981 resultados para LANDSAT THEMATIC MAPPER


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Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

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This paper maps the carbonate geochemistry of the Makgadikgadi Pans region of northern Botswana from moderate resolution (500 m pixels) remotely sensed data, to assess the impact of various geomorphological processes on surficial carbonate distribution. Previous palaeo-environmental studies have demonstrated that the pans have experienced several highstands during the Quaternary, forming calcretes around shoreline embayments. The pans are also a significant regional source of dust, and some workers have suggested that surficial carbonate distributions may be controlled, in part, by wind regime. Field studies of carbonate deposits in the region have also highlighted the importance of fluvial and groundwater processes in calcrete formation. However, due to the large area involved and problems of accessibility, the carbonate distribution across the entire Makgadikgadi basin remains poorly understood. The MODIS instrument permits mapping of carbonate distribution over large areas; comparison with estimates from Landsat Thematic Mapper data show reasonable agreement, and there is good agreement with estimates from laboratory analysis of field samples. The results suggest that palaeo-lake highstands, reconstructed here using the SRTM 3 arc-second digital elevation model, have left behind surficial carbonate deposits, which can be mapped by the MODIS instrument. Copyright (c) 2006 John Wiley & Sons, Ltd.

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ATSR-2 active fire data from 1996 to 2000, TRMM VIRS fire counts from 1998 to 2000 and burn scars derived from SPOT VEGETATION ( the Global Burnt Area 2000 product) were mapped for Peru and Bolivia to analyse the spatial distribution of burning and its intra- and inter-annual variability. The fire season in the region mainly occurs between May and October; though some variation was found between the six broad habitat types analysed: desert, grassland, savanna, dry forest, moist forest and yungas (the forested valleys on the eastern slope of the Andes). Increased levels of burning were generally recorded in ATSR-2 and TRMM VIRS fire data in response to the 1997/1998 El Nino, but in some areas the El Nino effect was masked by the more marked influences of socio-economic change on land use and land cover. There were differences between the three global datasets: ATSR-2 under-recorded fires in ecosystems with low net primary productivities. This was because fires are set during the day in this region and, when fuel loads are low, burn out before the ATSR-2 overpass in the region which is between 02.45 h and 03.30 h. TRMM VIRS was able to detect these fires because its overpasses cover the entire diurnal range on a monthly basis. The GBA2000 product has significant errors of commission (particularly areas of shadow in the well-dissected eastern Andes) and omission (in the agricultural zone around Santa Cruz, Bolivia and in north-west Peru). Particular attention was paid to biomass burning in high-altitude grasslands, where fire is an important pastoral management technique. Fires and burn scars from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for a range of years between 1987 and 2000 were mapped for areas around Parque Nacional Rio Abiseo (Peru) and Parque Nacional Carrasco (Bolivia). Burn scars mapped in the grasslands of these two areas indicate far more burning had taken place than either the fires or the burn scars derived from global datasets. Mean scar sizes are smaller and have a smaller range in size between years the in the study area in Peru (6.6-7.1 ha) than Bolivia (16.9-162.5 ha). Trends in biomass burning in the two highland areas can be explained in terms of the changing socio-economic environments and impacts of conservation. The mismatch between the spatial scale of biomass burning in the high-altitude grasslands and the sensors used to derive global fire products means that an entire component of the fire regime in the region studied is omitted, despite its importance in the farming systems on the Andes.

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The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

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Glaciers occupy an area of similar to 1600 km(2) in the Caucasus Mountains. There is widespread evidence of retreat since the Little Ice Age, but an up-to-date regional assessment of glacier change is lacking. In this paper, satellite imagery (Landsat Thematic Mapper and Enhanced Thematic Mapper Plus) is used to obtain the terminus position of 113 glaciers in the central Caucasus in 1985 and 2000, using a manual delineation process based on a false-colour composite (bands 5, 4, 3). Measurements reveal that 94% of the glaciers have retreated, 4% exhibited no overall change and 2% advanced. The mean retreat rate equates to similar to 8 m a(-1), and maximum retreat rates approach similar to 38 m a(-1). The largest (>10 km(2)) glaciers retreated twice as much (similar to 12 m a(-1)) as the smallest (<1 km(2)) glaciers (similar to 6 m a(-1)), and glaciers at lower elevations generally retreated greater distances. Supraglacial debris cover has increased in association with glacier retreat, and the surface area of bare ice has reduced by similar to 10% between 1985 and 2000. Results are compared to declassified Corona imagery from the 1960s and 1970s and detailed field measurements and mass-balance data for Djankuat glacier, central Caucasus. It is concluded that the decrease in glacier area appears to be primarily driven by increasing temperatures since the 1970s and especially since the mid-1990s. Continued retreat could lead to considerable changes in glacier runoff, with implications for regional water resources.

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This paper maps the carbonate geochemistry of the Makgadikgadi Pans region of northern Botswana from moderate resolution (500 m pixels) remotely sensed data, to assess the impact of various geomorphological processes on surficial carbonate distribution. Previous palaeo-environmental studies have demonstrated that the pans have experienced several highstands during the Quaternary, forming calcretes around shoreline embayments. The pans are also a significant regional source of dust, and some workers have suggested that surficial carbonate distributions may be controlled, in part, by wind regime. Field studies of carbonate deposits in the region have also highlighted the importance of fluvial and groundwater processes in calcrete formation. However, due to the large area involved and problems of accessibility, the carbonate distribution across the entire Makgadikgadi basin remains poorly understood. The MODIS instrument permits mapping of carbonate distribution over large areas; comparison with estimates from Landsat Thematic Mapper data show reasonable agreement, and there is good agreement with estimates from laboratory analysis of field samples. The results suggest that palaeo-lake highstands, reconstructed here using the SRTM 3 arc-second digital elevation model, have left behind surficial carbonate deposits, which can be mapped by the MODIS instrument. Copyright (c) 2006 John Wiley & Sons, Ltd.

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Informatics evolution presently offers the possibility of new technique and methodology development for studies in all human knowledge areas. In addition, the present personal computer capacity of handling a large volume of data makes the creation and application of new analysis tools easy. This paper aimed the application of a fuzzy partition matrix to analyze data obtained from the Landsat 5 TMN sensor, in order to elaborate the supervised classification of land use in Arroio das Pombas microbasin in Botucatu, SP, Brazil. It was possible that one single training area present input in more than one covering class due to weight attribution at the signature creation moment. A change in the classification result was also observed when compared to maximum likelihood classification, mainly when related to bigger uniformity and better class edges classification.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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During my Doctoral study I researched about the remote detection of canopy N concentration in forest stands, its potentials and problems, under many overlapping perspectives. The study consisted of three parts. In S. Rossore 2000 dataset analysis, I tested regressions between N concentration and NIR reflectances derived from different sources (field samples, airborne and satellite sensors). The analysis was further expanded using a larger dataset acquired in year 2009 as part of a new campaign funded by the ESA. In both cases, a good correlation was observed between Landsat NIR, using both TM (2009) and ETM+ (2000) imagery, and N concentration measured by a CHN elemental analyzer. Concerning airborne sensors I did not obtain the same good results, mainly because of the large FOV of the two instruments, and to the anisotropy of vegetation reflectance. We also tested the relation between ground based ASD measures and nitrogen concentration, obtaining really good results. Thus, I decided to expand my study to the regional level, focusing only on field and satellite measures. I analyzed a large dataset for the whole of Catalonia, Spain; MODIS imagery was used, in consideration of its spectral characteristics and despite its rather poor spatial resolution. Also in this case a regression between nitrogen concentration and reflectances was found, but not so good as in previous experiences. Moreover, vegetation type was found to play an important role in the observed relationship. We concluded that MODIS is not the most suitable satellite sensor in realities like Italy and Catalonia, which present a patchy and inhomogeneous vegetation cover; so it could be utilized for the parameterization of eco-physiological and biogeochemical models, but not for really local nitrogen estimate. Thus multispectral sensors similar to Landsat Thematic Mapper, with better spatial resolution, could be the most appropriate sensors to estimate N concentration.

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A post classification change detection technique based on a hybrid classification approach (unsupervised and supervised) was applied to Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Plus (ETM+), and ASTER images acquired in 1987, 2000 and 2004 respectively to map land use/cover changes in the Pic Macaya National Park in the southern region of Haiti. Each image was classified individually into six land use/cover classes: built-up, agriculture, herbaceous, open pine forest, mixed forest, and barren land using unsupervised ISODATA and maximum likelihood supervised classifiers with the aid of field collected ground truth data collected in the field. Ground truth information, collected in the field in December 2007, and including equalized stratified random points which were visual interpreted were used to assess the accuracy of the classification results. The overall accuracy of the land classification for each image was respectively: 1987 (82%), 2000 (82%), 2004 (87%). A post classification change detection technique was used to produce change images for 1987 to 2000, 1987 to 2004, and 2000 to 2004. It was found that significant changes in the land use/cover occurred over the 17- year period. The results showed increases in built up (from 10% to 17%) and herbaceous (from 5% to 14%) areas between 1987 and 2004. The increase of herbaceous was mostly caused by the abandonment of exhausted agriculture lands. At the same time, open pine forest and mixed forest areas lost (75%) and (83%) of their area to other land use/cover types. Open pine forest (from 20% to 14%) and mixed forest (from18 to 12%) were transformed into agriculture area or barren land. This study illustrated the continuing deforestation, land degradation and soil erosion in the region, which in turn is leading to decrease in vegetative cover. The study also showed the importance of Remote Sensing (RS) and Geographic Information System (GIS) technologies to estimate timely changes in the land use/cover, and to evaluate their causes in order to design an ecological based management plan for the park.

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This study describes detailed partitioning of phytomass carbon (C) and soil organic carbon (SOC) for four study areas in discontinuous permafrost terrain, Northeast European Russia. The mean aboveground phytomass C storage is 0.7 kg C/m**2. Estimated landscape SOC storage in the four areas varies between 34.5 and 47.0 kg C/m**2 with LCC (land cover classification) upscaling and 32.5-49.0 kg C/m**2 with soil map upscaling. A nested upscaling approach using a Landsat thematic mapper land cover classification for the surrounding region provides estimates within 5 ± 5% of the local high-resolution estimates. Permafrost peat plateaus hold the majority of total and frozen SOC, especially in the more southern study areas. Burying of SOC through cryoturbation of O- or A-horizons contributes between 1% and 16% (mean 5%) of total landscape SOC. The effect of active layer deepening and thermokarst expansion on SOC remobilization is modeled for one of the four areas. The active layer thickness dynamics from 1980 to 2099 is modeled using a transient spatially distributed permafrost model and lateral expansion of peat plateau thermokarst lakes is simulated using geographic information system analyses. Active layer deepening is expected to increase the proportion of SOC affected by seasonal thawing from 29% to 58%. A lateral expansion of 30 m would increase the amount of SOC stored in thermokarst lakes/fens from 2% to 22% of all SOC. By the end of this century, active layer deepening will likely affect more SOC than thermokarst expansion, but the SOC stores vulnerable to thermokarst are less decomposed.

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In this paper we proposed a composite depth of penetration (DOP) approach to excluding bottom reflectance in mapping water quality parameters from Landsat thematic mapper (TM) data in the shallow coastal zone of Moreton Bay, Queensland, Australia. Three DOPs were calculated from TM1, TM2 and TM3, in conjunction with bathymetric data, at an accuracy ranging from +/-5% to +/-23%. These depths were used to segment the image into four DOP zones. Sixteen in situ water samples were collected concurrently with the recording of the satellite image. These samples were used to establish regression models for total suspended sediment (TSS) concentration and Secchi depth with respect to a particular DOP zone. Containing identical bands and their transformations for both parameters, the models are linear for TSS concentration, logarithmic for Secchi depth. Based on these models, TSS concentration and Secchi depth were mapped from the satellite image in respective DOP zones. Their mapped patterns are consistent with the in situ observed ones. Spatially, overestimation and underestimation of the parameters are restricted to localised areas but related to the absolute value of the parameters. The mapping was accomplished more accurately using multiple DOP zones than using a single zone in shallower areas. The composite DOP approach enables the mapping to be extended to areas as shallow as <3 m. (C) 2004 Elsevier Inc. All rights reserved.

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Propôs-se, neste trabalho, estimar dados de albedo à superfície terrestre usando-se o sensor Thematic Mapper (TM) do satélite LANDSAT 5 e compará-lo com dados de duas estações agrometeorológicas localizadas em região de Cerrado e a outra em cultivo da cana-de-açúcar. A região de estudo está localizada no município de Santa Rita do Passa Quatro, SP, Brasil. Para a realização do estudo obtiveram-se seis imagens orbitais do satélite Landsat 5 sensores TM, na órbita 220 e ponto 75, nas datas de 22/02, 11/04, 29/05, 01/08, 17/08 e 21/11, todas do ano de 2005, a que correspondem os dias juliano de 53, 101, 149, 213, 229 e 325, respectivamente. As correções geométricas para as imagens foram realizadas e geradas as cartas de albedo. O algoritmo SEBAL estimou satisfatoriamente os valores de albedo de superfícies sobre áreas de cerrado e de cana-de-açúcar, na região de Santa Rita do Passa Quatro, SP, consistentes com observações realizadas do albedo à superfície.

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O mapeamento do uso da terra é fundamental para o entendimento dos processos de mudanças globais, especialmente em regiões como a Amazônia que estão sofrendo grande pressão de desenvolvimento. Tradicionalmente estes mapeamentos têm sido feitos utilizando técnicas de interpretação visual de imagens de satélites, que, embora de resultados satisfatórios, demandam muito tempo e alto custo. Neste trabalho é proposta uma técnica de segmentação da imagens com base em um algoritmo de crescimento de regiões, seguida de uma classificação não-supervisionada por regiões. Desta forma, a classificação temática se refere a um conjunto de elementos (pixels da imagem), beneficiando-se portanto da informação contextual e minimizando as limitações das técnicas de processamento digital baseadas em análise pontual (pixel-a-pixel). Esta técnica foi avaliada numa área típica da Amazônia, situada ao norte de Manaus, AM, utilizando imagens do sensor "Thematic Mapper" - TM do satélite Landsat, tanto na sua forma original quanto decomposta em elementos puros como vegetação verde, vegetação seca (madeira), sombra e solo, aqui denominada imagem misturas. Os resultados foram validados por um mapa de referência gerado a partir de técnicas consagradas de interpretação visual, com verificação de campo, e indicaram que a classificação automática é viável para o mapeamento de uso da terra na Amazônia. Testes estatísticos indicaram que houve concordância significativa entre as classificações automáticas digitais e o mapa de referência (em tomo de 95% de confiança).