Elisabete Caria Moraes

Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest

The objective of this study was to analyze the spatial and temporal distribution of burned areas in Rondonia State, Brazil during the years 2000 to 2011 and evaluate the burned area maps. A Linear Spectral Mixture Model (LSMM) was applied to MODIS surface reflectance images to originate the burned areas maps, which were validated with TM/Landsat 5 and ETM+/Landsat 7 images and field data acquired in August 2013. The validation presented a correlation ranging from 67% to 96% with an average value of 86%. The lower correlation values are related to the distinct spatial resolutions of the MODIS and TM/ETM+ sensors because small burn scars are not detected in MODIS images and higher spatial correlations are related to the presence of large fires, which are better identified in MODIS, increasing the accuracy of the mapping methodology. In addition, the 12-year burned area maps of Rondonia indicate that fires, as a general pattern, occur in areas that have already been converted to some land use, such as vegetal extraction, large animal livestock areas or diversified permanent crops. Furthermore, during the analyzed period, land use conversion associated with climatic events significantly influenced the occurrence of fire in Rondonia and amplified its impacts.

Monitoring the transport of biomass burning emission in South America

Abstract The main objective of this work is to use Fire Radiative Power (FRP) to estimate particulate matter with diameter less than 2.5 μm (PM2.5) and carbon monoxide (CO) emissions for the South America 2002 burning season. Sixteen small–scale combustion experiments were performed near the Laboratory of Radiometry (LARAD) at the National Institute for Space Research (DSR/INPE) to obtain the coefficient that relates the biomass consumption with the FRP released. The fire products MOD14/MYD14 from the MODIS Terra/Aqua platforms and the Wildfire Automated Biomass Burning Algorithm (WFABBA) on the Geostationary Operational Environmental Satellite (GOES) were utilized to calculate the total amount of biomass burned. This inventory is modeled in the Coupled Chemistry–Aerosol–Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT–BRAMS) and compared with data collected in the Large Scale Biosphere–Atmosphere (LBA) Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI) Experiments. The relationship between the modeled PM2.5 and CO shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.05 level by student t–test), for the CCATT–BRAMS simulations with PM2.5 and CO. Furthermore, the slope analysis reveals an underestimation of emission values with CCATT–BRAMS modeled values, 20–30% lower than observed data with discrepancies mainly on days with large fires. However, the underestimation is similar to the uncertainties in traditional emissions methods.

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.

Amazonian Deforestation: Impact of Global Warming on the Energy Balance and Climate

AbstractA coupled biosphere–atmosphere statistical–dynamical model is used to study the relative roles of the impact of the land change caused by tropical deforestation and global warming on energy balance and climate. Three experiments were made: 1) deforestation, 2) deforestation + 2 × CO2, and 3) deforestation + CO2, CH4, N2O, and O3 for 2100. In experiment 1, the climatic impact of the Amazonian deforestation is studied. In experiment 2, the effect of doubling CO2 is included. In experiment 3, the concentrations of the greenhouse gases (GHGs) correspond to the A1FI scenario from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios. The results showed that the percentage of the warming caused by deforestation relative to the warming when the increase in GHG concentrations is included is higher than 60% in the tropical region. On the other hand, with the increase in GHG concentrations, a reduction in the decrease of evapotranspiration and precipitation in the tropical regi...

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.

Conversão de dados radiométricos orbitais por diferentes metodologias de caracterização atmosférica

The conversion of digital numbers (DN) from orbital images to physical quantities of the Earth surface is dependent on trusted atmospheric characterization, which has been performed through the application of data collected from meteorological balloons or by solar photometers positioned at the Earth surface. Recently some orbital sensors have generated useful data that could be utilized in this characterization like those generated by sensor MODIS. Here, surface Bidirectional Reflectance Factors (BRF) estimated from field data were compared to those calculated from TM/Landsat-5 converted images through radiative transfer codes. The input data of these codes were estimated considering two different sources: the solar photometer and the MODIS sensor. The results have indicated that the MODIS data can be applied in the DN to surface BRF conversion.

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.

Validation of MODIS MCD45A1 product to identify burned areas in Acre State - Amazon forest

Burned areas map is essential in many applications and the orbital sensors have been used to monitor fires for many years, providing a better understanding of processes at different scales and being the only practical technique to estimate fires in large areas. However, remote sensing methods have limitations that could cause errors in the final products. Therefore, the objective of this work is to evaluate the MCD45A1 burned area product derived from MODIS sensor in Amazon tropical forest by comparing this dataset with the reference data derived from the mapping of burned areas in Acre State/Brazil acquired by TM sensor aboard of Landsat 5 and with a fieldwork that took place in November 2011. The results showed that de MCD45A1 product presented 93% of omission errors in 2010 and 96% in 2011 year in relation to reference data, presenting a low confidence in identifying the burned areas in Amazon region.

Determinação e modelagem da taxa de consumo de biomassa queimada

The present study evaluates the use of fire radiative energy (FRE) to estimate the emissions of particulate matter with diameter less than 2.5 μm (PM2,5µm) from the multiplicative coefficient relating the biomass consumption with the released FRE. The MODIS (Moderate Resolution Imaging Spectroradiometer) and GOES (Geostationary Operational Environmental Satellite) products were utilized to calculate the total amount of aerosol emitted to the atmosphere. The CCATT-BRAMS (Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modelling System) model was used to estimate the PM2,5µm concentration generated by biomass burning. The model results were compared with data obtained from the LBA (Large Scale Biosphere-Atmosphere), SMOCC (Smoke, Aerosols, Clouds, rainfall, and Climate) and RaCCI (Radiation, Cloud, and Climate Interactions) field experiments. The estimated PM2,5µm emission has a correlation with the SMOCC/RaCCI data greater than 92%. It was also verified that the maximum daily consumption can exceed 5 Tg (5,000,000 ton.), with a daily average of 2.1 Tg. The resulting method from laboratory analysis estimated a total of 0.28 ± 0.01 Pg (1015 g) biomass consumed from July to November 2002 in South America.

O uso da energia radiativa do fogo para estimar as emissões de queimadas para a América do Sul

Every year large areas of the globe are submitted to the action of anthropogenic and natural fires. It is estimated that more than 100 million tons of aerosols from smoke are emitted into the atmosphere, which 80% occur in tropical regions of the globe. The process of biomass burning releases into the atmosphere trace gases and aerosol particles that affect significantly the air quality, the tropospheric and stratospheric chemistry, the radiation balance and the dynamics and microphysics of clouds. This study aims to use the fire radiative energy (FRE) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and GOES (Geostationary Operational Environmental Satellite) to estimate emissions of carbon monoxide (CO) and particulate matter with diameter less than 2.5 micrometer (PM2.5µm) for 2002 South America fires, and to model these emissions in CCATT-BRAMS (Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modeling System). With a correlation greater than 86% between the aerosol emission data (in kg.s -1) and the FRE (MJ.s -1), three coefficients for GOES satellite data were originated. The use of FRE and emission coefficients to estimate the PM2.5µm m and CO emitted in biomass burning showed a correlation of approximately 91 % between modeled data and the data used as ground truth obtained from LBA (Large Scale Biosphere-Atmosphere Experiment in Amazonia) SMOCC (Smoke, Aerosols, Clouds, rainfall, and Climate) and RaCCI (Radiation, Cloud, and Climate Interactions).