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A Computational Geospatial Approach to Assessing Land-Use Compatibility in Urban Planning
by
Zaroujtaghi, Ayda
, Mansourihanis, Omid
, Maghsoodi Tilaki, Mohammad Javad
, Yousefian, Samira
in
case studies
/ Cities
/ City planning
/ Compatibility
/ compatibility analysis
/ Computer applications
/ Data integration
/ Decision making
/ Factories
/ Geographic information systems
/ Geospatial data
/ information science
/ Iran
/ land
/ Land economics
/ Land use
/ Land use management
/ Land use planning
/ Launching pads
/ Machine learning
/ Municipal research
/ Objectivity
/ Quantitative analysis
/ spatial conflicts
/ spatial data
/ spatial modeling
/ Subjectivity
/ Sustainable development
/ Urban development
/ Urban land use
/ Urban planning
/ Urbanization
2023
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A Computational Geospatial Approach to Assessing Land-Use Compatibility in Urban Planning
by
Zaroujtaghi, Ayda
, Mansourihanis, Omid
, Maghsoodi Tilaki, Mohammad Javad
, Yousefian, Samira
in
case studies
/ Cities
/ City planning
/ Compatibility
/ compatibility analysis
/ Computer applications
/ Data integration
/ Decision making
/ Factories
/ Geographic information systems
/ Geospatial data
/ information science
/ Iran
/ land
/ Land economics
/ Land use
/ Land use management
/ Land use planning
/ Launching pads
/ Machine learning
/ Municipal research
/ Objectivity
/ Quantitative analysis
/ spatial conflicts
/ spatial data
/ spatial modeling
/ Subjectivity
/ Sustainable development
/ Urban development
/ Urban land use
/ Urban planning
/ Urbanization
2023
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Do you wish to request the book?
A Computational Geospatial Approach to Assessing Land-Use Compatibility in Urban Planning
by
Zaroujtaghi, Ayda
, Mansourihanis, Omid
, Maghsoodi Tilaki, Mohammad Javad
, Yousefian, Samira
in
case studies
/ Cities
/ City planning
/ Compatibility
/ compatibility analysis
/ Computer applications
/ Data integration
/ Decision making
/ Factories
/ Geographic information systems
/ Geospatial data
/ information science
/ Iran
/ land
/ Land economics
/ Land use
/ Land use management
/ Land use planning
/ Launching pads
/ Machine learning
/ Municipal research
/ Objectivity
/ Quantitative analysis
/ spatial conflicts
/ spatial data
/ spatial modeling
/ Subjectivity
/ Sustainable development
/ Urban development
/ Urban land use
/ Urban planning
/ Urbanization
2023
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A Computational Geospatial Approach to Assessing Land-Use Compatibility in Urban Planning
Journal Article
A Computational Geospatial Approach to Assessing Land-Use Compatibility in Urban Planning
2023
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Overview
Amidst rapid urbanization, sustainable development requires moving beyond subjective land-use planning techniques toward innovative computational geospatial models. This paper introduces a GIS-based quantitative framework to enable objective, rigorous land-use compatibility analysis. Uniquely, the model evaluates radial impacts and expert-defined criteria across multiple scales, overcoming the limitations of qualitative approaches. Cell-by-cell computation identifies emerging spatial conflicts with enhanced realism. A case study in Qaemshahr, Iran, demonstrated the model’s proficiency in revealing incompatibilities and hotspots, surpassing conventional methodologies. Quantitative analysis provided accurate, transparent insights for evidence-based planning and consistency in evaluation. Ongoing improvements through 3D, real-time data integration and machine learning will further the objectivity. While extensive testing across diverse urban contexts is still needed, this pioneering computational technique marks a transition from subjective to objective methodologies. Situated at the intersection of geographic information science and urban planning, this study serves as a launchpad for advancing robust geospatial models to shape more equitable, resilient urban futures amidst complex sustainability challenges. The development of rigorous computational techniques remains fundamental, and the present innovative model can be used to provide objective, scientifically grounded compatibility analyses to guide land-use planning.
Publisher
MDPI AG
Subject
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