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Size distributions of slums across the globe using different data and classification methods

Friesen, John ; Taubenböck, Hannes ; Wurm, Michael ; Pelz, P. F. (2019)
Size distributions of slums across the globe using different data and classification methods.
In: European Journal of Remote Sensing, 2019
doi: 10.1080/22797254.2019.1579617
Artikel, Zweitveröffentlichung, Verlagsversion

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Kurzbeschreibung (Abstract)

More than 900 million people worldwide live in slums. These slums mainly can be found in cities of the global south and are characterized by poor living conditions and usually insufficient access to basic infrastructure such as water or energy. In order to improve the living conditions of slum inhabitants, information about the number, location and size of the slums is required to plan supply infrastructure. We therefore identify morphological slums in eight different cities in Africa, South America and Asia, using remote sensing data and analyse their size distributions. We show that 84.6% of all observed morphological slums have a size between 0.001 and 0.1 km2. These results rely on a consistent approach using a clear ontology and conceptual frame for classification. However, classification methods for these underserved areas differ. We show slum classifications based on different methods reveal a strong dependency between the particular method and the resulting size distribution. The study shows the relevance of remote sensing for the investigation of slums and the results can be used for infrastructure planning, as infrastructure improvement projects are often limited to the large known slums. Whereas, the large number of small slums distributed across the city is often neglected.

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Friesen, John ; Taubenböck, Hannes ; Wurm, Michael ; Pelz, P. F.
Art des Eintrags: Zweitveröffentlichung
Titel: Size distributions of slums across the globe using different data and classification methods
Sprache: Englisch
Publikationsjahr: 2019
Publikationsdatum der Erstveröffentlichung: 2019
Verlag: Taylor & Francis
Titel der Zeitschrift, Zeitung oder Schriftenreihe: European Journal of Remote Sensing
DOI: 10.1080/22797254.2019.1579617
URL / URN: https://tuprints.ulb.tu-darmstadt.de/8639/
Herkunft: Zweitveröffentlichung aus gefördertem Golden Open Access
Kurzbeschreibung (Abstract):

More than 900 million people worldwide live in slums. These slums mainly can be found in cities of the global south and are characterized by poor living conditions and usually insufficient access to basic infrastructure such as water or energy. In order to improve the living conditions of slum inhabitants, information about the number, location and size of the slums is required to plan supply infrastructure. We therefore identify morphological slums in eight different cities in Africa, South America and Asia, using remote sensing data and analyse their size distributions. We show that 84.6% of all observed morphological slums have a size between 0.001 and 0.1 km2. These results rely on a consistent approach using a clear ontology and conceptual frame for classification. However, classification methods for these underserved areas differ. We show slum classifications based on different methods reveal a strong dependency between the particular method and the resulting size distribution. The study shows the relevance of remote sensing for the investigation of slums and the results can be used for infrastructure planning, as infrastructure improvement projects are often limited to the large known slums. Whereas, the large number of small slums distributed across the city is often neglected.

Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-86395
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Fluidsystemtechnik (FST) (seit 01.10.2006)
16 Fachbereich Maschinenbau > Institut für Fluidsystemtechnik (FST) (seit 01.10.2006) > Urbanisierung und Infrastruktur
Hinterlegungsdatum: 21 Apr 2019 19:55
Letzte Änderung: 16 Mär 2022 12:29
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