Localising global urban development; simulating local exposure to natural hazards in the global 2UP model

Eric Koomen, Jolien van Huystee, Bas van Bemmel, Arno Bouwman, Willem Ligtvoet, Bo Pieter Johannes Andree

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademic

Abstract

Future population growth is expected to concentrate in urban agglomerations that are already exposed to numerous natural hazards. It is difficult, however, to assess this increase in risk as natural hazards are often concentrated in space and population growth scenarios tend to be defined at much coarser scales. By combining recently released high-resolution spatial data on land use, population density and natural hazards with a novel, computationally effective simulation approach we analyse global increases in local exposure to two important natural hazards: flood risk and landslides. We develop global spatially explicitp rojections of population change and urban expansion using a land-use and population allocation model. The model is developed in the Geo Data and Model
Server (GeoDMS) modelling framework, that also underlies Land Use Scanner and several other operational models of land-use change developed for individual countries, larger river catchment areas and the territory of the European Union. The model disaggregates scenario-based national-level population estimates to a high resolution spatial grid (30 arc seconds). It simulates local population
development and urban growth on a global scale. The main steps include: 1) compiling current global population and urban land use data layers; 2) developing projections of future population and urban area growth; 3) defining suitable locations for future development following a logistic regression
analysis explaining urban patterns around the globe; 4) allocating future urban area development and population change; 5) assessing exposure to natural hazards. We conclude that on global scale urban development is likely to strongly increase exposure to both floods and landslides. In almost all world regions urban growth during the coming decades is larger in hazard-prone areas than in non-exposed areas. This is especially prevalent for countries in Sub-Saharan Africa and South Asia. In developed countries growth rates are much lower and show far less variation between exposed and non-exposed areas. In our presentation we will discuss the functioning of the model, its calibration and validation and the most interesting outcomes. We will briefly reflect on its usefulness for policymakers, suggesting that the model is best applied in fast developing regions where model-based risk assessments were hitherto impossible because of a lack of data.
Original languageEnglish
Title of host publicationBook of abstracts
Subtitle of host publication21st European Colloquium on Theoretical and Quantitative Geography
EditorsG Caruso, P Gerber, K Jones, O Klein, C Perchoux
Place of PublicationEsch-sur-Alzette/Belval, Luxembourg
PublisherLuxembourg Institute of Socio-Economic Research (LISER)
Pages126
Number of pages1
ISBN (Print)978-2-9199594-0-2
Publication statusPublished - 8 Sep 2019

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natural hazard
urban development
land use
urban growth
population growth
landslide
urban area
global model
exposure
scanner
agglomeration
spatial data
land use change
logistics
European Union
population density
spatial resolution
risk assessment
calibration
river

Cite this

Koomen, E., van Huystee, J., van Bemmel, B., Bouwman, A., Ligtvoet, W., & Andree, B. P. J. (2019). Localising global urban development; simulating local exposure to natural hazards in the global 2UP model. In G. Caruso, P. Gerber, K. Jones, O. Klein, & C. Perchoux (Eds.), Book of abstracts: 21st European Colloquium on Theoretical and Quantitative Geography (pp. 126). Esch-sur-Alzette/Belval, Luxembourg: Luxembourg Institute of Socio-Economic Research (LISER).
Koomen, Eric ; van Huystee, Jolien ; van Bemmel, Bas ; Bouwman, Arno ; Ligtvoet, Willem ; Andree, Bo Pieter Johannes. / Localising global urban development; simulating local exposure to natural hazards in the global 2UP model. Book of abstracts: 21st European Colloquium on Theoretical and Quantitative Geography. editor / G Caruso ; P Gerber ; K Jones ; O Klein ; C Perchoux. Esch-sur-Alzette/Belval, Luxembourg : Luxembourg Institute of Socio-Economic Research (LISER), 2019. pp. 126
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title = "Localising global urban development; simulating local exposure to natural hazards in the global 2UP model",
abstract = "Future population growth is expected to concentrate in urban agglomerations that are already exposed to numerous natural hazards. It is difficult, however, to assess this increase in risk as natural hazards are often concentrated in space and population growth scenarios tend to be defined at much coarser scales. By combining recently released high-resolution spatial data on land use, population density and natural hazards with a novel, computationally effective simulation approach we analyse global increases in local exposure to two important natural hazards: flood risk and landslides. We develop global spatially explicitp rojections of population change and urban expansion using a land-use and population allocation model. The model is developed in the Geo Data and ModelServer (GeoDMS) modelling framework, that also underlies Land Use Scanner and several other operational models of land-use change developed for individual countries, larger river catchment areas and the territory of the European Union. The model disaggregates scenario-based national-level population estimates to a high resolution spatial grid (30 arc seconds). It simulates local populationdevelopment and urban growth on a global scale. The main steps include: 1) compiling current global population and urban land use data layers; 2) developing projections of future population and urban area growth; 3) defining suitable locations for future development following a logistic regressionanalysis explaining urban patterns around the globe; 4) allocating future urban area development and population change; 5) assessing exposure to natural hazards. We conclude that on global scale urban development is likely to strongly increase exposure to both floods and landslides. In almost all world regions urban growth during the coming decades is larger in hazard-prone areas than in non-exposed areas. This is especially prevalent for countries in Sub-Saharan Africa and South Asia. In developed countries growth rates are much lower and show far less variation between exposed and non-exposed areas. In our presentation we will discuss the functioning of the model, its calibration and validation and the most interesting outcomes. We will briefly reflect on its usefulness for policymakers, suggesting that the model is best applied in fast developing regions where model-based risk assessments were hitherto impossible because of a lack of data.",
author = "Eric Koomen and {van Huystee}, Jolien and {van Bemmel}, Bas and Arno Bouwman and Willem Ligtvoet and Andree, {Bo Pieter Johannes}",
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Koomen, E, van Huystee, J, van Bemmel, B, Bouwman, A, Ligtvoet, W & Andree, BPJ 2019, Localising global urban development; simulating local exposure to natural hazards in the global 2UP model. in G Caruso, P Gerber, K Jones, O Klein & C Perchoux (eds), Book of abstracts: 21st European Colloquium on Theoretical and Quantitative Geography. Luxembourg Institute of Socio-Economic Research (LISER), Esch-sur-Alzette/Belval, Luxembourg, pp. 126.

Localising global urban development; simulating local exposure to natural hazards in the global 2UP model. / Koomen, Eric; van Huystee, Jolien ; van Bemmel, Bas; Bouwman, Arno; Ligtvoet, Willem; Andree, Bo Pieter Johannes.

Book of abstracts: 21st European Colloquium on Theoretical and Quantitative Geography. ed. / G Caruso; P Gerber; K Jones; O Klein; C Perchoux. Esch-sur-Alzette/Belval, Luxembourg : Luxembourg Institute of Socio-Economic Research (LISER), 2019. p. 126.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademic

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T1 - Localising global urban development; simulating local exposure to natural hazards in the global 2UP model

AU - Koomen, Eric

AU - van Huystee, Jolien

AU - van Bemmel, Bas

AU - Bouwman, Arno

AU - Ligtvoet, Willem

AU - Andree, Bo Pieter Johannes

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N2 - Future population growth is expected to concentrate in urban agglomerations that are already exposed to numerous natural hazards. It is difficult, however, to assess this increase in risk as natural hazards are often concentrated in space and population growth scenarios tend to be defined at much coarser scales. By combining recently released high-resolution spatial data on land use, population density and natural hazards with a novel, computationally effective simulation approach we analyse global increases in local exposure to two important natural hazards: flood risk and landslides. We develop global spatially explicitp rojections of population change and urban expansion using a land-use and population allocation model. The model is developed in the Geo Data and ModelServer (GeoDMS) modelling framework, that also underlies Land Use Scanner and several other operational models of land-use change developed for individual countries, larger river catchment areas and the territory of the European Union. The model disaggregates scenario-based national-level population estimates to a high resolution spatial grid (30 arc seconds). It simulates local populationdevelopment and urban growth on a global scale. The main steps include: 1) compiling current global population and urban land use data layers; 2) developing projections of future population and urban area growth; 3) defining suitable locations for future development following a logistic regressionanalysis explaining urban patterns around the globe; 4) allocating future urban area development and population change; 5) assessing exposure to natural hazards. We conclude that on global scale urban development is likely to strongly increase exposure to both floods and landslides. In almost all world regions urban growth during the coming decades is larger in hazard-prone areas than in non-exposed areas. This is especially prevalent for countries in Sub-Saharan Africa and South Asia. In developed countries growth rates are much lower and show far less variation between exposed and non-exposed areas. In our presentation we will discuss the functioning of the model, its calibration and validation and the most interesting outcomes. We will briefly reflect on its usefulness for policymakers, suggesting that the model is best applied in fast developing regions where model-based risk assessments were hitherto impossible because of a lack of data.

AB - Future population growth is expected to concentrate in urban agglomerations that are already exposed to numerous natural hazards. It is difficult, however, to assess this increase in risk as natural hazards are often concentrated in space and population growth scenarios tend to be defined at much coarser scales. By combining recently released high-resolution spatial data on land use, population density and natural hazards with a novel, computationally effective simulation approach we analyse global increases in local exposure to two important natural hazards: flood risk and landslides. We develop global spatially explicitp rojections of population change and urban expansion using a land-use and population allocation model. The model is developed in the Geo Data and ModelServer (GeoDMS) modelling framework, that also underlies Land Use Scanner and several other operational models of land-use change developed for individual countries, larger river catchment areas and the territory of the European Union. The model disaggregates scenario-based national-level population estimates to a high resolution spatial grid (30 arc seconds). It simulates local populationdevelopment and urban growth on a global scale. The main steps include: 1) compiling current global population and urban land use data layers; 2) developing projections of future population and urban area growth; 3) defining suitable locations for future development following a logistic regressionanalysis explaining urban patterns around the globe; 4) allocating future urban area development and population change; 5) assessing exposure to natural hazards. We conclude that on global scale urban development is likely to strongly increase exposure to both floods and landslides. In almost all world regions urban growth during the coming decades is larger in hazard-prone areas than in non-exposed areas. This is especially prevalent for countries in Sub-Saharan Africa and South Asia. In developed countries growth rates are much lower and show far less variation between exposed and non-exposed areas. In our presentation we will discuss the functioning of the model, its calibration and validation and the most interesting outcomes. We will briefly reflect on its usefulness for policymakers, suggesting that the model is best applied in fast developing regions where model-based risk assessments were hitherto impossible because of a lack of data.

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SN - 978-2-9199594-0-2

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A2 - Klein, O

A2 - Perchoux, C

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Koomen E, van Huystee J, van Bemmel B, Bouwman A, Ligtvoet W, Andree BPJ. Localising global urban development; simulating local exposure to natural hazards in the global 2UP model. In Caruso G, Gerber P, Jones K, Klein O, Perchoux C, editors, Book of abstracts: 21st European Colloquium on Theoretical and Quantitative Geography. Esch-sur-Alzette/Belval, Luxembourg: Luxembourg Institute of Socio-Economic Research (LISER). 2019. p. 126