Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)

Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this stud...

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Autores principales:	Mohammad Reza Ramezani, Bofu Yu, Yahui Che
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	urban development population growth linear spectral mixture analysis (LSMA) landsat land use Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/28d280df94bd483bb653edbca511ce53
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spelling	oai:doaj.org-article:28d280df94bd483bb653edbca511ce532021-11-11T15:07:24ZPrediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)10.3390/app1121100442076-3417https://doaj.org/article/28d280df94bd483bb653edbca511ce532021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10044https://doaj.org/toc/2076-3417Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE < 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R<sup>2</sup> = 0.77) than that between population density and total imperviousness (R<sup>2</sup> = 0.52); (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.Mohammad Reza RamezaniBofu YuYahui CheMDPI AGarticleurban developmentpopulation growthlinear spectral mixture analysis (LSMA)landsatland useTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10044, p 10044 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	urban development population growth linear spectral mixture analysis (LSMA) landsat land use Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	urban development population growth linear spectral mixture analysis (LSMA) landsat land use Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Mohammad Reza Ramezani Bofu Yu Yahui Che Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
description	Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE < 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R<sup>2</sup> = 0.77) than that between population density and total imperviousness (R<sup>2</sup> = 0.52); (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.
format	article
author	Mohammad Reza Ramezani Bofu Yu Yahui Che
author_facet	Mohammad Reza Ramezani Bofu Yu Yahui Che
author_sort	Mohammad Reza Ramezani
title	Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
title_short	Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
title_full	Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
title_fullStr	Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
title_full_unstemmed	Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)
title_sort	prediction of total imperviousness from population density and land use data for urban areas (case study: south east queensland, australia)
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/28d280df94bd483bb653edbca511ce53
work_keys_str_mv	AT mohammadrezaramezani predictionoftotalimperviousnessfrompopulationdensityandlandusedataforurbanareascasestudysoutheastqueenslandaustralia AT bofuyu predictionoftotalimperviousnessfrompopulationdensityandlandusedataforurbanareascasestudysoutheastqueenslandaustralia AT yahuiche predictionoftotalimperviousnessfrompopulationdensityandlandusedataforurbanareascasestudysoutheastqueenslandaustralia
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Prediction of Total Imperviousness from Population Density and Land Use Data for Urban Areas (Case Study: South East Queensland, Australia)

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