Use of MODIS sensor images combined with reanalysis products to retrieve net radiation in Amazonia
de Oliveira, G
Dos Santos, TV
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
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.
Gabriel de Oliveira acknowledges the Brazilian Ministry of Science and Technology and Brazilian Ministry of Education for providing research fellowships through the CNPq (Grant No. 52521/2012-7) and CAPES (Grant No. 8210/2014-4) agencies, respectively. Luiz E. O. C. Aragão acknowledges the support of FAPESP (Grant No. 50533-5) and CNPq (Grant No. 304425/2013-3) agencies.
This is the final version of the article. Available from the publisher via the DOI in this record.
2016, 16, 956; doi:10.3390/s16070956
PubMed Central ID
Place of publication