Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model

The main motivation of this paper is to shed new light on the problem of spatial identification of urban and rural areas globally, and to provide a compatible disaggregation framework for linking associated country-specific, non-spatial data compilations, such as building type inventories. Existing...

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Main Authors:	Aubrecht, Christoph, Gunasekera, Rashmin, Ungar, Joachim, Ishizawa, Oscar
Format:	Journal Article
Language:	en_US
Published:	Elsevier 2016
Subjects:	urban-rural patterns spatial economics population distribution urbanization geospatial modeling adaptive
Online Access:	http://hdl.handle.net/10986/25370

id	okr-10986-25370
recordtype	oai_dc
spelling	okr-10986-253702021-05-25T10:54:36Z Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model Aubrecht, Christoph Gunasekera, Rashmin Ungar, Joachim Ishizawa, Oscar urban-rural patterns spatial economics population distribution urbanization geospatial modeling adaptive The main motivation of this paper is to shed new light on the problem of spatial identification of urban and rural areas globally, and to provide a compatible disaggregation framework for linking associated country-specific, non-spatial data compilations, such as building type inventories. Existing homogeneously set-up global urban extent models commonly ignore local-level specifics. While global consistency and regional comparability of urban characteristics are much strived-for goals in the global development and remote sensing communities, non-conformity at the national level often renders such models inapplicable for effective decision-making. Furthermore, the focus on identifying ‘urban’ leads to an ill-defined ‘rural’, which is simply defined by contrast as ‘everything else’; a questionable definition when referring to strongly spatially localized residential patterns. In this paper we introduce the novel iURBAN geospatial modeling approach, identifying Urban–Rural patterns in Built-up-Adjusted and Nationally-adaptive manner. The model operates at global scale, but at the same time conforms to country specifics. In this model, high-resolution, satellite-derived, built-up data is used to consistently detect global human settlements at unprecedented spatial detail. In combination with global gridded population data, and with reference to national level statistical information on urban population ratios globally compiled in the annually-released UN World Urbanization Prospects, iURBAN identifies matching urban extents. Additionally, a novel reallocation algorithm is introduced which addresses the poor representation of rural areas that is inherent in existing global population grids. Associating all of the population with inhabitable, built-up area and conforming to national urban–rural ratios, iURBAN sets a new standard by enabling careful consideration of both urban and rural as opposed to traditional urban-biased approaches. 2016-11-17T18:03:10Z 2016-11-17T18:03:10Z 2016-12 Journal Article Remote Sensing of Environment 0034-4257 http://hdl.handle.net/10986/25370 en_US CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo/ World Bank Elsevier Publications & Research :: Journal Article Publications & Research
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	en_US
topic	urban-rural patterns spatial economics population distribution urbanization geospatial modeling adaptive
spellingShingle	urban-rural patterns spatial economics population distribution urbanization geospatial modeling adaptive Aubrecht, Christoph Gunasekera, Rashmin Ungar, Joachim Ishizawa, Oscar Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
description	The main motivation of this paper is to shed new light on the problem of spatial identification of urban and rural areas globally, and to provide a compatible disaggregation framework for linking associated country-specific, non-spatial data compilations, such as building type inventories. Existing homogeneously set-up global urban extent models commonly ignore local-level specifics. While global consistency and regional comparability of urban characteristics are much strived-for goals in the global development and remote sensing communities, non-conformity at the national level often renders such models inapplicable for effective decision-making. Furthermore, the focus on identifying ‘urban’ leads to an ill-defined ‘rural’, which is simply defined by contrast as ‘everything else’; a questionable definition when referring to strongly spatially localized residential patterns. In this paper we introduce the novel iURBAN geospatial modeling approach, identifying Urban–Rural patterns in Built-up-Adjusted and Nationally-adaptive manner. The model operates at global scale, but at the same time conforms to country specifics. In this model, high-resolution, satellite-derived, built-up data is used to consistently detect global human settlements at unprecedented spatial detail. In combination with global gridded population data, and with reference to national level statistical information on urban population ratios globally compiled in the annually-released UN World Urbanization Prospects, iURBAN identifies matching urban extents. Additionally, a novel reallocation algorithm is introduced which addresses the poor representation of rural areas that is inherent in existing global population grids. Associating all of the population with inhabitable, built-up area and conforming to national urban–rural ratios, iURBAN sets a new standard by enabling careful consideration of both urban and rural as opposed to traditional urban-biased approaches.
format	Journal Article
author	Aubrecht, Christoph Gunasekera, Rashmin Ungar, Joachim Ishizawa, Oscar
author_facet	Aubrecht, Christoph Gunasekera, Rashmin Ungar, Joachim Ishizawa, Oscar
author_sort	Aubrecht, Christoph
title	Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
title_short	Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
title_full	Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
title_fullStr	Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
title_full_unstemmed	Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model
title_sort	consistent yet adaptive global geospatial identification of urban–rural patterns : the iurban model
publisher	Elsevier
publishDate	2016
url	http://hdl.handle.net/10986/25370
_version_	1764459678785339392

Consistent Yet Adaptive Global Geospatial Identification of Urban–Rural Patterns : The iURBAN Model

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