Gabriel de Oliveira

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia.

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.

Validação do balanço de radiação obtido a partir de dados MODIS/TERRA na Amazônia com medidas de superfície do LBA

This study aims to estimate the components of net radiation in two regions located in the state of Rondonia (southwest of the Brazilian Amazon), using Moderate Resolution Imaging Spectroradiometer (MODIS/TERRA) data based on Surface Energy Balance Algorithms for Land (SEBAL) model, and to validate the results with information acquired by the micrometeorological towers of LBA under the conditions of pasture (Fazenda Nossa Senhora Aparecida) and forest (Reserva Biologica do Jaru). Implementation of SEBAL model was performed directly on the MODIS data and included steps involving the computation of vegetation indices, albedo and atmospheric transmittance. Comparison between estimates from MODIS data and the observations showed relative errors for the condition of pasture between 0.2 and 19.2%, and for the condition of forest ranging between 0.8 and 15.6%. The integration of data at different scales was a useful proposition for the estimation and spatialization of the radiation fluxes in the Amazon region, which may contribute to a better understanding of the interaction between Amazon rainforest and atmosphere, and generate input information needed to the surface models coupled to atmospheric general circulation models.

Evaluation of MODIS-based estimates of water-use efficiency in Amazonia

ABSTRACT This study aimed to assess the spatial-temporal patterns of water-use efficiency (WUE) obtained through MODIS gross primary productivity (GPP) and evapotranspiration (ET) products (MOD17 for GPP and MOD16 for ET) in the Upper Tapajos and Curua-Una River basins, located in the oriental flank of the Amazon region, and to validate the results with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. The spatial variation of WUE was primarily related to the larger presence of forested areas in the Upper Tapajos River basin (western part) compared with the Curua-Una River basin (eastern part), which is situated within the so-called arc of deforestation. Temporally, WUE showed a pronounced seasonal pattern, varying with the dry and wet seasons in the region. A decrease of ~3% in WUE was observed during the dry season, which was related to the low water availability and increased vapour pressure deficit during the dry period, which induces stomatal closure, leading to a decline in the photosynthetic rate. Comparison between the WUE estimates obtained by MODIS data and observations from the LBA towers showed an average error of 17%, varying between ~12% and ~28% for the different sites. MODIS WUE depends on the accuracy of both GPP and ET estimation. In this sense, we highlight that improvements in both MODIS GPP and ET products are necessary and should focus on reducing the uncertainties related to the biophysical vegetation parameters and meteorological data that serve as input information in the algorithms.

Gross primary productivity in the northern region of Para state, Brazilian Amazon, from MOD17 data

This study aimed to characterize and analyze, based on MOD17 data, the spatio-temporal dynamics of GPP in the northern region of Para state, Brazilian Amazon, during a 6-year period (2001 to 2006). The study area encompasses two river basins (Upper Tapajos and Curua-Una) and covers ∼74,190 km2. The spatial variation of GPP was primarily related to the larger presence of forested areas in Upper Tapajos River basin in comparison with Curua-Una River basin. Temporally, GPP varied with the dry and wet seasons in the region. There was a decrease of ∼4% in GPP during the dry season, which was related to the fact that the water limitation during the dry season in Amazonia leads to a decrease in photosynthesis, affecting vegetation productivity. It was observed a reasonable interannual variation of GPP in the study area, which corresponded to ∼10%.

Use of MODIS products to assess the impacts of the 2012 drought on ET and GPP in a perennial agriculture system in Kansas

The objective of this study is to evaluate the impacts of the severe drought in the central US in 2012 on ET and GPP in a perennial wheatgrass crop in Kansas utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) products. The study period comprises three years (2012, 2013 and 2014). In the drought year (2012), the annual ET and GPP were ∼24% and ∼12% lower than the average for the wet years (2013 and 2014). The 2012 drought caused a higher impact on ET in comparison with GPP. Overall, the reductions on ET and GPP occurred as expected and are related to the fact that long periods with low precipitation can deplete soil moisture, inducing stomatal closure and leading to a decline in the photosynthesis rate.

Analysis of Precipitation and Evapotranspiration in Atlantic Rainforest Remnants in Southeastern Brazil from Remote Sensing Data

The Atlantic Rainforest has been intensely devastated since the beginning of the colonization of Brazil, mainly due to wood extraction and urban and rural settlement. Although the Atlantic Rainforest has been reduced and fragmented, its remnants are important sources of heat and water vapor to the atmosphere. The present study aimed to characterize and to analyze the temporal dynamics of precipitation and evapotrans‐ piration in the Atlantic Rainforest remnants in São Paulo state, southeastern Brazil, for the period from January 2000 to December 2010. To achieve this, global precipitation and evapotranspiration data from TRMM satellite and MOD16 algorithm as well as forest remnant maps produced by SOS Mata Atlântica Foundation and Brazilian National Institute for Space Research (INPE) were used. Results found in this study demonstrated that the use of remote sensing was an important tool for analyzing hydrological variables in Atlantic Rainforest remnants, which can contribute to better understand the interaction between tropical forests and the atmosphere, and for generating input data necessary for surface models coupled to atmospheric general circulation models.

Classificação Digital do Uso e Cobertura da Terra na Amazônia com Base em Dados Orbitais ASTER (Digital Classification of Land Use and Land Cover in Amazonia Based on ASTER Orbital Data)

current and historical information about a large environment and of difficult access. Studies and projects have been developed to map land use and land cover in the region, using different methods and orbital sensors. The aim of this study was to analyse the temporal dynamics of land use and land cover for an area located in the central-eastern part of Rondônia state, using ASTER/Terra images and supervisioned digital classification using Bhattacharya algorithm. For that, two ASTER images of the days 07/29/2002 and 08/01/2003 referring to the product of surface reflectance (AST07XT) were used. The classification was processed in the software SPRING 5.0.6 and involved steps of image segmentation and collection of test and training samples. The results showed intense degradation due to deforestation in the region. It was verified that in the study area primary rainforest and pasture land represent 9% and 70%, respectively. Moreover, during the study period, there was suppression of 501.0 ha (≈6%) of the primary rainforest areas. The ASTER images have potential for land use and land cover studies in the Amazon region due especially to its finer minimum spatial resolution (15 m) than those sensors commonly used in the region.