Modelling the spatial extent of urban growth using a cellular automata-based model: a case study for Quito, Ecuador

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Modelling the spatial extent of urban growth using a cellular automata-based model : a case study for Quito, Ecuador. / Valencia, Victor H.; Levin, Gregor; Hansen, Henning Sten.

I: Geografisk Tidsskrift - Danish Journal of Geography, Bind 120, Nr. 2, 2020, s. 156-173.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Valencia, Victor H. ; Levin, Gregor ; Hansen, Henning Sten. / Modelling the spatial extent of urban growth using a cellular automata-based model : a case study for Quito, Ecuador. I: Geografisk Tidsskrift - Danish Journal of Geography. 2020 ; Bind 120, Nr. 2. s. 156-173.

Bibtex

@article{a8b2fdea0b9245e48f37a10ba4d65dbc,
title = "Modelling the spatial extent of urban growth using a cellular automata-based model: a case study for Quito, Ecuador",
abstract = "Since the late 1980s, the city of Quito shows a considerable expansion of urban land. This study generates plausible scenarios of urban growth that can be applied within urban planning and used for applications, such as projections of transportation needs, or air pollution exposure. We develop a methodology to map urban growth using the LUCIA model. The urban growth is estimated based on land use maps, regulatory constraints, population, proximity, suitability, accessibility to main roads, urban areas, and sub-centralities. The model considers the complex topography of Quito by defining the driving forces according to the elevation of the terrain. The model is calibrated for the period 2000–2016 and satisfactorily evaluated for 2018 applying a cell by cell and spatial pattern comparison. We analyse the effect on the result assessment if small errors nearby the actual and simulated urban land are considered as correct, finding an increase of 30% in the accuracy for one cell of distance. We apply the model to predict the urban growth of Quito between 2016 and 2040. Results show that, if the current trend continues, the urban land will increase by 84% with a continuous fragmentation that stabilizes around the year 2025.",
keywords = "cellular automata, land use change, quito, spatial modelling, Urban growth",
author = "Valencia, {Victor H.} and Gregor Levin and Hansen, {Henning Sten}",
note = "Funding Information: This study is part of Ph.D. studies funded by SENECYT, Ecuador, Grant ID: CZ02-000105-2018. Publisher Copyright: {\textcopyright} 2020 The Royal Danish Geographical Society. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
doi = "10.1080/00167223.2020.1823867",
language = "English",
volume = "120",
pages = "156--173",
journal = "Geografisk Tidsskrift",
issn = "0016-7223",
publisher = "Routledge",
number = "2",

}

RIS

TY - JOUR

T1 - Modelling the spatial extent of urban growth using a cellular automata-based model

T2 - a case study for Quito, Ecuador

AU - Valencia, Victor H.

AU - Levin, Gregor

AU - Hansen, Henning Sten

N1 - Funding Information: This study is part of Ph.D. studies funded by SENECYT, Ecuador, Grant ID: CZ02-000105-2018. Publisher Copyright: © 2020 The Royal Danish Geographical Society. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - Since the late 1980s, the city of Quito shows a considerable expansion of urban land. This study generates plausible scenarios of urban growth that can be applied within urban planning and used for applications, such as projections of transportation needs, or air pollution exposure. We develop a methodology to map urban growth using the LUCIA model. The urban growth is estimated based on land use maps, regulatory constraints, population, proximity, suitability, accessibility to main roads, urban areas, and sub-centralities. The model considers the complex topography of Quito by defining the driving forces according to the elevation of the terrain. The model is calibrated for the period 2000–2016 and satisfactorily evaluated for 2018 applying a cell by cell and spatial pattern comparison. We analyse the effect on the result assessment if small errors nearby the actual and simulated urban land are considered as correct, finding an increase of 30% in the accuracy for one cell of distance. We apply the model to predict the urban growth of Quito between 2016 and 2040. Results show that, if the current trend continues, the urban land will increase by 84% with a continuous fragmentation that stabilizes around the year 2025.

AB - Since the late 1980s, the city of Quito shows a considerable expansion of urban land. This study generates plausible scenarios of urban growth that can be applied within urban planning and used for applications, such as projections of transportation needs, or air pollution exposure. We develop a methodology to map urban growth using the LUCIA model. The urban growth is estimated based on land use maps, regulatory constraints, population, proximity, suitability, accessibility to main roads, urban areas, and sub-centralities. The model considers the complex topography of Quito by defining the driving forces according to the elevation of the terrain. The model is calibrated for the period 2000–2016 and satisfactorily evaluated for 2018 applying a cell by cell and spatial pattern comparison. We analyse the effect on the result assessment if small errors nearby the actual and simulated urban land are considered as correct, finding an increase of 30% in the accuracy for one cell of distance. We apply the model to predict the urban growth of Quito between 2016 and 2040. Results show that, if the current trend continues, the urban land will increase by 84% with a continuous fragmentation that stabilizes around the year 2025.

KW - cellular automata

KW - land use change

KW - quito

KW - spatial modelling

KW - Urban growth

UR - http://www.scopus.com/inward/record.url?scp=85094915164&partnerID=8YFLogxK

U2 - 10.1080/00167223.2020.1823867

DO - 10.1080/00167223.2020.1823867

M3 - Journal article

AN - SCOPUS:85094915164

VL - 120

SP - 156

EP - 173

JO - Geografisk Tidsskrift

JF - Geografisk Tidsskrift

SN - 0016-7223

IS - 2

ER -