Assessment of mining extent and expansion in Myanmar based on freely-available satellite imagery

Remote Sensing

Volumn 8, Issue 11, 2016, Pages

  Connette, Katherine J LaJeunesse ^a,b   Connette, Grant ^a   Bernd, Asja ^b,c   Phyo, Paing ^b,d   Aung, Kyaw Htet ^b,d   Tun, Ye Lin ^b,d   Thein, Zaw Min ^b   Horning, Ned ^e   Leimgruber, Peter ^a   Songer, Melissa ^a  

^a SMITHSONIAN CONSERVATION BIOLOGY INSTITUTE   (United States)

^b Kamaryut Township   (Myanmar)

^c UNIVERSITY OF BAYREUTH   (Germany)

^d UNIVERSITY OF BERN   (Switzerland)

^e DIVISION OF INVERTEBRATE ZOOLOGY   (United States)

Author keywords

Change detection; Google earth; Landsat; Mining; Myanmar

Indexed keywords

LAND USE; MINING; OPEN SOURCE SOFTWARE; OPEN SYSTEMS; REMOTE SENSING; SOLAR RADIATION;

BARE GROUNDS; CHANGE DETECTION; FINE RESOLUTION; GOOGLE EARTHS; LANDSAT; LANDSAT IMAGES; MYANMARS; SATELLITE DATA;

SATELLITE IMAGERY;

EID: 84995478977     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs8110912     Document Type: Article

References (48)

1. Win, S.; Myint, M.M. Mineral potential of Myanmar. Resour. Geol. 1998, 48, 209-218.
2. Gardiner, N.J.; Robb, L.J.; Searle, M.P. The metallogenic provinces of Myanmar. Appl. Earth Sci. 2014, 123, 25-38.
3. Htun, K. Sustainable mining in Myanmar. Appl. Environ. Res. 2014, 36, 25-35.
4. Linn, S.N. Myanmar's Mining Investment and Its Discontents; East Asia Forum: Canbarra, Australia, 2015.
5. Oxford Business Group. Myanmar Mining to Welcome New Wave of FDI. Economic News, 26 February 2016. Available online: http://www.oxfordbusinessgroup.com/news/myanmar-mining-welcome-new-wave-fdi (accessed on 11 April 2016).
6. Hughes, C.; Toime, M. Myanmar Mining-An Update on Recent Developments. Berwin, Leighton, and Paisner, LLP. Available online: https://www.blplaw.com/expert-legal-insights/articles/myanmar-miningupdate-recent-developments (accessed on 11 April 2016).
7. Osawa, T.; Hatsukawa, Y. Artisanal and small-scale gold mining in Myanmar. Int. J. Hum. Cult. Stud. 2015, 2015, 221-230.
8. Kristensen, A.K.B.; Thomsen, J.F.; Mikkelsen, S. A review of mercury exposure among artisanal small-scale gold miners in developing countries. Int. Arch. Occup. Environ. Health 2014, 87, 579-590.
9. Lynn, T.A.; Oye, M. Natural Resources and Subnational Governments in Myanmar: Key Considerations for Wealth Sharing; Subnational Governance in Myanmar Discussion Paper Series; The Asia Foundation: San Francisco, CA, USA, 2014.
10. Woods, K. Commercial Agriculture Expansion in Myanmar: Links to deforestation, Conversion Timber, and Land Conflicts; Forest Trends: Washington, DC, USA, 2015.
11. Sabins, F.F. Remote sensing for mineral exploration. Ore Geol. Rev. 1999, 14, 157-183.
12. Gabr, S.; Ghulam, A.; Kusky, T. Detecting areas of high-potential gold mineralization using ASTER data. Ore Geol. Rev. 2010, 38, 59-69.
13. Kooistra, L.; Salas, E.A.L.; Clevers, J.;Wehrens, R.; Leuven, R.; Nienhuis, P.H.; Buydens, L.M.C. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains. Environ. Pollut. 2004, 127, 281-290.
14. Choe, E.; van der Meer, F.; van Ruitenbeek, F.; van der Werff, H.; de Smeth, B.; Kim, K.-W. Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain. Remote Sens. Environ. 2008, 112, 3222-3233.
15. Townsend, P.A.; Helmers, D.P.; Kingdon, C.C.; McNeil, B.E.; de Beurs, K.M.; Eshleman, K.N. Changes in the extent of surface mining and reclamation in the Central Appalachians detected using a 1976-2006 Landsat time series. Remote Sens. Environ. 2009, 113, 62-72.
16. Petropoulos, G.P.; Partsinevelos, P.; Mitraka, Z. Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery. Geocarto Int. 2013, 28, 323-342.
17. Prakash, A.; Gupta, R.P. Land-use mapping and change detection in a coal mining area-a case study in the Jharia coalfield, India. Int. J. Remote Sens. 1998, 19, 391-410.
18. Latifovic, R.; Fytas, K.; Chen, J.; Paraszczak, J. Assessing land cover change resulting from large surface mining development. Int. J. Appl. Earth Obs. Geoinf. 2005, 7, 29-48.
19. Schimmer, R. A remote sensing and GIS method for detecting land surface areas covered by copper mill tailings. In Proceedings of the Pecora 17-The Future of Land Imaging. Going Operational, Denver, CO, USA, 18-20 November 2008.
20. Demirel, N.; Emil, M.K.; Duzgun, H.S. Surface coal mine area monitoring using multi-temporal high-resolution satellite imagery. Int. J. Coal Geol. 2011, 86, 3-11.
21. Maxwell, A.E.;Warner, T.A.; Strager, M.P.; Pal, M. Combining RapidEye satellite imagery and LiDAR for mapping of mining and mine reclamation. Photogramm. Eng. Remote Sens. 2014, 80, 179-189.
22. Asner, G.P.; Llactayo, W.; Tupayachi, R.; Luna, E.R. Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring. Proc. Natl. Acad. Sci. USA 2013, 110, 18454-18459.
23. Akiwumi, F.A.; Butler, D.R. Mining and environmental change in Sierra Leone, West Africa: A remote sensing and hydrogeomorphological study. Environ. Monit. Assess. 2007, 142, 309-318.
24. Fernández-Manso, A.; Quintano, C.; Roberts, D. Evaluation of potential of multiple endmember spectral mixture analysis (MESMA) for surface coal mining affected area mapping in different world forest ecosystems. Remote Sens. Environ. 2012, 127, 181-193.
25. Areendran, G.; Rao, P.; Raj, K.; Mazumdar, S.; Puri, K. Land use/land cover change dynamics analysis in mining areas of Singrauli district in Madhya Pradesh, India. Trop. Ecol. 2013, 54, 239-250.
26. Li, J.; Zipper, C.E.; Donovan, P.F.; Wynne, R.H.; Oliphant, A.J. Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery. Environ. Monit. Assess. 2015, 187, 1-17.
27. Koruyan, K.; Deliormanli, A.H.; Karaca, Z.; Momayez, M.; Lu, H.; Yalçin, E. Remote sensing in management of mining land and proximate habitat. J. South. Afr. Inst. Min. Metall. 2012, 112, 667-672.
28. Sen, S.; Zipper, C.;Wynne, R.; Donovan, P. Identifying revegetated mines as disturbance/recovery trajectories using an Interannual Landsat Chronosequence. Photogramm. Eng. Remote Sens. 2012, 78, 223-235.
29. Bhagwat, T.; Hess, A.; Horning, N.; Khaing, T.; Thein, Z.M.; Aung, K.M.; Aung, K.H.; Phyo, P.; Tun, Y.L.; Oo, A.H.; et al. Losing a jewel-Rapid declines in Myanmar's intact forests from 2002-2014. PLoS ONE 2016. in review.
30. Smith, R.B. The Heat Budget of the Earth's Surface Deduced from Space; Yale University Center for Earth Observation: New Haven, CT, USA, 2010.
31. Liang, S. Narrowband to broadband conversions of land surface albedo I: Algorithms. Remote Sens. Environ. 2001, 76, 213-238.
32. U.S. Geological Survey. Earth Resources Observation and Science (EROS) Center. Landsat Section. Available online: https://www.earthexplorer.usgs.gov (accessed on 21 October 2016).
33. Zhu, Z.; Woodcock, C.E. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sens. Environ. 2012, 118, 83-94.
34. Zhu, Z.; Wang, S.; Woodcock, C.E. Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sens. Environ. 2015, 159, 269-277.
35. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2016.
36. Connette, G.; Oswald, P.; Songer, M.; Leimgruber, P. Mapping ecological forest types and degradation extent using multi-spectral Landsat imagery. Remote Sens. 2016, 8, 882.
37. QGIS Development Team. QGIS Geographic Information System. Available online: http://www.qgis.org/en/site/(accessed on 1 December 2015).
38. Lillesand, T.; Kiefer, R.W.; Chipman, J. Remote Sensing and Image Interpretation; John Wiley & Sons: Hoboken, NJ, USA, 2014.
39. Millard, K.; Richardson, M. On the importance of training data sample selection in random forest image classification: A case study in peatland ecosystem mapping. Remote Sens. 2015, 7, 8489-8515.
40. Google Earth Pro v7.1.7.2602; Google: Myanmar. Available online: https://www.google.com/earth/(accessed on 21 October 2016).
41. Bing Maps; Microsoft: Myanmar. Available online: https://www.bing.com/maps (accessed on 21 October 2016).
42. Paredes-Hernández, C.U.; Salinas-Castillo, W.E.; Guevara-Cortina, F.; Xicoténcatl, M. Horizontal positional accuracy of Google Earth's imagery over rural areas: A study case in Tamaulipas, Mexico. Boletim de Ciências Geodésicas 2013, 19, 588-601.
43. Dudka, S.; Adriano, D.C. Environmental impacts of metal ore mining and processing: A review. J. Environ. Qual. 1997, 26, 590-602.
44. Malaviya, S.; Munsi, M.; Oinam, G.; Joshi, P.K. Landscape approach for quantifying land use land cover change (1972-2006) and habitat diversity in a mining area in Central India (Bokaro, Jharkhand). Environ. Monit. Assess. 2010, 170, 215-229.
45. Soulard, C.E.; Acevedo, W.; Stehman, S.V.; Parker, O.P. Mapping extent and change in surface mines within the United States for 2001 to 2006. Land Degrad. Dev. 2016, 27, 248-257.
46. Gardiner, N.J.; Sykes, J.P.; Trench, A.; Robb, L.J. Tin mining in Myanmar: Production and potential. Resour. Policy 2015, 46, 219-233.
47. Extractive Industries Transparency Initiative. Myanmar: EITI. Available online: https://eiti.org/Myanmar (accessed on 18 July 2016).
48. MIMU Geonode. Available online: http://geonode.themimu.info (accessed on 31 October 2016).