A practical atmospheric correction algorithm, called Coupled Moderate Products for Atmospheric Correction (CMPAC), was developed and implemented for the Multispectral Camera (MUX) on-board the China-Brazil Earth Resources Satellite (CBERS-4). This algorithm uses a scene-based processing and sliding window technique to derive MUX surface reflectance (SR) at continental scale. Unlike other optical sensors, MUX instrument imposes constraints for atmospheric correction due to the absence of spectral bands for aerosol estimation from imagery itself. To overcome this limitation, the proposed algorithm performs a further processing of atmospheric products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors as input parameters for radiative transfer calculations. The success of CMPAC algorithm was fully assessed and confirmed by comparison of MUX SR data with the Landsat-8 OLI Level-2 and Aerosol Robotic Network (AERONET)-derived SR products. The spectral adjustment was performed to compensate for the differences of relative spectral response between MUX and OLI sensors. The results show that MUX SR values are fairly similar to operational Landsat-8 SR products (mean difference < 0.0062, expressed in reflectance). There is a slight underestimation of MUX SR compared to OLI product (except the NIR band), but the error metrics are typically low and scattered points are around the line 1:1. These results suggest the potential of combining these datasets (MUX and OLI) for quantitative studies. Further, the robust agreement of MUX and AERONET-derived SR values emphasizes the quality of moderate atmospheric products as input parameters in this application, with root-mean-square deviation lower than 0.0047. These findings confirm that (i) CMPAC is a suitable tool for estimating surface reflectance of CBERS MUX data, and (ii) ancillary products support the application of atmospheric correction by filling the gap of atmospheric information. The uncertainties of atmospheric products, negligence of the bidirectional effects, and two aerosol models were also identified as a limitation. Finally, this study presents a framework basis for atmospheric correction of CBERS-4 MUX images. The utility of CBERS data comes from its use, and this new product enables the quantitative remote sensing for land monitoring and environmental assessment at 20 m spatial resolution.

The Amazon Forest is a hotspot of biodiversity harboring an unknown number of undescribed taxa. Inventory studies are urgent, mainly in the areas most endangered by human activities such as extensive dam construction, where species could be in risk of extinction before being described and named. In 2015, intensive studies performed in a few locations in the Brazilian Amazon rainforest revealed three new species of the genus Scleroderma: S. anomalosporum, S. camassuense and S. duckei. The two first species were located in one of the many areas flooded by construction of hydroelectric dams throughout the Amazon; and the third in the Reserva Florestal Adolpho Ducke, a protected reverse by the INPA. The species were identified through morphology and molecular analyses of barcoding sequences (Internal Transcribed Spacer nrDNA). Scleroderma anomalosporum is characterized mainly by the smooth spores under LM in mature basidiomata (under SEM with small, unevenly distributed granules, a characteristic not observed in other species of the genus), the large size of the basidiomata, up to 120 mm diameter, and the stelliform dehiscence; S. camassuense mainly by the irregular to stellate dehiscence, the subreticulated spores and the bright sulfur-yellow colour, and Scleroderma duckei mainly by the verrucose exoperidium, stelliform dehiscence, and verrucose spores. Description, illustration and affinities with other species of the genus are provided.

The remote handling (RH) plays an important role in nuclear test facilities, such as in ITER, for in-vessel and ex-vessel maintenance operations. Unexpected situations may occur when RH devices fail. Since no human being is allowed during the RH operations, a Multi-purpose Rescue Vehicle (MPRV) must be required for providing support in site. This paper proposes a design of a MPRV, i.e., a mobile platform equipped with different sensors and two manipulators with different sets of end-effectors. A human–machine interface is also proposed to remotely operate the MPRV and to carry out rescue and recovery operations.

Brazil is a large and diverse country and almost all remote sensing application fields can be developed there: oceanographic, agricultural, environmental, urban, etc. Some applications are instrumental for environmental governance, some are very useful for business and others are devoted to research. As part of its remote sensing development, Brazil counts on the CBERS (China-Brazil Earth Resources Satellite) Program. Applications and accomplishments of the CBERS Program are presented in this article.

Este artigo considerou a hipótese de que o erro altimétrico do MDT obtido com LiDAR é compatível com a tolerância de 0,50 m em uma área florestal com relevo ondulado. O objetivo foi validar o MDT utilizando dados de campo como referência. A área de estudo é uma plantação de eucalipto para produção de celulose, localizada em Igaratá, São Paulo. O levantamento de campo teve como finalidade principal a obtenção de dados de referência para a validação do MDT, em quatro situações distintas: i) plana e sem cobertura florestal; ii) plana e com cobertura florestal; iii) com declividade e sem cobertura florestal e, iv) com declividade e com cobertura florestal. A Os erros posicionais obtidos foram 0,12 m nas coordenadas XY e 0,21 m na coordenada Y, satisfatórios para a validação desejada. Por meio de um levantamento aéreo foi obtida uma nuvem de pontos tridimensionais, os quais foram filtrados e classificados como terreno. Após isto, os pontos foram reamostrados em uma grade regular, utilizando interpolação linear. A validação foi realizada com perfis longitudinais, utilizando o RMSE (Root Mean Square Error) como uma medida estatística do erro. Na situação mais complexa (declividade e cobertura florestal), o RMSE foi 0,50 m. Isto é explicado pelos detalhes presentes no micro-relevo, como buracos, valas, galhos, troncos etc. A hipótese inicial foi aceita, ou seja, o MDT obtido com dados LiDAR apresenta erro altimétrico aceitável para produção cartográfica utilizada no planejamento florestal.

Os meios mais utilizados para obter dados dendrométricos são os inventários e levantamentos de campo, mas desde 1993, sensores ópticos ativos, conhecidos como laserscanners, começaram a ser utilizados especificamente no meio florestal. A proposta deste artigo é que a utilização das abordagens de máximos locais e crescimento por regiões viabilizará as estimativas de parâmetros dendrométricos com dados obtidos via laserscanner aerotransportado compatíveis com o inventário florestal tradicional. Os objetivos estabelecidos foram detectar os pontos referentes aos topos das árvores através de máximos locais, modelar a área de copa a partir de crescimento de regiões e validar estas estimativas em relação à referência de campo, para três parâmetros: quantidade de árvores, altura total e área de copa, com RMSE máximo aceitável de 10%. A área de estudo é localizada no município de Igaratá/SP e possui 145,46ha de plantio de eucaliptos com 4 anos de idade. Foi utilizado o Optech ALTM 2050, com footprint de 0,25m, adquiridos através de um levantamento aéreo. Considerando todas as parcelas medidas em campo, obteve-se um percentual de acerto de 96,35% (RMSE de 6,35%) para quantidade de árvores; 97,50% (RMSE de 6,50%) para altura total e; 83,53% (RMSE de 24,79%) para área de copa. A partir da análise dos dados foi possível verificar que as estimativas apresentaram erros aceitáveis para a quantidade de árvores e altura total, porém apresentou superestimativa da área de copa, com erro acima do limite tolerável.

Background Interventions to improve blood pressure (BP) control in hypertension have had limited success in clinical practise despite evidence of cardiovascular disease prevention in randomised controlled trials. Purpose To evaluate BP control and patterns of antihypertensive pharmacotherapy in a population in the Central Region of Portugal, attending a hospital outpatient clinic for routine follow-up. Materials and Methods Medical data of adult (age range, 18 to 85 years) hypertensive patients attending the hypertension clinic of Hospital Centre of Cova da Beira, Covilhã, Portugal, from March to August 2012, were prospectively obtained from medical records and analysed. Demographic variables, clinical data and BP values of hypertensive patients included in the study, as well as prescribing metrics, were examined on a descriptive basis and expressed as the mean±SD, frequency and percentages. Student’s test and Mann-Whitney rank sum test were used to compare continuous variables and the χ2 test and Fisher exact probability test were used to test for differences between variables in different categories. Results In all, 47% of hypertensive patients (n = 44) had their BP controlled according to international guidelines. About 54% of patients with a target BP < 140/90 mmHg (n = 74) were controlled, whereas in patients with diabetes and/or chronic kidney disease (n = 20) the corresponding figure was only 20% (P = 0.007). The angiotensin II-receptor antagonists were the most prescribed drugs (57.5%), followed by calcium channel blockers (55.3%) and β-blockers (42.5%). About 82.4% hypertensive patients with comorbid diabetes were treated with an angiotensin-converting enzyme inhibitor or an angiotensin II-receptor antagonist. Conclusions Many hypertensive patients prescribed antihypertensive treatment fail to achieve BP control in clinical practise; this control being worse among patients with diabetes or chronic kidney disease. As prescribing patterns seem to conform to international guidelines, further research is needed to identify the causes of poor BP control. No conflict of interest.

We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation ( INPE ‐ EM ). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 Pg C yr −1 . (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years , from 27 Mkm 2 in 2004 to 7 Mkm 2 in 2010. INPE ‐ EM process‐based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non‐process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 Pg C yr −1 in 2009; the non‐process model estimates a decrease from 0.33 to 0.10 Pg C yr −1 . We conclude that the INPE ‐ EM is a powerful tool for representing deforestation‐driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD +. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

The work investigated the localization of an avian industry and optimized its net, from the corporatives to the consumers, determining the amount of slaughterhouses and distribution centers that the concern should possess and their localization in order to minimize costs. From the collection of real data and by utilizing tools of Geographic Information Systems and binary linear programming, the optimum setting for the net as well the setting of several alternative scenarios were determined. The objective function utilized minimizes the sum of the costs of the slaughterhouse localization, the costs of the localization of the distribution center, the production costs and shipment of the living chickens from the corporatives to the slaughterhouse, the costs of slaughter and shipment as far as the distribution center and the storage costs in the distribution center and shipment to the end clients. The optimum scenario obtained takes into account only the establishment of a slaughterhouse and a distribution center of increased capacity, standing out scale gains. The results support the localization of slaughterhouses close to the coporatives and distribution centers close to the clients submitted to the several restrictions imposed by the local reality.

Forest fragmentation due to deforestation is one of the major causes of forest degradation in the Amazon. Biomass collapse near forest edges, especially within 100 m, alters aboveground biomass and has potentially important implications for carbon emissions in the region. This phenomenon is tightly linked to spatial and temporal dynamics of forest edges in a landscape. However, the potential biomass loss and carbon emissions from forest edges and these spatiotemporal changes have never been estimated for actual landscapes in the Amazon. We conducted a deep temporal analysis of Rondônia, southwestern Brazilian Amazonia, using six Landsat path‐row scenes covering the 1985–2008 time period to estimate annual biomass loss and associated carbon emissions within 100 m of forest edges. Annual edge biomass loss averaged 9.1% of the biomass loss from deforestation during the study period, whereas average annual edge‐related carbon emissions from biomass loss were 6.0% of deforestation‐derived carbon emissions. However, because many edges were subsequently deforested during the 24 year study period, actual unaccounted for edge‐related carbon emissions during the 1985–2008 period, calculated from edges of all ages extant on the landscape in 2008, amounted to 3.6% of that attributed to all deforestation‐derived carbon fluxes for this time interval. Biomass loss and carbon emissions are highly influenced by the extent and age of edge‐affected forests. Large annual contributions of biomass loss and carbon emissions were found from active deforestation regions with young edges, whereas regions dominated by older edges had lower biomass loss and carbon emissions from edges.

Forest edges in the Amazon are very dynamic with ongoing deforestation adding new edges as older edges are eroded. Rates of edge erosion and the composition of edge ages, together with distance from edges, are very important factors in determining the magnitude of forest degradation such as biomass collapse and carbon flux. However, we lack an understanding of how these factors change through time and over the different stages of deforestation. In this study, we quantify the spatial and temporal structures of forest edge in Rondonia, southwestern Amazon, by analyses of 22 years of annual satellite imagery, and discuss the implications for biomass dynamics and forest degradation caused by edges. Our results from three different stages of deforestation (early, intermediate and advanced) reveal that more than 50% of forest edges were eliminated in the first four years after edge creation and only 20% of edges survived more than 10 years. High edge erosion rates in the first year imply that many edges disappear before going through the process of edge-induced biomass collapse. At the early stage of deforestation, young forest edges are predominant, while at the advanced deforestation stage more than 50% of total edges are >10 years old. Rapid erosion is more prevalent in early stages, when young forest edges dominate the landscape. Edge-related biomass collapse is substantially more advanced in heavily deforested regions where forests are mostly surrounded mostly by older edges, but relatively few edges remain at this point. (C) 2009 Elsevier B.V. All rights reserved.

Northeast of Brazil is a semi-arid region, where water is a key strategic resource in the development of all sectors of the economy. Irrigation agriculture is the main water consumer in this region. Therefore, policy directives are calling for tools to aid operational monitoring in planning, control and charging of irrigation water. Using Landsat imagery, this study evaluates the utility of a process that measures the level of water use in an irrigated area of the state of Ceará. The experiment, which models evapotranspiration (ET), was carried out within the Jaguaribe-Apodi irrigation scheme (DIJA) during two months of the agricultural season. The ET was estimated with the model Mapping Evapotranspiration at High Resolution and with Internalized Calibration (METRIC). The model uses the residual of the energy balance equation to estimate ET for each pixel in the image. The results of the estimates were validated using measurements of ET from a micrometeorological tower installed within a banana plantation located near the irrigation scheme. After evaluating the ET estimates, the average fraction of depleted water for a set of agricultural parcels combined with the monthly ET mapping estimates by METRIC provided a method for predicting the total water use in DIJA for the study period. The results were then compared against the monthly accumulated flow rates for all the pumping stations provided by the district manager. Finally, this work discusses the potential use of the model as an alternative method to calculate water consumption in irrigated agriculture and the implications for water resource management in irrigated perimeters.

Optical imagery can reveal spectral properties of forest canopy, which rarely allows for finding accurate correspondence of canopy features with soils and hydrology. In Amazonia non-floodable swampy forests can not be easily distinguished from non-floodable terra-firme forests using just bidimensional spectral data. Accurate topographic data are required for the understanding of land surface processes at finer scales. Topographic detail has now become available with the Shuttle Radar Topographic Mission (SRTM) data. This new digital elevation model (DEM) shows the feature-rich relief of lowland rain forests, adding to the ability to map rain forest environments through many quantitative terrain descriptors. In this paper we report on the development of a new quantitative topographic algorithm, called HAND (Height Above the Nearest Drainage), based on SRTM-DEM data. We tested the HAND descriptor for a groundwater, topographic and vegetation dataset from central Amazonia. The application of the HAND descriptor in terrain classification revealed strong correlation between soil water conditions, like classes of water table depth, and topography. This correlation obeys the physical principle of soil draining potential, or relative vertical distance to drainage, which can be detected remotely through the topography of the vegetation canopy found in the SRTM-DEM data.

We used two hyperspectral sensors at two different scales to test their potential to estimate biophysical properties of grazed pastures in Rondonia in the Brazilian Amazon. Using a field spectrometer, ten remotely sensed measurements (i.e., two vegetation indices, four fractions of spectral mixture analysis, and four spectral absorption features) were generated for two grass species, Brachiaria brizantha and Brachiaria decumbens. These measures were compared to above ground biomass, live and senesced biomass, and grass canopy water content. The sample size was 69 samples for field grass biophysical data and grass canopy reflectance. Water absorption measures between 1 100 and 1250 nm had the highest correlations with above ground biomass, live biomass and canopy water content, while ligno-cellulose absorption measures between 2045 and 2218 nm were the best for estimating senesced biomass. These results suggest possible improvements on estimating grass measures using spectral absorption features derived from hyperspectral sensors. However, relationships were highly influenced by grass species architecture. B. decumbens, a more homogeneous, low growing species, had higher correlations between remotely sensed measures and biomass than B. brizantha, a more heterogeneous, vertically oriented species. The potential of using the Earth Observing-1 Hyperion data for pasture characterization was assessed and validated using field spectrometer and CCD camera data. Hyperion-derived NPV fraction provided better estimates of grass surface fraction compared to fractions generated from convolved ETM+/Landsat 7 data and minimized the problem of spectral ambiguity between NPV and Soil. The results suggest possible improvement of the quality of land-cover maps compared to maps made using multispectral sensors for the Amazon region. (C) 2007 Elsevier Inc. All rights reserved.

Este estudo teve por objetivo desenvolver uma metodologia para detectar a exploracao seletiva de madeira na Amazonia. Para alcancar este objetivo utilizou-se a tecnica de deteccao de mudancas baseada na rotacao radiometrica controlada por eixo de nao mudanca (RCEN) acoplada a um classificador tematico probabilistico. Esta tecnica tem como vantagem dispensar a necessidade de correcoes radiometricas previas para as imagens analisadas. Os resultados encontrados revelam que as areas de florestas afetadas pela extracao madeireira ultrapassaram a extensao das areas de florestas convertidas para fins agricolas na regiao de Claudia, Mato Grosso. O desempenho do mapeamento da atividade madeireira foi satisfatorio, apresentando um Kappa condicional de 0,72. Esforcos futuros para o aprimoramento de um sistema operacional automatizado utilizando esta tecnica serao envidados. Abstract The purpose of this study was to develop a methodology for detecting selective logging in the Amazon. To achieve this objective we used a change detection technique based on radiometric rotation controlled by the no-change axis (RCEN) coupled with a probabilistic thematic classifier. The advantage of this technique that is dispenses with radiometric corrections prior to the images analysis. The results show that Claudia, in the state of Mato Grosso . The performance of the method of mapping for logging activity was satisfactory, with a conditional Kappa value of 0.72. Future efforts to develop a system for automated operational detection using this technique will be undertaken.

Abstract

This research seeks the definition and thematic mapping of landscape units and its potential for ecotourism. The area of study includes regions of the municipal districts of Capitolio, Sao Joao Batista do Gloria and Sao Jose de Barra, in the region of medium Rio Grande, in Minas Gerais, Brazil, an area of immense potential for ecotourism. The work was based on the adaptation of the Ecological-Economical Zoning methodology by INPE and the “land units” concept, using remote sensing and geoprocessing techniques. The result of the work is a geographical database that allows consultations not only of the attractions, but also of the environment, through the concept of land unit. The information on the environmental and cultural aspects of the inventoried area were mapped, as a function of the access roads to the natural and/or cultural attractions, using the pictograms suggested by EMBRATUR, the official tourism organization in Brazil. These products can help managers of tourism in their decisions about ecotourism circuits and interpretative trails. Key words: Nature-based tourism. Land unit. Remote sensing. GIS.

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300 Mg ha(-1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300 Mg ha(-1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200 Mg ha(-1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and belowground biomass, is 86 Pg C with +/- 20% uncertainty.

The water balance and growth of Eucalyptus grandis hybrid plantations in Brazil are presented based on 6 years of intensive catchment hydrology, physiological and forest growth surveying, and modelling. The results show a balance between water supply by precipitation and output through evapotranspiration (considered as canopy interception, soil evaporation and trees transpiration) and runoff. The annual average precipitation was 1147mm and average evapotranspiration was 1092mm. The runoff was only 3% of the precipitation, because of high soil infiltration and the flat topography where the trees are planted. Evapotranspiration rates varied from 781mm to 1334mm during the years of the study and are strongly influenced by variations in annual precipitation and leaf area index. When the precipitation was close to the regional mean annual precipitation of 1350mm there was enough water to supply the demands of the trees and produce some runoff. Biomass production was high and the peak annual growth rate was 95m3ha−1year−1. The UAPE model [Soares, J.V., Almeida, A.C., 2001. Modeling the water balance and soil water fluxes in a fast-growing Eucalyptus plantation in Brazil. J. Hydrol. 253, 130–147] was used to estimate the water balance and the widely used 3-PG model [Landsberg, J.J., Waring, R.H., 1997. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. For. Ecol. Manage. 95, 209–228] was used to estimate forest growth and water-use efficiency.