Show simple item record

dc.creatorAnaya J.A.
dc.creatorGutiérrez-Vélez V.H.
dc.creatorPacheco-Pascagaza A.M.
dc.creatorPalomino-Ángel S.
dc.creatorHan N.
dc.creatorBalzter H.
dc.descriptionTropical forests are disappearing at unprecedented rates, but the drivers behind this transformation are not always clear. This limits the decision-making processes and the effectiveness of forest management policies. In this paper, we address the extent and drivers of deforestation of the Choco biodiversity hotspot, which has not received much scientific attention despite its high levels of plant diversity and endemism. The climate is characterized by persistent cloud cover which is a challenge for land cover mapping from optical satellite imagery. By using Google Earth Engine to select pixels with minimal cloud content and applying a random forest classifier to Landsat and Sentinel data, we produced a wall-to-wall land cover map, enabling a diagnosis of the status and drivers of forest loss in the region. Analyses of these new maps together with information from illicit crops and alluvial mining uncovered the pressure over intact forests. According to Global Forest Change (GFC) data, 2324 km2 were deforested in this area from 2001 to 2018, reaching a maximum in 2016 and 2017. We found that 68% of the area is covered by broadleaf forests (67,473 km2) and 15% by shrublands (14,483 km2), the latter with enormous potential to promote restoration projects. This paper provides a new insight into the conservation of this exceptional forest with a discussion of the drivers of forest loss, where illicit crops and alluvial mining were found to be responsible for 60% of forest loss. © 2020 by the authors.
dc.publisherMDPI AG
dc.sourceRemote Sensing
dc.subjectBiodiversity hotspotspa
dc.subjectGoogle earth enginespa
dc.subjectTropical humid forestsspa
dc.titleDrivers of forest loss in a megadiverse hotspot on the pacific Coast of Colombia
dc.publisher.programIngeniería Ambientalspa
dc.subject.keywordDecision makingeng
dc.subject.keywordDecision treeseng
dc.subject.keywordSatellite imageryeng
dc.subject.keywordBroadleaf foresteng
dc.subject.keywordDecision making processeng
dc.subject.keywordForest management policieseng
dc.subject.keywordLand cover mappingeng
dc.subject.keywordOptical satellite imageryeng
dc.subject.keywordRandom forest classifiereng
dc.subject.keywordRestoration projecteng
dc.subject.keywordTropical foresteng
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationAnaya, J.A., Facultad de Ingeniería, Universidad de Medellín, Medellín, 050026, Colombia
dc.affiliationGutiérrez-Vélez, V.H., Department of Geography and Urban Studies, Temple University, Philadelphia, PA 19122, United States
dc.affiliationPacheco-Pascagaza, A.M., Centre for Landscape and Climate Research (CLCR), School of Geography, Geology and the Environment, University of Leicester, Leicester, LE1 7RH, United Kingdom
dc.affiliationPalomino-Ángel, S., Facultad de Ingeniería, Universidad de Medellín, Medellín, 050026, Colombia
dc.affiliationHan, N., Faculty of Forestry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
dc.affiliationBalzter, H., Centre for Landscape and Climate Research (CLCR), School of Geography, Geology and the Environment, University of Leicester, Leicester, LE1 7RH, United Kingdom, National Centre for Earth Observation (NCEO), National Centre for Earth Observation (NCEO), University of Leicester, Leicester, LE1 7RH, United Kingdom
dc.relation.referencesDinerstein, E., Olson, D.M., Graham, D.L., Webster, A.L., Primm, S.A., Bookbinder, M.P., Ledec, G., (1995) A Conservation Assessment of the Terrestrial Ecoregions of Latin America and the Caribbean, p. 135. , The World Bank: Washington, DC, USA
dc.relation.referencesMyers, N., Mittermeier, R.A., Mittermeier, C.G., Da Fonseca, G.A.B., Kent, J., Biodiversity hotspots for conservation priorities (2000) Nature, 403, p. 853
dc.relation.referencesWatson, R.T., Dixon, J.A., Hamburg, S.P., Janetos, A.C., Moss, R.H., Protecting our planet, securing our future (1998) Linkages Among Global Environmental Issues and Human Heeds, p. 95. , UNEP
dc.relation.referencesThe World Bank: Washington, DC, USA
dc.relation.referencesMeyer, V., Saatchi, S., Ferraz, A., Xu, L., Duque, A., García, M., Chave, J., Forest degradation and biomass loss along the Chocó region of Colombia (2019) Carbon Balance Manag, 14, p. 2
dc.relation.referencesGaleano, G., Suárez, S., Balslev, H., Vascular plant species count in a wet forest in the Chocó area on the Pacific coast of Colombia (1998) Biodivers. Conserv, 7, pp. 1563-1575
dc.relation.referencesEtter, A., McAlpine, C., Pullar, D., Possingham, H., Modelling the conversion of Colombian lowland ecosystems since 1940: Drivers, patterns and rates (2006) J. Environ. Manag, 79, pp. 74-87
dc.relation.referencesProença, V., Pereira, H.M., Ecosystem Changes, Biodiversity Loss and Human Well-Being (2015) Reference Module in Earth Systems and Environmental Sciences, , Elsevier: Amsterdam, The Netherlands
dc.relation.referencesSierra, C.A., Mahecha, M., Poveda, G., Álvarez-Dávila, E., Gutierrez-Velez, V.H., Reu, B., Feilhauer, H., Benavides, A.M., Monitoring ecological change during rapid socio-economic and political transitions: Colombian ecosystems in the post-conflict era (2017) Environ. Sci. Policy, 76, pp. 40-49
dc.relation.referencesGill, M., Jongman, R.H.G., Luque, S., Mora, B., Paganini, M., Szantoi, Z., (2017) A Sourcebook of Methods and Procedures for Monitoring Essential Biodiversity Variables in Tropical Forests with Remote Sensing, , Land Cover Project Office: Edmonton, CA, USA
dc.relation.referencesÁlvarez, M.D., Environmental damage from illicit drug crops in Colombia (2007) Extreme Conflict and Tropical Forests, 5. , Jong, W.D., Donovan, D., Abe, K., Eds.
dc.relation.referencesSpringer: Dordrecht, The Netherlands
dc.relation.referencesLandholm, D.M., Pradhan, P., Kropp, J.P., Diverging forest land use dynamics induced by armed conflict across the tropics (2019) Glob. Environ. Chang, 56, pp. 86-94
dc.relation.referencesSantos, J.M., (2018) Letter to Next Colombian President, , Presidencia de la Republica: Bogota, Colombia
dc.relation.referencesArmenteras, D., Schneider, L., Dávalos, L.M., Fires in protected areas reveal unforeseen costs of Colombian peace (2019) Nature Ecol. Evol, 3, pp. 20-23
dc.relation.referencesRincón-Ruiz, A., Correa, H.L., León, D.O., Williams, S., Coca cultivation and crop eradication in Colombia: The challenges of integrating rural reality into effective anti-drug policy (2016) Int. J. Drug Policy, 33, pp. 56-65
dc.relation.referencesClerici, N., Armenteras, D., Kareiva, P., Botero, R., Ramírez-Delgado, J.P., Forero-Medina, G., Ochoa, J., Lora, C., Deforestation in Colombian protected areas increased during post-conflict periods (2020) Sci. Rep, 10, p. 4971
dc.relation.referencesArmenteras, D., Cabrera, E., Rodríguez, N., Retana, J., National and regional determinants of tropical deforestation in Colombia (2013) Reg. Environ. Change, 13, pp. 1181-1193
dc.relation.referencesFurumo, P.R., Lambin, E.F., Scaling up zero-deforestation initiatives through public-private partnerships: A look inside post-conflict Colombia (2020) Glob. Environ. Change, 62, p. 102055
dc.relation.referencesHansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Loveland, T.R., High-Resolution Global Maps of 21st-Century Forest Cover Change (2013) Science, 342, pp. 850-853
dc.relation.referencesCorlett, R., Primark, R., (2011) Tropical Rain Forests: An Ecological and Biogeographical Comparison, , Blackwell Publishing: Hoboken, NJ, USA
dc.relation.referencesPalomino-Ángel, S., Anaya-Acevedo, J.A., Botero, B.A., Evaluation of 3B42V7 and IMERG daily-precipitation products for a very high-precipitation region in northwestern South America (2019) Atmos. Res, 217, pp. 37-48
dc.relation.referencesAlongi, D.M., Mukhopadhyay, S.K., Contribution of mangroves to coastal carbon cycling in low latitude seas (2015) Agric. For. Meteorol, 213, pp. 266-272
dc.relation.referencesLema, L.F., Hermelin, D., Fontecha, M.M., Urrego, D., Climate Change Communication in Colombia (2017) Oxf. Res. Encycl. Clim. Sci, pp. 1-41
dc.relation.referencesRangel, J.O., Lowy, C.P., Aguilar, P.M., Garzón, C.A., (1997) Tipos de Vegetación en Colombia, p. 389. , Instituto de Ciencias Naturales
dc.relation.referencesUniversidad Nacional de Colombia
dc.relation.referencesIDEAM: Bogotá, Colombia
dc.relation.referencesBonilla-Mejía, L., Higuera-Mendieta, I., Protected Areas under Weak Institutions: Evidence from Colombia (2019) World Dev, 122, pp. 585-596
dc.relation.referencesChen, B., Li, X., Xiao, X., Zhao, B., Dong, J., Kou, W., Qin, Y., Sun, R., Mapping tropical forests and deciduous rubber plantations in Hainan Island, China by integrating PALSAR 25-m and multi-temporal Landsat images (2016) Int. J. Appl. Earth Obs. Geoinf, 50, pp. 117-130
dc.relation.referencesOliver, C., Quegan, S., (2004) Understanding Synthetic Aperture Radar Images, , SciTech Publishing: Boston, MA, USA
dc.relation.referencesDong, J., Xiao, X., Chen, B., Torbick, N., Jin, C., Zhang, G., Biradar, C., Mapping deciduous rubber plantations through integration of PALSAR and multi-temporal Landsat imagery (2013) Remote Sens. Environ, 134, pp. 392-402
dc.relation.referencesBreiman, L., Random Forests (2001) Mach. Learn, 45, pp. 5-32
dc.relation.referencesTeam, R.C., (2013) R: A Language and Environment for Statistical Computing, , Team RC: Vienna, Austria
dc.relation.referencesLaurin, G.V., Liesenberg, V., Chen, Q., Guerriero, L., Del Frate, F., Bartolini, A., Coomes, D., Valentini, R., Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa (2012) Int. J. Appl. Earth Obs. Geoinf, 21, pp. 7-16
dc.relation.referencesAnaya, J., Colditz, R., Valencia, G., Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series (2015) Remote Sens, 7, pp. 16274-16292
dc.relation.referencesGorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., Google Earth Engine: Planetary-scale geospatial analysis for everyone (2017) Remote Sens. Environ, 202, pp. 18-27
dc.relation.referencesAchard, F., Hansen, M.C., (2013) Global Forest Monitoring from Earth Observation, p. 316. , CRC Press
dc.relation.referencesTaylor & Francis Group: Boca Raton, FL, USA
dc.relation.referencesFlood, N., Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median) (2013) Remote Sens, 5, pp. 6481-6500
dc.relation.referencesMahdianpari, M., Salehi, B., Mohammadimanesh, F., Homayouni, S., Gill, E., The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform (2018) Remote Sens, 11, p. 43
dc.relation.referencesReiche, J., Verhoeven, R., Verbesselt, J., Hamunyela, E., Wielaard, N., Herold, M., Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts (2018) Remote Sens, 10, p. 777
dc.relation.referencesZhu, Z., Woodcock, C.E., Object-based cloud and cloud shadow detection in Landsat imagery (2012) Remote Sens. Environ, 118, pp. 83-94
dc.relation.referencesChastain, R., Housman, I., Goldstein, J., Finco, M., Tenneson, K., Empirical cross sensor comparison of Sentinel-2A and 2B MSI, Landsat-8 OLI, and Landsat-7 ETM+ top of atmosphere spectral characteristics over the conterminous United States (2019) Remote Sens. Environ, 221, pp. 274-285
dc.relation.referencesClaverie, M., Ju, J., Masek, J.G., Dungan, J.L., Vermote, E.F., Roger, J.-C., Skakun, S.V., Justice, C., The Harmonized Landsat and Sentinel-2 surface reflectance data set (2018) Remote Sens. Environ, 219, pp. 145-161
dc.relation.referencesZhang, H.K., Roy, D.P., Yan, L., Li, Z., Huang, H., Vermote, E., Skakun, S., Roger, J.-C., Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, and nadir BRDF adjusted reflectance and NDVI differences (2018) Remote Sens. Environ, 215, pp. 482-494
dc.relation.referencesPahlevan, N., Balasubramanian, S.V., Sarkar, S., Franz, B.A., Toward Long-Term Aquatic Science Products from Heritage Landsat Missions (2018) Remote Sens, 10, p. 1337
dc.relation.referencesLeyenda Nacional de Coberturas de la Tierra (2010) Metodología CORINE Land Cover Adaptada para Colombia Escala 1:100.000, p. 72. , Martínez, N.J.A., Ed.
dc.relation.referencesInstituto de Hidrología: Bogotá, Columbia
dc.relation.referencesGonzález-Martínez, M.D., Huguet, C., Pearse, J., McIntyre, N., Camacho, L.A., Assessment of potential contamination of Paramo soil and downstream water supplies in a coal-mining region of Colombia (2019) Appl. Geochem, 108, p. 104382
dc.relation.referencesLondoño, C., Cleef, A., Madriñán, S., Angiosperm flora and biogeography of the páramo region of Colombia, Northern Andes (2014) Flora Morphol. Distrib. Functi. Ecol. Plants, 209, pp. 81-87
dc.relation.referencesRivera, D., Rodríguez, C., (2011) Guía Divulgativa de Criterios para la Delimitación de Páramos de Colombia, , Alianza Ediprint Ltd.: Bogotá, Colombia
dc.relation.referencesGutiérrez-Vélez, V.H., DeFries, R., Annual multi-resolution detection of land cover conversion to oil palm in the Peruvian Amazon (2013) Remote Sens. Environ, 129, pp. 154-167
dc.relation.referencesLiaw, A., Wiener, M., Breiman and Cutler 's Random Forests for Classification and Regression (2018) R Package Vers 3.6.3, 4, pp. 6-14
dc.relation.referencesLoveland, T.R., Belward, A.S., The International Geosphere Biosphere Programme Data and Information System global land cover data set (DISCover) (1997) Acta Astronaut, 41, pp. 681-689
dc.relation.referencesRival, L., The meanings of forest governance in Esmeraldas, Ecuador (2003) Oxf. Dev. Stud, 31, pp. 479-501
dc.relation.referencesAnalysis of drug markets Opiates, cocaine, cannabis, synthetic drugs (2018) World Drug Report (WDR), p. 72. , Sales No. E.18. XI.9 UNODC Research: Vienna, Austria
dc.relation.referencesColombia Survey of territories affected by illicit crops-2016 (2017) Sistema Integrado de Monitoreo de Cultivos Ilícitos, p. 216. , United Nations Office on Drugs and Crime-Government of Colombia: Bogotá, Columbia
dc.relation.referencesCruz-Garcia, G.S., Vanegas Cubillos, M., Torres-Vitolas, C., Harvey, C.A., Shackleton, C.M., Schreckenberg, K., Willcock, S., Sachet, E., He says, she says: Ecosystem services and gender among indigenous communities in the Colombian Amazon (2019) Ecosyst. Serv, 37, p. 100921
dc.relation.referencesColombia Monitoreo de territorios afectados por cultivos ilícitos 2018 (2019) Sistema Integrado de Monitoreo de Cultivos Ilícitos, p. 115. , Oficina de las Naciones Unidas contra la Droga y el Delito-Gobierno de Colombia: Bogotá, Columbia
dc.relation.referencesColombia Coca cultivation survey 2013 (2014) Sistema Integrado de Monitoreo de Cultivos Ilícitos, p. 131. , United Nations Office on Drugs and Crime-Government of Colombia: Bogotá, Columbia
dc.relation.referencesVallejo Toro, P.P., Vásquez Bedoya, L.F., Correa, I.D., Bernal Franco, G.R., Alcántara-Carrió, J., Palacio Baena, J.A., Impact of terrestrial mining and intensive agriculture in pollution of estuarine surface sediments: Spatial distribution of trace metals in the Gulf of Urabá, Colombia (2016) Mar. Pollut. Bull, 111, pp. 311-320
dc.relation.referencesAnaya-Acevedo, J.A., Escobar-Martínez, J.F., Masson, H., Booman, G., Quiroz-Londoño, O.M., Cañón-Barriga, C., Montoya-Jaramillo, L.J., Palomino-Ángel, S., Identification of wetland areas in the context of agricultural development using Remote Sensing and GIS (2017) DYNA, 84, pp. 186-194
dc.relation.referencesMüller-Hansen, F., Heitzig, J., Donges, J.F., Cardoso, M.F., Dalla-Nora, E.L., Andrade, P., Kurths, J., Thonicke, K., Can Intensification of Cattle Ranching Reduce Deforestation in the Amazon? Insights From an Agent-based Social-Ecological Model (2019) Ecol. Econ, 159, pp. 198-211
dc.relation.referencesColombia Monitoreo de territorios afectados por cultivos ilícitos 2017 (2018) Sistema Integrado de Monitore de Cultivos Ilícitos, p. 168. , Oficina de las Naciones Unidas contra la Droga y el Delito-Gobierno de Colombia: Bogotá, Columbia
dc.relation.referencesOlofsson, P., Foody, G.M., Herold, M., Stehman, S.V., Woodcock, C.E., Wulder, M.A., Good practices for estimating area and assessing accuracy of land change (2014) Remote Sens. Environ, 148, pp. 42-57
dc.relation.referencesRodríguez-Piñeros, S., Martínez-Cortés, O., Villarraga-Flórez, L., Ruíz-Díaz, A., Timber market actors' values on forest legislation: A case study from Colombia (2018) Forest Policy Econ, 88, pp. 1-10
dc.relation.referencesColombia Monitoreo de territorios afectados por cultivos ilícitos 2015 (2016) Sistema Integrado de Monitoreo de Cultivos Ilícitos, p. 143. , Oficina de las Naciones Unidas contra la Droga y el Delito-Gobierno de Colombia: Bogotá, Columbia
dc.relation.referencesColombia Explotación de oro de aluvión. Evidencias a partir de percepción remota 2016 (2018) Sistema Integrado de Monitoreo de Cultivos Ilícitos, p. 144. , Oficina de las Naciones Unidas contra la Droga y el Delito: Bogotá, Columbia
dc.relation.references(2019) Luchan Contra la Minería Ilegal en Chocó, ,, (accessed on 20 November)
dc.relation.referencesLara-Rodríguez, J.S., All that glitters is not gold or platinum: Institutions and the use of mercury in mining in Chocó, Colombia (2018) Extr. Ind. Soc, 5, pp. 308-318
dc.relation.referencesPalacios-Torres, Y., Caballero-Gallardo, K., Olivero-Verbel, J., Mercury pollution by gold mining in a global biodiversity hotspot, the Choco biogeographic region, Colombia (2018) Chemosphere, 193, pp. 421-430
dc.relation.referencesVélez, M.A., Robalino, J., Cárdenas, J.C., Paz, A., Pacay, E., Ojeda, A., Is collective titling enough to protect forest? Evidence from Afro-descendant communities in the Colombian Pacific Region (2019) Centro de Estudios sobre Desarrollo Económico CEDE, , Universidad de los Andes
dc.relation.referencesSSRN: Bogota, Columbia

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record