[en] Informal small-scale mining is spread in many countries and provides livelihood to numerous families in rural areas yet often with devastating social and environmental impacts. The alluvial gold mining process in Colombia, also known as placer mining, involves excavations using heavy machinery and creates large footprints of bare soil and mining ponds. The very dynamic nature of this extractive activity and its spread in rural and remote areas make its mapping and monitoring very challenging. The use of freely available satellite data of the Copernicus programme provides great new possibilities to study these activities and provides stakeholders integrated data to better understand the spatial and temporal extent of the activities and mitigate affected areas. The objective of this work is to assess the potential of Sentinel-2 data to identify mining areas and to understand the dynamics in landcover change over a study area located at the border of the municipalities of El Bagre and Zaragoza in Bajo Cauca, Colombia. The study utilizes a classification approach followed by post-processing using field knowledge on a set of images from 2016 to 2019. Sequential pattern mining of classified images shows the likelihood of certain annual and seasonal changes in mining-impacted landcover and in the natural vegetation. The results show a slight reduction in the detected mining areas from 2016 to 2019. On the other hand, there are more mining activities in the dry season than in the wet season. Excavated areas of bare soil have a 50% chance to remain in excavation over the considered period or they transition to non-vegetated areas or mining ponds. Vegetation loss due to the extractive activities corresponds to about 35% while recovered vegetated areas are 7% of the total excavated areas in June 2019. An analysis of abandoned sites using NDVI shows that it takes a much longer period than the one considered in this paper for potential natural recovery of vegetation. Finally, the work was disseminated among stakeholders and the public on MapX (https://mapx.org), an online open platform for mapping and visualizing geospatial data on natural resources. It is a pilot study the will be the basis of the analysis of more regions in the department of Antioquia.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Ibrahim, Elsy ; Université de Liège - ULiège > Département ArGEnCo > Géoressources minérales & Imagerie géologique
Lema, Luisa
Barnabé, Pierre ; Université de Liège - ULiège > Département ArGEnCo > Géoressources minérales & Imagerie géologique
Lacroix, Pierre
Pirard, Eric ; Université de Liège - ULiège > Département ArGEnCo > Géoressources minérales & Imagerie géologique
Language :
English
Title :
Small-scale surface mining of gold placers: Detection, mapping, and temporal analysis through the use of free satellite imagery
Publication date :
July 2020
Journal title :
International Journal of Applied Earth Observation and Geoinformation
ISSN :
1569-8432
eISSN :
1872-826X
Publisher :
International Institute for Aerial Survey and Earth Sciences, Netherlands
Volume :
93
Peer reviewed :
Peer Reviewed verified by ORBi
Name of the research project :
CopX
Funders :
EIT - European Union. European Institute of Innovation and Technology
Andres, V., Espana, A., Rodriguez, A.R., Bardos, P., Naidu, R., Contaminated land in Colombia: a critical review of current status and future approach for the management of contaminated sites. Sci. Total Environ. 618 (2018), 199–209, 10.1016/j.scitotenv.2017.10.245.
Atibu, E.K., Lacroix, P., Sivalingam, P., Ray, N., Giuliani, G., Mulaji, C.K., Otamonga, J.p., Mpiana, P.T., Slaveykova, V.I., Pote, J., High contamination in the areas surrounding abandoned mines and mining activities: an impact assessment of the Dilala, Luilu and Mpingiri rivers, democratic Republic of the Congo. Chemosphere 191 (2018), 1008–1020, 10.1016/j.chemosphere.2017.10.052.
Bernal, M., Mineria de oro en Colombia: Auge y Problematica. 2016 (Online) https://revistadelogistica.com/actualidad/mineria-de-oro-en-colombia-auge-y-problematica/.
Betancur-Corredor, B., Loaiza-Usuga, J.C., Denich, M., Borgemeister, C., Gold mining as a potential driver of development in Colombia: challenges and opportunities. J. Clean. Prod. 199 (2018), 538–553, 10.1016/j.jclepro.2018.07.142.
Boyd, D.S., Jackson, B., Wardlaw, J., Foody, G.M., Marsh, S., Bales, K., Slavery from space: demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8. ISPRS J. Photogramm. Remote Sens. 142 (2018), 380–388, 10.1016/j.isprsjprs.2018.02.012.
Bustamante, N., Danoucaras, N., McIntyre, N., Diaz-Martinez, J.C., Restrepo-Baena, O.J., Review of improving the water management for the informal gold mining in Colombia. Revista Facultad de Ingeniería Universidad de Antioquia 79 (2016), 174–184, 10.17533/udea.redin.n79a16.
Carstens, J., European Policy Brief – Strategic Dialogue on Sustainable Raw Materials for Europe (STRADE) No. 09/2017: The Artisanal and Small-Scale Mining (ASM) Sector and its Importance for EU Cooperation with Resource-Rich Developing and Emerging countries. 2017 (Tech. Rep.) www.STRADEproject.eu.
Chen, V.Y.c., Lin, J.C., Tzeng, l.G.H., Assessment and improvement of wetlands environmental protection plans for achieving sustainable development. Environ. Res. 169:33 (2019), 280–296, 10.1016/j.envres.2018.10.015.
Cordy, P., Veiga, M.M., Salih, I., Al-saadi, S., Console, S., Garcia, O., Alberto, L., Velásquez-lópez, P.C., Roeser, M., Science of the total environment mercury contamination from artisanal gold mining in Antioquia, Colombia: the world's highest per capita mercury pollution. Sci. Total Environ. 410–411 (2011), 154–160, 10.1016/j.scitotenv.2011.09.006.
Csillik, O., Asner, G.P., Aboveground carbon emissions from gold mining in the peruvian amazon. Environ. Res. Lett., 15(1), 2020, 014006, 10.1088/1748-9326/ab639c.
Dane, I.I., Reporte no. 5 de Áreas afectadas por inundaciones 2010–2011. techreport., 2011 (accessed February 2019) https://www.dane.gov.co/files/noticias/Reporte_cinco.pdf.
García, O., Veiga, M., Cordy, P., Suescún, O., Martin, J., Roeser, M., Artisanal gold mining in Antioquia, Colombia: a successful case of mercury reduction. J. Clean. Prod. 90 (2015), 244–252, 10.1016/j.jclepro.2014.11.032.
Hausermann, H., Ferring, D., Atosona, B., Mentz, G., Amankwah, R., Chang, A., Hartfield, K., Effah, E., Asuamah, G.Y., Mansell, C., Sastri, N., Land-grabbing, land-use transformation and social differentiation: deconstructing “small-scale” in Ghana's recent gold rush. World Dev. 108 (2018), 103–114, 10.1016/j.worlddev.2018.03.014.
Huynh, B., Trinh, C., Huynh, H., Van, T., Vo, t.B., Snasel, V., An efficient approach for mining sequential patterns using multiple threads on very large databases. Eng. Appl. Artif. Intell. 74:2018 (2018), 242–251, 10.1016/j.engappai.2018.06.009.
Ibrahim, E., Kim, W., Crawford, M., Monbaliu, J., A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions. Ocean Dyn. 67:2 (2017), 299–316, 10.1007/s10236-016-1024-1.
IDEAM, Instituto de hidrología, Meteorología y estudios ambientales: Antioquia. 2019, 9 (Online, accessed February) http://atlas.ideam.gov.co/basefiles/antioquia_texto.pdf.
Isidro, C.M., McIntyre, N., Lechner, A.M., Callow, I., Applicability of earth observation for identifying small-scale mining footprints in a wet tropical region. Remote Sens., 9, 2017, 945, 10.3390/rs9090945.
Kranjcic, N., Medak, D., Zupan, R., Rezo, M., Support vector machine accuracy assessment for extracting green urban areas in towns. Remote Sens. 11:655 (2019), 1–13, 10.3390/rs11060655.
Lacroix, P., Moser, F., Benvenuti, A., Piller, T., Jensen, D., Petersen, I., Planque, M., Ray, N., Mapx: an open geospatial platform to manage, analyze and visualize data on natural resources and the environment. SoftwareX 9 (2019), 77–84, 10.1016/j.softx.2019.01.002 http://www.sciencedirect.com/science/article/pii/S2352711018300177.
Lara-Rodríguez, J.S., All that glitters is not gold or platinum: institutions and the use of mercury in mining in Chocó Colombia. Extr. Ind. Soc. 5:3 (2018), 308–318, 10.1016/j.exis.2018.03.011.
Liu, D., Xia, F., Assessing object-based classification: advantages and limitations. Remote Sens. Lett. 1:4 (2010), 187–194, 10.1080/01431161003743173.
Louis, J., Debaecker, V., Pflug, B., Main-Knorn, M., Bieniarz, J., Mueller-Wilm, U., Cadau, E., Gascon, F., Sentinel-2 SEN2COR: L2A Processor for Users. 2016, European Space Agency, (Special Publication) ESA SP SP-740(May), 9–13.
Martinez, Z.Q., Evaluación de las condiciones fisicoquímicas y la composición de algas fitoplanctonicas en lagunas derivadas de la actividad minera mecanizada en diferentes periodos de abandono, en el municipio de Cértegui, Chocó. Master thesis. 2018, Universidad De Manizales Centro De Investigaciones en Medio Ambiente Y Desarrollo “CIMAD”.
McInerney, D., Kempeneers, P., Marron, M., Mcroberts, R.E., Analysis of broadleaf encroachment in coniferous forest plantations using multi-temporal satellite imagery. Int. J. Appl. Earth Obs. Geoinf. 78:February (2019), 130–137, 10.1016/j.jag.2018.12.005.
Ministerio de Minas y Energía, C. Decreto 1666, Bogotá. 2016 (accessed January 2019) (Online) https://www.minminas.gov.co/documents/10180/23517/37238-Decreto-1666-21Oct2016.pdf/17f4f90c-4481-47cd-a084-c7fa0319f9cf.
Mountrakis, G., Im, J., Ogole, C., Support vector machines in remote sensing: a review. ISPRS J. Photogramm. Remote Sens. 66:3 (2011), 247–259, 10.1016/j.isprsjprs.2010.11.001.
Myint, S.W., Gober, P., Brazel, A., Grossman-Clarke, S., Weng, Q., Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sens. Environ. 115:5 (2011), 1145–1161, 10.1016/j.rse.2010.12.017 http://www.sciencedirect.com/science/article/pii/S0034425711000034.
Nations, U., Sustainable Development Goals. 2019 https://sustainabledevelopment.un.org/sdgs.
Obodai, J., Amaning, K., Nii, S., Lumor, M., Remote sensing applications: society and environment land use/land cover dynamics using landsat data in a gold mining basin: the Ankobra, Ghana. Remote Sens. Appl.: Soc. Environ. 13:October 2018 (2018), 247–256, 10.1016/j.rsase.2018.10.007.
Pal, M., Mather, P.M., Support vector machines for classification in remote sensing. Int. J. Remote Sens. 26:5 (2005), 1007–1011, 10.1080/01431160512331314083.
Parthasarathy, S., Zaki, M.J., Li, W., Memory placement techniques for parallel association mining. KDD-98 Proceedings, 1998.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E., Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12 (2011), 2825–2830.
Power, T., Digging to development? A Historical Look at Mining and Economic Development. 2002, University of Montana, Oxfam (Tech. Rep.) http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Digging+to+Development+?#1.
Rettberg, A., Ortiz-Riomalo, J.F., Golden opportunity, or a new twist on the resource-conflict relationship: links between the drug trade and illegal gold mining in Colombia. World Dev. 84 (2016), 82–96, 10.1016/j.worlddev.2016.03.020.
Smith, N.M., Ali, S., Bofinger, C., Collins, N., Human health and safety in artisanal and small-scale mining: an integrated approach to risk mitigation. J. Clean. Prod. 129 (2016), 43–52, 10.1016/j.jclepro.2016.04.124.
Smola, A.J., Olkopf, B.S.C.H., A tutorial on support vector regression. Stat. Comput. 14 (2004), 199–222.
Snapir, B., Simms, D., Waine, T., Mapping the expansion of galamsey gold mines in the cocoa growing area of Ghana using optical remote sensing. Int. J. Appl. Earth Obs. Geoinf. 58 (2017), 225–233, 10.1016/j.jag.2017.02.009 http://linkinghub.elsevier.com/retrieve/pii/S0303243417300351.
Telmer, K., Stapper, D., Evaluating and Monitoring Small Scale Gold Mining and Mercury Use: Building a Knowledge-base with Satellite Imagery and Field Work. 2007 UNIDO PROJECT EG/GLO/01/G34 (Tech. Rep.).
Teschner, B., Smith, N.M., Borrillo-hutter, T., Quaghe, Z., Wong, T.E., How efficient are they really? a simple testing method of small-scale gold miners’ gravity separation systems. Miner. Eng. 105 (2017), 44–51, 10.1016/j.mineng.2017.01.005.
UNITAR, Satellite Mapping of Artisanal and Small Scale Gold Mining in Central Kalimantan, Indonesia UNITAR's Operational Satellite Applications Programme., 2016 (Tech. Rep.) https://wedocs.unep.org/bitstream/handle/20.500.11822/11526/UNOSAT_Central_Kalimantan_Report_Feb2016o.pdf?sequence=1&%3BisAllowed=.
UNODC, Alluvial Gold Exploitation: Evidences from Remote Sensing 2016. 2018, United Nations office of Drugs and Crime (Tech. Rep.) http://www.biesimci.org/Documentos/Documentos.html.
Vargas, L., Diagnoostico De La Calidad Ecoloogica a Travees De Algas Perifiiticas en Escenarios Hidricos Afectados Por Mineria a Cielo Abierto Con Diferente Temporalidad, Jigualito, Condoto, Choco. Master's Thesis. 2012, University of Antioquia.
Wu, X., Zhang, X., An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images. Comput. Geosci. 124:January 2018 (2019), 128–139, 10.1016/j.cageo.2019.01.005.
Yang, Y., Erskine, P.D., Lechner, A.M., Mulligan, D., Zhang, S., Wang, Z., Detecting the dynamics of vegetation disturbance and recovery in surface mining area via Landsat imagery and LandTrendr algorithm. J. Clean. Prod. 178 (2018), 353–362, 10.1016/j.jclepro.2018.01.050.
Zaki, M.J., SPADE: an efficient algorithm for mining frequent sequences. Mach. Learn. 42 (2001), 31–60.
