946 resultados para Satellite imagery data


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The coastal portions of Kangerdlugssuaq and Helheim glaciers in southeast Greenland lost at least 51 +/- 8 km(-3) yr(-1) of ice between 2001-2006 due to thinning and retreat, according to an analysis of sequential digital elevation models (DEMs) derived from stereo ASTER satellite imagery. The dominant contribution to this ice loss was dynamic thinning caused by the acceleration in flow of both glaciers. Peak rates of change, including thinning rates of similar to 90 m yr(-1), coincided with the rapid increases in flow speed. Extrapolation of the measured data to the ice divides yields an estimated combined catchment volume loss of similar to 122 +/- 30 km(-3) yr(-1), which accounts for half the total mass loss from the ice sheet reported in recent studies. These catchment-wide volume losses contributed similar to 0.31 +/- 0.07 mm yr(-1) to global sea level rise over the 5-year observation period with the coastal regions alone contributing at least 0.1 +/- 0.02 mm yr(-1).

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Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone health. The objective of this work was to determine if the structural attributes of savanna riparian zones in northern Australia can be detected from commercially available remotely sensed image data. Two QuickBird images and coincident field data covering sections of the Daly River and the South Alligator River - Barramundie Creek in the Northern Territory were used. Semi-variograms were calculated to determine the characteristic spatial scales of riparian zone features, both vegetative and landform. Interpretation of semi-variograms showed that structural dimensions of riparian environments could be detected and estimated from the QuickBird image data. The results also show that selecting the correct spatial resolution and spectral bands is essential to maximize the accuracy of mapping spatial characteristics of savanna riparian features. The distribution of foliage projective cover of riparian vegetation affected spectral reflectance variations in individual spectral bands differently. Pan-sharpened image data enabled small-scale information extraction (< 6 m) on riparian zone structural parameters. The semi-variogram analysis results provide the basis for an inversion approach using high spatial resolution satellite image data to map indicators of savanna riparian zone health.

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Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2) = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

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A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.

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A quasi-Poisson generalized linear model combined with a distributed lag non-linear model was used to quantify the main effect of temperature on emergency department visits (EDVs) for childhood diarrhea in Brisbane from 2001 to 2010. Residual of the model was checked to examine whether there was an added effect due to heat waves. The change over time in temperature-diarrhea relation was also assessed. Both low and high temperatures had significant impact on childhood diarrhea. Heat waves had an added effect on childhood diarrhea, and this effect increased with intensity and duration of heat waves. There was a decreasing trend in the main effect of heat on childhood diarrhea in Brisbane across the study period. Brisbane children appeared to have gradually adapted to mild heat, but they are still very sensitive to persistent extreme heat. Development of future heat alert systems should take the change in temperature-diarrhea relation over time into account.

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This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

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This paper presents a GPU implementation of normalized cuts for road extraction problem using panchromatic satellite imagery. The roads have been extracted in three stages namely pre-processing, image segmentation and post-processing. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, vegetation,. and fallow regions). The road regions are then extracted using the normalized cuts algorithm. Normalized cuts algorithm is a graph-based partitioning `approach whose focus lies in extracting the global impression (perceptual grouping) of an image rather than local features. For the segmented image, post-processing is carried out using morphological operations - erosion and dilation. Finally, the road extracted image is overlaid on the original image. Here, a GPGPU (General Purpose Graphical Processing Unit) approach has been adopted to implement the same algorithm on the GPU for fast processing. A performance comparison of this proposed GPU implementation of normalized cuts algorithm with the earlier algorithm (CPU implementation) is presented. From the results, we conclude that the computational improvement in terms of time as the size of image increases for the proposed GPU implementation of normalized cuts. Also, a qualitative and quantitative assessment of the segmentation results has been projected.

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QuickBird high resolution (2.8 m) satellite imagery was evaluated for distinguishing giant reed ( Arundo donax L.) infestations along the Rio Grande in southwest Texas. (PDF has 5 pages.)

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We used fifteen years (1993-2007) of altimetric data, combined from different missions (ERS-1/2, TOPEX/Poseidon, Jason-1, and Envisat), to analyze the variability of the eddy kinetic energy (EKE) in the South China Sea (SCS). We found that the EKE ranged from 64 cm(2)/s(2) to 1 390 cm(2)/s(2) with a mean value of 314 cm(2)/s(2). The highest EKE center was observed to the east of Vietnam (with a mean value of 509 cm(2)/s(2)) and the second highest EKE region was located to the southwest of Taiwan Island (with a mean value of 319 cm(2)/s(2)). We also found that the EKE structure is the consequence of the superposition of different variability components. First, interannual variability is important in the SCS. Spectral analysis of the EKE interannual signal (IA-EKE) shows that the main periodicities of the IA-EKE to the east of Vietnam, to the southwest of Taiwan Island, and in the SCS are 3.75, 1.87, and 3.75 years, respectively. It is to the south of Taiwan Island that the IA-EKE signal has the most obvious impact on EKE variability. In addition, the IA-EKE exhibit different trends in different regions. An obvious positive trend is observed along the east coast of Vietnam, while a negative trend is found to the southwest of Taiwan Island and in the east basin of Vietnam. Correlation analysis shows that the IA-EKE has an obvious negative correlation with the SSTA in Nio3 (5A degrees S-5A degrees N, 90A degrees W-150A degrees W). El Nio-Southern Oscillation (ENSO) affects the IA-EKE variability in the SCS through an atmospheric bridge-wind stress curl over the SCS. Second, the seasonal cycle is the most obvious timescale affecting EKE variability. The locations of the most remarkable EKE seasonal variabilities in the SCS are to the east of Vietnam, to the southwest of Taiwan, and to the west of Philippines. To the east of Vietnam, the seasonal cycle is the dominant mechanism controlling EKE variability, which is attributed primarily to the annual cycle there of wind stress curl. In this area, the maximum EKE is observed in autumn. To the southwest of Taiwan Island, the EKE is enlarged by the stronger SCS circulation, which is caused by the intrusion branch from the Kuroshio in winter. Finally, intra-annual and mesoscale variability, although less important than the former, cannot be neglected. The most obvious intra-annual and mesoscale variability, which may be the result of baroclinic instability of the background flow, are observed to the southwest of Taiwan Island. Sporadic events can have an important effect on EKE variability.

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11-year satellite altimeter sea surface height (SSH) anomaly data from January 1993 to December 2003 are used to present the dominant spatial patterns and temporal variations of the South China Sea (SCS) surface circulation through Empirical Orthogonal Function (EOF) analysis. The first three EOF modes show the obvious seasonal variations of SSH in the SCS. EOF mode one is generally characterized by a basin-wide circulation. Mode two describes the double-cell basin scale circulation structure. The two cells were located off west of the Luzon Island and southeast of Vietnam, respectively. EOF mode three presents the mesoscale eddy structure in the western SCS, which develops into a strong cyclonic eddy rapidly from July to September. EOF mode one and mode three are also embedded with interannual signals, indicating that the SCS surface circulation variation is influenced by El Nino events prominently. The strong El Nino of 1997/98 obviously changed the SCS circulation structure. This study also shows that there existed a series of mesoscale eddies in the western SCS, and their temporal variation indicates intra-seasonal and interannual signals.

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Thèse diffusée initialement dans le cadre d'un projet pilote des Presses de l'Université de Montréal/Centre d'édition numérique UdeM (1997-2008) avec l'autorisation de l'auteur.