948 resultados para areal radar rainfall
Resumo:
Pneumothoraces (PTXs) are a common entity in thoracic trauma. Micropower impulse radar (MIR) has been able to detect PTXs in surgical patients. However, this technology has not been tested previously on trauma patients. The purpose of this study was to determine the sensitivity and specificity of MIR to detect clinically significant PTXs. We hypothesized that MIR technology can effectively screen trauma patients for clinically significant PTXs.
Resumo:
BACKGROUND: Pneumothoraces are a common injury pattern in emergency medicine. Rapid and safe identification can reduce morbidity and mortality. A new handheld, battery powered device, the Pneumoscan (CE 561036, PneumoSonics Inc., Cleveland, OH, USA), using micropower impulse radar (MIR) technology, has recently been introduced in Europe for the rapid and reliable detection of PTX. However, this technology has not yet been tested in trauma patients. This is the first quality control evaluation to report on emergency room performance of a new device used in the trauma setting. MATERIAL AND METHODS: This study was performed at a Level I trauma centre in Switzerland. All patients with thoracic trauma and undergoing chest X-ray and CT-scan were eligible for the study. Readings were performed before the chest X-ray and CT scan. The patients had eight lung fields tested (four on each side). All readings with the Pneumoscan were performed by two junior residents in our department who had previously received an instructional tutorial of 15min. The qualitative MIR results were blinded, and stored on the device. We then compared the results of the MIR to those of the clinical examination, chest X-ray and CT-scan. RESULTS: 50 patients were included, with a mean age of 46 (SD 17) years. Seven patients presented with PTX diagnosed by CT; six of these were detected by Pneumoscan, leading to an overall sensitivity of 85.7 (95% confidence interval 42.1-99.6)%. Only two of seven PTX were found during clinical examination and on chest X-ray (sensitivity 28.6 (95% CI 3.7-71.0)%). Of the remaining 43 of 50 patients without PTX, one false-positive PTX was found by the Pneumoscan, resulting in a specificity of 97.7 (95% CI 87.7-99.9)%. DISCUSSION: The Pneumoscan is an easy to use handheld technology with reliable results. In this series, the sensitivity to detect a PTX by the Pneumoscan was higher than by clinical examination and chest X-ray. Further studies with higher case numbers and a prospective study design are needed to confirm our findings.
Resumo:
Water held in the unsaturated zone is important for agriculture and construction and is replenished by infiltrating rainwater. Monitoring the soil water content of clay soils using ground-penetrating radar (GPR) has not been researched, as clay soils cause attenuation of GPR signal. In this study, GPR common-midpoint soundings (CMPs) are used in the clayey soils of the Miller Run floodplain to monitor changes in the soil water content (SWC) before and after rainfall events. GPR accomplishes this task because increases in water content will increase the dielectric constant of the subsurface material, and decrease the velocity of the GPR wave. Using an empirical relationship between dielectric constant and SWC, the Topp relation, we are able to calculate a SWC from these velocity measurements. Non-invasive electromagnetics, resistivity, and seismic were performed, and from these surveys, the layering at the field site was delineated. EM characterized the horizontal variation of the soil, allowing us to target the most clay rich area. At the CMP location, resistivity indicates the vertical structure of the subsurface consists of a 40 cm thick layer with a resistivity of 100 ohm*m. Between 40 cm and 1.5 m is a layer with a resistivity of 40 ohm*m. The thickness estimates were confirmed with invasive auger and trenching methods away from the CMP location. GPR CMPs were collected relative to a July 2013 and September 2013 storm. The velocity observations from the CMPs had a precision of +/- 0.001 m/ns as assessed by repeat analysis. In the case of both storms, the GPR data showed the expected relationship between the rainstorms and calculated SWC, with the SWC increasing sharply after the rainstorm and decreasing as time passed. We compared these data to auger core samples collected at the same time as the CMPs were taken, and the volumetric analysis of the cores confirmed the trend seen in the GPR, with SWC values between 3 and 5 percent lower than the GPR estimates. Our data shows that we can, with good precision, monitor changes in the SWC of conductive soils in response to rainfall events, despite the attenuation induced by the clay.
Resumo:
Icy debris fans have are newly-described landforms (Kochel and Trop, 2008 and 2012) as landforms developed immediately after deglaciation on Earth and similar features have been observed on Mars. Subsurface characteristics of Icy debris fans have not been previously investigated. Ground penetrating radar (GPR) was used to non-invasively investigate the subsurface characteristics of icy debris fans near McCarthy, Alaska, USA. The three fans investigated in Alaska are the East, West, and Middle fans (Kochel and Trop, 2008 and 2012) which below the Nabesna ice cap and on top of the McCarthy Creek Glacier. Icy debris fans in general are a largely unexplored suite of paraglacial landforms and processes in alpine regions. Recent field studies focused on direct observations and depositional processes. Their results showed that the fan's composition is primarily influenced by the type and frequency of depositional processes that supply the fan. Photographic studies show that the East Fan receives far more ice and snow avalanches whereas the Middle and West Fans receive fewer mass wasting events but more clastic debris is deposited on the Middle and West fan from rock falls and icy debris flows. GPR profiles and Wide-angle reflection and refraction (WARR) surveys consisting of both, common mid-point (CMP), and common shot-point (CSP) surveys investigated the subsurface geometry of the fans and the McCarthy Creek Glacier. All GPR surveys were collected in July of 2013 with 100MHz bi-static antennas. Four axial profiles and three cross-fan profiles were done on the West and Middle fans as well as the McCarthy Creek Glacier in order to investigate the relationship between the three features. GPR profiles yielded reflectors that were continuous for 10+ m and hyperbolic reflections in the subsurface. The depth to these reflections in the subsurface requires knowledge of the velocity of the subsurface. To find the velocity of the subsurface eight WARR surveys collected on the fans and on the McCarthy Creek glacier to provide information on variability of subsurface velocities. The profiles of the Middle and West fan have more reflections in their profiles compared to profiles done on the McCarthy Creek Glacier. Based on the WARR surveys, we interpret the lower energy return in the glacier to be caused by two reasons. 1) The increased attenuation due to wet ice versus drier ice and on the fan with GPR velocities >0.15m/ns. 2) Lack of interfaces in the glacier compared to those in the fans which are inferred to be produced by the alternating layers of stratified ice and lithic-rich layers. The GPR profiles on the West and Middle Fans show the shallow subsurface being dominated by lenticular reflections interpreted to be consistent with the shape of surficial deposits. The West Fan is distinguished from the Middle Fan by the nature of its reflections patterns and thicknesses of reflection packages that clearly shows the Middle fan with a greater thickness. The changes in subsurface reflections between the Middle and West Fans as well as the McCarthy Creek Glacier are thought to reflect the type and frequency of depositional processes and surrounding bedrock and talus slopes.
Resumo:
The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.
Resumo:
In 1998-2001 Finland suffered the most severe insect outbreak ever recorded, over 500,000 hectares. The outbreak was caused by the common pine sawfly (Diprion pini L.). The outbreak has continued in the study area, Palokangas, ever since. To find a good method to monitor this type of outbreaks, the purpose of this study was to examine the efficacy of multi-temporal ERS-2 and ENVISAT SAR imagery for estimating Scots pine (Pinus sylvestris L.) defoliation. Three methods were tested: unsupervised k-means clustering, supervised linear discriminant analysis (LDA) and logistic regression. In addition, I assessed if harvested areas could be differentiated from the defoliated forest using the same methods. Two different speckle filters were used to determine the effect of filtering on the SAR imagery and subsequent results. The logistic regression performed best, producing a classification accuracy of 81.6% (kappa 0.62) with two classes (no defoliation, >20% defoliation). LDA accuracy was with two classes at best 77.7% (kappa 0.54) and k-means 72.8 (0.46). In general, the largest speckle filter, 5 x 5 image window, performed best. When additional classes were added the accuracy was usually degraded on a step-by-step basis. The results were good, but because of the restrictions in the study they should be confirmed with independent data, before full conclusions can be made that results are reliable. The restrictions include the small size field data and, thus, the problems with accuracy assessment (no separate testing data) as well as the lack of meteorological data from the imaging dates.