Fabrício Brito Silva

Large-scale heterogeneity of Amazonian phenology revealed from 26-year long AVHRR/NDVI time-series

Depiction of phenological cycles in tropical forests is critical for an understanding of seasonal patterns in carbon and water fluxes as well as the responses of vegetation to climate variations. However, the detection of clear spatially explicit phenological patterns across Amazonia has proven difficult using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this work, we propose an alternative approach based on a 26-year time-series of the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) to identify regions with homogeneous phenological cycles in Amazonia. Specifically, we aim to use a pattern recognition technique, based on temporal signal processing concepts, to map Amazonian phenoregions and to compare the identified patterns with field-derived information. Our automated method recognized 26 phenoregions with unique intra-annual seasonality. This result highlights the fact that known vegetation types in Amazonia are not only structurally different but also phenologically distinct. Flushing of new leaves observed in the field is, in most cases, associated to a continuous increase in NDVI. The peak in leaf production is normally observed from the beginning to the middle of the wet season in 66% of the field sites analyzed. The phenoregion map presented in this work gives a new perspective on the dynamics of Amazonian canopies. It is clear that the phenology across Amazonia is more variable than previously detected using remote sensing data. An understanding of the implications of this spatial heterogeneity on the seasonality of Amazonian forest processes is a crucial step towards accurately quantifying the role of tropical forests within global biogeochemical cycles.

Using Remote Sensing Products for Environmental Analysis in South America

Land cover plays a major role in many biogeochemical models that represent processes and connections with terrestrial systems; hence, it is a key component for public decisions in ecosystems management. The advance of remote sensing technology, combined with the emergence of new operational products, offers alternatives to improve the accuracy of environmental monitoring and analysis. This work uses the GLOBCOVER, the Vegetation Continuous Field (VCF), MODIS Fire Radiative Power (FRP) and the Tropical Rainfall Measuring Mission (TRMM) remotely sensed databases to analyze the biomass burning distribution, the land use and land cover characteristics and the percent of tree cover in South America during the years 2000 to 2005. Initially, GLOBCOVER was assessed based on VCF product, and subsequently used for quantitative analysis of the spatial distribution of the South America fires with the fire radiative power (FRP). The results show that GLOBCOVER has a tendency to overestimate forest classes and to underestimate urban and mangroves areas. The fire quantification based on GLOBCOVER product shows that the highest incidence of fires can be observed in the arc of deforestation, located in the Amazon forest border, with vegetation cover composed mainly of broadleaved evergreen or semi-deciduous forest. A time series analysis of FRP database indicates that biomass burning occurs mainly in areas of broadleaved evergreen or semi-deciduous forest and in Brazilian Cerrado associated with grassland management, agricultural land clearing and with the deforestation of Amazon tropical rainforest. Also, variations in FRP intensity and spread can be attributed to rainfall anomalies, such as in 2004, when South America had a positive anomaly rainfall.

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.

Evidências de Mudanças Climáticas na Região de Transição Amazônia-Cerrado no Estado do Maranhão

The Amazon-Savanna transition zone is characterized by high diversity of ecosystems, biodiversity and climatic conditions. This work aims to investigate evidences of climate change on precipitation and temperature in the Maranhao state. The climatological normal data from 1977 to 2014 provided from 12 meteorological stations of National Meteorological Institute distributed in state area was used to build the climatic time series. This dataset was divided in two groups according to climate stations, dry and rain seasons. The Mann-Kendall test was applied to detect increase and decrease trends regarding complete time series and both, dry and rain season series. The results show a strong climate change in air temperature. In the amazon biome, Bacabal and Ze Doca stations registered increase and decrease tendencies, respectively. In the savanna biome, in Carolina and Colinas stations presented increase and decrease tendencies, respectively. The results presented in this work shows that climate change occurred differently in Maranhao state, not influenced necessarily by biome.

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).

Influência das Mudanças de Tempo e Variabilidade Climática sobre a Produção de Energia Fotovoltaica no Estado do Maranhão (Climate Risk for Photovoltaic Energy Production in the state of Maranhão)

O objetivo deste estudo foi desenvolver uma metodologia para utilizacao de dados provenientes de sensoriamento remoto para o planejamento de projetos de energia fotovoltaica no Maranhao. Foram utilizados dados de radiacao obtidos na base global GLDAS e precipitacao proveniente do satelite TRMM, no periodo de 2001 a 2014. Os dados de radiacao foram processados atraves da tecnica de analise de series temporais (ACP). O potencial de producao de energia fotovoltaica foi simulado considerando um sistema de 20 modulos fotovoltaicos, cada um com potencial nominal de 45Wp. Uma analise de regressao linear foi realizada para avaliar a correlacao entre radiacao e precipitacao. Por ultimo, o teste de Mann Kendall foi executado para avaliar as tendencias nos dados de radiacao e precipitacao. Atraves da ACP foram identificadas duas Zonas homogeneas em relacao a radiacao, uma menor na regiao do Oeste (bioma amazonico) e a maior na regiao Leste do Estado (bioma cerrado). A precipitacao respondeu por 21,3% na variacao anual da radiacao na regiao da Amazonia e 31,2% no Cerrado. A regiao de cerrado apresentou os maiores valores de radiacao solar, e os menores valores foram registrados na regiao da Amazonia. Pelo teste de Mann Kendall, houve uma tendencia linear de aumento na media mensal de radiacao solar incidente na regiao amazonica e cerrado, tanto no periodo seco quanto no chuvoso. As analises mostraram um cenario favoravel para producao de energia solar no Estado do Maranhao, com reduzido risco climatico devido a tendencia no aumento da radiacao. A B S T R A C T The objective of this study was to develop a methodology for use of data from remote sensing in planning photovoltaic energy projects in the Maranhao. Solar radiation data was obtained from global basis GLDAS and rainfall from the TRMM satellite, from 2001 to 2014. The radiation data were processed through the time series analysis technique (PCA). The photovoltaic power generation potential was simulated considering 20 photovoltaic module system, each one with a nominal power of 45Wp. A regression analysis was performed to evaluate the correlation between radiation and precipitation. Finally, the Mann Kendall’s test was performed to evaluate trends in radiation and precipitation data. By PCA were identified two homogeneous zones in relation to radiation, lower in the west (Amazon biome) and the largest east region of the state (Savanna biome). Rainfall represented 21.3% in the annual variation of radiation in the Amazon region and 31.2% in Savanna. The Savanna region showed the highest solar radiation values and the lowest values were recorded in the Amazon region. By Mann Kendall test, there was a positive linear trend of increase in the monthly average incident solar radiation in the Amazon region (Kendalls tau = 0.2173, p <0.0001) and in the Savanna region (Kendalls tau = 0.1651, p = 0.0011). Analyses showed a favorable scenario for the production of solar energy in the state of Maranhao, with a low climate risk due to the trend in increased radiation. Keywords: renewable energy, energy planning, climate change.

Spectral signature of leaves of amazon rainforest tree species

Remote sensing is based on the interaction of electromagnetic radiation with the portion of the electromagnetic radiation that interacts with Earth surface targets. Studies to analyze the spectrum of reflectance of surface targets by sensor systems could be done by terrestrial (laboratory and field), aerial and orbital acquisitions. Consequently, for vegetation studies through remote sensing observations is necessary to know the physiology of the plant studied and the reflectance spectrum, considering that the solar radiation reaches the earths surface and results in three fractions: one part is absorbed, another is reflected and a third part is transmitted. The leaves are the principal absorber of electromagnetic radiation in a canopy and represents the element that more contribute to the signal detected by orbital sensors. The present work has as its main goal the analysis of the spectral signature responses of common species of several forest functional types in a tropical forest area in the Amazon.

IMPACTOS DOS PARÂMETROS BIOFÍSICOS DA VEGETAÇÃO DERIVADOS DO SENSOR MODIS/TERRA NAS SIMULAÇÕES DO BALANÇO DE ENERGIA EM ÁREA DE CAATINGA

Considerando a complexa variabilidade sazonal do bioma caatingano Nordeste do Brasil (NEB), torna-se importante, no contextode modelagem da interacao biosfera-atmosfera para o NEB, uma caracterizacaoaprimorada dos parâmetros biofisicos sazonais da vegetacao referentesa essa classe da vegetacao. Tais parâmetros afetam as interacoesentre a biosfera terrestre e a atmosfera. Posto isto, o objetivo principaldeste trabalho foi obter uma representacao mais realista dos parâmetrosIndice de Area Foliar e Fracao de Cobertura Vegetal para o bioma caatingapor meio de imagens do sensor MODIS/TERRA e avaliar o impactodesses parâmetros nas simulacoes do balanco de energia na superficie.