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Prerequisites and Factors for Effective and Efficient Implementation of Land Pooling/Reconstitution

Learnings from Asian Countries

Bibliographic Data

ID20404540
AuthorsJyoti Dash (Department of Housing, School of Planning and Architecture, New Delhi, India, corresponding author), P S N Rao (Department of Housing, School of Planning and Architecture, New Delhi, India)
Year2023
Volume14
Issue2
Pages252-268
Publication date2023-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Urbanization Asia (JOURNAL)
Journal identifiersISSN: 0975-4253 • E-ISSN: 0976-3546
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/09754253231193125
OpenAlexW4388467071
LanguageEN
References cited22

The land pooling/readjustment (LP/R) technique has been extensively used for centuries for fostering planned urban development in various developing and developed countries. In the recent past LP/R models have emerged in several Indian states and cities as an alternate to compulsory land acquisition. These include land pooling in Raipur, Chhattisgarh through the Town Development Scheme - 2015, the land pooling policy for Delhi - 2013, land readjustment and land pooling in Navi Mumbai, Maharashtra - 2014, and land pooling for Amravati, Andhra Pradesh - 2015. There are several factors that could adversely affect the implementation of LP/R projects and different situations would require different kinds of contextually relevant approaches for effective implementation of LP/R projects. Given the emerging LP/R models in several Indian states as an alternative to compulsory land acquisition, this article analyses the opportunities and constraints as recorded in literature around the world, with a focus on Asian countries, to identify the prerequisites and factors for effective and efficient implementation of the LP/R mechanism

Business · Civil engineering · Developing country · Economic growth · Economics · Environmental planning · Geography · Land use · Pooling · Computer Science · Engineering · Housing Market and Economics · Land Rights and Reforms · Urban and Rural Development Challenges · Artificial Intelligence

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