78 resultados para SRTM


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In September-October 1982, the Soviet ship "Sebastopolsky Rybak" conducted a cruise on the Sofala Bank in the area between 16°20'S and parallel 19°40'S. Two surveys were made, one from South to North (depth 10-110 meters) and vice versa. The type of coverage used was systematic. The Sofala Bank was divided into seven sub-areas. During this cruise sub-areas 3 and 4 were covered. Sub-area 5 has not been fully covered.

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During the last 4 months of 1982, two research cruises had been carried out at the Sofala Bank by the SRTM "Sevastopolsky Rybak". The authors analyze and compare data on biological characteristics, sexual maturity and localization of Penaeus indicus and Metapenaeus monoceros.

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From November 18th to December 17th 1982, the SRTM "Sebastopolsky Rybak" carried out research cruises on the Sofala Bank in the area between 16°20'S and parallel 19°40'S. The authors analyze data collected on biological characteristics, sexual maturity and localization of Penaeus indicus, Metapenaeus monoceros, Penaeus japonicus, Penaeus monodon and Penaeus latisulcatus.

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为了检验航天飞机雷达地形测绘使命(SRTM)生产的数字高程数据在地表水文模拟分析中的应用效果,以贵州省内清水江流域为例,利用ArcHydroTools以CGIAR-CSI SRTM90m数据和国家基础地理信息系统1:400万数字水系图为数捌源,进行了流域地表水文模拟。分析结果表明:以CGIAR-CSI SRTM 90m数据为基础提取的数字河网的空间分布与实际情况十分接近,提取的数字流域界线与水文部门基本相符,说明CGIAR-CSI SRTM 90m数据在数字地形分析的诸多领域,特别是地表水文模拟分析方面必将有着十分广泛的应用前景.

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The shuttle radar topography mission (SRTM), was flow on the space shuttle Endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60 degrees north latitude and 56 degrees south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc-second (similar to 30m) for areas within the USA and at 3 arc-second (similar to 90m) resolution for the rest of the world. A resolution of 90m can be considered suitable for the small or medium-scale analysis, but it is too coarse for more detailed purposes. One alternative is to interpolate the SRTM data at a finer resolution; it will not increase the level of detail of the original digital elevation model (DEM), but it will lead to a surface where there is the coherence of angular properties (i.e. slope, aspect) between neighbouring pixels, which is an important characteristic when dealing with terrain analysis. This work intents to show how the proper adjustment of variogram and kriging parameters, namely the nugget effect and the maximum distance within which values are used in interpolation, can be set to achieve quality results on resampling SRTM data from 3"" to 1"". We present for a test area in western USA, which includes different adjustment schemes (changes in nugget effect value and in the interpolation radius) and comparisons with the original 1"" model of the area, with the national elevation dataset (NED) DEMs, and with other interpolation methods (splines and inverse distance weighted (IDW)). The basic concepts for using kriging to resample terrain data are: (i) working only with the immediate neighbourhood of the predicted point, due to the high spatial correlation of the topographic surface and omnidirectional behaviour of variogram in short distances; (ii) adding a very small random variation to the coordinates of the points prior to interpolation, to avoid punctual artifacts generated by predicted points with the same location than original data points and; (iii) using a small value of nugget effect, to avoid smoothing that can obliterate terrain features. Drainages derived from the surfaces interpolated by kriging and by splines have a good agreement with streams derived from the 1"" NED, with correct identification of watersheds, even though a few differences occur in the positions of some rivers in flat areas. Although the 1"" surfaces resampled by kriging and splines are very similar, we consider the results produced by kriging as superior, since the spline-interpolated surface still presented some noise and linear artifacts, which were removed by kriging.

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Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.

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As informações topográficas existentes para o território brasileiro, na escala 1:100.000, cobrem apenas 75,39% da área nacional, restando ainda imensos vazios cartográficos, principalmente na região Amazônica. Essas informações eram oriundas de métodos de restituição aerofotogramétricas, aplicados em fotos aéreas das décadas de 60 a 80. Devido à grande complexidade dos métodos empregados e a outros problemas de ordem técnico-financeira, grande parte das cartas plani-altimétricas está desatualizada, fato que compromete a utilização das mesmas. Atualmente, as informações topográficas são largamente extraídas a partir de modelos digitais de elevação, como por exemplo, as imagens do Shuttle Radar Topography Mission (SRTM). Neste trabalho, o modelo de elevação do SRTM foi analisado com base no Padrão de Exatidão Cartográfica (PEC) altimétrico, na atualização altimétrica da carta Plani-altimétrica Salinópolis do ano de 1982. A análise do PEC altimétrico do SRTM referente à região de Salinópolis, revelou que o mesmo pode ser utilizado na escala 1:50.000 classe C e escala 1:100.000 classe A. Já que as imagens SRTM são compatíveis com a escala e classe da carta Salinópolis, utilizou-se a versão original do SRTM (90 metros resolução espacial) para atualização altimétrica da carta Salinópolis e imagens TM Landsat-5, como base planimétrica, seguindo os parâmetros adotados pelo Instituto Brasileiro de Geografia e Estatística. Com a atualização da carta constatou-se várias diferenças, principalmente em relação à planimetria. A atualização das cartas é de grande importância, principalmente em regiões costeiras, devido à dinâmica e intensidade dos diferentes processos naturais e antrópicos atuantes, além disso, esta metodologia pode servir de base para a atualização de outras cartas e até mesmo a geração de novas cartas em locais de vazios cartográficos, resolvendo assim a questão da falta de informação topográfica em determinadas escalas. Palavras-chave: SRTM, atualização cartográfica, carta plani-altimétrica, Amazônia.

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Este estudo apresenta a estimativa dos parâmetros florísticos e estruturais (determinação da espécie, altura, diâmetro a altura do Peito - DAP e biomassa) do mangue a partir de informações da superfície adquiridas remotamente com os sensores Laser Detection and Range (LIDAR), Shuttle Radar Topography Mission (SRTM) e ortofotos na Ilha dos Guarás, conjunto de arquipélagos localizado a 30 km da desembocadura do rio amazonas. Para esse trabalho foram utilizadas informações do SRTM, LIDAR e fotografias aéreas processadas e ortorretificadas durante dois sobrevôos realizados entre o mês de julho e agosto de 2011. Com a ortofoto foi feito o mapa do reconhecimento de unidades geobotânicas que delimitou apenas a classe mangue. Em seguida, foi realizada a correção da altura elipsoidal para a altura ortométrica, onde a nuvem de pontos foi interpolada pelo método vizinho mais próximo, gerando Modelo Digital de Elevação (MDE) LIDAR (full points) com RMSE de 0,88 cm e por meio de uma linguagem macro foi estatisticamente separadas as informações do último pulso da superfície, conhecido também por ground points. Em seguida, os dados foram interpolados pelo método de krigeagem que gerou o valor de Modelo Digital de Superfície (MDS), o qual foi subtraído do MDE. Com base no Modelo Digital de Vegetação (MDV) foram definidos os sítios de coleta e selecionadas as árvores ascendentes, intermediárias e emergentes, porte no qual foi medido o DAP e altura. No total foram coletadas 212 amostras individuais de mangue e para assegurar o nível de acurácia do conjunto coletado, foi realizado o cálculo de RMSE entre as alturas do LIDAR e Campo, que resultou em RMSE= 1,10 m. Os modelos escolhidos para calibração LIDAR e altura de campo foi do tipo linear, com R2 = 91% e RMSE= 0,98 cm e para calibração da DAP e altura de campo foi escolhido o modelo Logarítmico R2 = 74,1%. Nos resultados da calibração do SRTM o modelo logarítmico também foi o mais adequado para a relação entre altura média e SRTM com R2 = 91% e RMSE de 2,2 m e DAP Médio e SRTM, com R2 = 88% e RMSE 2,2 cm. A partir de um inventário foi realizada a estimativa da biomassa por espécie por meio das equações alométricas de Fromard e posteriormente os resultados foram espacializados em forma de mapas com alto nível de detalhamento oriundo das informações LIDAR e SRTM corrigido e ortofotos.

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We produced a landscape scale map of mean tree height in mangrove forests in Everglades National Park (ENP) using the elevation data from the Shuttle Radar Topography Mission (SRTM). The SRTM data was calibrated using airborne lidar data and a high resolution USGS digital elevation model (DEM). The resulting mangrove height map has a mean tree height error of 2.0 m (RMSE) over a pixel of 30 m. In addition, we used field data to derive a relationship between mean forest stand height and biomass in order to map the spatial distribution of standing biomass of mangroves for the entire National Park. The estimation showed that most of the mangrove standing biomass in the ENP resides in intermediate- height mangrove stands around 8 m. We estimated the total mangrove standing biomass in ENP to be 5.6 X 109 kg.

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Floods are among the most devastating events that affect primarily tropical, archipelagic countries such as the Philippines. With the current predictions of climate change set to include rising sea levels, intensification of typhoon strength and a general increase in the mean annual precipitation throughout the Philippines, it has become paramount to prepare for the future so that the increased risk of floods on the country does not translate into more economic and human loss. Field work and data gathering was done within the framework of an internship at the former German Technical Cooperation (GTZ) in cooperation with the Local Government Unit of Ormoc City, Leyte, The Philippines, in order to develop a dynamic computer based flood model for the basin of the Pagsangaan River. To this end, different geo-spatial analysis tools such as PCRaster and ArcGIS, hydrological analysis packages and basic engineering techniques were assessed and implemented. The aim was to develop a dynamic flood model and use the development process to determine the required data, availability and impact on the results as case study for flood early warning systems in the Philippines. The hope is that such projects can help to reduce flood risk by including the results of worst case scenario analyses and current climate change predictions into city planning for municipal development, monitoring strategies and early warning systems. The project was developed using a 1D-2D coupled model in SOBEK (Deltares Hydrological modelling software package) and was also used as a case study to analyze and understand the influence of different factors such as land use, schematization, time step size and tidal variation on the flood characteristics. Several sources of relevant satellite data were compared, such as Digital Elevation Models (DEMs) from ASTER and SRTM data, as well as satellite rainfall data from the GIOVANNI server (NASA) and field gauge data. Different methods were used in the attempt to partially calibrate and validate the model to finally simulate and study two Climate Change scenarios based on scenario A1B predictions. It was observed that large areas currently considered not prone to floods will become low flood risk (0.1-1 m water depth). Furthermore, larger sections of the floodplains upstream of the Lilo- an’s Bridge will become moderate flood risk areas (1 - 2 m water depth). The flood hazard maps created for the development of the present project will be presented to the LGU and the model will be used to create a larger set of possible flood prone areas related to rainfall intensity by GTZ’s Local Disaster Risk Management Department and to study possible improvements to the current early warning system and monitoring of the basin section belonging to Ormoc City; recommendations about further enhancement of the geo-hydro-meteorological data to improve the model’s accuracy mainly on areas of interest will also be presented at the LGU.

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Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.