Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas

This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated pro...

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Main Authors:	Aubrecht, Christoph, León Torres, José Antonio
Format:	Journal Article
Language:	en_US
Published:	MDPI 2016
Subjects:	top-down modeling urban areas nighttime lights human activity global spatial data urbanization spatial economics geospatial modeling
Online Access:	http://hdl.handle.net/10986/25372

id	okr-10986-25372
recordtype	oai_dc
spelling	okr-10986-253722021-05-25T10:54:36Z Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas Aubrecht, Christoph León Torres, José Antonio top-down modeling urban areas nighttime lights human activity global spatial data urbanization spatial economics geospatial modeling This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure model has been developed as one of the key elements for disaster risk and loss estimation. Global spatial datasets are therefore used consistently to ensure wide-scale applicability and transferability. Residential and mixed use areas need to be identified in order to spatially link accordingly compiled property stock information. In the presented study, multi-sensor nighttime Earth Observation data and derivative products are evaluated as proxies to identify areas of peak human activity. Intense artificial night lighting in that context is associated with a high likelihood of commercial and/or industrial presence. Areas of low light intensity, in turn, can be considered more likely residential. Iterative intensity thresholding is tested for Cuenca City, Ecuador, in order to best match a given reference situation based on cadastral land use data. The results and findings are considered highly relevant for the CDRP initiative, but more generally underline the relevance of remote sensing data for top-down modeling approaches at a wide spatial scale. 2016-11-17T18:53:44Z 2016-11-17T18:53:44Z 2016-02-04 Journal Article Remote Sensing 2072-4292 http://hdl.handle.net/10986/25372 en_US CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank MDPI
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
language	en_US
topic	top-down modeling urban areas nighttime lights human activity global spatial data urbanization spatial economics geospatial modeling
spellingShingle	top-down modeling urban areas nighttime lights human activity global spatial data urbanization spatial economics geospatial modeling Aubrecht, Christoph León Torres, José Antonio Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
description	This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure model has been developed as one of the key elements for disaster risk and loss estimation. Global spatial datasets are therefore used consistently to ensure wide-scale applicability and transferability. Residential and mixed use areas need to be identified in order to spatially link accordingly compiled property stock information. In the presented study, multi-sensor nighttime Earth Observation data and derivative products are evaluated as proxies to identify areas of peak human activity. Intense artificial night lighting in that context is associated with a high likelihood of commercial and/or industrial presence. Areas of low light intensity, in turn, can be considered more likely residential. Iterative intensity thresholding is tested for Cuenca City, Ecuador, in order to best match a given reference situation based on cadastral land use data. The results and findings are considered highly relevant for the CDRP initiative, but more generally underline the relevance of remote sensing data for top-down modeling approaches at a wide spatial scale.
format	Journal Article
author	Aubrecht, Christoph León Torres, José Antonio
author_facet	Aubrecht, Christoph León Torres, José Antonio
author_sort	Aubrecht, Christoph
title	Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
title_short	Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
title_full	Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
title_fullStr	Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
title_full_unstemmed	Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas
title_sort	evaluating multi-sensor nighttime earth observation data for identification of mixed vs. residential use in urban areas
publisher	MDPI
publishDate	2016
url	http://hdl.handle.net/10986/25372
_version_	1764459684060725248

Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas

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