MODELO LINEAR DE MISTURA ESPECTRAL EM IMAGEM DE MODERADA RESOLUÇÃO ESPACIAL

The concept of spectral mixture offers a wide range of applications in theRemote Sensing area. The application of this concept, however, requires theprior estimation of the component’s (endmembers) spectral response. Thislatter requirement can be achieved by different methods, as reported in theliterature, such as techniques for the detection of pure pixels, use of spectrallibraries, and field radiometric measurements. Among those, the most oftenused is the pure pixel approach. In this approach, the components’ spectralreflectances are estimated by means of pixels covered entirely by a singlecomponent. This approach offers the advantage of allowing the extraction ofthe required spectral reflectance directly from the image data. This approach,however, becomes increasingly unfeasible as the spatial resolution of theimage data decreases, due to the larger ground area covered by a single pixel.In this study we propose a methodology to estimate the spectral reflectance foreach component class in moderate spatial resolution image data, by applyingthe linear mixing model (MLME), and higher spatial resolution image data asauxiliary data. It is expected that this methodology will provide a morepractical way to implement the spectral mixture approach to moderateresolution image data, allowing in this way the expansion of the informationabout the components’ proportions across larger areas, up-scaling informationin regional and global studies. Experiments were carried out using CCD (20m ground resolution) and IRMSS (80 m ground resolution) and WFI (260 mground resolution) CBERS-2 image data, as medium and moderate spatialresolution data, respectively. The spectral reflectances for the components inthe IRMSS and WFI CBERS-2 spectral bands are estimated by applying theproposed methodology. The reliability of the proposed methodology wasassessed by both analyzing scatter plots for CBERS-2 data and by comparingthe fraction images produced by image data sets of the sensors analyzed.O conceito de mistura espectral apresenta várias aplicações na área desensoriamento remoto. Esta abordagem requer, entretanto, o conhecimento apriori da resposta espectral dos membros de referência. Existem, na literatura,diferentes propostas para estimar esta resposta, como por exemplo, o uso depixels puros, o uso de bibliotecas espectrais e a realização de medidasradiométricas de campo. Na prática, a abordagem via pixel puro tem sido amais comumente empregada, por utilizar dados disponíveis na própriaimagem. Esta abordagem vai, entretanto tornando-se gradativamenteimpraticável, na medida em que a resolução espacial dos dados decresce,devido às dimensões da área coberta no terreno por cada pixel. Como soluçãoa este problema, é proposta neste estudo uma metodologia para fins deestimação de refletâncias espectrais em dados de imagens de moderadaresolução espacial, empregando o modelo linear de mistura espectral (MLME)e dados de imagens de resolução espacial média, na qualidade de dadosauxiliares. Objetiva-se desta forma facilitar a utilização das técnicas demistura espectral em estudos regionais, nos quais imagens de moderadaresolução espacial são freqüentemente as mais adequadas. A metodologia proposta foi testada utilizando-se dados dos sensores CCD (20 m) e IRMSS(80 m) e WFI (260 m) a bordo da plataforma CBERS-2, na qualidade dedados de média e moderada resolução espacial, respectivamente. Asrefletâncias espectrais para as classes membros de referência foram estimadaspara as bandas espectrais do IRMSS e WFI CBERS-2 por meio dametodologia proposta. A confiabilidade da abordagem proposta foi avaliadapor meio de diagramas de espalhamento para os dados CBERS-2 e tambémpela comparação entre as imagens-fração, produzidas a partir dos conjuntos dedados de imagem dos sensores analisados

Observações e Modelagem da Camada Limite Interna no Entorno de Extensos Sistemas Aquáticos

The determination of the spatial extent of the internal boundary layer (IBL) across a step change in surface roughness and surface heat flux and temperature is an important environmental aspect to the operation of industries, fossil-fuel, nuclear and wind power plants. The IBL of the land-water transition zone, such as in coastal regions, lakes and reservoirs, is strongly influenced by surface properties, as the roughness and stability change considerably within this zone. An observational study was conducted to measure meteorological properties near a large tropical reservoir and investigate the IBL at the water-land transition. A 42 m height meteorological mast was instrumented with sonic wind anemometers, air temperature and relative humidity sensors at 3, 10, 20 and 40 m height. Comparisons of the log profile model with the Monin-Obukhov similarity theory (MOS) and the observed wind profiles, shown that the MOS estimated the wind profile more accurately, especially if winds were from water to land.A determinação da estrutura da camada limite interna planetária (CLI) é um importante aspecto ambiental para o desenvolvimento de atividades industriais e operação de usinas termelétricas, nucleares e eólicas. A CLI pode ser influenciada por diversos fatores como rugosidade superficial, relevo e fluxos de calor e umidade superficiais. Tais características sofrem mudanças particularmente abruptas no entorno de extensos sistemas aquáticos como lagos, reservatórios hidroelétricos e regiões costeiras. Um estudo observacional com medições de temperatura, umidade, direção e intensidade do vento foi realizado de forma a investigar o comportamento da CLI no entorno de um grande reservatório hidroelétrico do Sudeste do Brasil. Os dados são derivados de uma torre meteorológica de 42 m instrumentada com sensores a 3, 10, 20 e 40 m, instalada na borda do corpo aquático por cerca de 12 meses. O perfil dos ventos foi analisado em função dos quadrantes predominantes de direção dos ventos (continental ou aquático). Os resultados foram comparados com dois modelos semi-empíricos da camada limite. A primeira formulação leva em consideração somente o parâmetro de rugozidade da superfície, o modelo logarítmico. O segundo modelo é baseado na teoria de similaridade de Monin-Obukhov (SMO) e considera a estabilidade atmosférica, além da rugosidade da superfície. Os resultados demostraram que o SMO estima o perfil de vento mais acuradamente, principalmente para ventos que sopram da água para a terra

Estudo da dinâmica espaço-temporal do bioma Pantanal por meio de imagens MODIS

The objective of this work was to evaluate multitemporal data, obtained by moderate resolution imaging spectroradiometer (MODIS) sensor, for the study of spatial-temporal dynamics in two subregions of the Pantanal biome. One hundred and thirty nine enhanced vegetation index (EVI) images, from MOD13 vegetation index product, altimetry data from shuttle radar topography mission (SRTM) and tropical rainfall measuring mission (TRMM) precipitation data were used. In order to reduce data dimensionality, MODIS EVI images were sampled based on contour lines spacing of 10 m. The autocorrelation and cluster analysis were used for spatial and temporal evaluation of the samples; and the principal components analysis was applied to all dataset for spatial and temporal analysis. Results showed a spatial and temporal dependence between spectral response and precipitation. The cluster analysis indicated two spatial groups, suggesting the need for the analysis of the entire study area. The principal components analysis allowed to distinguish four behaviors: the areas permanently flooded; nonflooded areas composed by vegetation; flooded areas with higher spectral vegetation response; and riparian vegetation areas.O objetivo deste trabalho foi avaliar dados multitemporais, obtidos pelo sensor "moderate resolution imaging spectroradiometer" (MODIS), para o estudo da dinâmica espaço-temporal de duas sub-regiões do bioma Pantanal. Foram utilizadas 139 imagens "enhanced vegetation index" (EVI), do produto MOD13 "vegetation index", dados de altimetria oriundos do "shuttle radar topography mission" (SRTM) e dados de precipitação do "tropical rainfall measuring mission" (TRMM). Para a redução da dimensionalidade dos dados, as imagens MODIS-EVI foram amostradas com base nas curvas de nível espaçadas em 10 m. Foram aplicadas as técnicas de análise de autocorrelação e análise de agrupamentos aos dados das amostras, e a análise de componentes principais na área total da imagem. Houve dependência tanto temporal quanto espacial da resposta espectral com a precipitação. A análise de agrupamentos apontou a presença de dois grupos, o que indicou a necessidade da análise completa da área. A análise de componentes principais permitiu diferenciar quatro comportamentos distintos: as áreas permanentemente alagadas; as áreas não inundáveis, compostas por vegetação; as áreas inundáveis com maior resposta de vegetação; e áreas com vegetação ripária

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

A interlocução como estratégia para fortalecimento da autonomia das organizações da sociedade civil no Município de Princesa Isabel – PB

Apesar dos avanços das últimas décadas no que ser refere à atuação das organizações da sociedade civil, ainda é fundamental fortalecer a autonomia desses grupos para enfrentar os cenários de adversidade social e política. O presente artigo visa apresentar a experiência do projeto de extensão “A Interlocução como Estratégia para Fortalecimento da Autonomia das Organizações da Sociedade Civil no Município de Princesa Isabel-PB”que teve como objetivo promover, junto a essas organizações atividades destinadas a fortalecer a autonomia das lideranças locais e a cooperação entre as mesmas. Para alcançar esse objetivo foi necessário identificar as organizações da sociedade civil existentes no município e construir um banco de dados com informações básicas sobre essas organizações. O mapeamento identificou 29 organizações, sendo esse número superior ao que havia sido planejado, e realizou encontros e oficinas para promover a integração entre as mesmas

Validação da TSM estimada pelo MODIS na região Nordeste do Oceano Atlântico Sul

Sea surface temperature (SST) from infrared satellite measurements are compared to SST measured by satellite tracked drifters, in the Northwest region of the South Atlantic, taken as reference values. Previous studies indicate that SST variability observed in this region has important influence on the seasonal and longer term precipitation changes on the Northeast Brazil. Mean SST RMSE between MODIS and drifter data are 0.40 °C and 0.52 °C during day and night, respectively. At night time the SST must be corrected by considering the bias (skin-subsurface) of 0.5°C.Pages: 7037-704

Monitoramento de mudanças na cobertura da terra na região da Floresta Nacional do Tapajós, Amazônia Brasileira, utilizando segmentação de imagens multitemporais

The main purpose of this paper is to present a semi-automated procedure for monitoring land cover changes in Brazilian Amazonia. For this, the region around the Tapajós National Forest in Pará State, Brazilian Amazonia was selected. The study area comprises approximately 10,650 km2 covered by the Landsat Thematic Mapper (TM) images acquired on 22 August 1989; 02 August 1999; and 28 July 2009. According to Radambrasil vegetation map, the study area is primarily covered by dense tropical rain forest (Floresta Ombrófila Densa) with a high number of emergent tree species. Firstly, the image segmentation technique was applied to multitemporal Landsat Thematic Mapper acquired over Tapajos National Forest region to generate the georeferenced polygons. Then the vegetation, soil and shade fraction images derived from TM images using Linear Spectral Mixing Model were used to classify these polygons in the land cover classes for each image date. Finally the Geographic Information System tools are used to map the changes occurred on the land cover and land use in the study site between the dates analysed. Then the results achieved by the proposed methodology were evaluated using the MODIS time series available in the LAF (Remote Sensing Laboratory for Agriculture and Forest applications) website (https://www.dsr.inpe.br/laf/series/en/index.html) at INPE and field data. The proposed methodology presents a potential tool for mapping and monitoring land cover and land use changes in the Brazilian Amazonia.Pages: 7786-779

Soybean grain yield monitoring and estimation aided by the mesoscale ETA Weather Forecast model

The objective of this work was to monitor and estimate soybean grain yield based on an agronomical model coupled to a Geographic Information System (GIS) using meteorological data generated by the Eta mesoscale weather forecast model. The agronomic model produced bi-weekly penalizing indices maps and soybean grain yield estimates for the States of Mato Grosso do Sul, Paraná and São Paulo, Brazil, during crop year 2004/05. Result showed that meteorological data from the Eta model, incorporated in an agronomic model, allowed monitoring, in time and space, the soybean crop. In addition, the meteorological data from Eta model are provided in almost real time allowing a quantitative and quick evaluation of weather conditions for soybean production

Mapping and monitoring land cover types in Corumbiara area, Brazilian Amazônia, using Landsat TM and JERS-1 SAR multitemporal data

This paper discusses the use of a Landsat Thematic Mapper (TM) and JERS-1 Synthetic Aperture Radar (SAR) time-series for mapping and monitoring land cover types in a test site in the region of Corumbiara, Rondônia State, western Brazilian Amazônia. In order to support JERS-1 data analysis, land cover maps were obtained by digital classification of Landsat TM images acquired from 1993 to 1997 period, following a procedure based on image segmentation, unsupervised classification, and post-classification image edition. The comparison of these products with JERS-1 temporal images shows that clear-cut areas are well-identified presenting a low backscattering response as expected. On the other hand, areas that have been cleared and even burned but with remaining forest material left on the ground present high backscattering response. Considering these observations and user interpretation expertise, temporal SAR images present an effective source of information for mapping and monitoring deforestation, especially in areas covered by clouds with restricted use of optical data

Avaliação de eventos de inundação na Região Norte Fluminense, Rio de Janeiro, utilizando imagens de sensores remotos

O presente trabalho teve por objetivo identificar e quantificar, por meio de imagens de sensoriamento remoto, as áreas atingidas pelas inundações ocorridas no período do verão de 2008/2009 na região Norte Fluminense, Rio de Janeiro. Para isso, foram utilizadas imagens dos sensores TM Landsat-5 e CCD CBERS-2B adquiridas antes e após a ocorrência das inundações. Nessas imagens foram aplicadas o Modelo Linear de Mistura Espectral - MLME para realçar as áreas ocupadas com os corpos d'água. Concluiu-se que, após comparar a imagem TM do dia 26/07/2007 (sem inundação) com as imagens TM (17/11/2008) e CCD (20/01/2009) tomadas depois do período chuvoso na região, o espelho d'água da região sofreu um incremento de 2,61 vezes, correspondendo a área total de 99.000 ha atingida pelas águas