A land cover map of Latin America and the Caribbean in the framework of the SERENA project. Blanco, P. D., Colditz, R. R., López Saldaña, G., Hardtke, L. A., Llamas, R. M., Mari, N. A., Fischer, A., Caride, C., Aceñolaza, P. G., del Valle, H. F., Lillo-Saavedra, M., Coronato, F., Opazo, S. A., Morelli, F., Anaya, J. A., Sione, W. F., Zamboni, P., & Arroyo, V. B. Remote Sensing of Environment, 132:13–31, May, 2013. Publisher: Elsevier Inc.![A land cover map of Latin America and the Caribbean in the framework of the SERENA project [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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. © 2012 Elsevier Inc.
@article{blanco_land_2013,
title = {A land cover map of {Latin} {America} and the {Caribbean} in the framework of the {SERENA} project},
volume = {132},
issn = {00344257},
url = {http://dx.doi.org/10.1016/j.rse.2012.12.025},
doi = {10.1016/j.rse.2012.12.025},
abstract = {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. © 2012 Elsevier Inc.},
journal = {Remote Sensing of Environment},
author = {Blanco, Paula D. and Colditz, Rene R. and López Saldaña, Gerardo and Hardtke, Leonardo A. and Llamas, Ricardo M. and Mari, Nicolás A. and Fischer, Angeles and Caride, Constanza and Aceñolaza, Pablo G. and del Valle, Héctor F. and Lillo-Saavedra, Mario and Coronato, Fernando and Opazo, Sergio A. and Morelli, Fabiano and Anaya, Jesús A. and Sione, Walter F. and Zamboni, Pamela and Arroyo, Victor Barrena},
month = may,
year = {2013},
note = {Publisher: Elsevier Inc.},
keywords = {NALCMS},
pages = {13--31},
}
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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. 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