Abstract 03JSSP012024

Unravelling the Role of Socio-Physical Drivers for Potential Built-up Site Selection in the Kumaun Himalayas Using GIS-Based Fuzzy-AHP and Machine Learning

Akash TIWARI1, Manish KUMAR*1, Syed Irtiza MAJID1, Sourav BHADWAL1, Naresh Kumar VERMA2, Dinesh Kumar TRIPATHI3, Subhash ANAND4
* Corresponding author
1 Central University of Haryana, School of Basic Sciences, Department of Geography, Jant-Pali, Mahendragarh, Haryana, INDIA
2 Jawaharlal Nehru University, Special Centre for National Security Studies, New Delhi, INDIA
3 Rana Pratap Post Graduate College, Sultanpur, Uttar Pradesh, INDIA
4 University of Delhi, Delhi School of Economics, Department of Geography, Delhi, INDIA
: researchakashgeo@gmail.com; ORCID: 0000-0003-0066-781X
: manish.ks1@gmail.com; ORCID: 0000-0002-2588-6499
: sirtiza34@gmail.com; ORCID: 0000-0002-7889-4281
: bhadwalsourav@gmail.com; ORCID: 0000-0002-9555-7957
: nareshrai.jnu@gmail.com; ORCID: 0009-0001-8621-2615
: tripathidk.geoinformatics@gmail.com; ORCID: 0000-0001-8274-5118
E-mail: sanandpvs@gmail.com; ORCID: 0000-0001-8274-5118
: 23-38. DOI: 10.24193/JSSP.2024.1.03
: 05 November 2023
Received in revised form
: 21 April 2024
Accepted for publication
: 11 June 2024
Available online
: 18 June 2024

Cite: Tiwari A., Kumar M., Majid S. I., Bhadwal S., Verma N. K., Tripathi D. K., Anand S. (2024), Unravelling the Role of Socio-Physical Drivers for Potential Built-up Site Selection in the Kumaun Himalayas Using GIS-Based Fuzzy-AHP and Machine Learning. Journal of Settlements and Spatial Planning, 15(1), 23-38. DOI: 10.24193/JSSP.2024.1.03

Abstract. Rapid and uncontrolled urban growth in the Kumaun Himalayas in absence of proper land use policy has pushed built-up areas towards the tectonically and ecologically sensitive regions, reducing the availability of suitable built-up land while simultaneously increasing the vulnerability of both communities and environment. The identification of areas for sustainable built-up growth is of paramount importance to address the challenges arising from unregulated urban expansion. In this study GIS-based Fuzzy-AHP technique and machine learning algorithms (SVM and BN) were employed to delineate the potential built-up sites selection in Hawalbagh Block, Uttarakhand (India) using nine socio-physical drivers, including slope, aspect, LU/LC, distance to road, distance to drainage, distance to lineament, distance to landslide, distance to settlement, and lithology. The suitability maps generated by the three methods were validated using AU-ROC analysis, which demonstrated that each approach produces outstanding results with AU-ROC values more than 0.90. The comparison of the approaches shows that SVM (AUROC=0.99) outperforms BN (0.95) and GIS-based Fuzzy-AHP (0.90). The suitability maps were classified into five suitability classes. Assuming that very high and high suitability classes are acceptable for built-up expansion, the study identified potential built-up locations in the study region covering an area of 148.86 km2, 85.23 km2, and 55.25 km2 according to the Fuzzy-AHP technique, SVM model, and BN model, respectively. The suitability zonation in this study can serve as a foundation for the development of land-use policy or the formulation of master plans aimed at achieving a sustainable mountain ecology in the Kumaun Himalayas.

K e y w o r d s: site suitability analysis, Fuzzy-AHP, support vector machine, Bayesian Network, Kumaun Himalayas