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Remote Sens. 2014, 6(7), 6636-6661; doi:10.3390/rs6076636

Geographic Object-Based Image Analysis Using Optical Satellite Imagery and GIS Data for the Detection of Mining Sites in the Democratic Republic of the Congo

1
Department of Geoinformatics—Z_GIS, University of Salzburg, Schillerstraße 30, A-5020 Salzburg, Austria
2
Helmholtz Association Head Office, Research Section, Anna-Louisa-Karsch-Straße 2, D-10178 Berlin, Germany
3
German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Münchener Straße 20, D-82234 Weßling, Germany
*
Author to whom correspondence should be addressed.
Received: 28 March 2014 / Revised: 24 June 2014 / Accepted: 27 June 2014 / Published: 21 July 2014
(This article belongs to the Special Issue Advances in Geographic Object-Based Image Analysis (GEOBIA))
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Abstract

Earth observation is an important source of information in areas that are too remote, too insecure or even both for traditional field surveys. A multi-scale analysis approach is developed to monitor the Kivu provinces in the Democratic Republic of the Congo (DRC) to identify hot spots of mining activities and provide reliable information about the situation in and around two selected mining sites, Mumba-Bibatama and Bisie. The first is the test case for the approach and the detection of unknown mining sites, whereas the second acts as reference case since it is the largest and most well-known location for cassiterite extraction in eastern Congo. Thus it plays a key-role within the context of the conflicts in this region. Detailed multi-temporal analyses of very high-resolution (VHR) satellite data demonstrates the capabilities of Geographic Object-Based Image Analysis (GEOBIA) techniques for providing information about the situation during a mining ban announced by the Congolese President between September 2010 and March 2011. Although the opening of new surface patches can serve as an indication for activities in the area, the pure change between the two satellite images does not in itself produce confirming evidence. However, in combination with observations on the ground, it becomes evident that mining activities continued in Bisie during the ban, even though the production volume went down considerably. View Full-Text
Keywords: geographic object-based image analysis (GEOBIA); feature extraction; change detection; monitoring; multi-scale; natural resources; artisanal and small-scale mining; Democratic Republic of the Congo; conflict research geographic object-based image analysis (GEOBIA); feature extraction; change detection; monitoring; multi-scale; natural resources; artisanal and small-scale mining; Democratic Republic of the Congo; conflict research
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Luethje, F.; Kranz, O.; Schoepfer, E. Geographic Object-Based Image Analysis Using Optical Satellite Imagery and GIS Data for the Detection of Mining Sites in the Democratic Republic of the Congo. Remote Sens. 2014, 6, 6636-6661.

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