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Remote Sens. 2016, 8(11), 912; doi:10.3390/rs8110912

Assessment of Mining Extent and Expansion in Myanmar Based on Freely-Available Satellite Imagery

1
Smithsonian Conservation Biology Institute, Conservation Ecology Center, 1500 Remount Rd., Front Royal, VA 22630, USA
2
EcoDev/ALARM, Kamaryut Township, Yangon 11041, Myanmar
3
Department of Biogeography, University of Bayreuth, Universitaetsstrasse 30, Bayreuth 95447, Germany
4
One Map Myanmar, Center for Development and the Environment, University of Bern, 18D Sein Lei Yeik Thar Street, Yankin Township, Yangon 11081, Myanmar
5
American Museum of Natural History, New York, NY 10024, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Krishna Prasad Vadrevu, Rama Nemani, Chris Justice, Garik Gutman, Soe Myint, Richard Gloaguen and Prasad S. Thenkabail
Received: 30 July 2016 / Revised: 22 October 2016 / Accepted: 28 October 2016 / Published: 3 November 2016
View Full-Text   |   Download PDF [1938 KB, uploaded 3 November 2016]   |  

Abstract

Using freely-available data and open-source software, we developed a remote sensing methodology to identify mining areas and assess recent mining expansion in Myanmar. Our country-wide analysis used Landsat 8 satellite data from a select number of mining areas to create a raster layer of potential mining areas. We used this layer to guide a systematic scan of freely-available fine-resolution imagery, such as Google Earth, in order to digitize likely mining areas. During this process, each mining area was assigned a ranking indicating our certainty in correct identification of the mining land use. Finally, we identified areas of recent mining expansion based on the change in albedo, or brightness, between Landsat images from 2002 and 2015. We identified 90,041 ha of potential mining areas in Myanmar, of which 58% (52,312 ha) was assigned high certainty, 29% (26,251 ha) medium certainty, and 13% (11,478 ha) low certainty. Of the high-certainty mining areas, 62% of bare ground was disturbed (had a large increase in albedo) since 2002. This four-month project provides the first publicly-available database of mining areas in Myanmar, and it demonstrates an approach for large-scale assessment of mining extent and expansion based on freely-available data. View Full-Text
Keywords: mining; change detection; Myanmar; Landsat; Google Earth mining; change detection; Myanmar; Landsat; Google Earth
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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

LaJeunesse Connette, K.J.; Connette, G.; Bernd, A.; Phyo, P.; Aung, K.H.; Tun, Y.L.; Thein, Z.M.; Horning, N.; Leimgruber, P.; Songer, M. Assessment of Mining Extent and Expansion in Myanmar Based on Freely-Available Satellite Imagery. Remote Sens. 2016, 8, 912.

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