A land cover map of Latin America and the Caribbean in the framework of the SERENA project
- Autores
- Blanco, Paula Daniela; Colditz, Rene R.; López Saldaña, Gerardo; Hardtke, Leonardo Andrés; Llamas, Ricardo M.; Mari, Nicolás Alejandro; Fischer, Maria De Los Angeles; Caride, Constanza; Aceñolaza, Pablo Gilberto; del Valle, Hector Francisco; Lillo Saavedra, Mario F.; Coronato, Fernando Raul; Opazo, Sergio A.; Morelli, Fabiano; Anaya Acevedo, Jesús Adolfo; Sione, Walter Fabian; Zamboni, Pamela; Barrena Arroyo, Victor
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Land cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling.
Instituto de Clima y Agua
Fil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Colditz, Rene R. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; México
Fil: López Saldaña, Gerardo. Universidade Técnica de Lisboa. Escuela de Agronomía. Department of Forestry; Portugal
Fil: Hardtke, Leonardo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Llamas, Ricardo M. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; México
Fil: Mari, Nicolás Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina
Fil: Fischer, Maria De Los Angeles. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina
Fil: Caride, Constanza. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina
Fil: Aceñolaza, Pablo Gilberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentina. Universidad Nacional de Entre Ríos; Argentina
Fil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Lillo Saavedra, Mario F. Universidad de Concepción. Department of Electronic Engineering; Chile
Fil: Coronato, Fernando Raul. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina
Fil: Opazo, Sergio A.. Universidad de Magallanes. Science and Agricultural Technology School; Chile
Fil: Morelli, Fabiano. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; Brasil
Fil: Anaya Acevedo, Jesús Adolfo. Universidad de Medellin. Facultad de Ingeniería; Colombia
Fil: Sione, Walter Fabian. Universidad Autónoma de Entre Ríos; Argentina. Universidad Nacional de Lujan; Argentina
Fil: Zamboni, Pamela. Universidad Autónoma de Entre Ríos; Argentina
Fil: Barrena Arroyo, Victor. Universidad Nacional Agraria La Molina; Perú - Fuente
- Remote Sensing of Environment 132 : 13-31 (May 2013)
- Materia
-
Vigilancia
Espectrorradiómetro de Imágenes de Resolución Moderada
Medio Ambiente
Cambio Climático
Monitoring
Moderate Resolution Imaging Spectroradiometer
Environment
Climate Change
Proyecto SERENA
América Latina
Caribe
MODIS - Nivel de accesibilidad
- acceso restringido
- Condiciones de uso
- Repositorio
.jpg)
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/5300
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A land cover map of Latin America and the Caribbean in the framework of the SERENA projectBlanco, Paula DanielaColditz, Rene R.López Saldaña, GerardoHardtke, Leonardo AndrésLlamas, Ricardo M.Mari, Nicolás AlejandroFischer, Maria De Los AngelesCaride, ConstanzaAceñolaza, Pablo Gilbertodel Valle, Hector FranciscoLillo Saavedra, Mario F.Coronato, Fernando RaulOpazo, Sergio A.Morelli, FabianoAnaya Acevedo, Jesús AdolfoSione, Walter FabianZamboni, PamelaBarrena Arroyo, VictorVigilanciaEspectrorradiómetro de Imágenes de Resolución ModeradaMedio AmbienteCambio ClimáticoMonitoringModerate Resolution Imaging SpectroradiometerEnvironmentClimate ChangeProyecto SERENAAmérica LatinaCaribeMODISLand cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling.Instituto de Clima y AguaFil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Colditz, Rene R. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; MéxicoFil: López Saldaña, Gerardo. Universidade Técnica de Lisboa. Escuela de Agronomía. Department of Forestry; PortugalFil: Hardtke, Leonardo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Llamas, Ricardo M. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; MéxicoFil: Mari, Nicolás Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, ArgentinaFil: Fischer, Maria De Los Angeles. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, ArgentinaFil: Caride, Constanza. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, ArgentinaFil: Aceñolaza, Pablo Gilberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentina. Universidad Nacional de Entre Ríos; ArgentinaFil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Lillo Saavedra, Mario F. Universidad de Concepción. Department of Electronic Engineering; ChileFil: Coronato, Fernando Raul. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Opazo, Sergio A.. Universidad de Magallanes. Science and Agricultural Technology School; ChileFil: Morelli, Fabiano. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; BrasilFil: Anaya Acevedo, Jesús Adolfo. Universidad de Medellin. Facultad de Ingeniería; ColombiaFil: Sione, Walter Fabian. Universidad Autónoma de Entre Ríos; Argentina. Universidad Nacional de Lujan; ArgentinaFil: Zamboni, Pamela. Universidad Autónoma de Entre Ríos; ArgentinaFil: Barrena Arroyo, Victor. Universidad Nacional Agraria La Molina; PerúElsevier2019-06-12T12:26:43Z2019-06-12T12:26:43Z2013-05-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/5300https://www.sciencedirect.com/science/article/pii/S00344257130000350034-4257https://doi.org/10.1016/j.rse.2012.12.025Remote Sensing of Environment 132 : 13-31 (May 2013)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-10-23T11:16:58Zoai:localhost:20.500.12123/5300instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-23 11:16:59.02INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
| dc.title.none.fl_str_mv |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| title |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| spellingShingle |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project Blanco, Paula Daniela Vigilancia Espectrorradiómetro de Imágenes de Resolución Moderada Medio Ambiente Cambio Climático Monitoring Moderate Resolution Imaging Spectroradiometer Environment Climate Change Proyecto SERENA América Latina Caribe MODIS |
| title_short |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| title_full |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| title_fullStr |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| title_full_unstemmed |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| title_sort |
A land cover map of Latin America and the Caribbean in the framework of the SERENA project |
| dc.creator.none.fl_str_mv |
Blanco, Paula Daniela Colditz, Rene R. López Saldaña, Gerardo Hardtke, Leonardo Andrés Llamas, Ricardo M. Mari, Nicolás Alejandro Fischer, Maria De Los Angeles Caride, Constanza Aceñolaza, Pablo Gilberto del Valle, Hector Francisco Lillo Saavedra, Mario F. Coronato, Fernando Raul Opazo, Sergio A. Morelli, Fabiano Anaya Acevedo, Jesús Adolfo Sione, Walter Fabian Zamboni, Pamela Barrena Arroyo, Victor |
| author |
Blanco, Paula Daniela |
| author_facet |
Blanco, Paula Daniela Colditz, Rene R. López Saldaña, Gerardo Hardtke, Leonardo Andrés Llamas, Ricardo M. Mari, Nicolás Alejandro Fischer, Maria De Los Angeles Caride, Constanza Aceñolaza, Pablo Gilberto del Valle, Hector Francisco Lillo Saavedra, Mario F. Coronato, Fernando Raul Opazo, Sergio A. Morelli, Fabiano Anaya Acevedo, Jesús Adolfo Sione, Walter Fabian Zamboni, Pamela Barrena Arroyo, Victor |
| author_role |
author |
| author2 |
Colditz, Rene R. López Saldaña, Gerardo Hardtke, Leonardo Andrés Llamas, Ricardo M. Mari, Nicolás Alejandro Fischer, Maria De Los Angeles Caride, Constanza Aceñolaza, Pablo Gilberto del Valle, Hector Francisco Lillo Saavedra, Mario F. Coronato, Fernando Raul Opazo, Sergio A. Morelli, Fabiano Anaya Acevedo, Jesús Adolfo Sione, Walter Fabian Zamboni, Pamela Barrena Arroyo, Victor |
| author2_role |
author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Vigilancia Espectrorradiómetro de Imágenes de Resolución Moderada Medio Ambiente Cambio Climático Monitoring Moderate Resolution Imaging Spectroradiometer Environment Climate Change Proyecto SERENA América Latina Caribe MODIS |
| topic |
Vigilancia Espectrorradiómetro de Imágenes de Resolución Moderada Medio Ambiente Cambio Climático Monitoring Moderate Resolution Imaging Spectroradiometer Environment Climate Change Proyecto SERENA América Latina Caribe MODIS |
| dc.description.none.fl_txt_mv |
Land cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling. Instituto de Clima y Agua Fil: Blanco, Paula Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Colditz, Rene R. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; México Fil: López Saldaña, Gerardo. Universidade Técnica de Lisboa. Escuela de Agronomía. Department of Forestry; Portugal Fil: Hardtke, Leonardo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Llamas, Ricardo M. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad; México Fil: Mari, Nicolás Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina Fil: Fischer, Maria De Los Angeles. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina Fil: Caride, Constanza. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua, Argentina Fil: Aceñolaza, Pablo Gilberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones Científicas y Transferencia de Tecnología a la Producción; Argentina. Universidad Nacional de Entre Ríos; Argentina Fil: del Valle, Hector Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Lillo Saavedra, Mario F. Universidad de Concepción. Department of Electronic Engineering; Chile Fil: Coronato, Fernando Raul. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentina Fil: Opazo, Sergio A.. Universidad de Magallanes. Science and Agricultural Technology School; Chile Fil: Morelli, Fabiano. Centro de Previsao de Tempo e Estudos Climaticos. Instituto Nacional de Pesquisas Espaciais; Brasil Fil: Anaya Acevedo, Jesús Adolfo. Universidad de Medellin. Facultad de Ingeniería; Colombia Fil: Sione, Walter Fabian. Universidad Autónoma de Entre Ríos; Argentina. Universidad Nacional de Lujan; Argentina Fil: Zamboni, Pamela. Universidad Autónoma de Entre Ríos; Argentina Fil: Barrena Arroyo, Victor. Universidad Nacional Agraria La Molina; Perú |
| description |
Land cover maps at different resolutions and mapping extents contribute to modeling and support decision making processes. Because land cover affects and is affected by climate change, it is listed among the 13 terrestrial essential climate variables. This paper describes the generation of a land cover map for Latin America and the Caribbean (LAC) for the year 2008. It was developed in the framework of the project Latin American Network for Monitoring and Studying of Natural Resources (SERENA), which has been developed within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLaTIF). The SERENA land cover map for LAC integrates: 1) the local expertise of SERENA network members to generate the training and validation data, 2) a methodology for land cover mapping based on decision trees using MODIS time series, and 3) class membership estimates to account for pixel heterogeneity issues. The discrete SERENA land cover product, derived from class memberships, yields an overall accuracy of 84% and includes an additional layer representing the estimated per-pixel confidence. The study demonstrates in detail the use of class memberships to better estimate the area of scarce classes with a scattered spatial distribution. The land cover map is already available as a printed wall map and will be released in digital format in the near future. The SERENA land cover map was produced with a legend and classification strategy similar to that used by the North American Land Change Monitoring System (NALCMS) to generate a land cover map of the North American continent, that will allow to combine both maps to generate consistent data across America facilitating continental monitoring and modeling. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013-05-15 2019-06-12T12:26:43Z 2019-06-12T12:26:43Z |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
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http://hdl.handle.net/20.500.12123/5300 https://www.sciencedirect.com/science/article/pii/S0034425713000035 0034-4257 https://doi.org/10.1016/j.rse.2012.12.025 |
| url |
http://hdl.handle.net/20.500.12123/5300 https://www.sciencedirect.com/science/article/pii/S0034425713000035 https://doi.org/10.1016/j.rse.2012.12.025 |
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0034-4257 |
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eng |
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application/pdf |
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Elsevier |
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Elsevier |
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Remote Sensing of Environment 132 : 13-31 (May 2013) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
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INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria |
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tripaldi.nicolas@inta.gob.ar |
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