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Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia.
de Oliveira, Gabriel; Brunsell, Nathaniel A; Moraes, Elisabete C; Bertani, Gabriel; Dos Santos, Thiago V; Shimabukuro, Yosio E; Aragão, Luiz E O C.
Afiliación
  • de Oliveira G; Remote Sensing Division, National Institute for Space Research, 1758 Astronautas Avenue, São José dos Campos, SP 12227-010, Brazil. gdo@dsr.inpe.br.
  • Brunsell NA; Department of Geography and Atmospheric Science, University of Kansas, 1475 Jayhawk Boulevard, Lawrence, KS 66045, USA. gdo@dsr.inpe.br.
  • Moraes EC; Department of Geography and Atmospheric Science, University of Kansas, 1475 Jayhawk Boulevard, Lawrence, KS 66045, USA. brunsell@ku.edu.
  • Bertani G; Remote Sensing Division, National Institute for Space Research, 1758 Astronautas Avenue, São José dos Campos, SP 12227-010, Brazil. bete@dsr.inpe.br.
  • Dos Santos TV; Remote Sensing Division, National Institute for Space Research, 1758 Astronautas Avenue, São José dos Campos, SP 12227-010, Brazil. gabrielb@dsr.inpe.br.
  • Shimabukuro YE; Department of Soil, Water and Climate, University of Minnesota, 1991 Upper Bufford Circle, Saint Paul, MN 55108, USA. dossa013@umn.edu.
  • Aragão LE; Remote Sensing Division, National Institute for Space Research, 1758 Astronautas Avenue, São José dos Campos, SP 12227-010, Brazil. yosio@dsr.inpe.br.
Sensors (Basel) ; 16(7)2016 Jun 24.
Article en En | MEDLINE | ID: mdl-27347957
ABSTRACT
In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001-December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2016 Tipo del documento: Article País de afiliación: Brasil

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2016 Tipo del documento: Article País de afiliación: Brasil