%0 Book Section
%3 oliveira_methods.pdf
%4 sid.inpe.br/plutao/2018/12.14.20.02
%A Oliveira, Gabriel de,
%A Brunsell, Nathaniel A.,
%A Moraes, Elisabete Caria,
%A Shimabukuro, Yosio Edemir,
%A Mataveli, Guilherme A. V.,
%A Santos, Thiago V. dos,
%A Von Randow, Celso,
%A Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Tropical forests: new edition
%@secondarytype PRE LI
%D 2018
%E Sudarshana, Padmini,
%E Nageswara-Rao, Madhugiri,
%E Soneji, Jaya,
%F lattes: 1913003589198061 4 OliveiraBMSMSRA:2018:MeEvLa
%I InTech
%K surface energy budget, CO2  fluxes, eddy covariance, remote sensing, Amazon region.
%P 67-94
%T Methods to evaluate land-atmosphere exchanges in Amazonia based on satellite imagery and ground measurements
%U http://www.intechopen.com/books/tropical-forests-new-edition/methods-to-evaluate-land-atmosphere-exchanges-in-amazonia-based-on-satellite-imagery-and-ground-meas
%X During the last three decades, intensive campaigns and experiments have been conducted for acquiring micrometeorological data in the Amazonian ecosystems, which has increased our understanding of the variation, especially seasonally, of the total energy available for the atmospheric heating process by the surface, evapotranspiration and carbon exchanges. However, the measurements obtained by such experiments generally cover small areas and are not representative of the spatial variability of these processes. This chapter aims to discuss several algorithms developed to estimate surface energy and carbon fluxes combining satellite data and micrometeorological observations, highlighting the potentialities and limitations of such models for applications in the Amazon region. We show that the use of these models presents an important role in understanding the spatial and temporal patterns of biophysical surface parameters in a region where most of the information is local. Data generated may be used as inputs in earth system surface models allowing the evaluation of the impact, both in regional as well as global scales, caused by land-use and land-cover changes.
%@area SRE
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress elisabete.moraes@inpe.br
%@electronicmailaddress yosio.shimabukuro@inpe.br
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress celso.vonrandow@inpe.br
%@electronicmailaddress luiz.aragao@inpe.br
%@documentstage not transferred
%@group
%@group
%@group DIDSR-CGOBT-INPE-MCTIC-GOV-BR
%@group DIDSR-CGOBT-INPE-MCTIC-GOV-BR
%@group
%@group
%@group COCST-COCST-INPE-MCTIC-GOV-BR
%@group DIDSR-CGOBT-INPE-MCTIC-GOV-BR
%@isbn 9781789235623
%@nexthigherunit 8JMKD3MGPCW/3ER446E
%@nexthigherunit 8JMKD3MGPCW/3F3T29H
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JH24
%@resumeid 8JMKD3MGP5W/3C9JJCQ
%@affiliation  University of Kansas,
%@affiliation  University of Kansas,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Universidade de São Paulo (USP)
%@affiliation University of Michigan
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@versiontype publisher
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%@doi 10.5772/intechopen.75194
%2 sid.inpe.br/plutao/2018/12.14.20.02.25