1000 resultados para Landsat-7 ETM
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In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.
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Using Landsat imagery, forest canopy density (FCD) estimated with the FCD Mapper®, was correlated with predominant height (PDH, measured as the average height of the tallest 50 trees per hectare) for 20 field plots measured in native forest at Noosa Heads, south-east Queensland, Australia. A corresponding image was used to calculate FCD in Leyte Island, the Philippines and was validated on the ground for accuracy. The FCD Mapper was produced for the International Tropical Timber Organisation and estimates FCD as an index of canopy density using reflectance characteristics of Landsat Enhanced Thematic (ETM) Mapper images. The FCD Mapper is a ‘semi-expert’ computer program which uses interactive screens to allow the operator to make decisions concerning the classification of land into bare soil, grass and forest. At Noosa, a positive strong nonlinear relationship (r2 = 0.86) was found between FCD and PDH for 15 field plots with variable PDH but complete canopy closure. An additional five field plots were measured in forest with a broken canopy and the software assessed these plots as having a much lower FCD than forest with canopy closure. FCD estimates for forest and agricultural land in the island of Leyte and subsequent field validation showed that at appropriate settings, the FCD Mapper differentiated between tropical rainforest and banana or coconut plantation. These findings suggest that in forests with a closed canopy this remote sensing technique has promise for forest inventory and productivity assessment. The findings also suggest that the software has promise for discriminating between native forest with a complete canopy and forest which has a broken canopy, such as coconut or banana plantation.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Resumo: O objetivo deste trabalho foi avaliar o desempenho dos classificadores digitais SVM e K-NN para a classificação orientada a objeto em imagens Landsat-8, aplicados ao mapeamento de uso e cobertura do solo da Alta Bacia do Rio Piracicaba-Jaguari, MG. A etapa de pré-processamento contou com a conversão radiométrica e a minimização dos efeitos atmosféricos. Em seguida, foi feita a fusão das bandas multiespectrais (30 m) com a banda pancromática (15 m). Com base em composições RGB e inspeções de campo, definiram-se 15 classes de uso e cobertura do solo. Para a segmentação de bordas, aplicaram-se os limiares 10 e 60 para as configurações de segmentação e união no aplicativo ENVI. A classificação foi feita usando SVM e K-NN. Ambos os classificadores apresentaram elevados valores de índice Kappa (k): 0,92 para SVM e 0,86 para K-NN, significativamente diferentes entre si a 95% de probabilidade. Uma significativa melhoria foi observada para SVM, na classificação correta de diferentes tipologias florestais. A classificação orientada a objetos é amplamente aplicada em imagens de alta resolução espacial; no entanto, os resultados obtidos no presente trabalho mostram a robustez do método também para imagens de média resolução espacial.
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El uso de imágenes procedentes de sensores multiespectrales de resolución media como es el caso de Landsat TM ha sido ampliamente utilizado desde décadas para detectar, entre otras variables, el decaimiento y la defoliación provocada por plagas y enfermedades forestales. El presente trabajo evalúa la utilidad del uso de estas imágenes en la detección de rodales de pino laricio (Pinus nigra Arn.) y pino silvestre (Pinus sylvestris L.) afectados por escolítidos. El área de estudio se localizó en el Solsonés (prepirineo de Lleida) seleccionando 34 áreas de entrenamiento (17 rodales afectados por la plaga y 17 rodales sanos). El análisis exploratorio de las imágenes se realizó mediante el programa ERDAS® IMAGINE 8.x. Los resultados del estudio mostraron una significación espectral en 5 de las 7 bandas analizadas, siendo TM5 y TM7 las que mejor comportamiento presentaron. Los niveles digitales obtenidos y los espacios de características creados señalaron sendas tendencias al agrupamiento de rodales afectados versus sanos, consiguiéndose plantear mejoras en el procedimiento metodológico.
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El presente trabajo pretende la caracterización de la distribución espacial típica del cultivo de arroz en regadíos del valle del Ebro, donde la presencia del cultivo está ligada a la existencia de suelos salino-sódicos. Esta caracterización ha de permitir identificar las áreas donde es típica la presencia del cultivo año tras año y las áreas donde es frecuente su fluctuación debido tanto a condiciones variables de salinidad del suelo como a variabilidad en las condiciones de mercado. Para ello se ha recurrido al análisis de una serie temporal de mapas de cultivos (7 años) derivados de la clasificación supervisada de imágenes Landsat TM. La determinación de las áreas típicas y de fluctuación del cultivo de arroz se hace entonces a partir del análisis estadístico de clases, y mediante superposición espacial de coberturas en un entorno SIG-Raster.
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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 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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Changes in area of 30 small glaciers (mostly <1 km2) in the northern Polar Urals (67.5-68.25 °N) between 1953 and 2000 were assessed using historic aerial photography from 1953 and 1960, ASTER and panchromatic Landsat ETM+ imagery from 2000, and data from 1981 and 2008 terrestrial surveys. Changes in volume and geodetic mass balance of IGAN and Obruchev glaciers were calculated using data from terrestrial surveys in 1963 and 2008. In total, glacier area declined by 22.3 ± 3.9% in the 1953/60-2000 period. The areas of individual glaciers decreased by 4-46%. Surfaces of Obruchev and IGAN glaciers lowered by 22.5 ± 1.7 m and 14.9 ± 2.1 m. Over 45 years, geodetic mass balances of Obruchev and IGAN glaciers were -20.66 ± 2.91 and -13.54 ± 2.57 m w.e. respectively. Glacier shrinkage in the Polar Urals is related to a summer warming of 1 °C between 1953-81 and 1981-2008 and its rates are consistent with other regions of northern Asia but are higher than in Scandinavia. While glacier shrinkage intensified in the 1981-2000 period relative to 1953-81, increasing winter precipitation and shading effects slowed glacier wastage in 2000-08.
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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)