable. Most of the suitable sites were located near the existing habitant area, and major roads. The suitability sites were validated using receiver-operating characteristic (ROC), and area under curve (AUC) value of 0.895 indicated that the model was effective. Sensitivity analysis revealed that the distance from road, drainage network, and health services are the dominant for selecting the optimal location of settlement development in research area. The findings of the delineated ideal areas for the intensive urban settlement development will be helpful to planners and policy makers for sustainable urban growth in the near future.

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Liladhar Rane, N., Achari, A., Hashemizadeh, A., Phalak, S., Pande, C. B., Giduturi, M., … Yadav, K. K. (2023). Identification of sustainable urban settlement sites using interrelationship based multi-influencing factor technique and GIS. Geocarto International, 38(1). https://doi.org/10.1080/10106049.2023.2272670

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