Ulloa Torrealba, Yrneh Z. und Neumayer, Dominik und Schmitt, Andreas und Taubenböck, Hannes (2023) Solid waste on the streets and socieconomic class using remote sensing. In: 2023 Joint Urban Remote Sensing Event, JURSE 2023, Seiten 1-4. IEEE. IEEE-CPS Joint Urban Remote Sensing Event (JURSE), 2023-05-17 - 2023-05-19, Heraklion, Greece. doi: 10.1109/JURSE57346.2023.10144153. ISBN 978-166549373-4. ISSN 2642-9535.
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Offizielle URL: https://ieeexplore.ieee.org/document/10144153
Kurzfassung
Solid waste dumped on the streets affects human hygiene, well-being, and increases deprivation. This happens as result of a failure in the solid waste management of a city. This is especially observed in informal poorer areas. With the current increase of population in urban settlements, and especially in informal areas, new techniques are in demand to identify litter dumped on the streets in a rapid manner. In this study, aerial imagery of the city of Medellín were segmented with a k-means based algorithm and classified with a Random Forest decision tree ensemble. The results show, that with this approach garbage detection is possible with an Overall Accuracy of 82 %. Comparison with socioeconomic data from a national census on housing shows that solid waste was identified with higher shares in poorer districts. This method can be implemented at city scale and therefore might be useful for decision makers.
elib-URL des Eintrags: | https://elib.dlr.de/196369/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag, Poster) | ||||||||||||||||||||
Titel: | Solid waste on the streets and socieconomic class using remote sensing | ||||||||||||||||||||
Autoren: |
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Datum: | 2023 | ||||||||||||||||||||
Erschienen in: | 2023 Joint Urban Remote Sensing Event, JURSE 2023 | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Nein | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.1109/JURSE57346.2023.10144153 | ||||||||||||||||||||
Seitenbereich: | Seiten 1-4 | ||||||||||||||||||||
Verlag: | IEEE | ||||||||||||||||||||
ISSN: | 2642-9535 | ||||||||||||||||||||
ISBN: | 978-166549373-4 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | urban remote sensing, machine learning, solid waste, urbanization | ||||||||||||||||||||
Veranstaltungstitel: | IEEE-CPS Joint Urban Remote Sensing Event (JURSE) | ||||||||||||||||||||
Veranstaltungsort: | Heraklion, Greece | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 17 Mai 2023 | ||||||||||||||||||||
Veranstaltungsende: | 19 Mai 2023 | ||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Fernerkundung u. Geoforschung, R - Geowissenschaftl. Fernerkundungs- und GIS-Verfahren | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Deutsches Fernerkundungsdatenzentrum > Georisiken und zivile Sicherheit | ||||||||||||||||||||
Hinterlegt von: | Taubenböck, Prof. Dr. Hannes | ||||||||||||||||||||
Hinterlegt am: | 06 Nov 2023 11:40 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:56 |
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