2.5D change detection from satellite imagery to monitor small-scale mining activities in the Democratic Republic of the Congo |
| |
Affiliation: | 1. Department of Geoinformatics – Z_GIS, University of Salzburg, Salzburg, Austria;2. Research Section, Helmholtz Association of German Research Centres, Head Office, Berlin, Germany;3. German Aerospace Center(DLR), German Remote Sensing Data Center (DFD), 82234 Oberpfaffenhofen, Germany;1. Biomedical Image Technologies (BIT), ETSI Telecomunicación, Universidad Politécnica de Madrid, Spain;2. Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Switzerland;3. Department of Radiology, Centre d’Imaginerie Biomédicale, University Hospital Center and University of Lausanne, Switzerland;4. Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain;1. National Commission for the Knowledge and Use of Biodiversity (CONABIO), Av. Liga Periférico − Insurgentes Sur No 4903, Col. Parques del Pedregal, Del. Tlalpan, 14010, Ciudad de Mexico, Mexico;2. Stockholm Environment Institute (SEI), 400 F Street, Davis, CA, 95616, USA |
| |
Abstract: | Mining natural resources serve fundamental societal needs or commercial interests, but it may well turn into a driver of violence and regional instability. In this study, very high resolution (VHR) optical stereo satellite data are analysed to monitor processes and changes in one of the largest artisanal and small-scale mining sites in the Democratic Republic of the Congo, which is among the world’s wealthiest countries in exploitable minerals To identify the subtle structural changes, the applied methodological framework employs object-based change detection (OBCD) based on optical VHR data and generated digital surface models (DSM). Results prove the DSM-based change detection approach enhances the assessment gained from sole 2D analyses by providing valuable information about changes in surface structure or volume. Land cover changes as analysed by OBCD reveal an increase in bare soil area by a rate of 47% between April 2010 and September 2010, followed by a significant decrease of 47.5% until March 2015. Beyond that, DSM differencing enabled the characterisation of small-scale features such as pits and excavations. The presented Earth observation (EO)-based monitoring of mineral exploitation aims at a better understanding of the relations between resource extraction and conflict, and thus providing relevant information for potential mitigation strategies and peace building. |
| |
Keywords: | Digital surface model Semi-global matching Object-based change detection Small-scale mining Natural resources |
本文献已被 ScienceDirect 等数据库收录! |
|