A Machine-Insight-Based Geocomputational Approach to Decode the Complexities of the Restless Landscapes

Toward Integration of Imaginations and Planning Interventions

Bibliographic Data

ID3775460
AuthorsNilanjan Bal (0009-0006-6973-7942, University of Delhi), Ashis Kumar Saha (0000-0002-8184-0495, University of Delhi, corresponding author), Sanjit Sarkar (0000-0001-5906-3098, Central University of Karnataka)
Year2025
Volume115
Issue9
Pages1-39
Publication date2025-07-16
Open AccessNo
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2025.2517736
OpenAlexW4412478735
LanguageEN
References cited69

The proliferating urban influence brought a complex sociospatial, economic structure over the urban periphery. Previous studies focused on different approaches to capturing this intricate process; generalization was done by setting their own criteria. This study builds a decision-making model to comprehend the nature of Varanasi city’s periphery. Settlement-wise data are collected to calculate the study’s initial parameters: functional index, physical infrastructure dynamics score, physiological density, and nonagricultural land to total land ratio. The independent component analysis calculates the composite score. The learning cloud incorporates settlement-wise data in an encoded format to run the XGBoost machine learning algorithm. The findings highlight a competitive pattern of settlements and identify four periurban zones based on the deviation diffusion of calculated parameters. The study implements the Monte Carlo simulation for visualizing periurban decision space and recorded an asymptotic one-sample Kolmogorov–Smirnov test score of 0.051 at a p value of 0.076. The findings suggest four peripheral settlement clusters where the Gaussian mixture model confirms the reliability. This study highlights the importance of these clusters in attracting government and private players to invest and innovate functioning urban like institutions. This study’s methodological framework and inclusive approaches for city region planning and policy formulation remain significant

Business · Data science · Psychological intervention · Sociology · Computer Science · Land Use and Ecosystem Services · Psychology · Urban Design and Spatial Analysis

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