Please use this identifier to cite or link to this item: http://dspace.spab.ac.in:80/handle/123456789/2463
Title: AI Based Predictive Modelling for Land Use Dynamics:
Other Titles: A Case of Ahmedabad
Authors: Bakshi, Shrimant
Keywords: Land-use Planning
Data-driven Decisions
Issue Date: 17-Dec-2024
Publisher: SPA Bhopal
Series/Report no.: 2022MURP026;TH002160
Abstract: India's rapid urbanization has caused several issues in terms of its development and service provision to the growing population. As the world is moving towards AI-driven technology, there are several attempts which are being made in order to identify where AI and data-driven methods can be deployed in order to get insights and results in quicker and efficient manner. The major concerns in present day spatial planning is the efficiency in which the plans and land-use allocations are carried out and the associated rationale behind them as well as the lack of implementation of land-uses in the urban areas at the ground-level. In order to address the same issue and to discover new technological intervention in the domain of spatial planning, it is an attempt to understand that how artificial intelligence and machine learning techniques can improve the speed and quality of analysing urban data and how it can interpret them and can be useful in prediction of future scenarios and land use change over a given period of time. In the study, through a case of Ahmedabad city, the data related to land parcels in present time coupled with various factors which actually act as a guiding factor for the land-use of a particular land parcel have been collected and various machine learning models have been used to understand the complex relationships between land parcel attributes and the macro and micro factors which can affect its use. The methodology broadly involves data pre-processing, feature engineering and model training. The study is also an attempt to understand how urban planners can anticipate future scenarios and its effects and help significantly in approaches to informed strategic decision-making process. The integration of machine learning and AI techniques can facilitate data-driven decision-making and in promoting transparency with sustainable development for cities which have a dynamic character. Keywords : Machine Learning, Artificial Intelligence (AI),
URI: http://dspace.spab.ac.in:80/handle/123456789/2463
Appears in Collections:Master of Planning (Urban and Regional Planning)

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