Monitoramento e detecção de desmatamento no bioma Cerrado matogrossense utilizando imagens de multisensores.

In the last decades, Brazil has become a global agricultural power and the Cerrado biome (Brazilian savanna) has been playing an important role in the Brazilian agriculture growth. To better analyze the biome human disturbance dynamics, it is necessary to develop and adopt effective methods of assessment and monitoring of land use and land cover changes. The goal is to provide adequate land cover classifications and implement an operational monitoring system in the Cerrado biome, since there is only a few attempts to control the degradation of this biome. This monitoring system can be accomplished using MODIS images, as this sensor has great potential for studies about the seasonal dynamics of Cerrado vegetation phytophysiognomies. Due to this new dynamics, the main objective of this work was to apply the PRODES and DETER like methodologies to detect and map deforestation in the Cerrado biome of Mato Grosso State, Brazil, using Landsat and MODIS data. The proposed methodology was able to detect correctly 65% of all MODIS detected polygons; this represented 74% of estimated area of deforestation. Also, it showed suitability to identify new deforested areas in both shrubland and forestland areas with a tendency to misclassify smaller polygons (< 50 ha) of deforestation

Use of MODIS sensor images combined with reanalysis products to retrieve net radiation in Amazonia

This is the final version of the article. Available from the publisher via the DOI in this record.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

Caracterização das unidades da paisagem em ambiente de floresta tropical por meio de imagens-fração MESMA.

O objetivo deste trabalho foi discriminar classes de uso e cobertura da terra por meio de imagens-fração derivadas do modelo múltiplo de mistura espectral (multiple endmember spectral mixture analysis - MESMA), considerando as diferentes formações florestais e sistemas agropecuários na FLONA Tapajós e seu entorno, com vistas à caracterização dos principais padrões da paisagem na região

Alterações antropogênicas nos remanescentes de vegetação natural (RVN) de savana do estado de São Paulo no ano de 2009.

Deforestation in São Paulo State was mainly driven by sugarcane and coffee crops during the XVIII and XIX centuries which caused a significant fragmentation in native forests. More recently, between the 1970?s and 1980?s decades the native forest fragmentation process was intensified and also the savannah area was drastically reduced due to sugarcane expansion for ethanol production. Much native vegetation was deteriorated and fragmented into smaller disconnected portions during this period. This work was performed within the scope of a technical cooperative agreement between the Environmental Secretary of São Paulo State (SMA) and the National Institute for Space Research (INPE). It consisted in monitoring monthly the land cover changes of 7,000 polygons of remanescent native vegetation (RVN) in the São Paulo State. The environmental assessment of the vegetation cover status was performed based on mesoregions for better discussion of the geographical distribution of the deforested RVN's from May to December 2009. The results showed that Bauru and Ribeirão Preto mesoregions presented the highest land cover changes with 19.4 and 12.1 km², respectively

Índice de vegetação na detecção de áreas recém-queimadas no Pantanal utilizando imagens CBERS.

Dentre os indicadores de sustentabilidade das fazendas pantaneiras, destaca-se o grau de intensidade de queimadas das paisagens, portanto, há a necessidade de um método prático para quantificar especialmente a intensidade da queima

Uso de um modelo linear de mistura espectral e índice de vegetação na avaliação de pastagens em degradação no Pantanal.

Este estudo teve por objetivo avaliar áreas de campos degradados por malva-branca por meio de imagens criadas a partir do modelo linear de mistura espectral e índice de vegetação de diferença normalizada utilizando imagens LANDSAT, em período de seca no Pantanal

Effects of monoclonal anti-PcrV antibody on Pseudomonas aeruginosa-induced acute lung injury in a rat model

BACKGROUND: The effects of the murine monoclonal anti-PcrV antibody Mab166 on acute lung injury induced by Pseudomonas aeruginosa were analyzed in a rat model. METHODS: Lung injury was induced by the instillation of P. aeruginosa strain PA103 directly into the left lungs of anesthetized rats. One hour after the bacterial instillation, rabbit polyclonal anti-PcrV IgG, murine monoclonal anti-PcrV IgG Mab166 or Mab166 Fab-fragments were administered intratracheally directly into the lungs. The degree of alveolar epithelial injury, amount of lung edema, decrease in oxygenation and extent of lung inflammation by histology were evaluated as independent parameters of acute lung injury. RESULTS: These parameters improved in rats that had received intratracheal instillation of either rabbit polyclonal anti-PcrV IgG, murine monoclonal anti-PcrV IgG Mab166 or Mab166 Fab-fragments in comparison with the control group. CONCLUSION: Mab166 and its Fab fragments have potential as adjuvant therapy for acute lung injury due to P. aeruginosa pneumonia

Effects of land‐cover changes on the partitioning of surface energy and water fluxes in Amazonia using high‐resolution satellite imagery

Spatial variability of surface energy and water fluxes at local scales is strongly controlled by soil and micrometeorological conditions. Thus, the accurate estimation of these fluxes from space at high spatial resolution has the potential to improve prediction of the impact of land‐use changes on the local environment. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) data were used to examine the partitioning of surface energy and water fluxes over different land‐cover types in one wet year (2004) and one drought year (2005) in eastern Rondonia state, Brazil. The spatial variation of albedo, net radiation (Rn), soil (G) and sensible (H) heat fluxes, evapotranspiration (ET), and evaporative fraction (EF) were primarily related to the lower presence of forest (primary [PF] or secondary [SF]) in the western side of the Ji‐Parana River in comparison with the eastern side, located within the Jaru Biological Reserve protected area. Water limitation in this part of Amazonia tends to affect anthropic (pasture [PA] and agriculture [AG]) ecosystems more than the natural land covers (PF and SF). We found statistically significant differences on the surface fluxes prior to and ~1 year after the deforestation. Rn over forested areas is ~10% greater in comparison with PA and AG. Deforestation and consequent transition to PA or AG increased the total energy (~200–400%) used to heat the soil subsurface and raise air temperatures. These differences in energy partitioning contributed to approximately three times higher ET over forested areas in comparison with nonforested areas. The conversion of PF to AG is likely to have a higher impact in the local climate in this part of Amazonia when compared with the change to PA and SF, respectively. These results illustrate the importance of conserving secondary forest areas in Amazonia.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/1/eco2126_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151879/2/eco2126.pd

A novel approach to improve GNSS Precise Point Positioning during strong ionospheric scintillation: theory and demonstration

At equatorial latitudes, ionospheric scintillation is the major limitation in achieving high-accuracy GNSS positioning. This is because scintillation affects the tracking ability of GNSS receivers causing losses of lock and degradation on code pseudorange and carrier phase measurements, thus degrading accuracy. During strong ionospheric scintillation, such effects are more severe and GNSS users cannot rely on the integrity, reliability, and availability required for safety-critical applications. In this paper, we propose a novel approach able to greatly reduce these effects of scintillation on precise point positioning (PPP). Our new approach consists of three steps: 1) a new functional model that corrects the effects of range errors in the observables; 2) a new stochastic model that uses these corrections to generate more accurate positioning; and 3) a new strategy to attenuate the effects of losses of lock and consequent ambiguities re-initializations that are caused by the need to re-initialize the tracking. We demonstrate the effectiveness of our method in an experiment using a 30-day static dataset affected by different levels of scintillation in the Brazilian southeastern region. Even with limitations imposed by data gaps, our results demonstrate improvements of up to 80% in the positioning accuracy. We show that, in the best cases, our method can completely negate the effects of ionospheric scintillation and can recover the original PPP accuracy that would have existed without any scintillation. The significance of this paper lies in the improvement it offers in the integrity, reliability, and availability of GNSS services and applications.</p