Residential Location Preferences in a Post-Conflict Context: An Agent-Based Modeling Approach to Assess High-Demand Areas in Kabul New City, Afghanistan

Vineet Chaturvedi and Walter Timo de Vries ()
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Vineet Chaturvedi: Chair of Land Management, Centre of Land, Water and Environmental Risk Management-Department Aerospace and Geodesy, School of Engineering and Design, Technical University of Munich, Arcisstraße 21, 80333 München, Germany
Walter Timo de Vries: Chair of Land Management, Centre of Land, Water and Environmental Risk Management-Department Aerospace and Geodesy, School of Engineering and Design, Technical University of Munich, Arcisstraße 21, 80333 München, Germany

Land, 2025, vol. 14, issue 7, 1-16

Abstract: As part of the post-conflict reconstruction and recovery, the development of Kabul New City aims to bring relief to the existing capital city, Kabul, which has experienced exponential population growth, putting heavy pressure on its existing resources. Kabul New City is divided into four subsectors, and each of them is being developed and is expected to reach a target population by 2025, as defined by the master plan. The study’s objective is to determine which of the four zones are in demand and need to be prioritized for development, as per the model results. The data collection involves an online questionnaire, and the responses are collected from residents of Kabul and Herat. Agent-based modeling (ABM) is an emerging method of simulating urban dynamics. Cities are evolving continuously and are forming unique spatial patterns that result from the movement of residents in search of new locations that accommodate their needs and preferences. An agent-based model is developed using the weighted random selection process based on household size and income levels. The agents are the residents of Kabul and Herat, and the environment is the land use classification image using the Sentinel 2 image of Kabul New City. The barren class is treated as the developable area and is divided into four sub-sectors. The model simulates three alternative growth rate scenarios, i.e., ambitious, moderate, and steady. The results of the simulation reveal that the sub-sector Dehsabz South, being closer to Kabul city, is in higher demand. Barikab is another sub-sector high in demand, which has connectivity through the highway and is an upcoming industrial hub.

Keywords: population growth; cumulative probability; weighted demand (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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