Data/hora: 09/06/2024 05:20:15

Biblioteca(s): 	Embrapa Territorial.	
Data corrente: 	01/12/2014	
Data da última atualização: 	03/12/2014	
Autoria: 	SAATCHI, S.; MASCARO, J.; XU, L.; KELLER, M.; YANG, Y.; DUFFY, P.; ESPÍRITO-SANTO, F.; BACCINI, A.; CHAMBERS, J.; SCHIMEL, D.	
Afiliação: 	SASSAN SAATCHI, NASA; JOSEPH MASCARO, American Association for the Advancement; LIANG XU, University of California; MICHAEL KELLER, Pesquisador visitante - CNPM/USDA; YAN YANG, University of California; PAUL DUFFY, Neptune and Company; FERNANDO ESPÍRITO-SANTO, NASA; ALESSANDRO BACCINI, The Woods Hole Research Center; JEFFERY CHAMBERS, University of California; DAVID SCHIMEL, NASA.	
Título: 	Seeing the forest beyond the trees.	
Ano de publicação: 	2014	
Fonte/Imprenta: 	Global Ecology and Biogeography, v. 23, n. 11, p. 1-5, nov. 2014.	
DOI: 	10.1111/geb.12256	
Idioma: 	Inglês	
Notas: 	Artigo publicado por Pesquisador Visitante da Embrapa Monitoramento por Satélite.	
Conteúdo: 	In a recent paper (Mitchard et al. 2014, Global Ecology and Biogeography, 23, 935?946) a new map of forest biomass based on a geostatistical model of field data for the Amazon (and surrounding forests) was presented and contrasted with two earlier maps based on remotesensing data Saatchi et al. (2011; RS1) and Baccini et al. (2012; RS2). Mitchard et al. concluded that both the earlier remote-sensing based maps were incorrect because they did not conform to Mitchard et al. interpretation of the field-based results. In making their case, however, they misrepresented the fundamental nature of primary field and remote-sensing data and committed critical errors in their assumptions about the accuracy of research plots, the interpolation methodology and the statistical analysis. By ignoring the large uncertainty associated with ground estimates of biomass and the significant under-sampling and spatial bias of research plots, Mitchard et al. reported erroneous trends and artificial patterns of biomass over Amazonia. Because of these misrepresentations and methodological flaws, we find their critique of the satellite-derived maps to be invalid.	
Palavras-Chave: 	Spatial modelling; Tree height.	
Thesaurus Nal: 	Allometry; Biomass; Lidar; Remote sensing; Tropical forests; Wood density.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/112639/1/4195.pdf	
Registro original: 	Embrapa Territorial (CNPM)	
Exemplares: 	CNPM - (4195-1) - UPC - AP - DD - 14/061 - AP - 2014.061 - DIS