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Markedly divergent estimates of A mazon forest carbon density from ground plots and satellites
Author(s) -
Mitchard Edward T. A.,
Feldpausch Ted R.,
Brienen Roel J. W.,
LopezGonzalez Gabriela,
Monteagudo Abel,
Baker Timothy R.,
Lewis Simon L.,
Lloyd Jon,
Quesada Carlos A.,
Gloor Manuel,
Steege Hans,
Meir Patrick,
Alvarez Esteban,
AraujoMurakami Alejandro,
Aragão Luiz E. O. C.,
Arroyo Luzmila,
Aymard Gerardo,
Banki Olaf,
Bonal Damien,
Brown Sandra,
Brown Foster I.,
Cerón Carlos E.,
Chama Moscoso Victor,
Chave Jerome,
Comiskey James A.,
Cornejo Fernando,
Corrales Medina Massiel,
Da Costa Lola,
Costa Flavia R. C.,
Di Fiore Anthony,
Domingues Tomas F.,
Erwin Terry L.,
Frederickson Todd,
Higuchi Niro,
Honorio Coronado Euridice N.,
Killeen Tim J.,
Laurance William F.,
Levis Carolina,
Magnusson William E.,
Marimon Beatriz S.,
Marimon Junior Ben Hur,
Mendoza Polo Irina,
Mishra Piyush,
Nascimento Marcelo T.,
Neill David,
Núñez Vargas Mario P.,
Palacios Walter A.,
Parada Alexander,
Pardo Molina Guido,
PeñaClaros Marielos,
Pitman Nigel,
Peres Carlos A.,
Poorter Lourens,
Prieto Adriana,
RamirezAngulo Hirma,
Restrepo Correa Zorayda,
Roopsind Anand,
Roucoux Katherine H.,
Rudas Agustin,
Salomão Rafael P.,
Schietti Juliana,
Silveira Marcos,
Souza Priscila F.,
Steininger Marc K.,
Stropp Juliana,
Terborgh John,
Thomas Raquel,
Toledo Marisol,
TorresLezama Armando,
Andel Tinde R.,
Heijden Geertje M. F.,
Vieira Ima C. G.,
Vieira Simone,
VilanovaTorre Emilio,
Vos Vincent A.,
Wang Ophelia,
Zartman Charles E.,
Malhi Yadvinder,
Phillips Oliver L.
Publication year - 2014
Publication title -
global ecology and biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.164
H-Index - 152
eISSN - 1466-8238
pISSN - 1466-822X
DOI - 10.1111/geb.12168
Subject(s) - pantropical , deforestation (computer science) , vegetation (pathology) , carbon cycle , amazon rainforest , biomass (ecology) , environmental science , field (mathematics) , grassland , reducing emissions from deforestation and forest degradation , forest inventory , physical geography , remote sensing , geography , forestry , ecology , climate change , carbon stock , mathematics , forest management , biology , computer science , ecosystem , medicine , pathology , pure mathematics , genus , programming language
The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset.