Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG]
This study aims to determine the wetland potential on a pixel basis on the floodplain of the Leon River: hydrology, hydrophytic vegetation and hydromorphic soils were taken into account. Field measurements and spatially explicit models were used to model surface hydrology and piezometric levels. Sat...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/4344
- Acceso en línea:
- http://hdl.handle.net/11407/4344
- Palabra clave:
- Agriculture
Environmental management
Piezometric levels
Topographic wetness index
Wetland
- Rights
- License
- http://purl.org/coar/access_right/c_16ec
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dc.title.spa.fl_str_mv |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
title |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
spellingShingle |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] Agriculture Environmental management Piezometric levels Topographic wetness index Wetland |
title_short |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
title_full |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
title_fullStr |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
title_full_unstemmed |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
title_sort |
Identification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG] |
dc.contributor.affiliation.spa.fl_str_mv |
Anaya-Acevedo, J.A., Universidad de Medellín, Medellín, Colombia Escobar-Martínez, J.F., Universidad de Antioquia, Medellín, Colombia Massone, H., Universidad de Mar del Plata, Mar del Plata, Argentina Booman, G., Universidad de Mar del Plata, Mar del Plata, Argentina Quiroz-Londoño, O.M., Universidad de Mar del Plata, Mar del Plata, Argentina Cañón-Barriga, C.C., Pontificia Universidad Javeriana de Cali, Cali, Colombia Montoya-Jaramillo, L.J., Universidad de Medellín, Medellín, Colombia Palomino-Ángel, S., Universidad de Medellín, Medellín, Colombia |
dc.subject.keyword.eng.fl_str_mv |
Agriculture Environmental management Piezometric levels Topographic wetness index Wetland |
topic |
Agriculture Environmental management Piezometric levels Topographic wetness index Wetland |
description |
This study aims to determine the wetland potential on a pixel basis on the floodplain of the Leon River: hydrology, hydrophytic vegetation and hydromorphic soils were taken into account. Field measurements and spatially explicit models were used to model surface hydrology and piezometric levels. Satellite data were used to derive inundated areas and vegetation. Existing maps from the national geographic institute (IGAC) were used to define the spatial distribution of hydromorphic soils. Special attention was paid to agricultural infrastructure, levees and diversion channels used to modify surface hydrology in order to promote plantations and cattle grazing. A total of 536 km2 meet one or more wetland conditions according to biophysical variables, but only 393 km2 were selected, using logical rules, as wetland pixels. The combination of biophysical variables to define wetland potential is discussed in terms of the spatial distribution and the implications for environmental resource management. © The author; licensee Universidad Nacional de Colombia. |
publishDate |
2017 |
dc.date.accessioned.none.fl_str_mv |
2017-12-19T19:36:49Z |
dc.date.available.none.fl_str_mv |
2017-12-19T19:36:49Z |
dc.date.created.none.fl_str_mv |
2017 |
dc.type.eng.fl_str_mv |
Article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/article |
dc.identifier.issn.none.fl_str_mv |
127353 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/11407/4344 |
dc.identifier.doi.none.fl_str_mv |
10.15446/dyna.v84n201.58600 |
dc.identifier.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional Universidad de Medellín |
dc.identifier.instname.spa.fl_str_mv |
instname:Universidad de Medellín |
identifier_str_mv |
127353 10.15446/dyna.v84n201.58600 reponame:Repositorio Institucional Universidad de Medellín instname:Universidad de Medellín |
url |
http://hdl.handle.net/11407/4344 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.isversionof.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026654774&doi=10.15446%2fdyna.v84n201.58600&partnerID=40&md5=8da771a005b124f7037551a369992b47 |
dc.relation.ispartofes.spa.fl_str_mv |
DYNA (Colombia) |
dc.relation.references.spa.fl_str_mv |
Cowardin, L.M., (1992) Classification of wetlands and deepwater habitats of the United States, p. 131. , U.S.F.a.W. Service, Editor. Government printing office: Washington, USA Cavalcanti, I.F.A., Large scale and synoptic features associated with extreme precipitation over South America: A review and case studies for the first decade of the 21st century (2012) Atmospheric Research, 118, pp. 27-40 Hoyos, N., Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: The human toll of an extreme weather event (2013) Applied Geography, 39, pp. 16-25 Brooks, R., (2011) Proposed Hydrogeomorphic classification for wetlands of the Mid-Atlantic Region, pp. 31 and 207-219. , USA. Wetlands Euliss, N.H., The wetland continumm: A conceptual framework for interpreting biological studies (2004) Wetlands, 24 (2), pp. 448-458 Costanza, R., Changes in the global value of ecosystem services (2014) Global Environmental Change, 26, pp. 152-158 Jones, K., Monitoring and assessment of wetlands using Earth Observation: The GlobWetland project (2009) Journal of Environmental Management, 90 (7), pp. 2154-2169 Combes, J.L., Deforestation and seigniorage in developing countries: A tradeoff? (2015) Ecological Economics, 116, pp. 220-230 Ceddia, M.G., Gunter, U., Corriveau-Bourque, A., Land tenure and agricultural expansion in Latin America: The role of Indigenous Peoples’ and local communities’ forest rights (2015) Global Environmental Change, 35, pp. 316-322 Reed, M.S., Who’s in and why? A typology of stakeholder analysis methods for natural resource management (2009) Journal of Environmental Management, 90 (5), pp. 1933-1949 Nelson, R.W., Weller, E., A better rationale for wetland management (1984) Environmental Management, 8 (4), pp. 295-308 (2005) Ecosystems and human well-being: Biodiversity synthesis, p. 86. , in Island Press, W.R. Institute, Editor, Washington, D.C Prance, T.G., A comparison of the efficacy of higher taxa and species numbers in the assessment of biodiversity in the neotropics (1994) Philosophical Transactions of The Royal Society, 345 (1311), pp. 89-99 Padial, A.A., Bini, L.M., Thomas, S.M., The study of aquatic macrophytes in Neotropics: A scientometrical view of the main trends and gaps (2008) Brazilian Journal of Biology., 68 (4), pp. 1051-1059 Johnston, R., WETwin: A structured approach to evaluating wetland management options in data-poor contexts (2013) Environmental Science & Policy, 34, pp. 3-17 Long, C.M., Pavelsky, T.M., Remote sensing of suspended sediment concentration and hydrologic connectivity in a complex wetland environment (2013) Remote Sensing of Environment, 129, pp. 197-209 Ward, D.P., Floodplain inundation and vegetation dynamics in the Alligator Rivers region (Kakadu) of northern Australia assessed using optical and radar remote sensing (2014) Remote Sensing of Environment, 147, pp. 43-55 Zhao, X., Stein, A., Chen, X.-L., Monitoring the dynamics of wetland inundation by random sets on multi-temporal images (2011) Remote Sensing of Environment, 115 (9), pp. 2390-2401 Restrepo, J.D., Kjerfve, B., Water discharge and sediment load from the western slopes of the colombian Andes with focus on rio San Juan (2000) The Journal of Geology, 108, pp. 17-33 Villegas, P., Assessing the hydrochemistry of the Urabá Aquifer, Colombia by principal component analysis (2013) Journal of Geochemical Exploration, 134, pp. 120-129 Holmes, R., Armanini, D.G., Yates, A.G., Effects of best management practice on ecological condition: Does location matter? (2016) Environmental Management, 57 (5), pp. 1062-1076 Mitsch, W.J., Tropical wetlands: Seasonal hydrologic pulsing, carbon sequestration and methane emissions (2010) Wetland Ecology and Management, 18, pp. 573-586 Fortin, M.J., Issues related to the detection of boundaries (2000) Lanscape Ecology, 15, pp. 453-466 Chen, L., Dynamic monitoring of wetland cover changes using time-series remote sensing imagery (2014) Ecological Informatics, 24, pp. 17-26 Huang, C., Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data (2014) Remote Sensing of Environment, 141, pp. 231-242 Marti-Cardona, B., Dolz-Ripolles, J., Lopez-Martinez, C., Wetland inundation monitoring by the synergistic use of ENVISAT/ASAR imagery and ancilliary spatial data (2013) Remote Sensing of Environment, 139, pp. 171-184 Petus, C., Lewis, M., White, D., Monitoring temporal dynamics of Great Artesian Basin wetland vegetation, Australia, using MODIS NDVI (2013) Ecological Indicators, 34, pp. 41-52 Grenier, M., (2008) Accuracy assessment method for wetland object-based classification, , in ISPRS, XXXVIII-4/C1. Calgary, Alberta, Canada Salari, A., Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing (2014) Wetlands, 34, pp. 565-574 Anaya, J.A., Chuvieco-Salinero, E., Accuracy assessment of burned area products in the Orinoco basin (2012) Photogrammetric Engineering and Remote Sensing, 78 (1), pp. 53-60 Palomino, S., Anaya, J.A., Evaluation of the causes of error in the MCD45 burned-area product of the savannas of northern South America (2012) DYNA, 79 (176), pp. 35-44 Cheng, T., Predicting leaf gravimetric water content from foliar reflectance across a range of plant species using continuous wavelet analysis (2012) Journal of Plant Physiology, 169 (12), pp. 1134-1142 Infascelli, R., Testing different topographic indexes to predict wetlands distribution (2013) Procedia Environmental Sciences, 19, pp. 733-746 Sorensen, R., Zinko, U., Seibert, J., On the calculation of the topographic wetness index: Evaluation of different methods based on field observations (2006) Hydrology and Earth System Sciences, 10, pp. 101-112 Tarboton, D.G., (2009) Generalized terrain-based flow analysis of digital elevation models, in World IMACS/ MODSIM, pp. 2000-2006 (2007) Estudio Semidetallado de Suelos 1:25000, , Departamento de Antioquia, Urabá Estudio general de suelos y zonificación de tierras (2007) Departamento de Antioquia, , 1:100000 (2010) Keys to Soil Taxonomy, p. 338. , N.R.C. service, Editor Ozesmi, S.L., Bauer, M.E., Satellite remote sensing of wetlands (2014) Wetlands Ecology and Management, 10 (5), pp. 381-402 Congalton, R.G., Green, K., (2009) Assessing the accuracy of remotely sensed data, p. 183. , 2nd ed, Boca Raton, FL, USA: CRC Press Giri, C., Status and distribution of mangrove forests of the world using earth observation satellite data (2011) Global Ecology and Biogeography, 20, pp. 154-159 McBratney, A.B., Webster, R., Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates (1986) Journal of Soil Science, 37, pp. 617-639 Pollice, A., Lasinio, G.J., Two approaches to imputation and adjustment of air quality data from a composite monitoring network (2009) Journal of Data Science, 7, pp. 43-59 Anaya, J., Colditz, R., Valencia, G., Land cover mapping of a tropical region by integrating multi-year data into an annual time series (2015) Remote Sensing, 7 (12), p. 15833 Ludwig, R., Schneider, P., Validation of digital elevation models from SRTM X-SAR for applications in hydrologic modeling (2006) ISPRS Journal of Photogrammetry and Remote Sensing, 60 (5), pp. 339-358 Zhu, J., Satish, M., A boundary element method for stochastic flow problems in a semiconfined aquifer with random boundary conditions (1997) Engineering Analysis with Boundary Elements, 19, pp. 199-208 (2014), 2013 Supplement to the 2006 IPCC Guidelines for National GreenHouse Gas Inventories: Wetlands., I.f.G.E. Strategies, Editor. Intergovernmental Panel on Climate Change: Switzerland Restrepo, J.D., Alvarado, E.M., (2011) 11.12 - Assessing major environmental issues in the Caribbean and Pacific coasts of Colombia, pp. 289-314. , South America: An overview of fluvial fluxes, coral reef degradation, and mangrove ecosystems impacted by river diversion, in: Wolanski E. and McLusky, D., Editors, Treatise on estuarine and coastal science, Academic Press: Waltham Naiman, R., Kantor, S., Bilby, R.E., River ecology and management (2013) Lessons from the Pacific Coastal ecoregion, p. 705. , ed. Springer: New York Wren, D.G., The evolution of an oxbow lake in the Mississippi alluvial floodplain (2008) Journal of Soil and Water Conservation, 63 (3), pp. 129-135 |
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2017-12-19T19:36:49Z2017-12-19T19:36:49Z2017127353http://hdl.handle.net/11407/434410.15446/dyna.v84n201.58600reponame:Repositorio Institucional Universidad de Medellíninstname:Universidad de MedellínThis study aims to determine the wetland potential on a pixel basis on the floodplain of the Leon River: hydrology, hydrophytic vegetation and hydromorphic soils were taken into account. Field measurements and spatially explicit models were used to model surface hydrology and piezometric levels. Satellite data were used to derive inundated areas and vegetation. Existing maps from the national geographic institute (IGAC) were used to define the spatial distribution of hydromorphic soils. Special attention was paid to agricultural infrastructure, levees and diversion channels used to modify surface hydrology in order to promote plantations and cattle grazing. A total of 536 km2 meet one or more wetland conditions according to biophysical variables, but only 393 km2 were selected, using logical rules, as wetland pixels. The combination of biophysical variables to define wetland potential is discussed in terms of the spatial distribution and the implications for environmental resource management. © The author; licensee Universidad Nacional de Colombia.engUniversidad Nacional de ColombiaFacultad de Ingenieríashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85026654774&doi=10.15446%2fdyna.v84n201.58600&partnerID=40&md5=8da771a005b124f7037551a369992b47DYNA (Colombia)Cowardin, L.M., (1992) Classification of wetlands and deepwater habitats of the United States, p. 131. , U.S.F.a.W. Service, Editor. Government printing office: Washington, USACavalcanti, I.F.A., Large scale and synoptic features associated with extreme precipitation over South America: A review and case studies for the first decade of the 21st century (2012) Atmospheric Research, 118, pp. 27-40Hoyos, N., Impact of the 2010-2011 La Niña phenomenon in Colombia, South America: The human toll of an extreme weather event (2013) Applied Geography, 39, pp. 16-25Brooks, R., (2011) Proposed Hydrogeomorphic classification for wetlands of the Mid-Atlantic Region, pp. 31 and 207-219. , USA. WetlandsEuliss, N.H., The wetland continumm: A conceptual framework for interpreting biological studies (2004) Wetlands, 24 (2), pp. 448-458Costanza, R., Changes in the global value of ecosystem services (2014) Global Environmental Change, 26, pp. 152-158Jones, K., Monitoring and assessment of wetlands using Earth Observation: The GlobWetland project (2009) Journal of Environmental Management, 90 (7), pp. 2154-2169Combes, J.L., Deforestation and seigniorage in developing countries: A tradeoff? (2015) Ecological Economics, 116, pp. 220-230Ceddia, M.G., Gunter, U., Corriveau-Bourque, A., Land tenure and agricultural expansion in Latin America: The role of Indigenous Peoples’ and local communities’ forest rights (2015) Global Environmental Change, 35, pp. 316-322Reed, M.S., Who’s in and why? A typology of stakeholder analysis methods for natural resource management (2009) Journal of Environmental Management, 90 (5), pp. 1933-1949Nelson, R.W., Weller, E., A better rationale for wetland management (1984) Environmental Management, 8 (4), pp. 295-308(2005) Ecosystems and human well-being: Biodiversity synthesis, p. 86. , in Island Press, W.R. Institute, Editor, Washington, D.CPrance, T.G., A comparison of the efficacy of higher taxa and species numbers in the assessment of biodiversity in the neotropics (1994) Philosophical Transactions of The Royal Society, 345 (1311), pp. 89-99Padial, A.A., Bini, L.M., Thomas, S.M., The study of aquatic macrophytes in Neotropics: A scientometrical view of the main trends and gaps (2008) Brazilian Journal of Biology., 68 (4), pp. 1051-1059Johnston, R., WETwin: A structured approach to evaluating wetland management options in data-poor contexts (2013) Environmental Science & Policy, 34, pp. 3-17Long, C.M., Pavelsky, T.M., Remote sensing of suspended sediment concentration and hydrologic connectivity in a complex wetland environment (2013) Remote Sensing of Environment, 129, pp. 197-209Ward, D.P., Floodplain inundation and vegetation dynamics in the Alligator Rivers region (Kakadu) of northern Australia assessed using optical and radar remote sensing (2014) Remote Sensing of Environment, 147, pp. 43-55Zhao, X., Stein, A., Chen, X.-L., Monitoring the dynamics of wetland inundation by random sets on multi-temporal images (2011) Remote Sensing of Environment, 115 (9), pp. 2390-2401Restrepo, J.D., Kjerfve, B., Water discharge and sediment load from the western slopes of the colombian Andes with focus on rio San Juan (2000) The Journal of Geology, 108, pp. 17-33Villegas, P., Assessing the hydrochemistry of the Urabá Aquifer, Colombia by principal component analysis (2013) Journal of Geochemical Exploration, 134, pp. 120-129Holmes, R., Armanini, D.G., Yates, A.G., Effects of best management practice on ecological condition: Does location matter? (2016) Environmental Management, 57 (5), pp. 1062-1076Mitsch, W.J., Tropical wetlands: Seasonal hydrologic pulsing, carbon sequestration and methane emissions (2010) Wetland Ecology and Management, 18, pp. 573-586Fortin, M.J., Issues related to the detection of boundaries (2000) Lanscape Ecology, 15, pp. 453-466Chen, L., Dynamic monitoring of wetland cover changes using time-series remote sensing imagery (2014) Ecological Informatics, 24, pp. 17-26Huang, C., Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data (2014) Remote Sensing of Environment, 141, pp. 231-242Marti-Cardona, B., Dolz-Ripolles, J., Lopez-Martinez, C., Wetland inundation monitoring by the synergistic use of ENVISAT/ASAR imagery and ancilliary spatial data (2013) Remote Sensing of Environment, 139, pp. 171-184Petus, C., Lewis, M., White, D., Monitoring temporal dynamics of Great Artesian Basin wetland vegetation, Australia, using MODIS NDVI (2013) Ecological Indicators, 34, pp. 41-52Grenier, M., (2008) Accuracy assessment method for wetland object-based classification, , in ISPRS, XXXVIII-4/C1. Calgary, Alberta, CanadaSalari, A., Quantifying tropical wetlands using field surveys, spatial statistics and remote sensing (2014) Wetlands, 34, pp. 565-574Anaya, J.A., Chuvieco-Salinero, E., Accuracy assessment of burned area products in the Orinoco basin (2012) Photogrammetric Engineering and Remote Sensing, 78 (1), pp. 53-60Palomino, S., Anaya, J.A., Evaluation of the causes of error in the MCD45 burned-area product of the savannas of northern South America (2012) DYNA, 79 (176), pp. 35-44Cheng, T., Predicting leaf gravimetric water content from foliar reflectance across a range of plant species using continuous wavelet analysis (2012) Journal of Plant Physiology, 169 (12), pp. 1134-1142Infascelli, R., Testing different topographic indexes to predict wetlands distribution (2013) Procedia Environmental Sciences, 19, pp. 733-746Sorensen, R., Zinko, U., Seibert, J., On the calculation of the topographic wetness index: Evaluation of different methods based on field observations (2006) Hydrology and Earth System Sciences, 10, pp. 101-112Tarboton, D.G., (2009) Generalized terrain-based flow analysis of digital elevation models, in World IMACS/ MODSIM, pp. 2000-2006(2007) Estudio Semidetallado de Suelos 1:25000, , Departamento de Antioquia, UrabáEstudio general de suelos y zonificación de tierras (2007) Departamento de Antioquia, , 1:100000(2010) Keys to Soil Taxonomy, p. 338. , N.R.C. service, EditorOzesmi, S.L., Bauer, M.E., Satellite remote sensing of wetlands (2014) Wetlands Ecology and Management, 10 (5), pp. 381-402Congalton, R.G., Green, K., (2009) Assessing the accuracy of remotely sensed data, p. 183. , 2nd ed, Boca Raton, FL, USA: CRC PressGiri, C., Status and distribution of mangrove forests of the world using earth observation satellite data (2011) Global Ecology and Biogeography, 20, pp. 154-159McBratney, A.B., Webster, R., Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates (1986) Journal of Soil Science, 37, pp. 617-639Pollice, A., Lasinio, G.J., Two approaches to imputation and adjustment of air quality data from a composite monitoring network (2009) Journal of Data Science, 7, pp. 43-59Anaya, J., Colditz, R., Valencia, G., Land cover mapping of a tropical region by integrating multi-year data into an annual time series (2015) Remote Sensing, 7 (12), p. 15833Ludwig, R., Schneider, P., Validation of digital elevation models from SRTM X-SAR for applications in hydrologic modeling (2006) ISPRS Journal of Photogrammetry and Remote Sensing, 60 (5), pp. 339-358Zhu, J., Satish, M., A boundary element method for stochastic flow problems in a semiconfined aquifer with random boundary conditions (1997) Engineering Analysis with Boundary Elements, 19, pp. 199-208(2014), 2013 Supplement to the 2006 IPCC Guidelines for National GreenHouse Gas Inventories: Wetlands., I.f.G.E. Strategies, Editor. Intergovernmental Panel on Climate Change: SwitzerlandRestrepo, J.D., Alvarado, E.M., (2011) 11.12 - Assessing major environmental issues in the Caribbean and Pacific coasts of Colombia, pp. 289-314. , South America: An overview of fluvial fluxes, coral reef degradation, and mangrove ecosystems impacted by river diversion, in: Wolanski E. and McLusky, D., Editors, Treatise on estuarine and coastal science, Academic Press: WalthamNaiman, R., Kantor, S., Bilby, R.E., River ecology and management (2013) Lessons from the Pacific Coastal ecoregion, p. 705. , ed. Springer: New YorkWren, D.G., The evolution of an oxbow lake in the Mississippi alluvial floodplain (2008) Journal of Soil and Water Conservation, 63 (3), pp. 129-135ScopusIdentification of wetland areas in the context of agricultural development using remote sensing and GIS [Identificación de áreas de humedal en el contexto del desarrollo agrícola usando teledetección y SIG]Articleinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Anaya-Acevedo, J.A., Universidad de Medellín, Medellín, ColombiaEscobar-Martínez, J.F., Universidad de Antioquia, Medellín, ColombiaMassone, H., Universidad de Mar del Plata, Mar del Plata, ArgentinaBooman, G., Universidad de Mar del Plata, Mar del Plata, ArgentinaQuiroz-Londoño, O.M., Universidad de Mar del Plata, Mar del Plata, ArgentinaCañón-Barriga, C.C., Pontificia Universidad Javeriana de Cali, Cali, ColombiaMontoya-Jaramillo, L.J., Universidad de Medellín, Medellín, ColombiaPalomino-Ángel, S., Universidad de Medellín, Medellín, ColombiaAnaya-Acevedo J.A.Escobar-Martínez J.F.Massone H.Booman G.Quiroz-Londoño O.M.Cañón-Barriga C.C.Montoya-Jaramillo L.J.Palomino-Ángel S.Universidad de Medellín, Medellín, ColombiaUniversidad de Antioquia, Medellín, ColombiaUniversidad de Mar del Plata, Mar del Plata, ArgentinaPontificia Universidad Javeriana de Cali, Cali, ColombiaUniversidad de Medellín, Medellín, ColombiaAgricultureEnvironmental managementPiezometric levelsTopographic wetness indexWetlandThis study aims to determine the wetland potential on a pixel basis on the floodplain of the Leon River: hydrology, hydrophytic vegetation and hydromorphic soils were taken into account. Field measurements and spatially explicit models were used to model surface hydrology and piezometric levels. Satellite data were used to derive inundated areas and vegetation. Existing maps from the national geographic institute (IGAC) were used to define the spatial distribution of hydromorphic soils. Special attention was paid to agricultural infrastructure, levees and diversion channels used to modify surface hydrology in order to promote plantations and cattle grazing. A total of 536 km2 meet one or more wetland conditions according to biophysical variables, but only 393 km2 were selected, using logical rules, as wetland pixels. The combination of biophysical variables to define wetland potential is discussed in terms of the spatial distribution and the implications for environmental resource management. © The author; licensee Universidad Nacional de Colombia.http://purl.org/coar/access_right/c_16ecTHUMBNAIL16. Identification of wetland areas in the context.pdf.jpg16. Identification of wetland areas in the context.pdf.jpgIM Thumbnailimage/jpeg9787http://repository.udem.edu.co/bitstream/11407/4344/2/16.%20Identification%20of%20wetland%20areas%20in%20the%20context.pdf.jpg25414ba186590d68bb11336485405647MD52ORIGINAL16. Identification of wetland areas in the context.pdf16. Identification of wetland areas in the context.pdfapplication/pdf786221http://repository.udem.edu.co/bitstream/11407/4344/1/16.%20Identification%20of%20wetland%20areas%20in%20the%20context.pdfdced5079fd1968414fb9731f2d94180dMD5111407/4344oai:repository.udem.edu.co:11407/43442020-05-27 18:24:24.618Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co |