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Estimating quality of life dimensions from urban spatial pattern metrics

Sapena Moll, Marta and Wurm, Michael and Taubenböck, Hannes and Tuia, Devis and Ruiz, Luis A. (2021) Estimating quality of life dimensions from urban spatial pattern metrics. Computers, Environment and Urban Systems, 85, pp. 1-11. Elsevier. doi: 10.1016/j.compenvurbsys.2020.101549. ISSN 0198-9715.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0198971520302829


The spatial structure of urban areas plays a major role in the daily life of dwellers. The current policy framework to ensure the quality of life of inhabitants leaving no one behind, leads decision-makers to seek better-informed choices for the sustainable planning of urban areas. Thus, a better understanding between the spatial structure of cities and their socio-economic level is of crucial relevance. Accordingly, the purpose of this paper is to quantify this two-way relationship. Therefore, we measured spatial patterns of 31 cities in North Rhine-Westphalia, Germany. We rely on spatial pattern metrics derived from a Local Climate Zone classification obtained by fusing remote sensing and open GIS data with a machine learning approach. Based upon the data, we quantified the relationship between spatial pattern metrics and socio-economic variables related to ‘education’, ‘health’, ‘living conditions’, ‘labor’, and ‘transport’ by means of multiple linear regression models, explaining the variability of the socio-economic variables from 43% up to 82%. Additionally, we grouped cities according to their level of ‘quality of life’ using the socio-economic variables, and found that the spatial pattern of low-dense built-up types was different among socio-economic groups. The proposed methodology described in this paper is transferable to other datasets, levels, and regions. This is of great potential, due to the growing availability of open statistical and satellite data and derived products. Moreover, we discuss the limitations and needed considerations when conducting such studies.

Item URL in elib:https://elib.dlr.de/136461/
Document Type:Article
Title:Estimating quality of life dimensions from urban spatial pattern metrics
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Sapena Moll, MartaMarta.Sapena-Moll (at) dlr.dehttps://orcid.org/0000-0003-3283-319X
Wurm, Michaelmichael.wurm (at) dlr.dehttps://orcid.org/0000-0001-5967-1894
Taubenböck, Hanneshannes.taubenboeck (at) dlr.dehttps://orcid.org/0000-0003-4360-9126
Tuia, Devisdevis.tuia (at) wur.nlhttps://orcid.org/0000-0003-0374-2459
Ruiz, Luis A.laruiz (at) cgf.upv.eshttps://orcid.org/0000-0003-0073-7259
Date:January 2021
Journal or Publication Title:Computers, Environment and Urban Systems
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1016/j.compenvurbsys.2020.101549
Page Range:pp. 1-11
Keywords:Spatial metrics, Socio-economic variables, Local climate zones, Quality of life, Remote sensing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods, R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Sapena Moll, Marta
Deposited On:07 Oct 2020 10:19
Last Modified:14 Jan 2022 11:00

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