FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS

Rapid urbanization in localities offers a lot of opportunities but also imposes a lot of challenges due to its direct relationship to population growth. This leads to an increase in the demand for essential goods and services such as food, energy, water among others. Hence, small-area population for...

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Autores principales:	L. Hilario, J. A. Duka, M. I. Mabalot, J. Domingo, K. A. Vergara, M. J. Villanueva-Jerez, K. A. Cabello, G. A. Rufino, C. J. Sarmiento
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
Acceso en línea:	https://doaj.org/article/a7a1acf308ff4a7d8bd1510942a0f47d
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spelling	oai:doaj.org-article:a7a1acf308ff4a7d8bd1510942a0f47d2021-11-19T01:36:30ZFORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS10.5194/isprs-archives-XLVI-4-W6-2021-185-20211682-17502194-9034https://doaj.org/article/a7a1acf308ff4a7d8bd1510942a0f47d2021-11-01T00:00:00Zhttps://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W6-2021/185/2021/isprs-archives-XLVI-4-W6-2021-185-2021.pdfhttps://doaj.org/toc/1682-1750https://doaj.org/toc/2194-9034Rapid urbanization in localities offers a lot of opportunities but also imposes a lot of challenges due to its direct relationship to population growth. This leads to an increase in the demand for essential goods and services such as food, energy, water among others. Hence, small-area population forecasts have long been an important element in urban and regional planning to aid in the decision-making processes in a locality. The promise of smart cities, through the use of advanced technologies, is to make cities livable and sustainable, preparing more opportunities and addressing challenges on urbanization. This study aims to forecast population distribution in Iloilo city by incorporating GIS techniques and highlighting the use of spatial autocorrelation models. The spatial interaction effects between neighboring barangays are taken into consideration to identify a set of factors affecting the population. The results identified a set of significant explanatory variables and whether it will result in an increase or decrease in population. The study also illustrates the resulting population forecast comparing it to the actual total population of the city.L. HilarioJ. A. DukaM. I. MabalotJ. DomingoK. A. VergaraM. J. Villanueva-JerezK. A. CabelloG. A. RufinoC. J. SarmientoCopernicus PublicationsarticleTechnologyTEngineering (General). Civil engineering (General)TA1-2040Applied optics. PhotonicsTA1501-1820ENThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-4-W6-2021, Pp 185-192 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
spellingShingle	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 L. Hilario J. A. Duka M. I. Mabalot J. Domingo K. A. Vergara M. J. Villanueva-Jerez K. A. Cabello G. A. Rufino C. J. Sarmiento FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
description	Rapid urbanization in localities offers a lot of opportunities but also imposes a lot of challenges due to its direct relationship to population growth. This leads to an increase in the demand for essential goods and services such as food, energy, water among others. Hence, small-area population forecasts have long been an important element in urban and regional planning to aid in the decision-making processes in a locality. The promise of smart cities, through the use of advanced technologies, is to make cities livable and sustainable, preparing more opportunities and addressing challenges on urbanization. This study aims to forecast population distribution in Iloilo city by incorporating GIS techniques and highlighting the use of spatial autocorrelation models. The spatial interaction effects between neighboring barangays are taken into consideration to identify a set of factors affecting the population. The results identified a set of significant explanatory variables and whether it will result in an increase or decrease in population. The study also illustrates the resulting population forecast comparing it to the actual total population of the city.
format	article
author	L. Hilario J. A. Duka M. I. Mabalot J. Domingo K. A. Vergara M. J. Villanueva-Jerez K. A. Cabello G. A. Rufino C. J. Sarmiento
author_facet	L. Hilario J. A. Duka M. I. Mabalot J. Domingo K. A. Vergara M. J. Villanueva-Jerez K. A. Cabello G. A. Rufino C. J. Sarmiento
author_sort	L. Hilario
title	FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
title_short	FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
title_full	FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
title_fullStr	FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
title_full_unstemmed	FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS
title_sort	forecasting urban population distribution of iloilo city using gis and spatial autocorrelation models
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/a7a1acf308ff4a7d8bd1510942a0f47d
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FORECASTING URBAN POPULATION DISTRIBUTION OF ILOILO CITY USING GIS AND SPATIAL AUTOCORRELATION MODELS

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