Estimating ambient population density using physical features from GIS and machine learning: a study based on Japanese neighborhood

Estimating ambient population density using physical features from GIS and machine learning: a study based on Japanese neighborhood

This research aimed to develop an alternative method for estimating ambient population density at the neighborhood scale by utilizing a simple and universally available dataset. Physical environment data from GIS & OSM databases, basic statistics, and population density data from Mobile Spatial...

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Bibliographic Details
Main Authors: Pasit Rojradtanasiri, Junko Tamura, Masami Kobayashi
Format: Article
Language:English
Published: Taylor & Francis Group 2024-11-01
Series:Journal of Asian Architecture and Building Engineering
Subjects:
neighborhood planning
machine learning
correlation analysis
ambient population
gis
Online Access:http://dx.doi.org/10.1080/13467581.2024.2428262
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