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

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

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

Abstract

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.

Item URL in elib:https://elib.dlr.de/115611/
Document Type:Article
Title:Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Aravena Pelizari, Patrickpatrick.aravenapelizari (at) dlr.deUNSPECIFIED
Spröhnle, Kristinkristin.sproehnle (at) dlr.deUNSPECIFIED
Geiß, Christianchristian.geiss (at) dlr.deUNSPECIFIED
Schoepfer, Elisabethelisabeth.schoepfer (at) dlr.deUNSPECIFIED
Plank, Simonsimon.plank (at) dlr.deUNSPECIFIED
Taubenböck, Hanneshannes.taubenboeck (at) dlr.deUNSPECIFIED
Date:2018
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:209
DOI :10.1016/j.rse.2018.02.025
Page Range:pp. 793-807
Publisher:Elsevier
ISSN:0034-4257
Status:Published
Keywords:Very high spatial resolution imagery, data Fusion, spectral-spatial features, feature selection, classification, built-up area, refugee camp mapping
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience, R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Deposited By: Aravena Pelizari, Patrick
Deposited On:23 Nov 2017 10:29
Last Modified:23 Feb 2019 00:22

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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) [Currently Displayed]

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