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Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements

Aravena Pelizari, Patrick und Spröhnle, Kristin und Geiß, Christian und Schoepfer, Elisabeth und Plank, Simon und Taubenböck, Hannes (2018) Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements. Remote Sensing of Environment, 209, Seiten 793-807. Elsevier. doi: 10.1016/j.rse.2018.02.025. ISSN 0034-4257.

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Offizielle URL: https://www.sciencedirect.com/science/article/pii/S0034425718300312

Kurzfassung

Detailed and up-to-date knowledge on the situation in temporary settlements of forced migrants plays an important role for effective humanitarian assistance. These settlements emerge as planned or spontaneous camps or camp-like structures, characterized by a small-scale physical morphology and high dynamics. Information on the built-up area (BUA; i.e. areas occupied by buildings) in these settlements provides important evidence on the local situation. The objective of this work is to present a generic procedure for the detailed extraction of BUA in complex temporary settlements from very high spatial resolution satellite data collected by different sensor types. The proposed approach is embedded in the methodological framework of object-based image analysis and is compound of i) the computation of an exhaustive set of spectral-spatial features aggregated on multiple hierarchic segmentation scales, ii) filter based feature subset selection and iii) supervised classification using a Random Forest classifier. Experimental results are obtained based on Pléiades multispectral optical and TerraSAR-X Staring Spotlight Synthetic Aperture Radar satellite imagery for six distinct but representative test areas within the refugee camp Al Zaatari in Jordan. The experiments include a detailed assessment of classification accuracy for varying configurations of considered feature types and training data set sizes as well as an analysis of the feature selection (FS) outcomes. We observe that the classification accuracy can be improved by the use of multiple segmentation levels as well as the integration of multi-sensor information and different feature types. In addition, the results show the potential of the applied FS approach for the identification of most relevant features. Accuracy values beyond 80% in terms of κ statistic and True Skill Statistic based on significantly reduced feature sets compared to the input underline the potential of the proposed method.

elib-URL des Eintrags:https://elib.dlr.de/115611/
Dokumentart:Zeitschriftenbeitrag
Titel:Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Aravena Pelizari, PatrickPatrick.AravenaPelizari (at) dlr.dehttps://orcid.org/0000-0003-0984-4675NICHT SPEZIFIZIERT
Spröhnle, Kristinkristin.sproehnle (at) dlr.dehttps://orcid.org/0000-0001-6878-3767NICHT SPEZIFIZIERT
Geiß, Christianchristian.geiss (at) dlr.dehttps://orcid.org/0000-0002-7961-8553NICHT SPEZIFIZIERT
Schoepfer, Elisabethelisabeth.schoepfer (at) dlr.dehttps://orcid.org/0000-0002-6496-4744NICHT SPEZIFIZIERT
Plank, Simonsimon.plank (at) dlr.dehttps://orcid.org/0000-0002-5793-052XNICHT SPEZIFIZIERT
Taubenböck, Hanneshannes.taubenboeck (at) dlr.dehttps://orcid.org/0000-0003-4360-9126NICHT SPEZIFIZIERT
Datum:2018
Erschienen in:Remote Sensing of Environment
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:209
DOI:10.1016/j.rse.2018.02.025
Seitenbereich:Seiten 793-807
Verlag:Elsevier
ISSN:0034-4257
Status:veröffentlicht
Stichwörter:Very high spatial resolution imagery, data Fusion, spectral-spatial features, feature selection, classification, built-up area, refugee camp mapping
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 - Vorhaben hochauflösende Fernerkundungsverfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Georisiken und zivile Sicherheit
Hinterlegt von: Aravena Pelizari, Patrick
Hinterlegt am:23 Nov 2017 10:29
Letzte Änderung:03 Nov 2023 10:19

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  • Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements. (deposited 23 Nov 2017 10:29) [Gegenwärtig angezeigt]

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