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Remote Sens. 2014, 6(10), 9277-9297; doi:10.3390/rs6109277

Earth Observation-Based Dwelling Detection Approaches in a Highly Complex Refugee Camp Environment — A Comparative Study

1
German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), D-82234 Oberpfaffenhofen, Germany
2
Department of Geoinformatics—Z_GIS, University of Salzburg, Salzburg 5020, Austria
3
Metria, Stockholm 10451, Sweden
*
Author to whom correspondence should be addressed.
Received: 31 March 2014 / Revised: 27 August 2014 / Accepted: 14 September 2014 / Published: 29 September 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
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Abstract

For effective management of refugee camps or camps for internally displaced persons (IDPs) relief organizations need up-to-date information on the camp situation. In cases where detailed field assessments are not available, Earth observation (EO) data can provide important information to get a better overview about the general situation on the ground. In this study, different approaches for dwelling detection were tested using the example of a highly complex camp site in Somalia. On the basis of GeoEye-1 imagery, semi-automatic object-based and manual image analysis approaches were applied, compared and evaluated regarding their analysis results (absolute numbers, population estimation, spatial pattern), statistical correlations and production time. Although even the results of the visual image interpretation vary considerably between the interpreters, there is a similar pattern resulting from all methods, which shows same tendencies for dense and sparse populated areas. The statistical analyses revealed that all approaches have problems in the more complex areas, whereas there is a higher variance in manual interpretations with increasing complexity. The application of advanced rule sets in an object-based environment allowed a more consistent feature extraction in the area under investigation that can be obtained at a fraction of the time compared to visual image interpretation if large areas have to be observed. View Full-Text
Keywords: feature extraction; object-based image analysis (OBIA); dwelling detection; population estimation; refugee camps; VHR data feature extraction; object-based image analysis (OBIA); dwelling detection; population estimation; refugee camps; VHR data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Spröhnle, K.; Tiede, D.; Schoepfer, E.; Füreder, P.; Svanberg, A.; Rost, T. Earth Observation-Based Dwelling Detection Approaches in a Highly Complex Refugee Camp Environment — A Comparative Study. Remote Sens. 2014, 6, 9277-9297.

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