WorldWideScience

Sample records for satellite detects record

  1. Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity

    Directory of Open Access Journals (Sweden)

    S. A. Henson

    2010-02-01

    Full Text Available Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR. We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years. Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

  2. Detecting potential ship objects from satellite pictures

    International Nuclear Information System (INIS)

    Luo, B.; Yang, C.C.; Chang, S.K.; Yang, M.C.K.

    1984-01-01

    Heuristic techniques are presented to detect potential ship objects from satellite pictures. These techniques utilize some noise structures of the pixel gray levels, and certain inherent features of a ship in a satellite picture. The scheme has been implemented and successfully tested on SEASAT satellite pictures. A general approach for database-oriented object detection is also suggested

  3. Sustained Satellite Missions for Climate Data Records

    Science.gov (United States)

    Halpern, David

    2012-01-01

    Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

  4. Review of Tracktable for Satellite Maneuver Detection

    Energy Technology Data Exchange (ETDEWEB)

    Acquesta, Erin C.S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Valicka, Christopher G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hinga, Mark B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ehn, Carollan Beret [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    As a tool developed to translate geospatial data into geometrical descriptors, Tracktable offers a highly efficient means to detect anomalous flight and maritime behavior. Following the success of using geometrical descriptors for detecting anomalous trajectory behavior, the question of whether Tracktable could be used to detect satellite maneuvers arose. In answering this question, this re- port will introduce a brief description of how Tracktable has been used in the past, along with an introduction to the fundamental properties of astrodynamics for satellite trajectories. This will then allow us to compare the two problem spaces, addressing how easily the methods used by Tracktable will translate to orbital mechanics. Based on these results, we will then be able to out- line the current limitations as well as possible path forward for using Tracktable to detect satellite maneuvers.

  5. A near real-time satellite-based global drought climate data record

    International Nuclear Information System (INIS)

    AghaKouchak, Amir; Nakhjiri, Navid

    2012-01-01

    Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

  6. Detection of jet contrails from satellite images

    Science.gov (United States)

    Meinert, Dieter

    1994-02-01

    In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.

  7. Feature Detection Systems Enhance Satellite Imagery

    Science.gov (United States)

    2009-01-01

    In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid

  8. How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

    Science.gov (United States)

    Weatherhead, Elizabeth C.; Harder, Jerald; Araujo-Pradere, Eduardo A.; Bodeker, Greg; English, Jason M.; Flynn, Lawrence E.; Frith, Stacey M.; Lazo, Jeffrey K.; Pilewskie, Peter; Weber, Mark; Woods, Thomas N.

    2017-12-01

    Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr-1 uncertainty (0.00008 W m-2 nm-1 yr-1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly

  9. Satellite Climate Data Records: Development, Applications, and Societal Benefits

    Directory of Open Access Journals (Sweden)

    Wenze Yang

    2016-04-01

    Full Text Available This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs in the context of transitioning research to operation (R2O. Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs, Thematic CDRs (TCDRs, Interim CDRs (ICDRs, and climate information records (CIRs are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset.

  10. Propagation Characteristics of Electromagnetic Waves Recorded by the Four CLUSTER Satellites

    International Nuclear Information System (INIS)

    Parrot, M.; Santolik, O.; Cornilleau-Wehrlin, N.; Maksimovic, M.; Harvey, Ch.

    2001-01-01

    This paper will describe the methods we use to determine the propagation characteristics of electromagnetic waves observed by the four CLUSTER satellites. The data is recorded aboard CLUSTER by the STAFF (Spatio-Temporal Analysis of Field Fluctuations) spectrum analyser. This instrument has several modes of operation, and can provide the spectral matrix of three magnetic and two electric components. This spectral matrix is processed by a dedicated software (PRASSADCO: Propagation Analysis of STAFF-SA Data with Coherency Tests) in order to determine the wave normal directions with respect to the DC magnetic field. PRASSADCO also provides a number of alternative methods to estimate wave polarisation and propagation parameters, such as the Poynting vector, and the refractive index. It is therefore possible to detect the source extension of various electromagnetic waves using the 4 satellites. Results of this data processing will be shown here for one event observed by one satellite. (author)

  11. Applying Metrological Techniques to Satellite Fundamental Climate Data Records

    Science.gov (United States)

    Woolliams, Emma R.; Mittaz, Jonathan PD; Merchant, Christopher J.; Hunt, Samuel E.; Harris, Peter M.

    2018-02-01

    Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels.

  12. Target Detection Based on EBPSK Satellite Passive Radar

    Directory of Open Access Journals (Sweden)

    Lu Zeyuan

    2015-05-01

    Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.

  13. Detecting aircrafts from satellite images using saliency and conical ...

    Indian Academy of Sciences (India)

    Samik Banerjee

    automatically detect all kinds of interesting targets in satellite images. .... which is used for text and image categorization, has been also introduced for object ...... 3.4 GHz processor, 32 GB RAM and Windows 7 (64 bit). Operating System. 6.

  14. Satellite sar detection of hurricane helene (2006)

    DEFF Research Database (Denmark)

    Ju, Lian; Cheng, Yongcun; Xu, Qing

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined. ...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

  15. Rapid response flood detection using the MSG geostationary satellite

    DEFF Research Database (Denmark)

    Proud, Simon Richard; Fensholt, Rasmus; Rasmussen, Laura Vang

    2011-01-01

    A novel technique for the detection of flooded land using satellite data is presented. This new method takes advantage of the high temporal resolution of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) series of satellites to derive several p...... of data gathered during the 2009 flooding events in West Africa shows that the presented method can detect floods of comparable size to the SEVIRI pixel resolution on a short timescale, making it a valuable tool for large scale flood mapping....

  16. Analysis of raw AIS spectrum recordings from a LEO satellite

    DEFF Research Database (Denmark)

    Larsen, Jesper Abildgaard; Mortensen, Hans Peter

    2014-01-01

    The AAUSAT3 satellite is a 1U cubesat, which has been developed by students at Aalborg University, Denmark in collaboration with the Danish Maritime Authority. The satellite was launched in February 2013 on a mission to monitor ships from space using their AIS broadcast signals as an indication...... of position. The SDR receiver developed to listen for these AIS signals also allows for sampling and storing of the raw intermediate frequency spectrum, which has been used in order to map channel utilization over the areas of interest for the mission, which is mainly the arctic regions. The SDR based...... receiver used onboard the satellite is using a single chip front-end solution, which down converts the AIS signal located around 162 MHz into an intermediate frequency, with a up to 200 kHz bandwidth. This I/F signal is sampled with a 750 kSPS A/D converter and further processed by an Analog Devices DSP...

  17. Rain detection over land surfaces using passive microwave satellite data

    NARCIS (Netherlands)

    Bauer, P.; Burose, D.; Schulz, J.

    2002-01-01

    An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

  18. Tile Drainage Expansion Detection using Satellite Soil Moisture Dynamics

    Science.gov (United States)

    Jacobs, J. M.; Cho, E.; Jia, X.

    2017-12-01

    In the past two decades, tile drainage installation has accelerated throughout the Red River of the North Basin (RRB) in parts of western Minnesota, eastern North Dakota, and a small area of northeastern South Dakota, because the flat topography and low-permeability soils in this region necessitated the removal of excess water to improve crop production. Interestingly, streamflow in the Red River has markedly increased and six of 13 major floods during the past century have occurred since the late 1990s. It has been suggested that the increase in RRB flooding could be due to change in agricultural practices, including extensive tile drainage installation. Reliable information on existing and future tile drainage installation is greatly needed to capture the rapid extension of tile drainage systems and to locate tile drainage systems in the north central U.S. including the RRB region. However, there are few reliable data of tile drainage installation records, except tile drainage permit records in the Bois de Sioux watershed (a sub-basin in southern part of the RRB where permits are required for tile drainage installation). This study presents a tile drainage expansion detection method based on a physical principle that the soil-drying rate may increase with increasing tile drainage for a given area. In order to capture the rate of change in soil drying rate with time over entire RRB (101,500 km2), two satellite-based microwave soil moisture records from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and AMSR2 were used during 2002 to 2016. In this study, a sub-watershed level (HUC10) potential tile drainage growth map was developed and the results show good agreement with tile drainage permit records of six sub-watersheds in the Bois de Sioux watershed. Future analyses will include improvement of the potential tile drainage map through additional information using optical- and thermal-based sensor products and evaluation of its

  19. Analysis of GPS Satellite Allocation for the United States Nuclear Detonation Detection System (USNDS)

    National Research Council Canada - National Science Library

    Bell, Aaron

    2002-01-01

    ...) satellites to detect atmospheric nuclear detonations. Though there are currently over 24 operational GPS satellites, USNDS ground based antennas are only capable of actively monitoring 24 satellites at a time...

  20. An Automatic Cloud Detection Method for ZY-3 Satellite

    Directory of Open Access Journals (Sweden)

    CHEN Zhenwei

    2015-03-01

    Full Text Available Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly.

  1. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  2. Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

    Science.gov (United States)

    Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

    2012-01-01

    With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

  3. Landslide detection using very high-resolution satellite imageries

    Science.gov (United States)

    Suga, Yuzo; Konishi, Tomohisa

    2012-10-01

    The heavy rain induced by the 12th typhoon caused landslide disaster at Kii Peninsula in the middle part of Japan. We propose a quick response method for landslide disaster mapping using very high resolution (VHR) satellite imageries. Especially, Synthetic Aperture Radar (SAR) is effective because it has the capability of all weather and day/night observation. In this study, multi-temporal COSMO-SkyMed imageries were used to detect the landslide areas. It was difficult to detect the landslide areas using only backscatter change pattern derived from pre- and post-disaster COSMOSkyMed imageries. Thus, the authors adopted a correlation analysis which the moving window was selected for the correlation coefficient calculation. Low value of the correlation coefficient reflects land cover change between pre- and post-disaster imageries. This analysis is effective for the detection of landslides using SAR data. The detected landslide areas were compared with the area detected by EROS-B high resolution optical image. In addition, we have developed 3D viewing system for geospatial visualizing of the damaged area using these satellite image data with digital elevation model. The 3D viewing system has the performance of geographic measurement with respect to elevation height, area and volume calculation, and cross section drawing including landscape viewing and image layer construction using a mobile personal computer with interactive operation. As the result, it was verified that a quick response for the detection of landslide disaster at the initial stage could be effectively performed using optical and SAR very high resolution satellite data by means of 3D viewing system.

  4. Sensor fault detection and recovery in satellite attitude control

    Science.gov (United States)

    Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

    2018-04-01

    This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

  5. Satellite-detected fluorescence reveals global physiology of ocean phytoplankton

    Directory of Open Access Journals (Sweden)

    M. J. Behrenfeld

    2009-05-01

    Full Text Available Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

  6. A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-09-01

    Full Text Available This study presents a method for adjusting long-term climate data records (CDRs for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS. Recently, a 23-year long (1983–2005 continuous SIS CDR has been generated based on the visible channel (0.45–1 μm of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF. Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005 and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present was applied that combines the Standard Normal Homogeneity Test (SNHT and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN and about 50 stations of the Global Energy Balance Archive (GEBA over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of

  7. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  8. Detecting weather radar clutter using satellite-based nowcasting products

    DEFF Research Database (Denmark)

    Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

    2006-01-01

    This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

  9. Processing Satellite Imagery To Detect Waste Tire Piles

    Science.gov (United States)

    Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

    2007-01-01

    A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

  10. LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. Tom

    2018-05-01

    Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  11. Lake Ice Detection in Low-Resolution Optical Satellite Images

    Science.gov (United States)

    Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

    2018-05-01

    Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  12. The ESA climate change initiative: Satellite data records for essential climate variables

    DEFF Research Database (Denmark)

    Hollmann, R.; Merchant, C.J.; Saunders, R.

    2013-01-01

    The European Space Agency (ESA) has launched the Climate Change Initiative (CCI) to provide satellite-based climate data records (CDRs) that meet the challenging requirements of the climate community. The aim is to realize the full potential of the long-term Earth observation (EO) archives...... that both ESA and third parties have established. This includes aspects of producing a CDR, which involve data acquisition, calibration, algorithm development, validation, maintenance, and provision of the data to the climate research community. The CCI is consistent with several international efforts...... targeting the generation of satellite derived climate data records. One focus of the CCI is to provide products for climate modelers who increasingly use satellite data to initialize, constrain, and validate models on a wide range of space and time scales....

  13. Volumetric Forest Change Detection Through Vhr Satellite Imagery

    Science.gov (United States)

    Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

    2016-06-01

    Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

  14. Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

    Science.gov (United States)

    Gregg, Watson

    2011-01-01

    The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected

  15. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  16. A Satellite-Based Sunshine Duration Climate Data Record for Europe and Africa

    Directory of Open Access Journals (Sweden)

    Steffen Kothe

    2017-05-01

    Full Text Available Besides 2 m - temperature and precipitation, sunshine duration is one of the most important and commonly used parameter in climatology, with measured time series of partly more than 100 years in length. EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF presents a climate data record for daily and monthly sunshine duration (SDU for Europe and Africa. Basis for the advanced retrieval is a highly resolved satellite product of the direct solar radiation from measurements by Meteosat satellites 2 to 10. The data record covers the time period 1983 to 2015 with a spatial resolution of 0.05° × 0.05°. The comparison against ground-based data shows high agreement but also some regional differences. Sunshine duration is overestimated by the satellite-based data in many regions, compared to surface data. In West and Central Africa, low clouds seem to be the reason for a stronger overestimation of sunshine duration in this region (up to 20% for monthly sums. For most stations, the overestimation is low, with a bias below 7.5 h for monthly sums and below 0.4 h for daily sums. A high correlation of 0.91 for daily SDU and 0.96 for monthly SDU also proved the high agreement with station data. As SDU is based on a stable and homogeneous climate data record of more than 30 years length, it is highly suitable for climate applications, such as trend estimates.

  17. Noise detection in heart sound recordings.

    Science.gov (United States)

    Zia, Mohammad K; Griffel, Benjamin; Fridman, Vladimir; Saponieri, Cesare; Semmlow, John L

    2011-01-01

    Coronary artery disease (CAD) is the leading cause of death in the United States. Although progression of CAD can be controlled using drugs and diet, it is usually detected in advanced stages when invasive treatment is required. Current methods to detect CAD are invasive and/or costly, hence not suitable as a regular screening tool to detect CAD in early stages. Currently, we are developing a noninvasive and cost-effective system to detect CAD using the acoustic approach. This method identifies sounds generated by turbulent flow through partially narrowed coronary arteries to detect CAD. The limiting factor of this method is sensitivity to noises commonly encountered in the clinical setting. Because the CAD sounds are faint, these noises can easily obscure the CAD sounds and make detection impossible. In this paper, we propose a method to detect and eliminate noise encountered in the clinical setting using a reference channel. We show that our method is effective in detecting noise, which is essential to the success of the acoustic approach.

  18. Interference and deception detection technology of satellite navigation based on deep learning

    Science.gov (United States)

    Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

    2017-10-01

    Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

  19. Ice Sheet Change Detection by Satellite Image Differencing

    Science.gov (United States)

    Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

    2010-01-01

    Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

  20. Gridded sunshine duration climate data record for Germany based on combined satellite and in situ observations

    Science.gov (United States)

    Walawender, Jakub; Kothe, Steffen; Trentmann, Jörg; Pfeifroth, Uwe; Cremer, Roswitha

    2017-04-01

    The purpose of this study is to create a 1 km2 gridded daily sunshine duration data record for Germany covering the period from 1983 to 2015 (33 years) based on satellite estimates of direct normalised surface solar radiation and in situ sunshine duration observations using a geostatistical approach. The CM SAF SARAH direct normalized irradiance (DNI) satellite climate data record and in situ observations of sunshine duration from 121 weather stations operated by DWD are used as input datasets. The selected period of 33 years is associated with the availability of satellite data. The number of ground stations is limited to 121 as there are only time series with less than 10% of missing observations over the selected period included to keep the long-term consistency of the output sunshine duration data record. In the first step, DNI data record is used to derive sunshine hours by applying WMO threshold of 120 W/m2 (SDU = DNI ≥ 120 W/m2) and weighting of sunny slots to correct the sunshine length between two instantaneous image data due to cloud movement. In the second step, linear regression between SDU and in situ sunshine duration is calculated to adjust the satellite product to the ground observations and the output regression coefficients are applied to create a regression grid. In the last step regression residuals are interpolated with ordinary kriging and added to the regression grid. A comprehensive accuracy assessment of the gridded sunshine duration data record is performed by calculating prediction errors (cross-validation routine). "R" is used for data processing. A short analysis of the spatial distribution and temporal variability of sunshine duration over Germany based on the created dataset will be presented. The gridded sunshine duration data are useful for applications in various climate-related studies, agriculture and solar energy potential calculations.

  1. Long-term Satellite Observations of Cloud and Aerosol Radiative Effects Using the (A)ATSR Satellite Data Record

    Science.gov (United States)

    Christensen, M.; McGarragh, G.; Thomas, G.; Povey, A.; Proud, S.; Poulsen, C. A.; Grainger, R. G.

    2016-12-01

    Radiative forcing by clouds, aerosols, and their interactions constitute some of the largest sources of uncertainties in the climate system (Chapter 7 IPCC, 2013). It is essential to understand the past through examination of long-term satellite observation records to provide insight into the uncertainty characteristics of these radiative forcers. As part of the ESA CCI (Climate Change Initiative) we have recently implemented a broadband radiative flux algorithm (known as BUGSrad) into the Optimal Retrieval for Aerosol and Cloud (ORAC) scheme. ORAC achieves radiative consistency of its aerosol and cloud products through an optimal estimation scheme and is highly versatile, enabling retrievals for numerous satellite sensors: ATSR, MODIS, VIIRS, AVHRR, SLSTR, SEVIRI, and AHI. An analysis of the 17-year well-calibrated Along Track Scanning Radiometer (ATSR) data is used to quantify trends in cloud and aerosol radiative effects over a wide range of spatiotemporal scales. The El Niño Southern Oscillation stands out as the largest contributing mode of variability to the radiative energy balance (long wave and shortwave fluxes) at the top of the atmosphere. Furthermore, trends in planetary albedo show substantial decreases across the Arctic Ocean (likely due to the melting of sea ice and snow) and modest increases in regions dominated by stratocumulus (e.g., off the coast of California) through notable increases in cloud fraction and liquid water path. Finally, changes in volcanic activity and biomass burning aerosol over this period show sizeable radiative forcing impacts at local-scales. We will demonstrate that radiative forcing from aerosols and clouds have played a significant role in the identified key climate processes using 17 years of satellite observational data.

  2. Lower hybrid wave cavities detected by the FREJA satellite

    International Nuclear Information System (INIS)

    Pecseli, H.L.; Iranpour, K.; Holter, Oe.; Lybekk, B.; Holtet J.; Truelsen, J.; Holback, B.

    1994-12-01

    Localized electrostatic wave packets in the frequency region of lower-hybrid waves have been detected by the instruments on the FREJA satellite. These waves are usually associated with local density depletions indicating that the structures can be interpreted as wave filled cavities. The basic features of the observations are discussed. Based on simple statistical arguments it is attempted to present some characteristics which have to be accommodated within an ultimate theory describing the observed wave phenomena. An explanation in terms of collapse of nonlinear lower-hybrid waves is discussed in particular. It is argued that such a model seems inapplicable, at least in its simplest form, by providing time and length scales which are not in agreement with observations. Alternatives to this model are presented. 24 refs., 8 figs

  3. The International Satellite Cloud Climatology Project H-Series climate data record product

    Science.gov (United States)

    Young, Alisa H.; Knapp, Kenneth R.; Inamdar, Anand; Hankins, William; Rossow, William B.

    2018-03-01

    This paper describes the new global long-term International Satellite Cloud Climatology Project (ISCCP) H-series climate data record (CDR). The H-series data contain a suite of level 2 and 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar-orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-series data currently span July 1983 to December 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite-based CDR of cloud properties. Access to the data is provided in network common data form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S" target="_blank">https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-series and the widely used predecessor D-series product which also spans from July 1983 through December 2009. Key refinements included in the ISCCP H-series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-series product into compliance with existing standards for climate data records.

  4. Satellite-based climate data records of surface solar radiation from the CM SAF

    Science.gov (United States)

    Trentmann, Jörg; Cremer, Roswitha; Kothe, Steffen; Müller, Richard; Pfeifroth, Uwe

    2017-04-01

    The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth's energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF is freely available via www.cmsaf.eu. Here we present the regional and the global climate data records of surface solar radiation from the CM SAF. The regional climate data record SARAH (Surface Solar Radiation Dataset - Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002) is based on observations from the series of Meteosat satellites. SARAH provides 30-min, daily- and monthly-averaged data of the effective cloud albedo, the solar irradiance (incl. spectral information), the direct solar radiation (horizontal and normal), and the sunshine duration from 1983 to 2015 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05° allowing for detailed regional studies. The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002) is based on observations from the series of AVHRR satellite instruments. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from 1982 to 2015 with a spatial resolution of 0.25°. In addition to the solar surface

  5. CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    K.-Y. Lee

    2016-06-01

    Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

  6. Cloud Detection of Optical Satellite Images Using Support Vector Machine

    Science.gov (United States)

    Lee, Kuan-Yi; Lin, Chao-Hung

    2016-06-01

    Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

  7. Vessel and oil spill early detection using COSMO satellite imagery

    Science.gov (United States)

    Revollo, Natalia V.; Delrieux, Claudio A.

    2017-10-01

    Oil spillage is one of the most common sources of environmental damage in places where coastal wild life is found in natural reservoirs. This is especially the case in the Patagonian coast, with a littoral more than 5000 km long and a surface above a million and half square km. In addition, furtive fishery activities in Argentine waters are depleting the food supplies of several species, altering the ecological equilibrium. For this reason, early oil spills and vessel detection is an imperative surveillance task for environmental and governmental authorities. However, given the huge geographical extension, human assisted monitoring is unfeasible, and therefore real time remote sensing technologies are the only operative and economically feasible solution. In this work we describe the theoretical foundations and implementation details of a system specifically designed to take advantage of the SAR imagery delivered by two satellite constellations (the SAOCOM mission, developed by the Argentine Space Agency, and the COSMO mission, developed by the Italian Space Agency), to provide real-time detection of vessels and oil spills. The core of the system is based on pattern recognition over a statistical characterization of the texture patterns arising in the positive and negative conditions (i.e., vessel, oil, or plain sea surfaces). Training patterns were collected from a large number of previously reported contacts tagged by experts in the National Commission on Space Activities (CONAE). The resulting system performs well above the sensitivity and specificity of other avalilable systems.

  8. Validation of Hotspots Detected by Satellites in Sentinel Asia

    Science.gov (United States)

    Kaku, K.; Kushida, K.; Fukuda, M.

    2008-12-01

    The Sentinel Asia (SA) initiative is a collaboration between space agencies and disaster management agencies, applying remote sensing and Web-GIS technologies to assist disaster management in the Asia- Pacific region. It aims to: "EImprove safety in society by ICT and space technology "EImprove speed and accuracy of disaster preparedness and early warning "EMinimize the number of victims and social/economic losses. SA is a voluntary initiative led by the Asia-Pacific Regional Space Agency Forum (APRSAF) to share disaster information in near-real-time across the Asia-Pacific region. Wildfire is a major and recurring phenomenon that has a serious impact on property and human health, affecting many countries in the Asia region. Compared to other disasters in the area, it does not necessarily cause many immediate fatalities. However, it causes serious impact on property and human health due to smoke. Furthermore, its effects are of great relevance both at a regional and global level, and accordingly bear substantial influence on global warming. Responding to requirements from Asian countries, under Sentinel Asia a dedicated Wildfire Working Group (WG) has been established to apply remote sensing technology to the management of wildfire. Having accurate information on the location and intensity of the fires, and subsequent control of wildfire, are therefore very important and urgent tasks across the region. SA primarily addresses the issue of near-real-time information distribution on wildfires in the region. Concerning hotspot data obtained by satellites, it is essential to validate and improve its accuracy. In the framework of Sentinel Asia Wildfire WG, various approaches to hotspot detection, including MOD14 algorithm for MODIS hotspots, were studied, and their validations were carried out, comparing them with active fires extracted from satellite imagery and ground truth data in Chiengmai, Thailand and in Kalimantan, Indonesia.

  9. Detection of pear thrips damage using satellite imagery data

    Science.gov (United States)

    James E. Vogelmann; Barrett N. Rock

    1991-01-01

    This study evaluates the potential of measuring, mapping and monitoring sugar maple damage caused by pear thrips in southern Vermont and northwestern Massachusetts using satellite imagery data. Landsat Thematic Mapper (TM) data were obtained during a major thrips infestation in June 1988, and were compared with satellite data acquired during June 1984 (before pear...

  10. The effect of subionospheric propagation on whistlers recorded by the DEMETER satellite – observation and modelling

    Directory of Open Access Journals (Sweden)

    O. E. Ferencz

    2007-06-01

    Full Text Available During a routine analysis of whistlers on the wide-band VLF recording of the DEMETER satellite, a specific signal structure of numerous fractional-hop whistlers, termed the "Spiky Whistler" (SpW was identified. These signals appear to be composed of a conventional whistler combined by the compound mode-patterns of guided wave propagation, suggesting a whistler excited by a lightning "tweek" spheric. Rigorous, full-wave modelling of tweeks, formed by the long subionospheric guided spheric propagation and of the impulse propagation across an arbitrarily inhomogeneous ionosphere, gave an accurate description of the SpW signals. The electromagnetic impulses excited by vertical, preferably CG lightning discharge, exhibited the effects of guided behaviour and of the dispersive ionospheric plasma along their paths. This modelling and interpretation provides a consistent way to determine the generation and propagation characteristics of the recorded SpW signals, as well as to describe the traversed medium.

  11. Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

    Science.gov (United States)

    Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

    2014-01-01

    Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

  12. Sun and planet detection system for satellites. Sonnen- und Erderfassungsverfahren fuer Satelliten

    Energy Technology Data Exchange (ETDEWEB)

    Lange, B O; Scheit, A

    1980-05-22

    The invention refers to a process for the sun and planet detection system for satellites stabilised in three axes and equipped with detection sensors. The purpose of the invention is to describe such a detection system, which makes quick and reliable guiding of the satellite to its final position possible, permits the use of sensors of simple construction and of simple control laws and simple control logic. According to the invention, this problem is solved by having cumulative or alternate steps, depending on the position of the satellite relative to the sun. According to the invention they refer to the position of the sun outside the field of view for the measurement of various components and the simultaneous availability of several component values. It is particularly advantageous if only the absolutely necessary satellite manoeuvres have to be carried out, as this saves fuel and makes it possible to increase the payload or extend the satellite's life. (HWJ).

  13. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  14. Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

    Science.gov (United States)

    Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

    2015-12-01

    Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

  15. Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2013-01-01

    Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

  16. Detection of movement artifact in recorded pulse oximeter saturation.

    Science.gov (United States)

    Poets, C F; Stebbens, V A

    1997-10-01

    Movement artifact (MA) must be detected when analysing recordings of pulse oximeter saturation (SpO2). Visual analysis of individual pulse waveforms is the safest, but also the most tedious, method for this purpose. We wanted to test the reliability of a computer algorithm (Edentec Motion Annotation System), based on a comparison between pulse and heart rate, for MA detection. Ten 12-h recordings of SpO2, pulse waveforms and heart rate from ten preterm infants were analysed for the presence of MA on the pulse waveform signal. These data were used to determine the sensitivity and specificity of the computer algorithm, and of the oximeter itself, in detecting MA. Recordings were divided into segments of 2.5 s duration to compare the movement identification methods. Of the segments 31% +/- 6% (mean +/- SD) contained MA. The computer algorithm identified 95% +/- 3% of these segments, the pulse oximeter only 18% +/- 11%. Specificity was 85% +/- 4% and 99% +/- 0%, respectively. SpO2 was signal showed MA during this time, leaving a significant potential for erroneous identification of hypoxaemia. Recordings of SpO2 do not allow a reliable identification of MA. Without additional information about movement artifact, a significant proportion of recording time of pulse oximeter signal may be regarded as demonstrating hypoxaemia which, in fact, simply reflects poor measurement conditions. The computer algorithm used in this study identified periods of movement artifact reliably.

  17. Tadarida: A Toolbox for Animal Detection on Acoustic Recordings

    Directory of Open Access Journals (Sweden)

    Yves Bas

    2017-02-01

    Full Text Available Passive Acoustic Monitoring (PAM recently extended to a very wide range of animals, but no available open software has been sufficiently generic to automatically treat several taxonomic groups. Here we present Tadarida, a software toolbox allowing for the detection and labelling of recorded sound events, and to classify any new acoustic data into known classes. It is made up of three modules handling Detection, Labelling and Classification and running on either Linux or Windows. This development resulted in the first open software (1 allowing generic sound event detection (multi-taxa, (2 providing graphical sound labelling at a single-instance level and (3 covering the whole process from sound detection to classification. This generic and modular design opens numerous reuse opportunities among (bioacoustics researchers, especially for those managing and/or developing PAM schemes. The whole toolbox is openly developed in C++ (Detection and Labelling and R (Classification and stored at https://github.com/YvesBas.

  18. The Satellite Passive-Microwave Record of Sea Ice in the Ross Sea Since Late 1978

    Science.gov (United States)

    Parkinson, Claire L.

    2009-01-01

    Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea ice is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea ice monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea ice imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the ice cover each year, along with its marked interannual variability. The Ross Sea ice extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea ice cover. The satellite data also allow calculation of trends in the ice cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea ice extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased ice extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February ice extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October ice extents. On a yearly average basis, for 1979-2007 the Ross Sea ice extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had

  19. EEG recordings as a source for the detection of IRBD

    DEFF Research Database (Denmark)

    Bisgaard, Sissel; Duun-Christensen, Bolette; Kempfner, Lykke

    2015-01-01

    The purpose of this pilot study was to develop a supportive algorithm for the detection of idiopathic Rapid Eye-Movement (REM) sleep Behaviour Disorder (iRBD) from EEG recordings. iRBD is defined as REM sleep without atonia with no current sign of neurodegenerative disease, and is one...... of the earliest known biomarkers of Parkinson's Disease (PD). It is currently diagnosed by polysomnography (PSG), primarily based on EMG recordings during REM sleep. The algorithm was developed using data collected from 42 control subjects and 34 iRBD subjects. A feature was developed to represent high amplitude...

  20. Extended seizure detection algorithm for intracranial EEG recordings

    DEFF Research Database (Denmark)

    Kjaer, T. W.; Remvig, L. S.; Henriksen, J.

    2010-01-01

    Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... and non-ictal iEEG. We compare our results to a method published by Shoeb in 2004. While the original method on sEEG was optimal with the use of only four subbands in the wavelet analysis, we found that better seizure detection could be made if all subbands were used for iEEG. Results: When using...

  1. Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

    Science.gov (United States)

    Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean. Healey

    2005-01-01

    Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR...

  2. Research on the new type of multi-functional satellite system for space debris detection

    Science.gov (United States)

    Guo, Linghua; Fu, Qiang; Jiang, Huilin; Xu, Xihe

    2017-05-01

    With the rapid development of space exploration and utilization, orbital debris increases dramatically, leading to great threat to human space activities and spacecraft security. In this paper, a new type of multi-functional space debris satellite system (MSDS) was put forward, which shared main optical system, and possessed functions of multidimensional information detection, polarized remote sensing and high rate transmission. The MSDS system can meet the requirements of detection and identification for the small orbital debris which is 1000km faraway, as well as the requirements of the data transmission by 50 Mbps to 2.5 Gbps@200-1000 km. At the same time, by the method of satellite orbital maneuver and attitude adjusting, the orbital debris information that is real-time, complex and refined, allweather can be acquired and transmitted by the new system. Such new type of multifunctional satellite system can provide important and effective technology for international orbital debris detection.

  3. Global Trends in Chlorophyll Concentration Observed with the Satellite Ocean Colour Data Record

    Science.gov (United States)

    Melin, F.; Vantrepotte, V.; Chuprin, A.; Grant, M.; Jackson, T.; Sathyendranath, S.

    2016-08-01

    To detect climate change signals in the data records derived from remote sensing of ocean colour, combining data from multiple missions is required, which implies that the existence of inter-mission differences be adequately addressed prior to undertaking trend studies. Trend distributions associated with merged products are compared with those obtained from single-mission data sets in order to evaluate their suitability for climate studies. Merged products originally developed for operational applications such as near-real time distribution (GlobColour) do not appear to be proper climate data records, showing large parts of the ocean with trends significantly different from trends obtained with SeaWiFS, MODIS or MERIS. On the other hand, results obtained from the Climate Change Initiative (CCI) data are encouraging, showing a good consistency with single-mission products.

  4. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2007-01-01

    based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

  5. Essential Technology and Application of Jitter Detection and Compensation for High Resolution Satellites

    Directory of Open Access Journals (Sweden)

    TONG Xiaohua

    2017-10-01

    Full Text Available Satellite jitter is a common and complex phenomenon for the on-orbit high resolution satellites, which may affect the mapping accuracy and quality of imagery. A framework of jitter detection and compensation integrating data processing of multiple sensors is proposed in this paper. Jitter detection is performed based on multispectral imagery, three-line-array imagery, dense ground control and attitude measurement data, and jitter compensation is conducted both on image and on attitude with the sensor model. The platform jitter of ZY-3 satellite is processed and analyzed using the proposed technology, and the results demonstrate the feasibility and reliability of jitter detection and compensation. The variation law analysis of jitter indicates that the frequencies of jitter of ZY-3 satellite hold in the range between 0.6 and 0.7 Hz, while the amplitudes of jitter of ZY-3 satellite drop from 1 pixel in the early stage to below 0.4 pixels and tend to remain stable in the following stage.

  6. Oil Spill Disasters Detection and Monitoring by RST Analysis of Optical Satellite Radiances: the Case of Deepwater Horizon Platform in the Gulf of Mexico

    Science.gov (United States)

    Pergola, N.; Grimaldi, S. C.; Coviello, I.; Faruolo, M.; Lacava, T.; Tramutoli, V.

    2010-12-01

    Marine oil spill disasters may have devastating effects on the marine and coastal environment. For monitoring and mitigation purposes, timely detection and continuously updated information on polluted areas are required. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/all-weather capability of the present operational sensors. Anyway, the present SARs revisiting time does not allow for a rapid detection and a near real-time monitoring of these phenomena at global scale. Passive optical sensors, on board meteorological satellites, thanks to their high temporal resolution (from a few hours to 15 minutes, depending on the characteristics of the platform/sensor), may represent, at this moment, a suitable SAR alternative/complement for oil spill detection and monitoring. Up to now, some techniques, based on optical satellite data, have been proposed for “a posteriori” mapping of already known oil spill discharges. On the other hand, reliable satellite methods for an automatic and timely detection of oil spills, for surveillance and warning purposes, are still currently missing. Recently, an innovative technique for automatic and near real time oil spill detection and monitoring has been proposed. The technique is based on the general RST (Robust Satellite Technique) approach which exploits multi-temporal satellite records in order to obtain a former characterization of the measured signal, in terms of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change detection step. Results obtained by using AVHRR (Advanced Very High Resolution Radiometer) Thermal Infrared data, in different geographic areas and observational conditions, demonstrated excellent detection capabilities both in

  7. A service for the application of data quality information to NASA earth science satellite records

    Science.gov (United States)

    Armstrong, E. M.; Xing, Z.; Fry, C.; Khalsa, S. J. S.; Huang, T.; Chen, G.; Chin, T. M.; Alarcon, C.

    2016-12-01

    A recurring demand in working with satellite-based earth science data records is the need to apply data quality information. Such quality information is often contained within the data files as an array of "flags", but can also be represented by more complex quality descriptions such as combinations of bit flags, or even other ancillary variables that can be applied as thresholds to the geophysical variable of interest. For example, with Level 2 granules from the Group for High Resolution Sea Surface Temperature (GHRSST) project up to 6 independent variables could be used to screen the sea surface temperature measurements on a pixel-by-pixel basis. Quality screening of Level 3 data from the Soil Moisture Active Passive (SMAP) instrument can be become even more complex, involving 161 unique bit states or conditions a user can screen for. The application of quality information is often a laborious process for the user until they understand the implications of all the flags and bit conditions, and requires iterative approaches using custom software. The Virtual Quality Screening Service, a NASA ACCESS project, is addressing these issues and concerns. The project has developed an infrastructure to expose, apply, and extract quality screening information building off known and proven NASA components for data extraction and subset-by-value, data discovery, and exposure to the user of granule-based quality information. Further sharing of results through well-defined URLs and web service specifications has also been implemented. The presentation will focus on overall description of the technologies and informatics principals employed by the project. Examples of implementations of the end-to-end web service for quality screening with GHRSST and SMAP granules will be demonstrated.

  8. Saharan dust detection using multi-sensor satellite measurements

    Directory of Open Access Journals (Sweden)

    Sriharsha Madhavan

    2017-02-01

    Full Text Available Contemporary scientists have vested interest in trying to understand the climatology of the North Atlantic Basin since this region is considered as the genesis for hurricane formation that eventually get shipped to the tropical Atlantic region and the Caribbean. The effects of atmospheric water cycle and the climate of West Africa and the Atlantic basin are hugely impacted by the radiative forcing of Saharan dust. The focus area in this paper would be to improve the dust detection schemes by employing the use of multi sensor measurements in the thermal emissive wavelengths using legacy sensors such as Terra (T and Aqua (A MODerate-resolution Imaging Spectroradiometer (MODIS, fusing with Ozone Monitoring Instrument (OMI. Previous work by Hao and Qu (2007 had considered a limited number of thermal infrared channels which led to a correlation coefficient R2 value of 0.765 between the Aerosol Optical Thickness (AOT at 550 nm and the modeled dust index. In this work, we extend the thermal infrared based dust detection by employing additional channels: the 8.55 μm which has shown high sensitivity to the Saharan dust, along with water vapor channel of 7.1 μm and cloud top channel of 13.1 μm. Also, the dust pixels were clearly identified using the OMI based aerosol types. The dust pixels were cleanly segregated from the other aerosol types such as sulfates, biomass, and other carbonaceous aerosols. These improvements led to a much higher correlation coefficient R2 value of 0.85 between the modified dust index and the AOT in comparison to the previous work. The key limitations from the current AOT products based on MODIS and were put to test by validating the improved dust detection algorithm. Two improvements were noted. First, the dust measurement radiometry using MODIS is significantly improved by at least an order of 2. Second the spatial measurements are enhanced by a factor of at least 10.

  9. Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

    Science.gov (United States)

    Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

    2015-03-01

    Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of

  10. SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

    Directory of Open Access Journals (Sweden)

    N. M. S. M. Kadhim

    2015-03-01

    Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

  11. Framework of Jitter Detection and Compensation for High Resolution Satellites

    Directory of Open Access Journals (Sweden)

    Xiaohua Tong

    2014-05-01

    Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

  12. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  13. An Unsupervised Anomalous Event Detection and Interactive Analysis Framework for Large-scale Satellite Data

    Science.gov (United States)

    LIU, Q.; Lv, Q.; Klucik, R.; Chen, C.; Gallaher, D. W.; Grant, G.; Shang, L.

    2016-12-01

    Due to the high volume and complexity of satellite data, computer-aided tools for fast quality assessments and scientific discovery are indispensable for scientists in the era of Big Data. In this work, we have developed a framework for automated anomalous event detection in massive satellite data. The framework consists of a clustering-based anomaly detection algorithm and a cloud-based tool for interactive analysis of detected anomalies. The algorithm is unsupervised and requires no prior knowledge of the data (e.g., expected normal pattern or known anomalies). As such, it works for diverse data sets, and performs well even in the presence of missing and noisy data. The cloud-based tool provides an intuitive mapping interface that allows users to interactively analyze anomalies using multiple features. As a whole, our framework can (1) identify outliers in a spatio-temporal context, (2) recognize and distinguish meaningful anomalous events from individual outliers, (3) rank those events based on "interestingness" (e.g., rareness or total number of outliers) defined by users, and (4) enable interactively query, exploration, and analysis of those anomalous events. In this presentation, we will demonstrate the effectiveness and efficiency of our framework in the application of detecting data quality issues and unusual natural events using two satellite datasets. The techniques and tools developed in this project are applicable for a diverse set of satellite data and will be made publicly available for scientists in early 2017.

  14. Land use change detection based on multi-date imagery from different satellite sensor systems

    Science.gov (United States)

    Stow, Douglas A.; Collins, Doretta; Mckinsey, David

    1990-01-01

    An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

  15. International Satellite Cloud Climatology Project (ISCCP) Climate Data Record, H-Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The International Satellite Cloud Climatology Project (ISCCP) focuses on the distribution and variation of cloud radiative properties to improve the understanding of...

  16. Homogeneity testing of the global ESA CCI multi-satellite soil moisture climate data record

    Science.gov (United States)

    Preimesberger, Wolfgang; Su, Chun-Hsu; Gruber, Alexander; Dorigo, Wouter

    2017-04-01

    ESA's Climate Change Initiative (CCI) creates a global, long-term data record by merging multiple available earth observation products with the goal to provide a product for climate studies, trend analysis, and risk assessments. The blending of soil moisture (SM) time series derived from different active and passive remote sensing instruments with varying sensor characteristics, such as microwave frequency, signal polarization or radiometric accuracy, could potentially lead to inhomogeneities in the merged long-term data series, undercutting the usefulness of the product. To detect the spatio-temporal extent of contiguous periods without inhomogeneities as well as subsequently minimizing their negative impact on the data records, different relative homogeneity tests (namely Fligner-Killeen test of homogeneity of variances and Wilcoxon rank-sums test) are implemented and tested on the combined active-passive ESA CCI SM data set. Inhomogeneities are detected by comparing the data against reference data from in-situ data from ISMN, and model-based estimates from GLDAS-Noah and MERRA-Land. Inhomogeneity testing is performed over the ESA CCI SM data time frame of 38 years (from 1978 to 2015), on a global quarter-degree grid and with regard to six alterations in the combination of observation systems used in the data blending process. This study describes and explains observed variations in the spatial and temporal patterns of inhomogeneities in the combined products. Besides we proposes methodologies for measuring and reducing the impact of inhomogeneities on trends derived from the ESA CCI SM data set, and suggest the use of inhomogeneity-corrected data for future trend studies. This study is supported by the European Union's FP7 EartH2Observe "Global Earth Observation for Integrated Water Resource Assessment" project (grant agreement number 331 603608).

  17. Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery

    Science.gov (United States)

    Park, Isaac W.

    2012-11-01

    This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.

  18. Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Ph.D. Thesis

    Science.gov (United States)

    Gutierrez, Alberto, Jr.

    1995-01-01

    This dissertation evaluates receiver-based methods for mitigating the effects due to nonlinear bandlimited signal distortion present in high data rate satellite channels. The effects of the nonlinear bandlimited distortion is illustrated for digitally modulated signals. A lucid development of the low-pass Volterra discrete time model for a nonlinear communication channel is presented. In addition, finite-state machine models are explicitly developed for a nonlinear bandlimited satellite channel. A nonlinear fixed equalizer based on Volterra series has previously been studied for compensation of noiseless signal distortion due to a nonlinear satellite channel. This dissertation studies adaptive Volterra equalizers on a downlink-limited nonlinear bandlimited satellite channel. We employ as figure of merits performance in the mean-square error and probability of error senses. In addition, a receiver consisting of a fractionally-spaced equalizer (FSE) followed by a Volterra equalizer (FSE-Volterra) is found to give improvement beyond that gained by the Volterra equalizer. Significant probability of error performance improvement is found for multilevel modulation schemes. Also, it is found that probability of error improvement is more significant for modulation schemes, constant amplitude and multilevel, which require higher signal to noise ratios (i.e., higher modulation orders) for reliable operation. The maximum likelihood sequence detection (MLSD) receiver for a nonlinear satellite channel, a bank of matched filters followed by a Viterbi detector, serves as a probability of error lower bound for the Volterra and FSE-Volterra equalizers. However, this receiver has not been evaluated for a specific satellite channel. In this work, an MLSD receiver is evaluated for a specific downlink-limited satellite channel. Because of the bank of matched filters, the MLSD receiver may be high in complexity. Consequently, the probability of error performance of a more practical

  19. Noise detection during heart sound recording using periodicity signatures

    International Nuclear Information System (INIS)

    Kumar, D; Carvalho, P; Paiva, R P; Henriques, J; Antunes, M

    2011-01-01

    Heart sound is a valuable biosignal for diagnosis of a large set of cardiac diseases. Ambient and physiological noise interference is one of the most usual and highly probable incidents during heart sound acquisition. It tends to change the morphological characteristics of heart sound that may carry important information for heart disease diagnosis. In this paper, we propose a new method applicable in real time to detect ambient and internal body noises manifested in heart sound during acquisition. The algorithm is developed on the basis of the periodic nature of heart sounds and physiologically inspired criteria. A small segment of uncontaminated heart sound exhibiting periodicity in time as well as in the time-frequency domain is first detected and applied as a reference signal in discriminating noise from the sound. The proposed technique has been tested with a database of heart sounds collected from 71 subjects with several types of heart disease inducing several noises during recording. The achieved average sensitivity and specificity are 95.88% and 97.56%, respectively

  20. PLASTIC AND GLASS GREENHOUSES DETECTION AND DELINEATION FROM WORLDVIEW-2 SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    D. Koc-San

    2016-06-01

    Full Text Available Greenhouse detection using remote sensing technologies is an important research area for yield estimation, sustainable development, urban and rural planning and management. An approach was developed in this study for the detection and delineation of greenhouse areas from high resolution satellite imagery. Initially, the candidate greenhouse patches were detected using supervised classification techniques. For this purpose, Maximum Likelihood (ML, Random Forest (RF, and Support Vector Machines (SVM classification techniques were applied and compared. Then, sieve filter and morphological operations were performed for improving the classification results. Finally, the obtained candidate plastic and glass greenhouse areas were delineated using boundary tracing and Douglas Peucker line simplification algorithms. The proposed approach was implemented in the Kumluca district of Antalya, Turkey utilizing pan-sharpened WorldView-2 satellite imageries. Kumluca is the prominent district of Antalya with greenhouse cultivation and includes both plastic and glass greenhouses intensively. When the greenhouse classification results were analysed, it can be stated that the SVM classification provides most accurate results and RF classification follows this. The SVM classification overall accuracy was obtained as 90.28%. When the greenhouse boundary delineation results were considered, the plastic greenhouses were delineated with 92.11% accuracy, while glass greenhouses were delineated with 80.67% accuracy. The obtained results indicate that, generally plastic and glass greenhouses can be detected and delineated successfully from WorldView-2 satellite imagery.

  1. Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

    Science.gov (United States)

    Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

    2016-10-01

    Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

  2. Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

    Directory of Open Access Journals (Sweden)

    Shaodan Li

    2017-11-01

    Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

  3. A MODIS-Based Robust Satellite Technique (RST for Timely Detection of Oil Spilled Areas

    Directory of Open Access Journals (Sweden)

    Teodosio Lacava

    2017-02-01

    Full Text Available Natural crude-oil seepages, together with the oil released into seawater as a consequence of oil exploration/production/transportation activities, and operational discharges from tankers (i.e., oil dumped during cleaning actions represent the main sources of sea oil pollution. Satellite remote sensing can be a useful tool for the management of such types of marine hazards, namely oil spills, mainly owing to the synoptic view and the good trade-off between spatial and temporal resolution, depending on the specific platform/sensor system used. In this paper, an innovative satellite-based technique for oil spill detection, based on the general robust satellite technique (RST approach, is presented. It exploits the multi-temporal analysis of data acquired in the visible channels of the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua satellite in order to automatically and quickly detect the presence of oil spills on the sea surface, with an attempt to minimize “false detections” caused by spurious effects associated with, for instance, cloud edges, sun/satellite geometries, sea currents, etc. The oil spill event that occurred in June 2007 off the south coast of Cyprus in the Mediterranean Sea has been considered as a test case. The resulting data, the reliability of which has been evaluated by both carrying out a confutation analysis and comparing them with those provided by the application of another independent MODIS-based method, showcase the potential of RST in identifying the presence of oil with a high level of accuracy.

  4. Integrated fiber optic sensors for hot spot detection and temperature field reconstruction in satellites

    International Nuclear Information System (INIS)

    Rapp, S; Baier, H

    2010-01-01

    Large satellites are often equipped with more than 1000 temperature sensors during the test campaign. Hundreds of them are still used for monitoring during launch and operation in space. This means an additional mass and especially high effort in assembly, integration and verification on a system level. So the use of fiber Bragg grating temperature sensors is investigated as they offer several advantages. They are lightweight, small in size and electromagnetically immune, which fits well in space applications. Their multiplexing capability offers the possibility to build extensive sensor networks including dozens of sensors of different types, such as strain sensors, accelerometers and temperature sensors. The latter allow the detection of hot spots and the reconstruction of temperature fields via proper algorithms, which is shown in this paper. A temperature sensor transducer was developed, which can be integrated into satellite sandwich panels with negligible mechanical influence. Mechanical and thermal vacuum tests were performed to verify the space compatibility of the developed sensor system. Proper reconstruction algorithms were developed to estimate the temperature field and detect thermal hot spots on the panel surface. A representative hardware demonstrator has been built and tested, which shows the capability of using an integrated fiber Bragg grating temperature sensor network for temperature field reconstruction and hot spot detection in satellite structures

  5. Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

    Science.gov (United States)

    Lasaponara, R.; Masini, n.

    2012-04-01

    archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological

  6. Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

    Science.gov (United States)

    Champion, Nicolas

    2016-06-01

    Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

  7. AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

    Directory of Open Access Journals (Sweden)

    N. Champion

    2016-06-01

    Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

  8. Ship detection in satellite imagery using rank-order greyscale hit-or-miss transforms

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, Neal R [Los Alamos National Laboratory; Porter, Reid B [Los Alamos National Laboratory; Theiler, James [Los Alamos National Laboratory

    2010-01-01

    Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.

  9. Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

    Science.gov (United States)

    Koeppen, W. C.; Pilger, E.; Wright, R.

    2011-07-01

    We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

  10. Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Seongmun Sim

    2018-04-01

    Full Text Available Even though deicing or airframe coating technologies continue to develop, aircraft icing is still one of the critical threats to aviation. While the detection of potential icing clouds has been conducted using geostationary satellite data in the US and Europe, there is not yet a robust model that detects potential icing areas in East Asia. In this study, we proposed machine-learning-based icing detection models using data from two geostationary satellites—the Communication, Ocean, and Meteorological Satellite (COMS Meteorological Imager (MI and the Himawari-8 Advanced Himawari Imager (AHI—over Northeast Asia. Two machine learning techniques—random forest (RF and multinomial log-linear (MLL models—were evaluated with quality-controlled pilot reports (PIREPs as the reference data. The machine-learning-based models were compared to the existing models through five-fold cross-validation. The RF model for COMS MI produced the best performance, resulting in a mean probability of detection (POD of 81.8%, a mean overall accuracy (OA of 82.1%, and mean true skill statistics (TSS of 64.0%. One of the existing models, flight icing threat (FIT, produced relatively poor performance, providing a mean POD of 36.4%, a mean OA of 61.0, and a mean TSS of 9.7%. The Himawari-8 based models also produced performance comparable to the COMS models. However, it should be noted that very limited PIREP reference data were available especially for the Himawari-8 models, which requires further evaluation in the future with more reference data. The spatio-temporal patterns of the icing areas detected using the developed models were also visually examined using time-series satellite data.

  11. Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

    International Nuclear Information System (INIS)

    Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

    2013-01-01

    Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

  12. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

    International Nuclear Information System (INIS)

    Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.

    2015-01-01

    The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

  13. Detection of land cover change using an Artificial Neural Network on a time-series of MODIS satellite data

    CSIR Research Space (South Africa)

    Olivier, JC

    2007-11-01

    Full Text Available An Artificial Neural Network (ANN) is proposed to detect human-induced land cover change using a sliding window through a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite surface reflectance pixel values. Training...

  14. Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America

    Directory of Open Access Journals (Sweden)

    D. Loyola

    2008-01-01

    Full Text Available Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash into the atmosphere, as well as several gases, including sulphur dioxide (SO2. These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO2 plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellite-based SO2 detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments.

  15. Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility

    Science.gov (United States)

    Kang, J.-M.; Baek, S.-H.; Jung, K.-Y.

    2012-07-01

    Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more effective

  16. ANALYSIS ON THE UTILITY OF SATELLITE IMAGERY FOR DETECTION OF AGRICULTURAL FACILITY

    Directory of Open Access Journals (Sweden)

    J.-M. Kang

    2012-07-01

    Full Text Available Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more

  17. Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

    Energy Technology Data Exchange (ETDEWEB)

    Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

    2008-07-01

    The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

  18. A new 25 years Arctic Sea level record from ESA satellites

    DEFF Research Database (Denmark)

    Andersen, Ole Baltazar; Cheng, Yongcun; Knudsen, Per

    The Arctic is an extremely challenging region for the use of remote sensing for ocean studies. One is the fact that despite 25 years of altimetry only very limited sea level observations exists in the interior of the Arctic Ocean. However, with Cryosat-2 SAR altimetry the situation is changing...... the ESA GOCE mission we are now able to derive a mean dynamic topography of the Arctic Ocean with unprecedented accuracy to constrain the ocean circulation. We present both a new estimation of the mean ocean circulation and new estimates of large scale sea level changes based on satellite data and perform...

  19. Wide area change detection with satellite imagery for locating underground nuclear testing

    International Nuclear Information System (INIS)

    Canty, M.J.; Jasani, B.; Schlittenhardt, J.

    2001-01-01

    With the advent of high resolution optical imagery from commercial earth observation satellites, the use of remote sensing data for verification of nuclear non-proliferation agreements is becoming increasingly attractive. Non-governmental organizations are routinely publishing high-quality imagery of sensitive nuclear installations round the world, and international verification authorities, such as the International Atomic Energy Agency (IAEA) or the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), will also want to make use, directly or indirectly, of this additional open source of information. Exact location of the sites of underground nuclear explosions is a task eminently suited to satellite imagery. Here both moderate resolutions for detecting signals in very large testing ranges as well as high resolution images for exact interpretation play important roles. We describe in our paper a particularly sensitive change detection procedure for bitemporal, multispectral satellite imagery which can be used to locate the spall zone of underground nuclear explosions with commercial satellite imagery. The method is based on the multivariate alteration detection (MAD) technique of Nielsen et al. Linear combinations of the spectral channels in two images of the same scene are chosen so as to minimize their positive correlation. This leads to a series of difference images - the so-called MAD components - which are mutually orthogonal (uncorrelated) and ordered according to decreasing variance in their pixel intensities. Since interesting changes in man-made structures may contribute minimally to the overall variance (as the latter may be dominated for instance by seasonal vegetation differences) it is often the case that such changes turn up in a higher order MAD component. This is because they will be uncorrelated with seasonal vegetation changes, stochastic image noise or other major contributions to the overall change signal. This in fact is one of the

  20. Satellite skill in detecting extreme episodes in near-surface air quality

    Science.gov (United States)

    Ruiz, D. J.; Prather, M. J.

    2017-12-01

    Ozone (O3) contributes to ambient air pollution, adversely affecting public health, agriculture, and ecosystems. Reliable, long-term, densely distributed surface networks are required to establish the scale, intensity and repeatability of major pollution events (designated here in a climatological sense as air quality extremes, AQX as defined in Schnell's work). Regrettably, such networks are only available for North America (NA) and Europe (EU), which does not include many populated regions where the deaths associated with air pollution exposure are alarmingly high. Directly measuring surface pollutants from space without lidar is extremely difficult. Mapping of daily pollution events requires cross-track nadir scanners and these have limited sensitivity to surface O3 levels. This work examines several years of coincident surface and OMI satellite measurements over NA-EU, in combination with a chemistry-transport model (CTM) hindcast of that period to understand how the large-scale AQX episodes may extend into the free troposphere and thus be more amenable to satellite mapping. We show how extreme NA-EU episodes are measured from OMI and then look for such patterns over other polluted regions of the globe. We gather individual high-quality O3 surface site measurements from these other regions, to check on our satellite detection. Our approach with global satellite detection would avoid issues associated with regional variations in seasonality, chemical regime, data product biases; and it does not require defining a separate absolute threshold for each data product (surface site and satellite). This also enables coherent linking of the extreme events into large-scale pollution episodes whose magnitude evolves over 100's of km for several days. Tools used here include the UC Irvine CTM, which shows that much of the O3 surface variability is lost at heights above 2 km, but AQX local events are readily seen in a 0-3 km column average. The OMI data are taken from X

  1. Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

    International Nuclear Information System (INIS)

    Riano M, Orlando

    2002-01-01

    In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

  2. Detection of a weak meddy-like anomaly from high-resolution satellite SST maps

    Directory of Open Access Journals (Sweden)

    Mikhail Emelianov

    2012-09-01

    Full Text Available Despite the considerable impact of meddies on climate through the long-distance transport of properties, a consistent observation of meddy generation and propagation in the ocean is rather elusive. Meddies propagate at about 1000 m below the ocean surface, so satellite sensors are not able to detect them directly and finding them in the open ocean is more fortuitous than intentional. However, a consistent census of meddies and their paths is required in order to gain knowledge about their role in transporting properties such as heat and salt. In this paper we propose a new methodology for processing high-resolution sea surface temperature maps in order to detect meddy-like anomalies in the open ocean on a near-real-time basis. We present an example of detection, involving an atypical meddy-like anomaly that was confirmed as such by in situ measurements.

  3. A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data

    International Nuclear Information System (INIS)

    Elvidge, Ch. D.; Erwin, E. H.; Ziskin, D.; Baugh, K. E.; Tuttle, B. T.; Ghosh, T.; Tuttle, B. T.; Ghosh, T.; Pack, D. W.; Zhizhin, M.

    2009-01-01

    We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of 68 billions USD. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2e ) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that

  4. NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    G. Máttyus

    2013-05-01

    Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  5. Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

    Science.gov (United States)

    Máttyus, G.

    2013-05-01

    Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

  6. Visual attention based detection of signs of anthropogenic activities in satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Skurikhin, Alexei N [Los Alamos National Laboratory

    2010-10-13

    With increasing deployment of satellite imaging systems, only a small fraction of collected data can be subject to expert scrutiny. We present and evaluate a two-tier approach to broad area search for signs of anthropogenic activities in high-resolution commercial satellite imagery. The method filters image information using semantically oriented interest points by combining Harris corner detection and spatial pyramid matching. The idea is that anthropogenic structures, such as rooftop outlines, fence corners, road junctions, are locally arranged in specific angular relations to each other. They are often oriented at approximately right angles to each other (which is known as rectilinearity relation). Detecting the rectilinearity provides an opportunity to highlight regions most likely to contain anthropogenic activity. This is followed by supervised classification of regions surrounding the detected corner points as man-made vs. natural scenes. We consider, in particular, a search for anthropogenic activities in uncluttered areas. In this paper, we proposed and evaluated a two-tier approach to broad area search for signs of anthropogenic activities. Results from experiments on high-resolution ({approx}0.6m) commercial satellite image data showed the potential applicability of this approach and its ability of achieving both high precision and recall rates. The main advantage of combining corner-based cueing with general object recognition is that the incorporation of domain specific knowledge even in its more general form, such as presence of comers, provides a useful cue to narrow the focus of search for signs of anthropogenic activities. Combination of comer based cueing with spatial pyramid matching addressed the issue of comer categorization. An important practical issue for further research is optimizing the balance between false positive and false negative rates. While the results presented in the paper are encouraging, the problem of an automated broad area

  7. Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

    Directory of Open Access Journals (Sweden)

    Brenden Jongman

    2015-10-01

    Full Text Available Humanitarian organizations have a crucial role in response and relief efforts after floods. The effectiveness of disaster response is contingent on accurate and timely information regarding the location, timing and impacts of the event. Here we show how two near-real-time data sources, satellite observations of water coverage and flood-related social media activity from Twitter, can be used to support rapid disaster response, using case-studies in the Philippines and Pakistan. For these countries we analyze information from disaster response organizations, the Global Flood Detection System (GFDS satellite flood signal, and flood-related Twitter activity analysis. The results demonstrate that these sources of near-real-time information can be used to gain a quicker understanding of the location, the timing, as well as the causes and impacts of floods. In terms of location, we produce daily impact maps based on both satellite information and social media, which can dynamically and rapidly outline the affected area during a disaster. In terms of timing, the results show that GFDS and/or Twitter signals flagging ongoing or upcoming flooding are regularly available one to several days before the event was reported to humanitarian organizations. In terms of event understanding, we show that both GFDS and social media can be used to detect and understand unexpected or controversial flood events, for example due to the sudden opening of hydropower dams or the breaching of flood protection. The performance of the GFDS and Twitter data for early detection and location mapping is mixed, depending on specific hydrological circumstances (GFDS and social media penetration (Twitter. Further research is needed to improve the interpretation of the GFDS signal in different situations, and to improve the pre-processing of social media data for operational use.

  8. Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

    Science.gov (United States)

    Kit, Oleksandr; Lüdeke, Matthias

    2013-09-01

    This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

  9. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  10. Deep learning for the detection of barchan dunes in satellite images

    Science.gov (United States)

    Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.

    2017-12-01

    Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the

  11. Detection and retrieval of multi-layered cloud properties using satellite data

    Science.gov (United States)

    Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

    2005-10-01

    Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

  12. Detecting Inappropriate Access to Electronic Health Records Using Collaborative Filtering.

    Science.gov (United States)

    Menon, Aditya Krishna; Jiang, Xiaoqian; Kim, Jihoon; Vaidya, Jaideep; Ohno-Machado, Lucila

    2014-04-01

    Many healthcare facilities enforce security on their electronic health records (EHRs) through a corrective mechanism: some staff nominally have almost unrestricted access to the records, but there is a strict ex post facto audit process for inappropriate accesses, i.e., accesses that violate the facility's security and privacy policies. This process is inefficient, as each suspicious access has to be reviewed by a security expert, and is purely retrospective, as it occurs after damage may have been incurred. This motivates automated approaches based on machine learning using historical data. Previous attempts at such a system have successfully applied supervised learning models to this end, such as SVMs and logistic regression. While providing benefits over manual auditing, these approaches ignore the identity of the users and patients involved in a record access. Therefore, they cannot exploit the fact that a patient whose record was previously involved in a violation has an increased risk of being involved in a future violation. Motivated by this, in this paper, we propose a collaborative filtering inspired approach to predicting inappropriate accesses. Our solution integrates both explicit and latent features for staff and patients, the latter acting as a personalized "finger-print" based on historical access patterns. The proposed method, when applied to real EHR access data from two tertiary hospitals and a file-access dataset from Amazon, shows not only significantly improved performance compared to existing methods, but also provides insights as to what indicates an inappropriate access.

  13. Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

    Science.gov (United States)

    Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

    2017-09-01

    The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

  14. Comparison of semiautomated bird song recognition with manual detection of recorded bird song samples

    Directory of Open Access Journals (Sweden)

    Lisa A. Venier

    2017-12-01

    Full Text Available Automated recording units are increasingly being used to sample wildlife populations. These devices can produce large amounts of data that are difficult to process manually. However, the information in the recordings can be summarized with semiautomated sound recognition software. Our objective was to assess the utility of the semiautomated bird song recognizers to produce data useful for conservation and sustainable forest management applications. We compared detection data generated from expert-interpreted recordings of bird songs collected with automated recording units and data derived from a semiautomated recognition process. We recorded bird songs at 109 sites in boreal forest in 2013 and 2014 using automated recording units. We developed bird-song recognizers for 10 species using Song Scope software (Wildlife Acoustics and each recognizer was used to scan a set of recordings that was also interpreted manually by an expert in birdsong identification. We used occupancy models to estimate the detection probability associated with each method. Based on these detection probability estimates we produced cumulative detection probability curves. In a second analysis we estimated detection probability of bird song recognizers using multiple 10-minute recordings for a single station and visit (35-63, 10-minute recordings in each of four one-week periods. Results show that the detection probability of most species from single 10-min recordings is substantially higher using expert-interpreted bird song recordings than using the song recognizer software. However, our results also indicate that detection probabilities for song recognizers can be significantly improved by using more than a single 10-minute recording, which can be easily done with little additional cost with the automate procedure. Based on these results we suggest that automated recording units and song recognizer software can be valuable tools to estimate detection probability and

  15. Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

    Science.gov (United States)

    Trinh, R. C.; Holt, B.; Gierach, M.

    2016-02-01

    Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also

  16. Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

    Science.gov (United States)

    Kim, Y.; Du, J.; Kimball, J. S.

    2017-12-01

    The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb

  17. Ionospheric Disturbances Recorded by DEMETER Satellite over Active Volcanoes: From August 2004 to December 2010

    Directory of Open Access Journals (Sweden)

    Jacques Zlotnicki

    2013-01-01

    Full Text Available The study analyzes electromagnetic data and plasma characteristics in the ionosphere recorded by DEMETER microsatellite over erupting volcanoes during the life of the mission: from August 2004 to December 2010. The time window in which anomalous changes are searched brackets the onset of the eruptive activity from 60 days before to 15 days after the period during which most pre- and posteruptive phenomena are amplified. 73 volcanoes have entered into eruption. For 58 of them, 269 anomalies were found in relation to 89 eruptions. They are distributed in 5 types, similarly to the ones observed above impeding earthquakes. The two main types are electrostatic turbulence (type 1, 23.4% and electromagnetic emissions (type 2, 69.5%. The maximum number of types 1 and 2 anomalies is recorded between 30 and 15 days before the surface activity, corresponding to the period of accelerating phenomena. The amount of anomalies seems related to the powerfulness of the eruptions. The appearance seems dependant on the likelihood to release bursts of gases during the preparatory eruptive phase. For the huge centenary October 26, 2010, Merapi (Indonesia eruption, 9 ionospheric type 2 anomalies appeared before the eruption. They mainly emerge during the mechanical fatigue stage during which microfracturing occurs.

  18. An algorithm of local earthquake detection from digital records

    Directory of Open Access Journals (Sweden)

    A. PROZOROV

    1978-06-01

    Full Text Available The problem of automatical detection of earthquake signals in seismograms
    and definition of first arrivals of p and s waves is considered.
    The algorithm is based on the analysis of t(A function which represents
    the time of first appearence of a number of going one after another
    swings of amplitudes greather than A in seismic signals. It allows to explore
    such common features of seismograms of earthquakes as sudden
    first p-arrivals of amplitude greater than general amplitude of noise and
    after the definite interval of time before s-arrival the amplitude of which
    overcomes the amplitude of p-arrival. The method was applied to
    3-channel recods of Friuli aftershocks, ¿'-arrivals were defined correctly
    in all cases; p-arrivals were defined in most cases using strict criteria of
    detection. Any false signals were not detected. All p-arrivals were defined
    using soft criteria of detection but less reliability and two false events
    were obtained.

  19. Wildfire Detection and Tracking over Greece Using MSG‑SEVIRI Satellite Data

    Directory of Open Access Journals (Sweden)

    Nicolaos I. Sifakis

    2011-03-01

    Full Text Available Greece is a high risk Mediterranean country with respect to wildfires. This risk has been increasing under the impact of climate change, and in summer 2007 approximately 200,000 ha of vegetated land were burnt. The SEVIRI sensor, on board the Meteosat Second Generation (MSG geostationary satellite, is the only spaceborne sensor providing five and 15-minute observations of Europe in 12 spectral channels, including a short-wave infrared band sensitive to fire radiative temperature. In August 2007, when the bulk of the destructive wildfires started in Greece, the receiving station, operated by the Institute for Space Applications and Remote Sensing, provided us with a time series of MSG-SEVIRI images. These images were processed in order to test the reliability of a real‑time detection and tracking system and its complementarity to conventional means provided by the Fire Brigade. EUMETSAT’s Active Fire Monitoring (FIR image processing algorithm for fire detection and monitoring was applied to SEVIRI data, then fine-tuned according to Greek conditions, and evaluated. Alarm announcements from the Fire Brigade’s archives were used as ground truthing data in order to assess detection reliability and system performance. During the examined period, MSG-SEVIRI data successfully detected 82% of the fire events in Greek territory with less than 1% false alarms.

  20. Bidirectional RNN for Medical Event Detection in Electronic Health Records.

    Science.gov (United States)

    Jagannatha, Abhyuday N; Yu, Hong

    2016-06-01

    Sequence labeling for extraction of medical events and their attributes from unstructured text in Electronic Health Record (EHR) notes is a key step towards semantic understanding of EHRs. It has important applications in health informatics including pharmacovigilance and drug surveillance. The state of the art supervised machine learning models in this domain are based on Conditional Random Fields (CRFs) with features calculated from fixed context windows. In this application, we explored recurrent neural network frameworks and show that they significantly out-performed the CRF models.

  1. Detection and Prediction of Hail Storms in Satellite Imagery using Deep Learning

    Science.gov (United States)

    Pullman, M.; Gurung, I.; Ramachandran, R.; Maskey, M.

    2017-12-01

    Natural hazards, such as damaging hail storms, dramatically disrupt both industry and agriculture, having significant socio-economic impacts in the United States. In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest 2016 weather phenomenon in the United States. The destructive nature and high cost of hail storms has driven research into the development of more accurate hail-prediction algorithms in an effort to mitigate societal impacts. Recently, weather forecasting efforts have turned to deep learning neural networks because neural networks can more effectively model complex, nonlinear, dynamical phenomenon that exist in large datasets through multiple stages of transformation and representation. In an effort to improve hail-prediction techniques, we propose a deep learning technique that leverages satellite imagery to detect and predict the occurrence of hail storms. The technique is applied to satellite imagery from 2006 to 2016 for the contiguous United States and incorporates hail reports obtained from the National Center for Environmental Information Storm Events Database for training and validation purposes. In this presentation, we describe a novel approach to predicting hail via a neural network model that creates a large labeled dataset of hail storms, the accuracy and results of the model, and its applications for improving hail forecasting.

  2. Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

    International Nuclear Information System (INIS)

    Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

    2011-01-01

    Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

  3. First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

    Science.gov (United States)

    Yang, Yuekui; Palm, Stephen P.; Marshak, Alexander; Wu, Dong L.; Yu, Hongbin; Fu, Qiang

    2014-01-01

    We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

  4. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Oscar Rojas

    2013-04-01

    Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

  5. Detecting Landscape Disturbance at the Nasca Lines Using SAR Data Collected from Airborne and Satellite Platforms

    Directory of Open Access Journals (Sweden)

    Douglas C. Comer

    2017-10-01

    Full Text Available We used synthetic aperture radar (SAR data collected over Peru’s Lines and Geoglyphs of the Nasca and Palpa World Heritage Site to detect and measure landscape disturbance threatening world-renowned archaeological features and ecosystems. We employed algorithms to calculate correlations between pairs of SAR returns, collected at different times, and generate correlation images. Landscape disturbances even on the scale of pedestrian travel are discernible in correlation images generated from airborne, L-band SAR. Correlation images derived from C-band SAR data collected by the European Space Agency’s Sentinel-1 satellites also provide detailed landscape change information. Because the two Sentinel-1 satellites together have a repeat pass interval that can be as short as six days, products derived from their data can not only provide information on the location and degree of ground disturbance, but also identify a time window of about one to three weeks during which disturbance must have occurred. For Sentinel-1, this does not depend on collecting data in fine-beam modes, which generally sacrifice the size of the area covered for a higher spatial resolution. We also report on pixel value stretching for a visual analysis of SAR data, quantitative assessment of landscape disturbance, and statistical testing for significant landscape change.

  6. Remote sensing for greenhouse detection from stereo pairs of WorldView-2 satellite

    Directory of Open Access Journals (Sweden)

    M.A. Aguilar

    2014-05-01

    Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.

  7. A graph-based approach to detect spatiotemporal dynamics in satellite image time series

    Science.gov (United States)

    Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

    2017-08-01

    Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

  8. DETECTION OF THE VELOCITY SHEAR EFFECT ON THE SPATIAL DISTRIBUTIONS OF THE GALACTIC SATELLITES IN ISOLATED SYSTEMS

    International Nuclear Information System (INIS)

    Lee, Jounghun; Choi, Yun-Young

    2015-01-01

    We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal

  9. Detection of the Velocity Shear Effect on the Spatial Distributions of the Galactic Satellites in Isolated Systems

    Science.gov (United States)

    Lee, Jounghun; Choi, Yun-Young

    2015-02-01

    We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal.

  10. Analytic studies on satellite detection of severe, two-cell tornadoes

    Science.gov (United States)

    Carrier, G. F.; Dergarabedian, P.; Fendell, F. E.

    1979-01-01

    From funnel-cloud-length interpretation, the severe tornado is characterized by peak swirl speed relative to the axis of rotation of about 90 m/s. Thermohydrodynamic achievement of the pressure deficit from ambient necessary to sustain such swirls requires that a dry, compressionally heated, non-rotating downdraft of initially tropopause-level air lie within an annulus of rapidly swirling, originally low-level air ascending on a near-moist-adiabatic locus of thermodynamic states. The two-cell structure furnishes an observable parameter possibly accessible to a passively instrumented, geosynchronous meteorological satellite with mesoscale resolution, for early detection of a severe tornado. Accordingly, the low-level turnaround region, in which the surface inflow layer separates to become a free ascending layer and for which inviscid modeling suffices, is examined quantitatively. Preliminary results indicate that swirl overshoot, i.e., swirl speeds in the turnaround region in excess of the maximum achieved in the potential vortex, is modest.

  11. Detection of soil erosion within pinyon-juniper woodlands using Thematic Mapper (TM) satellite data

    Science.gov (United States)

    Price, Kevin P.; Ridd, Merrill K.

    1991-01-01

    The sensitivity of Landsat TM data for detecting soil erosion within pinyon-juniper woodlands, and the potential of the spectral data for assigning the universal soil loss equation (USLE) crop managemnent (C) factor to varying cover types within the woodlands are assessed. Results show greatly accelerated rates of soil erosion on pinyon-juniper sites. Percent cover by pinyon-juniper, total soil-loss, and total nonliving ground cover accounted for nearly 70 percent of the variability in TM channels 2, 3, 4, and 5. TM spectral data were consistently better predictors of soil erosion than the biotic and abiotic field variables. Satellite data were more sensitive to vegetation variation than the USLE C factor, and USLE was found to be a poor predictor of soil loss on pinyon-juniper sites. A new string-to-ground soil erosion prediction technique is introduced.

  12. An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

    Science.gov (United States)

    Kim, Edward

    2011-01-01

    Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

  13. Forest fires detection in Indonesia using satellite Himawari-8 (case study: Sumatera and Kalimantan on august-october 2015)

    Science.gov (United States)

    Fatkhuroyan; Wati, Trinah; Panjaitan, Andersen

    2017-01-01

    Forest fires in Indonesia are serious problem affecting widely in material losses, health and environment. Himawari-8 as one of meteorological satellites with high resolution 0,5 km x 0,5 km can be used for forest fire monitoring and detection. Combination between 3, 4 and 6 channels using Sataid (Satellite Animation and Interactive Diagnosis) software will visualize forest fire in the study site. Monitoring which used Himawari-8 data on August, September and October 2015 can detect the distribution of smoke and the extents of forest fire in Sumatera and Kalimantan. The result showed the extent of forest fire can be identified for anticipation in the next step.

  14. Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

    Science.gov (United States)

    Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

    2017-12-15

    In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time

  15. Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

    Science.gov (United States)

    Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

    2017-12-01

    In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

  16. Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Yun-Long Kong

    2018-03-01

    Full Text Available A satellite image time series (SITS contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests and human activities (for example, deforestation and urbanisation will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1 illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

  17. Experimental Demonstration of an Algorithm to Detect the Presence of a Parasitic Satellite

    National Research Council Canada - National Science Library

    Dabrowski, Vincent

    2003-01-01

    Published reports of microsatellite weapons testing have led to a concern that some of these "parasitic" satellites could be deployed against US satellites to rendezvous dock and then disrupt, degrade...

  18. Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2014-01-01

    A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

  19. Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

    Science.gov (United States)

    Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

    2013-12-01

    During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST

  20. Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings

    DEFF Research Database (Denmark)

    Kempfner, Jacob; Sorensen, Helge B D; Nikolic, Miki

    2014-01-01

    SUMMARY: Idiopathic rapid-eye-movement (REM) sleep behavior disorder (iRBD) is most likely the earliest sign of Parkinson's Disease (PD) and is characterized by REM sleep without atonia (RSWA) and consequently increased muscle activity. However, some muscle twitching in normal subjects occurs...... during REM sleep. PURPOSE: There are no generally accepted methods for evaluation of this activity and a normal range has not been established. Consequently, there is a need for objective criteria. METHOD: In this study we propose a full-automatic method for detection of RSWA. REM sleep identification...... the number of outliers during REM sleep was used as a quantitative measure of muscle activity. RESULTS: The proposed method was able to automatically separate all iRBD test subjects from healthy elderly controls and subjects with periodic limb movement disorder. CONCLUSION: The proposed work is considered...

  1. Multitemporal satellite data analyses for archaeological mark detection: preliminary results in Italy and Argentina

    Science.gov (United States)

    Lasaponara, Rosa; Masini, Nicola

    2014-05-01

    The current availability of very high resolution satellite data provides an excellent tool to detect and monitor archaeological marks, namely spectral and spatial anomalies linked to the presence of buried archaeological remains from a landscape view down to local scale (single site) investigations. Since the end of the nineteenth century, aerial photography has been the remote sensing tool most widely used in archaeology for surveying both surface and sub-surface archaeological remains. Aerial photography was a real "revolution" in archaeology being an excellent tool for investigations addressed at detecting underground archaeological structures through the reconnaissance of the so-called "archaeological marks" generally grouped and named as "soil","crop marks" "snow marks", and also recently "weed marks" (Lasaponara and Masini). Such marks are generally visible only from an aerial view (see detail in Lasaponara and Masini 2009, Ciminale et al. 2009, Masini and Lasaponara 2006 Lasaponara et al 2011) . In particular, soil marks are changes in soil colour or texture due to the presence of surface and shallow remains. Crop marks are changes in crop texture linked to as differences in height or colour of crops which are under stress due to lack of water or deficiencies in other nutrients caused by the presence of masonry structures in the subsoil. Crop marks can also be formed above damp and nutritious soil of buried pits and ditches. Such marks are generally visible only from an aerial view, especially during the spring season. In the context of the Project "Remote sensing technologies applied to the management of natural and cultural heritage in sites located in Italy and Argentina: from risk monitoring to mitigatin startegies P@an_sat", funded by the Italian Ministry of Foreign Affair, we tested the capability of multitemporal data, from active and passive satellite sensors, in the detection of "archaeological marks". The areas of interested were selected from

  2. Detecting the manipulation of digital clinical records in dental practice

    International Nuclear Information System (INIS)

    Díaz-Flores-García, V.; Labajo-González, E.; Santiago-Sáez, A.; Perea-Pérez, B.

    2017-01-01

    Introduction: Radiography provides many advantages in the diagnosis and management of dental conditions. However, dental X-ray images may be subject to manipulation with malicious intent using easily accessible computer software. Methods: In this study, we sought to evaluate a dentist's ability to identify a manipulated dental X-ray images, when compared with the original, using a variant of the methodology described by Visser and Kruger. Sixty-six dentists were invited to participate and evaluate 20 intraoral dental X-ray images, 10 originals and 10 modified, manipulated using Adobe Photoshop to simulate fillings, root canal treatments, etc. Results: Participating dentists were correct in identifying the manipulated image in 56% of cases, 6% higher than by chance and 10% more than in the study by Visser and Kruger. Conclusion: Malicious changes to dental X-ray images may go unnoticed even by experienced dentists. Professionals must be aware of the legal consequences of such changes. A system of detection/validation should be created for radiographic images. - Highlights: • Fraudulent manipulation of dental X-ray images creates a problem of legal security. • Dentists were able to identify manipulated images on 56% of all occasions. • 6% more than the probability of a person with no dental training. • 10% more than in the study by Visser and Kruger.

  3. Detecting the manipulation of digital clinical records in dental practice.

    Science.gov (United States)

    Díaz-Flores-García, V; Labajo-González, E; Santiago-Sáez, A; Perea-Pérez, B

    2017-11-01

    Radiography provides many advantages in the diagnosis and management of dental conditions. However, dental X-ray images may be subject to manipulation with malicious intent using easily accessible computer software. In this study, we sought to evaluate a dentist's ability to identify a manipulated dental X-ray images, when compared with the original, using a variant of the methodology described by Visser and Kruger. Sixty-six dentists were invited to participate and evaluate 20 intraoral dental X-ray images, 10 originals and 10 modified, manipulated using Adobe Photoshop to simulate fillings, root canal treatments, etc. Participating dentists were correct in identifying the manipulated image in 56% of cases, 6% higher than by chance and 10% more than in the study by Visser and Kruger. Malicious changes to dental X-ray images may go unnoticed even by experienced dentists. Professionals must be aware of the legal consequences of such changes. A system of detection/validation should be created for radiographic images. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

  4. Satellite Detection of Orographic Gravity-wave Activity in the Winter Subtropical Stratosphere over Australia and Africa

    Science.gov (United States)

    Eckermann, S. D.; Wu, D. L.

    2012-01-01

    Orographic gravity-wave (OGW) parameterizations in models produce waves over subtropical mountain ranges in Australia and Africa that propagate into the stratosphere during austral winter and deposit momentum, affecting weather and climate. Satellite sensors have measured stratospheric GWs for over a decade, yet find no evidence of these waves. So are parameterizations failing here? Here we argue that the short wavelengths of subtropical OGWs place them near or below the detection limits of satellite sensors. To test this hypothesis, we reanalyze nine years of stratospheric radiances from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite during austral winter, applying new averaging techniques to maximize signal-to-noise and improve thresholds for OGW detection. Deep climatological enhancements in stratospheric OGW variance over specific mountain ranges in Australia and southern Africa are revealed for the first time, which exhibit temporal and vertical variations consistent with predicted OGW responses to varying background winds.

  5. The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

    Science.gov (United States)

    Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

    2016-12-01

    Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection

  6. Insertable cardiac event recorder in detection of atrial fibrillation after cryptogenic stroke: an audit report.

    Science.gov (United States)

    Etgen, Thorleif; Hochreiter, Manfred; Mundel, Markus; Freudenberger, Thomas

    2013-07-01

    Atrial fibrillation (AF) is the most frequent risk factor in ischemic stroke but often remains undetected. We analyzed the value of insertable cardiac event recorder in detection of AF in a 1-year cohort of patients with cryptogenic ischemic stroke. All patients with cryptogenic stroke and eligibility for oral anticoagulation were offered the insertion of a cardiac event recorder. Regular follow-up for 1 year recorded the incidence of AF. Of the 393 patients with ischemic stroke, 65 (16.5%) had a cryptogenic stroke, and in 22 eligible patients, an event recorder was inserted. After 1 year, in 6 of 22 patients (27.3%), AF was detected. These preliminary data show that insertion of cardiac event recorder was eligible in approximately one third of patients with cryptogenic stroke and detected in approximately one quarter of these patients new AF.

  7. Real time deforestation detection using ann and satellite images the Amazon rainforest study case

    CERN Document Server

    Nunes Kehl, Thiago; Roberto Veronez, Maurício; Cesar Cazella, Silvio

    2015-01-01

    The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides parameterization of the configuration for the neural network training to enable us to select the best neural architecture to address the problem. The tool makes use of confusion matrices to determine the degree of success of the network. A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network. The analysis enabled verification of quality of the implemented neural network classification and also aided in understanding the dynamics of deforestation in the Amazon rainforest, thereby highlighting the vast potential of neural networks for image classification. However, the complex task of detection of predatory actions at the beginning, i.e., generation of consistent alarms, instead of false alarms has not bee...

  8. A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

    Directory of Open Access Journals (Sweden)

    N. Zarrinpanjeh

    2017-09-01

    Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  9. A Comprehensive Training Data Set for the Development of Satellite-Based Volcanic Ash Detection Algorithms

    Science.gov (United States)

    Schmidl, Marius

    2017-04-01

    We present a comprehensive training data set covering a large range of atmospheric conditions, including disperse volcanic ash and desert dust layers. These data sets contain all information required for the development of volcanic ash detection algorithms based on artificial neural networks, urgently needed since volcanic ash in the airspace is a major concern of aviation safety authorities. Selected parts of the data are used to train the volcanic ash detection algorithm VADUGS. They contain atmospheric and surface-related quantities as well as the corresponding simulated satellite data for the channels in the infrared spectral range of the SEVIRI instrument on board MSG-2. To get realistic results, ECMWF, IASI-based, and GEOS-Chem data are used to calculate all parameters describing the environment, whereas the software package libRadtran is used to perform radiative transfer simulations returning the brightness temperatures for each atmospheric state. As optical properties are a prerequisite for radiative simulations accounting for aerosol layers, the development also included the computation of optical properties for a set of different aerosol types from different sources. A description of the developed software and the used methods is given, besides an overview of the resulting data sets.

  10. a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

    Science.gov (United States)

    Zarrinpanjeh, N.; Dadrassjavan, F.

    2017-09-01

    Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

  11. Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

    Science.gov (United States)

    Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

    2017-04-01

    The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

  12. Asynchronous Processing of a Constellation of Geostationary and Polar-Orbiting Satellites for Fire Detection and Smoke Estimation

    Science.gov (United States)

    Hyer, E. J.; Peterson, D. A.; Curtis, C. A.; Schmidt, C. C.; Hoffman, J.; Prins, E. M.

    2014-12-01

    The Fire Locating and Monitoring of Burning Emissions (FLAMBE) system converts satellite observations of thermally anomalous pixels into spatially and temporally continuous estimates of smoke release from open biomass burning. This system currently processes data from a constellation of 5 geostationary and 2 polar-orbiting sensors. Additional sensors, including NPP VIIRS and the imager on the Korea COMS-1 geostationary satellite, will soon be added. This constellation experiences schedule changes and outages of various durations, making the set of available scenes for fire detection highly variable on an hourly and daily basis. Adding to the complexity, the latency of the satellite data is variable between and within sensors. FLAMBE shares with many fire detection systems the goal of detecting as many fires as possible as early as possible, but the FLAMBE system must also produce a consistent estimate of smoke production with minimal artifacts from the changing constellation. To achieve this, NRL has developed a system of asynchronous processing and cross-calibration that permits satellite data to be used as it arrives, while preserving the consistency of the smoke emission estimates. This talk describes the asynchronous data ingest methodology, including latency statistics for the constellation. We also provide an overview and show results from the system we have developed to normalize multi-sensor fire detection for consistency.

  13. Fetal beat detection in abdominal ECG recordings: global and time adaptive approaches

    International Nuclear Information System (INIS)

    Rodrigues, Rui

    2014-01-01

    We present a method for location of fetal QRS in maternal abdominal ECG recordings. This method’s initial, global approach was proposed in the context of the 2013 PhysioNet/Computing in Cardiology Challenge where it was tested on the 447 four channel one-minute recordings. The first step is filtering to eliminate baseline wander and high frequency noise. Upon detection, maternal QRS is removed on each channel using a filter applied to the other three channels. Next we locate fetal QRS on each channel and select the channel with the best set of detections. The method was awarded the third-best score in the Challenge event 1 with 278.755 (beats/minute) and the fourth-best score on event 2 with 28.201 ms. The 5 min long recordings of the Abdominal and Direct Fetal ECG Database were used to further test the method. This database contains five recordings obtained from women in labor. Results in these longer recordings were not satisfactory. This appears to be particularly the case in recordings with a more clearly non-stationary nature. In a new approach to our method, some changes are introduced. Two features are updated over time: the filter used to eliminate maternal QRS and the channel used to detect fetal beats. These changes significantly improved the QRS detection performance on longer recordings, but the scores on the 1 minute Challenge recordings were degraded. (paper)

  14. Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

    2014-12-01

    Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

  15. Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.

    Directory of Open Access Journals (Sweden)

    Erico N de Souza

    Full Text Available A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM using vessel speed as observation variable. For longliners we have designed a Data Mining (DM approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.

  16. Use of high-resolution satellite images for detection of geothermal reservoirs

    Science.gov (United States)

    Arellano-Baeza, A. A.

    2012-12-01

    Chile has an enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile and Puchuldiza geothermal field located in the Region of Tarapaca. It was done by applying the lineament extraction technique developed by author. These structures have been compared with the distribution of main geological structures obtained in the fields. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

  17. About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

    Directory of Open Access Journals (Sweden)

    François Peyret

    2013-01-01

    Full Text Available Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.

  18. About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

    Science.gov (United States)

    Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François

    2013-01-01

    Reliable GPS positioning in city environment is a key issue actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results. PMID:23344379

  19. AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

    Directory of Open Access Journals (Sweden)

    N. Champion

    2012-08-01

    Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

  20. Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Biao Wang

    2017-08-01

    Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

  1. On the use of Satellite Remote Sensing and GIS to detect NO2 in the Troposphere

    DEFF Research Database (Denmark)

    Nielsen, Søren Zebitz

    2012-01-01

    This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...... measured in Denmark. Trends in the data are assessed and declining trends are seen over several European cities, whereas no significant trends are found in the Danish area. The mean distribution of NO2 from the satellite data is also used to evaluate the NOx emission inventory....

  2. Comparison of semiautomated bird song recognition with manual detection of recorded bird song samples

    OpenAIRE

    Lisa A. Venier; Marc J. Mazerolle; Anna Rodgers; Ken A. McIlwrick; Stephen Holmes; Dean Thompson

    2017-01-01

    Automated recording units are increasingly being used to sample wildlife populations. These devices can produce large amounts of data that are difficult to process manually. However, the information in the recordings can be summarized with semiautomated sound recognition software. Our objective was to assess the utility of the semiautomated bird song recognizers to produce data useful for conservation and sustainable forest management applications. We compared detection data generated from ex...

  3. Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

    Science.gov (United States)

    Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

    2017-07-01

    Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

  4. Flexible Method for the Automated Offline-Detection of Artifacts in Multi-Channel Electroencephalogram Recordings

    DEFF Research Database (Denmark)

    Waser, Markus; Garn, Heinrich; Benke, Thomas

    2017-01-01

    . However, these preprocessing steps do not allow for complete artifact correction. We propose a method for the automated offline-detection of remaining artifacts after preprocessing in multi-channel EEG recordings. In contrast to existing methods it requires neither adaptive parameters varying between...... recordings nor a topography template. It is suited for short EEG segments and is flexible with regard to target applications. The algorithm was developed and tested on 60 clinical EEG samples of 20 seconds each that were recorded both in resting state and during cognitive activation to gain a realistic...

  5. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

  6. Conflict Detection Performance Analysis for Function Allocation Using Time-Shifted Recorded Traffic Data

    Science.gov (United States)

    Guerreiro, Nelson M.; Butler, Ricky W.; Maddalon, Jeffrey M.; Hagen, George E.; Lewis, Timothy A.

    2015-01-01

    The performance of the conflict detection function in a separation assurance system is dependent on the content and quality of the data available to perform that function. Specifically, data quality and data content available to the conflict detection function have a direct impact on the accuracy of the prediction of an aircraft's future state or trajectory, which, in turn, impacts the ability to successfully anticipate potential losses of separation (detect future conflicts). Consequently, other separation assurance functions that rely on the conflict detection function - namely, conflict resolution - are prone to negative performance impacts. The many possible allocations and implementations of the conflict detection function between centralized and distributed systems drive the need to understand the key relationships that impact conflict detection performance, with respect to differences in data available. This paper presents the preliminary results of an analysis technique developed to investigate the impacts of data quality and data content on conflict detection performance. Flight track data recorded from a day of the National Airspace System is time-shifted to create conflicts not present in the un-shifted data. A methodology is used to smooth and filter the recorded data to eliminate sensor fusion noise, data drop-outs and other anomalies in the data. The metrics used to characterize conflict detection performance are presented and a set of preliminary results is discussed.

  7. A neural network detection system for lower-hybrid cavities in electron plasma density measured by the FREJA satellite

    International Nuclear Information System (INIS)

    Waldemark, J.; Karlsson, Jan

    1995-03-01

    This paper presents a lower-hybrid cavity detection system, CDS, for measurements of electron plasma density on the FREJA satellite wave experiment. The system can reduce the amount of data to be analysed by as much as 96% and still retain more than 85% of the desired information. The CDS is a combination of a hybrid neural network, HNN and expert rules. The HNN is a Self Organizing Map, SOM, combined with a feed forward back propagation neural net, BP. The CDS can be controlled by the user to operate with various degrees of sensitivity. Maximum detection capability is as high as 95% with data reduction lowered to 85%. 10 refs

  8. Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

    DEFF Research Database (Denmark)

    Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

    2005-01-01

    The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained in approxima......The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...

  9. Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device

    DEFF Research Database (Denmark)

    Saadi, Dorthe Bodholt; Egstrup, Kenneth; Branebjerg, Jens

    2012-01-01

    We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from ...

  10. Automatic lameness detection based on consecutive 3D-video recordings

    NARCIS (Netherlands)

    Hertem, van T.; Viazzi, S.; Steensels, M.; Maltz, E.; Antler, A.; Alchanatis, V.; Schlageter-Tello, A.; Lokhorst, C.; Romanini, C.E.B.; Bahr, C.; Berckmans, D.; Halachmi, I.

    2014-01-01

    Manual locomotion scoring for lameness detection is a time-consuming and subjective procedure. Therefore, the objective of this study is to optimise the classification output of a computer vision based algorithm for automated lameness scoring. Cow gait recordings were made during four consecutive

  11. Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

    Science.gov (United States)

    Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

    2018-01-01

    To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

  12. Detection of High Frequency Oscillations by Hybrid Depth Electrodes in Standard Clinical Intracranial EEG Recordings

    Directory of Open Access Journals (Sweden)

    Efstathios D Kondylis

    2014-08-01

    Full Text Available High frequency oscillations (HFOs have been proposed as a novel marker for epileptogenic tissue, spurring tremendous research interest into the characterization of these transient events. A wealth of continuously recorded intracranial electroencephalographic (iEEG data is currently available from patients undergoing invasive monitoring for the surgical treatment of epilepsy. In contrast to data recorded on research-customized recording systems, data from clinical acquisition systems remain an underutilized resource for HFO detection in most centers. The effective and reliable use of this clinically obtained data would be an important advance in the ongoing study of HFOs and their relationship to ictogenesis. The diagnostic utility of HFOs ultimately will be limited by the ability of clinicians to detect these brief, sporadic, and low amplitude events in an electrically noisy clinical environment. Indeed, one of the most significant factors limiting the use of such clinical recordings for research purposes is their low signal to noise ratio, especially in the higher frequency bands. In order to investigate the presence of HFOs in clinical data, we first obtained continuous intracranial recordings in a typical clinical environment using a commercially available, commonly utilized data acquisition system and off the shelf hybrid macro/micro depth electrodes. This data was then inspected for the presence of HFOs using semi-automated methods and expert manual review. With targeted removal of noise frequency content, HFOs were detected on both macro- and micro-contacts, and preferentially localized to seizure onset zones. HFOs detected by the offline, semi-automated method were also validated in the clinical viewer, demonstrating that 1 this clinical system allows for the visualization of HFOs, and 2 with effective signal processing, clinical recordings can yield valuable information for offline analysis.

  13. 5-bp Classical Satellite DNA Loci from Chromosome-1 Instability in Cervical Neoplasia Detected by DNA Breakage Detection/Fluorescence in Situ Hybridization (DBD-FISH).

    Science.gov (United States)

    Cortés-Gutiérrez, Elva I; Ortíz-Hernández, Brenda L; Dávila-Rodríguez, Martha I; Cerda-Flores, Ricardo M; Fernández, José Luis; López-Fernández, Carmen; Gosálvez, Jaime

    2013-02-19

    We aimed to evaluate the association between the progressive stages of cervical neoplasia and DNA damage in 5-bp classical satellite DNA sequences from chromosome-1 in cervical epithelium and in peripheral blood lymphocytes using DNA breakage detection/fluorescence in situ hybridization (DBD-FISH). A hospital-based unmatched case-control study was conducted in 2011 with a sample of 30 women grouped according to disease stage and selected according to histological diagnosis; 10 with low-grade squamous intraepithelial lesions (LG-SIL), 10 with high-grade SIL (HG-SIL), and 10 with no cervical lesions, from the Unidad Medica de Alta Especialidad of The Mexican Social Security Institute, IMSS, Mexico. Specific chromosome damage levels in 5-bp classical satellite DNA sequences from chromosome-1 were evaluated in cervical epithelium and peripheral blood lymphocytes using the DBD-FISH technique. Whole-genome DNA hybridization was used as a reference for the level of damage. Results of Kruskal-Wallis test showed a significant increase according to neoplastic development in both tissues. The instability of 5-bp classical satellite DNA sequences from chromosome-1 was evidenced using chromosome-orientation FISH. In conclusion, we suggest that the progression to malignant transformation involves an increase in the instability of 5-bp classical satellite DNA sequences from chromosome-1.

  14. 5-bp Classical Satellite DNA Loci from Chromosome-1 Instability in Cervical Neoplasia Detected by DNA Breakage Detection/Fluorescence in Situ Hybridization (DBD-FISH

    Directory of Open Access Journals (Sweden)

    Jaime Gosálvez

    2013-02-01

    Full Text Available We aimed to evaluate the association between the progressive stages of cervical neoplasia and DNA damage in 5-bp classical satellite DNA sequences from chromosome-1 in cervical epithelium and in peripheral blood lymphocytes using DNA breakage detection/fluorescence in situ hybridization (DBD-FISH. A hospital-based unmatched case-control study was conducted in 2011 with a sample of 30 women grouped according to disease stage and selected according to histological diagnosis; 10 with low-grade squamous intraepithelial lesions (LG-SIL, 10 with high-grade SIL (HG-SIL, and 10 with no cervical lesions, from the Unidad Medica de Alta Especialidad of The Mexican Social Security Institute, IMSS, Mexico. Specific chromosome damage levels in 5-bp classical satellite DNA sequences from chromosome-1 were evaluated in cervical epithelium and peripheral blood lymphocytes using the DBD-FISH technique. Whole-genome DNA hybridization was used as a reference for the level of damage. Results of Kruskal-Wallis test showed a significant increase according to neoplastic development in both tissues. The instability of 5-bp classical satellite DNA sequences from chromosome-1 was evidenced using chromosome-orientation FISH. In conclusion, we suggest that the progression to malignant transformation involves an increase in the instability of 5-bp classical satellite DNA sequences from chromosome-1.

  15. Reliability of recordings of subgingival calculus detected using an ultrasonic device.

    Science.gov (United States)

    Corraini, Priscila; López, Rodrigo

    2015-04-01

    To assess the intra-examiner reliability of recordings of subgingival calculus detected using an ultrasonic device, and to investigate the influence of subject-, tooth- and site-level factors on the reliability of these subgingival calculus recordings. On two occasions, within a 1-week interval, 147 adult periodontitis patients received a full-mouth clinical periodontal examination by a single trained examiner. Duplicate subgingival calculus recordings, in six sites per tooth, were obtained using an ultrasonic device for calculus detection and removal. Agreement was observed in 65 % of the 22,584 duplicate subgingival calculus recordings, ranging 45 % to 83 % according to subject. Using hierarchical modeling, disagreements in the subgingival calculus duplicate recordings were more likely in all other sites than the mid-buccal, and in sites harboring supragingival calculus. Disagreements were less likely in sites with PD ≥  4 mm and with furcation involvement  ≥  degree 2. Bleeding on probing or suppuration did not influence the reliability of subgingival calculus. At the subject-level, disagreements were less likely in patients presenting with the highest and lowest extent categories of the covariate subgingival calculus. The reliability of subgingival calculus recordings using the ultrasound technology is reasonable. The results of the present study suggest that the reliability of subgingival calculus recordings is not influenced by the presence of inflammation. Moreover, subgingival calculus can be more reliably detected using the ultrasound device at sites with higher need for periodontal therapy, i.e., sites presenting with deep pockets and premolars and molars with furcation involvement.

  16. Synthesis of a quarter-century of satellite and airborne altimetry records to resolve long-term ice sheet elevation change

    Science.gov (United States)

    Nilsson, J.; Paolo, F. S.; Simonsen, S.; Gardner, A. S.

    2017-12-01

    Satellite and airborne altimetry provide the longest continuous record from which the mass balance of the Antarctic ice sheet can be derived, starting with the launch of ERS-1 in 1992. Accurate knowledge of the long-term mass balance is vital for understanding the geophysical processes governing the ice sheet contribution to present day sea-level rise. However, this record is comprised of several different measurement systems, with different accuracies and varying resolution. This poses a major challenge on the interpretation and reconstruction of consistent elevation-change time series for determining long-term ice sheet trends and variability. Previous studies using data from multiple satellite altimetry missions have relied on a cross-calibration technique based on crossover bias analysis to merge records from different sensors. This methodology, though accurate, limits the spatial coverage to typical resolutions of 10-50 km, restricting the approach to regional or continental-wide studies. In this study, we present a novel framework for seamless integration of heterogeneous altimetry records, using an adaptive least-squares minimization technique. The procedure allows reconstructing time series at fine spatial (sheet, including both data from the European Space Agency (ERS-1, ERS-2, Envisat and CryoSat-2) and NASA (ICESat and Operation IceBridge), with future inclusion of data from NASA's ICESat-2. Mission specific errors, estimated from independent airborne measurements and crossover analysis, are propagated to derive uncertainty bounds for each individual time series. We also perform an extensive analysis of the major corrections applied to raw satellite altimetry data to assess their overall effect on the estimated uncertainty. This methodology will allow us to determine robust long-term changes in the surface elevation of grounded Antarctic ice. Such a dataset will be invaluable to advancing ice sheet assimilation efforts and to disentangle causal

  17. Use of the high-resolution satellite images for detection of fractures related to the ore deposits

    Science.gov (United States)

    Cruz-Mondaca, M.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

    2012-12-01

    The Aster and GeoEye satellite high-resolution images were used to detect the structures related to the fracturing of the upper crust in the North of Chile. In particular, lineament analysis has been applied to detect the presence of epithermal fluids of low sulfurization associated with the Paleozoic ore deposits. These results have been compared with the location of the minerals altered by the presence of geothermal fluids detected using the spectral libraries. Later, the presence of fractures has been corroborated during recognition of fractures in situ and the geochemical analysis of samples of minerals altered by the presence of fluids. It was shown that the results obtained are relevant for the gold vein detection.

  18. Synergistic Use of Satellite Volcano Detection and Science: A Fifteen Year Perspective of ASTER on Terra

    Science.gov (United States)

    Ramsey, M. S.

    2014-12-01

    The success of Terra-based observations using the ASTER instrument of active volcanic processes early in the mission gave rise to a funded NASA program designed to both increase the number of ASTER observations following an eruption and validate the satellite data. The urgent request protocol (URP) system for ASTER grew out of this initial study and has now operated in conjunction with and the support of the Alaska Volcano Observatory, the University of Alaska Fairbanks, the University of Hawaii, the USGS Land Processes DAAC, and the ASTER science team. The University of Pittsburgh oversees this rapid response/sensor-web system, which until 2011 had focused solely on the active volcanoes in the North Pacific region. Since that time, it has been expanded to operate globally with AVHRR and MODIS and now ASTER VNIR/TIR data are being acquired at numerous erupting volcanoes around the world. This program relies on the increased temporal resolution of AVHRR/MODIS midwave infrared data to trigger the next available ASTER observation, which results in ASTER data as frequently as every 2-5 days. For many targets, the URP has increased the observational frequency over active eruptions by as much 50%. The data have been used for operational response to new eruptions, longer-term scientific studies such as capturing detailed changes in lava domes/flows, pyroclastic flows and lahars. These data have also been used to infer the emplacement of new lava lobes, detect endogenous dome growth, and interpret hazardous dome collapse events. The emitted TIR radiance from lava surfaces has also been used effectively to model composition, texture and degassing. Now, this long-term archive of volcanic image data is being mined to provide statistics on the expectations of future high-repeat TIR data such as that proposed for the NASA HyspIRI mission. In summary, this operational/scientific program utilizing the unique properties of ASTER and the Terra mission has shown the potential for

  19. Detecting inpatient falls by using natural language processing of electronic medical records

    Directory of Open Access Journals (Sweden)

    Toyabe Shin-ichi

    2012-12-01

    Full Text Available Abstract Background Incident reporting is the most common method for detecting adverse events in a hospital. However, under-reporting or non-reporting and delay in submission of reports are problems that prevent early detection of serious adverse events. The aim of this study was to determine whether it is possible to promptly detect serious injuries after inpatient falls by using a natural language processing method and to determine which data source is the most suitable for this purpose. Methods We tried to detect adverse events from narrative text data of electronic medical records by using a natural language processing method. We made syntactic category decision rules to detect inpatient falls from text data in electronic medical records. We compared how often the true fall events were recorded in various sources of data including progress notes, discharge summaries, image order entries and incident reports. We applied the rules to these data sources and compared F-measures to detect falls between these data sources with reference to the results of a manual chart review. The lag time between event occurrence and data submission and the degree of injury were compared. Results We made 170 syntactic rules to detect inpatient falls by using a natural language processing method. Information on true fall events was most frequently recorded in progress notes (100%, incident reports (65.0% and image order entries (12.5%. However, F-measure to detect falls using the rules was poor when using progress notes (0.12 and discharge summaries (0.24 compared with that when using incident reports (1.00 and image order entries (0.91. Since the results suggested that incident reports and image order entries were possible data sources for prompt detection of serious falls, we focused on a comparison of falls found by incident reports and image order entries. Injury caused by falls found by image order entries was significantly more severe than falls detected by

  20. Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Hyangsun Han

    2015-07-01

    Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.

  1. Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection

    Directory of Open Access Journals (Sweden)

    Sanggyun Lee

    2016-08-01

    Full Text Available Satellite altimeters have been used to monitor Arctic sea ice thickness since the early 2000s. In order to estimate sea ice thickness from satellite altimeter data, leads (i.e., cracks between ice floes should first be identified for the calculation of sea ice freeboard. In this study, we proposed novel approaches for lead detection using two machine learning algorithms: decision trees and random forest. CryoSat-2 satellite data collected in March and April of 2011–2014 over the Arctic region were used to extract waveform parameters that show the characteristics of leads, ice floes and ocean, including stack standard deviation, stack skewness, stack kurtosis, pulse peakiness and backscatter sigma-0. The parameters were used to identify leads in the machine learning models. Results show that the proposed approaches, with overall accuracy >90%, produced much better performance than existing lead detection methods based on simple thresholding approaches. Sea ice thickness estimated based on the machine learning-detected leads was compared to the averaged Airborne Electromagnetic (AEM-bird data collected over two days during the CryoSat Validation experiment (CryoVex field campaign in April 2011. This comparison showed that the proposed machine learning methods had better performance (up to r = 0.83 and Root Mean Square Error (RMSE = 0.29 m compared to thickness estimation based on existing lead detection methods (RMSE = 0.86–0.93 m. Sea ice thickness based on the machine learning approaches showed a consistent decline from 2011–2013 and rebounded in 2014.

  2. CLUMPY STREAMS FROM CLUMPY HALOS: DETECTING MISSING SATELLITES WITH COLD STELLAR STRUCTURES

    International Nuclear Information System (INIS)

    Yoon, Joo Heon; Johnston, Kathryn V.; Hogg, David W.

    2011-01-01

    Dynamically cold stellar streams are ideal probes of the gravitational field of the Milky Way. This paper re-examines the question of how such streams might be used to test for the presence of m issing satellites - the many thousands of dark-matter subhalos with masses 10 5 -10 7 M sun which are seen to orbit within Galactic-scale dark-matter halos in simulations of structure formation in ΛCDM cosmologies. Analytical estimates of the frequency and energy scales of stream encounters indicate that these missing satellites should have a negligible effect on hot debris structures, such as the tails from the Sagittarius dwarf galaxy. However, long cold streams, such as the structure known as GD1 or those from the globular cluster Palomar 5 (Pal 5), are expected to suffer many tens of direct impacts from missing satellites during their lifetimes. Numerical experiments confirm that these impacts create gaps in the debris' orbital energy distribution, which will evolve into degree- and sub-degree-scale fluctuations in surface density over the age of the debris. Maps of Pal 5's own stream contain surface density fluctuations on these scales. The presence and frequency of these inhomogeneities suggests the existence of a population of missing satellites in numbers predicted in the standard ΛCDM cosmologies.

  3. Spatio-temporal hotspots of satellite-tracked arctic foxes reveal a large detection range in a mammalian predator.

    Science.gov (United States)

    Lai, Sandra; Bêty, Joël; Berteaux, Dominique

    2015-01-01

    The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice. While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio-temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one-two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast. Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.

  4. A simple system for detection of EEG artifacts in polysomnographic recordings.

    Science.gov (United States)

    Durka, P J; Klekowicz, H; Blinowska, K J; Szelenberger, W; Niemcewicz, Sz

    2003-04-01

    We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

  5. MODVOLC2: A Hybrid Time Series Analysis for Detecting Thermal Anomalies Applied to Thermal Infrared Satellite Data

    Science.gov (United States)

    Koeppen, W. C.; Wright, R.; Pilger, E.

    2009-12-01

    We developed and tested a new, automated algorithm, MODVOLC2, which analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes, fires, and gas flares. MODVOLC2 combines two previously developed algorithms, a simple point operation algorithm (MODVOLC) and a more complex time series analysis (Robust AVHRR Techniques, or RAT) to overcome the limitations of using each approach alone. MODVOLC2 has four main steps: (1) it uses the original MODVOLC algorithm to process the satellite data on a pixel-by-pixel basis and remove thermal outliers, (2) it uses the remaining data to calculate reference and variability images for each calendar month, (3) it compares the original satellite data and any newly acquired data to the reference images normalized by their variability, and it detects pixels that fall outside the envelope of normal thermal behavior, (4) it adds any pixels detected by MODVOLC to those detected in the time series analysis. Using test sites at Anatahan and Kilauea volcanoes, we show that MODVOLC2 was able to detect ~15% more thermal anomalies than using MODVOLC alone, with very few, if any, known false detections. Using gas flares from the Cantarell oil field in the Gulf of Mexico, we show that MODVOLC2 provided results that were unattainable using a time series-only approach. Some thermal anomalies (e.g., Cantarell oil field flares) are so persistent that an additional, semi-automated 12-µm correction must be applied in order to correctly estimate both the number of anomalies and the total excess radiance being emitted by them. Although all available data should be included to make the best possible reference and variability images necessary for the MODVOLC2, we estimate that at least 80 images per calendar month are required to generate relatively good statistics from which to run MODVOLC2, a condition now globally met by a decade of MODIS observations. We also found

  6. Leveraging GeoTIFF Compatibility for Visualizing a New EASE-Grid 2.0 Global Satellite Passive Microwave Climate Record

    Science.gov (United States)

    Paget, A. C.; Brodzik, M. J.; Long, D. G.; Hardman, M.

    2016-02-01

    The historical record of satellite-derived passive microwave brightness temperatures comprises data from multiple imaging radiometers (SMMR, SSM/I-SSMIS, AMSR-E), spanning nearly 40 years of Earth observations from 1978 to the present. Passive microwave data are used to monitor time series of many climatological variables, including ocean wind speeds, cloud liquid water and sea ice concentrations and ice velocity. Gridded versions of passive microwave data have been produced using various map projections (polar stereographic, Lambert azimuthal equal-area, cylindrical equal-area, quarter-degree Platte-Carree) and data formats (flat binary, HDF). However, none of the currently available versions can be rendered in the common visualization standard, geoTIFF, without requiring cartographic reprojection. Furthermore, the reprojection details are complicated and often require expert knowledge of obscure software package options. We are producing a consistently calibrated, completely reprocessed data set of this valuable multi-sensor satellite record, using EASE-Grid 2.0, an improved equal-area projection definition that will require no reprojection for translation into geoTIFF. Our approach has been twofold: 1) define the projection ellipsoid to match the reference datum of the satellite data, and 2) include required file-level metadata for standard projection software to correctly render the data in the geoTIFF standard. The Calibrated, Enhanced Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR), leverages image reconstruction techniques to enhance gridded spatial resolution to 3 km and uses newly available intersensor calibrations to improve the quality of derived geophysical products. We expect that our attention to easy geoTIFF compatibility will foster higher-quality analysis with the CETB product by enabling easy and correct intercomparison with other gridded and in situ data.

  7. Developing a Validated Long-Term Satellite-Based Albedo Record in the Central Alaska Range to Improve Regional Hydroclimate Reconstructions

    Science.gov (United States)

    Kreutz, K. J.; Godaire, T. P.; Burakowski, E. A.; Winski, D.; Campbell, S. W.; Wang, Z.; Sun, Q.; Hamilton, G. S.; Birkel, S. D.; Wake, C. P.; Osterberg, E. C.; Schaaf, C.

    2015-12-01

    Mountain glaciers around the world, particularly in Alaska, are experiencing significant surface mass loss from rapid climatic shifts and constitute a large proportion of the cryosphere's contribution to sea level rise. Surface albedo acts as a primary control on a glacier's mass balance, yet it is difficult to measure and quantify spatially and temporally in steep, mountainous settings. During our 2013 field campaign in Denali National Park to recover two surface to bedrock ice cores, we used an Analytical Spectral Devices (ASD) FieldSpec4 Standard Resolution spectroradiometer to measure incoming solar radiation, outgoing surface reflectance and optical grain size on the Kahiltna Glacier and at the Kahiltna Base Camp. A Campbell Scientific automatic weather station was installed on Mount Hunter (3900m) in June 2013, complementing a longer-term (2008-present) station installed at Kahiltna Base Camp (2100m). Use of our in situ data aids in the validation of surface albedo values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite imagery. Comparisons are made between ASD FieldSpec4 ground measurements and 500m MODIS imagery to assess the ability of MODIS to capture the variability of surface albedo across the glacier surface. The MODIS MCD43A3 BRDF/Albedo Product performs well at Kahiltna Base Camp (albedo (10-28% relative to ASD data) appear to occur along the Kahiltna Glacier due to the snow-free valley walls being captured in the 500m MODIS footprint. Incorporating Landsat imagery will strengthen our interpretations and has the potential to produce a long-term (1982-present) validated satellite albedo record for steep and mountainous terrain. Once validation is complete, we will compare the satellite-derived albedo record to the Denali ice core accumulation rate, aerosol records (i.e. volcanics and biomass burning), and glacier mass balance data. This research will ultimately contribute to an improved understanding of the

  8. Fetal movement detection based on QRS amplitude variations in abdominal ECG recordings.

    Science.gov (United States)

    Rooijakkers, M J; de Lau, H; Rabotti, C; Oei, S G; Bergmans, J W M; Mischi, M

    2014-01-01

    Evaluation of fetal motility can give insight in fetal health, as a strong decrease can be seen as a precursor to fetal death. Typically, the assessment of fetal health by fetal movement detection relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% to 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are typically unsuitable for ambulatory or long-term observation. In this paper, a novel method for fetal motion detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. The proposed method has a sensitivity and specificity of 0.67 and 0.90, respectively, outperforming alternative fetal ECG-based methods from the literature.

  9. Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

    Science.gov (United States)

    Moody, Daniela Irina

    2018-04-17

    An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

  10. Automatic Threshold Determination for a Local Approach of Change Detection in Long-Term Signal Recordings

    Directory of Open Access Journals (Sweden)

    David Hewson

    2007-01-01

    Full Text Available CUSUM (cumulative sum is a well-known method that can be used to detect changes in a signal when the parameters of this signal are known. This paper presents an adaptation of the CUSUM-based change detection algorithms to long-term signal recordings where the various hypotheses contained in the signal are unknown. The starting point of the work was the dynamic cumulative sum (DCS algorithm, previously developed for application to long-term electromyography (EMG recordings. DCS has been improved in two ways. The first was a new procedure to estimate the distribution parameters to ensure the respect of the detectability property. The second was the definition of two separate, automatically determined thresholds. One of them (lower threshold acted to stop the estimation process, the other one (upper threshold was applied to the detection function. The automatic determination of the thresholds was based on the Kullback-Leibler distance which gives information about the distance between the detected segments (events. Tests on simulated data demonstrated the efficiency of these improvements of the DCS algorithm.

  11. An Enhanced Satellite-Based Algorithm for Detecting and Tracking Dust Outbreaks by Means of SEVIRI Data

    Directory of Open Access Journals (Sweden)

    Francesco Marchese

    2017-05-01

    Full Text Available Dust outbreaks are meteorological phenomena of great interest for scientists and authorities (because of their impact on the climate, environment, and human activities, which may be detected, monitored, and characterized from space using different methods and procedures. Among the recent dust detection algorithms, the RSTDUST multi-temporal technique has provided good results in different geographic areas (e.g., Mediterranean basin; Arabian Peninsula, exhibiting a better performance than traditional split window methods, in spite of some limitations. In this study, we present an optimized configuration of this technique, which better exploits data provided by Spinning Enhanced Visible and Infrared Imager (SEVIRI aboard Meteosat Second Generation (MSG satellites to address those issues (e.g., sensitivity reduction over arid and semi-arid regions; dependence on some meteorological clouds. Three massive dust events affecting Europe and the Mediterranean basin in May 2008/2010 are analysed in this work, using information provided by some independent and well-established aerosol products to assess the achieved results. The study shows that the proposed algorithm, christened eRSTDUST (i.e., enhanced RSTDUST, which provides qualitative information about dust outbreaks, is capable of increasing the trade-off between reliability and sensitivity. The results encourage further experimentations of this method in other periods of the year, also exploiting data provided by different satellite sensors, for better evaluating the advantages arising from the use of this dust detection technique in operational scenarios.

  12. DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

    Science.gov (United States)

    Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

    2017-12-01

    Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

  13. Detection of induced seismicity effects on ground surface using data from Sentinel 1A/1B satellites

    Science.gov (United States)

    Milczarek, W.

    2017-12-01

    Induced seismicity is the result of human activity and manifests itself in the form of shock and vibration of the ground surface. One of the most common factors causing the occurrence of induced shocks is underground mining activity. Sufficiently strong high-energy shocks may cause displacements of the ground surface. This type of shocks can have a significant impact on buildings and infrastructure. Assessment of the size and influence of induced seismicity on the ground surface is one of the major problems associated with mining activity. In Poland (Central Eastern Europe) induced seismicity occurs in the area of hard coal mining in the Upper Silesian Coal Basin and in the area of the Legnica - Głogów Copper Basin.The study presents an assessment of the use of satellite radar data (SAR) for the detection influence of induced seismicity in mining regions. Selected induced shocks from the period 2015- 2017 which occurred in the Upper Silesian Coal Basin and the Legnica - Głogów Copper Basin areas have been analyzed. In the calculations SAR data from the Sentinel 1A and Sentinel 1B satellites have been used. The results indicate the possibility of quickly and accurate detection of ground surface displacements after an induced shock. The results of SAR data processing were compared with the results from geodetic measurements. It has been shown that SAR data can be used to detect ground surface displacements on the relative small regions.

  14. Atrial fibrillation detected by external loop recording for seven days or two-day simultaneous Holter recording: A comparison in patients with ischemic stroke or transient ischemic attack.

    Science.gov (United States)

    Sejr, Michala Herskind; Nielsen, Jens Cosedis; Damgaard, Dorte; Sandal, Birgitte Forsom; May, Ole

    Atrial fibrillation (AF) is the most common cardiac cause of ischemic stroke and transient ischemic attack (IS/TIA). To compare the diagnostic value of seven-day external loop recording (ELR) and two-day Holter recording for detecting AF after IS/TIA. 191 IS/TIA patients without AF history. Endpoint was AF >30s. We started two-day Holter recording and seven-day ELR simultaneously. Seven-day ELR and two-day Holter recording detected the same three AF patients. ELR detected another six patients with AF adjudicated by cardiologists, four detections after Holter (3 vs. 7, p=0.125) and two false-positive detections during Holter. Seven-day ELR automatically classified 50/191 patients (26%) with AF, but only 7/50 (14%) were confirmed as AF by cardiologists. Seven-day ELR did not detect significantly more patients with AF than two-day Holter recording. 86% of patients with ELR-classified AF were false positives, indicating a poor performance of the automatic AF detection algorithm used. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. A Dynamic Enhancement With Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection

    Science.gov (United States)

    Miller, Steven D.; Bankert, Richard L.; Solbrig, Jeremy E.; Forsythe, John M.; Noh, Yoo-Jeong; Grasso, Lewis D.

    2017-12-01

    This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multispectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0, 1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color red/green/blue imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

  16. Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

    Science.gov (United States)

    Benzouai, Siham; Smara, Youcef

    2010-12-01

    The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

  17. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  18. Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review.

    Science.gov (United States)

    Despins, Laurel A

    Severe sepsis and septic shock are global issues with high mortality rates. Early recognition and intervention are essential to optimize patient outcomes. Automated detection using electronic medical record (EMR) data can assist this process. This review describes automated sepsis detection using EMR data. PubMed retrieved publications between January 1, 2005 and January 31, 2015. Thirteen studies met study criteria: described an automated detection approach with the potential to detect sepsis or sepsis-related deterioration in real or near-real time; focused on emergency department and hospitalized neonatal, pediatric, or adult patients; and provided performance measures or results indicating the impact of automated sepsis detection. Detection algorithms incorporated systemic inflammatory response and organ dysfunction criteria. Systems in nine studies generated study or care team alerts. Care team alerts did not consistently lead to earlier interventions. Earlier interventions did not consistently translate to improved patient outcomes. Performance measures were inconsistent. Automated sepsis detection is potentially a means to enable early sepsis-related therapy but current performance variability highlights the need for further research.

  19. Forensic applications of infrared imaging for the detection and recording of latent evidence.

    Science.gov (United States)

    Lin, Apollo Chun-Yen; Hsieh, Hsing-Mei; Tsai, Li-Chin; Linacre, Adrian; Lee, James Chun-I

    2007-09-01

    We report on a simple method to record infrared (IR) reflected images in a forensic science context. Light sources using ultraviolet light have been used previously in the detection of latent prints, but the use of infrared light has been subjected to less investigation. IR light sources were used to search for latent evidence and the images were captured by either video or using a digital camera with a CCD array sensitive to IR wavelength. Bloodstains invisible to the eye, inks, tire prints, gunshot residue, and charred document on dark background are selected as typical matters that may be identified during a forensic investigation. All the evidence types could be detected and identified using a range of photographic techniques. In this study, a one in eight times dilution of blood could be detected on 10 different samples of black cloth. When using 81 black writing inks, the observation rates were 95%, 88% and 42% for permanent markers, fountain pens and ball-point pens, respectively, on the three kinds of dark cloth. The black particles of gunshot residue scattering around the entrance hole under IR light were still observed at a distance of 60 cm from three different shooting ranges. A requirement of IR reflectivity is that there is a contrast between the latent evidence and the background. In the absence of this contrast no latent image will be detected, which is similar to all light sources. The use of a video camera allows the recording of images either at a scene or in the laboratory. This report highlights and demonstrates the robustness of IR to detect and record the presence of latent evidence.

  20. Automated Detection of Craters in Martian Satellite Imagery Using Convolutional Neural Networks

    Science.gov (United States)

    Norman, C. J.; Paxman, J.; Benedix, G. K.; Tan, T.; Bland, P. A.; Towner, M.

    2018-04-01

    Crater counting is used in determining surface age of planets. We propose improvements to martian Crater Detection Algorithms by implementing an end-to-end detection approach with the possibility of scaling the algorithm planet-wide.

  1. A SERS-active sensor based on heterogeneous gold nanostar core-silver nanoparticle satellite assemblies for ultrasensitive detection of aflatoxinB1.

    Science.gov (United States)

    Li, Aike; Tang, Lijuan; Song, Dan; Song, Shanshan; Ma, Wei; Xu, Liguang; Kuang, Hua; Wu, Xiaoling; Liu, Liqiang; Chen, Xin; Xu, Chuanlai

    2016-01-28

    A surface-enhanced Raman scattering (SERS) sensor based on gold nanostar (Au NS) core-silver nanoparticle (Ag NP) satellites was fabricated for the first time to detect aflatoxinB1 (AFB1). We constructed the SERS sensor using AFB1 aptamer (DNA1)-modified Ag satellites and a complementary sequence (DNA2)-modified Au NS core. The Raman label (ATP) was modified on the surface of Ag satellites. The SERS signal was enhanced when the satellite NP was attached to the Au core NS. The AFB1 aptamer on the surface of Ag satellites would bind to the targets when AFB1 was present in the system, Ag satellites were then removed and the SERS signal decreased. This SERS sensor showed superior specificity for AFB1 and the linear detection range was from 1 to 1000 pg mL(-1) with the limit of detection (LOD) of 0.48 pg mL(-1). The excellent recovery experiment using peanut milk demonstrated that the sensor could be applied in food and environmental detection.

  2. Automated detection of follow-up appointments using text mining of discharge records.

    Science.gov (United States)

    Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

    2010-06-01

    To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

  3. Intraesophageal pressure recording improves the detection of cough during multichannel intraluminal impedance testing in children.

    Science.gov (United States)

    Rosen, Rachel; Amirault, Janine; Giligan, Emily; Khatwa, Umakanth; Nurko, Samuel

    2014-01-01

    One of the primary reasons for referral for reflux testing is to correlate reflux events with symptoms such as cough. Adult studies have suggested that symptom recording is flawed and pediatricians feel this is an even more significant problem because there may be errors in both parental and patient reports. We hypothesize that intraesophageal pressure recording (IEPR) provides an objective method to identify coughs during reflux testing in children. We recruited 20 children undergoing multichannel intraluminal impedance with pH (pH-MII) testing for the evaluation of cough. We placed simultaneous intraesophageal pressure and pH-MII catheters. Tracings were blindly scored by 2 observers without knowledge of patient/parent symptom report. After the blinded scoring, patient/parent report of symptoms was recorded. Ninety-four percent of all coughs were detected by IEPR and only 48% of all coughs were reported by patients/parents. The mean time from the IEPR cough to the patient/parent cough was 11±16 seconds. Using IEPR as the criterion standard for the detection of cough, the sensitivity of patient report for the detection of cough is 46%. Using varying symptom windows because of the increased precision of IEPR, the number of patients with a positive symptom index could be reduced from 30% to 0%, preventing children from being falsely categorized as having reflux-related lung disease. Parental and patient symptom recording in children is inadequate for making the diagnosis of reflux-related lung disease. If patients undergo pH-MII testing for reflux-related cough, IEPR should become the new standard by which to correlate reflux with cough.

  4. Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

    Science.gov (United States)

    Shiffman, Smadar

    2004-01-01

    Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

  5. Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data.

    Science.gov (United States)

    Rogers, Brendan M; Solvik, Kylen; Hogg, Edward H; Ju, Junchang; Masek, Jeffrey G; Michaelian, Michael; Berner, Logan T; Goetz, Scott J

    2018-02-26

    Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems. © 2018 John Wiley & Sons Ltd.

  6. Experimental study of electronic electrostatic waves detected in the terrestrial magnetosphere by the satellite GEOS 2

    International Nuclear Information System (INIS)

    Canu, P.

    1982-09-01

    After reviewing the general characteristics of electrostator waves a brief resume is given of the observations made up to the present moment. The GEOS satellite and the ''wave'' experiment are described, as well as the method and results of the statistical study of the strong electrostatic wave observed. Creating mechanisms of diffuse auroras are discussed. In a later chapter a new method of using the relaxation probe is presented as well as the results it gives on the mode of propagation of waves in the neighbourhood of the FUH frequency [fr

  7. Analysis of satellite data for sensor improvement (detection of severe storms from space)

    Science.gov (United States)

    Fujita, T. T.

    1984-01-01

    Stereo photography of clouds over southeast Asia was obtained using NOAA-7 and the Japanese GMS. Due to the breakdown of GMS2, GMS1, which had been retired, is being used as the replacement satellite. The launch of GMS should permit the US-Japan stereo experiment to be reactivated. The Lear jet experiment based at Grand Island, Nebraska was successful and provided data on the Redwood Falls clouds & Grand Island thunderstorm; an anvil-top cirrus deck; a circular thunderstorm; and jumping cirrus. The IR temperature field of the thunderstorm which induced the Andrews AFB microburst was analyzed with 1 C accuracy. The microburst and severe thunderstorm project is being planned.

  8. Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus.

    Science.gov (United States)

    Hirschmann, J; Schoffelen, J M; Schnitzler, A; van Gerven, M A J

    2017-10-01

    To investigate the possibility of tremor detection based on deep brain activity. We re-analyzed recordings of local field potentials (LFPs) from the subthalamic nucleus in 10 PD patients (12 body sides) with spontaneously fluctuating rest tremor. Power in several frequency bands was estimated and used as input to Hidden Markov Models (HMMs) which classified short data segments as either tremor-free rest or rest tremor. HMMs were compared to direct threshold application to individual power features. Applying a threshold directly to band-limited power was insufficient for tremor detection (mean area under the curve [AUC] of receiver operating characteristic: 0.64, STD: 0.19). Multi-feature HMMs, in contrast, allowed for accurate detection (mean AUC: 0.82, STD: 0.15), using four power features obtained from a single contact pair. Within-patient training yielded better accuracy than across-patient training (0.84vs. 0.78, p=0.03), yet tremor could often be detected accurately with either approach. High frequency oscillations (>200Hz) were the best performing individual feature. LFP-based markers of tremor are robust enough to allow for accurate tremor detection in short data segments, provided that appropriate statistical models are used. LFP-based markers of tremor could be useful control signals for closed-loop deep brain stimulation. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  9. Development of a technique for long-term detection of precursors of strong earthquakes using high-resolution satellite images

    Science.gov (United States)

    Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.

    2012-12-01

    Among a variety of processes involved in seismic activity, the principal process is the accumulation and relaxation of stress in the crust, which takes place at the depth of tens of kilometers. While the Earth's surface bears at most the indirect sings of the accumulation and relaxation of the crust stress, it has long been understood that there is a strong correspondence between the structure of the underlying crust and the landscape. We assume the structure of the lineaments reflects an internal structure of the Earth's crust, and the variation of the lineament number and arrangement reflects the changes in the stress patterns related to the seismic activity. Contrary to the existing assumptions that lineament structure changes only at the geological timescale, we have found that the much faster seismic activity strongly affects the system of lineaments extracted from the high-resolution multispectral satellite images. Previous studies have shown that accumulation of the stress in the crust previous to a strong earthquake is directly related to the number increment and preferential orientation of lineament configuration present in the satellite images of epicenter zones. This effect increases with the earthquake magnitude and can be observed approximately since one month before. To study in details this effect we have developed a software based on a series of algorithms for automatic detection of lineaments. It was found that the Hough transform implemented after the application of discontinuity detection mechanisms like Canny edge detector or directional filters is the most robust technique for detection and characterization of changes in the lineament patterns related to strong earthquakes, which can be used as a robust long-term precursor of earthquakes indicating regions of strong stress accumulation.

  10. Test-day records as a tool for subclinical ketosis detection

    OpenAIRE

    Gantner Vesna; Potočnik K.; Jovanovac Sonja

    2009-01-01

    The prevalence, as well as the effect of subclinical ketosis on daily milk yield, was observed using 1.299,630 test-day records collected from January 2000 to December 2005 on 73,255 Slovenian Holstein cows. Subclinical ketosis was indicated by the fat to protein ratio (F/P ratio) higher than 1.5 in cows that yielded between 33 to 50 kg of milk per day (Eicher, 2004). The ketosis index was defined in relation to the timing of subclinical ketosis detection to the subsequent measures of test-da...

  11. Predictive modeling of structured electronic health records for adverse drug event detection.

    Science.gov (United States)

    Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik

    2015-01-01

    The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and

  12. Satellite detection of carbon monoxide emission prior to the Gujarat earthquake of 26 January 2001

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Ramesh P., E-mail: rsingh@chapman.edu [Department of Physics, Computational Science and Engineering, Schmid College of Science, Chapman University, One University Drive, Orange CA 92866 (United States); Senthil Kumar, J.; Zlotnicki, Jacques [Observatoire de Physique du Globe de Clermont-Ferrand, OPGC-CNRS, Campus des Cuzeaux, 24, av. des Landais, 63177 Aubiere Cedex (France); Kafatos, Menas [Department of Physics, Computational Science and Engineering, Schmid College of Science, Chapman University, One University Drive, Orange CA 92866 (United States)

    2010-04-15

    NOAA AVHRR images have clearly shown anomalous changes in land surface temperature associated with earthquakes in the past two decades. Soon after the Gujarat earthquake of January 26, 2001, an anomalous increase in land surface temperature was inferred from MODIS satellite data a few days prior to the main earthquake event. The cause of such an anomalous change in surface temperature prior to the earthquake is attributed to many probable phenomena, but no definite cause has been identified. In the present study, changes of a complementary nature were found of land surface temperature associated with the emission of CO from the epicentral region. The observed changes on land and atmosphere associated with the Gujarat earthquake of 26 January, 2001, show the existence of strong coupling between land, atmosphere and ionosphere.

  13. Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

    Science.gov (United States)

    Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

    2014-12-01

    Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

  14. Data-driven drug safety signal detection methods in pharmacovigilance using electronic primary care records: A population based study

    Directory of Open Access Journals (Sweden)

    Shang-Ming Zhou

    2017-04-01

    Data-driven analytic methods are a valuable aid to signal detection of ADEs from large electronic health records for drug safety monitoring. This study finds the methods can detect known ADE and so could potentially be used to detect unknown ADE.

  15. The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

    Science.gov (United States)

    Athale, R.; Lee, S. H.

    1976-01-01

    Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

  16. On the feasibility of using satellite gravity observations for detecting large-scale solid mass transfer events

    Science.gov (United States)

    Peidou, Athina C.; Fotopoulos, Georgia; Pagiatakis, Spiros

    2017-10-01

    The main focus of this paper is to assess the feasibility of utilizing dedicated satellite gravity missions in order to detect large-scale solid mass transfer events (e.g. landslides). Specifically, a sensitivity analysis of Gravity Recovery and Climate Experiment (GRACE) gravity field solutions in conjunction with simulated case studies is employed to predict gravity changes due to past subaerial and submarine mass transfer events, namely the Agulhas slump in southeastern Africa and the Heart Mountain Landslide in northwestern Wyoming. The detectability of these events is evaluated by taking into account the expected noise level in the GRACE gravity field solutions and simulating their impact on the gravity field through forward modelling of the mass transfer. The spectral content of the estimated gravity changes induced by a simulated large-scale landslide event is estimated for the known spatial resolution of the GRACE observations using wavelet multiresolution analysis. The results indicate that both the Agulhas slump and the Heart Mountain Landslide could have been detected by GRACE, resulting in {\\vert }0.4{\\vert } and {\\vert }0.18{\\vert } mGal change on GRACE solutions, respectively. The suggested methodology is further extended to the case studies of the submarine landslide in Tohoku, Japan, and the Grand Banks landslide in Newfoundland, Canada. The detectability of these events using GRACE solutions is assessed through their impact on the gravity field.

  17. Feasibility of Using Mobile ECG Recording Technology to Detect Atrial Fibrillation in Low-Resource Settings.

    Science.gov (United States)

    Evans, Grahame F; Shirk, Arianna; Muturi, Peter; Soliman, Elsayed Z

    2017-12-01

    Screening for atrial fibrillation (AF), a major risk factor for stroke that is on the rise in Africa, is becoming increasingly critical. This study sought to examine the feasibility of using mobile electrocardiogram (ECG) recording technology to detect AF. In this prospective observational study, we used a mobile ECG recorder to screen 50 African adults (66% women; mean age 54.3 ± 20.5 years) attending Kijabe Hospital (Kijabe, Kenya). Five hospital health providers involved in this study's data collection process also completed a self-administered survey to obtain information on their access to the Internet and mobile devices, both factors necessary to implement ECG mobile technology. Outcome measures included feasibility (completion of the study and recruitment of the patients on the planned study time frame) and the yield of the screening by the mobile ECG technology (ability to detect previously undiagnosed AF). Patients were recruited in a 2-week period as planned; only 1 of the 51 patients approached refused to participate (98% acceptance rate). All of the 50 patients who agreed to participate completed the test and produced readable ECGs (100% study completion rate). ECG tracings of 4 of the 50 patients who completed the study showed AF (8% AF yield), and none had been previously diagnosed with AF. When asked about continuous access to Internet and personal mobile devices, almost all of the health care providers surveyed answered affirmatively. Using mobile ECG technology in screening for AF in low-resource settings is feasible, and can detect a significant proportion of AF cases that will otherwise go undiagnosed. Further study is needed to examine the cost-effectiveness of this approach for detection of AF and its effect on reducing the risk of stroke in developing countries. Copyright © 2016 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

  18. Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

    Science.gov (United States)

    Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

    2013-01-01

    There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

  19. Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

    Science.gov (United States)

    Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

    2012-06-01

    The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

  20. Object-Oriented Analysis of Satellite Images Using Artificial Neural Networks for Post-Earthquake Buildings Change Detection

    Science.gov (United States)

    Khodaverdi zahraee, N.; Rastiveis, H.

    2017-09-01

    Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

  1. On the robustness of EC-PC spike detection method for online neural recording.

    Science.gov (United States)

    Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

    2014-09-30

    Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

    Directory of Open Access Journals (Sweden)

    Claire E. Bulgin

    2018-04-01

    Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

  3. Combining satellite-based fire observations and ground-based lightning detections to identify lightning fires across the conterminous USA

    Science.gov (United States)

    Bar-Massada, A.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

    2012-01-01

    Lightning fires are a common natural disturbance in North America, and account for the largest proportion of the area burned by wildfires each year. Yet, the spatiotemporal patterns of lightning fires in the conterminous US are not well understood due to limitations of existing fire databases. Our goal here was to develop and test an algorithm that combined MODIS fire detections with lightning detections from the National Lightning Detection Network to identify lightning fires across the conterminous US from 2000 to 2008. The algorithm searches for spatiotemporal conjunctions of MODIS fire clusters and NLDN detected lightning strikes, given a spatiotemporal lag between lightning strike and fire ignition. The algorithm revealed distinctive spatial patterns of lightning fires in the conterminous US While a sensitivity analysis revealed that the algorithm is highly sensitive to the two thresholds that are used to determine conjunction, the density of fires it detected was moderately correlated with ground based fire records. When only fires larger than 0.4 km2 were considered, correlations were higher and the root-mean-square error between datasets was less than five fires per 625 km2 for the entire study period. Our algorithm is thus suitable for detecting broad scale spatial patterns of lightning fire occurrence, and especially lightning fire hotspots, but has limited detection capability of smaller fires because these cannot be consistently detected by MODIS. These results may enhance our understanding of large scale patterns of lightning fire activity, and can be used to identify the broad scale factors controlling fire occurrence.

  4. Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

    Science.gov (United States)

    Tuyisenge, Viateur; Trebaul, Lena; Bhattacharjee, Manik; Chanteloup-Forêt, Blandine; Saubat-Guigui, Carole; Mîndruţă, Ioana; Rheims, Sylvain; Maillard, Louis; Kahane, Philippe; Taussig, Delphine; David, Olivier

    2018-03-01

    Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usually much lower than the number of good channels, we implemented an ensemble bagging classifier known to be optimal in terms of stability and predictive accuracy for datasets with imbalanced class distributions. This method was applied on stereo-electroencephalographic (SEEG) signals recording during low frequency stimulations performed in 206 patients from 5 clinical centers. We found that the classification accuracy was extremely good: It increased with the number of subjects used to train the classifier and reached a plateau at 99.77% for 110 subjects. The classification performance was thus not impacted by the multicentric nature of data. The proposed method to automatically detect bad channels demonstrated convincing results and can be envisaged to be used on larger datasets for automatic quality control of iEEG data. This is the first method proposed to classify bad channels in iEEG and should allow to improve the data selection when reviewing iEEG signals. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  5. Statistical methods for change-point detection in surface temperature records

    Science.gov (United States)

    Pintar, A. L.; Possolo, A.; Zhang, N. F.

    2013-09-01

    We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

  6. Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

    Science.gov (United States)

    Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

    2012-12-01

    Light absorbing particles such as carbonaceous aerosols generated from biomass burning activities and windblown dust particles can exert a net warming effect on climate; the strength of which depends on the absorption capacity of the particles and brightness of the underlying reflecting background. When advected over low-level bright clouds, these aerosols absorb the cloud reflected radiation from ultra-violet (UV) to shortwave-IR (SWIR) and makes cloud scene darker-a phenomenon commonly known as "cloud darkening". The apparent "darkening" effect can be seen by eyes in satellite images as well as quantitatively in the spectral reflectance measurements made by space borne sensors over regions where light absorbing carbonaceous and dust aerosols overlay low-level cloud decks. Theoretical radiative transfer simulations support the observational evidence, and further reveal that the strength of the cloud darkening and its spectral signature (or color ratio) between measurements at two wavelengths are a bi-function of aerosol and cloud optical thickness (AOT and COT); both are measures of the total amount of light extinction caused by aerosols and cloud, respectively. Here, we developed a retrieval technique, named as the "color ratio method" that uses the satellite measurements at two channels, one at shorter wavelength in the visible and one at longer wavelength in the shortwave-IR for the simultaneous retrieval of AOT and COT. The present technique requires assumptions on the aerosol single-scattering albedo and aerosol-cloud separation which are supplemented by the Aerosol Robotic Network (AERONET) and space borne CALIOP lidar measurements. The retrieval technique has been tested making use of the near-UV and visible reflectance observations made by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) for distinct above-cloud smoke and dust aerosol events observed seasonally over the southeast and tropical Atlantic Ocean

  7. Use of high-resolution satellite images for detection of geological structures related to Calerias geothermal field, Chile

    Science.gov (United States)

    Arellano-Baeza, A. A.; Urzua, L.

    2011-12-01

    Chile has enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique developed by authors. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

  8. Using satellite fire detection to calibrate components of the fire weather index system in Malaysia and Indonesia.

    Science.gov (United States)

    Dymond, Caren C; Field, Robert D; Roswintiarti, Orbita; Guswanto

    2005-04-01

    Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and

  9. Landuse change detection in a surface coal mine area using multi-temporal high resolution satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Demirel, N.; Duzgun, S.; Kemal Emil, M. [Middle East Technical Univ., Ankara (Turkey). Dept. of Mining Engineering

    2010-07-01

    Changes in the landcover and landuse of a mine area can be caused by surface mining activities, exploitation of ore and stripping and dumping overburden. In order to identify the long-term impacts of mining on the environment and land cover, these changes must be continuously monitored. A facility to regularly observe the progress of surface mining and reclamation is important for effective enforcement of mining and environmental regulations. Remote sensing provides a powerful tool to obtain rigorous data and reduce the need for time-consuming and expensive field measurements. The purpose of this study was to conduct post classification change detection for identifying, quantifying, and analyzing the spatial response of landscape due to surface lignite coal mining activities in Goynuk, Bolu, Turkey, from 2004 to 2008. The paper presented the research algorithm which involved acquiring multi temporal high resolution satellite data; preprocessing the data; performing image classification using maximum likelihood classification algorithm and performing accuracy assessment on the classification results; performing post classification change detection algorithm; and analyzing the results. Specifically, the paper discussed the study area, data and methodology, and image preprocessing using radiometric correction. Image classification and change detection were also discussed. It was concluded that the mine and dump area decreased by 192.5 ha from 2004 to 2008 and was caused by the diminishing reserves in the area and decline in the required production. 5 refs., 2 tabs., 4 figs.

  10. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Rodrigo Tavares; Martinelli Filho, Martino, E-mail: martino@cardiol.br; Peixoto, Giselle de Lima; Lima, José Jayme Galvão de; Siqueira, Sérgio Freitas de; Costa, Roberto; Gowdak, Luís Henrique Wolff [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Paula, Flávio Jota de [Unidade de Transplante Renal - Divisão de Urologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Kalil Filho, Roberto; Ramires, José Antônio Franchini [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil)

    2015-11-15

    The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

  11. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    Directory of Open Access Journals (Sweden)

    Rodrigo Tavares Silva

    2015-11-01

    Full Text Available AbstractBackground:The recording of arrhythmic events (AE in renal transplant candidates (RTCs undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used.Objective:We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR.Methods:A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE.Results:During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002, and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001 were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041.Conclusions:In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

  12. Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

    Science.gov (United States)

    Silva, Rodrigo Tavares; Martinelli Filho, Martino; Peixoto, Giselle de Lima; de Lima, José Jayme Galvão; de Siqueira, Sérgio Freitas; Costa, Roberto; Gowdak, Luís Henrique Wolff; de Paula, Flávio Jota; Kalil Filho, Roberto; Ramires, José Antônio Franchini

    2015-01-01

    Background The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. Objective We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). Methods A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. Results During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). Conclusions In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT. PMID:26351983

  13. The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite

    Directory of Open Access Journals (Sweden)

    M. Schröder

    2013-03-01

    Full Text Available The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF aims at the provision and sound validation of well documented Climate Data Records (CDRs in sustained and operational environments. In this study, a total column water vapour path (WVPA climatology from CM SAF is presented and inter-compared to water vapour data records from various data sources. Based on homogenised brightness temperatures from the Special Sensor Microwave Imager (SSM/I, a climatology of WVPA has been generated within the Hamburg Ocean–Atmosphere Fluxes and Parameters from Satellite (HOAPS framework. Within a research and operation transition activity the HOAPS data and operation capabilities have been successfully transferred to the CM SAF where the complete HOAPS data and processing schemes are hosted in an operational environment. An objective analysis for interpolation, namely kriging, has been applied to the swath-based WVPA retrievals from the HOAPS data set. The resulting climatology consists of daily and monthly mean fields of WVPA over the global ice-free ocean. The temporal coverage ranges from July 1987 to August 2006. After a comparison to the precursor product the CM SAF SSM/I-based climatology has been comprehensively compared to different types of meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA40, ERA INTERIM and operational analyses and from the Japan Meteorological Agency (JMA–JRA. This inter-comparison shows an overall good agreement between the climatology and the analyses, with daily absolute biases generally smaller than 2 kg m−2. The absolute value of the bias to JRA and ERA INTERIM is typically smaller than 0.5 kg m−2. For the period 1991–2006, the root mean square error (RMSE for both reanalyses is approximately 2 kg m−2. As SSM/I WVPA and radiances are assimilated into JMA and all ECMWF analyses and

  14. Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings.

    Science.gov (United States)

    Baldassano, Steven N; Brinkmann, Benjamin H; Ung, Hoameng; Blevins, Tyler; Conrad, Erin C; Leyde, Kent; Cook, Mark J; Khambhati, Ankit N; Wagenaar, Joost B; Worrell, Gregory A; Litt, Brian

    2017-06-01

    There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  15. Quest for automated land cover change detection using satellite time series data

    CSIR Research Space (South Africa)

    Salmon, BP

    2009-07-01

    Full Text Available and surface climate in the next fifty years,” Global Change Biology, vol. 8, no. 5, pp. 438–458, May 2002. [3] J. A. Foley et al., “Global consequences of land use,” Science, vol. 309, no. 5734, pp. 570–574, July 2005. [4] R. S. Lunetta et al., “Land... (class 1). These four subsets were used to produce a confusion matrix to test if the operational MLP can detect change reliably in an automated fashion on subsets 1 and 2, while not falsely detecting change for subsets 3 and 4. This particular splic...

  16. A statistical approach to bioclimatic trend detection in the airborne pollen records of Catalonia (NE Spain)

    Science.gov (United States)

    Fernández-Llamazares, Álvaro; Belmonte, Jordina; Delgado, Rosario; De Linares, Concepción

    2014-04-01

    Airborne pollen records are a suitable indicator for the study of climate change. The present work focuses on the role of annual pollen indices for the detection of bioclimatic trends through the analysis of the aerobiological spectra of 11 taxa of great biogeographical relevance in Catalonia over an 18-year period (1994-2011), by means of different parametric and non-parametric statistical methods. Among others, two non-parametric rank-based statistical tests were performed for detecting monotonic trends in time series data of the selected airborne pollen types and we have observed that they have similar power in detecting trends. Except for those cases in which the pollen data can be well-modeled by a normal distribution, it is better to apply non-parametric statistical methods to aerobiological studies. Our results provide a reliable representation of the pollen trends in the region and suggest that greater pollen quantities are being liberated to the atmosphere in the last years, specially by Mediterranean taxa such as Pinus, Total Quercus and Evergreen Quercus, although the trends may differ geographically. Longer aerobiological monitoring periods are required to corroborate these results and survey the increasing levels of certain pollen types that could exert an impact in terms of public health.

  17. Using limnological and optical knowledge to detect discharges from nuclear facilities - Potential application of satellite imagery for international safeguards

    International Nuclear Information System (INIS)

    Borstad, G.; Truong, Q.S. Bob; Keeffe, R.; Baines, P.; Staenz, K.; Neville, R.

    2001-01-01

    Previous work carried out under the Canadian Safeguards Support Program, has shown that thermal imagery from the American Landsat satellites could be used to detect the cooling water discharges, and could therefore be used to verify the operational status of nuclear facilities. In some images, thermal plumes could be easily detected in single band imagery with no mathematical manipulation and little image enhancement because there was a very strong thermal contrast between the effluent and the receiving water. However, for certain situations such as discharges into well mixed conditions (cold water and violent tides) the thermal plume may be more subtle. We show here that the visible bands of Landsat and IKONOS images often contain additional information, and that the thermal signature of a discharge from a nuclear facility is not the only signal available to describe its operation. This paper introduces some important hydrological phenomena that govern the biological and physical organization of water bodies, and discusses some basic concepts of marine and aquatic optics that are relevant to the safeguards problem. Using image analysis techniques that have been used widely in ocean optics work and in applications in the mapping and monitoring of water quality, we have re-analyzed data that were obtained under a joint project between various Canadian government departments. We present a preliminary examination of imagery from both satellite multispectral and aircraft hyperspectral sensors, and discuss methods to extract information that could be useful in the detection and verification of declared or undeclared nuclear activities. In one example of an IKONOS image of the Canadian Bruce Nuclear Generating Facility, simple enhancement techniques failed to find any plume other than a small jet visible in the surface wave field. With knowledge of limnology, oceanography and aquatic optics, we have been able to separate and remove the surface reflection, and detect a

  18. A novel Spatio-temporal change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2014-07-01

    Full Text Available The use of hyper-temporal MODIS time-series data for the detection of land cover change in South Africa has been an active research area the last few year. This paper expands on previous studies that show that this type of data can be effectively...

  19. Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

    Science.gov (United States)

    Daolan Zheng; Linda S. Heath; Mark J. Ducey

    2008-01-01

    We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

  20. Deforestation change detection in North Korea between 1999 and 2008 using multi temporal satellite image

    Science.gov (United States)

    KIM, K. M.

    2017-12-01

    After the mid-1990s, North Korea has gone through a hard time of shortage of food and fuel due to the large scale flood and landslide. This became a vicious circle, which has kept accelerating the deforestation in North Korea. This study aims to analyze the change of deforestation in North Korea using two different seasonal satellite images of Landsat 5-TM and SPOT-5 between 1999 and 2008. The Land cover was classified into 6 categories: forest, cropland, grassland, bare land, built area and water body. And the deforested and degraded forest area was extracted considering forest land boundary and classified into 3 categories: the cultivated, the unstocked forest land and the bare mountain. For the all classification process, unsupervised classification method was used since North Korea is inaccessible area. The results of the study showed that the stocked forest area has decreased 1,379,000 ha compared with those in 1999, whereas the deforested and degraded forest area has increased 1,207,000 ha in 2008. The increase of 880,000 ha in the unstocked forest land was the biggest expansion among 3 categories of the deforested and degraded forest area during 9 yrs. It is resulted from an increase of firewood usage, which is presumably owing to the severe shortage of fuel and food. I look forward for the outcome of this study to being used as baseline data for inter-Korean forest cooperation. Especially, it is expected to serve as important input data for the potential REDD project site selection with results of the 3rd forest monitoring(2018) of North Korea.

  1. Detecting Drought-Induced Tree Mortality in Sierra Nevada Forests with Time Series of Satellite Data

    Directory of Open Access Journals (Sweden)

    Sarah Byer

    2017-09-01

    Full Text Available A five-year drought in California led to a significant increase in tree mortality in the Sierra Nevada forests from 2012 to 2016. Landscape level monitoring of forest health and tree dieback is critical for vegetation and disaster management strategies. We examined the capability of multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS in detecting and explaining the impacts of the recent severe drought in Sierra Nevada forests. Remote sensing metrics were developed to represent baseline forest health conditions and drought stress using time series of MODIS vegetation indices (VIs and a water index. We used Random Forest algorithms, trained with forest aerial detection surveys data, to detect tree mortality based on the remote sensing metrics and topographical variables. Map estimates of tree mortality demonstrated that our two-stage Random Forest models were capable of detecting the spatial patterns and severity of tree mortality, with an overall producer’s accuracy of 96.3% for the classification Random Forest (CRF and a RMSE of 7.19 dead trees per acre for the regression Random Forest (RRF. The overall omission errors of the CRF ranged from 19% for the severe mortality class to 27% for the low mortality class. Interpretations of the models revealed that forests with higher productivity preceding the onset of drought were more vulnerable to drought stress and, consequently, more likely to experience tree mortality. This method highlights the importance of incorporating baseline forest health data and measurements of drought stress in understanding forest response to severe drought.

  2. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Science.gov (United States)

    Marghany, Maged

    2016-10-01

    In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  3. Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

    Science.gov (United States)

    Moore, Timothy; Dowell, Mark; Franz, Bryan A.

    2012-01-01

    A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

  4. Detection of Traveling Ionospheric Disturbances (TIDs) from various man-made sources using Global Navigation Satellite System (GNSS)

    Science.gov (United States)

    Helmboldt, J.; Park, J.; von Frese, R. R. B.; Grejner-Brzezinska, D. A.

    2016-12-01

    Traveling ionospheric disturbance (TID) is generated by various sources and detectable by observing the spatial and temporal change of electron contents in the ionosphere. This study focused on detecting and analyzing TIDs generated by acoustic-gravity waves from man-made events including underground nuclear explosions (UNEs), mine collapses, mine blasts, and large chemical explosions (LCEs) using Global Navigation Satellite System (GNSS). In this study we selected different types of events for case study which covers two US and three North Korean UNEs, two large US mine collapses, three large US mine blasts, and a LCE in northern China and a second LCE at the Nevada Test Site. In most cases, we successfully detected the TIDs as array signatures from the multiple nearby GNSS stations. The array-based TID signatures from these studies were found to yield event-appropriate TID propagation speeds ranging from about a few hundred m/s to roughly a km/s. In addition, the event TID waveforms, and propagation angles and directions were established. The TID waveforms and the maximum angle between each event and the IPP of its TID with the longest travel distance from the source may help differentiate UNEs and LCEs, but the uneven distributions of the observing GNSS stations complicates these results. Thus, further analysis is required of the utility of the apertures of event signatures in the ionosphere for discriminating these events. In general, the results of this study show the potential utility of GNSS observations for detecting and mapping the ionospheric signatures of large-energy anthropological explosions and subsurface collapses.

  5. NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat-B1) Infrared Channel Brightness Temperature, Version 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and...

  6. Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

    Science.gov (United States)

    Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

    2015-04-01

    Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

  7. Ventricular Tachycardia Detected by Implantable Loop Recorder in a Child with Recurrent Syncope

    Directory of Open Access Journals (Sweden)

    İsa Özyılmaz

    2014-06-01

    Full Text Available In this article, we present a 10-year-old boy who was admitted to the hospital with recurrent syncope. There was no remarkable finding in patient’s physical examination, family history, and the diagnostic 12-lead electrocardiogram (ECG, chest x-ray, ECG Holter monitoring, event recording, echocardiography, coronary computed tomography (CT angiography, Ajmaline test for the diagnosis of Brugada syndrome, brain magnetic resonance imaging, and sleep/wake electroencephalogram. We started beta-blocker therapy because the patient had exercise-induced syncope. An Implantable loop recorder (ILR was inserted to the patient. Three years later, polymorphic ventricular tachycardia called torsades de pointes was detected by the ILR during syncope occurred with exercise. The patient had been taking high-dose betablocker treatment, an implantable cardioverter defibrillator was implanted into the patient. ILR can play an important role in the diagnosis of life-threatening arrhythmia in children with unexplained syncope. (The Me­di­cal Bul­le­tin of Ha­se­ki 2014; 52: 123-5

  8. Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

    Science.gov (United States)

    Hester, David Barry

    The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

  9. The effects of clouds on the detection of light signals from near-ground nuclear bursts at satellite

    International Nuclear Information System (INIS)

    Zhang Zhongshan; Zhang Enshan; Zhao Wenli; Gao Chunxia

    2002-01-01

    The effects of clouds on the detection of light signals from near-ground nuclear bursts are analysed quantitatively. The results indicate: the degree of the effect increasing with the growth of clouds optical thickness and satellite look angle; clouds lead really harmful effect in detectable signal intensity and precision of optical location, but degree of the effect is not great too. The enhancement of the photon optical paths by multiple scattering within the cloud will cause both a delay and a time-broadening of an impulsive light signal, and get 'lower and fat'; upward optical transmission of light through clouds is essentially the same as if there were no cloud present at all, when a point source is above the geometrical mid-plane of the cloud. And if the point source is below the mid-plane, then upward optical transmission of light through clods will be related closely to the distance of the source below the mid-plane. Given also some charts which evaluate conveniently degree of the effect due to clouds for the purpose of reference and use of a person of the same trade or occupation are given also

  10. Self-Assembled Core-Satellite Gold Nanoparticle Networks for Ultrasensitive Detection of Chiral Molecules by Recognition Tunneling Current.

    Science.gov (United States)

    Zhang, Yuanchao; Liu, Jingquan; Li, Da; Dai, Xing; Yan, Fuhua; Conlan, Xavier A; Zhou, Ruhong; Barrow, Colin J; He, Jin; Wang, Xin; Yang, Wenrong

    2016-05-24

    Chirality sensing is a very challenging task. Here, we report a method for ultrasensitive detection of chiral molecule l/d-carnitine based on changes in the recognition tunneling current across self-assembled core-satellite gold nanoparticle (GNP) networks. The recognition tunneling technique has been demonstrated to work at the single molecule level where the binding between the reader molecules and the analytes in a nanojunction. This process was observed to generate a unique and sensitive change in tunneling current, which can be used to identify the analytes of interest. The molecular recognition mechanism between amino acid l-cysteine and l/d-carnitine has been studied with the aid of SERS. The different binding strength between homo- or heterochiral pairs can be effectively probed by the copper ion replacement fracture. The device resistance was measured before and after the sequential exposures to l/d-carnitine and copper ions. The normalized resistance change was found to be extremely sensitive to the chirality of carnitine molecule. The results suggested that a GNP networks device optimized for recognition tunneling was successfully built and that such a device can be used for ultrasensitive detection of chiral molecules.

  11. An improved automated procedure for informal and temporary dwellings detection and enumeration, using mathematical morphology operators on VHR satellite data

    Science.gov (United States)

    Jenerowicz, Małgorzata; Kemper, Thomas

    2016-10-01

    Every year thousands of people are displaced by conflicts or natural disasters and often gather in large camps. Knowing how many people have been gathered is crucial for an efficient relief operation. However, it is often difficult to collect exact information on the total number of the population. This paper presents the improved morphological methodology for the estimation of dwellings structures located in several Internally Displaced Persons (IDPs) Camps, based on Very High Resolution (VHR) multispectral satellite imagery with pixel sizes of 1 meter or less including GeoEye-1, WorldView-2, QuickBird-2, Ikonos-2, Pléiades-A and Pléiades-B. The main topic of this paper is the approach enhancement with selection of feature extraction algorithm, the improvement and automation of pre-processing and results verification. For the informal and temporary dwellings extraction purpose the high quality of data has to be ensured. The pre-processing has been extended by including the input data hierarchy level assignment and data fusion method selection and evaluation. The feature extraction algorithm follows the procedure presented in Jenerowicz, M., Kemper, T., 2011. Optical data are analysed in a cyclic approach comprising image segmentation, geometrical, textural and spectral class modeling aiming at camp area identification. The successive steps of morphological processing have been combined in a one stand-alone application for automatic dwellings detection and enumeration. Actively implemented, these approaches can provide a reliable and consistent results, independent of the imaging satellite type and different study sites location, providing decision support in emergency response for the humanitarian community like United Nations, European Union and Non-Governmental relief organizations.

  12. Distress detection, location, and communications using advanced space technology. [satellite-borne synthetic aperture radar

    Science.gov (United States)

    Sivertson, W. E., Jr.

    1977-01-01

    This paper briefly introduces a concept for low-cost, global, day-night, all-weather disaster warning and assistance. Evolving, advanced space technology with passive radio frequency reflectors in conjunction with an imaging synthetic aperture radar is employed to detect, identify, locate, and provide passive communication with earth users in distress. This concept evolved from a broad NASA research on new global search and rescue techniques. Appropriate airborne radar test results from this research are reviewed and related to potential disaster applications. The analysis indicates the approach has promise for disaster communications relative to floods, droughts, earthquakes, volcanic eruptions, and severe storms.

  13. Detection of Interictal Epileptiform Discharges Using Signal Envelope Distribution Modelling: Application to Epileptic and Non-Epileptic Intracranial Recordings

    Czech Academy of Sciences Publication Activity Database

    Janča, R.; Ježdík, P.; Čmejla, R.; Tomášek, M.; Worrell, G. A.; Stead, M.; Wagenaar, J.; Jefferys, J. G. R.; Kršek, P.; Komárek, V.; Jiruška, Přemysl; Marusič, P.

    2015-01-01

    Roč. 28, č. 1 (2015), s. 172-183 ISSN 0896-0267 Grant - others:GA Mzd(CZ) NT11460 Institutional support: RVO:67985823 Keywords : spike detection * interictal epileptiform discharges * intracranial recording * automatic detection * Hilbert transform * principal component analysis Subject RIV: FH - Neurology Impact factor: 3.727, year: 2015

  14. Optomagnetic Detection of MicroRNA Based on Duplex-Specific Nuclease-Assisted Target Recycling and Multilayer Core-Satellite Magnetic Superstructures

    DEFF Research Database (Denmark)

    Tian, Bo; Ma, Jing; Qiu, Zhen

    2017-01-01

    -efficiency, and potential for bioresponsive multiplexing. Herein, we demonstrate a sensitive and rapid miRNA detection method based on optomagnetic read-out, duplex-specific nuclease (DSN)-assisted target recycling, and the use of multilayer core-satellite magnetic superstructures. Triggered by the presence of target mi...

  15. Detection and Monitoring of Surface Motions in Active Open Pit Iron Mine in the Amazon Region, Using Persistent Scatterer Interferometry with TerraSAR-X Satellite Data

    Directory of Open Access Journals (Sweden)

    Marcos E. Hartwig

    2013-09-01

    Full Text Available Persistent Scatterer interferometry (PSI represents a powerful tool for the detection and monitoring of tiny surface deformations in vast areas, allowing a better understanding of its triggering mechanisms, planning of mitigation measures, as well as to find better solutions for social and environmental issues. However, there is no record hitherto of its use in active open pit mine in tropical rainforest environment. In this paper we evaluate the use of the PSI technique for the detection and monitoring of mine slope deformations in the N4W iron mine and its surroundings, Pará State, Northern Brazil. The PSI processing was performed with 18 ascending SAR scenes of the TerraSAR-X satellite acquired in the dry season of 2012. The results showed a significant number of widely distributed persistent scatterers. It was observed that most of the study area was stable during the time span. Nevertheless, high deformation rates (312 mm/year were mapped over the mine waste piles, but do not offer any hazard, since they are expected displacements of meters in magnitude for these manmade land structures. Additionally, it was mapped tiny deformation rates in both the east and west flanks of pits 1 and 2. The main underlying reasons can be assigned to the accommodation phenomena of very poor rock masses, to the local geometric variations of the slope cuts, to the geological contact between ironstones and the country rocks, to the exploitation activities, as well as to the major geological structures. This study showed the applicability of the PSI technique using TerraSAR-X scenes in active open pit mines in tropical moist environment. However, the PSI technique is not capable in providing real-time warnings, and faces limitations due to SAR viewing geometry. In this sense, we strongly recommend the use of radar scenes acquired in both ascending and descending orbits, which would also provide a more complete understanding of the deformation patterns.

  16. Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

    Science.gov (United States)

    Suepa, Tanita

    The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability

  17. Gait phase detection from sciatic nerve recordings in functional electrical stimulation systems for foot drop correction

    International Nuclear Information System (INIS)

    Chu, Jun-Uk; Song, Kang-Il; Han, Sungmin; Suh, Jun-Kyo Francis; Choi, Kuiwon; Youn, Inchan; Lee, Soo Hyun; Kang, Ji Yoon; Hwang, Dosik

    2013-01-01

    Cutaneous afferent activities recorded by a nerve cuff electrode have been used to detect the stance phase in a functional electrical stimulation system for foot drop correction. However, the implantation procedure was difficult, as the cuff electrode had to be located on the distal branches of a multi-fascicular nerve to exclude muscle afferent and efferent activities. This paper proposes a new gait phase detection scheme that can be applied to a proximal nerve root that includes cutaneous afferent fibers as well as muscle afferent and efferent fibers. To test the feasibility of this scheme, electroneurogram (ENG) signals were measured from the rat sciatic nerve during treadmill walking at several speeds, and the signal properties of the sciatic nerve were analyzed for a comparison with kinematic data from the ankle joint. On the basis of these experiments, a wavelet packet transform was tested to define a feature vector from the sciatic ENG signals according to the gait phases. We also propose a Gaussian mixture model (GMM) classifier and investigate whether it could be used successfully to discriminate feature vectors into the stance and swing phases. In spite of no significant differences in the rectified bin-integrated values between the stance and swing phases, the sciatic ENG signals could be reliably classified using the proposed wavelet packet transform and GMM classification methods. (paper)

  18. Recent changes in phenology over the northern high latitudes detected from multi-satellite data

    International Nuclear Information System (INIS)

    Zeng Heqing; Jia Gensuo; Epstein, Howard

    2011-01-01

    Phenology of vegetation is a sensitive and valuable indicator of the dynamic responses of terrestrial ecosystems to climate change. Therefore, to better understand and predict ecosystems dynamics, it is important to reduce uncertainties in detecting phenological changes. Here, changes in phenology over the past several decades across the northern high-latitude region (≥60°N) were examined by calibrating and analyzing time series of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR). Over the past decade (2000–10), an expanded length of the growing season (LOS) was detected by MODIS, largely due to an earlier start of the growing season (SOS) by 4.7 days per decade and a delayed end of the growing season (EOS) by 1.6 days per decade over the northern high latitudes. There were significant differences between North America and Eurasia in phenology from 2000 to 2010 based on MODIS data (SOS: df = 21, F = 49.02, p < 0.0001; EOS: df = 21, F = 49.25, p < 0.0001; LOS: df = 21, F = 79.40, p < 0.0001). In northern America, SOS advanced by 11.5 days per decade, and EOS was delayed by 2.2 days per decade. In Eurasia, SOS advanced by 2.7 days per decade, and EOS was delayed by 3.5 days per decade. SOS has likely advanced due to the warming Arctic during April and May. Our results suggest that in recent decades the longer vegetation growing seasons can be attributed to more advanced SOS rather than delayed EOS. AVHRR detected longer LOS over the past three decades, largely related to delayed EOS rather than advanced SOS. These two datasets are significantly different in key phenological parameters (SOS: df = 17, F = 14.63, p = 0.0015; EOS: df = 17, F = 38.69, p < 0.0001; LOS: df = 17, F = 16.47, p = 0.0009) from 2000 to 2008 over the northern high latitudes. Thus, further inter-calibration between the sensors is needed to resolve the inconsistency and to better understand long-term trends of vegetation growth

  19. Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher

    2013-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

  20. SEDHI: a new generation of detection electronics for earth observation satellites

    Science.gov (United States)

    Dantes, Didier; Neveu, Claude; Biffi, Jean-Marc; Devilliers, Christophe; Andre, Serge

    2017-11-01

    Future earth observation optical systems will be more and more demanding in terms of ground sampling distance, swath width, number of spectral bands, duty cycle. Existing architectures of focal planes and video processing electronics are hardly compatible with these new requirements: electronic functions are split in several units, and video processing is limited to frequencies around 5 MHz in order to fulfil the radiometric requirements expected for high performance image quality systems. This frequency limitation induces a high number of video chains operated in parallel to process the huge amount of pixels at focal plane output, and leads to unacceptable mass and power consumption budgets. Furthermore, splitting the detection electronics functions into several units (at least one for the focal plane and proximity electronics, and one for the video processing functions) does not optimise the production costs : specific development efforts must be performed on critical analogue electronics at each equipment level and operations of assembly, integration and tests are duplicated at equipment and subsystem levels. Alcatel Space Industries has proposed to CNES a new concept of highly integrated detection electronics (SEDHI), and is developing for CNES a breadboard which will allow to confirm its potentialities. This paper presents the trade-off study which have been performed before selection of this new concept and summarises the main advantages and drawbacks of each possible architecture. The electrical, mechanical and thermal aspects of the SEDHI concept are described, including the basic technologies : ASIC for phase shift of detector clocks, ASIC for video processing, hybrids, microchip module... The adaptability to a large amount of missions and optical instruments is also discussed.

  1. Detection of soil erosion with Thematic Mapper (TM) satellite data within Pinyon-Juniper woodlands

    Science.gov (United States)

    Price, Kevin Paul

    1987-01-01

    Pinyon-Juniper woodlands dominate approximately 24.3 million hectares (60 million acres) in the western United States. The overall objective was to test the sensitivity of the LANDSAT Thematic Mapper (TM) spectral data for detecting varying degrees of soil erosion within the Pinyon-Juniper woodlands. A second objective was to assess the potential of the spectral data for assigning the Universal Soil Loss Equation (USLE) crop management (C) factor values to varying cover types within the woodland. Thematic Mapper digital data for June 2, 1984 on channels 2, 3, 4, and 5 were used. Digital data analysis was performed using the ELAS software package. Best results were achieved using CLUS, an unsupervised clustering algorithm. Fifteen of the 40 Pinyon-Juniper signatures were identified as being relatively pure Pinyon-Juniper woodland. Final analysis resulted in the grouping of the 15 signatures into three major groups. Ten study sites were selected from each of the three groups and located on the ground. At each site the following field measurements were taken: percent tree canopy and percent understory cover, soil texture, total soil loss, and soil erosion rate estimates. A technique for measuring soil erosion within Pinyon-Juniper woodlands was developed. A theoretical model of site degradation after Pinyon-Juniper invasion is presented.

  2. Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2014-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in forest vegetation cover for areas burned by wildfires in the Sierra Nevada Mountains of California between the periods of 1975- 79 and 1995-1999. Results for areas burned by wildfire between 1995 and 1999 confirmed the importance of regrowing forest vegetation over 17% of the combined burned areas. A notable fraction (12%) of the entire 5-km (unburned) buffer area outside the 1995-199 fires perimeters showed decline in forest cover, and not nearly as many regrowing forest areas, covering only 3% of all the 1995-1999 buffer areas combined. Areas burned by wildfire between 1975 and 1979 confirmed the importance of disturbed (or declining evergreen) vegetation covering 13% of the combined 1975- 1979 burned areas. Based on comparison of these results to ground-based survey data, the LEDAPS methodology should be capable of fulfilling much of the need for consistent, low-cost monitoring of changes due to climate and biological factors in western forest regrowth following stand-replacing disturbances.

  3. Synergistic Use of Thermal Infrared Field and Satellite Data: Eruption Detection, Monitoring and Science

    Science.gov (United States)

    Ramsey, Michael

    2015-04-01

    The ASTER-based observational success of active volcanic processes early in the Terra mission later gave rise to a funded NASA program designed to both increase the number of ASTER scenes following an eruption and perform the ground-based science needed to validate that data. The urgent request protocol (URP) system for ASTER grew out of this initial study and has now operated in conjunction with and the support of the Alaska Volcano Observatory, the University of Alaska Fairbanks, the University of Hawaii, the USGS Land Processes DAAC, and the ASTER science team. The University of Pittsburgh oversees this rapid response/sensor-web system, which until 2011 had focused solely on the active volcanoes in the North Pacific region. Since that time, it has been expanded to operate globally with AVHRR and MODIS and now ASTER visible and thermal infrared (TIR) data are being acquired at numerous active volcanoes around the world. This program relies on the increased temporal resolution of AVHRR/MODIS midwave infrared data to trigger the next available ASTER observation, which results in ASTER data as frequently as every 2-5 days. For many new targets such as Mt. Etna, the URP has increased the observational frequency by as much 50%. Examples of these datasets will be presented, which have been used for operational response to new eruptions as well as longer-term scientific studies. These studies include emplacement of new lava flows, detection of endogenous dome growth, and interpretation of hazardous dome collapse events. As a means to validate the ASTER TIR data and capture higher-resolution images, a new ground-based sensor has recently been developed that consists of standard FLIR camera modified with wavelength filters similar to the ASTER bands. Data from this instrument have been acquired of the lava lake at Kilauea and reveal differences in emissivity between molten and cooled surfaces confirming prior laboratory results and providing important constraints on lava

  4. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    Directory of Open Access Journals (Sweden)

    Chandi Witharana

    2016-04-01

    Full Text Available The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR satellite imagery and closely examined the transferability of knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.

  5. Threshold-based system for noise detection in multilead ECG recordings

    International Nuclear Information System (INIS)

    Jekova, Irena; Krasteva, Vessela; Christov, Ivaylo; Abächerli, Roger

    2012-01-01

    This paper presents a system for detection of the most common noise types seen on the electrocardiogram (ECG) in order to evaluate whether an episode from 12-lead ECG is reliable for diagnosis. It implements criteria for estimation of the noise corruption level in specific frequency bands, aiming to identify the main sources of ECG quality disruption, such as missing signal or limited dynamics of the QRS components above 4 Hz; presence of high amplitude and steep artifacts seen above 1 Hz; baseline drift estimated at frequencies below 1 Hz; power–line interference in a band ±2 Hz around its central frequency; high-frequency and electromyographic noises above 20 Hz. All noise tests are designed to process the ECG series in the time domain, including 13 adjustable thresholds for amplitude and slope criteria which are evaluated in adjustable time intervals, as well as number of leads. The system allows flexible extension toward application-specific requirements for the noise levels in acceptable quality ECGs. Training of different thresholds’ settings to determine different positive noise detection rates is performed with the annotated set of 1000 ECGs from the PhysioNet database created for the Computing in Cardiology Challenge 2011. Two implementations are highlighted on the receiver operating characteristic (area 0.968) to fit to different applications. The implementation with high sensitivity (Se = 98.7%, Sp = 80.9%) appears as a reliable alarm when there are any incidental problems with the ECG acquisition, while the implementation with high specificity (Sp = 97.8%, Se = 81.8%) is less susceptible to transient problems but rather validates noisy ECGs with acceptable quality during a small portion of the recording. (paper)

  6. Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series

    International Nuclear Information System (INIS)

    Zeng, Heqing; Jia, Gensuo; Forbes, Bruce C

    2013-01-01

    There is an urgent need to reduce the uncertainties in remotely sensed detection of phenological shifts of high latitude ecosystems in response to climate changes in past decades. In this study, vegetation phenology in western Arctic Russia (the Yamal Peninsula) was investigated by analyzing and comparing Normalized Difference Vegetation Index (NDVI) time series derived from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and SPOT-Vegetation (VGT) during the decade 2000–2010. The spatial patterns of key phenological parameters were highly heterogeneous along the latitudinal gradients based on multi-satellite data. There was earlier SOS (start of the growing season), later EOS (end of the growing season), longer LOS (length of the growing season), and greater MaxNDVI from north to south in the region. The results based on MODIS and VGT data showed similar trends in phenological changes from 2000 to 2010, while quite a different trend was found based on AVHRR data from 2000 to 2008. A significantly delayed EOS (p < 0.01), thus increasing the LOS, was found from AVHRR data, while no similar trends were detected from MODIS and VGT data. There were no obvious shifts in MaxNDVI during the last decade. MODIS and VGT data were considered to be preferred data for monitoring vegetation phenology in northern high latitudes. Temperature is still a key factor controlling spatial phenological gradients and variability, while anthropogenic factors (reindeer husbandry and resource exploitation) might explain the delayed SOS in southern Yamal. Continuous environmental damage could trigger a positive feedback to the delayed SOS. (letter)

  7. Stormwater Runoff Plumes in Southern California Detected with Satellite SAR and MODIS Imagery - Areas of Increased Contamination Risk

    Science.gov (United States)

    Trinh, R. C.; Holt, B.; Gierach, M.

    2016-12-01

    Coastal pollution poses both a major health and environmental hazard, not only for beachgoers and coastal communities, but for marine organisms as well. Stormwater runoff is the largest source of pollution in the coastal waters of the Southern California Bight (SCB). The SCB is the final destination of four major urban watersheds and associated rivers, Ballona Creek, the Los Angeles River, the San Gabriel River, and the Santa Ana River, which act as channels for runoff and pollution during and after episodic rainstorms. Previous studies of SCB water quality have made use of both fine resolution Synthetic Aperture Radar (SAR) imagery and wide-swath medium resolution optical "ocean color" imagery from SeaWiFS and MODIS. In this study, we expand on previous SAR efforts, compiling a more extensive collection of multi-sensor SAR data, spanning from 1992 to 2014, analyzing the surface slick component of stormwater plumes. We demonstrate the use of SAR data in early detection of coastal stormwater plumes, relating plume extent to cumulative river discharge, and shoreline fecal bacteria loads. Intensity maps of the primary extent and direction of plumes were created, identifying coastal areas that may be subject to the greatest risk of environmental contamination. Additionally, we illustrate the differences in the detection of SAR surface plumes with the sediment-related discharge plumes derived from MODIS ocean color imagery. Finally, we provide a concept for satellite monitoring of stormwater plumes, combining both optical and radar sensors, to be used to guide the collection of in situ water quality data and enhance the assessment of related beach closures.

  8. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  9. Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland

    Science.gov (United States)

    Jan U.H. Eitel; Lee A. Vierling; Marcy E. Litvak; Dan S. Long; Urs Schulthess; Alan A. Ager; Dan J. Krofcheck; Leo Stoscheck

    2011-01-01

    Multiple plant stresses can affect the health, esthetic condition, and timber harvest value of conifer forests. To monitor spatial and temporal dynamic forest stress conditions, timely, accurate, and cost-effective information is needed that could be provided by remote sensing. Recently, satellite imagery has become available via the RapidEye satellite constellation to...

  10. Detection of extremely high bit density signals with a narrow track width GMR head in double layered perpendicular recording media

    International Nuclear Information System (INIS)

    Kiya, T.; Honda, N.; Ariake, J.; Ouchi, K.; Iwasaki, S.

    2001-01-01

    Recording resolution, medium noise and thermal stability have been investigated for double layered perpendicular magnetic recording media. The recording performance was improved by introducing a stacked intermediate layer between a soft magnetic backlayer and a storage layer due to increased crystal orientation with a small magnetic domain size and suppressed initial growing layer of the storage layer. The reproduced output at an extremely high linear density of 950 kFRPI was detected by using a contact-type CF-SPT head for write and a GMR head with a narrow read track width of 0.4 μm

  11. Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

    Directory of Open Access Journals (Sweden)

    Cheng Liu

    2011-07-01

    Full Text Available Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction,have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR and near infrared (NIR channels of satellite sensors have been employed for detecting live fuel moisture content (FMC, and the Normalized Difference Water Index (NDWI was used for evaluating the forest vegetation condition and its moisture status.

  12. Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

    Science.gov (United States)

    Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

    2011-08-01

    Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

  13. Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

    Science.gov (United States)

    Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

    2011-01-01

    Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

  14. Acoustic occurrence detection of a newly recorded Indo-Pacific humpback dolphin population in waters southwest of Hainan Island, China.

    Science.gov (United States)

    Dong, Lijun; Liu, Mingming; Dong, Jianchen; Li, Songhai

    2017-11-01

    In 2014, Indo-Pacific humpback dolphins were recorded for the first time in waters southwest of Hainan Island, China. In this paper, the temporal occurrence of Indo-Pacific humpback dolphins in this region was detected by stationary passive acoustic monitoring. During the 130-day observation period (from January to July 2016), 1969 click trains produced by Indo-Pacific humpback dolphins were identified, and 262 ten-minute recording bins contained echolocation click trains of dolphins, of which 70.9% were at night and 29.1% were during the day. A diurnal rhythm with a nighttime peak in acoustic detections was found. Passive acoustic detections indicated that the Indo-Pacific humpback dolphins frequently occurred in this area and were detected mainly at night. This information may be relevant to conservation efforts for these dolphins in the near future.

  15. Using Satellite Data to Monitor the Impacts of CyanoHAB Events on Drinking Water: A Texas Case Study

    Science.gov (United States)

    Overview of CYAN and it's mission to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying algal blooms and related water quality using satellite data records.

  16. A Demonstration of an Improved Filtering Technique for Analyzing Climate Records via Comparisons of Satellite MSU/AMSU Instrument Temperature Products from Three Research Groups

    Science.gov (United States)

    Swanson, R. E.

    2017-12-01

    Climate data records typically exhibit considerable variation over short time scales both from natural variability and from instrumentation issues. The use of linear least squares regression can provide overall trend information from noisy data, however assessing intermediate time periods can also provide useful information unavailable from basic trend calculations. Extracting the short term information in these data for assessing changes to climate or for comparison of data series from different sources requires the application of filters to separate short period variations from longer period trends. A common method used to smooth data is the moving average, which is a simple digital filter that can distort the resulting series due to the aliasing of the sampling period into the output series. We utilized Hamming filters to compare MSU/AMSU satellite time series developed by three research groups (UAH, RSS and NOAA STAR), the results published in January 2017 [http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-16-0121.1]. Since the last release date (July 2016) for the data analyzed in that paper, some of these groups have updated their analytical procedures and additional months of data are available to extend the series. An updated analysis of these data using the latest data releases available from each group is to be presented. Improved graphics will be employed to provide a clearer visualization of the differences between each group's results. As in the previous paper, the greatest difference between the UAH TMT series and those from the RSS and NOAA data appears during the early period of data from the MSU instruments before about 2003, as shown in the attached figure, and preliminary results indicate this pattern continues. Also to be presented are other findings regarding seasonal changes which were not included in the previous study.

  17. A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

    Science.gov (United States)

    Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

    2018-06-01

    Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

  18. Development of an algorithm for heartbeats detection and classification in Holter records based on temporal and morphological features

    International Nuclear Information System (INIS)

    García, A; Romano, H; Laciar, E; Correa, R

    2011-01-01

    In this work a detection and classification algorithm for heartbeats analysis in Holter records was developed. First, a QRS complexes detector was implemented and their temporal and morphological characteristics were extracted. A vector was built with these features; this vector is the input of the classification module, based on discriminant analysis. The beats were classified in three groups: Premature Ventricular Contraction beat (PVC), Atrial Premature Contraction beat (APC) and Normal Beat (NB). These beat categories represent the most important groups of commercial Holter systems. The developed algorithms were evaluated in 76 ECG records of two validated open-access databases 'arrhythmias MIT BIH database' and M IT BIH supraventricular arrhythmias database . A total of 166343 beats were detected and analyzed, where the QRS detection algorithm provides a sensitivity of 99.69 % and a positive predictive value of 99.84 %. The classification stage gives sensitivities of 97.17% for NB, 97.67% for PCV and 92.78% for APC.

  19. Preliminary study on peroxidase isoenzyme detection and RAPD molecular verification for sweet pepper 87-2 carried by a recoverable satellite

    International Nuclear Information System (INIS)

    Liu Min; Li Jinguo; Wang Yalin; Zhang Zan; Xue Huai; Zhang Chunhua; Li Sherong

    1999-01-01

    The detection technology of peroxidase isoenzyme pattern and RAPD (Randomly Amplified Polymorphic DNA) analysis were used to space-flown sweet pepper variety of 87-2 carried by a recoverable satellite, and its correspondent ground control Longjiao-2. Determination of peroxidase isoenzyme revealed that the physiological activities of space-flown sweet pepper were significantly higher than those of its ground control. To detect the polymorphism of gene sequence and the difference in molecular level. 42 primers were used, among them, 38 primers amplified polymorphic products, and the amplified products from 5 primers of sweet pepper 87-2 differed from those of ground control

  20. Detecting the changes in rural communities in Taiwan by applying multiphase segmentation on FORMOSA-2 satellite imagery

    Science.gov (United States)

    Huang, Yishuo

    2015-09-01

    regions containing roads, buildings, and other manmade construction works and the class with high values of NDVI indicates that those regions contain vegetation in good health. In order to verify the processed results, the regional boundaries were extracted and laid down on the given images to check whether the extracted boundaries were laid down on buildings, roads, or other artificial constructions. In addition to the proposed approach, another approach called statistical region merging was employed by grouping sets of pixels with homogeneous properties such that those sets are iteratively grown by combining smaller regions or pixels. In doing so, the segmented NDVI map can be generated. By comparing the areas of the merged classes in different years, the changes occurring in the rural communities of Taiwan can be detected. The satellite imagery of FORMOSA-2 with 2-m ground resolution is employed to evaluate the performance of the proposed approach. The satellite imagery of two rural communities (Jhumen and Taomi communities) is chosen to evaluate environmental changes between 2005 and 2010. The change maps of 2005-2010 show that a high density of green on a patch of land is increased by 19.62 ha in Jhumen community and conversely a similar patch of land is significantly decreased by 236.59 ha in Taomi community. Furthermore, the change maps created by another image segmentation method called statistical region merging generate similar processed results to multiphase segmentation.

  1. A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

    Science.gov (United States)

    Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

    2018-01-01

    The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

  2. Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

    Science.gov (United States)

    Ledezma, Carlos A.; Perpiñan, Gilberto; Severeyn, Erika; Altuve, Miguel

    2015-12-01

    Heart diseases are the main cause of death worldwide. The first step in the diagnose of these diseases is the analysis of the electrocardiographic (ECG) signal. In turn, the ECG analysis begins with the detection of the QRS complex, which is the one with the most energy in the cardiac cycle. Numerous methods have been proposed in the bibliography for QRS complex detection, but few authors have analyzed the possibility of taking advantage of the information redundancy present in multiple ECG leads (simultaneously acquired) to produce accurate QRS detection. In our previous work we presented such an approach, proposing various data fusion techniques to combine the detections made by an algorithm on multiple ECG leads. In this paper we present further studies that show the advantages of this multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance. A well known QRS detection algorithm was used to test the fusion techniques on the St. Petersburg Institute of Cardiological Technics database. Results show improvement in the detection performance with as little as three leads, but the reliability of these results becomes interesting only after using seven or more leads. Results were evaluated using the detection error rate (DER). The multi-lead detection approach allows an improvement from DER = 3:04% to DER = 1:88%. Further works are to be made in order to improve the detection performance by implementing further fusion steps.

  3. A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders.

    Directory of Open Access Journals (Sweden)

    Robert M Dorazio

    Full Text Available Several spatial capture-recapture (SCR models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.We developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.Our approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in

  4. Improvements on Near Real Time Detection of Volcanic Ash Emissions for Emergency Monitoring with Limited Satellite Bands

    Directory of Open Access Journals (Sweden)

    Torge Steensen

    2015-03-01

    Full Text Available Quantifying volcanic ash emissions syneruptively is an important task for the global aviation community. However, due to the near real time nature of volcano monitoring, many parameters important for accurate ash mass estimates cannot be obtained easily. Even when using the best possible estimates of those parameters, uncertainties associated with the ash masses remain high, especially if the satellite data is only available in the traditional 10.8 and 12.0 μm bands. To counteract this limitation, we developed a quantitative comparison between the ash extents in satellite and model data. The focus is the manual cloud edge definition based on the available satellite reverse absorption (RA data as well as other knowledge like pilot reports or ground-based observations followed by an application of the Volcanic Ash Retrieval on the defined subset with an RA threshold of 0 K. This manual aspect, although subjective to the experience of the observer, can show a significant improvement as it provides the ability to highlight ash that otherwise would be obscured by meteorological clouds or, by passing over different surfaces with unaccounted temperatures, might be lost entirely and thus remains undetectable for an automated satellite approach. We show comparisons to Volcanic Ash Transport and Dispersion models and outline a quantitative match as well as percentages of overestimates based on satellite or dispersion model data which can be converted into a level of reliability for near real time volcano monitoring. 

  5. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Detection Environmental Data Record (EDR) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of suspended matter from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

  6. Robust detection of heart beats in multimodal records using slope- and peak-sensitive band-pass filters.

    Science.gov (United States)

    Pangerc, Urška; Jager, Franc

    2015-08-01

    In this work, we present the development, architecture and evaluation of a new and robust heart beat detector in multimodal records. The detector uses electrocardiogram (ECG) signals, and/or pulsatile (P) signals, such as: blood pressure, artery blood pressure and pulmonary artery pressure, if present. The base approach behind the architecture of the detector is collecting signal energy (differentiating and low-pass filtering, squaring, integrating). To calculate the detection and noise functions, simple and fast slope- and peak-sensitive band-pass digital filters were designed. By using morphological smoothing, the detection functions were further improved and noise intervals were estimated. The detector looks for possible pacemaker heart rate patterns and repairs the ECG signals and detection functions. Heart beats are detected in each of the ECG and P signals in two steps: a repetitive learning phase and a follow-up detecting phase. The detected heart beat positions from the ECG signals are merged into a single stream of detected ECG heart beat positions. The merged ECG heart beat positions and detected heart beat positions from the P signals are verified for their regularity regarding the expected heart rate. The detected heart beat positions of a P signal with the best match to the merged ECG heart beat positions are selected for mapping into the noise and no-signal intervals of the record. The overall evaluation scores in terms of average sensitivity and positive predictive values obtained on databases that are freely available on the Physionet website were as follows: the MIT-BIH Arrhythmia database (99.91%), the MGH/MF Waveform database (95.14%), the augmented training set of the follow-up phase of the PhysioNet/Computing in Cardiology Challenge 2014 (97.67%), and the Challenge test set (93.64%).

  7. Detection and variability of the Congo River plume from satellite derived sea surface temperature, salinity, ocean colour and sea level

    Science.gov (United States)

    Hopkins, Jo; Lucas, Marc; Dufau, Claire; Sutton, Marion; Lauret, Olivier

    2013-04-01

    The Congo River in Africa has the world's second highest annual mean daily freshwater discharge and is the second largest exporter of terrestrial organic carbon into the oceans. It annually discharges an average of 1,250 × 109 m3 of freshwater into the southeast Atlantic producing a vast fresh water plume, whose signature can be traced hundreds of kilometres from the river mouth. Large river plumes such as this play important roles in the ocean carbon cycle, often functioning as carbon sinks. An understanding of their extent and seasonality is therefore essential if they are to be realistically accounted for in global assessments of the carbon cycle. Despite its size, the variability and dynamics of the Congo plume are minimally documented. In this paper we analyse satellite derived sea surface temperature, salinity, ocean colour and sea level anomaly to describe and quantify the extent, strength and variability of the far-field plume and to explain its behaviour in relation to winds, ocean currents and fresh water discharge. Empirical Orthogonal Function analysis reveals strong seasonal and coastal upwelling signals, potential bimodal seasonality of the Angola Current and responses to fresh water discharge peaks in all data sets. The strongest plume-like signatures however were found in the salinity and ocean colour where the dominant sources of variability come from the Congo River itself, rather than from the wider atmosphere and ocean. These two data sets are then analysed using a statistically based water mass detection technique to isolate the behaviour of the plume. The Congo's close proximity to the equator means that the influence of the earth's rotation on the fresh water inflow is relatively small and the plume tends not to form a distinct coastal current. Instead, its behaviour is determined by wind and surface circulation patterns. The main axis of the plume between November and February, following peak river discharge, is oriented northwest, driven

  8. A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

    Science.gov (United States)

    Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

    2017-06-01

    Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

  9. A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

    Science.gov (United States)

    Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

    2017-06-01

    Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

  10. Data Matching Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection

    CERN Document Server

    Christen, Peter

    2012-01-01

    Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of da

  11. Advancing satellite-based solar power forecasting through integration of infrared channels for automatic detection of coastal marine inversion layer

    Energy Technology Data Exchange (ETDEWEB)

    Kostylev, Vladimir; Kostylev, Andrey; Carter, Chris; Mahoney, Chad; Pavlovski, Alexandre; Daye, Tony [Green Power Labs Inc., Dartmouth, NS (Canada); Cormier, Dallas Eugene; Fotland, Lena [San Diego Gas and Electric Co., San Diego, CA (United States)

    2012-07-01

    The marine atmospheric boundary layer is a layer or cool, moist maritime air with the thickness of a few thousand feet immediately below a temperature inversion. In coastal areas as moist air rises from the ocean surface, it becomes trapped and is often compressed into fog above which a layer of stratus clouds often forms. This phenomenon is common for satellite-based solar radiation monitoring and forecasting. Hour ahead satellite-based solar radiation forecasts are commonly using visible spectrum satellite images, from which it is difficult to automatically differentiate low stratus clouds and fog from high altitude clouds. This provides a challenge for cloud motion tyracking and cloud cover forecasting. San Diego Gas and Electric {sup registered} (SDG and E {sup registered}) Marine Layer Project was undertaken to obtain information for integration with PV forecasts, and to develop a detailed understanding of long-term benefits from forecasting Marine Layer (ML) events and their effects on PV production. In order to establish climatological ML patterns, spatial extent and distribution of marine layer, we analyzed visible and IR spectrum satellite images (GOES WEST) archive for the period of eleven years (2000 - 2010). Historical boundaries of marine layers impact were established based on the cross-classification of visible spectrum (VIS) and infrared (IR) images. This approach is successfully used by us and elsewhere for evaluating cloud albedo in common satellite-based techniques for solar radiation monitoring and forecasting. The approach allows differentiation of cloud cover and helps distinguish low laying fog which is the main consequence of marine layer formation. ML occurrence probability and maximum extent inland was established for each hour and day of the analyzed period and seasonal/patterns were described. SDG and E service area is the most affected region by ML events with highest extent and probability of ML occurrence. Influence of ML was the

  12. Performance of short ECG recordings twice daily to detect paroxysmal atrial fibrillation in stroke and transient ischemic attack patients

    DEFF Research Database (Denmark)

    Poulsen, Mai Bang; Binici, Zeynep; Domínguez, Helena

    2017-01-01

    Aims Prolonged cardiac monitoring after stroke is recommended though there is no consensus on optimal methods. Short-term ECG recordings with a "thumb-ECG" device have shown promising preliminary results regarding effectiveness and cost benefit. We aimed to examine the performance of thumb...... methods was poor and the trial was not powered to detect a minor difference between the devices. The inter-observer agreement for the thumb-ECG was substantial. www.clinicalTrials.gov UI: NCT02261766....

  13. Detecting air traffic controller interventions in recorded air transportation system data

    Science.gov (United States)

    Kwon, Yul

    In this study, I propose a systematic method of detecting aircraft deviation due to air traffic controller (ATC) intervention. The aircraft deviations associated with ATC interventions are detected using a heuristic algorithm developed from analyzing the actual positions of an aircraft to its filed flight plan when the aircraft trajectories were identified as having an encounter in a loss-of-separation incident. An actual (closed-loop) flight trajectory of the Cleveland Air Route Traffic Control Center (ZOB ARTCC) was collected from the FlightAware database. This was compared with the corresponding planned (open-loop) trajectory dataset generated by the Microsoft(c) Flight Simulator X (FSX). I implemented a conflict-detection algorithm in Matlab to identify open-loop flight trajectories that encounters in loss-of-separation. I analyzed the differences between the closed-loop and open-loop flight trajectories of aircrafts that were identified to have encounters in loss of separation. The analysis identified operationally significant deviations in the closed-loop trajectory data with respect to the horizontal paths of the aircrafts. I then developed and validated a heuristic algorithm, the ATC intervention detection algorithm, based on the findings from the analysis. When used with a test dataset to validate the algorithm, it achieved an 85.7% detection rate in detecting horizontal deviations made by the ATC in resolving identified conflicts, and a false-alarm rate of 68%. In addition to the ATC intervention detection algorithm, I present in this paper an analysis of deviated flight trajectories in an effort to display how the presented methodology can be utilized to provide insight into air traffic controller resolution strategies.

  14. Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

    Science.gov (United States)

    Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner

    2010-01-01

    In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979

  15. Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

    Science.gov (United States)

    Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

    2018-04-01

    Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

  16. a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

    Science.gov (United States)

    Haigang, Sui; Zhina, Song

    2016-06-01

    Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

  17. H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

    Science.gov (United States)

    Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

    2017-01-01

    Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

  18. Creation of an Accurate Algorithm to Detect Snellen Best Documented Visual Acuity from Ophthalmology Electronic Health Record Notes.

    Science.gov (United States)

    Mbagwu, Michael; French, Dustin D; Gill, Manjot; Mitchell, Christopher; Jackson, Kathryn; Kho, Abel; Bryar, Paul J

    2016-05-04

    Visual acuity is the primary measure used in ophthalmology to determine how well a patient can see. Visual acuity for a single eye may be recorded in multiple ways for a single patient visit (eg, Snellen vs. Jäger units vs. font print size), and be recorded for either distance or near vision. Capturing the best documented visual acuity (BDVA) of each eye in an individual patient visit is an important step for making electronic ophthalmology clinical notes useful in research. Currently, there is limited methodology for capturing BDVA in an efficient and accurate manner from electronic health record (EHR) notes. We developed an algorithm to detect BDVA for right and left eyes from defined fields within electronic ophthalmology clinical notes. We designed an algorithm to detect the BDVA from defined fields within 295,218 ophthalmology clinical notes with visual acuity data present. About 5668 unique responses were identified and an algorithm was developed to map all of the unique responses to a structured list of Snellen visual acuities. Visual acuity was captured from a total of 295,218 ophthalmology clinical notes during the study dates. The algorithm identified all visual acuities in the defined visual acuity section for each eye and returned a single BDVA for each eye. A clinician chart review of 100 random patient notes showed a 99% accuracy detecting BDVA from these records and 1% observed error. Our algorithm successfully captures best documented Snellen distance visual acuity from ophthalmology clinical notes and transforms a variety of inputs into a structured Snellen equivalent list. Our work, to the best of our knowledge, represents the first attempt at capturing visual acuity accurately from large numbers of electronic ophthalmology notes. Use of this algorithm can benefit research groups interested in assessing visual acuity for patient centered outcome. All codes used for this study are currently available, and will be made available online at https://phekb.org.

  19. Wall-Current-Monitor based Ghost and Satellite Bunch Detection in the CERN PS and the LHC Accelerators

    CERN Document Server

    Steinhagen, R J; Belleman, J; Bohl, T; Damerau, H

    2012-01-01

    While most LHC detectors and instrumentation systems are optimised for a nominal bunch spacing of 25 ns, the LHC RF cavities themselves operate at the 10th harmonic of the maximum bunch frequency. Due to the beam production scheme and transfers in the injector chain, part of the nominally ‘empty’ RF buckets may contain particles, referred to as ghost or satellite bunches. These populations must be accurately quantified for high-precision experiments, luminosity calibration and control of parasitic particle encounters at the four LHC interaction points. This contribution summarises the wall-current-monitor based ghost and satellite bunch measurements in CERN’s PS and LHC accelerators. Instrumentation set-up, post-processing and achieved performance are discussed.

  20. Site use by dark-bellied brent geese Branta bernicla bernicla on the Russian tundra as recorded by satellite telemetry: implications for East Atlantic flyway conservation

    NARCIS (Netherlands)

    Green, M.; Alerstam, T.; Clausen, P.; Drent, R.; Ebbinge, B.S.

    2002-01-01

    In 1999, seven dark-bellied brent geese Branta bemicla bemicla were followed during spring migration from western Europe to Arctic Russia using satellite telemetry. For six of the birds we were also able to monitor their summer stay at the Taimyr Peninsula, and for five birds part of their autumn

  1. Site use by dark-bellied brent geese Branta bernicla bernicla on the Russian tundra as recorded by satellite telemetry : implications for East Atlantic Flyway conservation

    NARCIS (Netherlands)

    Green, M; Alerstam, T; Clausen, P; Drent, R; Ebbinge, BS

    In 1999, seven dark-bellied brent geese Branta bemicla bemicla were followed during spring migration from western Europe to Arctic Russia using satellite telemetry. For six of the birds we were also able to monitor their summer stay at the Taymyr Peninsula, and for five birds part of their autumn

  2. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    OpenAIRE

    Chandi Witharana; Heather J. Lynch

    2016-01-01

    The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA) methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR) satellite imagery and closely examined the transferability of knowle...

  3. Nowcast of thunderstorm and typhoon activity based on lightning detection and flexible operation of micro-satellites

    Science.gov (United States)

    Takahashi, Y.

    2016-12-01

    It has become known that lightning activity represents the thunderstorm activity, namely, the intensity and area of precipitation and/or updraft. Thunderstorm is also important as a proxy of the energy input from ocean to atmosphere in typhoon, meaning that if we could monitor the thunderstorm with lightning we could predict the maximum wind velocity near the typhoon center by one or two days before. Constructing ELF and VLF radio wave observation network in Southeast Asia (AVON) and a regional dense network of automated weather station in a big city, we plan to establish the monitoring system for thunderstorm development in western pacific warm pool (WPWP) where typhoon is formed and in detail in big city area. On the other hand, some developing countries in SE-Asia are going to own micro-satellites dedicated to meteorological remote sensing. Making use of the lightning activity data measured by the ground-based networks, and information on 3-D structures of thunderclouds observed by the flexible on-demand operation of the remote-sensing micro-satellites, we would establish a new methodology to obtain very detail semi-real time information that cannot be achieved only with existing observation facilities, such as meteorological radar or large meteorological satellite. Using this new system we try to issue nowcast for the local thunderstorm and for typhoons. The first attempt will be carried out in Metro Manila in Philippines and WPWP as one of the SATREPS projects.

  4. A Wireless sEMG Recording System and Its Application to Muscle Fatigue Detection

    Science.gov (United States)

    Chang, Kang-Ming; Liu, Shin-Hong; Wu, Xuan-Han

    2012-01-01

    Surface electromyography (sEMG) is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference. PMID:22368481

  5. A Wireless sEMG Recording System and Its Application to Muscle Fatigue Detection

    Directory of Open Access Journals (Sweden)

    Xuan-Han Wu

    2012-01-01

    Full Text Available Surface electromyography (sEMG is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference.

  6. LiteBIRD: a small satellite for the study of B-mode polarization and inflation from cosmic background radiation detection

    Science.gov (United States)

    Hazumi, M.; Borrill, J.; Chinone, Y.; Dobbs, M. A.; Fuke, H.; Ghribi, A.; Hasegawa, M.; Hattori, K.; Hattori, M.; Holzapfel, W. L.; Inoue, Y.; Ishidoshiro, K.; Ishino, H.; Karatsu, K.; Katayama, N.; Kawano, I.; Kibayashi, A.; Kibe, Y.; Kimura, N.; Koga, K.; Komatsu, E.; Lee, A. T.; Matsuhara, H.; Matsumura, T.; Mima, S.; Mitsuda, K.; Morii, H.; Murayama, S.; Nagai, M.; Nagata, R.; Nakamura, S.; Natsume, K.; Nishino, H.; Noda, A.; Noguchi, T.; Ohta, I.; Otani, C.; Richards, P. L.; Sakai, S.; Sato, N.; Sato, Y.; Sekimoto, Y.; Shimizu, A.; Shinozaki, K.; Sugita, H.; Suzuki, A.; Suzuki, T.; Tajima, O.; Takada, S.; Takagi, Y.; Takei, Y.; Tomaru, T.; Uzawa, Y.; Watanabe, H.; Yamasaki, N.; Yoshida, M.; Yoshida, T.; Yotsumoto, K.

    2012-09-01

    LiteBIRD [Lite (Light) satellite for the studies of B-mode polarization and Inflation from cosmic background Radiation Detection] is a small satellite to map the polarization of the cosmic microwave background (CMB) radiation over the full sky at large angular scales with unprecedented precision. Cosmological inflation, which is the leading hypothesis to resolve the problems in the Big Bang theory, predicts that primordial gravitational waves were created during the inflationary era. Measurements of polarization of the CMB radiation are known as the best probe to detect the primordial gravitational waves. The LiteBIRD working group is authorized by the Japanese Steering Committee for Space Science (SCSS) and is supported by JAXA. It has more than 50 members from Japan, USA and Canada. The scientific objective of LiteBIRD is to test all the representative inflation models that satisfy single-field slow-roll conditions and lie in the large-field regime. To this end, the requirement on the precision of the tensor-to-scalar ratio, r, at LiteBIRD is equal to or less than 0.001. Our baseline design adopts an array of multi-chroic superconducting polarimeters that are read out with high multiplexing factors in the frequency domain for a compact focal plane. The required sensitivity of 1.8μKarcmin is achieved with 2000 TES bolometers at 100mK. The cryogenic system is based on the Stirling/JT technology developed for SPICA, and the continuous ADR system shares the design with future X-ray satellites.

  7. Detecting oscillatory patterns and time lags from proxy records with non-uniform sampling: Some pitfalls and possible solutions

    Science.gov (United States)

    Donner, Reik

    2013-04-01

    Time series analysis offers a rich toolbox for deciphering information from high-resolution geological and geomorphological archives and linking the thus obtained results to distinct climate and environmental processes. Specifically, on various time-scales from inter-annual to multi-millenial, underlying driving forces exhibit more or less periodic oscillations, the detection of which in proxy records often allows linking them to specific mechanisms by which the corresponding drivers may have affected the archive under study. A persistent problem in geomorphology is that available records do not present a clear signal of the variability of environmental conditions, but exhibit considerable uncertainties of both the measured proxy variables and the associated age model. Particularly, time-scale uncertainty as well as the heterogeneity of sampling in the time domain are source of severe conceptual problems that may lead to false conclusions about the presence or absence of oscillatory patterns and their mutual phasing in different archives. In my presentation, I will discuss how one can cope with non-uniformly sampled proxy records to detect and quantify oscillatory patterns in one or more data sets. For this purpose, correlation analysis is reformulated using kernel estimates which are found superior to classical estimators based on interpolation or Fourier transform techniques. In order to characterize non-stationary or noisy periodicities and their relative phasing between different records, an extension of continuous wavelet transform is utilized. The performance of both methods is illustrated for different case studies. An extension to explicitly considering time-scale uncertainties by means of Bayesian techniques is briefly outlined.

  8. Ionospheric and satellite observations for studying the dynamic behavior of typhoons and the detection of severe storms and tsunamis

    Science.gov (United States)

    Hung, R. J.; Smith, R. E.

    1978-01-01

    Atmospheric acoustic-gravity waves associated with severe thunderstorms, tornadoes, typhoons (hurricanes) and tsunamis can be studied through the coupling between the ionosphere and the troposphere. Reverse ray tracing computations of acoustic-gravity waves observed by an ionospheric Doppler sounder array show that wave sources are in the nearby storm systems and that the waves are excited prior to the storms. Results show that ionospheric observations, together with satellite observations, can contribute to the understanding of the dynamical behavior of typhoons, severe storms and tsunamis.

  9. Detection of minor and major satellite DNA in cytokinesis-blocked mouse splenocytes by a PRINS tandem labelling approach.

    Science.gov (United States)

    Russo, A; Tommasi, A M; Renzi, L

    1996-11-01

    A protocol for the simultaneous visualization of minor and major satellite DNA by primed in situ DNA synthesis (PRINS) was developed in cytokinesis-blocked murine splenocytes. After individuation of optimal experimental conditions, a micronucleus (MN) test was carried out by treating splenocytes in vitro with the clastogenic agent mitomycin C and the aneugenic compound Colcemid. It was found that PRINS gives highly reproducible results, also comparable with the literature on MN results obtained by fluorescent in situ hybridization (FISH). Therefore the PRINS methodology may be proposed as a fast alternative to FISH for the characterization of induced MN.

  10. Testing an advanced satellite technique for dust detection as a decision support system for the air quality assessment

    Science.gov (United States)

    Falconieri, Alfredo; Filizzola, Carolina; Femiano, Rossella; Marchese, Francesco; Sannazzaro, Filomena; Pergola, Nicola; Tramutoli, Valerio; Di Muro, Ersilia; Divietri, Mariella; Crisci, Anna Maria; Lovallo, Michele; Mangiamele, Lucia; Vaccaro, Maria Pia; Palma, Achille

    2014-05-01

    In order to correctly apply the European directive for air quality (2008/50/CE), local Authorities are often requested to discriminate the possible origin (natural/anthropic) of anomalous concentration of pollutants in the air (art.20 Directive 2008/50/CE). In this framework, it's been focused on PM10 and PM2,5 concentrations and sources. In fact, depending on their origin, appropriate counter-measures can be taken devoted to prevent their production (e.g. by traffic restriction) or simply to reduce their impact on citizen health (e.g. information campaigns). In this context suitable satellite techniques can be used in order to identify natural sources (particularly Saharan dust, but also volcanic ash or forest fire smoke) that can be responsible of over-threshold concentration of PM10/2,5 in populated areas. In the framework of the NIBS (Networking and Internationalization of Basilicata Space Technologies) project, funded by the Basilicata Region within the ERDF 2007-2013 program, the School of Engineering of University of Basilicata, the Institute of Methodologies for Environmental Analysis of National Research Council (IMAA-CNR) and the Regional Agency for the Protection of the Environment of Basilicata Region (ARPAB) have started a collaboration devoted to assess the potential of the use of advanced satellite techniques for Saharan dust events identification to support ARPAB activities related to the application of the European directive for air quality (2008/50/CE) in Basilicata region. In such a joint activity, the Robust Satellite Technique (RST) approach has been assessed and tested as a decision support system for monitoring and evaluating air quality at local and regional level. In particular, RST-DUST products, derived by processing high temporal resolution data provided by SEVIRI (Spinning Enhanced Visible and Infrared Imager) sensor on board Meteosat Second Generation platforms, have been analysed together with PM10 measurements performed by the ground

  11. Machine Learning Approaches for Detecting Diabetic Retinopathy from Clinical and Public Health Records.

    Science.gov (United States)

    Ogunyemi, Omolola; Kermah, Dulcie

    2015-01-01

    Annual eye examinations are recommended for diabetic patients in order to detect diabetic retinopathy and other eye conditions that arise from diabetes. Medically underserved urban communities in the US have annual screening rates that are much lower than the national average and could benefit from informatics approaches to identify unscreened patients most at risk of developing retinopathy. Using clinical data from urban safety net clinics as well as public health data from the CDC's National Health and Nutrition Examination Survey, we examined different machine learning approaches for predicting retinopathy from clinical or public health data. All datasets utilized exhibited a class imbalance. Classifiers learned on the clinical data were modestly predictive of retinopathy with the best model having an AUC of 0.72, sensitivity of 69.2% and specificity of 55.9%. Classifiers learned on public health data were not predictive of retinopathy. Successful approaches to detecting latent retinopathy using machine learning could help safety net and other clinics identify unscreened patients who are most at risk of developing retinopathy and the use of ensemble classifiers on clinical data shows promise for this purpose.

  12. Assessment of Satellite Capabilities to Detect Impacts of Oil and Natural Gas Activity by Analysis of SONGNEX 2015 Aircraft Measurements

    Science.gov (United States)

    Thayer, M. P.; Keutsch, F. N.; Wolfe, G.; St Clair, J. M.; Hanisco, T. F.; Aikin, K. C.; Brown, S. S.; Dubé, W.; Eilerman, S. J.; Gilman, J.; De Gouw, J. A.; Koss, A.; Lerner, B. M.; Neuman, J. A.; Peischl, J.; Ryerson, T. B.; Thompson, C. R.; Veres, P. R.; Warneke, C.; Washenfelder, R. A.; Wild, R. J.; Womack, C.; Yuan, B.; Zarzana, K. J.

    2017-12-01

    In the last decade, the rate of domestic energy production from oil and natural gas has grown dramatically, resulting in increased concurrent emissions of methane and other volatile organic compounds (VOCs). Products of VOC oxidation and radical cycling, such as tropospheric ozone (O3) and secondary organic aerosols (SOA), have detrimental impacts on human health and climate. The ability to monitor these emissions and their impact on atmospheric composition from remote-sensing platforms will benefit public health by improving air quality forecasts and identifying localized drivers of tropospheric pollution. New satellite-based instruments, such as TROPOMI (October 2017 launch) and TEMPO (2019-2021 projected launch), will be capable of measuring chemical species related to energy drilling and production on unprecedented spatial and temporal scales, however there is need for improved assessments of their capabilities with respect to specific applications. We use chemical and physical parameters measured via aircraft in the boundary layer and free troposphere during the Shale Oil and Natural Gas Nexus (SONGNEX 2015) field campaign to view chemical enhancements over tight oil and shale gas basins from a satellite perspective. Our in-situ data are used to calculate the planetary boundary layer contributions to the column densities for formaldehyde, glyoxal, O3, and NO2. We assess the spatial resolution and chemical precisions necessary to resolve various chemical features, and compare these limits to TEMPO and TROPOMI capabilities to show the degree to which their retrievals will be able to discern the signatures of oil and natural gas activity.

  13. CHANGE DETECTION OF CROPPING PATTERN IN PADDY FIELD USING MULTI SPECTRAL SATELLITE DATA FOR ESTIMATING IRRIGATION WATER NEEDS

    Directory of Open Access Journals (Sweden)

    Rizatus Shofiyati1

    2012-10-01

    Full Text Available This paper investigates the use of multi spectral satellite data for cropping pattern monitoring in paddy field. The southern coastal of Citarum watershed, West Java Province was selected as study sites. The analysis used in this study is identifying crop pattern based on growth stages of wetland paddy and other crops by investi-gating the characteristic of Normalized Differen-ce Vegetation Indices (NDVI and Wetness of Tasseled Cap Transformation (TCT derived from 14 scenes of Landsat TM date 1988 to 2001. In general, the phenological of growth stages of wetland paddy can be used to distinguish with other seasonal crops. The research results indicate that multi spectral satellite data has a great potential for identi-fication and monitoring cropping pattern in paddy field. Specific character of NDVI and Wetness can also produce a map of cropping pattern in paddy field that is useful to monitor agricultural land condition. The cropping pattern can also be used to estimate irrigation water needed of paddy field in the area. Expected implication of the information obtained from this analysis is useful for guiding more appropriate planning and better agricultural management.

  14. Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

    Directory of Open Access Journals (Sweden)

    Tony A. Cole

    2017-03-01

    Full Text Available Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS Day/Night Band (DNB can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

  15. Systems for detecting and recording hard corpuscular and electromagnetic radiations using a superconducting element

    International Nuclear Information System (INIS)

    Drukier, A.K.; Valette, Claude; Waysand, Georges.

    1975-01-01

    The invention relates to systems for detecting hard X ray or gamma radiations above 5 keV in energy, intended, for example, for gammagraphy by emission in the biological, anatomic and medical fields. It describes systems of the above type which directly give the image of a radiation distribution, that is to say without intermediate processing. Another purpose of the invention is to provide the devices with main memory measuring the radiation distribution, in other words systems that display the said data for as long as the operator deems necessary and that can be reset, that is to say returned to measuring conditions, immediately. The invention makes use of the properties of type I superconductors [fr

  16. Detection of explosive cough events in audio recordings by internal sound analysis.

    Science.gov (United States)

    Rocha, B M; Mendes, L; Couceiro, R; Henriques, J; Carvalho, P; Paiva, R P

    2017-07-01

    We present a new method for the discrimination of explosive cough events, which is based on a combination of spectral content descriptors and pitch-related features. After the removal of near-silent segments, a vector of event boundaries is obtained and a proposed set of 9 features is extracted for each event. Two data sets, recorded using electronic stethoscopes and comprising a total of 46 healthy subjects and 13 patients, were employed to evaluate the method. The proposed feature set is compared to three other sets of descriptors: a baseline, a combination of both sets, and an automatic selection of the best 10 features from both sets. The combined feature set yields good results on the cross-validated database, attaining a sensitivity of 92.3±2.3% and a specificity of 84.7±3.3%. Besides, this feature set seems to generalize well when it is trained on a small data set of patients, with a variety of respiratory and cardiovascular diseases, and tested on a bigger data set of mostly healthy subjects: a sensitivity of 93.4% and a specificity of 83.4% are achieved in those conditions. These results demonstrate that complementing the proposed feature set with a baseline set is a promising approach.

  17. Detection of a dynamic topography signal in last interglacial sea-level records.

    Science.gov (United States)

    Austermann, Jacqueline; Mitrovica, Jerry X; Huybers, Peter; Rovere, Alessio

    2017-07-01

    Estimating minimum ice volume during the last interglacial based on local sea-level indicators requires that these indicators are corrected for processes that alter local sea level relative to the global average. Although glacial isostatic adjustment is generally accounted for, global scale dynamic changes in topography driven by convective mantle flow are generally not considered. We use numerical models of mantle flow to quantify vertical deflections caused by dynamic topography and compare predictions at passive margins to a globally distributed set of last interglacial sea-level markers. The deflections predicted as a result of dynamic topography are significantly correlated with marker elevations (>95% probability) and are consistent with construction and preservation attributes across marker types. We conclude that a dynamic topography signal is present in the elevation of last interglacial sea-level records and that the signal must be accounted for in any effort to determine peak global mean sea level during the last interglacial to within an accuracy of several meters.

  18. Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

    Science.gov (United States)

    Tigges, P; Kathmann, N; Engel, R R

    1997-07-01

    Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

  19. On-Particle Rolling Circle Amplification-Based Core-Satellite Magnetic Superstructures for MicroRNA Detection

    DEFF Research Database (Denmark)

    Tian, Bo; Qiu, Zhen; Ma, Jing

    2018-01-01

    -specific nuclease in the presence of target microRNA, resulting in a release of MNPs that can be quantified in an optomagnetic sensor. The proposed biosensor has a simple mix-separate-measure strategy. For let-7b detection, the proposed biosensor offers a wide linear detection range of approximately 5 orders...

  20. Detection of ionospheric perturbations associated with Japanese earthquakes on the basis of reception of LF transmitter signals on the satellite DEMETER

    Directory of Open Access Journals (Sweden)

    F. Muto

    2008-02-01

    Full Text Available There have been recently reported a lot of electromagnetic phenomena associated with earthquakes (EQs. Among these, the ground-based reception of subionospheric waves from VLF/LF transmitters, is recognized as a promising tool to investigate the ionospheric perturbations associated with EQs. This paper deals with the corresponding whistler-mode signals in the upper ionosphere from those VLF/LF transmitters, which is the counterpart of subionospheric signals. The whistler-mode VLF/LF transmitter signals are detected on board the French satellite, DEMETER launched on 29 June 2004. We have chosen several large Japanese EQs including the Miyagi-oki EQ (16 August 2005; M=7.2, depth=36 km, and the target transmitter is a Japanese LF transmitter (JJY whose transmitter frequency is 40 kHz. Due to large longitudinal separation of each satellite orbit (2500 km, we have to adopt a statistical analysis over a rather long period (such as 3 weeks or one month to have reliable data set. By analyzing the spatial distribution of JJY signal intensity (in the form of signal to noise ratio SNR during a period of 4 months including the Miyagi-oki EQ, we have found significant changes in the intensity; generally the SNR is significantly depleted before the EQ, which is considered to be a precursory ionospheric signature of the EQ. This abnormal effect is reasonably explained in terms of either (1 enhanced absorption of whistler-mode LF signals in the lower ionosphere due to the lowering of the lower ionosphere, or (2 nonlinear wave-wave scattering. Finally, this analysis suggests an important role of satellite observation in the study of lithosphere-atmosphere-ionosphere coupling.

  1. Saturn satellites

    International Nuclear Information System (INIS)

    Ruskol, E.L.

    1981-01-01

    The characteristics of the Saturn satellites are discussed. The satellites close to Saturn - Janus, Mimas, Enceladus, Tethys, Dione and Rhea - rotate along the circular orbits. High reflectivity is attributed to them, and the density of the satellites is 1 g/cm 3 . Titan is one of the biggest Saturn satellites. Titan has atmosphere many times more powerful than that of Mars. The Titan atmosphere is a peculiar medium with a unique methane and hydrogen distribution in the whole Solar system. The external satellites - Hyperion, Japetus and Phoebe - are poorly investigated. Neither satellite substance density, nor their composition are known. The experimental data on the Saturn rings obtained on the ''Pioneer-11'' and ''Voyager-1'' satellites are presented [ru

  2. Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

    Science.gov (United States)

    Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

    2016-09-01

    The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

  3. Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

    Directory of Open Access Journals (Sweden)

    Eija Parmes

    2017-08-01

    Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

  4. A CLOUD BOUNDARY DETECTION SCHEME COMBINED WITH ASLIC AND CNN USING ZY-3, GF-1/2 SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    Z. Guo

    2018-04-01

    Full Text Available Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

  5. A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

    Science.gov (United States)

    Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nikolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

    2012-01-01

    We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

  6. Utilization of a genetic algorithm for the automatic detection of oil spill from RADARSAT-2 SAR satellite data

    International Nuclear Information System (INIS)

    Marghany, Maged

    2014-01-01

    Highlights: • An oil platform located 70 km from the coast of Louisiana sank on Thursday. • Oil spill has backscatter values of −25 dB in RADARSAT-2 SAR. • Oil spill is portrayed in SCNB mode by shallower incidence angle. • Ideal detection of oil spills in SAR images requires moderate wind speeds. • Genetic algorithm is excellent tool for automatic detection of oil spill in RADARSAT-2 SAR data. - Abstract: In this work, a genetic algorithm is applied for the automatic detection of oil spills. The procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow single-beam data acquired in the Gulf of Mexico. The study demonstrates that the implementation of crossover allows for the generation of an accurate oil spill pattern. This conclusion is confirmed by the receiver-operating characteristic (ROC) curve. The ROC curve indicates that the existence of oil slick footprints can be identified using the area between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills, and the ScanSAR Narrow single-beam mode serves as an excellent sensor for oil spill detection and survey

  7. A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

    Science.gov (United States)

    Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

    2018-01-01

    The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

  8. TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 1: Line Segment Detection and Extraction

    Directory of Open Access Journals (Sweden)

    Mehdi Rahnama

    2014-06-01

    Full Text Available Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual interpretation of optical data and digital elevation models. We developed a freely available Matlab based toolbox TecLines (Tectonic Lineament Analysis for locating and quantifying lineament patterns using satellite data and digital elevation models. TecLines consists of a set of functions including frequency filtering, spatial filtering, tensor voting, Hough transformation, and polynomial fitting. Due to differences in the mathematical background of the edge detection and edge linking procedure as well as the breadth of the methods, we introduce the approach in two-parts. In this first study, we present the steps that lead to edge detection. We introduce the data pre-processing using selected filters in spatial and frequency domains. We then describe the application of the tensor-voting framework to improve position and length accuracies of the detected lineaments. We demonstrate the robustness of the approach in a complex area in the northeast of Afghanistan using a panchromatic QUICKBIRD-2 image with 1-meter resolution. Finally, we compare the results of TecLines with manual lineament extraction, and other lineament extraction algorithms, as well as a published fault map of the study area.

  9. Artificial intelligence systems for rainy areas detection and convective cells' delineation for the south shore of Mediterranean Sea during day and nighttime using MSG satellite images

    Science.gov (United States)

    Tebbi, Mohsene Abdelfettah; Haddad, Boualem

    2016-09-01

    The aim of this study is to investigate the potential of cloud classification by means of support vector machines using high resolution images from northern Algeria. The images were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board of the Meteosat Second Generation (MSG) satellite. An automatic system was developed to operate during both day and nighttime by following two steps of data processing. The first aims to detect rainy areas in cloud systems, whereas the second delineates convective cells from stratiform ones. A set of 12 spectral parameters was selected to extract information about cloud properties, which are different from day to night. The training and validation steps of this study were performed by in-situ rainfall measurement data, collected during the rainy season of years 2011 and 2012 via automatic rain gauge stations distributed in northern Algeria. Artificial neural networks (ANNs) and support vector machine (SVM) were explored, by combining spectral parameters derived from MSG images. Better performances were obtained by the SVM classifier, in terms of Critical Success Index and Probability of Detection for rainy areas detection (CSI = 0.81, POD = 91%), and also for convective/stratiform delineation (CSI = 0.55, POD = 74%).

  10. Observations of 50/60 Hz Power Line Radiation in the Low Latitude Ionosphere Detected by the Electric Field Instrument on the C/NOFS Satellite

    Science.gov (United States)

    Pfaff, R. F., Jr.; Freudenreich, H. T.; Simoes, F. A.; Liebrecht, M. C.; Farrell, W.

    2017-12-01

    One of the most ubiquitous forms of EM radiation emanating from the earth's surface is that of power line radiation. Associated with AC electric power generation, such emissions are typically launched along conducting power lines that may travel hundreds, or even thousands of km, from generating stations. The fundamental frequencies of such emissions are characteristically 50 Hz or 60 Hz, depending on the regional standards for power generation/consumption. The frequency of this radiation is well below that of the plasma frequency of the ionosphere (typically several MHz) and hence is expected to reflect back to the earth and propagate in the waveguide formed by the earth's surface and the bottom ledge of the ionosphere, typically near 100 km. Given that such power lines are widespread on the exposed lithosphere, the leakage of some ELF emissions associated with electric power generation might nevertheless be expected in the ionosphere, in the same manner in which a small fraction of the power associated with ELF Schumann resonances and lightning sferics have been shown to penetrate into the ionosphere. We present direct measurements of 50/60 Hz power line radiation detected by in situ probes on an orbiting satellite in the earth's ionosphere. The data were gathered by the Vector Electric Field Investigation (VEFI) tri-axial double probe detector flown on the Communication/Navigation Outage Forecast System (C/NOFS) satellite. C/NOFS was launched in April, 2008 into a low latitude (13 deg inclination) orbit with perigee and apogee of 400 km and 850 km, respectively. The electric field wave data were gathered by ELF receivers comprised of two orthogonal broadband channels sampled at 512 s/sec each, and digitized with 16 bit A/D converters. The data show distinct 60 Hz emissions while the satellite sampled within the Brazilian sector whereas distinct 50 Hz emissions were detected over India. Other, less distinct, emissions were observed over Africa and southeast Asia

  11. Emergency Department Chief Complaint and Diagnosis Data to Detect Influenza-Like Illness with an Electronic Medical Record

    Science.gov (United States)

    May, Larissa S.; Griffin, Beth Ann; Bauers, Nicole Maier; Jain, Arvind; Mitchum, Marsha; Sikka, Neal; Carim, Marianne; Stoto, Michael A.

    2010-01-01

    Background: The purpose of syndromic surveillance is early detection of a disease outbreak. Such systems rely on the earliest data, usually chief complaint. The growing use of electronic medical records (EMR) raises the possibility that other data, such as emergency department (ED) diagnosis, may provide more specific information without significant delay, and might be more effective in detecting outbreaks if mechanisms are in place to monitor and report these data. Objective: The purpose of this study is to characterize the added value of the primary ICD-9 diagnosis assigned at the time of ED disposition compared to the chief complaint for patients with influenza-like illness (ILI). Methods: The study was a retrospective analysis of the EMR of a single urban, academic ED with an annual census of over 60, 000 patients per year from June 2005 through May 2006. We evaluate the objective in two ways. First, we characterize the proportion of patients whose ED diagnosis is inconsistent with their chief complaint and the variation by complaint. Second, by comparing time series and applying syndromic detection algorithms, we determine which complaints and diagnoses are the best indicators for the start of the influenza season when compared to the Centers for Disease Control regional data for Influenza-Like Illness for the 2005 to 2006 influenza season using three syndromic surveillance algorithms: univariate cumulative sum (CUSUM), exponentially weighted CUSUM, and multivariate CUSUM. Results: In the first analysis, 29% of patients had a different diagnosis at the time of disposition than suggested by their chief complaint. In the second analysis, complaints and diagnoses consistent with pneumonia, viral illness and upper respiratory infection were together found to be good indicators of the start of the influenza season based on temporal comparison with regional data. In all examples, the diagnosis data outperformed the chief-complaint data. Conclusion: Both analyses

  12. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  13. Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird)

    Science.gov (United States)

    Atwood, Elizabeth C.; Englhart, Sandra; Lorenz, Eckehard; Halle, Winfried; Wiedemann, Werner; Siegert, Florian

    2016-01-01

    Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2–3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future. PMID:27486664

  14. Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird).

    Science.gov (United States)

    Atwood, Elizabeth C; Englhart, Sandra; Lorenz, Eckehard; Halle, Winfried; Wiedemann, Werner; Siegert, Florian

    2016-01-01

    Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.

  15. Unsupervised detection and removal of muscle artifacts from scalp EEG recordings using canonical correlation analysis, wavelets and random forests.

    Science.gov (United States)

    Anastasiadou, Maria N; Christodoulakis, Manolis; Papathanasiou, Eleftherios S; Papacostas, Savvas S; Mitsis, Georgios D

    2017-09-01

    This paper proposes supervised and unsupervised algorithms for automatic muscle artifact detection and removal from long-term EEG recordings, which combine canonical correlation analysis (CCA) and wavelets with random forests (RF). The proposed algorithms first perform CCA and continuous wavelet transform of the canonical components to generate a number of features which include component autocorrelation values and wavelet coefficient magnitude values. A subset of the most important features is subsequently selected using RF and labelled observations (supervised case) or synthetic data constructed from the original observations (unsupervised case). The proposed algorithms are evaluated using realistic simulation data as well as 30min epochs of non-invasive EEG recordings obtained from ten patients with epilepsy. We assessed the performance of the proposed algorithms using classification performance and goodness-of-fit values for noisy and noise-free signal windows. In the simulation study, where the ground truth was known, the proposed algorithms yielded almost perfect performance. In the case of experimental data, where expert marking was performed, the results suggest that both the supervised and unsupervised algorithm versions were able to remove artifacts without affecting noise-free channels considerably, outperforming standard CCA, independent component analysis (ICA) and Lagged Auto-Mutual Information Clustering (LAMIC). The proposed algorithms achieved excellent performance for both simulation and experimental data. Importantly, for the first time to our knowledge, we were able to perform entirely unsupervised artifact removal, i.e. without using already marked noisy data segments, achieving performance that is comparable to the supervised case. Overall, the results suggest that the proposed algorithms yield significant future potential for improving EEG signal quality in research or clinical settings without the need for marking by expert

  16. Detecting the Elusive P-Wave: A New ECG Lead to Improve the Recording of Atrial Activity.

    Science.gov (United States)

    Kennedy, Alan; Finlay, Dewar D; Guldenring, Daniel; Bond, Raymond R; McLaughlin, James

    2016-02-01

    In this study, we report on a lead selection method that was developed to detect the optimal bipolar electrode placement for recording of the P-wave. The study population consisted of 117 lead body surface potential maps recorded from 229 healthy subjects. The optimal bipolar lead was developed using the training set (172 subjects) then extracted from the testing dataset (57 subjects) and compared to other lead systems previously reported for improved recording of atrial activity. All leads were assessed in terms of P-wave, QRS, and STT root mean square (RMS). The P/QRST RMS ratio was also investigated to determine the atrioventricular RMS ratio. Finally, the effect of minor electrode misplacements on the P-lead was investigated. The P-lead discovered in this study outperformed all other investigated leads in terms of P-wave RMS. The P-lead showed a significant improvement in median P-wave RMS (93 versus 72 μV, p < 0.001) over the next best lead, Lead II. An improvement in QRS and STT RMS was also observed from the P-lead in comparison to lead II (668 versus 573 μV, p < 0.001) and (327 versus 196 μV, p < 0.001). Although P-wave RMS was reduced by incorrect electrode placement, significant improvement over Lead II was still evident. The P-lead improves P-wave RMS signal strength over all other investigated leads. Also the P-lead does not reduce QRS and STT RMS making it an appropriate choice for atrial arrhythmia monitoring. Given the improvement in signal-to-noise ratio, an improvement in algorithms that rely on P-wave analysis may be achieved.

  17. Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI)

    NARCIS (Netherlands)

    Van Hoek, Mattijn; Jia, Li; Zhou, J.; Zheng, Chaolei; Menenti, M.

    2016-01-01

    The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation)

  18. Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

    Science.gov (United States)

    Rendon Santillan, Jojene; Makinano-Santillan, Meriam

    2018-04-01

    We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

  19. ANALYSIS OF IN-SITU SPECTRAL REFLECTANCE OF SAGO AND OTHER PALMS: IMPLICATIONS FOR THEIR DETECTION IN OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    J. R. Santillan

    2018-04-01

    Full Text Available We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345–1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2. Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

  20. Development of a climate record of tropospheric and stratospheric column ozone from satellite remote sensing: evidence of an early recovery of global stratospheric ozone

    Directory of Open Access Journals (Sweden)

    J. R. Ziemke

    2012-07-01

    Full Text Available Ozone data beginning October 2004 from the Aura Ozone Monitoring Instrument (OMI and Aura Microwave Limb Sounder (MLS are used to evaluate the accuracy of the Cloud Slicing technique in effort to develop long data records of tropospheric and stratospheric ozone and for studying their long-term changes. Using this technique, we have produced a 32-yr (1979–2010 long record of tropospheric and stratospheric column ozone from the combined Total Ozone Mapping Spectrometer (TOMS and OMI. Analyses of these time series suggest that the quasi-biennial oscillation (QBO is the dominant source of inter-annual variability of stratospheric ozone and is clearest in the Southern Hemisphere during the Aura time record with related inter-annual changes of 30–40 Dobson Units. Tropospheric ozone for the long record also indicates a QBO signal in the tropics with peak-to-peak changes varying from 2 to 7 DU. The most important result from our study is that global stratospheric ozone indicates signature of a recovery occurring with ozone abundance now approaching the levels of year 1980 and earlier. The negative trends in stratospheric ozone in both hemispheres during the first 15 yr of the record are now positive over the last 15 yr and with nearly equal magnitudes. This turnaround in stratospheric ozone loss is occurring about 20 yr earlier than predicted by many chemistry climate models. This suggests that the Montreal Protocol which was first signed in 1987 as an international agreement to reduce ozone destroying substances is working well and perhaps better than anticipated.

  1. Uniting Satellite Data With Health Records to Address the Societal Impacts of Particulate Air Pollution: NASA's Multi-Angle Imager for Aerosols

    Science.gov (United States)

    Nastan, A.; Diner, D. J.

    2017-12-01

    Epidemiological studies have demonstrated convincingly that airborne particulate matter has a major impact on human health, particularly in urban areas. However, providing an accurate picture of the health effects of various particle mixtures — distinguished by size, shape, and composition — is difficult due to the constraints of currently available measurement tools and the heterogeneity of atmospheric chemistry and human activities over space and time. The Multi-Angle Imager for Aerosols (MAIA) investigation, currently in development as part of NASA's Earth Venture Instrument Program, will address this issue through a powerful combination of technologies and informatics. Atmospheric measurements collected by the MAIA satellite instrument featuring multiangle and innovative polarimetric imaging capabilities will be combined with available ground monitor data and a chemical transport model to produce maps of speciated particulate matter at 1 km spatial resolution for a selected set of globally distributed cities. The MAIA investigation is also original in integrating data providers (atmospheric scientists), data users (epidemiologists), and stakeholders (public health experts) into a multidisciplinary science team that will tailor the observation and analysis strategy within each target area to improve our understanding of the linkages between different particle types and adverse human health outcomes.

  2. Asteroid Satellites

    Science.gov (United States)

    Merline, W. J.

    2001-11-01

    Discovery and study of small satellites of asteroids or double asteroids can yield valuable information about the intrinsic properties of asteroids themselves and about their history and evolution. Determination of the orbits of these moons can provide precise masses of the primaries, and hence reliable estimates of the fundamental property of bulk density. This reveals much about the composition and structure of the primary and will allow us to make comparisons between, for example, asteroid taxonomic type and our inventory of meteorites. The nature and prevalence of these systems will also give clues as to the collisional environment in which they formed, and have further implications for the role of collisions in shaping our solar system. A decade ago, binary asteroids were more of a theoretical curiosity. In 1993, the Galileo spacecraft allowed the first undeniable detection of an asteroid moon, with the discovery of Dactyl, a small moon of Ida. Since that time, and particularly in the last year, the number of known binaries has risen dramatically. Previously odd-shaped and lobate near-Earth asteroids, observed by radar, have given way to signatures indicating, almost certainly, that at least four NEAs are binary systems. The tell-tale lightcurves of several other NEAs reveal a high likelihood of being double. Indications are that among the NEAs, there may be a binary frequency of several tens of percent. Among the main-belt asteroids, we now know of 6 confirmed binary systems, although their overall frequency is likely to be low, perhaps a few percent. The detections have largely come about because of significant advances in adaptive optics systems on large telescopes, which can now reduce the blurring of the Earth's atmosphere to compete with the spatial resolution of space-based imaging (which itself, via HST, is now contributing valuable observations). Most of these binary systems have similarities, but there are important exceptions. Searches among other

  3. Long-term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America.

    Science.gov (United States)

    Baldi, Germán; Nosetto, Marcelo D; Aragón, Roxana; Aversa, Fernando; Paruelo, José M; Jobbágy, Esteban G

    2008-09-03

    In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR "Normalized Difference Vegetation Index" (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (≤11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the "Eastern Paraguay" and "Uruguay River margins" focal regions, the

  4. Detecting the influence of ocean process on the moisture supply for India summer monsoon from Satellite Sea Surface Salinity

    Science.gov (United States)

    Tang, W.; Yueh, S. H.; Liu, W. T.; Fore, A.; Hayashi, A.

    2016-02-01

    A strong contrast in the onset of Indian summer monsoon was observed by independent satellites: average rain rate over India subcontinent (IS) in June was more than doubled in 2013 than 2012 (TRMM); also observed are larger area of wet soil (Aquarius) and high water storage (GRACE). The difference in IS rainfall was contributed to the moisture inputs through west coast of India, estimated from ocean wind (OSCAT2) and water vapor (TMI). This is an interesting testbed for studying the role of ocean on terrestrial water cycle, in particular the Indian monsoon, which has tremendous social-economical impact. What is the source of extra moisture in 2013 or deficit in 2012 for the monsoon onset? Is it possible to quantify the contribution of ocean process that maybe responsible for redistributing the freshwater in favor of the summer monsoon moisture supply? This study aims to identify the influence of ocean processes on the freshwater exchange between air-sea interfaces, using Aquarius sea surface salinity (SSS). We found two areas in Indian Ocean with high correlation between IS rain rate and Aquarius SSS: one area is in the Arabian Sea adjacent to IS, another area is a horizontal patch from 60°E to 100°E centered around 10°S. On the other hand, E-P (OAflux, TRMM) shows no similar correlation patterns with IS rain. Based on the governing equation of the salt budget in the upper ocean, we define the freshwater flux, F, from the oceanic branch of the water cycle, including contributions from salinity tendency, advection, and subsurface process. The tendency and advection terms are estimated using Aquarius SSS and OSCAR ocean current. We will present results of analyzing the spatial and temporal variability of F and evidence of and hypothesis on how the oceanic processes may enhance the moisture supply for summer Indian monsoon onset in 2013 comparing with 2012. The NASA Soil Moisture Active Passive (SMAP) has been producing the global soil moisture (SM) every 2-3 days

  5. Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection

    Directory of Open Access Journals (Sweden)

    Antonino Maltese

    2013-03-01

    of operational satellite-based products for supporting agricultural practices. This study is carried out in the framework of the COSMOLAND project (Use of COSMO-SkyMed SAR data for LAND cover classification and surface parameters retrieval over agricultural sites funded by the Italian Space Agency (ASI.

  6. Satellite Communications

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'

  7. 2.5D change detection from satellite imagery to monitor small-scale mining activities in the Democratic Republic of the Congo

    Science.gov (United States)

    Kranz, Olaf; Lang, Stefan; Schoepfer, Elisabeth

    2017-09-01

    Mining natural resources serve fundamental societal needs or commercial interests, but it may well turn into a driver of violence and regional instability. In this study, very high resolution (VHR) optical stereo satellite data are analysed to monitor processes and changes in one of the largest artisanal and small-scale mining sites in the Democratic Republic of the Congo, which is among the world's wealthiest countries in exploitable minerals To identify the subtle structural changes, the applied methodological framework employs object-based change detection (OBCD) based on optical VHR data and generated digital surface models (DSM). Results prove the DSM-based change detection approach enhances the assessment gained from sole 2D analyses by providing valuable information about changes in surface structure or volume. Land cover changes as analysed by OBCD reveal an increase in bare soil area by a rate of 47% between April 2010 and September 2010, followed by a significant decrease of 47.5% until March 2015. Beyond that, DSM differencing enabled the characterisation of small-scale features such as pits and excavations. The presented Earth observation (EO)-based monitoring of mineral exploitation aims at a better understanding of the relations between resource extraction and conflict, and thus providing relevant information for potential mitigation strategies and peace building.

  8. Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-10-01

    Full Text Available Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008 vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI and the recently developed passive-microwave-based Vegetation Optical Depth (VOD. The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

  9. Updating older forest inventory data with a growth model and satellite records to improve the responsiveness and currency of national carbon monitoring

    Science.gov (United States)

    Healey, S. P.; Zhao, F. R.; McCarter, J. B.; Frescino, T.; Goeking, S.

    2017-12-01

    International reporting of American forest carbon trends depends upon the Forest Service's nationally consistent network of inventory plots. Plots are measured on a rolling basis over a 5- to 10-year cycle, so estimates related to any variable, including carbon storage, reflect conditions over a 5- to 10-year window. This makes it difficult to identify the carbon impact of discrete events (e.g., a bad fire year; extraction rates related to home-building trends), particularly if the events are recent.We report an approach to make inventory estimates more sensitive to discrete and recent events. We use a growth model (the Forest Vegetation Simulator - FVS) that is maintained by the Forest Service to annually update the tree list for every plot, allowing all plots to contribute to a series of single-year estimates. Satellite imagery from the Landsat platform guides the FVS simulations by providing information about which plots have been disturbed, which are recovering from disturbance, and which are undergoing undisturbed growth. The FVS model is only used to "update" plot tree lists until the next field measurement is made (maximum of 9 years). As a result, predicted changes are usually small and error rates are low. We present a pilot study of this system in Idaho, which has experienced several major fire events in the last decade. Empirical estimates of uncertainty, accounting for both plot sampling error and FVS model error, suggest that this approach greatly increases temporal specificity and sensitivity to discrete events without sacrificing much estimate precision at the level of a US state. This approach has the potential to take better advantage of the Forest Service's rolling plot measurement schedule to report carbon storage in the US, and it offers the basis of a system that might allow near-term, forward-looking analysis of the effects of hypothetical forest disturbance patterns.

  10. Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records.

    Science.gov (United States)

    Lee, Suehyun; Choi, Jiyeob; Kim, Hun-Sung; Kim, Grace Juyun; Lee, Kye Hwa; Park, Chan Hee; Han, Jongsoo; Yoon, Dukyong; Park, Man Young; Park, Rae Woong; Kang, Hye-Ryun; Kim, Ju Han

    2017-07-01

    We propose 2 Medical Dictionary for Regulatory Activities-enabled pharmacovigilance algorithms, MetaLAB and MetaNurse, powered by a per-year meta-analysis technique and improved subject sampling strategy. This study developed 2 novel algorithms, MetaLAB for laboratory abnormalities and MetaNurse for standard nursing statements, as significantly improved versions of our previous electronic health record (EHR)-based pharmacovigilance method, called CLEAR. Adverse drug reaction (ADR) signals from 117 laboratory abnormalities and 1357 standard nursing statements for all precautionary drugs ( n   = 101) were comprehensively detected and validated against SIDER (Side Effect Resource) by MetaLAB and MetaNurse against 11 817 and 76 457 drug-ADR pairs, respectively. We demonstrate that MetaLAB (area under the curve, AUC = 0.61 ± 0.18) outperformed CLEAR (AUC = 0.55 ± 0.06) when we applied the same 470 drug-event pairs as the gold standard, as in our previous research. Receiver operating characteristic curves for 101 precautionary terms in the Medical Dictionary for Regulatory Activities Preferred Terms were obtained for MetaLAB and MetaNurse (0.69 ± 0.11; 0.62 ± 0.07), which complemented each other in terms of ADR signal coverage. Novel ADR signals discovered by MetaLAB and MetaNurse were successfully validated against spontaneous reports in the US Food and Drug Administration Adverse Event Reporting System database. The present study demonstrates the symbiosis of laboratory test results and nursing statements for ADR signal detection in terms of their system organ class coverage and performance profiles. Systematic discovery and evaluation of the wide spectrum of ADR signals using standard-based observational electronic health record data across many institutions will affect drug development and use, as well as postmarketing surveillance and regulation. © The Author 2017. Published by Oxford University Press on behalf of the American

  11. Overview of intercalibration of satellite instruments

    Science.gov (United States)

    Chander, G.; Hewison, T.J.; Fox, N.; Wu, X.; Xiong, X.; Blackwell, W.J.

    2013-01-01

    Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms

  12. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  13. Satellite failures revisited

    Science.gov (United States)

    Balcerak, Ernie

    2012-12-01

    In January 1994, the two geostationary satellites known as Anik-E1 and Anik-E2, operated by Telesat Canada, failed one after the other within 9 hours, leaving many northern Canadian communities without television and data services. The outage, which shut down much of the country's broadcast television for hours and cost Telesat Canada more than $15 million, generated significant media attention. Lam et al. used publicly available records to revisit the event; they looked at failure details, media coverage, recovery effort, and cost. They also used satellite and ground data to determine the precise causes of those satellite failures. The researchers traced the entire space weather event from conditions on the Sun through the interplanetary medium to the particle environment in geostationary orbit.

  14. Satellite myths

    Science.gov (United States)

    Easton, Roger L.; Hall, David

    2008-01-01

    Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.

  15. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....

  16. Boomerang Satellites

    Science.gov (United States)

    Hesselbrock, Andrew; Minton, David A.

    2017-10-01

    We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.

  17. A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

    International Nuclear Information System (INIS)

    Hallum, C.

    1993-01-01

    Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

  18. Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

    Science.gov (United States)

    Karlsson, Karl-Göran; Håkansson, Nina

    2018-02-01

    The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts

  19. A satellite view of the sources and interannual variability of free tropospheric PAN over the eastern Pacific Ocean during summer and its timeline for trend detection

    Science.gov (United States)

    Zhu, L.; Fischer, E. V.; Payne, V.; Walker, T. W.; Worden, J. R.; Jiang, Z.; Kulawik, S. S.

    2016-12-01

    Peroxyacetyl nitrate (PAN) is the most important reservoir for nitrogen oxide radicals (NOx = NO + NO2) in the troposphere and plays a significant role in the redistribution of NOx to remote regions. There is strong evidence that PAN decomposition in specific plumes of Asian origin subsiding over the eastern Pacific Ocean can lead to significant ozone (O3) enhancements in the troposphere. Thus quantifying the spatial and temporal variability of PAN over the eastern Pacific Ocean is an important part of understanding the O3 budget upwind of the North American airshed. Here we present observations of PAN from the Tropospheric Emission Spectrometer (TES) over the eastern Pacific for July 2006-2010. We focus our analysis on July because prior work based on in situ observations has primarily addressed the transpacific transport of PAN in spring. Plumes containing elevated PAN are present almost every day in the month of July, and we show that elevated PAN observed in July has multiple sources, including fires in Siberia, anthropogenic and lightning sources in eastern China, and re-circulated pollution from the continental U.S. We provide examples of each type of source using both HYPLIT trajectories and a GEOS-Chem adjoint sensitivity analysis. Based on the variability observed in the TES PAN retrievals over this region, we predict it would be faster to detect a trend of a given magnitude in PAN using satellite observations over the eastern Pacific Ocean region rather than surface in situ observations at one site, and that a trend of a given magnitude would be more quickly detected in summer than spring.

  20. A Global System of in situ Sensors, Communication Satellites and in situ Actuators Dedicated to the Nearly-Real-Time Detection and Mitigation of Natural Disasters

    Science.gov (United States)

    Bevis, M.

    2009-05-01

    Most of the ~ 230,000 lives lost in the Indian Ocean Tsunami of December 2004 could have been saved if the victims had had 5 - 15 minutes notice of the tsunami's arrival, provided that the local authorities had had some evacuation plan in place, e.g. running up hill when a klaxon sounded, or retreating to low cost shelters constructed to provide a vertical escape from inundation. Similar structures, equipped with supplies of drinking water, food, blankets, etc., could save countless thousands of people from drowning in flood-prone locations such as Bangladesh or the delta region of Burma, or dying in the aftermath of such events. Given sufficiently rapid communications, a disaster nowcasting system could also order the closing of gas mains, or the powering down of electricity networks, as well as the sounding of klaxons, only tens of seconds before an earthquake wave strikes a major city such as Los Angeles. The central and critical requirement for mitigating natural disasters is two-way communication. Imagine a globally accessible internet collecting event-triggered messages from arrays of sensors (that detect inundation, for example) so they can be analyzed by centralized computer systems in nearly real-time, which then send instructions to alarm systems and actuators in the areas at risk. (Of course, local authorities would have to be involved in planning the local responses to alarms, in constructing rescue facilities, and in educating their populations accordingly). Only a constellation of satellites could provide a communications system with global accessibility and the required robustness. Such an infrastructure would allow the international community to exploit the many common elements in the detection, assessment and response to unfolding disasters. I shall describe some of the elements of such a system, for which I propose the working name CELERITY.

  1. Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

    Science.gov (United States)

    Bandibas, J. C.; Takarada, S.

    2013-12-01

    Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

  2. A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings

    International Nuclear Information System (INIS)

    Vullings, R; Bergmans, J W M; Peters, C H L; Hermans, M J M; Wijn, P F F; Oei, S G

    2010-01-01

    The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications

  3. The Skeletal Muscle Satellite Cell

    Science.gov (United States)

    2011-01-01

    The skeletal muscle satellite cell was first described and named based on its anatomic location between the myofiber plasma and basement membranes. In 1961, two independent studies by Alexander Mauro and Bernard Katz provided the first electron microscopic descriptions of satellite cells in frog and rat muscles. These cells were soon detected in other vertebrates and acquired candidacy as the source of myogenic cells needed for myofiber growth and repair throughout life. Cultures of isolated myofibers and, subsequently, transplantation of single myofibers demonstrated that satellite cells were myogenic progenitors. More recently, satellite cells were redefined as myogenic stem cells given their ability to self-renew in addition to producing differentiated progeny. Identification of distinctively expressed molecular markers, in particular Pax7, has facilitated detection of satellite cells using light microscopy. Notwithstanding the remarkable progress made since the discovery of satellite cells, researchers have looked for alternative cells with myogenic capacity that can potentially be used for whole body cell-based therapy of skeletal muscle. Yet, new studies show that inducible ablation of satellite cells in adult muscle impairs myofiber regeneration. Thus, on the 50th anniversary since its discovery, the satellite cell’s indispensable role in muscle repair has been reaffirmed. PMID:22147605

  4. Satellite Radio

    Indian Academy of Sciences (India)

    Satellites have been a highly effective platform for multi- form broadcasts. This has led to a ... diversity offormats, languages, genre, and a universal reach that cannot be met by .... programs can be delivered to whom it is intended. In the case of.

  5. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Volcanic Ash Detection and Height Environmental Data Record (EDR) from NDE

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of volcanic ash from the Visible Infrared Imaging Radiometer (VIIRS) instrument...

  6. Characterization of Location Discrepancies between Envisat/ERS Ship Detection Reports and AIS Records During MARISS Phase 2 Trials in France

    Science.gov (United States)

    Le Bras, Jean-Yves; Germain, Olivier; Hajduch, Guillaume

    2008-01-01

    During the first phase of the MARISS [1] project CLShas set-up a near real time vessel monitoring chainbased on its operational system for surveillance ofillegal fishing in the Indian Ocean and integrating the©SARTool software, developed by BOOSTT echnologies.Trials performed in the English Channel in 2006 were presented in ENVISA T Symposium 2007 showing several coupling examples between ENVISAT IS6 data and VMS systems, a comparison by the user to VTMS data, and also raising several perspectives of improvement [2]. This paper focuses on the second phase of the project.As for the first phase, ENVISAT SAR scenes (narrow swath, IS6 submode, HH polarization) were acquired, processed at Level 1b (ASA_IMP products) and provided by Kongsberg Satellite Services (KSAT), and completed by ERS PRI images acquired by ESA stations through Cat-1 mechanism, ENVISAT WS ship detection reports through ESA GSE MARCOAST, and metocean data acquired by CLS.Automatic Identification System (AIS) data were used in addition to VMS and VTMS for ground truth identification of vessels.This paper presents the main results of these trials:• An assessment of new chain capabilities implemented after the first phase, such as the azimuth ambiguity removal function in the new version of SARTool©• The use of GIS to reduce false alarms and assess image geolocation.• The potential interest of combining ERS and ENVISAT data• A characterization of differences between locations reported by satellite radar and automatic identification systems.

  7. A Geometry-Based Cycle Slip Detection and Repair Method with Time-Differenced Carrier Phase (TDCP for a Single Frequency Global Position System (GPS + BeiDou Navigation Satellite System (BDS Receiver

    Directory of Open Access Journals (Sweden)

    Chuang Qian

    2016-12-01

    Full Text Available As the field of high-precision applications based on carriers continues to expand, the development of low-cost, small, modular receivers and their application in diverse scenarios and situations with complex data quality has increased the requirements of carrier-phase data preprocessing. A new geometry-based cycle slip detection and repair method based on Global Position System (GPS + BeiDou Navigation Satellite System (BDS is proposed. The method uses a Time-differenced Carrier Phase (TDCP model, which eliminates the Inner-System Bias (ISB between GPS and BDS, and it is conducive to the effective combination of GPS and BDS. It avoids the interference of the noise of the pseudo-range with cycle slip detection, while the cycle slips are preserved as integers. This method does not limit the receiver frequency number, and it is applicable to single-frequency data. The process is divided into two steps to detect and repair cycle slip. The first step is cycle slip detection, using the Improved Local Analysis Method (ILAM to find satellites that have cycle slips; The second step is to repair the cycle slips, including estimating the float solution of changes in ambiguities at the satellites that have cycle slips with the least squares method and the integer solution of the cycle slips by rounding. In the process of rounding, in addition to the success probability, a decimal test is carried out to validate the result. Finally, experiments with filed test data are carried out to prove the effectiveness of this method. The results show that the detectable cycle slips number with GPS + BDS is much greater than that with GPS. The method can also detect the non-integer outliers while fixing the cycle slip. The maximum decimal bias in repair is less than that with GPS. It implies that this method takes full advantages of multi-system.

  8. Structure and performance of a real-time algorithm to detect tsunami or tsunami-like alert conditions based on sea-level records analysis

    Directory of Open Access Journals (Sweden)

    L. Bressan

    2011-05-01

    Full Text Available The goal of this paper is to present an original real-time algorithm devised for detection of tsunami or tsunami-like waves we call TEDA (Tsunami Early Detection Algorithm, and to introduce a methodology to evaluate its performance. TEDA works on the sea level records of a single station and implements two distinct modules running concurrently: one to assess the presence of tsunami waves ("tsunami detection" and the other to identify high-amplitude long waves ("secure detection". Both detection methods are based on continuously updated time functions depending on a number of parameters that can be varied according to the application. In order to select the most adequate parameter setting for a given station, a methodology to evaluate TEDA performance has been devised, that is based on a number of indicators and that is simple to use. In this paper an example of TEDA application is given by using data from a tide gauge located at the Adak Island in Alaska, USA, that resulted in being quite suitable since it recorded several tsunamis in the last years using the sampling rate of 1 min.

  9. Fast optical detecting media based on semiconductor nanostructures for recording images obtained using charges of free photocarriers

    International Nuclear Information System (INIS)

    Kasherininov, P. G.; Tomasov, A. A.; Beregulin, E. V.

    2011-01-01

    Available published data on the properties of optical recording media based on semiconductor structures are reviewed. The principles of operation, structure, parameters, and the range of application for optical recording media based on MIS structures formed of photorefractive crystals with a thick layer of insulator and MIS structures with a liquid crystal as the insulator (the MIS LC modulators), as well as the effect of optical bistability in semiconductor structures (semiconductor MIS structures with nanodimensionally thin insulator (TI) layer, M(TI)S nanostructures). Special attention is paid to recording media based on the M(TI)S nanostructures promising for fast processing of highly informative images and to fabrication of optoelectronic correlators of images for noncoherent light.

  10. Scientific Satellites

    Science.gov (United States)

    1967-01-01

    noise signal level exceeds 10 times the normal background. EXPERIMENTS FOR SATELLITE ASTRONOMY 615 ANTENNA MONOPOLE -., PREAMPLFE = BANDPASS-FILTER...OUTPUT TO AND DETECTOR TELEMETRYCHANNELS (18) CALIBRATION NOISE MATRIX CLOCK NOISE SOURCE ’ON’ SOURCE COMMAND F ROM PROGRAMERP ANTENNA MONOPOLE FIGURE 13...Animal Tempera- ture Sensing for Studying the Effect of Prolonged Orbital Flight on the Circadian Rhythms of Pocket Mice . Unmanned Spacecraft Meeting

  11. Is detection of adverse events affected by record review methodology? an evaluation of the "Harvard Medical Practice Study" method and the "Global Trigger Tool".

    Science.gov (United States)

    Unbeck, Maria; Schildmeijer, Kristina; Henriksson, Peter; Jürgensen, Urban; Muren, Olav; Nilsson, Lena; Pukk Härenstam, Karin

    2013-04-15

    There has been a theoretical debate as to which retrospective record review method is the most valid, reliable, cost efficient and feasible for detecting adverse events. The aim of the present study was to evaluate the feasibility and capability of two common retrospective record review methods, the "Harvard Medical Practice Study" method and the "Global Trigger Tool" in detecting adverse events in adult orthopaedic inpatients. We performed a three-stage structured retrospective record review process in a random sample of 350 orthopaedic admissions during 2009 at a Swedish university hospital. Two teams comprised each of a registered nurse and two physicians were assigned, one to each method. All records were primarily reviewed by registered nurses. Records containing a potential adverse event were forwarded to physicians for review in stage 2. Physicians made an independent review regarding, for example, healthcare causation, preventability and severity. In the third review stage all adverse events that were found with the two methods together were compared and all discrepancies after review stage 2 were analysed. Events that had not been identified by one of the methods in the first two review stages were reviewed by the respective physicians. Altogether, 160 different adverse events were identified in 105 (30.0%) of the 350 records with both methods combined. The "Harvard Medical Practice Study" method identified 155 of the 160 (96.9%, 95% CI: 92.9-99.0) adverse events in 104 (29.7%) records compared with 137 (85.6%, 95% CI: 79.2-90.7) adverse events in 98 (28.0%) records using the "Global Trigger Tool". Adverse events "causing harm without permanent disability" accounted for most of the observed difference. The overall positive predictive value for criteria and triggers using the "Harvard Medical Practice Study" method and the "Global Trigger Tool" was 40.3% and 30.4%, respectively. More adverse events were identified using the "Harvard Medical Practice Study

  12. Solar satellites

    Energy Technology Data Exchange (ETDEWEB)

    Poher, C.

    1982-01-01

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  13. Solar satellites

    Science.gov (United States)

    Poher, C.

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  14. Do asteroids have satellites

    International Nuclear Information System (INIS)

    Weidenschilling, S.J.; Paolicchi, P.; Zappala, V.

    1989-01-01

    A substantial body of indirect evidence suggests that some asteroids have satelities, although none has been detected unambiguously. Collisions between asteroids provide physically plausible mechanisms for the production of binaries, but these operate with low probability; only a small minority of asteroids are likely to have satellites. The abundance of binary asteroids can constrain the collisional history of the entire belt population. The allowed angular momentum of binaries and their rate of tidal evolution limit separations to no more than a few tens of the primary's radii. Their expected properties are consistent with failure to detect them by current imaging techniques

  15. Repeated monitoring as an effective early detection means: first records of naturalised Solidago gigantea Aiton (Asteraceae) in southern Africa

    Czech Academy of Sciences Publication Activity Database

    Kalwij, Jesse; Steyn, C.; le Roux, P. C.

    2014-01-01

    Roč. 93, Jul 2014 (2014), s. 204-206 ISSN 0254-6299 Institutional support: RVO:67985939 Keywords : Solidago * early detection * invasive species Subject RIV: EF - Botanics Impact factor: 0.978, year: 2014

  16. Using Digital Acoustic Recording Tags to Detect Marine Mammals on Navy Ranges and Study their Responses to Naval Sonar

    Science.gov (United States)

    2011-02-01

    densirostris) off the coast of El Hierro in the Canary Islands. A tag was deployed with relative ease on an adult beaked whale which proceeded to carry it for...located off-shore of El Hierro by chance. On examination, we found that water ingress had again caused failure of the recording circuit early in the

  17. The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records.

    Science.gov (United States)

    de Wet, C; Bowie, P

    2009-04-01

    A multi-method strategy has been proposed to understand and improve the safety of primary care. The trigger tool is a relatively new method that has shown promise in American and secondary healthcare settings. It involves the focused review of a random sample of patient records using a series of "triggers" that alert reviewers to potential errors and previously undetected adverse events. To develop and test a global trigger tool to detect errors and adverse events in primary-care records. Trigger tool development was informed by previous research and content validated by expert opinion. The tool was applied by trained reviewers who worked in pairs to conduct focused audits of 100 randomly selected electronic patient records in each of five urban general practices in central Scotland. Review of 500 records revealed 2251 consultations and 730 triggers. An adverse event was found in 47 records (9.4%), indicating that harm occurred at a rate of one event per 48 consultations. Of these, 27 were judged to be preventable (42%). A further 17 records (3.4%) contained evidence of a potential adverse event. Harm severity was low to moderate for most patients (82.9%). Error and harm rates were higher in those aged > or =60 years, and most were medication-related (59%). The trigger tool was successful in identifying undetected patient harm in primary-care records and may be the most reliable method for achieving this. However, the feasibility of its routine application is open to question. The tool may have greater utility as a research rather than an audit technique. Further testing in larger, representative study samples is required.

  18. Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

    Science.gov (United States)

    Li, Qi; Melton, Kristin; Lingren, Todd; Kirkendall, Eric S; Hall, Eric; Zhai, Haijun; Ni, Yizhao; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

    2014-01-01

    Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  19. The use of ion mobility spectrometry and gas chromatography/mass spectrometry for the detection of illicit drugs on clandestine records

    Science.gov (United States)

    Donnelly, Brian; Jourdan, Thomas; Fetterolf, Dean D.; Beasley, James O., II

    1995-01-01

    the records. The detection of trace drug residue on surfaces by ion mobility spectrometry (IMS) is well documented in literature. The following procedure will deal primarily with the newer techniques of trace drug analysis and drug record analysis developed by the Chemistry/Toxicology Unit of the FBI Laboratory since the more traditional techniques of latent finger print analysis and document analysis are well known.

  20. POSSIBILITIES OF TEACHERS FOR MONITORING, DETECTING AND RECORDING OF INDIVIDUAL CHARACTERISTICS OF STUDENTS IN EARLY SCHOOL AGE

    Directory of Open Access Journals (Sweden)

    Tatjana Koteva-mojsovska

    2015-06-01

    Full Text Available The monitoring and recording of the individual characteristics of children are very important for the development of quality education. Also the views of the teachers about the differences in the development, the potentials and the affinities of the children in the early school period are especially important. The quality education process in the modern school should be adapted to the individual potentials of the children. The children are individuals with their own integrity and characteristics. (Johnston and Halocha, 2010. They have individual pace and develop individual approaches in the learning process. This individual pace in the development of the children requires the teachers to regularly monitor and record the individual characteristics and differences of the children, monitoring the children’s interests, planning instruction which will adapt to the different learning approaches and the different pace of progress of the students.Setting out from this paradigm, this paper, which is based on a realized research, aims to offer findings about the treatment of the individual characteristics of the early school-age children in our country. According to this, we carried out a research in four primary schools in Skopje, which showed us that the teachers lack the appropriate conditions and possibilities to monitor and record the individual characteristics and the specific differences of the students in the early school period. 

  1. Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction.

    Science.gov (United States)

    Soylu, Abdullah Ruhi; Arpinar-Avsar, Pinar

    2010-08-01

    The effects of fatigue on maximum voluntary contraction (MVC) parameters were examined by using force and surface electromyography (sEMG) signals of the biceps brachii muscles (BBM) of 12 subjects. The purpose of the study was to find the sEMG time interval of the MVC recordings which is not affected by the muscle fatigue. At least 10s of force and sEMG signals of BBM were recorded simultaneously during MVC. The subjects reached the maximum force level within 2s by slightly increasing the force, and then contracted the BBM maximally. The time index of each sEMG and force signal were labeled with respect to the time index of the maximum force (i.e. after the time normalization, each sEMG or force signal's 0s time index corresponds to maximum force point). Then, the first 8s of sEMG and force signals were divided into 0.5s intervals. Mean force, median frequency (MF) and integrated EMG (iEMG) values were calculated for each interval. Amplitude normalization was performed by dividing the force signals to their mean values of 0s time intervals (i.e. -0.25 to 0.25s). A similar amplitude normalization procedure was repeated for the iEMG and MF signals. Statistical analysis (Friedman test with Dunn's post hoc test) was performed on the time and amplitude normalized signals (MF, iEMG). Although the ANOVA results did not give statistically significant information about the onset of the muscle fatigue, linear regression (mean force vs. time) showed a decreasing slope (Pearson-r=0.9462, pfatigue starts after the 0s time interval as the muscles cannot attain their peak force levels. This implies that the most reliable interval for MVC calculation which is not affected by the muscle fatigue is from the onset of the EMG activity to the peak force time. Mean, SD, and range of this interval (excluding 2s gradual increase time) for 12 subjects were 2353, 1258ms and 536-4186ms, respectively. Exceeding this interval introduces estimation errors in the maximum amplitude calculations

  2. Satellite line mapping in Eu3+–Ce3+ and Pr3+–Ce3+ codoped Y2SiO5

    International Nuclear Information System (INIS)

    Serrano, D.; Karlsson, J.; Zheng, L.; Dong, Y.; Ferrier, A.; Goldner, P.; Walther, A.; Rippe, L.; Kröll, S.

    2016-01-01

    In this work we perform a high-resolution spectroscopic investigation of Eu 3+ –Ce 3+ and Pr 3+ –Ce 3+ codoped Y 2 SiO 5 crystals. Satellite line spectra were recorded at low temperatures around the Eu 3+ : 7 F 0 → 5 D 0 and the Pr 3+ : 3 H 4 → 1 D 2 transitions. It is observed that the incorporation of Ce 3+ as a codopant notably changes the Eu 3+ and Pr 3+ satellite line patterns. Satellite lines measured in singly doped Eu 3+ :Y 2 SiO 5 were found at the same spectral positions in Eu 3+ –Ce 3+ codoped crystals. These coincident lines were concluded to be due to pairs of Eu 3+ ions. Extra satellite lines appeared in the codoped crystals, which were assigned to Ce 3+ related structures such as Ce 3+ –Eu 3+ pairs. The analysis of the Pr 3+ satellite line spectra presents further challenges. Satellite lines associated to Pr 3+ pairs show weaker intensity, presumably due to the efficient quenching of the Pr 3+1 D 2 emission through cross-relaxation paths ( 1 D 2 → 1 G 4 ; 3 H 4 → 3 F 4 ). The investigation of the Eu 3+ and Pr 3+ satellite line patterns in Y 2 SiO 5 is particularly interesting for their exploitation in rare-earth based quantum computation schemes. - Highlights: • We recorded Eu and Pr satellite lines in Y 2 SiO 5 with and without Ce as a codopant. • The presence of Ce leads to the appearance of extra satellite lines in the spectra. • The satellite lines are associated to minor crystal sites such as ion pairs. • Less than 100 ion pairs were detected per satellite line. • The exploitation of the satellite line structure is proposed for quantum computing.

  3. Applications for detection of acute kidney injury using electronic medical records and clinical information systems: workgroup statements from the 15(th) ADQI Consensus Conference.

    Science.gov (United States)

    James, Matthew T; Hobson, Charles E; Darmon, Michael; Mohan, Sumit; Hudson, Darren; Goldstein, Stuart L; Ronco, Claudio; Kellum, John A; Bagshaw, Sean M

    2016-01-01

    Electronic medical records and clinical information systems are increasingly used in hospitals and can be leveraged to improve recognition and care for acute kidney injury. This Acute Dialysis Quality Initiative (ADQI) workgroup was convened to develop consensus around principles for the design of automated AKI detection systems to produce real-time AKI alerts using electronic systems. AKI alerts were recognized by the workgroup as an opportunity to prompt earlier clinical evaluation, further testing and ultimately intervention, rather than as a diagnostic label. Workgroup members agreed with designing AKI alert systems to align with the existing KDIGO classification system, but recommended future work to further refine the appropriateness of AKI alerts and to link these alerts to actionable recommendations for AKI care. The consensus statements developed in this review can be used as a roadmap for development of future electronic applications for automated detection and reporting of AKI.

  4. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  5. High-resolution records detect human-caused changes to the boreal forest wildfire regime in interior Alaska

    Science.gov (United States)

    Gaglioti, Benjamin V.; Mann, Daniel H.; Jones, Benjamin M.; Wooller, Matthew J.; Finney, Bruce P.

    2016-01-01

    Stand-replacing wildfires are a keystone disturbance in the boreal forest, and they are becoming more common as the climate warms. Paleo-fire archives from the wildland–urban interface can quantify the prehistoric fire regime and assess how both human land-use and climate change impact ecosystem dynamics. Here, we use a combination of a sedimentary charcoal record preserved in varved lake sediments (annually layered) and fire scars in living trees to document changes in local fire return intervals (FRIs) and regional fire activity over the last 500 years. Ace Lake is within the boreal forest, located near the town of Fairbanks in interior Alaska, which was settled by gold miners in AD 1902. In the 400 years before settlement, fires occurred near the lake on average every 58 years. After settlement, fires became much more frequent (average every 18  years), and background charcoal flux rates rose to four times their preindustrial levels, indicating a region-wide increase in burning. Despite this surge in burning, the preindustrial boreal forest ecosystem and permafrost in the watershed have remained intact. Although fire suppression has reduced charcoal influx since the 1950s, an aging fuel load experiencing increasingly warm summers may pose management problems for this and other boreal sites that have similar land-use and fire histories. The large human-caused fire events that we identify can be used to test how increasingly common megafires may alter ecosystem dynamics in the future.

  6. Computer-Aided Detection with a Portable Electrocardiographic Recorder and Acceleration Sensors for Monitoring Obstructive Sleep Apnea

    Directory of Open Access Journals (Sweden)

    Ji-Won Baek

    2014-03-01

    Full Text Available Obstructive sleep apnea syndrome is a sleep-related breathing disorder that is caused by obstruction of the upper airway. This condition may be related with many clinical sequelae such as cardiovascular disease, high blood pressure, stroke, diabetes, and clinical depression. To diagnosis obstructive sleep apnea, in-laboratory full polysomnography is considered as a standard test to determine the severity of respiratory disturbance. However, polysomnography is expensive and complicated to perform. In this research, we explore a computer-aided diagnosis system with portable ECG equipment and tri-accelerometer (x, y, and z-axes that can automatically analyze biosignals and test for OSA. Traditional approaches to sleep apnea data analysis have been criticized; however, there are not enough suggestions to resolve the existing problems. As an effort to resolve this issue, we developed an approach to record ECG signals and abdominal movements induced by breathing by affixing ECG-enabled electrodes onto a triaxial accelerometer. With the two signals simultaneously measured, the apnea data obtained would be more accurate, relative to cases where a single signal is measured. This would be helpful in diagnosing OSA. Moreover, a useful feature point can be extracted from the two signals after applying a signal processing algorithm, and the extracted feature point can be applied in designing a computer-aided diagnosis algorithm using a machine learning technique.

  7. Water Quality Monitoring by Satellite

    Science.gov (United States)

    Journal of Chemical Education, 2004

    2004-01-01

    The availability of abundant water resources in the Upper Midwest of the United States is nullified by their contamination through heavy commercial and industrial activities. Scientists have taken the responsibility of detecting the water quality of these resources through remote-sensing satellites to develop a wide-ranging water purification plan…

  8. Joint inversion of satellite-detected tidal and magnetospheric signals constrains electrical conductivity and water content of the upper mantle and transition zone

    DEFF Research Database (Denmark)

    Grayver, Alexander V.; Munch, F. D.; Kuvshinov, Alexey V.

    2017-01-01

    and ocean tidal magnetic signals from the most recent Swarm and CHAMP data. The challenging task of properly accounting for the ocean effect in the data was addressed through full three-dimensional solution of Maxwell's equations. We show that simultaneous inversion of magnetospheric and tidal magnetic......We present a new global electrical conductivity model of Earth's mantle. The model was derived by using a novel methodology, which is based on inverting satellite magnetic field measurements from different sources simultaneously. Specifically, we estimated responses of magnetospheric origin...

  9. Pollen Bearing Honey Bee Detection in Hive Entrance Video Recorded by Remote Embedded System for Pollination Monitoring

    Science.gov (United States)

    Babic, Z.; Pilipovic, R.; Risojevic, V.; Mirjanic, G.

    2016-06-01

    Honey bees have crucial role in pollination across the world. This paper presents a simple, non-invasive, system for pollen bearing honey bee detection in surveillance video obtained at the entrance of a hive. The proposed system can be used as a part of a more complex system for tracking and counting of honey bees with remote pollination monitoring as a final goal. The proposed method is executed in real time on embedded systems co-located with a hive. Background subtraction, color segmentation and morphology methods are used for segmentation of honey bees. Classification in two classes, pollen bearing honey bees and honey bees that do not have pollen load, is performed using nearest mean classifier, with a simple descriptor consisting of color variance and eccentricity features. On in-house data set we achieved correct classification rate of 88.7% with 50 training images per class. We show that the obtained classification results are not far behind from the results of state-of-the-art image classification methods. That favors the proposed method, particularly having in mind that real time video transmission to remote high performance computing workstation is still an issue, and transfer of obtained parameters of pollination process is much easier.

  10. Landsat—Earth observation satellites

    Science.gov (United States)

    ,

    2015-11-25

    Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.

  11. Iodine Satellite

    Science.gov (United States)

    Kamhawi, Hani; Dankanich, John; Martinez, Andres; Petro, Andrew

    2015-01-01

    The Iodine Satellite (iSat) spacecraft will be the first CubeSat to demonstrate high change in velocity from a primary propulsion system by using Hall thruster technology and iodine as a propellant. The mission will demonstrate CubeSat maneuverability, including plane change, altitude change and change in its closest approach to Earth to ensure atmospheric reentry in less than 90 days. The mission is planned for launch in fall 2017. Hall thruster technology is a type of electric propulsion. Electric propulsion uses electricity, typically from solar panels, to accelerate the propellant. Electric propulsion can accelerate propellant to 10 times higher velocities than traditional chemical propulsion systems, which significantly increases fuel efficiency. To enable the success of the propulsion subsystem, iSat will also demonstrate power management and thermal control capabilities well beyond the current state-of-the-art for spacecraft of its size. This technology is a viable primary propulsion system that can be used on small satellites ranging from about 22 pounds (10 kilograms) to more than 1,000 pounds (450 kilograms). iSat's fuel efficiency is ten times greater and its propulsion per volume is 100 times greater than current cold-gas systems and three times better than the same system operating on xenon. iSat's iodine propulsion system consists of a 200 watt (W) Hall thruster, a cathode, a tank to store solid iodine, a power processing unit (PPU) and the feed system to supply the iodine. This propulsion system is based on a 200 W Hall thruster developed by Busek Co. Inc., which was previously flown using xenon as the propellant. Several improvements have been made to the original system to include a compact PPU, targeting greater than 80 percent reduction in mass and volume of conventional PPU designs. The cathode technology is planned to enable heaterless cathode conditioning, significantly increasing total system efficiency. The feed system has been designed to

  12. Analysis of Satellite and Airborne Imagery for Detection of Water Hyacinth and Other Invasive Floating Macrophytes and Tracking of Aquatic Weed Control Efficacy

    Science.gov (United States)

    Potter, Christopher

    2016-01-01

    Waterways of the Sacramento San Joaquin Delta have recently become infested with invasive aquatic weeds such as floating water hyacinth (Eichhoria crassipes) and water primrose (Ludwigia peploides). These invasive plants cause many negative impacts, including, but not limited to: the blocking of waterways for commercial shipping and boating; clogging of irrigation screens, pumps and canals; and degradation of biological habitat through shading. Zhang et al. (1997, Ecological Applications, 7(3), 1039-1053) used NASA Landsat satellite imagery together with field calibration measurements to map physical and biological processes within marshlands of the San Francisco Bay. Live green biomass (LGB) and related variables were correlated with a simple vegetation index ratio of red and near infra-red bands from Landsat images. More recently, the percent (water area) cover of water hyacinth plotted against estimated LGB of emergent aquatic vegetation in the Delta from September 2014 Landsat imagery showed an 80 percent overall accuracy. For the past two years, we have partnered with the U. S. Department of Agriculture (USDA) and the Department of Plant Sciences, University of California at Davis to conduct new validation surveys of water hyacinth and water primrose coverage and LGB in Delta waterways. A plan is underway to transfer decision support tools developed at NASA's Ames Research Center based on Landsat satellite images to improve Delta-wide integrated management of floating aquatic weeds, while reducing chemical control costs. The main end-user for this application project will be the Division of Boating and Waterways (DBW) of the California Department of Parks and Recreation, who has the responsibility for chemical control of water hyacinth in the Delta.

  13. Trends in communications satellites

    CERN Document Server

    Curtin, Denis J

    1979-01-01

    Trends in Communications Satellites offers a comprehensive look at trends and advances in satellite communications, including experimental ones such as NASA satellites and those jointly developed by France and Germany. The economic aspects of communications satellites are also examined. This book consists of 16 chapters and begins with a discussion on the fundamentals of electrical communications and their application to space communications, including spacecraft, earth stations, and orbit and wavelength utilization. The next section demonstrates how successful commercial satellite communicati

  14. Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records.

    Science.gov (United States)

    Sylvestre, Emmanuelle; Bouzillé, Guillaume; Chazard, Emmanuel; His-Mahier, Cécil; Riou, Christine; Cuggia, Marc

    2018-01-24

    Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database. We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication. Then, we compared the drug indications in the Theriaque database with the ICD-10 billing codes in EHR to detect potentially missing comorbidities based on drug prescriptions. Finally, we improved comorbidity detection by matching drug prescriptions and laboratory test results. We tested the obtained algorithm by using two retrospective datasets extracted from the Rennes University Hospital (RUH) CDW. The first dataset included all adult patients hospitalized in the ear, nose, throat (ENT) surgical ward between October and December 2014 (ENT dataset). The second included all adult patients hospitalized at RUH between January and February 2015 (general dataset). We reviewed medical records to find written evidence of the suggested comorbidities in current or past stays. Among the 22,132 Common Units of Dispensation (CUD) codes present in the Theriaque database, 19,970 drugs (90.2%) were associated with one or several ICD-10 diagnoses, based on their indication, and 11,162 (50.4%) with at least one of the 4878 comorbidities from the comorbidity list. Among the 122 patients of the ENT dataset, 75.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 44.6% of the cases. Among the 4312 patients of the general dataset, 68.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the

  15. Laser color recording unit

    Science.gov (United States)

    Jung, E.

    1984-05-01

    A color recording unit was designed for output and control of digitized picture data within computer controlled reproduction and picture processing systems. In order to get a color proof picture of high quality similar to a color print, together with reduced time and material consumption, a photographic color film material was exposed pixelwise by modulated laser beams of three wavelengths for red, green and blue light. Components of different manufacturers for lasers, acousto-optic modulators and polygon mirrors were tested, also different recording methods as (continuous tone mode or screened mode and with a drum or flatbed recording principle). Besides the application for the graphic arts - the proof recorder CPR 403 with continuous tone color recording with a drum scanner - such a color hardcopy peripheral unit with large picture formats and high resolution can be used in medicine, communication, and satellite picture processing.

  16. Using exceedance probabilities to detect anomalies in routinely recorded animal health data, with particular reference to foot-and-mouth disease in Viet Nam.

    Science.gov (United States)

    Richards, K K; Hazelton, M L; Stevenson, M A; Lockhart, C Y; Pinto, J; Nguyen, L

    2014-10-01

    The widespread availability of computer hardware and software for recording and storing disease event information means that, in theory, we have the necessary information to carry out detailed analyses of factors influencing the spatial distribution of disease in animal populations. However, the reliability of such analyses depends on data quality, with anomalous records having the potential to introduce significant bias and lead to inappropriate decision making. In this paper we promote the use of exceedance probabilities as a tool for detecting anomalies when applying hierarchical spatio-temporal models to animal health data. We illustrate this methodology through a case study data on outbreaks of foot-and-mouth disease (FMD) in Viet Nam for the period 2006-2008. A flexible binomial logistic regression was employed to model the number of FMD infected communes within each province of the country. Standard analyses of the residuals from this model failed to identify problems, but exceedance probabilities identified provinces in which the number of reported FMD outbreaks was unexpectedly low. This finding is interesting given that these provinces are on major cattle movement pathways through Viet Nam. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Development of Next Generation Memory Test Experiment for Deployment on a Small Satellite

    Science.gov (United States)

    MacLeod, Todd; Ho, Fat D.

    2012-01-01

    The original Memory Test Experiment successfully flew on the FASTSAT satellite launched in November 2010. It contained a single Ramtron 512K ferroelectric memory. The memory device went through many thousands of read/write cycles and recorded any errors that were encountered. The original mission length was schedule to last 6 months but was extended to 18 months. New opportunities exist to launch a similar satellite and considerations for a new memory test experiment should be examined. The original experiment had to be designed and integrated in less than two months, so the experiment was a simple design using readily available parts. The follow-on experiment needs to be more sophisticated and encompass more technologies. This paper lays out the considerations for the design and development of this follow-on flight memory experiment. It also details the results from the original Memory Test Experiment that flew on board FASTSAT. Some of the design considerations for the new experiment include the number and type of memory devices to be used, the kinds of tests that will be performed, other data needed to analyze the results, and best use of limited resources on a small satellite. The memory technologies that are considered are FRAM, FLASH, SONOS, Resistive Memory, Phase Change Memory, Nano-wire Memory, Magneto-resistive Memory, Standard DRAM, and Standard SRAM. The kinds of tests that could be performed are read/write operations, non-volatile memory retention, write cycle endurance, power measurements, and testing Error Detection and Correction schemes. Other data that may help analyze the results are GPS location of recorded errors, time stamp of all data recorded, radiation measurements, temperature, and other activities being perform by the satellite. The resources of power, volume, mass, temperature, processing power, and telemetry bandwidth are extremely limited on a small satellite. Design considerations must be made to allow the experiment to not interfere

  18. Satellite and ground detection of very dense smoke clouds produced on the islands of the Paraná river delta that affected a large region in Central Argentina

    Science.gov (United States)

    Ipiña, A.; Salum, G. M.; Crinó, E.; Piacentini, R. D.

    2012-03-01

    Intense fires were produced on the Paraná river delta islands, Argentina, during most part of 2008, by a combination of an exceptionally dry period and the farmers' use of a fire land-cleaning technique. In April 2008, those fires significantly affected the nearby regions and their inhabitants, from Rosario city to Buenos Aires mega-city. In this work we present satellite as well as ground Aerosol Optical Depth (AOD) at 550 nm data obtained during the propagation of pollution clouds to the central zone of Argentina. The highest value (1.18) was registered at Buenos Aires by atmospheric remote sensing, using the satellite instrument MODIS/Terra on April 18th 2008 at 10:35 local time (= UT - 3 h). On the same day, ground air quality detectors also measured in this city the highest Total Suspended Particle (TSP) value of the month, 2.02 mg/m3. The AOD(550) daily variation at Rosario Astronomical Observatory, which is located near the Paraná riverside, was derived by combining solar ultraviolet erythemal irradiance data (measured with a YES biometre) with model calculations. On April 25th 2008, from 12:00 to 15:30 local time, a rather high and constant AOD(550) value was registered, with a mean value of (0.90 ± 0.21). Cities located on the side of the Rosario-Buenos Aires highway (San Nicolás, Baradero and San Pedro) were also affected, showing a mean AOD(550) between the Rosario and Buenos Aires values. The particulate matter was collected with gridded samplers placed on the Paraná river islands as well as at the Rosario Observatory. They were analysed with a Scanning Electron Microscope (SEM) and mainly showed a biological origin. Even if normally large particles travel small distances from the source, organic aerosol in the range of 40-100 μm and complex asymmetric structures were registered several kilometres away from the aerosol sources on the islands. Another event of intense UV index attenuation (98.6%) occurred on September 18th 2008, due to very dense

  19. Detecting ecosystem performance anomalies for land management in the upper colorado river basin using satellite observations, climate data, and ecosystem models

    Science.gov (United States)

    Gu, Yingxin; Wylie, B.K.

    2010-01-01

    This study identifies areas with ecosystem performance anomalies (EPA) within the Upper Colorado River Basin (UCRB) during 2005-2007 using satellite observations, climate data, and ecosystem models. The final EPA maps with 250-m spatial resolution were categorized as normal performance, underperformance, and overperformance (observed performance relative to weather-based predictions) at the 90% level of confidence. The EPA maps were validated using "percentage of bare soil" ground observations. The validation results at locations with comparable site potential showed that regions identified as persistently underperforming (overperforming) tended to have a higher (lower) percentage of bare soil, suggesting that our preliminary EPA maps are reliable and agree with ground-based observations. The 3-year (2005-2007) persistent EPA map from this study provides the first quantitative evaluation of ecosystem performance anomalies within the UCRB and will help the Bureau of Land Management (BLM) identify potentially degraded lands. Results from this study can be used as a prototype by BLM and other land managers for making optimal land management decisions. ?? 2010 by the authors.

  20. Satellite image collection optimization

    Science.gov (United States)

    Martin, William

    2002-09-01

    Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

  1. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2017-01-01

    The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.

  2. Non-Stationary Internal Tides Observed with Satellite Altimetry

    Science.gov (United States)

    Ray, Richard D.; Zaron, E. D.

    2011-01-01

    Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

  3. Satellite Control Laboratory

    DEFF Research Database (Denmark)

    Wisniewski, Rafal; Bak, Thomas

    2001-01-01

    The Satellite Laboratory at the Department of Control Engineering of Aalborg University (SatLab) is a dynamic motion facility designed for analysis and test of micro spacecraft. A unique feature of the laboratory is that it provides a completely gravity-free environment. A test spacecraft...... of the laboratory is to conduct dynamic tests of the control and attitude determination algorithms during nominal operation and in abnormal conditions. Further it is intended to use SatLab for validation of various algorithms for fault detection, accommodation and supervisory control. Different mission objectives...... can be implemented in the laboratory, e.g. three-axis attitude control, slew manoeuvres, spins stabilization using magnetic actuation and/or reaction wheels. The spacecraft attitude can be determined applying magnetometer measurements...

  4. Persistent pre-seismic signature detected by means of Na-K-Mg geothermometry records in a saline spring of Vrancea area (Romania

    Directory of Open Access Journals (Sweden)

    H. Mitrofan

    2010-02-01

    Full Text Available A six year-long hydrochemical monitoring operation was conducted in Vrancea seismic zone (Romania, addressing a saline spring that proved to be suitable for Na-K-Mg geothermometry diagnosis. During the considered time-interval (2003–2009, only one important earthquake (mb=5.8 occurred in Vrancea region, this circumstance providing an unambiguous reference-moment between pre-seismic and post-seismic periods. On occurrence of that earthquake, an anomalous fluctuation of the Na-K temperature was detected – a result largely similar to previous ones recorded worldwide (California, southwest Egypt, northeast India. Yet such fluctuations may not necessarily be induced by earthquake-associated processes: they can occur also "routinely", possibly reflecting some environmental, meteorologically-induced "noise". It was therefore important to examine whether the variations observed in the data values could be plausibly related to a seismogenesis process. By additionally investigating (in a "scattterplot" diagram the correlation between the Na-K temperatures and the values of a so-called "maturity index", a specific pattern emerged, with pre-seismic data-points plotting in a distinct domain of the diagram; moreover, those data-points appeared to describe a "drift away" pathway with respect to the remaining data-points "cluster", recorded during the subsequent 4 years of post-seismic monitoring. The "drift away" pattern persistently evolved for at least 18 months, ending just before the mb=5.8 earthquake and consequently suggesting the existence of some kind of long-term precursory phenomenon.

  5. GPS Satellite Simulation Facility

    Data.gov (United States)

    Federal Laboratory Consortium — The GPS satellite simulation facility consists of a GPS satellite simulator controlled by either a Silicon Graphics Origin 2000 or PC depending upon unit under test...

  6. A new approach for the detection of charged particles by photographic recording systems - first applications in corpuscular physics, biology and electron microscopy

    International Nuclear Information System (INIS)

    Rechenmann, R.V.; Wittendorp, E.; Senger, B.

    1977-01-01

    The activation procedure consists not only of the introduction of more or less sophisticated treatments in the development phase, but also of the setting up of a specific ionographic methodology which will be described. The working hypotheses which led to the formulation of the so-called activation treatments will be outlined, notably the concept of the stable sub-latent image. The consequences of the activation procedure in ionography will be recalled, e.g. the drastic increase of the signal/noise ratio ranging from 1.5 to 20 and more, as well as the remarkable stability of the fog. The interest of the activation procedure for corpuscular physics as well as for the life sciences will be illustrated by first applications in autoradiography, electron microscopy and microdosimetry. As far as the autoradiographic methods are concerned, the considerable increase in efficiency and in resolution results in a drastic decrease of the exposure time or/and of the quantity of tracer elements applied, as well as in the possibility to carry out studies implying the detection of very small amounts of activity. The activation of the latent image can also be applied to exposed electron microscope photographic plates in order to allow a non-destructive observation of very sensitive specimens (macromolecules, etc.). In the field of corpuscular physics, the activation treatments led to the detection of secondary events distributed along α tracks of medium and low energy recorded in nuclear emulsions. An analytical study confirmed the hypotheses that the largest part of these protuberances are tracks of electrons and H-nuclei ejected by the incoming particle. These investigations are intended to lead to a description of the ionizing track pattern as well as to the interpretation of experimentally determined fluctuations of the track width. (author)

  7. Pulse oximetry recorded from the Phone Oximeter for detection of obstructive sleep apnea events with and without oxygen desaturation in children.

    Science.gov (United States)

    Garde, Ainara; Dehkordi, Parastoo; Wensley, David; Ansermino, J Mark; Dumont, Guy A

    2015-01-01

    Obstructive sleep apnea (OSA) disrupts normal ventilation during sleep and can lead to serious health problems in children if left untreated. Polysomnography, the gold standard for OSA diagnosis, is resource intensive and requires a specialized laboratory. Thus, we proposed to use the Phone Oximeter™, a portable device integrating pulse oximetry with a smartphone, to detect OSA events. As a proportion of OSA events occur without oxygen desaturation (defined as SpO2 decreases ≥ 3%), we suggest combining SpO2 and pulse rate variability (PRV) analysis to identify all OSA events and provide a more detailed sleep analysis. We recruited 160 children and recorded pulse oximetry consisting of SpO2 and plethysmography (PPG) using the Phone Oximeter™, alongside standard polysomnography. A sleep technician visually scored all OSA events with and without oxygen desaturation from polysomnography. We divided pulse oximetry signals into 1-min signal segments and extracted several features from SpO2 and PPG analysis in the time and frequency domain. Segments with OSA, especially the ones with oxygen desaturation, presented greater SpO2 variability and modulation reflected in the spectral domain than segments without OSA. Segments with OSA also showed higher heart rate and sympathetic activity through the PRV analysis relative to segments without OSA. PRV analysis was more sensitive than SpO2 analysis for identification of OSA events without oxygen desaturation. Combining SpO2 and PRV analysis enhanced OSA event detection through a multiple logistic regression model. The area under the ROC curve increased from 81% to 87%. Thus, the Phone Oximeter™ might be useful to monitor sleep and identify OSA events with and without oxygen desaturation at home.

  8. Spatial and energy distributions of satellite-speed helium atoms reflected from satellite-type surfaces

    International Nuclear Information System (INIS)

    Liu, S.M.; Rodgers, W.E.; Knuth, E.L.

    1977-01-01

    Interactions of satellite-speed helium atoms (accelerated in an expansion from an arc-heated supersonic-molecular-beam source) with practical satellite surfaces have been investigated experimentally. The density and energy distributions of the scattered atoms were measured using a detection system developed for this study. This detection system includes (a) a target positioning mechanism, (b) a detector rotating mechanism, and (c) a mass spectrometer and/or a retarding-field energy analyzer. (Auth.)

  9. Meteorological satellite systems

    CERN Document Server

    Tan, Su-Yin

    2014-01-01

    “Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.

  10. Theory of geostationary satellites

    CERN Document Server

    Zee, Chong-Hung

    1989-01-01

    Geostationary or equatorial synchronous satellites are a daily reminder of our space efforts during the past two decades. The nightly television satellite weather picture, the intercontinental telecommunications of television transmissions and telephone conversations, and the establishrnent of educational programs in remote regions on Earth are constant reminders of the presence of these satellites. As used here, the term 'geo­ stationary' must be taken loosely because, in the long run, the satellites will not remain 'stationary' with respect to an Earth-fixed reference frame. This results from the fact that these satellites, as is true for all satellites, are incessantly subject to perturbations other than the central-body attraction of the Earth. Among the more predominant pertur­ bations are: the ellipticity of the Earth's equator, the Sun and Moon, and solar radiation pressure. Higher harmonics of the Earth's potential and tidal effects also influence satellite motion, but they are of second­ order whe...

  11. Homogeneity of a Global Multisatellite Soil Moisture Climate Data Record

    Science.gov (United States)

    Su, Chun-Hsu; Ryu, Dongryeol; Dorigo, Wouter; Zwieback, Simon; Gruber, Alexander; Albergel, Clement; Reichle, Rolf H.; Wagner, Wolfgang

    2016-01-01

    Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.

  12. Protected transitional solution to transformational satellite communications

    Science.gov (United States)

    Brand, Jerry C.

    2005-06-01

    As the Warfighter progresses into the next generation battlefield, transformational communications become evident as an enabling technology. Satellite communications become even more vital as the battles range over greater non-contiguous spaces. While current satellite communications provide suitable beyond line-of-sight communications and the Transformational Communications Architecture (TCA) sets the stage for sound information exchange, a realizable transition must occur to ensure successful succession to this higher level. This paper addresses the need for a planned escalation to the next generation satellite communications architecture and offers near-term alternatives. Commercial satellite systems continue to enable the Warfighter to reach back to needed information resources, providing a large majority of available bandwidth. Four areas of concentration for transition include encrypted Telemetry, Tracking and Control (or Command) (TT&C), encrypted and covered data, satellite attack detection and protection, and operational mobility. Solution methodologies include directly embedding COMSEC devices in the satellites and terminals, and supplementing existing terminals with suitable equipment and software. Future satellites planned for near-term launches can be adapted to include commercial grade and higher-level secure equipment. Alternately, the expected use of programmable modems (Software Defined Radios (SDR)) enables incorporation of powerful cipher methods approaching military standards as well as waveforms suitable for on-the-move operation. Minimal equipment and software additions on the satellites can provide reasonable attack detection and protection methods in concert with the planned satellite usage. Network management suite modifications enable cohesive incorporation of these protection schemes. Such transitional ideas offer a smooth and planned transition as the TCA takes life.

  13. Satellite SAR imagery for site discovery, change detection and monitoring activities in cultural heritage sites: experiments on the Nasca region, Peru

    Science.gov (United States)

    Tapete, D.; Cigna, F.; Masini, N.; Lasaponara, R.

    2012-04-01

    Besides their suitability for multi-temporal and spatial deformation analysis, the Synthetic Aperture Radar (SAR) image archives acquired by space-borne radar sensors can be exploited to support archaeological investigations over huge sites, even those partially or totally buried and still to be excavated. Amplitude information is one of the main properties of SAR data from which it is possible to retrieve evidences of buried structures, using feature extraction and texture analysis. Multi-temporality allows the reconstruction of past and recent evolution of both landscape and built-up environment, with the possibility to detect natural and/or anthropogenic changes, including human-induced damages to the conservation of cultural heritage. We present the methodology and first results of the experiments currently undertaken using SAR data in the Nasca region (Southern Peru), where two important civilizations such as Paracas and Nasca developed and flourished from 4th century BC to the 6th century AD. The study areas include a wide spectrum of archaeological and environmental elements to be preserved, among which: the archaeological site of Cahuachi and its surroundings, considered the largest adobe Ceremonial Centre in the World; the Nasca lines and geoglyphs in the areas of Palpa, Atarco and Nasca; the ancient networks of aqueducts and drainage galleries in the Puquios area, built by Nasca in the 1st-6th centuries AD. Archaeological prospection and multi-purpose remote sensing activities are currently carried out in the framework of the Italian mission of heritage Conservation and Archaeogeophysics (ITACA), with the direct involvement of researchers from the Institute for Archaeological and Monumental Heritage and the Institute of Methodologies for Environmental Analysis, Italian National Research Council. In this context, C- and L-band SAR images covering the Nasca region since 2001 were identified for the purposes of this research and, in particular, the following

  14. MASSIVE SATELLITES OF CLOSE-IN GAS GIANT EXOPLANETS

    International Nuclear Information System (INIS)

    Cassidy, Timothy A.; Johnson, Robert E.; Mendez, Rolando; Arras, Phil; Skrutskie, Michael F.

    2009-01-01

    We study the orbits, tidal heating and mass loss from satellites around close-in gas giant exoplanets. The focus is on large satellites which are potentially observable by their transit signature. We argue that even Earth-size satellites around hot Jupiters can be immune to destruction by orbital decay; detection of such a massive satellite would strongly constrain theories of tidal dissipation in gas giants, in a manner complementary to orbital circularization. The star's gravity induces significant periodic eccentricity in the satellite's orbit. The resulting tidal heating rates, per unit mass, are far in excess of Io's and dominate radioactive heating out to planet orbital periods of months for reasonable satellite tidal Q. Inside planet orbital periods of about a week, tidal heating can completely melt the satellite. Lastly, we compute an upper limit to the satellite mass loss rate due to thermal evaporation from the surface, valid if the satellite's atmosphere is thin and vapor pressure is negligible. Using this upper limit, we find that although rocky satellites around hot Jupiters with orbital periods less than a few days can be significantly evaporated in their lifetimes, detectable satellites suffer negligible mass loss at longer orbital periods.

  15. Dissemination of satellite-based river discharge and flood data

    Science.gov (United States)

    Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

    2014-12-01

    In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

  16. Hospital staff should use more than one method to detect adverse events and potential adverse events: incident reporting, pharmacist surveillance and local real‐time record review may all have a place

    Science.gov (United States)

    Olsen, Sisse; Neale, Graham; Schwab, Kat; Psaila, Beth; Patel, Tejal; Chapman, E Jane; Vincent, Charles

    2007-01-01

    Background Over the past five years, in most hospitals in England and Wales, incident reporting has become well established but it remains unclear how well reports match clinical adverse events. International epidemiological studies of adverse events are based on retrospective, multi‐hospital case record review. In this paper the authors describe the use of incident reporting, pharmacist surveillance and local real‐time record review for the recognition of clinical risks associated with hospital inpatient care. Methodology Data on adverse events were collected prospectively on 288 patients discharged from adult acute medical and surgical units in an NHS district general hospital using incident reports, active surveillance of prescription charts by pharmacists and record review at time of discharge. Results Record review detected 26 adverse events (AEs) and 40 potential adverse events (PAEs) occurring during the index admission. In contrast, in the same patient group, incident reporting detected 11 PAEs and no AEs. Pharmacy surveillance found 10 medication errors all of which were PAEs. There was little overlap in the nature of events detected by the three methods. Conclusion The findings suggest that incident reporting does not provide an adequate assessment of clinical adverse events and that this method needs to be supplemented with other more systematic forms of data collection. Structured record review, carried out by clinicians, provides an important component of an integrated approach to identifying risk in the context of developing a safety and quality improvement programme. PMID:17301203

  17. Communication satellite applications

    Science.gov (United States)

    Pelton, Joseph N.

    The status and future of the technologies, numbers and services provided by communications satellites worldwide are explored. The evolution of Intelsat satellites and the associated earth terminals toward high-rate all-digital telephony, data, facsimile, videophone, videoconferencing and DBS capabilities are described. The capabilities, services and usage of the Intersputnik, Eutelsat, Arabsat and Palapa systems are also outlined. Domestic satellite communications by means of the Molniya, ANIK, Olympus, Intelsat and Palapa spacecraft are outlined, noting the fast growth of the market and the growing number of different satellite manufacturers. The technical, economic and service definition issues surrounding DBS systems are discussed, along with presently operating and planned maritime and aeronautical communications and positioning systems. Features of search and rescue and tracking, data, and relay satellite systems are summarized, and services offered or which will be offered by every existing or planned communication satellite worldwide are tabulated.

  18. Satellite services system overview

    Science.gov (United States)

    Rysavy, G.

    1982-01-01

    The benefits of a satellite services system and the basic needs of the Space Transportation System to have improved satellite service capability are identified. Specific required servicing equipment are discussed in terms of their technology development status and their operative functions. Concepts include maneuverable television systems, extravehicular maneuvering unit, orbiter exterior lighting, satellite holding and positioning aid, fluid transfer equipment, end effectors for the remote manipulator system, teleoperator maneuvering system, and hand and power tools.

  19. Towards an integrated strategy for monitoring wetland inundation with virtual constellations of optical and radar satellites

    Science.gov (United States)

    DeVries, B.; Huang, W.; Huang, C.; Jones, J. W.; Lang, M. W.; Creed, I. F.; Carroll, M.

    2017-12-01

    The function of wetlandscapes in hydrological and biogeochemical cycles is largely governed by surface inundation, with small wetlands that experience periodic inundation playing a disproportionately large role in these processes. However, the spatial distribution and temporal dynamics of inundation in these wetland systems are still poorly understood, resulting in large uncertainties in global water, carbon and greenhouse gas budgets. Satellite imagery provides synoptic and repeat views of the Earth's surface and presents opportunities to fill this knowledge gap. Despite the proliferation of Earth Observation satellite missions in the past decade, no single satellite sensor can simultaneously provide the spatial and temporal detail needed to adequately characterize inundation in small, dynamic wetland systems. Surface water data products must therefore integrate observations from multiple satellite sensors in order to address this objective, requiring the development of improved and coordinated algorithms to generate consistent estimates of surface inundation. We present a suite of algorithms designed to detect surface inundation in wetlands using data from a virtual constellation of optical and radar sensors comprising the Landsat and Sentinel missions (DeVries et al., 2017). Both optical and radar algorithms were able to detect inundation in wetlands without the need for external training data, allowing for high-efficiency monitoring of wetland inundation at large spatial and temporal scales. Applying these algorithms across a gradient of wetlands in North America, preliminary findings suggest that while these fully automated algorithms can detect wetland inundation at higher spatial and temporal resolutions than currently available surface water data products, limitations specific to the satellite sensors and their acquisition strategies are responsible for uncertainties in inundation estimates. Further research is needed to investigate strategies for

  20. Challenges of coordinating global climate observations - Role of satellites in climate monitoring

    Science.gov (United States)

    Richter, C.

    2017-12-01

    Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

  1. Isolation, Culture, Functional Assays, and Immunofluorescence of Myofiber-Associated Satellite Cells.

    Science.gov (United States)

    Vogler, Thomas O; Gadek, Katherine E; Cadwallader, Adam B; Elston, Tiffany L; Olwin, Bradley B

    2016-01-01

    Adult skeletal muscle stem cells, termed satellite cells, regenerate and repair the functional contractile cells in adult skeletal muscle called myofibers. Satellite cells reside in a niche between the basal lamina and sarcolemma of myofibers. Isolating single myofibers and their associated satellite cells provides a culture system that partially mimics the in vivo environment. We describe methods for isolating and culturing intact individual myofibers and their associated satellite cells from the mouse extensor digitorum longus muscle. Following dissection and isolation of individual myofibers we provide protocols for myofiber transplantation, satellite cell transfection, immune detection of satellite cell antigens, and assays to examine satellite cell self-renewal and proliferation.

  2. Satellite Remote Sensing in Seismology. A Review

    Directory of Open Access Journals (Sweden)

    Andrew A. Tronin

    2009-12-01

    Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

  3. Satellite Communications Industry

    Science.gov (United States)

    1993-04-01

    Ariane $loom SAJAC 1 Hughes Satellite Japan 06/94 $150m SAJAC 2 Hughes Satellite Japan -- (spare) $150m SatcomHl GE GE Americom /95 $50m SOLIDARIDAD ...1 Hughes SCT (Mexico) 11/93 Ariane $loom SOLIDARIDAD 2 Hughes SCT (Mexico) /94 $loom Superbird Al Loral Space Com Gp (Jap) 11/92 Ariane $175m

  4. Partnership via Satellite.

    Science.gov (United States)

    Powell, Marie Clare

    1980-01-01

    Segments of the 1980 National Catholic Educational Association (NCEA) conference were to be telecast nationally by satellite. The author briefly explains the satellite transmission process and advises Catholic educators on how to pick up the broadcast through their local cable television system. (SJL)

  5. Plasma waves and electric discharges induced by a beam from a high-latitude satellite

    International Nuclear Information System (INIS)

    Kuns, G.; Koen, G.

    1985-01-01

    Using P78-2 satellite measurements of characteristics of space probe charging in synchronous orbit are carried out. A particle beam generation system including electron and ion guns was part of the satellite equipment. Electric charge analyser placed aboard the satellite in course of electron and ion beam generation recorded plasma waves and electric discharges

  6. The satellite situation center

    International Nuclear Information System (INIS)

    Teague, M.J.; Sawyer, D.M.; Vette, J.I.

    1982-01-01

    Considerations related to the early planning for the International Magnetospheric Study (IMS) took into account the desirability of an establishment of specific entities for generating and disseminating coordination information for both retrospective and predictive periods. The organizations established include the IMS/Satellite Situation Center (IMS/SSC) operated by NASA. The activities of the SSC are related to the preparation of reports on predicted and actually achieved satellite positions, the response to inquiries, the compilation of information on satellite experiments, and the issue of periodic status summaries. Attention is given to high-altitude satellite services, other correlative satellite services, non-IMS activities of the SSC, a summary of the SSC request activity, and post-IMS and future activities

  7. Development of Discrimination, Detection, and Location Capabilities in Central and Southern Asia Using Middle-Period Surface Waves Recorded by a Regional Array

    National Research Council Canada - National Science Library

    Levshin, Anatoli

    1997-01-01

    .... We present group velocity maps from 10 s to 40 s period for both Rayleigh and Love waves. Broadband waveform data from about 600 events from 1988 - 1995 recorded at 83 individual stations from several global and regional networks...

  8. Combining airborne and satellite remote sensing programs to repress illegal oil discharges in restricted sea areas

    International Nuclear Information System (INIS)

    Price, M.

    2005-01-01

    An airborne surveillance program has been conducted over the Belgian part of the North Sea since 1991. The role of the program is to detect infringements on the Marpol Convention via remote sensing, and to take legal action against polluters through the use of recorded observations. Although Belgium has a restricted sea area of about 3,500 km with no fixed offshore oil installations, a pollution risk is constantly present due to 2 dense traffic separation schemes close to the shoreline. The Belgian marine areas and adjacent waters are regularly scanned with a Side Looking Airborne Radar (SLAR) on board a remote sensing aircraft. This paper describes an evaluation trial that the Belgian Management Unit of the North Sea Mathematical Models (MUMM) joined in 2004, together with various agencies from the United Kingdom, Germany and the Netherlands. The trial consists of a cost-sharing satellite service for oil detection with ENVISAT ASAR data. The trial was co-funded by the European Space Agency (ESA) and run by Kongsberg Satellite Services. MUMM's objective was to evaluate the effectiveness and operational character of satellite services for detecting oil spills at sea. The results of the 3 month trial have indicated that aerial remote sensing for the detection of illegal oil discharges at sea increases the chances of catching polluters more efficiently, with improved chances of evidence collecting. It was concluded that when various services are integrated and strict operational conditions are met, satellite services may prove to be valuable in restricted, very densely navigated national waters that are easily reached by airborne means. 12 refs., 8 tabs., 3 figs

  9. Probability of satellite collision

    Science.gov (United States)

    Mccarter, J. W.

    1972-01-01

    A method is presented for computing the probability of a collision between a particular artificial earth satellite and any one of the total population of earth satellites. The collision hazard incurred by the proposed modular Space Station is assessed using the technique presented. The results of a parametric study to determine what type of satellite orbits produce the greatest contribution to the total collision probability are presented. Collision probability for the Space Station is given as a function of Space Station altitude and inclination. Collision probability was also parameterized over miss distance and mission duration.

  10. Observation of GEO Satellite Above Thailand’s Sky

    Science.gov (United States)

    Kasonsuwan, K.; Wannawichian, S.; Kirdkao, T.

    2017-09-01

    The direct observations of Geostationary Orbit (GEO) satellites above Thailand’s sky by 0.7-meters telescope were proceeded at Inthanon Mt., Chiang Mai, Thailand. The observation took place at night with Sidereal Stare Mode (SSM). With this observing mode, the moving object will appear as a streak. The star identification for image calibration is based on (1) a star catalogue, (2) the streak detection of the satellite using the software and (3) the extraction of the celestial coordinate of the satellite as a predicted position. Finally, the orbital elements for GEO satellites were calculated.

  11. On the reliable use of satellite-derived surface water products for global flood monitoring

    Science.gov (United States)

    Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

    2015-12-01

    Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

  12. UV Spectrophotometry of the Galilean Satellites, Saturnian Satellites & Selected Asteroids

    Science.gov (United States)

    Nelson, Robert M.

    leading face of Iapetus has not been well characterized because the time period where optimum detection of the dark material occurs only lasts about one-half day and past scheduling has not permitted data acquisition In this time-window. We wish to carefully arrange the observations to permit this critical measurement, as well as acquiring a few other orbital phase angles for Dione and Rhea. The Voyager spacecraft made a few broad-band measurements at 260 nm but IUE data are needed to fix the low solar phase angle data. These data will form the basis of a UV spectral geometric albedo set for these satellites.

  13. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2013-01-01

    Top space experts from around the world have collaborated to produce this comprehensive, authoritative, and clearly illustrated reference guide to the fast growing, multi-billion dollar field of satellite applications and space communications. This handbook, done under the auspices of the International Space University based in France, addresses not only system technologies but also examines market dynamics, technical standards and regulatory constraints. The handbook is a completely multi-disciplinary reference book that covers, in an in-depth fashion, the fields of satellite telecommunications, Earth observation, remote sensing, satellite navigation, geographical information systems, and geosynchronous meteorological systems. It covers current practices and designs as well as advanced concepts and future systems. It provides a comparative analysis of the common technologies and design elements for satellite application bus structures, thermal controls, power systems, stabilization techniques, telemetry, com...

  14. Domestic Communication Satellites

    Science.gov (United States)

    Horowitz, Andrew

    1974-01-01

    A discussion of the Federal Communications Commission's new policy on domestic satellites in light of our 1) military and economic history; 2) corporate interests; 3) citizen surveillance; and 4) media control. (HB)

  15. SATELLITE CONSTELLATION DESIGN PARAMETER

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. SATELLITE CONSTELLATION DESIGN PARAMETER. 1. ORBIT CHARACTERISTICS. ORBITAL HEIGHT >= 20,000 KM. LONGER VISIBILITY; ORBITAL PERIOD. PERTURBATIONS(MINIMUM). SOLAR RADIATION PRESSURE (IMPACTS ECCENTRICITY); LUNI ...

  16. Structural assurance testing for post-shipping satellite inspection

    Science.gov (United States)

    Reynolds, Whitney D.; Doyle, Derek; Arritt, Brandon

    2012-04-01

    Current satellite transportation sensors can provide a binary indication of the acceleration or shock that a satellite has experienced during the shipping process but do little to identify if significant structural change has occurred in the satellite and where it may be located. When a sensor indicates that the satellite has experienced shock during transit, an extensive testing process begins to evaluate the satellite functionality. If errors occur during the functional checkout, extensive physical inspection of the structure follows. In this work an alternate method for inspecting satellites for structural defects after shipping is presented. Electro- Mechanical Impedance measurements are used as an indication of the structural state. In partnership with the Air Force Research Laboratory University Nanosatellite Program, Cornell's CUSat mass model was instrumented with piezoelectric transducers and tested under several structural damage scenarios. A method for detecting and locating changes in the structure using EMI data is presented.

  17. Applications of Satellite Observations of Tropospheric Composition

    Science.gov (United States)

    Monks, Paul S.; Beirle, Steffen

    A striking feature of the field of tropospheric composition is the sheer number of chemical species that have been detected and measured with satellite instruments. The measurements have found application both in atmospheric chemistry itself, providing evidence, for example, of unexpected cryochemistry in the Arctic regions, and also in environmental monitoring with, for example, the observed growth in NO2 emissions over eastern Asia. Chapter 8 gives an overview of the utility of satellite observations for measuring tropospheric composition, dealing with each of the many compounds seen in detail. A comprehensive compound by compound table of the many studies performed is a most useful feature.

  18. DS-CDMA satellite diversity reception for personal satellite communication: Downlink performance analysis

    Science.gov (United States)

    DeGaudenzi, Riccardo; Giannetti, Filippo

    1995-01-01

    The downlink of a satellite-mobile personal communication system employing power-controlled Direct Sequence Code Division Multiple Access (DS-CDMA) and exploiting satellite-diversity is analyzed and its performance compared with a more traditional communication system utilizing single satellite reception. The analytical model developed has been thoroughly validated by means of extensive Monte Carlo computer simulations. It is shown how the capacity gain provided by diversity reception shrinks considerably in the presence of increasing traffic or in the case of light shadowing conditions. Moreover, the quantitative results tend to indicate that to combat system capacity reduction due to intra-system interference, no more than two satellites shall be active over the same region. To achieve higher system capacity, differently from terrestrial cellular systems, Multi-User Detection (MUD) techniques are likely to be required in the mobile user terminal, thus considerably increasing its complexity.

  19. Passivity Based Nonlinear Attitude Control of the Rømer Satellite

    DEFF Research Database (Denmark)

    Quottrup, Michael Melholt; Krogh-Sørensen, J.; Wisniewski, Rafal

    2001-01-01

    This paper suggests nonlinear attitude control of the Danish satellite Rømer. This satellite will be designed to fulfil two scientific objectives: The observation of stellar oscillations and the detection and localisation of gamma-ray bursts. The satellite will be equipped with a tetrahedron...

  20. Satellite Communications for ATM

    Science.gov (United States)

    Shamma, Mohammed A.

    2003-01-01

    This presentation is an overview on Satellite Communication for the Aeronautical Telecommunication Management (ATM) research. Satellite Communications are being considered by the FAA and NASA as a possible alternative to the present and future ground systems supporting Air Traffic Communications. The international Civil Aviation Organization (ICAO) have in place Standards and Recommended Practices (SARPS) for the Aeronautical Mobile Satellite Services (AMSS) which is mainly derived from the pre-existing Inmarsat service that has been in service since the 1980s. The Working Group A of the Aeronautical Mobile Communication Panel of ICAO has also been investigating SARPS for what is called the Next Generation Satellite Service (NGSS) which conforms less to the Inmarsat based architecture and explores wider options in terms of satellite architectures. Several designs are being proposed by Firms such as Boeing, ESA, NASA that are geared toward full or secondary usage of satellite communications for ATM. Satellite communications for ATM can serve several purposes ranging from primary usage where ground services would play a minimal backup role, to an integrated solution where it will be used to cover services, or areas that are less likely to be supported by the proposed and existing ground infrastructure. Such Integrated roles can include usage of satellite communications for oceanic and remote land areas for example. It also can include relieving the capacity of the ground network by providing broadcast based services of Traffic Information Services messages (TIS-B), or Flight Information Services (FIS-B) which can take a significant portion of the ground system capacity. Additionally, satellite communication can play a backup role to support any needs for ground replacement, or additional needed capacity even after the new digital systems are in place. The additional bandwidth that can be provided via satellite communications can also open the door for many new

  1. Phenological Records

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Phenology is the scientific study of periodic biological phenomena, such as flowering, breeding, and migration, in relation to climatic conditions. The few records...

  2. Which adherence measure - self-report, clinician recorded or pharmacy refill - is best able to predict detectable viral load in a public ART programme without routine plasma viral load monitoring?

    Science.gov (United States)

    Mekuria, Legese A; Prins, Jan M; Yalew, Alemayehu W; Sprangers, Mirjam A G; Nieuwkerk, Pythia T

    2016-07-01

    Combination antiretroviral therapy (cART) suppresses viral replication to an undetectable level if a sufficiently high level of adherence is achieved. We investigated which adherence measurement best distinguishes between patients with and without detectable viral load in a public ART programme without routine plasma viral load monitoring. We randomly selected 870 patients who started cART between May 2009 and April 2012 in 10 healthcare facilities in Addis Ababa, Ethiopia. Six hundred and sixty-four (76.3%) patients who were retained in HIV care and were receiving cART for at least 6 months were included and 642 had their plasma HIV-1 RNA concentration measured. Patients' adherence to cART was assessed according to self-report, clinician recorded and pharmacy refill measures. Multivariate logistic regression model was fitted to identify the predictors of detectable viremia. Model accuracy was evaluated by computing the area under the receiver operating characteristic (ROC) curve. A total of 9.2% and 5.5% of the 642 patients had a detectable viral load of ≥40 and ≥400 RNA copies/ml, respectively. In the multivariate analyses, younger age, lower CD4 cell count at cART initiation, being illiterate and widowed, and each of the adherence measures were significantly and independently predictive of having ≥400 RNA copies/ml. The ROC curve showed that these variables altogether had a likelihood of more than 80% to distinguish patients with a plasma viral load of ≥400 RNA copies/ml from those without. Adherence to cART was remarkably high. Self-report, clinician recorded and pharmacy refill non-adherence were all significantly predictive of detectable viremia. The choice for one of these methods to detect non-adherence and predict a detectable viral load can therefore be based on what is most practical in a particular setting. © 2016 John Wiley & Sons Ltd.

  3. On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

    Science.gov (United States)

    Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

    2014-12-01

    Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

  4. ESA's satellite communications programme

    Science.gov (United States)

    Bartholome, P.

    1985-02-01

    The developmental history, current status, and future plans of the ESA satellite-communications programs are discussed in a general survey and illustrated with network diagrams and maps. Consideration is given to the parallel development of national and European direct-broadcast systems and telecommunications networks, the position of the European space and electronics industries in the growing world market, the impact of technological improvements (both in satellite systems and in ground-based networks), and the technological and commercial advantages of integrated space-terrestrial networks. The needs for a European definition of the precise national and international roles of satellite communications, for maximum speed in implementing such decisions (before the technology becomes obsolete), and for increased cooperation and standardization to assure European equipment manufacturers a reasonable share of the market are stressed.

  5. Solar Power Satellites

    CERN Document Server

    Flournoy, Don M

    2012-01-01

    Communication satellites are a $144 billion industry. Is there any space-based industry that could possibly beat that market? 'Solar Power Satellites' shows why and how the space satellite industry will soon begin expanding its market from relaying signals to Earth to generating energy in space and delivering it to the ground as electricity. In all industrialized nations, energy demand is growing exponentially. In the developing world, the need for energy is as basic as food and water. The Sun's energy is available everywhere, and it is non-polluting. As business plans demonstrate its technical feasibility, commercial potential, and environmental acceptability, every country on Earth will look to space for the power it needs.

  6. Geostationary satellites collocation

    CERN Document Server

    Li, Hengnian

    2014-01-01

    Geostationary Satellites Collocation aims to find solutions for deploying a safe and reliable collocation control. Focusing on the orbital perturbation analysis, the mathematical foundations for orbit and control of the geostationary satellite are summarized. The mathematical and physical principle of orbital maneuver and collocation strategies for multi geostationary satellites sharing with the same dead band is also stressed. Moreover, the book presents some applications using the above algorithms and mathematical models to help readers master the corrective method for planning station keeping maneuvers. Engineers and scientists in the fields of aerospace technology and space science can benefit from this book. Hengnian Li is the Deputy Director of State Key Laboratory of Astronautic Dynamics, China.

  7. Automated tracking for advanced satellite laser ranging systems

    Science.gov (United States)

    McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

    1996-06-01

    NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

  8. Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records.

    Science.gov (United States)

    Perrin, Jean-Baptiste; Durand, Benoît; Gay, Emilie; Ducrot, Christian; Hendrikx, Pascal; Calavas, Didier; Hénaux, Viviane

    2015-01-01

    We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.

  9. A national accounts satellite for human capital and education

    OpenAIRE

    Bos, Frits

    2011-01-01

    The official national accounts statistics do not show the role of human capital in the national economy. A set of satellite tables supplementing the standard national accounts statistics could serve this data need. In this satellite account, expenditure on education and training are recorded as human capital formation. This includes not only the expenditure on primary, secondary and tertiary education, but also expenditure on training and courses by employers and the earnings foregone by stud...

  10. Exobiology of icy satellites

    Science.gov (United States)

    Simakov, M. B.

    At the beginning of 2004 the total number of discovered planets near other stars was 119 All of them are massive giants and met practically in all orbits In a habitable zone from 0 8 up to 1 1 AU at less 11 planets has been found starting with HD 134987 and up to HD 4203 It would be naive to suppose existence of life in unique known to us amino-nucleic acid form on the gas-liquid giant planets Nevertheless conditions for onset and evolutions of life can be realized on hypothetical satellites extrasolar planets All giant planets of the Solar system have a big number of satellites 61 of Jupiter 52 of Saturn known in 2003 A small part of them consist very large bodies quite comparable to planets of terrestrial type but including very significant share of water ice Some from them have an atmosphere E g the mass of a column of the Titan s atmosphere exceeds 15 times the mass of the Earth atmosphere column Formation or capture of satellites is a natural phenomenon and satellite systems definitely should exist at extrasolar planets A hypothetical satellite of the planet HD 28185 with a dense enough atmosphere and hydrosphere could have biosphere of terrestrial type within the limits of our notion about an origin of terrestrial biosphere As an example we can see on Titan the largest satellite of Saturn which has a dense nitrogen atmosphere and a large quantity of liquid water under ice cover and so has a great exobiological significance The most recent models of the Titan s interior lead to the conclusion that a substantial liquid layer

  11. GPS satellite surveying

    CERN Document Server

    Leick, Alfred; Tatarnikov, Dmitry

    2015-01-01

    THE MOST COMPREHENSIVE, UP-TO-DATE GUIDE ON GPS TECHNOLOGY FOR SURVEYING Three previous editions have established GPS Satellite Surveying as the definitive industry reference. Now fully updated and expanded to reflect the newest developments in the field, this Fourth Edition features cutting-edge information on GNSS antennas, precise point positioning, real-time relative positioning, lattice reduction, and much more. Expert authors examine additional tools and applications, offering complete coverage of geodetic surveying using satellite technologies. The past decade has seen a major evolut

  12. Detecting relationships between the interannual variability in climate records and ecological time series using a multivariate statistical approach - four case studies for the North Sea region

    Energy Technology Data Exchange (ETDEWEB)

    Heyen, H. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik

    1998-12-31

    A multivariate statistical approach is presented that allows a systematic search for relationships between the interannual variability in climate records and ecological time series. Statistical models are built between climatological predictor fields and the variables of interest. Relationships are sought on different temporal scales and for different seasons and time lags. The possibilities and limitations of this approach are discussed in four case studies dealing with salinity in the German Bight, abundance of zooplankton at Helgoland Roads, macrofauna communities off Norderney and the arrival of migratory birds on Helgoland. (orig.) [Deutsch] Ein statistisches, multivariates Modell wird vorgestellt, das eine systematische Suche nach potentiellen Zusammenhaengen zwischen Variabilitaet in Klima- und oekologischen Zeitserien erlaubt. Anhand von vier Anwendungsbeispielen wird der Klimaeinfluss auf den Salzgehalt in der Deutschen Bucht, Zooplankton vor Helgoland, Makrofauna vor Norderney, und die Ankunft von Zugvoegeln auf Helgoland untersucht. (orig.)

  13. Creating a Satellite-Based Record of Tropospheric Ozone

    Science.gov (United States)

    Oetjen, Hilke; Payne, Vivienne H.; Kulawik, Susan S.; Eldering, Annmarie; Worden, John; Edwards, David P.; Francis, Gene L.; Worden, Helen M.

    2013-01-01

    The TES retrieval algorithm has been applied to IASI radiances. We compare the retrieved ozone profiles with ozone sonde profiles for mid-latitudes for the year 2008. We find a positive bias in the IASI ozone profiles in the UTLS region of up to 22 %. The spatial coverage of the IASI instrument allows sampling of effectively the same air mass with several IASI scenes simultaneously. Comparisons of the root-mean-square of an ensemble of IASI profiles to theoretical errors indicate that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. The total degrees of freedom for signal of the retrieval for ozone are 3.1 +/- 0.2 and the tropospheric degrees of freedom are 1.0 +/- 0.2 for the described cases. IASI ozone profiles agree within the error bars with coincident ozone profiles derived from a TES stare sequence for the ozone sonde station at Bratt's Lake (50.2 deg N, 104.7 deg W).

  14. The American Satellite Company (ASC) satellite deployed from payload bay

    Science.gov (United States)

    1985-01-01

    The American Satellite Company (ASC) communications satellite is deployed from the payload bay of the Shuttle Discovery. A portion of the cloudy surface of the earth can be seen to the left of the frame.

  15. RECORDS REACHING RECORDING DATA TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    G. W. L. Gresik

    2013-07-01

    Full Text Available The goal of RECORDS (Reaching Recording Data Technologies is the digital capturing of buildings and cultural heritage objects in hard-to-reach areas and the combination of data. It is achieved by using a modified crane from film industry, which is able to carry different measuring systems. The low-vibration measurement should be guaranteed by a gyroscopic controlled advice that has been , developed for the project. The data were achieved by using digital photography, UV-fluorescence photography, infrared reflectography, infrared thermography and shearography. Also a terrestrial 3D laser scanner and a light stripe topography scanner have been used The combination of the recorded data should ensure a complementary analysis of monuments and buildings.

  16. Records Reaching Recording Data Technologies

    Science.gov (United States)

    Gresik, G. W. L.; Siebe, S.; Drewello, R.

    2013-07-01

    The goal of RECORDS (Reaching Recording Data Technologies) is the digital capturing of buildings and cultural heritage objects in hard-to-reach areas and the combination of data. It is achieved by using a modified crane from film industry, which is able to carry different measuring systems. The low-vibration measurement should be guaranteed by a gyroscopic controlled advice that has been , developed for the project. The data were achieved by using digital photography, UV-fluorescence photography, infrared reflectography, infrared thermography and shearography. Also a terrestrial 3D laser scanner and a light stripe topography scanner have been used The combination of the recorded data should ensure a complementary analysis of monuments and buildings.

  17. Leveraging the NPS Femto Satellite for Alternative Satellite Communication Networks

    Science.gov (United States)

    2017-09-01

    programmed for eventual integration with the Iridium Network , which is then tested. C. THESIS ORGANIZATION The thesis addresses these questions...NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS by Faisal S. Alshaya September 2017 Co-Advisors: Steven J. Iatrou...TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE LEVERAGING THE NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS 5

  18. Satellite Surveillance: Domestic Issues

    National Research Council Canada - National Science Library

    Best, Jr., Richard A; Elsea, Jennifer K

    2008-01-01

    ... and law enforcement purposes, in addition to the civil applications that have been supported for years. In 2007, it moved to transfer responsibility for coordinating civilian use of satellites to the Department of Homeland Security. The transfer occurred, however, apparently without notification of key congressional oversight committees.

  19. Analysis of satellite-derived solar irradiance over the Netherlands

    Science.gov (United States)

    Dirksen, Marieke; Fokke Meirink, Jan; Sluiter, Raymond

    2017-04-01

    Measurements from geostationary satellites allow the retrieval of surface solar irradiance homogeneously over large areas, thereby providing essential information for the solar energy sector. In this paper, the SICCS solar irradiance data record derived from 12 years of Meteosat Second Generation satellite measurements is analysed with a focus on the Netherlands, where the spatial resolution is about 6 by 3 km2. Extensive validation of the SICCS data with pyranometer observations is performed, indicating a bias of approximately 3 W/m2 and RMSE of 11 W/m2 for daily data. Long term averages and seasonal variations of solar irradiance show regional patterns related to the surface type (e.g., coastal waters, forests, cities). The inter-annual variability over the time frame of the data record is quantified. Methods to merge satellite and surface observations into an optimized data record are explored.

  20. Cibola flight experiment satellite

    Science.gov (United States)

    Davies, P.; Liddle, Doug; Paffett, John; Sweeting, Martin; Curiel, A.; Sun, Wei; Eves, Stuart

    2004-11-01

    In order to achieve an "economy of scale" with respect to payload capacity the major trend in telecommunications satellites is for larger and larger platforms. With these large platforms the level of integration between platform and payload is increasing leading to longer delivery schedules. The typical lifecycle for procurement of these large telecommunications satellites is now 3-6 years depending on the level of non-recurring engineering needed. Surrey Satellite Technology Ltd (SSTL) has designed a low-cost platform aimed at telecommunications and navigation applications. SSTL's Geostationary Minisatellite Platform (GMP) is a new entrant addressing the lower end of the market with payloads up to 250kg requiring less than 1.5 kW power. The British National Space Centre through the MOSAIC Small Satellite Initiative supported the development of GMP. The main design goals for GMP are low-cost for the complete mission including launch and operations and a platform allowing flexible payload accommodation. GMP is specifically designed to allow rapid development and deployment with schedules typically between 1 and 2 years from contract signature to flight readiness. GMP achieves these aims by a modular design where the level of integration between the platform and payload is low. The modular design decomposes the satellite into three major components - the propulsion bay, the avionics bay and the payload module. Both the propulsion and avionics bays are reusable, largely unchanged, and independent of the payload configuration. Such a design means that SSTL or a 3rd party manufacturer can manufacture the payload in parallel to the platform with integration taking place quite late in the schedule. In July 2003 SSTL signed a contract for ESA's first Galileo navigation satellite known as GSTBV2/A. The satellite is based on GMP and ESA plan to launch it into a MEO orbit late in 2005. The second flight of GMP is likely to be in 2006 carrying a geostationary payload

  1. Future development of IR thermovision weather satellite equipment

    Science.gov (United States)

    Listratov, A. V.

    1974-01-01

    The self radiation of the surface being viewed is used for image synthesis in IR thermovision equipment. The installation of such equipment aboard weather satellites makes it possible to obtain cloud cover pictures of the earth's surface in a complete orbit, regardless of the illumination conditions, and also provides quantitative information on the underlying surface temperature and cloud top height. Such equipment is used successfully aboard the Soviet satellites of the Meteor system, and experimentally on the American satellites of the Nimbus series. With regard to surface resolution, the present-day IR weather satellite equipment is inferior to the television equipment. This is due primarily to the comparatively low detectivity of the IR detectors used. While IR equipment has several fundamental advantages in comparison with the conventional television equipment, the problem arises of determining the possibility for future development of weather satellite IR thermovision equipment. Criteria are examined for evaluating the quality of IR.

  2. Hurricane Satellite (HURSAT) Microwave (MW)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from Microwave (MW) observations of tropical cyclones worldwide data consist of raw satellite observations. The data derive from the...

  3. Satellite transmission of oceanographic data

    Digital Repository Service at National Institute of Oceanography (India)

    Desa, E.S.; Desai, R.G.P.; DeSa, E.J.

    Oceanographic data collected on a research vessel has been transmitted to a shore laboratory using the INMARSAT maritime satellite The system configuration used, consisted of Satellite Communication Terminals interfaced to desk top computers...

  4. Satellite Ocean Heat Content Suite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This collection contains an operational Satellite Ocean Heat Content Suite (SOHCS) product generated by NOAA National Environmental Satellite, Data, and Information...

  5. Monitoring Cyanobacteria with Satellites Webinar

    Science.gov (United States)

    real-world satellite applications can quantify cyanobacterial harmful algal blooms and related water quality parameters. Provisional satellite derived cyanobacteria data and different software tools are available to state environmental and health agencies.

  6. Defense Meteorological Satellite Program (DMSP)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Defense Meteorological Satellite Program (DMSP) satellites collect visible and infrared cloud imagery as well as monitoring the atmospheric, oceanographic,...

  7. User Validation of VIIRS Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Don Hillger

    2015-12-01

    Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

  8. Satellite Sounder Observations of Contrasting Tropospheric Moisture Transport Regimes: Saharan Air Layers, Hadley Cells, and Atmospheric Rivers

    Energy Technology Data Exchange (ETDEWEB)

    Nalli, Nicholas R.; Barnet, Christopher D.; Reale, Tony; Liu, Quanhua; Morris, Vernon R.; Spackman, J. Ryan; Joseph, Everette; Tan, Changyi; Sun, Bomin; Tilley, Frank; Leung, L. Ruby; Wolfe, Daniel

    2016-12-01

    This paper examines the performance of satellite sounder atmospheric vertical moisture proles (AVMP) under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs) and Pacific Ocean moisture conveyer belts (MCBs) commonly referred to as atmospheric rivers (ARs), both of these being mesoscale to synoptic meteorological phenomena within the vicinity of subtropical Hadley subsidence zones. Operational AVMP environmental data records retrieved from the Suomi National Polar-orbiting Partnership (SNPP) NOAA-Unique Combined Atmospheric Processing System (NUCAPS) are collocated with dedicated radiosonde observations (RAOBs) obtained from ocean-based intensive field campaigns; these RAOBs provide uniquely independent correlative truth data not assimilated into numerical weather prediction models for satellite sounder validation over open ocean. Using these marine-based data, we empirically assess the performance of the operational NUCAPS AVMP product for detecting and resolving these tropospheric moisture features over otherwise RAOB-sparse regions.

  9. Atrial fibrillation detected by continuous electrocardiographic monitoring using implantable loop recorder to prevent stroke in individuals at risk (The LOOP study)

    DEFF Research Database (Denmark)

    Diederichsen, Søren Zöga; Haugan, Ketil Jørgen; Køber, Lars

    2017-01-01

    years or older and previously diagnosed as having at least one of the following conditions: hypertension, diabetes mellitus, heart failure, or previous stroke. Exclusion criteria include history of AF and current oral anticoagulation treatment. When an AF episode lasting ≥6minutes is detected, oral...... anticoagulation will be initiated according to guidelines. Expected follow-up is 4years. The primary end point is time to stroke or systemic embolism, whereas secondary end points include time to AF diagnosis and death. CONCLUSION: The LOOP study will evaluate health benefits and cost-effectiveness of ILR...... as a screening tool for AF to prevent stroke in patients at risk. Secondary objectives include identification of risk factors for the development of AF and characterization of arrhythmias in the population. The trial holds the potential to influence the future of stroke prevention....

  10. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  11. Valid measures of periodic leg movements (PLMs) during a suggested immobilization test using the PAM-RL leg activity monitors require adjusting detection parameters for noise and signal in each recording.

    Science.gov (United States)

    Yang, Myung Sung; Montplaisir, Jacques; Desautels, Alex; Winkelman, John W; Cramer Bornemann, Michel A; Earley, Christopher J; Allen, Richard P

    2014-01-01

    Individuals with restless legs syndrome (RLS) (Willis-Ekbom disease [WED]) usually have periodic leg movements (PLMs). The suggested immobilization test (SIT) measures sensory and motor features of WED during wakefulness. Surface electromyogram (EMG) recordings of the anterior tibialis (AT) are used as the standard for counting PLMs. However, due to several limitations, leg activity meters such as the PAM-RL were advanced as a potential substitute. In our study, we assessed the validity of the measurements of PLM during wakefulness (PLMW) in the SIT for PAM-RL using both default and custom detection threshold parameters compared to AT EMG. Data were obtained from 39 participants who were diagnosed with primary WED and who were on stable medication as part of another study using the SIT to repeatedly evaluate WED symptoms over 6-12 months. EMG recordings and PAM-RL, when available, were used to detect PLMW for each SIT. Complete PAM-RL and polysomnography (PSG) EMG data were available for 253 SITs from that study. The default PAM-RL (dPAM-RL) detected leg movements based on manufacturer's noise (resting) and signal (movement) amplitude criteria developed to accurately detect PLM during sleep (PLMS). The custom PAM-RL (cPAM-RL) similarly detected leg movements except the noise and movement detection parameters were adjusted to match the PAM-RL data for each SIT. The distributions of the differences between either dPAM-RL or cPAM-RL and EMG PLMW were strongly leptokurtic (Kurtosis >2) with many small differences and a few unusually large differences. These distributions are better described by median and quartile ranges than mean and standard deviation. Despite an adequate correlation (r=0.66) between the dPAM-RL and EMG recordings, the dPAM-RL on average significantly underscored the number of PLMW (median: quartiles=-13: -51.2, 0.0) and on Bland-Altman plots had a significant magnitude bias with greater underscoring for larger average PLMW/h. There also was an

  12. Telelibrary: Library Services via Satellite.

    Science.gov (United States)

    Liu, Rosa

    1979-01-01

    Investigates the provision of library services via satellite, explains briefly the operation and advantages of communication satellites, and discusses the various telecommunications equipment and services which, when coupled with satellite transmission, will enhance library activities. Demand trend projections for telecommunications services…

  13. Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

    Science.gov (United States)

    Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.; hide

    2012-01-01

    Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

  14. Advancing the capabilities of reservoir remote sensing by leveraging multi-source satellite data

    Science.gov (United States)

    Gao, H.; Zhang, S.; Zhao, G.; Li, Y.

    2017-12-01

    With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.

  15. Is Metabolic Syndrome On the Radar? Improving Real-Time Detection of Metabolic Syndrome and Physician Response by Computerized Scan of the Electronic Medical Record

    Science.gov (United States)

    Lui, Kingwai; Randhawa, Gagandeep; Totten, Vicken; Smith, Adam E.; Raese, Joachim

    2016-01-01

    Objective: Metabolic syndrome is a common underdiagnosed condition among psychiatric patients exacerbated by second-generation antipsychotics, with the exception of aripiprazole and ziprasidone. This study evaluated the prescribing and treating behavior with regard to antipsychotics and metabolic syndrome of psychiatrists before and after implementation of a mandatory admission order set and electronic notification of results. Method: Baseline data from 9,100 consecutive psychiatric admissions to a mental health hospital (July 2013–July 2014) were compared to postintervention data (July 2014–January 2015), which included 1,499 consecutive patient records. The intervention initiated standardized admission testing with electronic notification to psychiatrists when patients met metabolic syndrome criteria (according to Axis III of the DSM-IV). Charts were examined for inclusion of this diagnosis at discharge and for treatment changes. Results: At baseline, only 2.4% of patients (n = 214) were evaluated for metabolic syndrome. Of these, 34.5% (0.8% of the total sample) met metabolic syndrome criteria. Only 15 patients (0.16%) were comprehensively treated. No chart listed metabolic syndrome under Axis III of the DSM-IV. After the intervention, the diagnosis of patients meeting the criteria for metabolic syndrome increased from 0% to 29.3%. Less than 3% of patients were switched to drugs with a more benign metabolic profile. All patients who continued on second-generation antipsychotics had metabolic retesting. Thirty-eight experienced a significant and rapid increase in triglyceride levels after only 3 to 17 days. Conclusions: Mandatory intake testing increases the number of patients evaluated for metabolic syndrome. Electronic alerts increase the inclusion of metabolic syndrome among discharge diagnoses but rarely affect prescribing practices. PMID:27247842

  16. Glacier Melt Detection in Complex Terrain Using New AMSR-E Calibrated Enhanced Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record

    Science.gov (United States)

    Ramage, J. M.; Brodzik, M. J.; Hardman, M.

    2016-12-01

    Passive microwave (PM) 18 GHz and 36 GHz horizontally- and vertically-polarized brightness temperatures (Tb) channels from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) have been important sources of information about snow melt status in glacial environments, particularly at high latitudes. PM data are sensitive to the changes in near-surface liquid water that accompany melt onset, melt intensification, and refreezing. Overpasses are frequent enough that in most areas multiple (2-8) observations per day are possible, yielding the potential for determining the dynamic state of the snow pack during transition seasons. AMSR-E Tb data have been used effectively to determine melt onset and melt intensification using daily Tb and diurnal amplitude variation (DAV) thresholds. Due to mixed pixels in historically coarse spatial resolution Tb data, melt analysis has been impractical in ice-marginal zones where pixels may be only fractionally snow/ice covered, and in areas where the glacier is near large bodies of water: even small regions of open water in a pixel severely impact the microwave signal. We use the new enhanced-resolution Calibrated Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record product's twice daily obserations to test and update existing snow melt algorithms by determining appropriate melt thresholds for both Tb and DAV for the CETB 18 and 36 GHz channels. We use the enhanced resolution data to evaluate melt characteristics along glacier margins and melt transition zones during the melt seasons in locations spanning a wide range of melt scenarios, including the Patagonian Andes, the Alaskan Coast Range, and the Russian High Arctic icecaps. We quantify how improvement of spatial resolution from the original 12.5 - 25 km-scale pixels to the enhanced resolution of 3.125 - 6.25 km improves the ability to evaluate melt timing across boundaries and transition zones in diverse glacial environments.

  17. Classification of Modern and Old Río Tinto Sedimentary Deposits Through the Biomolecular Record Using a Life Marker Biochip: Implications for Detecting Life on Mars

    Science.gov (United States)

    Parro, Victor; Fernández-Remolar, David; Rodríguez-Manfredi, José A.; Cruz-Gil, Patricia; Rivas, Luis A.; Ruiz-Bermejo, Marta; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Gómez-Ortiz, David; Blanco-López, Yolanda; Menor-Salván, César; Prieto-Ballesteros, Olga; Gómez-Elvira, Javier

    2011-01-01

    The particular mineralogy formed in the acidic conditions of the Río Tinto has proven to be a first-order analogue for the acid-sulfate aqueous environments of Mars. Therefore, studies about the formation and preservation of biosignatures in the Río Tinto will provide insights into equivalent processes on Mars. We characterized the biomolecular patterns recorded in samples of modern and old fluvial sediments along a segment of the river by means of an antibody microarray containing more than 200 antibodies (LDCHIP200, for Life Detector Chip) against whole microorganisms, universal biomolecules, or environmental extracts. Samples containing 0.3-0.5g of solid material were automatically analyzed in situ by the Signs Of LIfe Detector instrument (SOLID2), and the results were corroborated by extensive analysis in the laboratory. Positive antigen-antibody reactions indica