Markedly divergent estimates of A mazon forest carbon density from ground plots and satellites

作者：Edward T. A. Mitchard, Ted R. Feldpausch, Roel J. W. Brienen, Gabriela López‐González, Abel Lorenzo Monteagudo, Timothy R. Baker, Simon L. Lewis, Jon Lloyd, Carlos Alberto Quesada, Manuel U. Gloor, Hans ter Steege, Patrick Meir, Esteban Alvarez, Alejandro Araujo‐Murakami, Luiz E. O. C. Aragão, Luzmila Arroyo, Gerardo A. Aymard C., Olaf Bánki, Damien Bonal, Sandra Brown, Foster Brown, Carlos Cerón, Víctor Chama Moscoso, Jérôme Chave, James A. Comiskey, Fernando Cornejo Valverde, Massiel Corrales Medina, Lola da Costa, Flávia R. C. Costa, Anthony Di Fiore, Tomas Ferreira Domingues, Terry L. Erwin, Todd Frederickson, Níro Higuchi, Eurídice N. Honorio Coronado, Tim J. Killeen, Susan G. W. Laurance, Carolina Levis, William Ernest Magnusson, Beatriz Schwantes Marimon, Ben Hur Marimon-Junior, Irina Mendoza Polo, Piyush Mishra, Marcelo Trindade Nascimento, David Neill, Mario Percy Núñez Vargas, Walter A. Palacios, Alexander Parada, Guido Pardo Molina, Marielos Peña‐Claros, Nigel C. A. Pitman, Carlos A. Peres, Lourens Poorter, Adriana Prieto, Hirma Ramírez‐Angulo, Zorayda Restrepo Correa, Anand Roopsind, Katherine H. Roucoux, Agustín Rudas, Rafael P. Salomão, Juliana Schietti, Marcos Silveira, Priscila Figueira de Souza, Marc K. Steininger, Juliana Stropp, John Terborgh, Raquel Thomas, Marisol Toledo, Armando Torres‐Lezama, Tinde R van Andel, Geertje M. F. van der Heijden, Ima Célia Guimarães Vieira, Simone Aparecida Vieira, Emilio Vilanova, Vincent Antoine Vos, Ophelia Wang, Charles E. Zartman, Yadvinder Singh Malhi, Oliver Lawrence Phillips · 发表于：Global Ecology and Biogeography · 年份：2014 · DOI：10.1111/geb.12168 · 被引用次数：326 · 研究领域：Remote Sensing and LiDAR Applications、Forest ecology and management、Remote Sensing in Agriculture

AIM: 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. LOCATION: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. METHODS: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. RESULTS: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. MAIN CONCLUSIONS: Pantropical biomass maps are widely used by governments and by projects aiming to...