@misc{braden_satellite-derived_2024,
	title = {Satellite-{Derived} {Forest} {Extent} {Likelihood} {Map} for {Mexico}},
	url = {https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2320},
	doi = {10.3334/ORNLDAAC/2320},
	abstract = {This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas.},
	language = {en},
	urldate = {2024-04-24},
	author = {Braden, D. and Mondal, P. and Park, T. and De la rosa, J.A.A. and Leal, M.I.A. and Lara, R.A.C. and Saucedo, R.M. and Salas-Aguilar, V.M. and Soriano-Luna, M.A. and Vargas, R.},
	collaborator = {{ORNL DAAC}},
	year = {2024},
	note = {Artwork Size: 0 MB
Medium: COG, ESRI Shapefile
Publisher: [object Object]
Version Number: 1},
	keywords = {NALCMS},
}

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These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. 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These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. 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A shapefile is included that outlines Mexico mainland areas.},\n\tlanguage = {en},\n\turldate = {2024-04-24},\n\tauthor = {Braden, D. and Mondal, P. and Park, T. and De la rosa, J.A.A. and Leal, M.I.A. and Lara, R.A.C. and Saucedo, R.M. and Salas-Aguilar, V.M. and Soriano-Luna, M.A. and Vargas, R.},\n\tcollaborator = {{ORNL DAAC}},\n\tyear = {2024},\n\tnote = {Artwork Size: 0 MB\nMedium: COG, ESRI Shapefile\nPublisher: [object Object]\nVersion Number: 1},\n\tkeywords = {NALCMS},\n}\n\n\n\n","author_short":["Braden, D.","Mondal, P.","Park, T.","De la rosa , J.","Leal, M.","Lara, R.","Saucedo, R.","Salas-Aguilar, V.","Soriano-Luna, M.","Vargas, R."],"key":"braden_satellite-derived_2024","id":"braden_satellite-derived_2024","bibbaseid":"braden-mondal-park-delarosa-leal-lara-saucedo-salasaguilar-etal-satellitederivedforestextentlikelihoodmapformexico-2024","role":"author","urls":{"Paper":"https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2320"},"keyword":["NALCMS"],"metadata":{"authorlinks":{}}},"bibtype":"misc","biburl":"https://bibbase.org/zotero/NAAtlas2024","dataSources":["uR8BQAvcFWBaoyn6D","vLHEaQhjzjSqBtnJu","mCt6u2XQbc2BG7LDZ","xjk3ZfRaAEhPcYdMz","qLjf8q88GSLZ5dAmC","aYMHPeamjRmd3KNYY"],"keywords":["nalcms"],"search_terms":["satellite","derived","forest","extent","likelihood","map","mexico","braden","mondal","park","de la rosa ","leal","lara","saucedo","salas-aguilar","soriano-luna","vargas"],"title":"Satellite-Derived Forest Extent Likelihood Map for Mexico","year":2024}