974 resultados para Landsat-5
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A partir dos anos 1970, a ocupação pelo homem do espaço do centro-oeste brasileiro apresentou um elevado crescimento devido a políticas de expansão agrícola. Este fato ocorreu por meio do alto grau de mecanização agrícola e aplicação de fertilizantes, visando elevados níveis de produção em diversas localidades, como o sudoeste do Estado de Goiás. Tal predicado da alta produtividade mantém-se até os dias atuais, indicando a grande intensidade da dinâmica de uso e cobertura das terras nesta região. Desta forma, tornase necessário o conhecimento da dinâmica e distribuição espacial dos padrões de uso e cobertura da terra, podendo fornecer subsídios a ações de planejamento agrícola sobre o espaço em alguns municípios do sudoeste goiano. Para isto, imagens orbitais do satélite Landsat TM-5 foram adquiridas em diferentes períodos do ciclo agrícola ao longo de 2007. Informações complementares acerca do uso regional foram utilizadas para apoiar a interpretação e classificação, principalmente a partir dos dados obtidos em campo. Os mapas de uso e cobertura da terra para os municípios de Rio Verde, Acreúna, Santo Antônio da Barra, Santa Helena de Goiás, Montividiu e Paraúna foram obtidos utilizando ferramentas do programa Spring 4.3.3 como a segmentação de imagens, bem como o classificador semi-automático Bhattacharya Distance, sendo estabelecidas dez classes temáticas, com base na legenda proposta pelo IBGE e Corine. A análise multitemporal, assim como a segmentação mostraram-se eficientes na distinção das classes de uso e cobertura da terra da região. A classe de uso destinada ao plantio da soja apresentou o maior percentual da área, mudando para culturas safrinha, solo exposto ou pousio no inverno. Outras classes também merecem destaque como a Pastagem e a Cana-de-açúcar, que apresentaram distribuição espacial bastante concentrada. Este mapeamento fornece subsídios ao planejamento do uso e ocupação das terras na região, considerando os aspectos ambientais e sociais, assegurando maior produtividade agrícola, visando um manejo sustentável das terras e a qualidade de vida ao homem do campo.
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The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.
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This work aims to analyze the land use evolution in the city of Santa Cruz do Rio Pardo - SP through supervised classification of Landsat-5 TM satellite images according to the maximum likelihood (Maxlike), as well as verifying the mapping accuracy through Kappa index, comparing NDVI and SAVI vegetation indexes in different adjustment factors for the canopy substrate and determining the vegetal coverage percentage in all methods used on 2007, May 26 th; 2009, January 7 th and 2009, April 29 th. The Maxlike classification showed several spatial changes in land use over the study period. The most appropriated vegetation indexes were NDVI and SAVI - 0,25 factor, which showed similar values of vegetal coverage percentage, but discrepant from the inferred value for Maxlike classification.
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Empirical approaches and, more recently, physical approaches, have grounded the establishment of logical connections between radiometric variables derived from remote data and biophysical variables derived from vegetation cover. This study was aimed at evaluating correlations of dendrometric and density data from canopies of Eucalyptus spp., as collected in Capao Bonito forest unit, with radiometric data from imagery acquired by the TM/Landsat-5 sensor on two orbital passages over the study site (dates close to field data collection). Results indicate that stronger correlations were identified between crown dimensions and canopy height with near-infrared spectral band data (rho(s)4), irrespective of the satellite passage date. Estimates of spatial distribution of dendrometric data and canopy density (D) using spectral characterization were consistent with the spatial distribution of tree ages during the study period. Statistical tests were applied to evaluate performance disparities of empirical models depending on which date data were acquired. Results indicated a significant difference between models based on distinct data acquisition dates.
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Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)
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Foram estudados, com o auxílio de fotografias aéreas, aspectos qualitativos e quantitativos do relevo e da rede de drenagem de solos de uma área de Santa Bárbara D'Oeste, SP. Esta região compreende 14.625 ha, onde foram selecionadas bacias hidrográficas de 3ª ordem de ramificação e amostras circulares de 5km². As unidades de mapeamento simples ou associações de solos são: Latossolo Vermelho Escuro, Podzólico, Litossolo + Podzólico, Terra Roxa Estruturada + Latossolo Roxo distrófico. Após a caracterização das feições fisiográficas, da área de ocorrência desses solos, foram realizados dois mapas morfopedológicos. No primeiro utilizou-se fotografias aéreas verticais pancromáticas na escala 1: 35.000 (data de 25/6/78) e no segundo imagens orbitais do sensor Thematic Mapper do LANDSAT-5, nas bandas 3, 4 e 5 e composição colorida 3/4/5 na escala 1: 100.000 (data de 12/9/91). As análises qualitativas e quantitativas do relevo (índice de declividade média) e rede de drenagem (densidade de drenagem, freqüência de rios, razão de textura) mostraram-se eficientes na diferenciação das unidades de solo estudadas, tanto em bacias hidrográficas como em amostras circulares. A utilização de fotografias aéreas, permitiu maior riqueza de detalhes na precisão dos limites das unidades de mapeamento e no maior número de unidades de mapeamento discriminadas em relação as imagens orbitais. A composição colorida 3/4/5 permitiu diferenciar os Latossolos argilosos dos Latossolos de textura média, assim como o Latossolo Húmico.
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This work embraces the application of Landsat 5-TM digital images, comprising August 2 1989 and September 22 1998, for temporal mapping and geoenvironmental analysis of the dynamic of Piranhas-Açu river mouth, situated in the Macau (RN) region. After treatment using several digital processing techniques (e.g. colour composition in RGB, ratio of bands, principal component analysis, index methods, among others), it was possible to generate several image products and multitemporal maps of the coastal morphodynamics of the studied area. Using the image products it was possible the identification and characterization of the principal elements of interest (vegetation, soil, geology and water) in the surface of the studied area, associating the spectral characteristics of these elements to that presented by the image products resulting of the digital processing. Thus, it was possible to define different types of soils: Amd, AQd6, SK1 and LVe4; vegetation grouping: open arboreal-shrubby caatinga, closed arborealshrubby caatinga, closed arboreal caatinga, mangrove vegetation, dune vegetation and areas predominately constituted by juremas; geological units: quaternary units beach sediments, sand banks, dune flats, barrier island, mobile dunes, fixed dunes, alluvium, tidal and inundation flats, and sandy facies of the Potengi Formation; tertiary-quaternary units Barreiras Formation grouped to the clayey facies of the Potengi Formation, Macau Formation grouped to the sediments of the Tibau Formation; Cretaceous units Jandaíra Formation; moreover it was to identify the sea/land limit, shallow submersed areas and suspended sediments. The multitemporal maps of the coastal morphodynamics allowed the identification and a semi-quantitative evoluation of regions which were submitted to erosive and constructive processes in the last decade. This semi-quantitative evoluation in association with an geoenvironmental characterization of the studied area are important data to the elaboration of actions that may minimize the possible/probable impacts caused by the implantation of the Polo Gas/Sal and to the monitoring of areas explorated by the petroleum and salt industries
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This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation
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Algae bloom is one of the major consequences of the eutrophication of aquatic systems, including algae capable of producing toxic substances. Among these are several species of cyanobacteria, also known as blue-green algae, that have the capacity to adapt themselves to changes in the water column. Thus, the horizontal distribution of cyanobacteria harmful algae blooms (CHABs) is essential, not only to the environment, but also for public health. The use of remote sensing techniques for mapping CHABs has been explored by means of bio-optical modeling of phycocyanin (PC), a unique inland waters cyanobacteria pigment. However, due to the small number of sensors with a spectral band of the PC absorption feature, it is difficult to develop semi-analytical models. This study evaluated the use of an empirical model to identify CHABs using TM and ETM+ sensors aboard Landsat 5 and 7 satellites. Five images were acquired for applying the model. Besides the images, data was also collected in the Guarapiranga Reservoir, in São Paulo Metropolitan Region, regarding the cyanobacteria cell count (cells/mL), which was used as an indicator of CHABs biomass. When model values were analyzed excluding calibration factors for temperate lakes, they showed a medium correlation (R²=0.81, p=0.036), while when the factors were included the model showed a high correlation (R²=0.96, p=0.003) to the cyanobacteria cell count. The empirical model analyzed proved useful as an important tool for policy makers, since it provided information regarding the horizontal distribution of CHABs which could not be acquired from traditional monitoring techniques.
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The Companhia Energetica de Sao Paulo - CESP owns six hydroelectric dams in the state of São Paulo. The dams, both in its construction and in operation, cause some environmental impacts, most of them negatives, for example, the flooding in regions before not flooded, deviation of the river’s course, among others, bringing harm to flora and fauna of these environments. As a way to compensating these damages, the CESP has acquired a region that was influenced by Sérgio Motta Hydroelectric Plant Engineer, or Porto Primavera, and turned it into Reserva Particular do Patrimônio Natural Foz do Rio Aguapeí. By law it fits in a Conservation Unit, and thus should be contemplate for a management plan, ie, a multidisciplinary technical document which allows, simply, the practice of actions within and around in a sustainably way. This work aimed at developing a land cover map of the reserve for this plan can be made and executed more efficiently. Initially, the project included field visits and meetings with members of the CESP to be specified classes contained on the map. Later, we ran different types of classifications of multispectral images (TM / Landsat 5)... (Complete abstract click electronic access below)
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The objectives of this study were to evaluate land use and occupation of Permanent Preservation Areas (PPA) as well as its use conflicts by TM (Thematic Mapper) image of the 2010 Landsat-5 satellite, according to the Forest Code. For that purpose, Geographic Information Systems in the Ribeirão Paraíso watershed, São Manuel, SP were used. The combination of Remote Sensing and Geographic Information System technologies allowed representation of spatial distribution of the landscape and data integration in the diagnosis of geographic interest. The 2010 mapping showed 12 use categories, and the sugar cane crop had the largest land occupation, 48.25% of the area. The areas of permanent preservation amounted to 925.74 ha, which is an ideal value based on the Brazilian legislation. Mapping of land use conflicts showed intensive anthropic actions going 80.13% forward on PPAs, with only 19.87% remaining forests, which highlights their negative impact and illegal situations in these areas.
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A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set. The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.