1000 resultados para Landsat-7 ETM


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This paper presents a comparison of descriptive statistics obtained for brittle structural lineaments extracted manually from LANDSAT images and shaded relief images from SRTM 3 DEM at 1:100, 000 and 1:500, 000 scales. The selected area is located in the southern of Brazil and comprises Precambrian rocks and stratigraphic units of the Paraná Basin. The application of this methodology shows that the visual interpretation depends on the kind of remote sensing image. The resulting descriptive statistics obtained for lineaments extracted from the images do not follow the same pattern according to the scale adopted. The main direction obtained for Proterozoic rocks using both image types at a 1:500, 000 scale are close to NS±10, whereas at a 1:100, 000 scale N45E was obtained for shaded relief images from SRTM 3 DEM and N10W for LANDSAT images. The Paleozoic sediments yielded the best results for the different images and scales (N50W). On the other hand, the Mesozoic igneous rocks showed greatest differences, the shaded relief images from SRTM 3 DEM images highlighting NE structures and the LANDSAT images highlighting NW structures. The accumulated frequency demonstrated high similarity between products for each image type no matter the scale, indicating that they can be used in multiscale studies. Conversely, major differences were found when comparing data obtained using shaded relief images from SRTM 3 DEM and Landsat images at a 1:100, 000 scale.

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Government agencies responsible for riparian environments are assessing the utility of remote sensing for mapping and monitoring environmental health indicators. The objective of this work was to evaluate IKONOS and Landsat-7 ETM+ imagery for mapping riparian vegetation health indicators in tropical savannas for a section of Keelbottom Creek, Queensland, Australia. Vegetation indices and image texture from IKONOS data were used for estimating percentage canopy cover (r2=0.86). Pan-sharpened IKONOS data were used to map riparian species composition (overall accuracy=55%) and riparian zone width (accuracy within 4 m). Tree crowns could not be automatically delineated due to the lack of contrast between canopies and adjacent grass cover. The ETM+ imagery was suited for mapping the extent of riparian zones. Results presented demonstrate the capabilities of high and moderate spatial resolution imagery for mapping properties of riparian zones, which may be used as riparian environmental health indicators

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The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

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O objetivo desta pesquisa foi avaliar o uso de dados hiperespectrais Hyperion/EO-1 na discriminação de alvos agrícolas, comparando a acurácia de classificação obtida pelos dados desse sensor à obtida por dados multiespectrais ETM+/Landsat-7. Para isso, alvos agrícolas da região de Franca - SP, com diferenças espectrais bem definidas e outros alvos com diferenças espectrais sutis, imageados por ambos os sensores, em 16 de julho de 2002, foram discriminados utilizando o classificador supervisionado de Máxima Verossimilhança (MaxVer). Os alvos agrícolas com diferenças espectrais bem definidas foram caracterizados por seis classes de uso e cobertura do solo; já os com diferenças espectrais sutis, por cinco classes de variedades de cana-de-açúcar. Quando os dados ETM+ foram classificados, a acurácia foi de 91,5% para as classes de uso e cobertura do solo e de 67,6% para as classes de variedades de cana-de-açúcar, enquanto, para os dados do sensor Hyperion, a acurácia de classificação foi de 94,9% e de 87,1%, respectivamente, demonstrando, assim, a importância do uso de dados hiperespectrais na discriminação de alvos agrícolas com características espectrais semelhantes.

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Government agencies responsible for riparian environments are assessing the utility of remote sensing for mapping and monitoring vegetation structural parameters. The objective of this work was to evaluate Ikonos and Landsat-7 ETM+ imagery for mapping structural parameters and species composition of riparian vegetation in Australian tropical savannahs for a section of Keelbottom Creek, Queensland, Australia. Vegetation indices and image texture from Ikonos data were used for estimating leaf area index (R-2 = 0.13) and canopy percentage foliage cover (R-2 = 0.86). Pan-sharpened Ikonos data were used to map riparian species composition (overall accuracy = 55 percent) and riparian zone width (accuracy within +/- 3 m). Tree crowns could not be automatically delineated due to the lack of contrast between canopies and adjacent grass cover. The ETM+ imagery was suited for mapping the extent of riparian zones. Results presented demonstrate the capabilities of high and moderate spatial resolution imagery for mapping properties of riparian zones.

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O presente estudo teve como objetivo comparar a eficiência dos dados dos sensores Aster e ETM+/Landsat 7 na classificação do uso e cobertura da terra, com ênfase nos níveis de degradação das pastagens na Zona da Mata Mineira, através da utilização de redes neurais artificiais. Foram testadas três composições de uma imagem do sensor Aster e uma do ETM+/Landsat 7, para definição das melhores feições discriminantes para o classificador. As classes de uso e cobertura consideradas foram: floresta, café, área urbana/solo exposto e três níveis de degradação das pastagens (moderado, forte e muito forte). Utilizou-se o simulador de redes neurais Java Neural Network Simulator e o algoritmo empregado foi o back-propagation. Dentre as composições de imagens testadas o melhor resultado foi alcançado com a utilização das 9 bandas do Aster (30m) como variáveis discriminantes, que também permitiu uma melhor discriminação dos níveis de degradação das pastagens considerados. Este resultado é atribuído à melhor resolução espectral desta composição de imagem quando comparada às demais. Dentre as classes consideradas, a pastagem no nível de degradação muito forte foi a que apresentou o maior erro de classificação, em todas as composições, sendo bastante confundida com a pastagem no nível de degradação forte.

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This study aims to examine the thermal structure of the urban climate based on the interpretation of the satellite Landsat 7 (thermal channel) and measures for the area. It identifies how the production of urban climate develops based on an analysis of the structure of space forms and characteristics of land use and constructive materials in the generation of heat islands and their implications in environmental comfort in a tropical climate medium size city at Brazil. To check intra-urban air temperature, measures were carried out in mobile transects in the North-South and East-West routes. Thermal Channel data of Landsat-7, were converted to surface values. The results showed that the pattern of urbanization and characteristics of land use are responsible for the distribution of temperature generating heat islands in downtown and popular densely built neighborhoods. In those cases the highest indexes of social segregation added to higher temperature also provokes elevation in the number of illnesses and morbidity cases, mostly of respiratory diseases.

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The purpose of this paper is to analyze the usefulness of traditional indexes, such as NDVI and NDWI along with a recently proposed index (NDDI) using merged data for multiple dates, with the aim of obtaining drought data to facilitate the analysis for government premises. In this study we have used Landsat 7 ETM+ data for the month of June (2001-2009), which merged to get bands with twice the resolution. The three previous indices were calculated from these new bands, getting in turn drought maps that can enhance the effectiveness of decision making.

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Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (upto 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.

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Os problemas ambientais urbanos se agravaram nas últimas décadas devido ao crescimento das cidades sem ou com inadequado planejamento urbano. Assim, a preocupação com a qualidade ambiental urbana ganha foco e suas técnicas de análise também. Desta forma, entre os diferentes problemas relacionados a essa questão destaca-se o clima urbano, gerado a partir de mudanças realizadas na cobertura da superfície urbana, resultando em mudanças na atmosfera local, percebidas principalmente na temperatura do ar.  Esta pesquisa teve como objetivo analisar as diferenças nas temperaturas da superfície intraurbana na cidade de Cândido Mota/SP e compará-las com a temperatura da superfície do ambiente rural próximo. Para a realização deste estudo, foi utilizada imagem de satélite – canal termal do satélite LandSat 7, banda 6, com resolução espacial de 60 metros – tratada no software IDRISI (marca registrada da Clark University) transformando os valores digitais para temperatura em graus Celsius (ºC). Este procedimento possibilitou uma análise das temperaturas das diferentes coberturas das estruturas da cidade e também da densidade de cobertura vegetal. A área de estudo selecionada foi a cidade de Cândido Mota/SP, e verificou-se que mesmo sendo de pequeno porte, apresenta diferenças significativas na temperatura da superfície quando se compara com o ambiente rural. 

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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A conversão de áreas com cobertura florestal contínua por fragmentos florestais vem contribuindo para a diminuição da diversidade biológica, em função da perda de micro-habitats únicos, mudanças nos padrões de dispersão e migração, isolamento de habitats e erosão do solo. A solução desses problemas está intimamente vinculada ao planejamento e manutenção de bacias hidrográficas. A sub-bacia do Arroio Jacaré, localizada no Vale do Taquari, RS, compreende uma área de 538,98 km², onde estão parcial ou totalmente inseridos nove municípios. Essa bacia se encontra em uma região de ecótono entre as formações vegetais do tipo Floresta Estacional Decidual (FED) e Floresta Ombrófila Mista - Mata de Araucária (FOM). Foram elaboradas e analisadas informações relacionadas às características estruturais das classes de mata na região (FED, FOM e vegetação secundária), utilizando-se imagem do satélite Landsat 7 ETM+, referente à passagem 04/02/2002 e software de Sistemas de Informações Geográficas (SIG) Idrisi, 3.2, software de Ecologia de Paisagem Fragstats 3.3. Os resultados indicaram que a região apresenta aproximadamente 50% de suas matas nativas conservadas ou em estágio de regeneração, porém de forma altamente fragmentada, com 87,82% dos fragmentos menores que 1 ha. Considerando um efeito de borda de 50 m, em torno de 40% dos fragmentos ainda apresentam área nuclear.

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Para investigar alterações no albedo, no Índice de Vegetação por Diferença Normalizada (NDVI), no saldo de radiação e no fluxo de calor no solo, em decorrência do regime pluviométrico no semiárido cearense, desenvolveu-se um estudo na bacia do Rio Trussu - Ceará, empregando-se sensoriamento remoto. Foram utilizadas duas imagens Landsat 7 ETM+, datadas de 25-10-2000 e 24-7-2001, sendo as variáveis estimadas pelo emprego do algoritmo SEBAL (Surface Energy Balance Algorithms for Land). Os resultados mostraram que as variáveis investigadas apresentaram alterações entre as duas estações, sendo os maiores valores de albedo registrados na estação seca. O NDVI apresentou maior sensibilidade ao regime hídrico, mostrando alto potencial de recuperação da vegetação ao efeito da precipitação. As margens do Rio Trussu apresentaram NDVI superior a 0,39, sendo indicativo de preservação da mata ciliar. A vegetação da bacia mostrou alto poder resiliente expresso pelo incremento nos valores de NDVI para o ano de 2001. A estação chuvosa exerceu também influência marcante sobre o saldo de radiação e fluxo de calor no solo, confirmando o efeito da estação climática na modificação do balanço de energia sobre a bacia.

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The Buordakh Massif, in the Cherskiy Range of northeast Siberia, contains mountains over 3000 in and, despite its and climate, numerous glaciers. This paper presents a glacier inventory for the region and documents some 80 glaciers, which range in size from 0.1 to 10.4 km(2) (total glacierized area is ca. 70 km(2)). The inventory is based on mapping derived from Landsat 7 ETM+ satellite imagery from August 2001, augmented with data from field investigations obtained at that time. The glaciers in this region are of the 'firn-less,' cold, continental type, and their mass balance relies heavily on the formation of superimposed ice. The most recent glacier maximum extents have also been delineated, and these are believed to date from the Little Ice Age (ca. A.D. 1550-1850). Glacier areal extent has reduced by some 14.8 km(2) (ca. 17%) since this most. recent maximum. Of the 80 glaciers catalogued, 49 have undergone a measurable retreat from their most recent maximum extent.