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Sample records for satellite detects record

  1. 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.

  2. Change detection in satellite images

    Science.gov (United States)

    Thonnessen, U.; Hofele, G.; Middelmann, W.

    2005-05-01

    Change detection plays an important role in different military areas as strategic reconnaissance, verification of armament and disarmament control and damage assessment. It is the process of identifying differences in the state of an object or phenomenon by observing it at different times. The availability of spaceborne reconnaissance systems with high spatial resolution, multi spectral capabilities, and short revisit times offer new perspectives for change detection. Before performing any kind of change detection it is necessary to separate changes of interest from changes caused by differences in data acquisition parameters. In these cases it is necessary to perform a pre-processing to correct the data or to normalize it. Image registration and, corresponding to this task, the ortho-rectification of the image data is a further prerequisite for change detection. If feasible, a 1-to-1 geometric correspondence should be aspired for. Change detection on an iconic level with a succeeding interpretation of the changes by the observer is often proposed; nevertheless an automatic knowledge-based analysis delivering the interpretation of the changes on a semantic level should be the aim of the future. We present first results of change detection on a structural level concerning urban areas. After pre-processing, the images are segmented in areas of interest and structural analysis is applied to these regions to extract descriptions of urban infrastructure like buildings, roads and tanks of refineries. These descriptions are matched to detect changes and similarities.

  3. Arctic sea ice reaches second lowest in satellite record

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Xinhua reports that the blanket of sea ice that floats on the Arctic Ocean appears to have reached its lowest extent for 2011, the second lowest recorded since satellites began measuring it in 1979, according to a report released on September 15 by the University of Colorado Boulder's National Snow and Ice Data Center (NSIDC).

  4. Evidence for climate change in the satellite cloud record

    Science.gov (United States)

    Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

    2016-08-01

    Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

  5. Robust satellite techniques for oil spill detection and monitoring

    Science.gov (United States)

    Casciello, D.; Pergola, N.; Tramutoli, V.

    Discharge of oil into the sea is one of the most dangerous, among technological hazards, for the maritime environment. In the last years maritime transport and exploitation of marine resources continued to increase; as a result, tanker accidents are nowadays increasingly frequent, continuously menacing the maritime security and safety. Satellite remote sensing could contribute in multiple ways, in particular for what concerns early warning and real-time (or near real-time) monitoring. Several satellite techniques exist, mainly based on the use of SAR (Synthetic Aperture Radar) technology, which are able to recognise, with sufficient accuracy, oil spills discharged into the sea. Unfortunately, such methods cannot be profitably used for real-time detection, because of the low observational frequency assured by present satellite platforms carrying SAR sensors (the mean repetition rate is something like 30 days). On the other hand, potential of optical sensors aboard meteorological satellites, was not yet fully exploited and no reliable techniques have been developed until now for this purpose. Main limit of proposed techniques can be found in the ``fixed threshold'' approach which makes such techniques difficult to implement without operator supervision and, generally, without an independent information on the oil spill presence that could drive the choice of the best threshold. A different methodological approach (RAT, Robust AVHRR Techniques) proposed by Tramutoli (1998) and already successfully applied to several natural and environmental emergencies related to volcanic eruptions, forest fires and seismic activity. In this paper its extension to near real-time detection and monitoring of oil spills by means of NOAA-AVHRR (Advanced Very High Resolution Radiometer) records will be described. Briefly, RAT approach is an automatic change-detection scheme that considers a satellite image as a space-time process, described at each place (x,y) and time t, by the value of

  6. 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.

  7. Towards a satellite-based sea ice climate data record

    Science.gov (United States)

    Meier, W. N.; Fetterer, F.; Stroeve, J.; Cavalieri, D.; Parkinson, C.; Comiso, J.; Weaver, R.

    2005-12-01

    Sea ice plays an important role in the Earth's climate through its influence on the surface albedo, heat and moisture transfer between the ocean and the atmosphere, and the thermohaline circulation. Satellite data reveal that since 1979, summer Arctic sea ice has, overall, been declining at a rate of almost 8%/decade, with recent summers (beginning in 2002) being particularly low. The receding sea ice is having an effect on wildlife and indigenous peoples in the Arctic, and concern exists that these effects may become increasingly severe. Thus, a long-term, ongoing climate data record of sea ice is crucial for tracking the changes in sea ice and for assessing the significance of long-term trends. Since the advent of passive microwave satellite instruments in the early 1970s, sea ice has been one of the most consistently monitored climate parameters. There is now a 27+ year record of sea ice extent and concentration from multi-channel passive microwave radiometers that has undergone inter-sensor calibration and other quality controls to ensure consistency throughout the record. Several algorithms have been developed over the years to retrieve sea ice extent and concentration and two of the most commonly used algorithms, the NASA Team and Bootstrap, have been applied to the entire SMMR-SSM/I record to obtain a consistent time series. These algorithms were developed at NASA Goddard Space Flight Center and are archived at the National Snow and Ice Data Center. However, the complex surface properties of sea ice affect the microwave signature, and algorithms can yield ambiguous results; no single algorithm has been found to work uniformly well under all sea ice conditions. Thus there are ongoing efforts to further refine the algorithms and the time series. One approach is to develop data fusion methods to optimally combine sea ice fields from two or more algorithms. Another approach is to take advantage of the improved capabilities of JAXA's AMSR-E sensor on NASA's Aqua

  8. DISTRIBUTED ANOMALY DETECTION USING SATELLITE DATA FROM MULTIPLE MODALITIES

    Data.gov (United States)

    National Aeronautics and Space Administration — DISTRIBUTED ANOMALY DETECTION USING SATELLITE DATA FROM MULTIPLE MODALITIES KANISHKA BHADURI*, KAMALIKA DAS, AND PETR VOTAVA* Abstract. There has been a tremendous...

  9. Radiometric Analysis of Daytime Satellite Detection

    Science.gov (United States)

    2006-03-01

    detector m No 300 km – 1500 km 400 km Cos(θs) cosine of satellite orientation angle unitless No 0-1 0.5 Δf noise-equivalent bandwidth Hz No...Dependence Asat area of satellite m2 9 m2 linear Rsat-det distance from satellite to detector m 400 km 2 1 x Cos(θs) cosine of satellite orientation angle

  10. Detecting negative ions on board small satellites

    Science.gov (United States)

    Lepri, S. T.; Raines, J. M.; Gilbert, J. A.; Cutler, J.; Panning, M.; Zurbuchen, T. H.

    2017-04-01

    Recent measurements near comets, planets, and their satellites have shown that heavy ions, energetic neutral atoms, molecular ions, and charged dust contain a wealth of information about the origin, evolution, and interaction of celestial bodies with their space environment. Using highly sensitive plasma instruments, positively charged heavy ions have been used to trace exospheric and surface composition of comets, planets, and satellites as well as the composition of interplanetary and interstellar dust. While positive ions dominate throughout the heliosphere, negative ions are also produced from surface interactions. In fact, laboratory experiments have shown that oxygen released from rocky surfaces is mostly negatively charged. Negative ions and negatively charged nanograins have been detected with plasma electron analyzers in several different environments (e.g., by Cassini and Rosetta), though more extensive studies have been challenging without instrumentation dedicated to negative ions. We discuss an adaptation of the Fast Imaging Plasma Spectrometer (FIPS) flown on MErcury Surface, Space ENvironment, GEochemistry and Ranging (MESSENGER) for the measurement of negatively charged particles. MESSENGER/FIPS successfully measured the plasma environment of Mercury from 2011 until 2015, when the mission ended, and has been used to map multiple ion species (H+ through Na+ and beyond) throughout Mercury's space environment. Modifications to the existing instrument design fits within a 3U CubeSat volume and would provide a low mass, low power instrument, ideal for future CubeSat or distributed sensor missions seeking, for the first time, to characterize the contribution of negative particles in the heliospheric plasmas near the planets, moons, comets, and other sources.

  11. Satellite-Based EMI Detection, Identification, and Mitigation

    Science.gov (United States)

    Stottler, R.; Bowman, C.

    2016-09-01

    Commanding, controlling, and maintaining the health of satellites requires a clear operating spectrum for communications. Electro Magnetic Interference (EMI) from other satellites can interfere with these communications. Determining which satellite is at fault improves space situational awareness and can be used to avoid the problem in the future. The Rfi detection And Prediction Tool, Optimizing Resources (RAPTOR) monitors the satellite communication antenna signals to detect EMI (also called RFI for Radio Frequency Interference) using a neural network trained on past cases of both normal communications and EMI events. RAPTOR maintains a database of satellites that have violated the reserved spectrum in the past. When satellite-based EMI is detected, RAPTOR first checks this list to determine if any are angularly close to the satellite being communicated with. Additionally, RAPTOR checks the Space Catalog to see if any of its active satellites are angularly close. RAPTOR also consults on-line databases to determine if the described operating frequencies of the satellites match the detected EMI and recommends candidates to be added to the known offenders database, accordingly. Based on detected EMI and predicted orbits and frequencies, RAPTOR automatically reschedules satellite communications to avoid current and future satellite-based EMI. It also includes an intuitive display for a global network of satellite communications antennas and their statuses including the status of their EM spectrum. RAPTOR has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication signals and is currently undergoing full-scale development. This paper describes the RAPTOR technologies and results of testing.

  12. Spatial Cloud Detection and Retrieval System for Satellite Images

    Directory of Open Access Journals (Sweden)

    Ayman Nasr

    2013-01-01

    Full Text Available In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection. Satellite images having a large percentage of cloud cannot be used in further analysis. While there are many approaches that deal with different semantic meaning, there are rarely approaches that deal specifically with cloud detection and retrieval. In this paper we introduce a novel approach that spatially detect and retrieve clouds in satellite images using their unique properties .Our approach is developed as spatial cloud detection and retrieval system (SCDRS that introduce a complete framework for specific semantic retrieval system. It uses a Query by polygon (QBP paradigm for the content of interest instead of using the more conventional rectangular query by image approach. First, we extract features from the satellite images using multiple tile sizes using spatial and textural properties of cloud regions. Second, we retrieve our tiles using a parametric statistical approach within a multilevel refinement process. Our approach has been experimentally validated against the conventional ones yielding enhanced precision and recall rates in the same time it gives more precise detection of cloud coverage regions.

  13. Vehicle Detection and Classification from High Resolution Satellite Images

    Science.gov (United States)

    Abraham, L.; Sasikumar, M.

    2014-11-01

    In the past decades satellite imagery has been used successfully for weather forecasting, geographical and geological applications. Low resolution satellite images are sufficient for these sorts of applications. But the technological developments in the field of satellite imaging provide high resolution sensors which expands its field of application. Thus the High Resolution Satellite Imagery (HRSI) proved to be a suitable alternative to aerial photogrammetric data to provide a new data source for object detection. Since the traffic rates in developing countries are enormously increasing, vehicle detection from satellite data will be a better choice for automating such systems. In this work, a novel technique for vehicle detection from the images obtained from high resolution sensors is proposed. Though we are using high resolution images, vehicles are seen only as tiny spots, difficult to distinguish from the background. But we are able to obtain a detection rate not less than 0.9. Thereafter we classify the detected vehicles into cars and trucks and find the count of them.

  14. 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...... 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....... The receiver also allows for this 750 kSPS signal to be stored onboard the receiver and later downloaded. A number of 330 ms samples have been downloaded via the satellite and further analyzed. The results shows, that there is a large variation of AIS band utilization depending on if it is the northern...

  15. Submerged turbulence detection with optical satellites

    CERN Document Server

    Gibson, Carl H; Bondur, Valery G; Leung, Pak T; Prandke, H; Vithanage, D

    2007-01-01

    During fall periods in 2002, 2003 and 2004 three major oceanographic expeditions were carried out in Mamala Bay, Hawaii. These were part of the RASP Remote Anthropogenic Sensing Program. Ikonos and Quickbird optical satellite images of sea surface glint revealed ~100 m spectral anomalies in km^2 averaging patches in regions leading from the Honolulu Sand Island Municipal Outfall diffuser to distances up to 20 km. To determine the mechanisms behind this phenomenon, the RASP expeditions monitored the waters adjacent to the outfall with an array of hydrographic, optical and turbulence microstructure sensors in anomaly and ambient background regions. Drogue tracks and mean turbulence parameters for 2x10^4 microstructure patches were analyzed to understand complex turbulence, fossil turbulence and zombie turbulence near-vertical internal wave transport processes. The dominant mechanism appears to be generic to stratified natural fluids including planet and star atmospheres and is termed beamed zombie turbulence ma...

  16. 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....... There is a good agreement between the SAR-estimated HE center location and the best track data from the National Hurricane Center. The wind speeds at 10 m above the ocean surface are also retrieved from the SAR data using the geophysical model function (GMF), CMOD5, and compared with in situ wind speed...... 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)....

  17. Satellite detection of wastewater diversion plumes in Southern California

    Science.gov (United States)

    Gierach, Michelle M.; Holt, Benjamin; Trinh, Rebecca; Jack Pan, B.; Rains, Christine

    2017-02-01

    Multi-sensor satellite observations proved useful in detecting surfacing wastewater plumes during the 2006 Hyperion Treatment Plant (HTP) and 2012 Orange County Sanitation District (OCSD) wastewater diversion events in Southern California. Satellite sensors were capable of detecting biophysical signatures associated with the wastewater, compared to ambient ocean waters, enabling monitoring of environmental impacts over a greater spatial extent than in situ sampling alone. Thermal satellite sensors measured decreased sea surface temperatures (SSTs) associated with the surfacing plumes. Ocean color satellite sensors did not measure a distinguishable biological response in terms of chlorophyll-a (chl-a) concentrations during the short lived, three-day long, 2006 HTP diversion. A period of decreased chl-a concentration was observed during the three-week long 2012 OCSD diversion, likely in association with enhanced chlorination of the discharged wastewater that suppressed the phytoplankton response and/or significant uptake by heterotrophic bacteria. Synthetic aperture radar (SAR) satellite data were able to identify and track the 2006 HTP wastewater plume through changes in surface roughness related to the oily components of the treated surfacing wastewater. Overall, it was found that chl-a and SST values must have differences of at least 1 mg m-3 and 0.5 °C, respectively, in comparison with adjacent waters for wastewater plumes and their biophysical impact to be detectable from satellite. For a wastewater plume to be identifiable in SAR imagery, wind speeds must range between ∼3 and 8 m s-1. The findings of this study illustrate the benefit of utilizing multiple satellite sensors to monitor the rapidly changing environmental response to surfacing wastewater plumes, and can help inform future wastewater diversions in coastal areas.

  18. Channel Estimation And Multiuser Detection In Asynchronous Satellite Communications

    CERN Document Server

    Chaouech, Helmi; 10.5121/ijwmn.2010.2411

    2010-01-01

    In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.

  19. Ice Sheet Temperature Records - Satellite and In Situ Data from Antarctica and Greenland

    Science.gov (United States)

    Shuman, C. A.; Comiso, J. C.

    2001-12-01

    Recently completed decadal-length surface temperature records from Antarctica and Greenland are providing insights into the challenge of detecting climate change. Ice and snow cover at high latitudes influence the global climate system by reflecting much of the incoming solar energy back to space. An expected consequence of global warming is a decrease in area covered by snow and ice and an increase in Earth's absorption of solar radiation. Models have predicted that the effects of climate warming may be amplified at high latitudes; thinning of the Greenland ice sheet margins and the breakup of Antarctic Peninsula ice shelves suggest this process may have begun. Satellite data provide an excellent means of observing climate parameters across both long temporal and remote spatial domains but calibration and validation of their data remains a challenge. Infrared sensors can provide excellent temperature information but cloud cover and calibration remain as problems. Passive-microwave sensors can obtain data during the long polar night and through clouds but have calibration issues and a much lower spatial resolution. Automatic weather stations are generally spatially- and temporally-restricted and may have long gaps due to equipment failure. Stable isotopes of oxygen and hydrogen from ice sheet locations provide another means of determining temperature variations with time but are challenging to calibrate to observed temperatures and also represent restricted areas. This presentation will discuss these issues and elaborate on the development and limitations of composite satellite, automatic weather station, and proxy temperature data from selected sites in Antarctica and Greenland.

  20. Detecting Urban Warming Signals in Climate Records

    Institute of Scientific and Technical Information of China (English)

    HE Yuting; JIA Gensuo; HU Yonghong; ZHOU Zijiang

    2013-01-01

    Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale.With support of historical remote sensing data,this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing,Tianjin,and Hebei Province over the last three decades.There were significant positive relations between the two factors at all stations.Stronger warming was detected at the meteorological stations that experienced greater urbanization,i.e.,those with a higher urbanization rate.While the total urban area affects the absolute temperature values,the change of the urban area (urbanization rate) likely affects the temperature trend.Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13℃ rise in air temperature records in addition to regional climate warming.This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions.Generally,the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years,and the regional climate warming was 0.30℃ (10 yr)-1 in the last three decades.

  1. Rapid Brightness Variations as a Tool to Enhance Satellite Detectability

    Science.gov (United States)

    Laas-Bourez, Myrtille; Klotz, Alain; Ducrotte, Etienne; Boer, Michel; Blanchet, Gwendoline

    2009-03-01

    To preserve the space environment for future generations and ensure the safety of space missions, we have to improve our knowledge of the debris at all altitudes. Since 2004, we have started to observe and study satellites and debris on the geostationary orbit. We use a network of robotic telescopes called TAROT (Télescopes Action Rapide pour les Objets Transitoires - Rapid Action Telescope for Transient Objects) which are located in France and Chile. This system processes the data in real time. Its wide field of view is useful for detection, systematic survey and to follow both catalogued and uncatalogued objects. The TAROTs are 25 cm telescopes with a wide field of view of 1.86deg x 1.86deg. It can detect objects up to 17th magnitude with an integration time of 30 seconds, corresponding to an object of 50cm in the geostationary belt with a 0.2 albedo. Tiny debris are also dangerous for space mission and satellites. To detect them, we need either to increase the TAROT sensitivity or to observe them in optimal light conditions.Last year we detected very important magnitude variations from several geostationary satellites during observations close to equinoxes. The brightness of a geostationary satellite evolves during the night and during the year, depending on the angle between the observer, the satellite and the sun. Geostationary satellites will be brighter near March 1st and of October 10th, at their exit of the shade. In this period the sun crosses the equatorial plan of the Earth, the enlightened surface will reach a maximum during a limited periods of time (about 30 minutes), provoking a short, bright flash. This phenomenon is used in two ways: first, it allows to detect smaller objects, which are usually below the detection limit, enhancing the sensitivity of the survey. Secondly, for longer objects the light curve during and outside the °ash contains information on the object intrinsic geometry and reflectivity. In this paper we discuss how the various

  2. Impact detections of temporarily captured natural satellites

    Science.gov (United States)

    Clark, David; Spurný, Pavel; Wiegert, Paul; Brown, Peter G.; Borovicha, Jiri; Tagliaferri, Ed; Shrbeny, Lukas

    2016-10-01

    Temporarily Captured Orbiters (TCOs) are Near-Earth Objects (NEOs) which make a few orbits of Earth before returning to heliocentric orbits. Only one TCO has been observed to date, 2006 RH120, captured by Earth for one year before escaping. Detailed modeling predicts capture should occur from the NEO population predominantly through the Sun-Earth L1 and L2 points, with 1% of TCOs impacting Earth and approximately 0.1% of meteoroids being TCOs. Although thousands of meteoroid orbits have been measured, none until now have conclusively exhibited TCO behaviour, largely due to difficulties in measuring initial meteoroid speed with sufficient precision. We report on a precise meteor observation of January 13, 2014 by a new generation of all-sky fireball digital camera systems operated in the Czech Republic as part of the European Fireball Network, providing the lowest natural object entry speed observed in decades long monitoring by networks world-wide. Modeling atmospheric deceleration and fragmentation yields an initial mass of ~5 kg and diameter of 15 cm, with a maximum Earth-relative velocity just over 11.0 km/s. Spectral observations prove its natural origin. Back-integration across observational uncertainties yields a 92 - 98% probability of TCO behaviour, with close lunar dynamical interaction. The capture duration varies across observational uncertainties from 48 days to 5+ years. We also report on two low-speed impacts recorded by US Government sensors, and we examine Prairie Network event PN39078 from 1965 having an extremely low entry speed of 10.9 km/s. In these cases uncertainties in measurement and origin make TCO designation uncertain.

  3. Variability and trends of surface solar radiation in Europe based on CM SAF satellite data records

    Science.gov (United States)

    Trentmann, Jörg; Pfeifroth, Uwe; Sanchez-Lorenzo, Arturo; Urbain, Manon; Clerbaux, Nicolas

    2017-04-01

    The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based high-quality climate data records, with a focus on the global energy and water cycle. Here, the latest releases of the CM SAF's data records of surface solar radiation, Surface Solar Radiation Data Set - Heliosat (SARAH), and CM SAF cLouds, Albedo and Radiation dataset from AVHRR data (CLARA), are analyzed and validated with reference to ground-based measurements, e.g., provided by the Baseline Surface Radiation Network (BSRN), the World Radiation Data Center (WRDC) and the Global Energy Balance Archive (GEBA). Focus is given to the trends and the variability of the surface irradiance in Europe as derived from the surface and the satellite-based data records. Both data sources show an overall increase (i.e., brightening) after the 1980s, and indicate substantial decadal variability with periods of reduced increase (or even a decrease) and periods with a comparable high increase. Also the increase shows a pronounced spatial pattern, which is also found to be consistent between the two data sources. The good correspondence between the satellite-based data records and the surface measurements highlight the potential of the satellite data to represent the variability and changes in the surface irradiance and document the dominant role of clouds over aerosol to explain its variations. Reasons for remaining differences between the satellite- and the surface-based data records (e.g., in Southern Europe) will be discussed. To test the consistency of the CM SAF solar radiation data records we also assess the decadal variability of the solar reflected radiation at the top-of-the atmosphere (TOA) from the CM SAF climate data record based on the MVIRI / SEVIRI measurements from 1983 to 2015. This data record complements the SARAH data record in its temporal and spatial coverage; fewer and different assumptions are used in the retrieval to generate the TOA reflected solar

  4. 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

  5. Satellite images analysis for shadow detection and building height estimation

    Science.gov (United States)

    Liasis, Gregoris; Stavrou, Stavros

    2016-09-01

    Satellite images can provide valuable information about the presented urban landscape scenes to remote sensing and telecommunication applications. Obtaining information from satellite images is difficult since all the objects and their surroundings are presented with feature complexity. The shadows cast by buildings in urban scenes can be processed and used for estimating building heights. Thus, a robust and accurate building shadow detection process is important. Region-based active contour models can be used for satellite image segmentation. However, spectral heterogeneity that usually exists in satellite images and the feature similarity representing the shadow and several non-shadow regions makes building shadow detection challenging. In this work, a new automated method for delineating building shadows is proposed. Initially, spectral and spatial features of the satellite image are utilized for designing a custom filter to enhance shadows and reduce intensity heterogeneity. An effective iterative procedure using intensity differences is developed for tuning and subsequently selecting the most appropriate filter settings, able to highlight the building shadows. The response of the filter is then used for automatically estimating the radiometric property of the shadows. The customized filter and the radiometric feature are utilized to form an optimized active contour model where the contours are biased to delineate shadow regions. Post-processing morphological operations are also developed and applied for removing misleading artefacts. Finally, building heights are approximated using shadow length and the predefined or estimated solar elevation angle. Qualitative and quantitative measures are used for evaluating the performance of the proposed method for both shadow detection and building height estimation.

  6. 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.

  7. 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.

  8. 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.

  9. 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...... parameters that describe the sensitivity of land surface reflectivity to variation in solar position throughout the day. Examination of these parameters can then yield information describing the nature of the surface being viewed, including the presence of water due to flooding, on a 3-day basis. An analysis...... 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....

  10. A pathway to generating Climate Data Records of sea-surface temperature from satellite measurements

    Science.gov (United States)

    Minnett, Peter J.; Corlett, Gary K.

    2012-11-01

    In addition to having known uncertainty characteristics, Climate Data Records (CDRs) of geophysical variables derived from satellite measurements must be of sufficient length to resolve signals that might reveal the signatures of climate change against a background of larger, unrelated variability. The length of the record requires using satellite measurements from many instruments over several decades, and the uncertainty requirement implies that a consistent approach be used to establish the errors in the satellite retrievals over the entire period. Retrieving sea-surface temperature (SST) from satellite is a relatively mature topic, and the uncertainties of satellite retrievals are determined by comparison with collocated independent measurements. To avoid the complicating effects of near-surface temperature gradients in the upper ocean, the best validating measurements are from ship-board radiometers that measure, at source, the surface emission that is measured in space, after modification by its propagation through the atmosphere. To attain sufficient accuracy, such ship-based radiometers must use internal blackbody calibration targets, but to determine the uncertainties in these radiometric measurements, i.e. to confirm that the internal calibration is effective, it is necessary to conduct verification of the field calibration using independent blackbodies with accurately known emissivity and at very accurately measured temperatures. This is a well-justifiable approach to providing the necessary underpinning of a Climate Data Record of SST.

  11. Global solar radiation: comparison of satellite-based climatology with station records

    Science.gov (United States)

    Skalak, Petr; Zahradnicek, Pavel; Stepanek, Petr; Farda, Ales

    2016-04-01

    We analyze surface incoming shortwave radiation (SIS) from the SARAH dataset prepared by the EUMETSAT Climate Monitoring Satellite Applications Facility from satellite observations of the visible channels of the MVIRI and SEVIRI instruments onboard the geostationary Meteosat satellites. The satellite SIS data are evaluated within the period 1984-2014 on various time scales: from individual months and years to long-term climate means. The validation is performed using the ground measurements of global solar radiation (GLBR) carried out on 11 meteorological stations of the Czech Hydrometeorological Institute in the Czech Republic with at least 30 years long data series. Our aim is to explore whether the SIS data could potentially serve as an alternative source of information on GLBR outside of a relatively sparse network of meteorological stations recording GLBR. Acknowledgement: Supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Program I (NPU I), grant number LO1415.

  12. Detecting surface geostrophic currents using wavelet filter from satellite geodesy

    Institute of Scientific and Technical Information of China (English)

    HSU; HouTse

    2007-01-01

    According to the features of spatial spectrum of the dynamic ocean topography (DOT),wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96),combining an altimetry-derived mean sea surface height model (KMSS04),two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter,and the DOT models asso-ciated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global,Kuroshio and equatorial Pacific regions with that from oceanography,and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale,the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography,which indicates that ocean currents detected by satellite measurement have reached relatively high precision.

  13. Detecting surface geostrophic currents using wavelet filter from satellite geodesy

    Institute of Scientific and Technical Information of China (English)

    ZHANG ZiZhan; LU Yang; HSU HouTse

    2007-01-01

    According to the features of spatial spectrum of the dynamic ocean topography (DOT), wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96), combining an altimetry-derived mean sea surface height model (KMSS04), two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter, and the DOT models associated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global, Kuroshio and equatorial Pacific regions with that from oceanography, and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale, the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography, which indicates that ocean currents detected by satellite measurement have reached relatively high precision.

  14. 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.

  15. 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....

  16. Urban Land Use Change Detection Using Multisensor Satellite Images

    Institute of Scientific and Technical Information of China (English)

    DENG Jin-Song; WANG Ke; LI Jun; DENG Yan-Hua

    2009-01-01

    Due to inappropriate planning and management, accelerated urban growth and tremendous loss in land, especially cropland, have become a great challenge for sustainable urban development in China, especially in developed urban area in the coastal regions; therefore, there is an urgent need to effectively detect and monitor the land use changes and provide accurate and timely information for planning and management. In this study a method combining principal component analysis (PCA) of multiseusor satellite images from SPOT (systeme pour l'observation de la terre or earth observation satellite)-5 muttispectral (XS) and Landsat-7 enhanced thematic mapper (ETM) panchromatic (PAN) data, and supervised classification was used to detect and analyze the dynamics of land use changes in the city proper of Hangzhou. The overall accuracy of the land use change detection was 90.67% and Kappa index was 0.89. The results indicated that there was a considerable land use change (10.03% of the total area) in the study area from 2001 to 2003, with three major types of land use conversions: from cropland into bnilt-up land, construction site, and water area (fish pond). Changes from orchard land into built-up land were also detected. The method described in this study is feasible and useful for detecting rapid land use change in the urban area.

  17. 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

  18. Towards Multi-Stage Intrusion Detection using IP Flow Records

    OpenAIRE

    Muhammad Fahad Umer; Muhammad Sher; Imran Khan

    2016-01-01

    Traditional network-based intrusion detection sys-tems using deep packet inspection are not feasible for modern high-speed networks due to slow processing and inability to read encrypted packet content. As an alternative to packet-based intrusion detection, researchers have focused on flow-based intrusion detection techniques. Flow-based intrusion detection systems analyze IP flow records for attack detection. IP flow records contain summarized traffic information. However, flow data is very ...

  19. Airport runway detection in satellite images by Adaboost learning

    Science.gov (United States)

    Zongur, Ugur; Halici, Ugur; Aytekin, Orsan; Ulusoy, Ilkay

    2009-09-01

    Advances in hardware and pattern recognition techniques, along with the widespread utilization of remote sensing satellites, have urged the development of automatic target detection systems in satellite images. Automatic detection of airports is particularly essential, due to the strategic importance of these targets. In this paper, a runway detection method using a segmentation process based on textural properties is proposed for the detection of airport runways, which is the most distinguishing element of an airport. Several local textural features are extracted including not only low level features such as mean, standard deviation of image intensity and gradient, but also Zernike Moments, Circular-Mellin Features, Haralick Features, as well as features involving Gabor Filters, Wavelets and Fourier Power Spectrum Analysis. Since the subset of the mentioned features, which have a role in the discrimination of airport runways from other structures and landforms, cannot be predicted trivially, Adaboost learning algorithm is employed for both classification and determining the feature subset, due to its feature selector nature. By means of the features chosen in this way, a coarse representation of possible runway locations is obtained. Promising experimental results are achieved and given.

  20. 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

  1. 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.

  2. Bowie Lecture: The Record of Sea Level Change from Satellite Measurements: What Have We Learned?

    Science.gov (United States)

    Nerem, R. S.

    2005-12-01

    Over the last decade, satellite geodetic measurements together with in situ measurements, have revolutionized our understanding of present-day sea level change. This is important because sea level change can be used as one barometer of climate variations and because of the implications sea level change has for coastal populations. With measurements from satellite altimeter missions (TOPEX/Posiedon and Jason), satellite gravity missions (GRACE), and the Global Positioning System (GPS), we are now able to start asking some important questions with regards to global sea level change and its regional variations. What has been the rate of global mean sea level change over the last dozen years? Is this rate different from the historical rate observed by the tide gauges over the last century? What are the principal causes of the observed sea level change, and are they related to anthropogenic climate variations? The record of sea level change from satellite altimetry will be reviewed, its error sources and limitations discussed, and the results placed in context with other estimates of sea level change from tide gauges, in situ measurements, and global climate models. The much shorter, but just as important, record of ocean mass variations from satellite gravity measurements will be similarly reviewed. In addition, GPS measurements of the deformation of the solid Earth due to the melting of continental ice and what they tell us about sea level change will be discussed. A sea level change budget will be presented, both for the altimetric era and the last century, containing estimates of contributions from thermal expansion, ocean mass changes (melting ice, runoff, etc.), and other contributions to sea level change. Finally, the need for continuing the satellite measurements of sea level change will be discussed in the context of future missions and the scientific gain that would result.

  3. 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

  4. Detection of ship tracks in ATSR2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2008-08-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both west Africa and south-western Europe. In order to automate their detection within the Along Track Scanning Radiometer 2 (ATSR2 data set an algorithm was developed and integrated with the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of its neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR2 data. A month of results have been compared with other satellite datasets to validate the algorithm. There is a high ratio of false detections. Nevertheless the global distribution of ship tracks shows a similar pattern to the ship emissions distribution.

  5. Efficient Algorithm for Railway Tracks Detection Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2012-10-01

    Full Text Available Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

  6. Satellite-derived emissions inventories and detection of missing sources

    Science.gov (United States)

    McLinden, C. A.; Fioletov, V.; Shephard, M.; Krotkov, N. A.; Li, C.; Joiner, J.

    2016-12-01

    Our understanding of the impacts of air pollution on health and the environment, and our ability to predict future levels, is limited by our knowledge of its sources. Here, a global inventory of SO2 emissions, derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite and independent of conventional emissions databases, is presented. Our OMI-based inventory is found to be generally consistent with these conventional inventories. However, since we are also able to detect emission sources (in addition to quantifying their emissions), many SO2 sources were identified that are evidently missing from bottom-up inventories, including nearly 40 large anthropogenic sources pointing to significant discrepancies in some regions such as the Middle-East. The methodology, inventory highlights, and applications to other pollutants (NO2 from OMI and NH3 from the Cross-track Infrared Sounder) will be discussed.

  7. A System to Detect Residential Area in Multispectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Seyfallah Bouraoui

    2011-11-01

    Full Text Available In this paper, we propose a new solution to extract complex structures from High-Resolution (HR remote-sensing images. We propose to represent shapes and there relations by using region adjacency graphs. They are generated automatically from the segmented images. Thus, the nodes of the graph represent shape like houses, streets or trees, while arcs describe the adjacency relation between them. In order to be invariant to transformations such as rotation and scaling, the extraction of objects of interest is done by combining two techniques: one based on roof color to detect the bounding boxes of houses, and one based on mathematical morphology notions to detect streets. To recognize residential areas, a model described by a regular language is built. The detection is achieved by looking for a path in the region adjacency graph, which can be recognized as a word belonging to the description language. Our algorithm was tested with success on images from the French satellite SPOT 5 representing the urban area of Strasbourg (France at different spatial resolution.

  8. 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

  9. 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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    F. Lefeuvre

    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.

  12. A Global Record of Daily Landscape Freeze-Thaw Status from Satellite Microwave Remote Sensing

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; Colliander, A.; McDonald, K. C.

    2011-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, seasonal vegetation growth dynamics and terrestrial carbon budgets. A global Earth System Data Record (ESDR) of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The product is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier product validation is applied using in situ temperature and tower carbon flux measurements, and other satellite FT retrievals. The FT-ESDR record shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to surface air temperature measurements from global weather stations. Other comparisons against spatially dense temperature observations from an Alaska ecological transect reveal satellite sensor frequency dependence and variable FT sensitivity to surface air, vegetation, soil and snow properties. Other satellite sensor retrievals, including AMSR-E and SMOS show similar FT classification accuracies, but variable sensitivity to different landscape elements. Sensor FT classification differences reflect differences in microwave frequency, footprint resolution and satellite

  13. Automatic detection of ship tracks in ATSR-2 satellite imagery

    Directory of Open Access Journals (Sweden)

    E. Campmany

    2009-03-01

    Full Text Available Ships modify cloud microphysics by adding cloud condensation nuclei (CCN to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. An algorithm has been developed to automate the detection of ship tracks in Along Track Scanning Radiometer 2 (ATSR-2 imagery. The scheme has been integrated into the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of their neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR-2 data. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both West Africa and South-Western Europe. The global distribution of ship tracks shows strong seasonality, little inter-annual variability and a similar spatial pattern to the distribution of ship emissions.

  14. Detection of wind wakes offshore from satellite SAR

    Science.gov (United States)

    Christiansen, M. B.; Hasager, C. B.

    A study is presented on the mapping of ocean wind fields for detection of wind wakes downstream of an offshore wind farm. The study is based on ERS-2 Synthetic Aperture Radar (SAR) scenes obtained in 2003 over Horns Reef in the North Sea. A large offshore wind farm (80 wind turbines) is located 14-20 km offshore of Denmark on this submerged reef. Meteorological observations are available from an offshore mast; wind speed is measured at four heights up to 62 m and wind direction is measured at 60 m. Maps of wind speed are generated from geophysical model functions (CMOD-4, CMOD-IFR2) with a resolution of 400 m by 400 m using wind direction obtained from in-situ measurements as model input. The wind maps display zones of reduced mean wind speed downstream of the wind farm compared to upwind conditions. The reduction is approximately 10 % immediately behind the wind farm and the wake effect is vanishing over distances in the order of 10 km downstream. This is consistent with wake model predictions. Satellite SAR provides a good estimate of the propagation of wind wakes. Information on how structures affect the local wind climate is useful for wind energy purposes, particularly for siting of future offshore wind farms.

  15. 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

  16. Towards Multi-Stage Intrusion Detection using IP Flow Records

    Directory of Open Access Journals (Sweden)

    Muhammad Fahad Umer

    2016-10-01

    Full Text Available Traditional network-based intrusion detection sys-tems using deep packet inspection are not feasible for modern high-speed networks due to slow processing and inability to read encrypted packet content. As an alternative to packet-based intrusion detection, researchers have focused on flow-based intrusion detection techniques. Flow-based intrusion detection systems analyze IP flow records for attack detection. IP flow records contain summarized traffic information. However, flow data is very large in high-speed networks and cannot be processed in real-time by the intrusion detection system. In this paper, an efficient multi-stage model for intrusion detection using IP flows records is proposed. The first stage in the model classifies the traffic as normal or malicious. The malicious flows are further analyzed by a second stage. The second stage associates an attack type with malicious IP flows. The proposed multi-stage model is efficient because the majority of IP flows are discarded in the first stage and only malicious flows are examined in detail. We also describe the implementation of our model using machine learning techniques.

  17. 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 earl......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...... contents of the EEG and a semi-automatic signal reduction method was introduced. The reduced feature set was used for a subject-based classification. With a subject specific re-scaling of the feature set and the use of an outlier detection classifier the algorithm reached an accuracy of 0.78. The result...... shows that EEG recordings contain valid information for a supportive algorithm for the detection of iRBD. Further investigation could lead to promising application of EEG recordings as a supportive source for the detection of iRBD....

  18. Validating a Satellite Microwave Remote Sensing Based Global Record of Daily Landscape Freeze-Thaw Dynamics

    Science.gov (United States)

    Kimball, J. S.; Kim, Y.; McDonald, K. C.

    2012-12-01

    The freeze-thaw (FT) parameter from satellite microwave remote sensing quantifies the predominant landscape frozen or thawed state and is closely linked to surface energy budget and hydrologic activity, vegetation growth, terrestrial carbon budgets and land-atmosphere trace gas exchange. A global Earth System Data Record of daily landscape FT status (FT-ESDR) was developed using a temporal change classification of overlapping 37 GHz brightness temperature (Tb) series from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I), and encompassing land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 yr) FT record was created by ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The FT-ESDR is designed to determine the FT status of the composite landscape vegetation-snow-soil medium with sufficient accuracy to characterize frozen temperature constraints to surface water mobility, vegetation productivity and land-atmosphere CO2 fluxes. A multi-tier validation scheme was applied using in situ temperature measurements, other satellite FT retrievals and synergistic biophysical data. These results are incorporated into the product metadata structure, including mean daily spatial classification accuracies and annual quality assessment (QA) maps accounting for landscape heterogeneity, algorithm limitations and sensor retrieval gaps. The resulting FT-ESDR shows mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals. Accuracy is reduced during seasonal transition periods when FT heterogeneity is maximized within the relatively coarse (~25-km) satellite footprint. The QA rankings range from low (estimated accuracy 90%) categories; mean annual QA results for the 1979-2011 period show relative proportions of

  19. Distributed Anomaly Detection Using Satellite Data From Multiple Modalities

    Data.gov (United States)

    National Aeronautics and Space Administration — There has been a tremendous increase in the volume of Earth Science data over the last decade from modern satellites, in-situ sensors and different climate models....

  20. A Collective Detection Based GPS Receiver for Small Satellites Project

    Data.gov (United States)

    National Aeronautics and Space Administration — To solve the problem of autonomous navigation on small satellite platforms less than 20 kg, we propose to develop an onboard orbit determination receiver for small...

  1. Detecting Anomaly Regions in Satellite Image Time Series Based on Sesaonal Autocorrelation Analysis

    Science.gov (United States)

    Zhou, Z.-G.; Tang, P.; Zhou, M.

    2016-06-01

    Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1) it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2) it is flexible to meet some requirement (e.g., z-value or significance level) of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3) it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.

  2. DETECTING ANOMALY REGIONS IN SATELLITE IMAGE TIME SERIES BASED ON SESAONAL AUTOCORRELATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    Z.-G. Zhou

    2016-06-01

    Full Text Available Anomaly regions in satellite images can reflect unexpected changes of land cover caused by flood, fire, landslide, etc. Detecting anomaly regions in satellite image time series is important for studying the dynamic processes of land cover changes as well as for disaster monitoring. Although several methods have been developed to detect land cover changes using satellite image time series, they are generally designed for detecting inter-annual or abrupt land cover changes, but are not focusing on detecting spatial-temporal changes in continuous images. In order to identify spatial-temporal dynamic processes of unexpected changes of land cover, this study proposes a method for detecting anomaly regions in each image of satellite image time series based on seasonal autocorrelation analysis. The method was validated with a case study to detect spatial-temporal processes of a severe flooding using Terra/MODIS image time series. Experiments demonstrated the advantages of the method that (1 it can effectively detect anomaly regions in each of satellite image time series, showing spatial-temporal varying process of anomaly regions, (2 it is flexible to meet some requirement (e.g., z-value or significance level of detection accuracies with overall accuracy being up to 89% and precision above than 90%, and (3 it does not need time series smoothing and can detect anomaly regions in noisy satellite images with a high reliability.

  3. Data Assimilation of Satellite Fire Detection in Coupled Atmosphere-Fire Simulation by WRF-SFIRE

    CERN Document Server

    Mandel, Jan; Vejmelka, Martin; Beezley, Jonathan D

    2014-01-01

    Currently available satellite active fire detection products from the VIIRS and MODIS instruments on polar-orbiting satellites produce detection squares in arbitrary locations. There is no global fire/no fire map, no detection under cloud cover, false negatives are common, and the detection squares are much coarser than the resolution of a fire behavior model. Consequently, current active fire satellite detection products should be used to improve fire modeling in a statistical sense only, rather than as a direct input. We describe a new data assimilation method for active fire detection, based on a modification of the fire arrival time to simultaneously minimize the difference from the forecast fire arrival time and maximize the likelihood of the fire detection data. This method is inspired by contour detection methods used in computer vision, and it can be cast as a Bayesian inverse problem technique, or a generalized Tikhonov regularization. After the new fire arrival time on the whole simulation domain is...

  4. Climate Change Detection in the UTLS with the GPS Radio Occultation Record

    Science.gov (United States)

    Steiner, A. K.; Kirchengast, G.; Lackner, B. C.; Hegerl, G. C.; Pirscher, B.; Foelsche, U.

    2009-12-01

    Radio Occultation (RO) based on signals from Global Positioning System (GPS) satellites provides a new climate record of high quality and vertical resolution in the upper troposphere and lower stratosphere (UTLS). RO data are considered a climate benchmark data type since they are based on timing with precise atomic clocks and tied to the international definition of the second. Long-term stability and the consistency of RO data stemming from different satellites (without need for inter-calibration) make RO well suited for climate change detection. RO data are available on a continuous basis from Sep 2001 to Sep 2008 from the CHAMP satellite and intermittent periods of observations from the GPS/Met proof-of-concept mission exist in the years 1995-1997, with sufficient data only for Oct 1995 and Feb 1997. We present a climate change detection study based on monthly mean zonal mean RO climatologies in the UTLS region within 9-25 km (300-30 hPa) where we use different detection methods. An optimal fingerprinting technique is applied to the whole record of RO accessible parameters refractivity, geopotential height, and temperature to detect a forced climate signal. Three representative global climate models of the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are employed to estimate natural climate variability using pre-industrial control runs. The response pattern to the external forcings is presented by an ensemble mean of the models' A2 and B1 scenario runs. Optimal fingerprinting shows that a climate change signal can be detected in the RO refractivity and in the RO temperature record (90 % significance level). Furthermore, standard and multiple linear regression is applied to temperature time series for February (1997 and 2002-2008) and for October (1995 and 2001-2007), taking RO errors into account. In the tropics, we also investigate the influence of stratospheric quasi-biennial oscillation (QBO) and tropospheric El Nino

  5. 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.

  6. Sources of Divergence in Remote Sensing of Vegetation Phenology From Multiple Long Term Satellite Data Records

    Science.gov (United States)

    Barreto, A.; Didan, K.; Miura, T.

    2008-12-01

    Changes in vegetation phenology depict an integrated response to change in environmental factors and provide valuable information to global change research. Typically, remote sensing of vegetation phenology is based on the analysis of vegetation index temporal profiles, because of their simplicity, stability, and inherent resistant to noise. Most phenology estimates are, however, limited to using one sensor owing to the inter-sensor continuity challenges. Although, phenology is used for a variety of research and application topics, the central premise remains the study of vegetation dynamics change in response to change in climate and other factors. Consequently, the consistency and length of data records are key requirements. With satellite missions lasting few years only, long term phenology measures will have to be based on a mixture of satellite data records. In this study we compared phenology parameters from the AVHRR-GIMMS and MODIS NDVI records (1982- 2007). We analyzed both records globally using a cluster approach to abate noise and focus on the landscape level vegetation dynamic. The cluster approach, assumes that phenology is controlled by a complex set of factors that could be encapsulated by homogeneous climate, soil, elevational gradient, sun- shade exposure, and biophysical capacity. We applied this method to each of the sensors and examined three fundamental phenology parameters: the start and end of the growing season and the cumulative seasonal signal. These parameters are sensitive to, and are capable of capturing changes in the underlying environmental factors. Our results indicate that a large divergence exist over the dense forest of the tropics. This divergence was attributed to MODIS saturation rather than NDVI saturation. Boreal forests exhibited also large disagreement owing to snow cover and related differences in data processing. Furthermore, agricultural areas showed the most irregular phenological signals. This noise resulted from the

  7. 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...... the original implementation a sensitivity of 92.8% and a false positive ratio (FPR) of 0.93/h were obtained. Our extension of the algorithm rendered a 95.9% sensitivity and only 0.65 false detections per hour. Conclusion: Better seizure detection can be performed when the higher frequencies in the iEEG were...

  8. ELF/VLF Perturbations Above the Haarp Transmitter Recorded by the Demeter Satellite in the Upper Ionosphere

    Science.gov (United States)

    Titova, E. E.; Demekhov, A. G.; Mochalov, A. A.; Gvozdevsky, B. B.; Mogilevsky, M. M.; Parrot, M.

    2015-08-01

    In the studies of the data received from DEMETER (orbit altitude above the Earth is about 700 km), we detected for the first time electromagnetic perturbations, which are due to the ionospheric modification by HAARP, a high-power high-frequency transmitter, simultaneously in the extremely low-frequency (ELF, below 1200 Hz) and very low-frequency (VLF, below 20 kHz) ranges. Of the thirteen analyzed flybys of the satellite above the heated area, the ELF/VLF signals were detected in three cases in the daytime (LT = 11-12 h), when the minimum distance between the geomagnetic projections of the satellite and the heated area center on the Earth's surface did not exceed 31 km. During the nighttime flybys, the ELF/VLF perturbations were not detected. The size of the perturbed region was about 100 km. The amplitude, spectrum, and polarization of the ELF perturbations were analyzed, and their comparison with the characteristics of natural ELF noise above the HAARP transmitter was performed. In particular, it was shown that in the daytime the ELF perturbation amplitude above the heated area can exceed by a factor of 3 to 8 the amplitude of natural ELF noise. The absence of the nighttime records of artificial ELF/VLF perturbations above the heated area can be due to both the lower frequency of the heating signal, at which the heating occurs in the lower ionosphere, and the higher level of natural noise. The spectrum of the VLF signals related to the HAARP transmitter operation had two peaks at frequencies of 8 to 10 kHz and 15 to 18 kHz, which are close to the first and second harmonics of the lower-hybrid resonance in the heated area. The effect of the whistler wave propagation near the lower-hybrid resonance region on the perturbation spectrum recorded in the upper ionosphere for these signals has been demonstrated. In particular, some of the spectrum features can be explained by assuming that the VLF signals propagate in quasiresonance, rather than quasilongitudinal, regime

  9. 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

  10. A study of warm rain detection using A-Train satellite data

    National Research Council Canada - National Science Library

    Ruiyue Chen; Zhanqing Li; Robert J. Kuligowski; Ralph Ferraro; Fuzhong Weng

    2011-01-01

    .... This study exploits multi-sensor data from the A-Train satellite constellation to investigate the rain contribution from warm clouds and the potential of using cloud microphysical parameters for warm rain detection...

  11. Fault Detection and Isolation of Satellite Formations using a Ground Station Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal is for the development a fault detection and isolation (FDI) algorithm for a formation of satellites but processed at a ground station. The algorithm...

  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... of Tasmania, Australia ABSTRACT There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification in South Africa and in particular, the monitoring of human settlement expansion...

  13. APPLICABILITY EVALUATION OF OBJECT DETECTION METHOD TO SATELLITE AND AERIAL IMAGERIES

    Directory of Open Access Journals (Sweden)

    K. Kamiya

    2016-06-01

    Full Text Available Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  14. Applicability Evaluation of Object Detection Method to Satellite and Aerial Imageries

    Science.gov (United States)

    Kamiya, K.; Fuse, T.; Takahashi, M.

    2016-06-01

    Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ object detection before object recognition can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

  15. Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

    Science.gov (United States)

    Potter, Christopher; Tan, Pang-Ning; Kumar, Vipin; Kicharik, Chris; Klooster, Steven; Genovese, Vanessa

    2004-01-01

    Ecosystem structure and function are strongly impacted 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) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

  16. Image Processing Technique for Automatic Detection of Satellite Streaks

    Science.gov (United States)

    2007-02-01

    satellites actifs et d’autres débris doivent être contrôlées. Dans ces cas, les paramètres orbitaux sont connus, mais après un certain temps cette...artéfacts de capteur (tel que des pixels morts, gradient de fond, bruit) et dégradation du signal (coulage, éblouissement, saturation, etc...Cette étude explique comment les artéfacts du capteur peuvent être corrigés, le fond de l’image enlevé et le bruit partiellement effacé. Puis, elle

  17. Long-Term Record of Arctic and Antarctic Sea and Ice Surface Temperatures from Thermal Infrared Satellite Sensors

    Science.gov (United States)

    Luis, Cristina; Dybkjær, Gorm; Eastwood, Steinar; Tonboe, Rasmus; Høyer, Jacob

    2015-04-01

    Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 µm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperature (IST) and ice cap skin temperature dataset spanning 27 years (1982-2009). This long-term climate record is the first of its kind for IST. In this project we used brightness temperatures from the infrared channels of AVHRR sensors aboard NOAA and Metop polar-orbiting satellites. Surface temperatures were calculated using separate split window algorithms for day SST, night SST, and IST. The snow surface emissivity across all angles of the swath were simulated specifically for all sensors using an emission model. Additionally, all algorithms were tuned to the Arctic using simulated brightness temperatures from a radiative transfer model with atmospheric profiles and skin temperatures from European Centre for Medium-Range Forecasts (ECMWF) re-analysis data (ERA-Interim). Here we present the results of product quality as compared to in situ measurements from buoys and infrared radiometers, as well as a preliminary analysis of climate trends revealed by the record.

  18. The experience of land cover change detection by satellite data

    Institute of Scientific and Technical Information of China (English)

    Lev SPIVAK; Irina VITKOVSKAYA; Madina BATYRBAYEVA; Alexey TEREKHOV

    2012-01-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan.As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan.The major process of desertification takes place in the arid and semi-arid areas.To allocate spots of stable degradation of vegetation,the transition zone was first identified.Productivity of vegetation in transfer zone is slightly dependent on climate conditions.Multi-year digital maps of vegetation index were generated with NOAA satellite images.According to the result,the territory of the republic was zoned by means of vegetation productivity criterion.All the arable lands in Kazakhstan are in the risky agriculture zone.Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture,where natural factors,such as wind and water erosion,can significantly change land quality in a relatively short time period.We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from lowresolution satellite data for all of Kazakhstan.This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  19. Avalanche Debris Detection Using Satellite- and Drone Based Radar and Optical Remote Sensing

    Science.gov (United States)

    Eckerstorfer, M.; Malnes, E.; Vickers, H.; Solbø, S. A.; Tøllefsen, A.

    2014-12-01

    The mountainous fjord landscape in the county of Troms, around its capital Tromsø in Northern Norway is prone to high avalanche activity during the snow season. Large avalanches pose a hazard to infrastructure, such as buildings and roads, located between the steep mountainsides and the fjords. A prolonged cold spell during January and February 2014 was followed by rapid new-snow loading during March 2014, inducing a significant avalanche cycle with many spontaneous, size D4 avalanches that affected major transport veins. During and shortly after the avalanche cycle of March 2014, we obtained 11 Radarsat-2 Ultrafine mode scenes, chosen according to reported avalanche activity. We further collected four Radarsat-2 ScanSAR mode scenes and two Landsat-8 scenes covering the entire county of Troms. For one particular avalanche, we obtained a drone-based orthophoto, from which a DEM of the avalanche debris surface was derived, using structure-from-motion photogrammetry. This enabled us to calculate the debris volume accurately. We detected avalanche debris in the radar images visually, by applying two detection algorithms that make use of the increased backscatter in avalanche debris. This backscatter increase is a product of increased snow water equivalent and surface roughness, roughly of the order of 3 dB. In addition, we applied a multi-temporal approach by repeatedly detecting avalanche debris at different acquisition times, as well as a multi-sensor approach, covering similar areas with different sensors. This multi-temporal and multi-sensor approach enabled us to map the spatial extent and magnitude of the March 2014 avalanche cycle in the county Troms. With ESA's Sentinel-1 satellite, providing high-resolution, large swath radar images with a short repeat cycle, a complete avalanche record for a forecasting region could become feasible. In this first test season, we detected more than 550 avalanches that were released during a one-month period over an area of

  20. Application of Uncertainty Reasoning Theory to satellite Fault Detection and Diagnosis

    Institute of Scientific and Technical Information of China (English)

    YangTianshe; LiHuaizu; SunYanbong

    2004-01-01

    Reasoning theories are divided into certainty reasoning theories and uncertainty reasoning theories.Now,only certainty reason-ing theories use to deitcs are used to detect and diagnose satellite faults.However,in practice,it is difficult to detect and diagnose some faults of the satellite autiomatically only by use of ccrtainty.Fortunately.uncerlainty Reasoning theories are applied to detect and diagnose satellite faults.Uncertainty reasoning theories include several kinds of theories,such as inclusion degree theory,rough set theory,evidence reasoning theory,probabilisticresoning theory,fuzzy,fuzzy reasoningteory,and so on.Inclusion degree theory.rough set theory and evidence reasoning theory are three advanced ones,Based on these three theories respectively.the audhor introduces three new methods to detect and diagnose satellite faults in this paper.It is shown that the methods,suitable for detecting and diagnosing satellite faults,especially uncertainty faults,can remedy the defects of the current methods.

  1. Satellite Detection of Smoke Aerosols Over a Snow/Ice Surface by TOMS

    Science.gov (United States)

    Hsu, N. Christina; Herman, Jay R.; Gleason, J. F.; Torres, O.; Seftor, C. J.

    1998-01-01

    The use of TOMS (Total Ozone Mapping Spectrometer) satellite data demonstrates the recently developed technique of using satellite UV radiance measurements to detect absorbing tropospheric aerosols is effective over snow/ice surfaces. Instead of the traditional single wavelength (visible or infrared) method of measuring tropospheric aerosols, this method takes advantage of the wavelength dependent reduction in the backscattered radiance due to the presence of absorbing aerosols over snow/ice surfaces. An example of the resulting aerosol distribution derived from TOMS data is shown for an August 1998 event in which smoke generated by Canadian forest fires drifts over and across Greenland. As the smoke plume moved over Greenland, the TOMS observed 380 nm reflectivity over the snow/ice surface dropped drastically from 90-100% down to 30-40%. To study the effects of this smoke plume in both the UV and visible regions of the spectrum, we compared a smoke-laden spectrum taken over Greenland by the high spectral resolution (300 to 800 nm) GOME instrument with one that is aerosol-free. We also discuss the results of modeling the darkening effects of various types of absorbing aerosols over snow/ice surfaces using a radiative transfer code. Finally, we investigated the history of such events by looking at the nearly twenty year record of TOMS aerosol index measurements and found that there is a large interannual variability in the amount of smoke aerosols observed over Greenland. This information will be available for studies of radiation and transport properties in the Arctic.

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

    Directory of Open Access Journals (Sweden)

    M. J. Behrenfeld

    2008-11-01

    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 use satellite-based fluorescence measurements to evaluate light-absorption and energy-dissipation processes influencing phytoplankton light use efficiency and demonstrate its utility as a global physiological indicator of iron-limited growth conditions. This new tool provides a path for monitoring climate-phytoplankton physiology interactions, improving descriptions of light use efficiency in ocean productivity models, evaluating nutrient-stress predictions in ocean ecosystem models, and appraising phytoplankton responses to natural iron enrichments or purposeful iron fertilizations activities.

  3. Speckle filtering in satellite SAR change detection imagery

    NARCIS (Netherlands)

    Dekker, R.J.

    1998-01-01

    Repeat-pass Synthetic Aperture Radar (SAR) imagery is useful for change detection. A disadvantage of SAR is the system-inherent speckle noise. This can be reduced by filtering. Various filter types and methods are described in the literature, but not one fits the speckle noise in change detection

  4. 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.

  5. Satellite Remote Sensing of Inundated Wetlands: Global Data Record Assembly and Planned Uncertainty Analysis

    Science.gov (United States)

    McDonald, K. C.; Chapman, B. D.; Podest, E.; Schröder, R.; Hess, L. L.; Jones, L. A.; Kimball, J. S.; Moghaddam, M.; Whitcomb, J.

    2011-12-01

    sensing and ground training and validation data sets employed, algorithms applied, and cross-product harmonization. The systematic analyses will create an enhanced ESDR of inundated wetlands with statistically robust uncertainty estimates. The ESDR documentation will include a detailed breakdown of error sources and associated uncertainties within the data record. This effort will ensure that the ESDR inundation products will be the best available data sets for global-scale modeling that involves a surface water component. This work was carried out in part within the framework of the ALOS Kyoto & Carbon Initiative. PALSAR data were provided by JAXA/EORC and the Alaska Satellite Facility. Portions of this work were conducted at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space Administration.

  6. 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.

  7. Small Moving Vehicle Detection in a Satellite Video of an Urban Area

    Science.gov (United States)

    Yang, Tao; Wang, Xiwen; Yao, Bowei; Li, Jing; Zhang, Yanning; He, Zhannan; Duan, Wencheng

    2016-01-01

    Vehicle surveillance of a wide area allows us to learn much about the daily activities and traffic information. With the rapid development of remote sensing, satellite video has become an important data source for vehicle detection, which provides a broader field of surveillance. The achieved work generally focuses on aerial video with moderately-sized objects based on feature extraction. However, the moving vehicles in satellite video imagery range from just a few pixels to dozens of pixels and exhibit low contrast with respect to the background, which makes it hard to get available appearance or shape information. In this paper, we look into the problem of moving vehicle detection in satellite imagery. To the best of our knowledge, it is the first time to deal with moving vehicle detection from satellite videos. Our approach consists of two stages: first, through foreground motion segmentation and trajectory accumulation, the scene motion heat map is dynamically built. Following this, a novel saliency based background model which intensifies moving objects is presented to segment the vehicles in the hot regions. Qualitative and quantitative experiments on sequence from a recent Skybox satellite video dataset demonstrates that our approach achieves a high detection rate and low false alarm simultaneously. PMID:27657091

  8. Small Moving Vehicle Detection in a Satellite Video of an Urban Area.

    Science.gov (United States)

    Yang, Tao; Wang, Xiwen; Yao, Bowei; Li, Jing; Zhang, Yanning; He, Zhannan; Duan, Wencheng

    2016-09-21

    Vehicle surveillance of a wide area allows us to learn much about the daily activities and traffic information. With the rapid development of remote sensing, satellite video has become an important data source for vehicle detection, which provides a broader field of surveillance. The achieved work generally focuses on aerial video with moderately-sized objects based on feature extraction. However, the moving vehicles in satellite video imagery range from just a few pixels to dozens of pixels and exhibit low contrast with respect to the background, which makes it hard to get available appearance or shape information. In this paper, we look into the problem of moving vehicle detection in satellite imagery. To the best of our knowledge, it is the first time to deal with moving vehicle detection from satellite videos. Our approach consists of two stages: first, through foreground motion segmentation and trajectory accumulation, the scene motion heat map is dynamically built. Following this, a novel saliency based background model which intensifies moving objects is presented to segment the vehicles in the hot regions. Qualitative and quantitative experiments on sequence from a recent Skybox satellite video dataset demonstrates that our approach achieves a high detection rate and low false alarm simultaneously.

  9. Region of Interest Detection Based on Histogram Segmentation for Satellite Image

    Science.gov (United States)

    Kiadtikornthaweeyot, Warinthorn; Tatnall, Adrian R. L.

    2016-06-01

    High resolution satellite imaging is considered as the outstanding applicant to extract the Earth's surface information. Extraction of a feature of an image is very difficult due to having to find the appropriate image segmentation techniques and combine different methods to detect the Region of Interest (ROI) most effectively. This paper proposes techniques to classify objects in the satellite image by using image processing methods on high-resolution satellite images. The systems to identify the ROI focus on forests, urban and agriculture areas. The proposed system is based on histograms of the image to classify objects using thresholding. The thresholding is performed by considering the behaviour of the histogram mapping to a particular region in the satellite image. The proposed model is based on histogram segmentation and morphology techniques. There are five main steps supporting each other; Histogram classification, Histogram segmentation, Morphological dilation, Morphological fill image area and holes and ROI management. The methods to detect the ROI of the satellite images based on histogram classification have been studied, implemented and tested. The algorithm is be able to detect the area of forests, urban and agriculture separately. The image segmentation methods can detect the ROI and reduce the size of the original image by discarding the unnecessary parts.

  10. Fully automated procedure for ship detection using optical satellite imagery

    Science.gov (United States)

    Corbane, C.; Pecoul, E.; Demagistri, L.; Petit, M.

    2009-01-01

    Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.

  11. 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

    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...... 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....

  12. Procedure to detect impervious surfaces using satellite images and light detection and ranging (lidar) data

    Science.gov (United States)

    Rodríguez-Cuenca, B.; Alonso-Rodríguez, M. C.; Domenech-Tofiño, E.; Valcárcel Sanz, N.; Delgado-Hernández, J.; Peces-Morera, Juan José; Arozarena-Villar, Antonio

    2014-10-01

    The detection of impervious surfaces is an important issue in the study of urban and rural environments. Imperviousness refers to water's inability to pass through a surface. Although impervious surfaces represent a small percentage of the Earth's surface, knowledge of their locations is relevant to planning and managing human activities. Impervious structures are primarily manmade (e.g., roads and rooftops). Impervious surfaces are an environmental concern because many processes that modify the normal function of land, air, and water resources are initiated during their construction. This paper presents a novel method of identifying impervious surfaces using satellite images and light detection and ranging (LIDAR) data. The inputs for the procedure are SPOT images formed by four spectral bands (corresponding to red, green, near-infrared and mid-infrared wavelengths), a digital terrain model, and an .las file. The proposed method computes five decision indexes from the input data to classify the studied area into two categories: impervious (subdivided into buildings and roads) and non-impervious surfaces. The impervious class is divided into two subclasses because the elements forming this category (mainly roads and rooftops) have different spectral and height properties, and it is difficult to combine these elements into one group. The classification is conducted using a decision tree procedure. For every decision index, a threshold is set for which every surface is considered impervious or non-impervious. The proposed method has been applied to four different regions located in the north, center, and south of Spain, providing satisfactory results for every dataset.

  13. Improved sea level record over the satellite altimetry era (1993–2010 from the Climate Change Initiative Project

    Directory of Open Access Journals (Sweden)

    M. Ablain

    2014-08-01

    Full Text Available Sea level is one of the 50 Essential Climate Variables (ECVs listed by the Global Climate Observing System (GCOS in climate change monitoring. In the last two decades, sea level has been routinely measured from space using satellite altimetry techniques. In order to address a number of important scientific questions such as: "Is sea level rise accelerating?", "Can we close the sea level budget?", "What are the causes of the regional and interannual variability?", "Can we already detect the anthropogenic forcing signature and separate it from the internal/natural climate variability?", and "What are the coastal impacts of sea level rise?", the accuracy of altimetry-based sea level records at global and regional scales needs to be significantly improved. For example, the global mean and regional sea level trend uncertainty should become better than 0.3 and 0.5 mm year−1, respectively (currently of 0.6 and 1–2 mm year−1. Similarly, interannual global mean sea level variations (currently uncertain to 2–3 mm need to be monitored with better accuracy. In this paper, we present various respective data improvements achieved within the European Space Agency (ESA Climate Change Initiative (ESA CCI project on "Sea Level" during its first phase (2010–2013, using multi-mission satellite altimetry data over the 1993–2010 time span. In a first step, using a new processing system with dedicated algorithms and adapted data processing strategies, an improved set of sea level products has been produced. The main improvements include: reduction of orbit errors and wet/dry atmospheric correction errors, reduction of instrumental drifts and bias, inter-calibration biases, intercalibration between missions and combination of the different sea level data sets, and an improvement of the reference mean sea surface. We also present preliminary independent validations of the SL_cci products, based on tide gauges comparison and sea level budget closure approach

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

    National Research Council Canada - National Science Library

    Christopher D Elvidge; Daniel Ziskin; Kimberly E Baugh; Benjamin T Tuttle; Tilottama Ghosh; Dee W Pack; Edward H Erwin; Mikhail Zhizhin

    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...

  15. Atmospheric Climate Change Detection Based on the GPS Radio Occultation Record

    Science.gov (United States)

    Steiner, A. K.; Lackner, B. C.; Hegerl, G. C.; Pirscher, B.; Borsche, M.; Foelsche, U.; Kirchengast, G.

    2009-04-01

    Monitoring of global climate change requires high quality observations of the Earth's atmosphere. Radio occultation (RO) measurements based on signals from Global Positioning System (GPS) satellites provide a useful upper air record in this respect. RO data are considered a climate benchmark data type since they are based on timing with precise atomic clocks and tied to the international definition of the second. High quality and vertical resolution in the upper troposphere and lower stratosphere (UTLS), long-term stability, and consistency of RO data stemming from satellites in different orbits without need for inter-calibration make RO well suited for atmospheric observations and climate change detection. RO data are available on a continuous basis since fall of 2001 from the German research satellite CHAMP (CHAllenging Minisatellite Payload for geoscientific research), establishing the first RO climate record covering more than seven years. Intermittent periods of observations from the U.S. GPS/Met proof-of-concept mission exist in the years 1995-1997, with sufficient data only for October 1995 and February 1997. We present a climate change detection study based on monthly mean zonal mean RO climatologies in the UTLS region within 9-25 km (300-30 hPa) where we use different detection methods. An optimal fingerprinting technique is applied to the whole record of RO accessible parameters refractivity, geopotential height, and temperature to detect a forced climate signal. Three representative global climate models of the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are employed to estimate natural climate variability by making use of pre-industrial control runs. The response pattern to the external forcings is presented by an ensemble mean of the models' A2 and B1 scenario runs. Optimal fingerprinting shows that a climate change signal can be detected at the 90% significance level in the RO refractivity record. Furthermore, simple

  16. Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

    CERN Document Server

    Kodge, B G

    2011-01-01

    In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.

  17. 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

    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...... by the resolution of the radar data. Subsequently, a supervised classifier was developed based on training data selected by a weather radar expert. Results of classification of data from several different meteorological events are shown. Cases of widespread sea clutter caused by anomalous propagation are especially...

  18. A stable, unbiased, long-term satellite based data record of sea surface temperature from ESA's Climate Change Initiative

    Science.gov (United States)

    Rayner, Nick; Good, Simon; Merchant, Chris

    2013-04-01

    The study of climate change demands long-term, stable observational records of climate variables such as sea surface temperature (SST). ESA's Climate Change Initiative was set up to unlock the potential of satellite data records for this purpose. As part of this initiative, 13 projects were established to develop the data records for different essential climate variables - aerosol, cloud, fire, greenhouse gases, glaciers, ice sheets, land cover, ocean colour, ozone, sea ice, sea level, soil moisture and SST. In this presentation we describe the development work that has taken place in the SST project and present new prototype data products that are available now for users to trial. The SST project began in 2010 and has now produced two prototype products. The first is a long-term product (covering mid-1991 - 2010 currently, but with a view to update this in the future), which prioritises length of data record and stability over other considerations. It is based on data from the Along-Track Scanning Radiometer (ATSR) and Advanced Very-High Resolution Radiometer (AVHRR) series of satellite instruments. The product aims to combine the favourable stability and bias characteristics of ATSR data with the geographical coverage achieved with the AVHRR series. Following an algorithm selection process, an optimal estimation approach to retrieving SST from the satellite measurements from both sensors was adopted. The retrievals do not depend on in situ data and so this data record represents an independent assessment of SST change. In situ data are, however, being used to validate the resulting data. The second data product demonstrates the coverage that can be achieved using the modern satellite observing system including, for example, geostationary satellite data. Six months worth of data have been processed for this demonstration product. The prototype SST products will be released in April to users to trial in their work. The long term product will be available as

  19. 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

  20. 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.

  1. Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data.

    Science.gov (United States)

    Morshed, Md Manjur; Islam, Md Tazmul; Jamil, Raihan

    2016-02-01

    This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R (2) value, low P value, and low Akaike's Information Criterion. About 20% variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.

  2. 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.

  3. Saharan dust detection using multi-sensor satellite measurements.

    Science.gov (United States)

    Madhavan, Sriharsha; Qu, John J; Hao, X

    2017-02-01

    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 R(2) 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 R(2) 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.

  4. 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.

  5. Validation of a 30+ year soil moisture record from multi-satellite observations

    Science.gov (United States)

    de Jeu, R.; Dorigo, W.; Wagner, W.; Chung, D.; Parinussa, R.; van der Werf, G.; Liu, Y.; Mittelbach, H.; Hirschi, M.

    2012-12-01

    As part of the ESA Climate Change Initiative soil moisture project a 30+ year consistent soil moisture dataset is currently in development by harmonizing retrievals from both passive and active microwave satellite observations. The harmonization of these datasets incorporates the advantage of both microwave techniques and spans the entire period from 1978 onwards. A statistical methodology based on scaling, ranking and blending was developed to address differences in sensor specifications to create one consistent dataset. A soil moisture dataset provided by a land surface model (GLDAS-1-Noah) was used to scale the different satellite-based products to the same range. The blending of the active and passive datasets was based on their respective performance, which is closely related to vegetation cover. While this approach imposes the absolute values of the land surface model dataset to the final product, it preserves the relative dynamics (e.g., seasonality, inter-annual variations) and trends of the original satellite derived retrievals. Different validation methods were performed to quantify the skill of the various soil moisture datasets at different temporal and spatial scales. In situ data from the International Soil Moisture Network (ISMN) were used to calculate the local correlation (both Pearson and Spearman) and Root Mean Square Difference between ground observations and the satellite retrievals for different climate regimes. In addition a triple collocation analysis was applied on the passive and active satellite products in order to analyze the error structures at a global scale for the different sensors. Furthermore, indirect proxies like tree ring width data were used to study the consistency of the inter-annual variability within the 30+ year dataset. The combination of these techniques revealed a strong dynamical behavior in data quality in both time and space. In the future this additional information on error dynamics could be used to further

  6. Chinese Surveying and Control Network for Earth-Orbit Satellites and Deep Space Detection

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The relationship between the surveying and control network(CSN) for earth-orbit satellite and spatial geodesy, and the relationship between the CSN for deep space celestial bodies and detectors, and deep space detection are briefly summarized, and so are the basic technical needs of the deep space surveying and control network(DSN). Then, the techniques, the constituents and the distributing of Chinese satellite CSN (CSCSN) and other radio observing establishments in China are introduced. Lastly, with the primary CSCSN and other observing establishments, some projects for China to rebuild a more perfect CSCSN, and to establish a DSN are analyzed and stated.

  7. On the problem of re-scaling short-term satellite data records

    Science.gov (United States)

    Satellite data have been a proven valuable source of information for model improvement through data assimilation over the past decade. The US Department of Agriculture (USDA) Foreign Agricultural Services (FAS) crop monitoring and prediction system currently relies on root-zone soil moisture (SM) es...

  8. Satellite change detection analysis of deforestation rates and patterns along the Colombia-Ecuador border.

    Science.gov (United States)

    Viña, Andrés; Echavarria, Fernando R; Rundquist, Donald C

    2004-05-01

    This study uses Landsat satellite data to document the rates and patterns of land-cover change along a portion of the Colombia-Ecuador border during a 23-yr period (1973-1996). Human colonization has resulted in extensive deforestation in both countries. Satellite change detection analysis showed that the annual rates of deforestation were considerably higher for the Colombian side of the border. In addition, loss of forest cover on the Colombian side for the study period was almost 43%, while only 22% on the Ecuadorian side. The study found that there is no single factor driving deforestation on either side of the border, but concluded that the higher rates on the Colombian side may be due to higher colonization pressures and intensification of illegal coca cultivation. On the Ecuador side of the border the satellite images documented patterns of deforestation that reflected road networks associated with oil exploration and development.

  9. 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

  10. Neural network-based recognition of whistlers on spectrograms detected by satellite

    Science.gov (United States)

    Conti, Livio

    2016-04-01

    We present a system to automatically recognize and classify the occurrence of whistler waves on spectrograms of electric field measurements performed by satellite. Whistlers - VLF waves generated by lightning, with a specific spectral dispersion relation - can induce precipitation of trapped Van Allen particles and have a role in the chemistry of some atmospheric components (mainly NOx). Moreover, it has also been suggested that the increase of the number of anomalous whistlers (i.e. whistlers with high value of dispersion constant) could be induced by disturbances in the Earth-ionosphere wave-guide, generated by seismo-electromagnetic emissions. On satellite, the recognition of whistlers asks for analyzing high-resolution spectrograms that cannot be downloaded to Earth, due to the limits of data transmission. For this reason, a real time identification and classification must be performed on satellite, by avoiding downloading all the unprocessed data. The procedure that we have developed is based on a Time Delay Neural Network (TDNN). The TDNN, proposed some years ago for speech recognition, can be fruitfully also applied in real-time analysis of electromagnetic spectrograms in order to detect phenomena characterized by a specific shape/signature such as those of the whistler waves. Some studies have been performed by the RNF experiment on board of the DEMETER satellite and our algorithm could be adopted on board of the satellite CSES (China Seismo-Electromagnetic Satellite), launch scheduled by the end of 2016. Moreover, the procedure can be also adopted to automatic analysis of whistlers detected on ground.

  11. Gravitational detection of a low-mass dark satellite at cosmological distance

    CERN Document Server

    Vegetti, S; McKean, J P; Auger, M W; Fassnacht, C D; Koopmans, L V E

    2012-01-01

    The mass-function of dwarf satellite galaxies that are observed around Local Group galaxies substantially differs from simulations based on cold dark matter: the simulations predict many more dwarf galaxies than are seen. The Local Group, however, may be anomalous in this regard. A massive dark satellite in an early-type lens galaxy at z = 0.222 was recently found using a new method based on gravitational lensing, suggesting that the mass fraction contained in substructure could be higher than is predicted from simulations. The lack of very low mass detections, however, prohibited any constraint on their mass function. Here we report the presence of a 1.9 +/- 0.1 x 10^8 M_sun dark satellite in the Einstein-ring system JVAS B1938+666 at z = 0.881, where M_sun denotes solar mass. This satellite galaxy has a mass similar to the Sagittarius galaxy, which is a satellite of the Milky Way. We determine the logarithmic slope of the mass function for substructure beyond the local Universe to be alpha = 1.1^+0.6_-0.4, ...

  12. Testing and Adapting a Daytime Four Band Satellite Ash Detection Algorithm for Eruptions in Alaska and the Kamchatka Peninsula, Russia

    Science.gov (United States)

    Andrup-Henriksen, G.; Skoog, R. A.

    2007-12-01

    Volcanic ash is detectable from satellite remote sensing due to the differences in spectral signatures compared to meteorological clouds. Recently a new global daytime ash detection algorithm was developed at University of Madison, Wisconsin. The algorithm is based on four spectral bands with the central wavelengths 0.65, 3.75, 11 and 12 micrometers that are common on weather satellite sensors including MODIS, AVHRR, GOES and MTSAT. The initial development of the algorithm was primarily based on MODIS data with global coverage. We have tested it using three years of AVHRR data in Alaska and the Kamchatka Peninsula, Russia. All the AVHRR data have been manually analyzed and recorded into an observational database during the daily monitoring performed by the remote sensing group at the Alaska Volcano Observatory (AVO). By taking the manual observations as accurate we were able to examine the accuracy of the four-channel algorithm for daytime data. The results were also compared to the current automated ash alarm used by AVO, based on the reverse absorption technique, also known as the split window method, with a threshold of -1.7K. This comparison indicates that the four- banded technique has a higher sensitivity to volcanic ash, but a greater number of false alarms. The algorithm was modified to achieve a false alarm rate comparable to current ash alarm while still maintaining increased sensitivity.

  13. Icing detection from Communication, Ocean and Meteorological Satellite and Himawari-8 data using machine learning approaches

    Science.gov (United States)

    Sim, S.; Park, H.; Im, J.; Park, S.

    2016-12-01

    Aircraft icing is a hazardous phenomenon which has potential to cause fatalities and socioeconomic losses. It is caused by super-cooled droplets (SCDs) colliding on the surface of aircraft frame when an aircraft flies through SCD rich clouds. When icing occurs, the aerodynamic balance of the aircraft is disturbed, resulting in a potential problem in aircraft operation. Thus, identification of potential icing clouds is crucial for aviation. Satellite remote sensing data such as Geostationary Operational Environmental Satellite (GOES) series have been widely used to detect potential icing clouds. An icing detection algorithm, operationally used in the US, consists of several thresholds of cloud optical depth, effective radius, and liquid water path based on the physical properties of icing. On the other hand, there is no operational icing detection algorithm in Asia, although there are several geostationary meteorological satellite sensors. In this study, we proposed machine learning-based models to detect icing over East Asia focusing on the Korean Peninsula using two geostationary satellite sensors—Meteorological Imager (MI) onboard Communication, Ocean and Meteorological Satellite (COMS) and Advanced Himawari Imager (AHI) onboard Himawari-8. While COMS MI provides data at 5 channels, Himawari-8 AHI has advanced capability of data collection, providing data at 16 channels. Instead of simple thresholding approaches used in the literature, we adopted two machine learning algorithms—decision trees (DT) and random forest (RF) to develop icing detection models based on Pilot REPorts (PIREPs) as reference data. Results show that the COMS icing detection model by RF produced a detection rate of 88.67% and a false alarm rate of 14.42%, which were improved when compared with the result of the direct application of the GOES algorithm to the COMS MI data (a detection rate of 20.83% and a false alarm rate of 25.44%). Although much higher accuracy (a detection rate > 95

  14. The HOAPS Climatology V4: updates and results from comparisons to various satellite, buoy and ship data records

    Science.gov (United States)

    Schroeder, Marc; Graw, Kathrin; Andersson, Axel; Fennig, Karsten; Bakan, Stephan; Klepp, Christian

    2017-04-01

    The global water cycle is a key component of the global climate system as it describes and links many important processes such as evaporation, convection, cloud formation and precipitation. Through latent heat release, it is also closely connected to the global energy cycle and its changes. The difference between precipitation and evaporation yields the freshwater flux, which indicates if a particular region of the earth receives more water through precipitation than it loses through evaporation or vice versa. On global scale and long time periods, however, the amounts of evaporation and precipitation are balanced. A profound understanding of the water cycle is therefore a key prerequisite for successful climate modelling. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) set is a fully satellite based climatology of precipitation, evaporation and freshwater budget as well as related turbulent heat fluxes and atmospheric state variables over the global ice free oceans. All geophysical parameters are derived from passive microwave radiometers, except for the SST, which is taken from AVHRR measurements based on thermal emission of the Earth. Starting with the release 3.1, the HOAPS climate data record is hosted by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) and the further development is shared with the University of Hamburg and the MPI-M. While the HOAPS release 3.2 in 2012 covered the entire record of the passive microwave radiometer SSM/I, the new version of the HOAPS data set, version 4, includes also the SSMIS record up to December 2014 and uncertainty estimates for parameters related to evaporation. These HOAPS data products are available as monthly averages and 6-hourly composites on a regular latitude/longitude grid with a spatial resolution of 0.5° x 0.5° from July 1987 to December 2014 (December 2008 for HOAPS3.2). Covering nearly 28 years the new HOAPS data set is highly valuable for climate

  15. Detection of ZY-3 Satellite Platform Jitter Using Multi-spectral Imagery

    Directory of Open Access Journals (Sweden)

    ZHU Ying

    2015-04-01

    Full Text Available Satellite platform jitter is one of the factors that affect the quality of high resolution imagery, which can cause image blur and internal distortion. Taking ZiYuan-3 (ZY-3 multi-spectral camera as a prototype, this paper proposes a satellite platform jitter detection method by utilizing multi-spectral imagery. First, imaging characteristics of multispectral camera and the main factors affecting band-to-band registration error are introduced. Then the regularity of registration error caused by platform jitter is analyzed by theoretical derivation and simulation. Meanwhile, the platform jitter detection method based on high accuracy dense points matching is presented. Finally, the experiments were conducted by using ZY-3 multi-spectral imagery captured in different time. The result indicates that ZY-3 has a periodic platform jitter about 0.6 Hz in the imaging period of test data, and the jitter amplitude across track is greater than that along track, which causes periodic band-to-band registration error with the same frequency. The result shows the possibility of the improvement in geometric processing accuracy for ZY-3 imagery products and provides an important reference for satellite platform jitter source analysis and satellite platform design optimization.

  16. Ground validation of oceanic snowfall detection in satellite climatologies during LOFZY

    Science.gov (United States)

    Klepp, Christian; Bumke, Karl; Bakan, Stephan; Bauer, Peter

    2010-08-01

    A thorough knowledge of global ocean precipitation is an indispensable prerequisite for the understanding of the water cycle in the global climate system. However, reliable detection of precipitation over the global oceans, especially of solid precipitation, remains a challenging task. This is true for both, passive microwave remote sensing and reanalysis based model estimates. The optical disdrometer ODM 470 is a ground validation instrument capable of measuring rain and snowfall on ships even under high wind speeds. It was used for the first time over the Nordic Seas during the LOFZY 2005 campaign. A dichotomous verification of precipitation occurrence resulted in a perfect correspondence between the disdrometer, a precipitation detector and a shipboard observer's log. The disdrometer data is further point-to-area collocated against precipitation from the satellite based Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data (HOAPS) climatology. HOAPS precipitation turns out to be overall consistent with the disdrometer data resulting in a detection accuracy of 0.96. The collocated data comprises light precipitation events below 1 mm h-1. Therefore two LOFZY case studies with high precipitation rates are presented that indicate plausible HOAPS satellite precipitation rates. Overall, this encourages longer term measurements of ship-to-satellite collocated precipitation in the near future.

  17. Detecting aircrafts from satellite images using saliency and conical pyramid based template representation

    Indian Academy of Sciences (India)

    SAMIK BANERJEE; NITIN GUPTA; SUKHENDU DAS; PINAKI ROY CHOWDHURY; L K SINHA

    2016-10-01

    Automatic target localization in satellite images still remains as a challenging problem in the field of computer vision. The issues involved in locating targets in satellite images are viewpoint, spectral (intensity) and scale variations. Diversity in background texture and target clutter also adds up to the complexity of the problem of localizing aircrafts in satellite images. Failure of modern feature extraction and object detection methods highlight the complexity of the problem. In the proposed work, pre-processing techniques, viz.denoising and contrast enhancement, are first used to improve the quality of the images. Then, the concept of unsupervised saliency is used to detect the potential regions of interest, which reduces the search space. Parts from the salient regions are further processed using clustering and morphological processing to get the probable regions of isolated aircraft targets. Finally, a novel conical pyramid based framework for template representation of the target samples is proposed for matching. Experimental results shown on a few satellite images exhibit the superior performance of the proposed methods.

  18. Plastic and Glass Greenhouses Detection and Delineation from WORLDVIEW-2 Satellite Imagery

    Science.gov (United States)

    Koc-San, D.; Sonmez, N. K.

    2016-06-01

    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.

  19. 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%.

  20. AUTOMATIC URBAN ILLEGAL BUILDING DETECTION USING MULTI-TEMPORAL SATELLITE IMAGES AND GEOSPATIAL INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    N. Khalili Moghadam

    2015-12-01

    Full Text Available With the unprecedented growth of urban population and urban development, we are faced with the growing trend of illegal building (IB construction. Field visit, as the currently used method of IB detection, is time and man power consuming, in addition to its high cost. Therefore, an automatic IB detection is required. Acquiring multi-temporal satellite images and using image processing techniques for automatic change detection is one of the optimum methods which can be used in IB monitoring. In this research an automatic method of IB detection has been proposed. Two-temporal panchromatic satellite images of IRS-P5 of the study area in a part of Tehran, the city map and an updated spatial database of existing buildings were used to detect the suspected IBs. In the pre-processing step, the images were geometrically and radiometrically corrected. In the next step, the changed pixels were detected using K-means clustering technique because of its quickness and less user’s intervention required. Then, all the changed pixels of each building were identified and the change percentage of each building with the standard threshold of changes was compared to detect the buildings which are under construction. Finally, the IBs were detected by checking the municipality database. The unmatched constructed buildings with municipal database will be field checked to identify the IBs. The results show that out of 343 buildings appeared in the images; only 19 buildings were detected as under construction and three of them as unlicensed buildings. Furthermore, the overall accuracies of 83%, 79% and 75% were obtained for K-means change detection, detection of under construction buildings and IBs detection, respectively.

  1. Indirect dark matter detection limits from the ultrafaint Milky Way satellite Segue 1

    Science.gov (United States)

    Essig, Rouven; Sehgal, Neelima; Strigari, Louis E.; Geha, Marla; Simon, Joshua D.

    2010-12-01

    We use new kinematic data from the ultrafaint Milky Way satellite Segue 1 to model its dark matter distribution and derive upper limits on the dark matter annihilation cross section. Using gamma-ray flux upper limits from the Fermi satellite and MAGIC, we determine cross section exclusion regions for dark matter annihilation into a variety of different particles including charged leptons. We show that these exclusion regions are beginning to probe the regions of interest for a dark matter interpretation of the electron and positron fluxes from PAMELA, Fermi, and HESS, and that future observations of Segue 1 have strong prospects for testing such an interpretation. We additionally discuss prospects for detecting annihilation with neutrinos using the IceCube detector, finding that in an optimistic scenario a few neutrino events may be detected. Finally, we use the kinematic data to model the Segue 1 dark matter velocity dispersion and constrain Sommerfeld enhanced models.

  2. Indirect Dark Matter Detection Limits from the Ultra-Faint Milky Way Satellite Segue 1

    Energy Technology Data Exchange (ETDEWEB)

    Essig, Rouven; /SLAC; Sehgal, Neelima; Strigari, Louis E.; /KIPAC, Menlo Park /Stanford U., Phys. Dept.; Geha, Marla; /Yale U.; Simon, Joshua D.; /Carnegie Inst. Observ.

    2011-08-11

    We use new kinematic data from the ultra-faint Milky Way satellite Segue 1 to model its dark matter distribution and derive upper limits on the dark matter annihilation cross-section. Using gamma-ray ux upper limits from the Fermi satellite and MAGIC, we determine cross-section exclusion regions for dark matter annihilation into a variety of different particles including charged leptons. We show that these exclusion regions are beginning to probe the regions of interest for a dark matter interpretation of the electron and positron uxes from PAMELA, Fermi, and HESS, and that future observations of Segue 1 have strong prospects for testing such an interpretation. We additionally discuss prospects for detecting annihilation with neutrinos using the IceCube detector, finding that in an optimistic scenario a few neutrino events may be detected. Finally we use the kinematic data to model the Segue 1 dark matter velocity dispersion and constrain Sommerfeld enhanced models.

  3. A weekly Arctic sea-ice thickness data record from merged CryoSat-2 and SMOS satellite data

    Science.gov (United States)

    Ricker, Robert; Hendricks, Stefan; Kaleschke, Lars; Tian-Kunze, Xiangshan; King, Jennifer; Haas, Christian

    2017-07-01

    Sea-ice thickness on a global scale is derived from different satellite sensors using independent retrieval methods. Due to the sensor and orbit characteristics, such satellite retrievals differ in spatial and temporal resolution as well as in the sensitivity to certain sea-ice types and thickness ranges. Satellite altimeters, such as CryoSat-2 (CS2), sense the height of the ice surface above the sea level, which can be converted into sea-ice thickness. Relative uncertainties associated with this method are large over thin ice regimes. Another retrieval method is based on the evaluation of surface brightness temperature (TB) in L-band microwave frequencies (1.4 GHz) with a thickness-dependent emission model, as measured by the Soil Moisture and Ocean Salinity (SMOS) satellite. While the radiometer-based method looses sensitivity for thick sea ice (> 1 m), relative uncertainties over thin ice are significantly smaller than for the altimetry-based retrievals. In addition, the SMOS product provides global sea-ice coverage on a daily basis unlike the altimeter data. This study presents the first merged product of complementary weekly Arctic sea-ice thickness data records from the CS2 altimeter and SMOS radiometer. We use two merging approaches: a weighted mean (WM) and an optimal interpolation (OI) scheme. While the weighted mean leaves gaps between CS2 orbits, OI is used to produce weekly Arctic-wide sea-ice thickness fields. The benefit of the data merging is shown by a comparison with airborne electromagnetic (AEM) induction sounding measurements. When compared to airborne thickness data in the Barents Sea, the merged product has a root mean square deviation (RMSD) of about 0.7 m less than the CS2 product and therefore demonstrates the capability to enhance the CS2 product in thin ice regimes. However, in mixed first-year (FYI) and multiyear (MYI) ice regimes as in the Beaufort Sea, the CS2 retrieval shows the lowest bias.

  4. A decadal satellite record of gravity wave activity in the lower stratosphere to study polar stratospheric cloud formation

    Science.gov (United States)

    Hoffmann, Lars; Spang, Reinhold; Orr, Andrew; Alexander, M. Joan; Holt, Laura A.; Stein, Olaf

    2017-02-01

    Atmospheric gravity waves yield substantial small-scale temperature fluctuations that can trigger the formation of polar stratospheric clouds (PSCs). This paper introduces a new satellite record of gravity wave activity in the polar lower stratosphere to investigate this process. The record is comprised of observations of the Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite from January 2003 to December 2012. Gravity wave activity is measured in terms of detrended and noise-corrected 15 µm brightness temperature variances, which are calculated from AIRS channels that are the most sensitive to temperature fluctuations at about 17-32 km of altitude. The analysis of temporal patterns in the data set revealed a strong seasonal cycle in wave activity with wintertime maxima at mid- and high latitudes. The analysis of spatial patterns indicated that orography as well as jet and storm sources are the main causes of the observed waves. Wave activity is closely correlated with 30 hPa zonal winds, which is attributed to the AIRS observational filter. We used the new data set to evaluate explicitly resolved temperature fluctuations due to gravity waves in the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis. It was found that the analysis reproduces orographic and non-orographic wave patterns in the right places, but that wave amplitudes are typically underestimated by a factor of 2-3. Furthermore, in a first survey of joint AIRS and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite observations, nearly 50 gravity-wave-induced PSC formation events were identified. The survey shows that the new AIRS data set can help to better identify such events and more generally highlights the importance of the process for polar ozone chemistry.

  5. 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.

  6. Low Complexity Multiuser Detection Algorithm for Multi-Beam Satellite Systems

    Institute of Scientific and Technical Information of China (English)

    Yang Wang; Danfeng Zhao; Xi Liao

    2015-01-01

    The minimum mean square error⁃successive interference cancellation ( MMSE⁃SIC ) multiuser detection algorithm has high complexity and long processing latency. A multiuser detection algorithm is proposed for multi⁃beam satellite systems in order to decrease the complexity and latency. The spot beams are grouped base on the distance between them in the proposed algorithm. Some groups are detected in parallel after a crucial group⁃wise interference cancellation. Furthermore, the multi⁃stage structure is introduced to improve the performance. Simulation results show that the proposed algorithm can achieve better performance with less complexity compared with the existing group detection algorithm. Moreover, the proposed algorithm using one stage can reduce the complexity over the fast MMSE⁃SIC and existing group detection algorithm by 9% and 20�9%. The processing latency is reduced significantly compared with the MMSE⁃SIC.

  7. 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

  8. Detection of Transionospheric SuperDARN HF Waves by the Radio Receiver Instrument on the enhanced Polar Outflow Probe Satellite

    Science.gov (United States)

    Gillies, R. G.; Yau, A. W.; James, H. G.; Hussey, G. C.; McWilliams, K. A.

    2014-12-01

    The enhanced Polar Outflow Probe (ePOP) Canadian small-satellite was launched in September 2013. Included in this suite of eight scientific instruments is the Radio Receiver Instrument (RRI). The RRI has been used to measure VLF and HF radio waves from various ground and spontaneous ionospheric sources. The first dedicated ground transmission that was detected by RRI was from the Saskatoon Super Dual Auroral Radar Network (SuperDARN) radar on Nov. 7, 2013 at 14 MHz. Several other passes over the Saskatoon SuperDARN radar have been recorded since then. Ground transmissions have also been observed from other radars, such as the SPEAR, HAARP, and SURA ionospheric heaters. However, the focus of this study will be on the results obtained from the SuperDARN passes. An analysis of the signal recorded by the RRI provides estimates of signal power, Doppler shift, polarization, absolute time delay, differential mode delay, and angle of arrival. By comparing these parameters to similar parameters derived from ray tracing simulations, ionospheric electron density structures may be detected and measured. Further analysis of the results from the other ground transmitters and future SuperDARN passes will be used to refine these results.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Mikhail Zhizhin

    2009-08-01

    Full Text Available 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 m3 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 billion. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO2e 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

  11. Tree detection in orchards from VHR satellite images using scale-space theory

    Science.gov (United States)

    Mahour, Milad; Tolpekin, Valentyn; Stein, Alfred

    2016-10-01

    This study focused on extracting reliable and detailed information from very High Resolution (VHR) satellite images for the detection of individual trees in orchards. The images contain detailed information on spectral and geometrical properties of trees. Their scale level, however, is insufficient for spectral properties of individual trees, because adjacent tree canopies interlock. We modeled trees using a bell shaped spectral profile. Identifying the brightest peak was challenging due to sun illumination effects caused 1 by differences in positions of the sun and the satellite sensor. Crown boundary detection was solved by using the NDVI from the same image. We used Gaussian scale-space methods that search for extrema in the scale-space domain. The procedures were tested on two orchards with different tree types, tree sizes and tree observation patterns in Iran. Validation was done using reference data derived from an UltraCam digital aerial photo. Local extrema of the determinant of the Hessian corresponded well to the geographical coordinates and the size of individual trees. False detections arising from a slight asymmetry of trees were distinguished from multiple detections of the same tree with different extents. Uncertainty assessment was carried out on the presence and spatial extents of individual trees. The study demonstrated how the suggested approach can be used for image segmentation for orchards with different types of trees. We concluded that Gaussian scale-space theory can be applied to extract information from VHR satellite images for individual tree detection. This may lead to improved decision making for irrigation and crop water requirement purposes in future studies.

  12. Best period for high spatial resolution satellite images for the detection of marks of buried structures

    Directory of Open Access Journals (Sweden)

    Dimitrios Kaimaris

    2012-06-01

    Full Text Available Improvements in sensor technology in recent decades led to the creation of ground, air and space imaging systems, whose data can be used in archaeological studies. Greece is one of the lucky areas that are rich in archaeological heritage. The detection of prehistoric/historic undiscovered constructions on satellite images or aerial photos is a complex and complicated matter. These marks are not visible from the ground, they can, however, be traced on satellite or aerial images, because of the differences in tone and texture. These differences appear as crop, soil and shadow marks. Undoubtedly, the detection of buried structures requires a suitable spatial resolution image, taken under appropriate meteorological conditions and during the best period of the vegetation growing cycle. According to the pertinent literature, detecting covered memorials may be achieved either accidentally or, usually, after a systematic investigation based on historical narratives. The purpose of this study is to determine the factors that facilitate or hinder the detection of buried structures through high spatial resolution satellite imagery. In this study, pan sharpened images from the QuickBird-2 satellite were used, of a spatial resolution of 0.60-0.70 m. This study concerns the detection of marks of the ancient Via Egnatia, from the ancient Amphipolis to Philippi (Eastern Macedonia, Greece. We studied different types of vegetation in the region and their phenological cycle. Taking into account the vegetation phenological cycle of the study area as well as the meteorological data, four pan sharpened QuickBird-2 images of a spatial resolution of 0.60–0.70 m. were used, during four different seasons. By processing the four images, we can determine the one acquired during the most appropriate conditions for the detection of buried structures. The application of this methodology in the study area had positive results, and not only was the main purpose of this

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

    DEFF Research Database (Denmark)

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

    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......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...... and through development of tailored retrackers dealing with presence of sea ice within the radar footprint, we can now develop sea surface height and its variation in most of the Arctic Ocean. We have processed 5 years of Cryosat-2 data quantified as either Lead or Ocean data within the Cryosat-2 SAR mask...

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

    DEFF Research Database (Denmark)

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

    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......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...... and through development of tailored retrackers dealing with presence of sea ice within the radar footprint, we can now develop sea surface height and its variation in most of the Arctic Ocean. We have processed 5 years of Cryosat-2 data quantified as either Lead or Ocean data within the Cryosat-2 SAR mask...

  15. Coherent detection of position errors in inter-satellite laser communications

    Science.gov (United States)

    Xu, Nan; Liu, Liren; Liu, De'an; Sun, Jianfeng; Luan, Zhu

    2007-09-01

    Due to the improved receiver sensitivity and wavelength selectivity, coherent detection became an attractive alternative to direct detection in inter-satellite laser communications. A novel method to coherent detection of position errors information is proposed. Coherent communication system generally consists of receive telescope, local oscillator, optical hybrid, photoelectric detector and optical phase lock loop (OPLL). Based on the system composing, this method adds CCD and computer as position error detector. CCD captures interference pattern while detection of transmission data from the transmitter laser. After processed and analyzed by computer, target position information is obtained from characteristic parameter of the interference pattern. The position errors as the control signal of PAT subsystem drive the receiver telescope to keep tracking to the target. Theoretical deviation and analysis is presented. The application extends to coherent laser rang finder, in which object distance and position information can be obtained simultaneously.

  16. 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...

  17. Learning Oriented Region-based Convolutional Neural Networks for Building Detection in Satellite Remote Sensing Images

    Science.gov (United States)

    Chen, C.; Gong, W.; Hu, Y.; Chen, Y.; Ding, Y.

    2017-05-01

    The automated building detection in aerial images is a fundamental problem encountered in aerial and satellite images analysis. Recently, thanks to the advances in feature descriptions, Region-based CNN model (R-CNN) for object detection is receiving an increasing attention. Despite the excellent performance in object detection, it is problematic to directly leverage the features of R-CNN model for building detection in single aerial image. As we know, the single aerial image is in vertical view and the buildings possess significant directional feature. However, in R-CNN model, direction of the building is ignored and the detection results are represented by horizontal rectangles. For this reason, the detection results with horizontal rectangle cannot describe the building precisely. To address this problem, in this paper, we proposed a novel model with a key feature related to orientation, namely, Oriented R-CNN (OR-CNN). Our contributions are mainly in the following two aspects: 1) Introducing a new oriented layer network for detecting the rotation angle of building on the basis of the successful VGG-net R-CNN model; 2) the oriented rectangle is proposed to leverage the powerful R-CNN for remote-sensing building detection. In experiments, we establish a complete and bran-new data set for training our oriented R-CNN model and comprehensively evaluate the proposed method on a publicly available building detection data set. We demonstrate State-of-the-art results compared with the previous baseline methods.

  18. 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.

  19. Neutron detection on the Foton-M2 satellite by a track etch detector stack.

    Science.gov (United States)

    Pálfalvi, J K; Szabó, J; Dudás, B

    2007-01-01

    In the frame of a European Space Agency (ESA) project called 'Biology and Physics in Space', a returning satellite, Foton-M2, was orbiting a container, the BIOPAN-5, loaded with biological experiments and facilities for radiation dosimetry (RADO) in the open space. One of the RADO experiments was dedicated to the detection of the primary cosmic rays and secondary neutrons by a track etch detector stack. The system was calibrated at high-energy particle accelerators and neutron generators. The developed detectors were investigated by an image analyser, and from the track parameters the linear energy transfer spectra and the absorbed dose were determined (26 microGy/d). Also, the neutron flux was estimated below 5 MeV and found to be 2.4 cm(-2) s(-1) directly from the space. The construction of the stack allowed to investigate the neutrons also from the direction of the carrying satellite, where the flux was found somewhat higher.

  20. 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...... are conducted, and it is shown that plumes from major Danish source areas can be detected in all wind directions, and that pollution transported from Europe is seen when the wind has a southern component. Examples of day to day tracking of transport of NO2 are also given to explain two pollution episodes...... stations in the Danish Air Quality Measurement network to find correlation between the two datasets. Clear weekly and annual cycles are found in both datasets and they are shown to be significantly correlated, though with a low correlation coefficient. Analyses of the patterns in different wind directions...

  1. Satellite Image Edge Detection for Population Distribution Pattern Identification using Levelset with Morphological Filtering Process

    Science.gov (United States)

    Harsiti; Munandar, T. A.; Suhendar, A.; Abdullah, A. G.; Rohendi, D.

    2017-03-01

    Population distribution pattern is directly related with economic gap of a region. Analysis of population distribution pattern is usually performed by studying statistical data on population. This study aimed to analyze population distribution pattern using image analysis concept, i.e. using satellite images. Levelset and morphological image filtering methods were used to analyze images to see distribution pattern. The research result showed that Levelset and morphological image filtering could remove a lot of noises in analysis result images and form object edge contours very clearly. The detected object contours were used as references to recognize population distribution pattern based on satellite image analysis. The pattern made based on the research result didn’t show optimal result because Levelset performed image segmentation based on the contours of the analyzed objects. Other segmentation methods should be combined with it to produce clearer population distribution pattern.

  2. Detection of the urban heat island in Beijing using HJ-1B satellite imagery

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Satellite images are used extensively in studying the urban heat island(UHI) phenomenon.We evaluated the suitability of thermal infrared(TIR) data from the HJ-1B satellite for detecting UHI using a case study in Beijing.Two modified algorithms for retrieving the land surface temperature(LST) from HJ-1B data were tested.The results were compared with LST images derived from a Landsat TM thermal band and the MODIS LST output.The spatial pattern of UHI generated using HJ-1B data matched well with that produced using TM and MODIS data.Of the two algorithms,the mono-window algorithm performed better but further tests are necessary.With more frequent coverage than TM and higher spatial resolution than MODIS,the HJ-1B TIR data present a unique opportunity to study thermal environments in cities in China and neighboring countries.

  3. Appearance learning for 3D pose detection of a satellite at close-range

    Science.gov (United States)

    Oumer, Nassir W.; Kriegel, Simon; Ali, Haider; Reinartz, Peter

    2017-03-01

    In this paper we present a learning-based 3D detection of a highly challenging specular object exposed to a direct sunlight at very close-range. An object detection is one of the most important areas of image processing, and can also be used for initialization of local visual tracking methods. While the object detection in 3D space is generally a difficult problem, it poses more difficulties when the object is specular and exposed to the direct sunlight as in a space environment. Our solution to a such problem relies on an appearance learning of a real satellite mock-up based on a vector quantization and the vocabulary tree. Our method, implemented on a standard computer (CPU), exploits a full perspective projection model and provides near real-time 3D pose detection of a satellite for close-range approach and manipulation. The time consuming part of the training (feature description, building the vocabulary tree and indexing, depth buffering and back-projection) are performed offline, while a fast image retrieval and 3D-2D registration are performed on-line. In contrast, the state of the art image-based 3D pose detection methods are slower on CPU or assume a weak perspective camera projection model. In our case the dimension of the satellite is larger than the distance to the camera, hence the assumption of the weak perspective model does not hold. To evaluate the proposed method, the appearance of a full scale mock-up of the rear part of the TerraSAR-X satellite is trained under various illumination and camera views. The training images are captured with a camera mounted on six degrees of freedom robot, which enables to position the camera in a desired view, sampled over a sphere. The views that are not within the workspace of the robot are interpolated using image-based rendering. Moreover, we generate ground truth poses to verify the accuracy of the detection algorithm. The achieved results are robust and accurate even under noise due to specular reflection

  4. Detection of Burn Area and Severity with MODIS Satellite Images and Spatial Autocorrelation Techniques

    Science.gov (United States)

    Kaya, S.; Kavzoglu, T.; Tonbul, H.

    2014-12-01

    Effects of forest fires and implications are one of the most important natural disasters all over the world. Statistical data observed that forest fires had a variable structure in the last century in Turkey, but correspondingly the population growth amount of forest fires and burn area increase widely in recent years. Depending on this, erosion, landslides, desertification and mass loss come into existence. In addition; after forest fires, renewal of forests and vegetation are very important for land management. Classic methods used for detection of burn area and severity requires a long and challenging process due to time and cost factors. Thanks to advanced techniques used in the field of Remote Sensing, burn area and severity can be determined with high detail and precision. The purpose of this study based on blending MODIS (Moderate Resolution Imaging Spectradiometer) satellite images and spatial autocorrelation techniques together, thus detect burn area and severity absolutely. In this context, spatial autocorrelation statistics like Moran's I and Get is-Ord Local Gi indexes were used to measure and analyze to burned area characteristics. Prefire and postfire satellite images were used to determine fire severity depending on spectral indexes corresponding to biomass loss and carbon emissivity intensities. Satellite images have used for identification of fire damages and risks in terms of fire management for a long time. This study was performed using prefire and postfire satellite images and spatial autocorrelation techniques to determining and analyzing forest fires in Antalya, Turkey region which serious fires occurred. In this context, this approach enables the characterization of distinctive texture of burned area and helps forecasting more precisely. Finally, it is observed that mapping of burned area and severity could be performed from local scale to national scale. Key Words: Spatial autocorrelation, MODIS, Fire, Burn Severity

  5. 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

  6. Development of a fire detection algorithm for the COMS (Communication Ocean and Meteorological Satellite)

    Science.gov (United States)

    Kim, Goo; Kim, Dae Sun; Lee, Yang-Won

    2013-10-01

    The forest fires do much damage to our life in ecological and economic aspects. South Korea is probably more liable to suffer from the forest fire because mountain area occupies more than half of land in South Korea. They have recently launched the COMS(Communication Ocean and Meteorological Satellite) which is a geostationary satellite. In this paper, we developed forest fire detection algorithm using COMS data. Generally, forest fire detection algorithm uses characteristics of 4 and 11 micrometer brightness temperature. Our algorithm additionally uses LST(Land Surface Temperature). We confirmed the result of our fire detection algorithm using statistical data of Korea Forest Service and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. We used the data in South Korea On April 1 and 2, 2011 because there are small and big forest fires at that time. The detection rate was 80% in terms of the frequency of the forest fires and was 99% in terms of the damaged area. Considering the number of COMS's channels and its low resolution, this result is a remarkable outcome. To provide users with the result of our algorithm, we developed a smartphone application for users JSP(Java Server Page). This application can work regardless of the smartphone's operating system. This study can be unsuitable for other areas and days because we used just two days data. To improve the accuracy of our algorithm, we need analysis using long-term data as future work.

  7. Monitoring and remote failure detection of grid-connected PV systems based on satellite observations

    Energy Technology Data Exchange (ETDEWEB)

    Drews, A.; Lorenz, E.; Betcke, J.; Heinemann, D. [Oldenburg University, Institute of Physics, Carl-von-Ossietzky-Str. 9-11, 26129 Oldenburg (Germany); de Keizer, A.C.; van Sark, W.G.J.H.M. [University of Utrecht, Copernicus Institute, Department of Science, Technology, and Society, Heidelberglaan 2, 3584 CH Utrecht (Netherlands); Beyer, H.G. [University of Applied Sciences Magdeburg-Stendal (FH), Institute of Electrical Engineering, Breitscheidstr. 2, 39114 Magdeburg (Germany); Heydenreich, W.; Wiemken, E. [Fraunhofer Institute for Solar Energy Systems, Heidenhofstr. 2, 79110 Freiburg (Germany); Stettler, S.; Toggweiler, P. [Enecolo AG, Lindhofstr. 52, 8617 Moenchaltorf (Switzerland); Bofinger, S.; Schneider, M.; Heilscher, G. [Meteocontrol GmbH, Spicherer Strasse 48, 86157 Augsburg (Germany)

    2007-04-15

    Small grid-connected photovoltaic systems up to 5 kW{sub p} are often not monitored because advanced surveillance systems are not economical. Hence, some system failures which lead to partial energy losses stay unnoticed for a long time. Even a failure that results in a larger energy deficit can be difficult to detect by PV laymen due to the fluctuating energy yields. Within the EU project PVSAT-2, a fully automated performance check has been developed to assure maximum energy yields and to optimize system maintenance for small grid-connected PV systems. The aim is the early detection of system malfunctions and changing operating conditions to prevent energy and subsequent financial losses for the operator. The developed procedure is based on satellite-derived solar irradiance information that replaces on-site measurements. In conjunction with a simulation model the expected energy yield of a PV system is calculated. In case of the occurrence of a defined difference between the simulated and actual energy yield, an automated failure detection routine searches for the most probable failure sources and notifies the operator. This paper describes the individual components of the developed procedure - the satellite-derived irradiance, the used PV simulation model, and the principles of the automated failure detection routine. Moreover, it presents results of an 8-months test phase with 100 PV systems in three European countries. (author)

  8. Accelerating Satellite Image Based Large-Scale Settlement Detection with GPU

    Energy Technology Data Exchange (ETDEWEB)

    Patlolla, Dilip Reddy [ORNL; Cheriyadat, Anil M [ORNL; Weaver, Jeanette E [ORNL; Bright, Eddie A [ORNL

    2012-01-01

    Computer vision algorithms for image analysis are often computationally demanding. Application of such algorithms on large image databases\\---- such as the high-resolution satellite imagery covering the entire land surface, can easily saturate the computational capabilities of conventional CPUs. There is a great demand for vision algorithms running on high performance computing (HPC) architecture capable of processing petascale image data. We exploit the parallel processing capability of GPUs to present a GPU-friendly algorithm for robust and efficient detection of settlements from large-scale high-resolution satellite imagery. Feature descriptor generation is an expensive, but a key step in automated scene analysis. To address this challenge, we present GPU implementations for three different feature descriptors\\-- multiscale Historgram of Oriented Gradients (HOG), Gray Level Co-Occurrence Matrix (GLCM) Contrast and local pixel intensity statistics. We perform extensive experimental evaluations of our implementation using diverse and large image datasets. Our GPU implementation of the feature descriptor algorithms results in speedups of 220 times compared to the CPU version. We present an highly efficient settlement detection system running on a multiGPU architecture capable of extracting human settlement regions from a city-scale sub-meter spatial resolution aerial imagery spanning roughly 1200 sq. kilometers in just 56 seconds with detection accuracy close to 90\\%. This remarkable speedup gained by our vision algorithm maintaining high detection accuracy clearly demonstrates that such computational advancements clearly hold the solution for petascale image analysis challenges.

  9. Vehicle detection in WorldView-2 satellite imagery based on Gaussian modeling and contextual learning

    Science.gov (United States)

    Shen, Bichuan; Chen, Chi-Hau; Marchisio, Giovanni B.

    2012-06-01

    In this paper, we aim to study the detection of vehicles from WorldView-2 satellite imagery. For this purpose, accurate modeling of vehicle features and signatures and efficient learning of vehicle hypotheses are critical. We present a joint Gaussian and maximum likelihood based modeling and machine learning approach using SVM and neural network algorithms to describe the local appearance densities and classify vehicles from non-vehicle buildings, objects, and backgrounds. Vehicle hypotheses are fitted by elliptical Gaussians and the bottom-up features are grouped by Gabor orientation filtering based on multi-scale analysis and distance transform. Global contextual information such as road networks and vehicle distributions can be used to enhance the recognition. In consideration of the problem complexity the practical vehicle detection task faces due to dense and overlapping vehicle distributions, partial occlusion and clutters by building, shadows, and trees, we employ a spectral clustering strategy jointly combined with bootstrapped learning to estimate the parameters of centroid, orientation, and extents for local densities. We demonstrate a high detection rate 94.8%,with a missing rate 5.2% and a false alarm rate 5.3% on the WorldView-2 satellite imagery. Experimental results show that our method is quite effective to model and detect vehicles.

  10. Oil Palm Tree Detection with High Resolution Multi-Spectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Panu Srestasathiern

    2014-10-01

    Full Text Available Oil palm tree is an important cash crop in Thailand. To maximize the productivity from planting, oil palm plantation managers need to know the number of oil palm trees in the plantation area. In order to obtain this information, an approach for palm tree detection using high resolution satellite images is proposed. This approach makes it possible to count the number of oil palm trees in a plantation. The process begins with the selection of the vegetation index having the highest discriminating power between oil palm trees and background. The index having highest discriminating power is then used as the primary feature for palm tree detection. We hypothesize that oil palm trees are located at the local peak within the oil palm area. To enhance the separability between oil palm tree crowns and background, the rank transformation is applied to the index image. The local peak on the enhanced index image is then detected by using the non-maximal suppression algorithm. Since both rank transformation and non-maximal suppression are window based, semi-variogram analysis is used to determine the appropriate window size. The performance of the proposed method was tested on high resolution satellite images. In general, our approach uses produced very accurate results, e.g., about 90 percent detection rate when compared with manual labeling.

  11. Evaluation of algorithms for fire detection and mapping across North America from satellite

    Science.gov (United States)

    Li, Zhanqing; Fraser, R.; Jin, J.; Abuelgasim, A. A.; Csiszar, I.; Gong, P.; Pu, R.; Hao, W.

    2003-01-01

    This paper presents an evaluation of advanced very high resolution radiometer (AVHRR)-based remote sensing algorithms for detecting active vegetation fires [, 2000a] and mapping burned areas [, 2000] throughout North America. The procedures were originally designed for application in Canada with AVHRR data aboard the NOAA 14 satellite. They were tested here with both NOAA 11 and NOAA 14 covering the period 1989-2000. It was found that the active fire detection algorithm performs well with low commission and omission error rates over forested regions in the absence of cloud cover. Moderate errors were found over semi-arid areas covered by thin clouds, as well as along rivers and around lakes observed from sun-glint angles. A modification to a fire algorithm threshold and the addition of a new test can significantly improve the detection accuracy. Burned areas mapped by satellite were compared against extensive fire polygon data acquired by U.S. forest agencies in five western states. The satellite-based mapping matches nearly 90% of total forested burned area, with the difference being mainly attributable to omission of some nonburned islands and patches within the fire polygons. In addition, it maps a significant area of burning outside the fire polygons that appear to be true fires. The 10% omission error was found to be caused mainly by three factors: lack or insufficient number of active fires, partial burning, and vegetation recovery after early season burning. In addition to total area, the location and shapes of burned scars are consistent with the ground-based maps. Overall, the two algorithms are competent for detecting and mapping forest fires in North America north of Mexico with minor modifications.

  12. 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.

  13. Validation of the Global NASA Satellite-based Flood Detection System in Bangladesh

    Science.gov (United States)

    Moffitt, C. B.

    2009-12-01

    Floods are one of the most destructive natural forces on earth, affecting millions of people annually. Nations lying in the downstream end of an international river basin often suffer the most damage during flooding and could benefit from the real-time communication of rainfall and stream flow data from countries upstream. This is less likely to happen among developing nations due to a lack of freshwater treaties (Balthrop and Hossain, Water Policy, 2009). A more viable option is for flood-prone developing nations to utilize the global satellite rainfall and modeled runoff data that is independently and freely available from the NASA Satellite-based Global Flood Detection System. Although the NASA Global Flood Detection System has been in operation in real-time since 2006, the ‘detection’ capability of flooding has only been validated against qualitative reports in news papers and other types of media. In this study, a more quantitative validation against in-situ measurements of the flood detection system over Bangladesh is presented. Using ground-measured stream flow data as well as satellite-based flood potential and rainfall data, the study looks into the relationship between rainfall and flood potential, rainfall and stream flow, and stream flow and flood potential for three very distinct river systems in Bangladesh - 1) Ganges- a snow-fed river regulated by upstream India 2) Brahmaputra - a snow-fed river that is also braided 3) Meghna - a rain-fed river. The quantitative assessment will show the effectiveness of the NASA Global Flood Detection System for a very humid and flood prone region like Bangladesh that is also faced with tremendous transboundary hurdles that can only be resolved from the vantage of space.

  14. Automatic cloud detection for high resolution satellite stereo images and its application in terrain extraction

    Science.gov (United States)

    Wu, Teng; Hu, Xiangyun; Zhang, Yong; Zhang, Lulin; Tao, Pengjie; Lu, Luping

    2016-11-01

    The automatic extraction of terrain from high-resolution satellite optical images is very difficult under cloudy conditions. Therefore, accurate cloud detection is necessary to fully use the cloud-free parts of images for terrain extraction. This paper addresses automated cloud detection by introducing an image matching based method under a stereo vision framework, and the optimization usage of non-cloudy areas in stereo matching and the generation of digital surface models (DSMs). Given that clouds are often separated from the terrain surface, cloudy areas are extracted by integrating dense matching DSM, worldwide digital elevation model (DEM) (i.e., shuttle radar topography mission (SRTM)) and gray information from the images. This process consists of the following steps: an image based DSM is firstly generated through a multiple primitive multi-image matcher. Once it is aligned with the reference DEM based on common features, places with significant height differences between the DSM and the DEM will suggest the potential cloud covers. Detecting cloud at these places in the images then enables precise cloud delineation. In the final step, elevations of the reference DEM within the cloud covers are assigned to the corresponding region of the DSM to generate a cloud-free DEM. The proposed approach is evaluated with the panchromatic images of the Tianhui satellite and has been successfully used in its daily operation. The cloud detection accuracy for images without snow is as high as 95%. Experimental results demonstrate that the proposed method can significantly improve the usage of the cloudy panchromatic satellite images for terrain extraction.

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

    Science.gov (United States)

    Kim, E. J.

    2011-12-01

    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, 2011. 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.

  16. Automated electronic medical record sepsis detection in the emergency department

    OpenAIRE

    Su Q. Nguyen; Edwin Mwakalindile; Booth, James S.; Vicki Hogan; Jordan Morgan; Prickett, Charles T; Donnelly, John P; Wang, Henry E.

    2014-01-01

    Background. While often first treated in the emergency department (ED), identification of sepsis is difficult. Electronic medical record (EMR) clinical decision tools offer a novel strategy for identifying patients with sepsis. The objective of this study was to test the accuracy of an EMR-based, automated sepsis identification system. Methods. We tested an EMR-based sepsis identification tool at a major academic, urban ED with 64,000 annual visits. The EMR system collected vital sign and lab...

  17. Automated electronic medical record sepsis detection in the emergency department

    OpenAIRE

    Nguyen, Su Q.; Edwin Mwakalindile; Booth, James S.; Vicki Hogan; Jordan Morgan; Prickett, Charles T; Donnelly, John P.; Wang, Henry E.

    2014-01-01

    Background. While often first treated in the emergency department (ED), identification of sepsis is difficult. Electronic medical record (EMR) clinical decision tools offer a novel strategy for identifying patients with sepsis. The objective of this study was to test the accuracy of an EMR-based, automated sepsis identification system. Methods. We tested an EMR-based sepsis identification tool at a major academic, urban ED with 64,000 annual visits. The EMR system collected vital sign and lab...

  18. Automated electronic medical record sepsis detection in the Emergency Department

    OpenAIRE

    Nguyen, Su; Mwakalindile, Edwin; Booth, James S.; Hogan, Vicki; Morgan, Jordan; Prickett, Charles T; Donnelly, John P.; Wang, Henry E.

    2014-01-01

    Background: While often first treated in the Emergency Department (ED), identification of sepsis is difficult. Electronic medical record (EMR) clinical decision tools offer a novel strategy for identifying patients with sepsis. The objective of this study was to test the accuracy of an EMR-based, automated sepsis identification system. Methods : We tested an EMR-based sepsis identification tool at a major academic, urban ED with 64,000 annual visits. The EMR system collected vital sign and la...

  19. Origins and features of oil slicks in the Bohai Sea detected from satellite SAR images.

    Science.gov (United States)

    Ding, Yi; Cao, Conghua; Huang, Juan; Song, Yan; Liu, Guiyan; Wu, Lingjuan; Wan, Zhenwen

    2016-05-15

    Oil slicks were detected using satellite Synthetic Aperture Radar (SAR) images in 2011. We investigated potential origins and regional and seasonal features of oil slick in the Bohai Sea. Distance between oil slicks and potential origins (ships, seaports, and oil exploitation platforms) and the angle at which oil slicks move relative to potential driving forces were evaluated. Most oil slicks were detected along main ship routes rather than around seaports and oil exploitation platforms. Few oil slicks were detected within 20km of seaports. Directions of oil slicks movement were much more strongly correlated with directions of ship routes than with directions of winds and currents. These findings support the premise that oil slicks in the Bohai Sea most likely originate from illegal disposal of oil-polluted wastes from ships. Seasonal variation of oil slicks followed an annual cycle, with a peak in August and a trough in December.

  20. 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.

  1. 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

  2. Self-assembly of core-satellite gold nanoparticles for colorimetric detection of copper ions.

    Science.gov (United States)

    Weng, Ziqing; Wang, Hongbin; Vongsvivut, Jitraporn; Li, Runqing; Glushenkov, Alexey M; He, Jin; Chen, Ying; Barrow, Colin J; Yang, Wenrong

    2013-11-25

    Molecule-coated nanoparticles are hybrid materials which can be engineered with novel properties. The molecular coating of metal nanoparticles can provide chemical functionality, enabling assembly of the nanoparticles that are important for applications, such as biosensing devices. Herein, we report a new self-assembly of core-satellite gold nanoparticles linked by a simple amino acid l-Cysteine for biosensing of Cu(2+). The plasmonic properties of core-satellite nano-assemblies were investigated, a new red shifted absorbance peak from about 600 to 800 nm was found, with specific wavelength depending on ratios with assembly of large and small gold nanoparticles. The spectral features obtained using surface-enhanced Raman spectroscopy (SERS) provided strong evidence for the assembly of the Cu(2+) ions to the L-Cysteine molecules leading to the successful formation of the core-satellite Cu(l-Cysteine) complex on the gold surfaces. In addition, a linear relationship between the concentration of mediating Cu(2+) and absorbance of self-assembled gold nanoparticles (GNPs) at 680 nm was obtained. These results strongly address the potential strategy for applying the functionalized GNPs as novel biosensing tools in trace detections of certain metal ions.

  3. A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT)

    Science.gov (United States)

    Wang, Xi; Guo, Zheng; Huang, Yipeng; Fan, Hongjie; Li, Wanbiao

    2017-01-01

    Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite (TANSAT), a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager (CAPI), which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloudscreening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer (VIRR) onboard the Chinese FengYun-3A Polar-orbiting Meteorological Satellite (FY-3A), which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas (desert, snow, ocean, forest) for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.

  4. Effects of sea ice cover on satellite-detected primary production in the Arctic Ocean.

    Science.gov (United States)

    Kahru, Mati; Lee, Zhongping; Mitchell, B Greg; Nevison, Cynthia D

    2016-11-01

    The influence of decreasing Arctic sea ice on net primary production (NPP) in the Arctic Ocean has been considered in multiple publications but is not well constrained owing to the potentially large errors in satellite algorithms. In particular, the Arctic Ocean is rich in coloured dissolved organic matter (CDOM) that interferes in the detection of chlorophyll a concentration of the standard algorithm, which is the primary input to NPP models. We used the quasi-analytic algorithm (Lee et al 2002 Appl. Opti. 41, 5755-5772. (doi:10.1364/AO.41.005755)) that separates absorption by phytoplankton from absorption by CDOM and detrital matter. We merged satellite data from multiple satellite sensors and created a 19 year time series (1997-2015) of NPP. During this period, both the estimated annual total and the summer monthly maximum pan-Arctic NPP increased by about 47%. Positive monthly anomalies in NPP are highly correlated with positive anomalies in open water area during the summer months. Following the earlier ice retreat, the start of the high-productivity season has become earlier, e.g. at a mean rate of -3.0 d yr(-1) in the northern Barents Sea, and the length of the high-productivity period has increased from 15 days in 1998 to 62 days in 2015. While in some areas, the termination of the productive season has been extended, owing to delayed ice formation, the termination has also become earlier in other areas, likely owing to limited nutrients.

  5. Indirect Dark Matter detection from Dwarf satellites: joint expectations from astrophysics and supersymmetry

    Energy Technology Data Exchange (ETDEWEB)

    Martinez, Gregory D.; Bullock, James S.; Kaplinghat, Manoj [Center for Cosmology, Department of Physics and Astronomy, University of California, Irvine, CA 92697 (United States); Strigari, Louis E. [Kavli Institute for Particle Astrophysics and Cosmology, Physics Department, Stanford University, Stanford, CA 94305 (United States); Trotta, Roberto, E-mail: gmartine@uci.edu, E-mail: bullock@uci.edu, E-mail: mkapling@uci.edu, E-mail: strigari@stanford.edu, E-mail: r.trotta@imperial.ac.uk [Imperial College London, Astrophysics Group, Blackett Laboratory, Prince Consort Road, London SW7 2AZ (United Kingdom)

    2009-06-01

    We present a general methodology for determining the gamma-ray flux from annihilation of dark matter particles in Milky Way satellite galaxies, focusing on two promising satellites as examples: Segue 1 and Draco. We use the SuperBayeS code to explore the best-fitting regions of the Constrained Minimal Supersymmetric Standard Model (CMSSM) parameter space, and an independent MCMC analysis of the dark matter halo properties of the satellites using published radial velocities. We present a formalism for determining the boost from halo substructure in these galaxies and show that its value depends strongly on the extrapolation of the concentration-mass (c(M)) relation for CDM subhalos down to the minimum possible mass. We show that the preferred region for this minimum halo mass within the CMSSM with neutralino dark matter is ∼ 10{sup −9}–10{sup −6} M{sub s}un. For the boost model where the observed power-law c(M) relation is extrapolated down to the minimum halo mass we find average boosts of about 20, while the Bullock et al (2001) c(M) model results in boosts of order unity. We estimate that for the power-law c(M) boost model and photon energies greater than a GeV, the Fermi space-telescope has about 20% chance of detecting a dark matter annihilation signal from Draco with signal-to-noise greater than 3 after about 5 years of observation.

  6. 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.

  7. 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.

  8. 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...

  9. A neocentromere on human chromosome 3 without detectable alpha-satellite DNA forms morphologically normal kinetochores

    DEFF Research Database (Denmark)

    Wandall, A; Tranebjaerg, L; Tommerup, Niels

    1998-01-01

    A neocentromere at 3q26 was observed in a father and his daughter on a chromosome 3 with deleted centromeric region. No alpha-satellite DNA was detectable at the 3q26 neocentromere, but it was weakly positive with anticentromere (CREST) antibodies. Electron microscopy showed that the neocentromere...... formed microtubule-associated kinetochores with normal morphology and of the same size as the kinetochores of other large chromosomes. The deleted centromere formed a small linear marker chromosome that reacted strongly with anticentromere antibodies, but showed reduced kinetochore size. The 3q26...

  10. Satellite propulsion spectral signature detection and analysis through Hall effect thruster plume and atmospheric modeling

    Science.gov (United States)

    Wheeler, Pamela; Cobb, Richard; Hartsfield, Carl; Prince, Benjamin

    2016-09-01

    Space Situational Awareness (SSA) is of utmost importance in today's congested and contested space environment. Satellites must perform orbital corrections for station keeping, devices like high efficiency electric propulsion systems such as a Hall effect thrusters (HETs) to accomplish this are on the rise. The health of this system is extremely important to ensure the satellite can maintain proper position and perform its intended mission. Electron temperature is a commonly used diagnostic to determine the efficiency of a hall thruster. Recent papers have coordinated near infrared (NIR) spectral measurements of emission lines in xenon and krypton to electron temperature measurements. Ground based observations of these spectral lines could allow the health of the thruster to be determined while the satellite is in operation. Another issue worth considering is the availability of SSA assets for ground-based observations. The current SSA architecture is limited and task saturated. If smaller telescopes, like those at universities, could successfully detect these signatures they could augment data collection for the SSA network. To facilitate this, precise atmospheric modeling must be used to pull out the signature. Within the atmosphere, the NIR has a higher transmission ratio and typical HET propellants are approximately 3x the intensity in the NIR versus the visible spectrum making it ideal for ground based observations. The proposed research will focus on developing a model to determine xenon and krypton signatures through the atmosphere and estimate the efficacy through ground-based observations. The model will take power modes, orbit geometries, and satellite altitudes into consideration and be correlated with lab and field observations.

  11. Detecting single DNA molecule interactions with optical microcavities (Presentation Recording)

    Science.gov (United States)

    Vollmer, Frank

    2015-09-01

    Detecting molecules and their interactions lies at the heart of all biosensor devices, which have important applications in health, environmental monitoring and biomedicine. Achieving biosensing capability at the single molecule level is, moreover, a particularly important goal since single molecule biosensors would not only operate at the ultimate detection limit by resolving individual molecular interactions, but they could also monitor biomolecular properties which are otherwise obscured in ensemble measurements. For example, a single molecule biosensor could resolve the fleeting interaction kinetics between a molecule and its receptor, with immediate applications in clinical diagnostics. We have now developed a label-free biosensing platform that is capable of monitoring single DNA molecules and their interaction kinetics[1], hence achieving an unprecedented sensitivity in the optical domain, Figure 1. We resolve the specific contacts between complementary oligonucleotides, thereby detecting DNA strands with less than 2.4 kDa molecular weight. Furthermore we can discern strands with single nucleotide mismatches by monitoring their interaction kinetics. Our device utilizes small glass microspheres as optical transducers[1,2, 3], which are capable of increasing the number of interactions between a light beam and analyte molecules. A prism is used to couple the light beam into the microsphere. Ourr biosensing approach resolves the specific interaction kinetics between single DNA fragments. The optical transducer is assembled in a simple three-step protocol, and consists of a gold nanorod attached to a glass microsphere, where the surface of the nanorod is further modified with oligonucleotide receptors. The interaction kinetics of an oligonucleotide receptor with DNA fragments in the surrounding aqueous solution is monitored at the single molecule level[1]. The light remains confined inside the sphere where it is guided by total internal reflections along a

  12. Potential application of Kanade-Lucas-Tomasi tracker on satellite images for automatic change detection

    Science.gov (United States)

    Ahmed, Tasneem; Singh, Dharmendra; Raman, Balasubramanian

    2016-04-01

    Monitoring agricultural areas is still a very challenging task. Various models and methodologies have been developed for monitoring the agricultural areas with satellite images, but their practical applicability is limited due to the complexity in processing and dependence on a priori information. Therefore, in this paper, an attempt has been made to investigate the utility of the Kanade-Lucas-Tomasi (KLT) tracker, which is generally useful for tracking objects in video images, for monitoring agricultural areas. The KLT tracker was proposed to deal with the problem of image registration, but the use of the KLT tracker in satellite images for land cover monitoring is rarely reported. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) data has been used to identify and track the agricultural areas. The tracked pixels were compared with the agriculture pixels obtained from a decision tree algorithm and both results are closely matched. An image differencing change detection technique has been applied after KLT tracker implementation to observe the "change" and "no change" pixels in agricultural areas. It is observed that two kinds of changes are being detected. The areas where agriculture was not there earlier, but now is present, the changes are called positive changes. In the areas where agriculture was present earlier, but now is not present, those changes are referred to as negative changes. Unchanged areas retrieved from both the images are labeled as "no change" pixels. The novelty of the proposed algorithm is that it uses a simplified version of the KLT tracker to efficiently select and track the agriculture features on the basis of their spatial information and does not require a priori information every time.

  13. Amazon Rainforest Deforestation Daily Detection Tool Using Artificial Neural Networks and Satellite Images

    Directory of Open Access Journals (Sweden)

    Silvio César Cazella

    2012-10-01

    Full Text Available The main purpose of this work was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA [1] sensor and Artificial Neural Networks. The developed tool provides the parameterization of the configuration for the neural network training to enable us to find the best neural architecture to address the problem. The tool makes use of confusion matrixes to determine the degree of success of the network. Part of the municipality of Porto Velho, in Rondônia state, is located inside the tile H11V09 of the MODIS/TERRA sensor, which was used as the study area. A spectrum-temporal analysis of this area was made on 57 images from 20 of May to 15 of July 2003 using the trained neural network. This analysis allowed us to verify the quality of the implemented neural network classification as well as helping our understanding of the dynamics of deforestation in the Amazon rainforest. The great potential of neural networks for image classification was perceived with this work. However, the generation of consistent alarms, in other words, detecting predatory actions at the beginning; instead of firing false alarms is a complex task that has not yet been solved. Therefore, the major contribution of this paper is to provide a theoretical basis and practical use of neural networks and satellite images to combat illegal deforestation.

  14. Persistent scatterers detection on synthetic aperture radar images acquired by Sentinel-1 satellite

    Science.gov (United States)

    Dǎnişor, Cosmin; Popescu, Anca; Datcu, Mihai

    2016-12-01

    Persistent Scatterers Interferometry (PS-InSAR) has become a popular method in remote sensing because of its capability to measure terrain deformations with very high accuracy. It relies on multiple Synthetic Aperture Radar (SAR) acquisitions, to monitor points with stable proprieties over time, called Persistent Scatterers (PS)[1]. These points are unaffected by temporal decorrelation, therefore by analyzing their interferometric phase variation we can estimate the scene's deformation rates within a given time interval. In this work, we apply two incoherent detection algorithms to identify Persistent Scatterers candidates in the city of Focșani, Romania. The first method studies the variation of targets' intensities along the SAR acquisitions and the second method analyzes the spectral proprieties of the scatterers. The algorithms were implemented on a dataset containing 11 complex images of the region covering Buzău, Brăila and Focșani cities. Images were acquired by Sentinel-1 satellite in a time span of 5 months, from October 2014 to February 2015. The processing chain follows the requirements imposed by the new C-band SAR images delivered by the Sentinel-1 satellite (launched in April 2014) imaging in Interferometric Wide (IW) mode. Considering the particularities of the TOPS (Terrain Observation with Progressive Scans in Azimuth) imaging mode[2], special requirements had to be considered for pre-processing steps. The PS detection algorithms were implemented in Gamma RS program, a software which contains various function packages dedicated to SAR images focalization, analysis and processing.

  15. 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.

  16. ELF/VLF wave disturbances detected by the DEMETER satellite over the HAARP transmitter

    Science.gov (United States)

    Titova, Elena; Demekhov, Andrei; Parrot, Michel; Mogilevsky, Mikhail; Mochalov, Alexey; Pashin, Anatoly

    We report observations of electromagnetic the ELF/VLF wave disturbances by the DEMETER satellite (670 km altitude) overflying the HAARP heating facility (62.39(°) N, 145.15(°) W, L = 4.9). The HAARP HF transmitter operated at the maximum available power of 3.6 MW, O-mode polarization, and the beam directed towards the magnetic zenith. ELF/VLF waves caused by the HAARP heating are detected by the DEMETER satellite when the HF radio wave frequency was close to the critical frequency (foF2) of the ionospheric F2 layer but below it. ELF/VLF wave disturbances observed above the HAARP transmitter were detected by electrical antennas in an area with characteristic size 10 (2) km. We analyze amplitude and polarization spectra of the ELF disturbances and compare them with the characteristics of natural ELF hiss above HAARP. The VLF wave disturbances in the topside ionosphere above the HAARP transmitter were detected in the frequency ranges 8-17 kHz and 15-18 kHz which are close to the lower hybrid resonance frequency f _LHR in the heating region and its second harmonic (2f _LHR), respectively. In the case where the HAARP HF power was modulated, the detected VLF waves were also modulated with the same frequency whereas in the ELF frequency range the modulation period of the HAARP power was not observed. Possible mechanisms of generation of the ELF/VLF disturbances produced by the HAARP transmitter in the topside ionosphere are discussed.

  17. Study on the detection of red-tide outbreaks using big satellite database

    Science.gov (United States)

    Son, Young Baek; Eun, Yoon Joo; Park, Kyongseok; Lee, Sanghwan; Lee, Ryong; Kim, Sang-Hyun; Yoo, Sinjae

    2014-11-01

    Satellite remote sensing has been successfully employed to monitor and detect the increasing incidence of harmful algal blooms (HABs) under various water conditions. In this study, to establish a comprehensive monitoring system of HAB outbreaks (particularly Cochlodinium polykrikoides blooms) in the southern coast of Korea (SCK), we tested the several proposed red-tide detection methods using SeaWiFS and MODIS ocean color data. Temporal and spatial information of red tide events from 2002 to 2013 were obtained from the National Fisheries Research and Development of Korea (NFRDI), which were matched with synchronously obtained satellite-derived ocean color data. The spectral characteristics of C. polykrikoides red tides were that increased phytoplankton absorption at 443 nm and pigment backscattering 555 nm resulted in a steeper slope between 488 and 555 nm with a hinge point at 488 (or 490) nm. On the other hand, non-red tide water, typically were presented by broader radiance spectra between the blue and green bands were associated with reduced pigment absorption and backscattering. The analysis of ocean color imageries that captured C. polykrikoides red tide blooms showed discolored waters with enhanced pigment concentrations, high chlorophyll, fluorescence, absorption at 443 nm. However, most red tide detection algorithms found a large number of false positive but only a small number of true positive areas. These proposed algorithms are not useful to distinguish true red tide water from complex non-red tide water. Our proposed method substantially reduces the false signal rate (false positive) from strong absorption at short wavelengths and provide a more reliable and robust detection of C. polykrikoides blooms in the SCK from the space.

  18. Detection of facilities in satellite imagery using semi-supervized image classification and auxiliary contextual observables

    Science.gov (United States)

    Harvey, Neal R.; Ruggiero, C.; Pawley, N. H.; MacDonald, B.; Oyer, A.; Balick, L.; Brumby, S. P.

    2009-05-01

    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  19. Detection of facilities in satellite imagery using semi-supervised image classification and auxiliary contextual observables

    Energy Technology Data Exchange (ETDEWEB)

    Harvey, Neal R [Los Alamos National Laboratory; Ruggiero, Christy E [Los Alamos National Laboratory; Pawley, Norma H [Los Alamos National Laboratory; Brumby, Steven P [Los Alamos National Laboratory; Macdonald, Brian [Los Alamos National Laboratory; Balick, Lee [Los Alamos National Laboratory; Oyer, Alden [Los Alamos National Laboratory

    2009-01-01

    Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

  20. Investigation of the recent recolonisation of Beech on Mont Ventoux using historical records, vegetation analyses from satellite image and landscape genetics

    OpenAIRE

    Prouillet-Leplat, Hélène

    2009-01-01

    In this study, we investigated the genetic structure and the recolonisation process of the European beech (Fagus sylvatica) over the north face of the Mont Ventoux Mountain, using of combination of historical record investigation, vegetation mapping from satellite image and unsupervised classification process, and a landscape genetic approach. Mont Ventoux has undergone large deforestation phases until the XIXth century due to over-grazing and over-logging for woof supply. Historical records ...

  1. 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...... 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...... 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...

  2. Multidecadal time series of satellite-detected accumulations of cyanobacteria in the Baltic Sea

    Science.gov (United States)

    Kahru, M.; Elmgren, R.

    2014-07-01

    Cyanobacteria, primarily of the species Nodularia spumigena, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scums. The area of these accumulations can reach ~ 200 000 km2. We describe the compilation of a 35-year-long time series (1979-2013) of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria), followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA) and the total accumulated area affected (TA) were used to characterize the intensity and extent of the accumulations. The fraction with cyanobacteria accumulations was calculated as the ratio of the number of detected accumulations to the number of cloud-free sea-surface views per pixel during the season (July-August). The total accumulated area affected was calculated by adding the area of pixels where accumulations were detected at least once during the season. The fraction with cyanobacteria accumulations and TA were correlated (R2 = 0.55) and both showed large interannual and decadal-scale variations. The average FCA was significantly higher for the second half of the time series (13.8%, 1997-2013) than for the first half (8.6%, 1979-1996). However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11-17%), but rare (FCA below 4%) during 1985-1990; they increased again starting in 1991 and particularly in 1999, reaching maxima in FCA (~ 25

  3. Satellite detection of multi-decadal time series of cyanobacteria accumulations in the Baltic Sea

    Science.gov (United States)

    Kahru, M.; Elmgren, R.

    2014-02-01

    Cyanobacteria, primarily of the species Nodularia spumigena, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scum. We describe the compilation of a 35 year (1979-2013) long time series of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on increased remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria), followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA) and the total accumulated area affected (TA) were used to characterize the intensity and extent of the accumulations. FCA was calculated as the ratio of the number of detected accumulations to the number of cloud free sea-surface views per pixel during the season (July-August). TA was calculated by adding the area of pixels where accumulations were detected at least once during the season. FCA and TA were correlated (R2 = 0.55) and both showed large interannual and decadal-scale variations. The average FCA was significantly higher for the 2nd half of the time series (13.8%, 1997-2013) than for the first half (8.6%, 1979-1996). However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11-17%), but rare (FCA below 4%) from 1985 to 1990; they increased again from 1991 and particularly from 1999, reaching maxima in FCA (~ 25%) and TA (~ 210 000 km2) in 2005 and 2008. After 2008 FCA declined to more moderate levels (6-17%). The timing of the accumulations has become earlier in the season, at a

  4. Satellite detection of multi-decadal time series of cyanobacteria accumulations in the Baltic Sea

    Directory of Open Access Journals (Sweden)

    M. Kahru

    2014-02-01

    Full Text Available Cyanobacteria, primarily of the species Nodularia spumigena, form extensive surface accumulations in the Baltic Sea in July and August, ranging from diffuse flakes to dense surface scum. We describe the compilation of a 35 year (1979–2013 long time series of cyanobacteria surface accumulations in the Baltic Sea using multiple satellite sensors. This appears to be one of the longest satellite-based time series in biological oceanography. The satellite algorithm is based on increased remote sensing reflectance of the water in the red band, a measure of turbidity. Validation of the satellite algorithm using horizontal transects from a ship of opportunity showed the strongest relationship with phycocyanin fluorescence (an indicator of cyanobacteria, followed by turbidity and then by chlorophyll a fluorescence. The areal fraction with cyanobacteria accumulations (FCA and the total accumulated area affected (TA were used to characterize the intensity and extent of the accumulations. FCA was calculated as the ratio of the number of detected accumulations to the number of cloud free sea-surface views per pixel during the season (July–August. TA was calculated by adding the area of pixels where accumulations were detected at least once during the season. FCA and TA were correlated (R2 = 0.55 and both showed large interannual and decadal-scale variations. The average FCA was significantly higher for the 2nd half of the time series (13.8%, 1997–2013 than for the first half (8.6%, 1979–1996. However, that does not seem to represent a long-term trend but decadal-scale oscillations. Cyanobacteria accumulations were common in the 1970s and early 1980s (FCA between 11–17%, but rare (FCA below 4% from 1985 to 1990; they increased again from 1991 and particularly from 1999, reaching maxima in FCA (~ 25% and TA (~ 210 000 km2 in 2005 and 2008. After 2008 FCA declined to more moderate levels (6–17%. The timing of the accumulations has become earlier in

  5. Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection

    Directory of Open Access Journals (Sweden)

    J.A. Moreno-Ruiz

    2014-12-01

    Full Text Available We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km of spatial resolution. The proposed methodology has several stages: 1 pre-processing daily images to obtain composite images of n days; 2 building of space of statistical variables or attributes to consider; 3 designing an algorithm, by selecting and filtering the training cases; 4 obtaining probability maps related to the considered thematic classes; 5 post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.. The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation and using scattering plots against reference data (correlation coefficient and slope of the regression line. The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km, but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.

  6. Detection and Separation of Speech Events in Meeting Recordings Using a Microphone Array

    National Research Council Canada - National Science Library

    Asano, Futoshi; Yamamoto, Kiyoshi; Ogata, Jun; Yamada, Miichi; Nakamura, Masami

    2007-01-01

    ...) framework is proposed. The main feature of this method is that all the information necessary for the adaptation of ABF, including microphone calibration, is obtained from meeting recordings based on the results of speech-event detection...

  7. a Comparison of Empirical and Inteligent Methods for Dust Detection Using Modis Satellite Data

    Science.gov (United States)

    Shahrisvand, M.; Akhoondzadeh, M.

    2013-09-01

    Nowadays, dust storm in one of the most important natural hazards which is considered as a national concern in scientific communities. This paper considers the capabilities of some classical and intelligent methods for dust detection from satellite imagery around the Middle East region. In the study of dust detection, MODIS images have been a good candidate due to their suitable spectral and temporal resolution. In this study, physical-based and intelligent methods including decision tree, ANN (Artificial Neural Network) and SVM (Support Vector Machine) have been applied to detect dust storms. Among the mentioned approaches, in this paper, SVM method has been implemented for the first time in domain of dust detection studies. Finally, AOD (Aerosol Optical Depth) images, which are one the referenced standard products of OMI (Ozone Monitoring Instrument) sensor, have been used to assess the accuracy of all the implemented methods. Since the SVM method can distinguish dust storm over lands and oceans simultaneously, therefore the accuracy of SVM method is achieved better than the other applied approaches. As a conclusion, this paper shows that SVM can be a powerful tool for production of dust images with remarkable accuracy in comparison with AOT (Aerosol Optical Thickness) product of NASA.

  8. A COMPARISON OF EMPIRICAL AND INTELIGENT METHODS FOR DUST DETECTION USING MODIS SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    M. Shahrisvand

    2013-09-01

    Full Text Available Nowadays, dust storm in one of the most important natural hazards which is considered as a national concern in scientific communities. This paper considers the capabilities of some classical and intelligent methods for dust detection from satellite imagery around the Middle East region. In the study of dust detection, MODIS images have been a good candidate due to their suitable spectral and temporal resolution. In this study, physical-based and intelligent methods including decision tree, ANN (Artificial Neural Network and SVM (Support Vector Machine have been applied to detect dust storms. Among the mentioned approaches, in this paper, SVM method has been implemented for the first time in domain of dust detection studies. Finally, AOD (Aerosol Optical Depth images, which are one the referenced standard products of OMI (Ozone Monitoring Instrument sensor, have been used to assess the accuracy of all the implemented methods. Since the SVM method can distinguish dust storm over lands and oceans simultaneously, therefore the accuracy of SVM method is achieved better than the other applied approaches. As a conclusion, this paper shows that SVM can be a powerful tool for production of dust images with remarkable accuracy in comparison with AOT (Aerosol Optical Thickness product of NASA.

  9. Use of near-infrared video recording system for the detection of freeze damaged citrus leaves

    Science.gov (United States)

    Escobar, D. E.; Bowen, R. L.; Gausman, H. W.; Cooper, G. (Principal Investigator)

    1982-01-01

    A video recording system with a visible light blocking filter to give sensitivity in the 0.78 m to 1.1 m waveband detected freeze-damaged citrus leaves rapidly. With this technique, the time to analyze images can be decreased from about one day for conventional photography to less than one hour for video recording.

  10. Extending the Record of Greenland Ice Sheet Subsurface Meltwater: Exploring New Applications of Satellite Remote Sensing Data

    Science.gov (United States)

    Carter, M.; Reusch, D. B.; Karmosky, C. C.

    2015-12-01

    The discovery of pervasive year-round englacial meltwater in southeastern Greenland by Forster et. al (2012) in the form of a Perennial Firn Aquifer (PFA) with an estimated 140+/120 GT of water (pre-2011 melt season) has significantly changed the understanding of meltwater retention, energy balance models and Greenland hydrology. Prior to this, englacial meltwater was not considered a significant portion of the water budget in Greenland. The cryosphere and hydrology communities are currently observing and studying PFAs through data obtained from the NASA ICEBridge Program. Due to environmental and time constraints, data is limited to a few months each year beginning in 2010. This leaves a significant need to explore new methods of monitoring PFAs both throughout the year and across time in order to improve the understanding of PFA formation and hydrologic consequences. Both passive microwave and infrared radiation have been used to monitor surface melt via satellite remote sensing, are recorded regularly over Greenland, and are available from 1979. While infrared data are confined to the surface, microwaves have been noted to penetrate past the ice sheet surface and return a subsurface melt signal. A combination of microwave and infrared reflectance signals has the potential to identify subsurface meltwater distinct from surface melt throughout the year. This method of identifying englacial meltwater will be compared to recognized data sets, and correlated to meteorological requirements to determine accuracy. If this method proves effective, it could significantly extend the record of PFA location and physical and temporal extent so that hydrologic and climatic results can be better analyzed.

  11. Air pollution detection by satellites: The transport and deposition of air pollutants over oceans

    Science.gov (United States)

    Chung, Y. S.

    Research is continuing towards the possible detection of air pollution by remote sensing techniques, and satellite imagery has been examined to find evidence of cross-Atlantic transport of air pollution. Pollution masses from industrial areas are often carried out over the Atlantic Ocean by tropospheric winds. However, the pollution mass is generally steered by convergent flows and fronts of extra-tropical cyclones, and wet deposition and scavenging of air pollutants within clouds occur primarily over the cold ocean, especially during the occlusion stage of a cyclone. As a result, the oceanic area from Cape Hatteras to 1500 km ENE of Newfoundland (the SW sector of the Icelandic low area) is often a 'dumping ground' (sink region) for air pollution from N America. However, a dust cloud generated by a volcanic eruption and a smoke plume from large-forest fires in western N America have been observed near the W coast of Europe. Saharan dust carried to N America by trade winds have been identified on satellite imagery. The massive smoke generation by large forest fires in Siberia is also identified in the present study. The results of research on forest fire smoke are currently being used by scientists studying the atmospheric effects of a large-scale nuclear war. It is suggested that the area between the S of Japan and the SW section of the Aleutian low is another principal sink of air pollutants and dust originating from NE Asia.

  12. 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.

  13. 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.

  14. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jounghun [Astronomy Program, Department of Physics and Astronomy, Seoul National University, Seoul 151-747 (Korea, Republic of); Choi, Yun-Young, E-mail: jounghun@astro.snu.ac.kr, E-mail: yy.choi@khu.ac.kr [Department of Astronomy and Space Science, Kyung Hee University, Gyeonggi 446-701 (Korea, Republic of)

    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.

  16. Development of hybrid fog detection algorithm (FDA) using satellite and ground observation data for nighttime

    Science.gov (United States)

    Kim, So-Hyeong; Han, Ji-Hae; Suh, Myoung-Seok

    2017-04-01

    In this study, we developed a hybrid fog detection algorithm (FDA) using AHI/Himawari-8 satellite and ground observation data for nighttime. In order to detect fog at nighttime, Dual Channel Difference (DCD) method based on the emissivity difference between SWIR and IR1 is most widely used. DCD is good at discriminating fog from other things (middle/high clouds, clear sea and land). However, it is difficult to distinguish fog from low clouds. In order to separate the low clouds from the pixels that satisfy the thresholds of fog in the DCD test, we conducted supplementary tests such as normalized local standard derivation (NLSD) of BT11 and the difference of fog top temperature (BT11) and air temperature (Ta) from NWP data (SST from OSTIA data). These tests are based on the larger homogeneity of fog top than low cloud tops and the similarity of fog top temperature and Ta (SST). Threshold values for the three tests were optimized through ROC analysis for the selected fog cases. In addition, considering the spatial continuity of fog, post-processing was performed to detect the missed pixels, in particular, at edge of fog or sub-pixel size fog. The final fog detection results are presented by fog probability (0 100 %). Validation was conducted by comparing fog detection probability with the ground observed visibility data from KMA. The validation results showed that POD and FAR are ranged from 0.70 0.94 and 0.45 0.72, respectively. The quantitative validation and visual inspection indicate that current FDA has a tendency to over-detect the fog. So, more works which reducing the FAR is needed. In the future, we will also validate sea fog using CALIPSO data.

  17. A climatology of fine absorbing biomass burning, urban and industrial aerosols detected from satellites

    Science.gov (United States)

    Kalaitzi, Nikoleta; Hatzianastassiou, Nikos; Gkikas, Antonis; Papadimas, Christos D.; Torres, Omar; Mihalopoulos, Nikos

    2017-04-01

    Natural biomass burning (BB) along with anthropogenic urban and industrial aerosol particles, altogether labeled here as BU aerosols, contain black and brown carbon which both absorb strongly the solar radiation. Thus, BU aerosols warm significantly the atmosphere also causing adjustments to cloud properties, which traditionally are known as cloud indirect and semi-direct effects. Given the role of the effects of BU aerosols for contemporary and future climate change, and the uncertainty associated with BU, both ascertained by the latest IPCC reports, there is an urgent need for improving our knowledge on the spatial and temporal variability of BU aerosols all over the globe. Over the last few decades, thanks to the rapid development of satellite observational techniques and retrieval algorithms it is now possible to detect BU aerosols based on satellite measurements. However, care must be taken in order to ensure the ability to distinguish BU from other aerosol types usually co-existing in the Earth's atmosphere. In the present study, an algorithm is presented, based on a synergy of different satellite measurements, aiming to identify and quantify BU aerosols over the entire globe and during multiple years. The objective is to build a satellite-based climatology of BU aerosols intended for use for various purposes. The produced regime, namely the spatial and temporal variability of BU aerosols, emphasizes the BU frequency of occurrence and their intensity, in terms of aerosol optical depth (AOD). The algorithm is using the following aerosol optical properties describing the size and atmospheric loading of BU aerosols: (i) spectral AOD, (ii) Ångström Exponent (AE), (iii) Fine Fraction (FF) and (iv) Aerosol Index (AI). The relevant data are taken from Collection 006 MODIS-Aqua, except for AI which is taken from OMI-Aura. The identification of BU aerosols by the algorithm is based on a specific thresholding technique, with AI≥1.5, AE≥1.2 and FF≥0.6 threshold

  18. CAPS satellite spread spectrum communication blind multi-user detecting system based on chaotic sequences

    Institute of Scientific and Technical Information of China (English)

    LEI LiHua; SHI HuLi; MA GuanYi

    2009-01-01

    Multiple Path Interference (MPI) and Multiple Access Interference (MAI) are Important factors that affect the performance of Chinese Area Positioning System (CAPS),These problems can be solved by using spreading sequences with ideal properties and multi-user detectors.Chaotic sequences based on Chebyshev map are studied and the satellite communication system model is set up to investigate the application of chaotic sequences for CAPS in this paper,Simulation results show that chaotic sequences have desirable correlation properties and it is easy to generate a large number of chaotic sequences with good security.It has great practical value to apply chaotic sequences to CAPS together with multi-user detecting technology and the system performance can be improved greatly.

  19. 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.

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

    Science.gov (United States)

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

    2015-10-01

    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 NDVI705) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest.

  1. CAPS satellite spread spectrum communication blind multi-user detecting system based on chaotic sequences

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Multiple Path Interference (MPI) and Multiple Access Interference (MAI) are important factors that affect the performance of Chinese Area Positioning System (CAPS). These problems can be solved by using spreading sequences with ideal properties and multi-user detectors. Chaotic sequences based on Chebyshev map are studied and the satellite communication system model is set up to investigate the application of chaotic sequences for CAPS in this paper. Simulation results show that chaotic sequences have desirable correlation properties and it is easy to generate a large number of chaotic sequences with good security. It has great practical value to apply chaotic sequences to CAPS together with multi-user detecting technology and the system performance can be improved greatly.

  2. Near-Real-Time Detection and Monitoring of Intense Pyroconvection from Geostationary Satellites

    Science.gov (United States)

    Peterson, D. A.; Fromm, M. D.; Hyer, E. J.; Surratt, M. L.; Solbrig, J. E.; Campbell, J. R.

    2016-12-01

    Intense fire-triggered thunderstorms, known as pyrocumulonimbus (or pyroCb), can alter fire behavior, influence smoke plume trajectories, and hinder fire suppression efforts. PyroCb are also known for injecting a significant quantity of aerosol mass into the upper-troposphere and lower-stratosphere (UTLS). Near-real-time (NRT) detection and monitoring of pyroCb is highly desirable for a variety of forecasting and research applications. The Naval Research Laboratory (NRL) recently developed the first automated NRT pyroCb detection algorithm for geostationary satellite sensors. The algorithm uses multispectral infrared observations to isolate deep convective clouds with the distinct microphysical signal of pyroCb. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation of the current system is that pyroCb anvils can be small relative to satellite pixel size, especially in in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. This algorithm has been automated using the GeoIPS processing system developed at NRL, which produces a variety of imagery products and statistical output for rapid analysis of potential pyroCb events. NRT application of this algorithm has been extended to the majority of regions worldwide known to have a high frequency of pyroCb occurrence. This involves a constellation comprised of GOES-East, GOES-West, and Himawari-8. Imagery is posted immediately to an NRL-maintained web page. Alerts are generated by the system and disseminated via email. This detection system also has potential to serve

  3. 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.

  4. 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.

  5. Hail detection algorithm for the Global Precipitation Measuring mission core satellite sensors

    Science.gov (United States)

    Mroz, Kamil; Battaglia, Alessandro; Lang, Timothy J.; Tanelli, Simone; Cecil, Daniel J.; Tridon, Frederic

    2017-04-01

    By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission core satellite's suite of sensors and by the ground-based S-band Next-Generation Radar (NEXRAD) network over continental US, proxies for the identification of hail are developed based on the GPM core satellite observables. The full capabilities of the GPM observatory are tested by analyzing more than twenty observables and adopting the hydrometeor classification based on ground-based polarimetric measurements as truth. The proxies have been tested using the Critical Success Index (CSI) as a verification measure. The hail detection algorithm based on the mean Ku reflectivity in the mixed-phase layer performs the best, out of all considered proxies (CSI of 45%). Outside the Dual frequency Precipitation Radar (DPR) swath, the Polarization Corrected Temperature at 18.7 GHz shows the greatest potential for hail detection among all GMI channels (CSI of 26% at a threshold value of 261 K). When dual variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka-bands outperforms all the other proxies, with a CSI of 49%. The best-performing radar-radiometer algorithm is based on the mixed-phase reflectivity at Ku-band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

  6. Satellite detection, tracing, and early warning of harmful algal blooms (HABs) for the Asian waters

    Science.gov (United States)

    Tang, D. L.

    Over the past two decades, Harmful Algal Blooms (HABs) appear to have increased in frequency, intensity and geographic distribution worldwide, and have caused large economic losses in aquacultured and wild fisheries in recent years. Understanding of the oceanic mechanisms is important for early warning of HAB events. The present study reported several extensive HABs in the Asian waters during 1998 to 2003 detected by satellite remote sensing data (SeaWiFS, NOAA AVHRR, and QuikScat) and in situ observations. An extensive HAB off southeastern Vietnamese waters during late June to July 2002 was detected and its related oceanographic features were analyzed. The HAB had high Chlorophyll-a (Chl-a) concentrations (up to 4.5 mg m-3), occurring about 200 km off the coast and about 200 km northeast of the Mekong River mouth, for a period of about 6 weeks. The bloom was dominated by the harmful algae haptophyte Phaeocystis cf. globosa, and caused a very significant mortality of aquacultured fishes and other marine life. In the same period, Sea Surface Temperature (SST) imagery showed a coldwater plume extending from the coast to the open sea, and QuikScat data showed strong southwesterly winds blowing parallel with the coastline. It indicated the HAB was induced and supported by offshore upwelling that bring nutrients from the deep ocean to the surface and from coastal water to the offshore, and the upwelling was driven by strong wind through Ekman transport when winds were parallel with the coastline. This study demonstrated the possibility of utilizing a combination of satellite data of Chl-a, SST and wind velocity together with coastal bathymetric information and in situ observation to give a better understanding of the biological oceanography of HABs; these results may help for the early warming of HAB.

  7. Neural Network Change Detection Model for Satellite Images Using Textural and Spectral Characteristics

    Directory of Open Access Journals (Sweden)

    A. K. Helmy

    2010-01-01

    Full Text Available Problem statement: Change detection is the process of identifying difference of the state of an object or phenomena by observing it at different time. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. Information about change is necessary for evaluating land cover and the management of natural resources. Approach: A neural network model based on both spectral and textural analysis is developed. Change detection system in this study is presented using modified version of back-propagation-training algorithm with dynamic learning rate and momentum. Through proposed model, the two images at different dates are fed into the input layer of neural network, in addition with Variance, Skewness and Eculedian for each image that represent different texture measure. This leads to better discrimination process. Results: The results showed that the trained network with texture measures achieve 23% higher accuracy than that without textural parameters. Conclusion: Adding textural parameters of satellite images through training phase increases the efficiently of change detection process also, it provides adequate information about the type of changes. It also found, when using dynamic momentum and learning rate, time and effort needed to select their appropriate value is reduced.

  8. Change detection from very high resolution satellite time series with variable off-nadir angle

    Science.gov (United States)

    Barazzetti, Luigi; Brumana, Raffaella; Cuca, Branka; Previtali, Mattia

    2015-06-01

    Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L'Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.

  9. 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

  10. 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

  11. Satellite Ocean Color Data Merging Using a Bio-optical model: A Path for Earth Science Data Records ?

    Science.gov (United States)

    Maritorena, S.; Siegel, D. A.; Hembise Fanton D'Andon, O.; Mangin, A.; Frew, J.; Nelson, N.

    2009-12-01

    The characteristics and benefits of ocean color merged data sets created using a semi-analytical model and the normalized water-leaving radiance observations from the SeaWiFS, MODIS-AQUA and MERIS ocean color missions are presented. Merged data products are coalesced from multiple mission observations into a single data product with better spatial and temporal coverage than the individual missions. Using the data from SeaWiFS, MODIS-AQUA and MERIS for the 2002-2009 time period, the average daily coverage of a merged product is ~25% of the world ocean which is nearly twice that of any single mission’s observations. The frequency at which a particular area is sampled from space is also greatly improved in merged data as some areas can be sampled as frequently as 64% of the time (in days). The merged data are validated through matchup analyses and by comparing them to the data sets obtained from individual missions. Further, a complete error budget was developed which accounts for uncertainty associated with input water-leaving radiances, the bio-optical model and uncertainty estimates for the output products (i.e. the chlorophyll concentration, the combined dissolved and detrital absorption coefficient and the particulate backscattering coefficient). These merged products and their uncertainties at each pixel were developed within the NASA MEASURES (http://wiki.icess.ucsb.edu/measures/index.php/Main_Page) and ESA GlobColour (http://www.globcolour.info/) projects and are available to the scientific community. The merging approach has many potential benefits for the creation of Earth Science Data Records from satellite ocean color observations.

  12. Feasibility to Detect Signs of Potential CO2 Leakage with Multi-Temporal SPOT Satellite Vegetation Imagery in Otway, Victoria

    Science.gov (United States)

    Cholathat, R.; Ge, L.; Li, X.; Hu, Z.

    2012-07-01

    This paper presents image processing results for the OtwayCO2storage site, a demonstration project of CO2 sequestration in south-western Victoria, Australia. These results were derived from SPOT-VGT S10 datasets of 2001 to mid 2011. Over 65,000 tonnes of CO2-rich gas stream was injected into a depleted gas reservoir at a depth of 2050 meters at the site since 2008. Over time, CO2 migration up-dip within the 31 m thick reservoir sandstone capped by the impervious thick seal rock has been recorded. But no top soil contamination has been discovered. This study has analysed the site vegetation growth using NDVI as a measure on a pixel by pixel basis. The multi-year time series result shows that NDVI values at the site regularly vary according to the seasons. Furthermore, precipitation levels were fluctuating in the past 10 years, especially in the years of 2002 and 2006, which correlated with low NDVI measuring results. But there are detected hot spots that cannot be linked with rainfall. Authors have found that some hot spots correspond with site well drilling and pipelines construction periods and locations. While others might be due to image data biased. Therefore, certain low NDVI spikes in the temporal evolution results cannot be attributed to only drought or pasture grazing. These subtle changes detected in the NDVI index prove the ability to use satellite image for providing valuable information to decision makers in relation to CO2 sequestration site environmental safety monitoring for searching CO2 leakage signals.

  13. 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.

  14. Detection of centers of tropical cyclones using Communication, Ocean, and Meteorological Satellite data

    Science.gov (United States)

    Lee, Juhyun; Im, Jungho; Park, Seohui; Yoo, Cheolhee

    2017-04-01

    Tropical cyclones are one of major natural disasters, which results in huge damages to human and society. Analyzing behaviors and characteristics of tropical cyclones is essential for mitigating the damages by tropical cyclones. In particular, it is important to keep track of the centers of tropical cyclones. Cyclone center and track information (called Best Track) provided by Joint Typhoon Warning Center (JTWC) are widely used for the reference data of tropical cyclone centers. However, JTWC uses multiple resources including numerical modeling, geostationary satellite data, and in situ measurements to determine the best track in a subjective way and makes it available to the public 6 months later after an event occurred. Thus, the best track data cannot be operationally used to identify the centers of tropical cyclones in real time. In this study, we proposed an automated approach for identifying the centers of tropical cyclones using only Communication, Ocean, and Meteorological Satellite (COMS) Meteorological Imager (MI) sensor derived data. It contains 5 bands—VIS (0.67µm), SWIR (3.7µm), WV (6.7µm), IR1 (10.8µm), and IR2 (12.0µm). We used IR1 band images to extract brightness temperatures of cloud tops over Western North Pacific between 2011 and 2012. The Angle deviation between brightness temperature-based gradient direction in a moving window and the reference angle toward the center of the window was extracted. Then, a spatial analysis index called circular variance was adopted to identify the centers of tropical cyclones based on the angle deviation. Finally, the locations of the minimum circular variance indexes were identified as the centers of tropical cyclones. While the proposed method has comparable performance for detecting cyclone centers in case of organized cloud convections when compared with the best track data, it identified the cyclone centers distant ( 2 degrees) from the best track centers for unorganized convections.

  15. Detecting extrasolar moons akin to solar system satellites with an orbital sampling effect

    Energy Technology Data Exchange (ETDEWEB)

    Heller, René, E-mail: rheller@physics.mcmaster.ca [Department of Physics and Astronomy, McMaster University (Canada)

    2014-05-20

    Despite years of high accuracy observations, none of the available theoretical techniques has yet allowed the confirmation of a moon beyond the solar system. Methods are currently limited to masses about an order of magnitude higher than the mass of any moon in the solar system. I here present a new method sensitive to exomoons similar to the known moons. Due to the projection of transiting exomoon orbits onto the celestial plane, satellites appear more often at larger separations from their planet. After about a dozen randomly sampled observations, a photometric orbital sampling effect (OSE) starts to appear in the phase-folded transit light curve, indicative of the moons' radii and planetary distances. Two additional outcomes of the OSE emerge in the planet's transit timing variations (TTV-OSE) and transit duration variations (TDV-OSE), both of which permit measurements of a moon's mass. The OSE is the first effect that permits characterization of multi-satellite systems. I derive and apply analytical OSE descriptions to simulated transit observations of the Kepler space telescope assuming white noise only. Moons as small as Ganymede may be detectable in the available data, with M stars being their most promising hosts. Exomoons with the ten-fold mass of Ganymede and a similar composition (about 0.86 Earth radii in radius) can most likely be found in the available Kepler data of K stars, including moons in the stellar habitable zone. A future survey with Kepler-class photometry, such as Plato 2.0, and a permanent monitoring of a single field of view over five years or more will very likely discover extrasolar moons via their OSEs.

  16. 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...

  17. Evaluation of autonomous recording units for detecting 3 species of secretive marsh birds

    Science.gov (United States)

    Sidie-Slettehahl, Anna M.; Jensen, Kent C.; Johnson, Rex R.; Arnold, Todd W.; Austin, Jane; Stafford, Joshua D.

    2015-01-01

    Population status and habitat use of yellow rails (Coturnicops noveboracensis), Nelson's sparrows (Ammodramus nelsoni), and Le Conte's sparrows (A. leconteii) are poorly known, so standardized surveys of these species are needed to inform conservation planning and management. A protocol for monitoring secretive marsh birds exists; however, these species regularly call at night and may be missed during early morning surveys. We tested the effectiveness of autonomous recording units (hereafter, recording units) to survey these species by analyzing recorded vocalizations using bioacoustics software. We deployed 22 recording units at 54 sites in northern Minnesota and eastern North Dakota, USA, and conducted traditional broadcast surveys during May–June, 2010 and 2011. We compared detection probabilities between recording units and standard monitoring protocols using robust-design occupancy models. On average, recording units detected 0.59 (SE = 0.11) fewer Le Conte's sparrows, 0.76 (SE = 0.15) fewer Nelson's sparrows, and 1.01 (SE = 0.14) fewer yellow rails per survey than were detected using the standard protocol. Detection probabilities using the standard protocol averaged 0.95 (yellow rail; 95% CI = 0.86–0.98), 0.93 (Le Conte's sparrow; 95% CI = 0.78–0.98), and 0.89 (Nelson's sparrow; 95% CI = 0.56–0.98), but averaged 0.71 (yellow rail; 95% CI = 0.56–0.83), 0.61 (Le Conte's sparrow; 95% CI = 0.42–0.78), and 0.51 (Nelson's sparrow; 95% CI = 0.19–0.82) using recording units. Reduced detection by recording units was likely due to the ability of human listeners to identify birds calling at greater distances. Recording units may be effective for surveying nocturnal secretive marsh birds if investigators correct for differential detectability. Reduced detectability may be outweighed by the increased spatial and temporal coverage feasible with recording units.

  18. 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.

  19. Detection and Separation of Speech Events in Meeting Recordings Using a Microphone Array

    Directory of Open Access Journals (Sweden)

    Yamada Miichi

    2007-01-01

    Full Text Available When applying automatic speech recognition (ASR to meeting recordings including spontaneous speech, the performance of ASR is greatly reduced by the overlap of speech events. In this paper, a method of separating the overlapping speech events by using an adaptive beamforming (ABF framework is proposed. The main feature of this method is that all the information necessary for the adaptation of ABF, including microphone calibration, is obtained from meeting recordings based on the results of speech-event detection. The performance of the separation is evaluated via ASR using real meeting recordings.

  20. Detection and Separation of Speech Events in Meeting Recordings Using a Microphone Array

    Directory of Open Access Journals (Sweden)

    Futoshi Asano

    2007-07-01

    Full Text Available When applying automatic speech recognition (ASR to meeting recordings including spontaneous speech, the performance of ASR is greatly reduced by the overlap of speech events. In this paper, a method of separating the overlapping speech events by using an adaptive beamforming (ABF framework is proposed. The main feature of this method is that all the information necessary for the adaptation of ABF, including microphone calibration, is obtained from meeting recordings based on the results of speech-event detection. The performance of the separation is evaluated via ASR using real meeting recordings.

  1. Beat-to-beat heart rate detection in multi-lead abdominal fetal ECG recordings.

    Science.gov (United States)

    Peters, C H L; van Laar, J O E H; Vullings, R; Oei, S G; Wijn, P F F

    2012-04-01

    Reliable monitoring of fetal condition often requires more information than is provided by cardiotocography, the standard technique for fetal monitoring. Abdominal recording of the fetal electrocardiogram may offer valuable additional information, but unfortunately is troubled by poor signal-to-noise ratios during certain parts of pregnancy. To increase the usability of abdominal fetal ECG recordings, an algorithm was developed that enhances fetal QRS complexes in these recordings and thereby provides a promising method for detecting the beat-to-beat fetal heart rate in recordings with poor signal-to-noise ratios. The method was evaluated on generated recordings with controlled signal-to-noise ratios and on actual recordings that were performed in clinical practice and were annotated by two independent experts. The evaluation on the generated signals demonstrated excellent results (sensitivity of 0.98 for SNR≥1.5). Only for SNRheart rate detection exceeded 2 ms, which may still suffice for cardiotocography but is unacceptable for analysis of the beat-to-beat fetal heart rate variability. The sensitivity and positive predictive value of the method in actual recordings were reduced to approximately 90% for SNR≤2.4, but were excellent for higher signal-to-noise ratios.

  2. Early detection of hepatic encephalopathy by recording visual evoked potential (VEP).

    Science.gov (United States)

    Zamir, Doron; Storch, Shimon; Kovach, Ivan; Storch, Rita; Zamir, Chen

    2002-01-01

    The visual evoked potential (VEP) record in response to a pattern stimulus is a non invasive and reliable method of detecting central and peripheral nerve system abnormalities. VEP recording have been used in animals with fulminant hepatic failure, and also in-patients with hepatic encephalopathy and acute severe hepatitis. Our aims were: a. to evaluate the potency of PVEP in assessing hepatic encephalopathy. b. to find the rate of pathologic PVEP in patients with advanced liver cirrhosis. VEP was recorded in 14 chronic liver cirrhotic patients (6 alcoholic, 6 HCV-related, 2 cryptogenic) and 14 controls. Patients with any neurologic abnormalities were excluded from the study. All patients were subjected to the Mental State Score (MSS) test, and venous blood ammonia was measured on the same day of VEP recording. In 10/14 (71%) patients some VEP recording abnormality was detected. In the cirrhotic patients, P100 latency was significantly longer (P VEP developed hepatic encephalpathy during a follow-up of one year, compared to one out of 4 patients with no pathology on VEP recording. VEP recording may be a valuable tool in assessing patients with early hepatic encephalopathy and in predicting encephalopathy.

  3. Detection of regional air pollution episodes utilizing satellite digital data in the visual range

    Science.gov (United States)

    Burke, H.-H. K.

    1982-01-01

    Digital analyses of satellite visible data for selected high-sulfate cases over the northeastern U.S., on July 21 and 22, 1978, are compared with ground-based measurements. Quantitative information on total aerosol loading derived from the satellite digitized data using an atmospheric radiative transfer model is found to agree with the ground measurements, and it is shown that the extent and transport of the haze pattern may be monitored from the satellite data over the period of maximum intensity for the episode. Attention is drawn to the potential benefits of satellite monitoring of pollution episodes demonstrated by the model.

  4. 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.

  5. Land cover change detection based on satellite data for an arid area to the south of Aksu in Taklimakan desert

    Institute of Scientific and Technical Information of China (English)

    Kiyoshi; TSUCHIYA; Tamotsu; IGARSHI; Muhtar; QONG

    2010-01-01

    An experiment is made to detect the land-cover change in the area located to the south of Aksu in the northern Taklimakan desert through analyses of satellite data pixel by pixel basis. The analyzed data are those observed in the late summer and early autumn of 1973, 1977, 1993 and 1995. As a parameter of land-cover, SAVI (Soil Adjusted Vegetation Index) derived from the data of Landsat MSS and JERS-1 OPS (Optical Sensor) is used. The result indicates the increase of vegetation in the oasis areas, confluent area of the Yarkant and Kashgar Rivers and around reservoirs while little change occurs in the desert area. The 1973 satellite image shows the abundant flow in the Yarkant River while the river is almost dried up in the satellite images of later years. The trend of the decrease in the Hotan River flow is recognized although not so dramatic as that of the Yarkant River.

  6. The Transiting Exoplanet Survey Satellite: Simulations of planet detections and astrophysical false positives

    CERN Document Server

    Sullivan, Peter W; Berta-Thompson, Zachory K; Charbonneau, David; Deming, Drake; Dressing, Courtney D; Latham, David W; Levine, Alan M; McCullough, Peter R; Morton, Timothy; Ricker, George R; Vanderspek, Roland; Woods, Deborah

    2015-01-01

    The Transiting Exoplanet Survey Satellite (TESS) is a NASA-sponsored Explorer mission that will perform a wide-field survey for planets that transit bright host stars. Here, we predict the properties of the transiting planets that TESS will detect along with the eclipsing binary stars that produce false-positive photometric signals. The predictions are based on Monte Carlo simulations of the nearby population of stars, occurrence rates of planets derived from Kepler, and models for the photometric performance and sky coverage of the TESS cameras. We expect that TESS will find approximately 1700 transiting planets from 200,000 pre-selected target stars. This includes 556 planets smaller than twice the size of Earth, of which 419 are hosted by M dwarf stars and 137 are hosted by FGK dwarfs. Approximately 130 of the R < 2 R_Earth planets will have host stars brighter than K = 9. Approximately 48 of the planets with R < 2 R_Earth lie within or near the habitable zone (0.2 < S/S_Earth < 2), and between...

  7. Global Cloud Detection and Distribution with Night Time using Satellite Infrared Data

    Science.gov (United States)

    Kadosaki, G.; Yamanouchi, T.; Hirasawa, N.

    2007-12-01

    Knowledge of the current climate system is necessary to clearly estimate large-scale global warming and abnormal weather in the future. Net radiation is one of the main factors that influence a climate system. The earth, which is covered by cloud of dozens of surface giving it a high albedo, reflects a large part of solar radiation. In addition, during nights, when the earth's radiation increases, the earth acts as a radiator. There is no doubt that clouds are closely related to the radiation balance. Satellite data analysis is the most useful method to understand cloud climatology. The targets are to establish an algorithm to detect clouds for night term of the earth, and to get to know more about global cloud distribution with night term. Brightness temperature difference of split window channels is used in this method. We decided three thresholds which have some slopes are used in the case of over land, open sea, and snow or ice surface including sea ice, respectively. We examined on some sensors which has difference response function in itself plat home, GLI/ADEOS2, AVHRR/NOAA, MODIS/Terra and Aqua.

  8. The development of an improved long-term total ozone record through investigation into systematic and random differences between comparable satellite measurements.

    Science.gov (United States)

    Leigh, R. J.; Corlett, G. K.; Monks, P. S.

    2003-04-01

    Knowledge of stratospheric ozone trends is vital both for interpretation of the current record of surface temperature variation and for prediction of future patterns of climate evolution. Historically, data records from the TOMS satellite instruments and the Dobson ground-based networks have provided the premier standard for analysis, although recent work has invested much effort in deriving combined TOMS and GOME datasets. Despite problems of calibration and systematic uncertainties, the satellite data record has been valuable in demonstrating trends in total ozone as a function of latitude and month. Perhaps most critically, the trend analyses are complex, with disruption to the TOMS record due to the Mt. Pinatubo eruption (1991-93), and also a data gap (1994-96). Previous investigation in our department has shown systematic differences between comparable satellite measurements between 1996 and 1998. This poster presents results from an extended investigation into differences between total ozone measurements from TOVS, TOMS and GOME from 1996 to 2001. Such differences need to be quantified and understood in order to produce a reliable long-term record, and to provide a firm foundation that can be extended with data from new instruments such as SCIAMACHY, OMI and GOME-2, which so far will be the only instruments operating in the post-TOMS era. The new analyses over the 1996 2001 time period provide further evidence of regular systematic discrepancies of up to 30DU between co-located and concurrent measurements of total ozone from the three instruments. The increased time-series has permitted a more detailed study of the temporal periodicity and geographic patterns evident in the residuals. Specifically, effects due to clouds, topography, and albedo have been investigated, with initial results indicating a clear correlation between albedo and differences between measurements from all three instruments. Moreover, the effects instrument-specific problems encountered

  9. 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...

  10. 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.

  11. 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 ...

  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. 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.

  14. Statistical analysis of automatically detected ion density variations recorded by DEMETER and their relation to seismic activity

    Directory of Open Access Journals (Sweden)

    Michel Parrot

    2012-04-01

    Full Text Available

    Many examples of ionospheric perturbations observed during large seismic events were recorded by the low-altitude satellite DEMETER. However, there are also ionospheric variations without seismic activity. The present study is devoted to a statistical analysis of the night-time ion density variations. Software was implemented to detect variations in the data before earthquakes world-wide. Earthquakes with magnitudes >4.8 were selected and classified according to their magnitudes, depths and locations (land, close to the coast, or below the sea. For each earthquake, an automatic search for ion density variations was conducted from 15 days before the earthquake, when the track of the satellite orbit was at less than 1,500 km from the earthquake epicenter. The result of this first step provided the variations relative to the background in the vicinity of the epicenter for each 15 days before each earthquake. In the second step, comparisons were carried out between the largest variations over the 15 days and the earthquake magnitudes. The statistical analysis is based on calculation of the median values as a function of the various seismic parameters (magnitude, depth, location. A comparison was also carried out with two other databases, where on the one hand, the locations of the epicenters were randomly modified, and on the other hand, the longitudes of the epicenters were shifted. The results show that the intensities of the ionospheric perturbations are larger prior to the earthquakes than prior to random events, and that the perturbations increase with the earthquake magnitudes.


  15. Satellite-based detection and monitoring of phytoplankton blooms along the Oregon coast

    Science.gov (United States)

    McKibben, S. M.; Strutton, P. G.; Foley, D. G.; Peterson, T. D.; White, A. E.

    2012-12-01

    We have applied a normalized difference algorithm to 8 day composite chlorophyll-a (CHL) and fluorescence line height (FLH) imagery obtained from the Moderate Resolution Imaging Spectroradiometer aboard the Aqua spacecraft in order to detect and monitor phytoplankton blooms in the Oregon coastal region. The resulting bloom products, termed CHLrel and FLHrel, respectively, describe the onset and advection of algal blooms as a function of the percent relative change observed in standard 8 day CHL or FLH imagery over time. Bloom product performance was optimized to consider local time scales of biological variability (days) and cloud cover. Comparison of CHLrel and FLHrelretrievals to in situ mooring data collected off the central Oregon coast from summer 2009 through winter 2010 shows that the products are a robust means to detect bloom events during the summer upwelling season. Evaluation of winter performance was inconclusive due to persistent cloud cover and limited in situ chl-a records. Pairing the products with coincident in situ physical proxies provides a tool to elucidate the conditions that induce bloom onset and identify the physical mechanisms that affect bloom advection, persistence, and decay. These products offer an excellent foundation for remote bloom detection and monitoring in this region, and the methods developed herein are applicable to any region with sufficient CHL and FLH coverage.

  16. 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

  17. Intermittent short ECG recording is more effective than 24-hour Holter ECG in detection of arrhythmias.

    Science.gov (United States)

    Hendrikx, Tijn; Rosenqvist, Mårten; Wester, Per; Sandström, Herbert; Hörnsten, Rolf

    2014-04-01

    Many patients report symptoms of palpitations or dizziness/presyncope. These patients are often referred for 24-hour Holter ECG, although the sensitivity for detecting relevant arrhythmias is comparatively low. Intermittent short ECG recording over a longer time period might be a convenient and more sensitive alternative. The objective of this study is to compare the efficacy of 24-hour Holter ECG with intermittent short ECG recording over four weeks to detect relevant arrhythmias in patients with palpitations or dizziness/presyncope. prospective, observational, cross-sectional study. Clinical Physiology, University Hospital. 108 consecutive patients referred for ambiguous palpitations or dizziness/presyncope. All individuals underwent a 24-hour Holter ECG and additionally registered 30-second handheld ECG (Zenicor EKG® thumb) recordings at home, twice daily and when having cardiac symptoms, during 28 days. Significant arrhythmias: atrial fibrillation (AF), paroxysmal supraventricular tachycardia (PSVT), atrioventricular (AV) block II-III, sinus arrest (SA), wide complex tachycardia (WCT). 95 patients, 42 men and 53 women with a mean age of 54.1 years, completed registrations. Analysis of Holter registrations showed atrial fibrillation (AF) in two patients and atrioventricular (AV) block II in one patient (= 3.2% relevant arrhythmias [95% CI 1.1-8.9]). Intermittent handheld ECG detected nine patients with AF, three with paroxysmal supraventricular tachycardia (PSVT) and one with AV-block-II (= 13.7% relevant arrhythmias [95% CI 8.2-22.0]). There was a significant difference between the two methods in favour of intermittent ECG with regard to the ability to detect relevant arrhythmias (P = 0.0094). With Holter ECG, no symptoms were registered during any of the detected arrhythmias. With intermittent ECG, symptoms were registered during half of the arrhythmia episodes. Intermittent short ECG recording during four weeks is more effective in detecting AF and PSVT in

  18. Dynamic Neural Network-Based Pulsed Plasma Thruster (PPT) Fault Detection and Isolation for Formation Flying of Satellites

    Science.gov (United States)

    Valdes, A.; Khorasani, K.

    The main objective of this paper is to develop a dynamic neural network-based fault detection and isolation (FDI) scheme for the Pulsed Plasma Thrusters (PPTs) that are used in the Attitude Control Subsystem (ACS) of satellites that are tasked to perform a formation flying mission. By using data collected from the relative attitudes of the formation flying satellites our proposed "High Level" FDI scheme can detect the pair of thrusters which is faulty, however fault isolation cannot be accomplished. Based on the "High Level" FDI scheme and the DNN-based "Low Level" FDI scheme developed earlier by the authors, an "Integrated" DNN-based FDI scheme is then proposed. To demonstrate the FDI capabilities of the proposed schemes various fault scenarios are simulated.

  19. Presence of nonlinearity in intracranial EEG recordings: detected by Lyapunov exponents

    Science.gov (United States)

    Liu, Chang-Chia; Shiau, Deng-Shan; Chaovalitwongse, W. Art; Pardalos, Panos M.; Sackellares, J. C.

    2007-11-01

    In this communication, we performed nonlinearity analysis in the EEG signals recorded from patients with temporal lobe epilepsy (TLE). The largest Lyapunov exponent (Lmax) and phase randomization surrogate data technique were employed to form the statistical test. EEG recordings were acquired invasively from three patients in six brain regions (left and right temporal depth, sub-temporal and orbitofrontal) with 28-32 depth electrodes placed in depth and subdural of the brain. All three patients in this study have unilateral epileptic focus region on the right hippocampus(RH). Nonlinearity was detected by comparing the Lmax profiles of the EEG recordings to its surrogates. The nonlinearity was seen in all different states of the patient with the highest found in post-ictal state. Further our results for all patients exhibited higher degree of differences, quantified by paired t-test, in Lmax values between original and its surrogate from EEG signals recorded from epileptic focus regions. The results of this study demonstrated the Lmax is capable to capture spatio-temporal dynamics that may not be able to detect by linear measurements in the intracranial EEG recordings.

  20. Improved sea level record over the satellite altimetry era (1993-2010) from the Climate Change Initiative project

    DEFF Research Database (Denmark)

    Ablain, M.; Cazenave, A.; Larnicol, G.;

    2015-01-01

    Sea level is one of the 50 Essential Climate Variables (ECVs) listed by the Global Climate Observing System (GCOS) in climate change monitoring. In the past two decades, sea level has been routinely measured from space using satellite altimetry techniques. In order to address a number of importan...

  1. Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China

    Directory of Open Access Journals (Sweden)

    Kunpeng Yi

    2013-12-01

    Full Text Available This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from 1984 to 2006. Regressing post-fire NDVI values on the pre-fire values helped identify the NDVI for burnt pixels in vegetation stands. Stand differences in fire damage were classified into five levels: Very High (VH, High (H, Moderate (M, Low (L and Slight (S. Furthermore, intra-annual and inter-annual post-fire vegetation recovery trajectories were analyzed by deriving a time series of NDVI and relative regrowth index (RRI values for the entire burned area. Finally, spatial pattern and trend analyses were conducted using the pixel-based post-fire annual stands regrowth index (SRI with a nonparametric Mann-Kendall (MK statistics method. The results show that October was a better period compared to other months for distinguishing the post- and pre-fire vegetation conditions using the NDVI signals in boreal forests of China because colored leaves on grasses and shrubs fall down, while the leaves on healthy trees remain green in October. The MK statistics method is robustly capable of detecting vegetation trends in a relatively long time series. Because tree planting primarily occurred in the severely burned area (approximately equal to the Medium, High and Very High fire damage areas following the Daxing’anling fire in 1987, the severely burned area exhibited a better recovery trend than the lightly burned regions. Reasonable tree planting can substantially quicken the recovery and shorten the restoration time of the target species. More detailed satellite analyses and field data will be required in the future for a more convincing validation of the results.

  2. Authenticity examination of compressed audio recordings using detection of multiple compression and encoders' identification.

    Science.gov (United States)

    Korycki, Rafal

    2014-05-01

    Since the appearance of digital audio recordings, audio authentication has been becoming increasingly difficult. The currently available technologies and free editing software allow a forger to cut or paste any single word without audible artifacts. Nowadays, the only method referring to digital audio files commonly approved by forensic experts is the ENF criterion. It consists in fluctuation analysis of the mains frequency induced in electronic circuits of recording devices. Therefore, its effectiveness is strictly dependent on the presence of mains signal in the recording, which is a rare occurrence. Recently, much attention has been paid to authenticity analysis of compressed multimedia files and several solutions were proposed for detection of double compression in both digital video and digital audio. This paper addresses the problem of tampering detection in compressed audio files and discusses new methods that can be used for authenticity analysis of digital recordings. Presented approaches consist in evaluation of statistical features extracted from the MDCT coefficients as well as other parameters that may be obtained from compressed audio files. Calculated feature vectors are used for training selected machine learning algorithms. The detection of multiple compression covers up tampering activities as well as identification of traces of montage in digital audio recordings. To enhance the methods' robustness an encoder identification algorithm was developed and applied based on analysis of inherent parameters of compression. The effectiveness of tampering detection algorithms is tested on a predefined large music database consisting of nearly one million of compressed audio files. The influence of compression algorithms' parameters on the classification performance is discussed, based on the results of the current study.

  3. Automated dust storm detection using satellite images. Development of a computer system for the detection of dust storms from MODIS satellite images and the creation of a new dust storm database

    Science.gov (United States)

    El-Ossta, Esam Elmehde Amar

    Dust storms are one of the natural hazards, which have increased in frequency in the recent years over Sahara desert, Australia, the Arabian Desert, Turkmenistan and northern China, which have worsened during the last decade. Dust storms increase air pollution, impact on urban areas and farms as well as affecting ground and air traffic. They cause damage to human health, reduce the temperature, cause damage to communication facilities, reduce visibility which delays both road and air traffic and impact on both urban and rural areas. Thus, it is important to know the causation, movement and radiation effects of dust storms. The monitoring and forecasting of dust storms is increasing in order to help governments reduce the negative impact of these storms. Satellite remote sensing is the most common method but its use over sandy ground is still limited as the two share similar characteristics. However, satellite remote sensing using true-colour images or estimates of aerosol optical thickness (AOT) and algorithms such as the deep blue algorithm have limitations for identifying dust storms. Many researchers have studied the detection of dust storms during daytime in a number of different regions of the world including China, Australia, America, and North Africa using a variety of satellite data but fewer studies have focused on detecting dust storms at night. The key elements of this present study are to use data from the Moderate Resolution Imaging Spectroradiometers on the Terra and Aqua satellites to develop more effective automated method for detecting dust storms during both day and night and generate a MODIS dust storm database..

  4. Recurrent Neural Networks for Polyphonic Sound Event Detection in Real Life Recordings

    OpenAIRE

    Parascandolo, Giambattista; Huttunen, Heikki; Virtanen, Tuomas

    2016-01-01

    In this paper we present an approach to polyphonic sound event detection in real life recordings based on bi-directional long short term memory (BLSTM) recurrent neural networks (RNNs). A single multilabel BLSTM RNN is trained to map acoustic features of a mixture signal consisting of sounds from multiple classes, to binary activity indicators of each event class. Our method is tested on a large database of real-life recordings, with 61 classes (e.g. music, car, speech) from 10 different ever...

  5. Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

    Directory of Open Access Journals (Sweden)

    B. Revilla-Romero

    2014-07-01

    Full Text Available One of the main challenges for global hydrological modelling is the limited availability of observational data for calibration and model verification. This is particularly the case for real time applications. This problem could potentially be overcome if discharge measurements based on satellite data were sufficiently accurate to substitute for ground-based measurements. The aim of this study is to test the potentials and constraints of the remote sensing signal of the Global Flood Detection System for converting the flood detection signal into river discharge values. The study uses data for 322 river measurement locations in Africa, Asia, Europe, North America and South America. Satellite discharge measurements were calibrated for these sites and a validation analysis with in situ discharge was performed. The locations with very good performance will be used in a future project where satellite discharge measurements are obtained on a daily basis to fill the gaps where real time ground observations are not available. These include several international river locations in Africa: Niger, Volta and Zambezi rivers. Analysis of the potential factors affecting the satellite signal was based on a classification decision tree (Random Forest and showed that mean discharge, climatic region, land cover and upstream catchment area are the dominant variables which determine good or poor performance of the measurement sites. In general terms, higher skill scores were obtained for locations with one or more of the following characteristics: a river width higher than 1 km; a large floodplain area and in flooded forest; with a potential flooded area greater than 40%; sparse vegetation, croplands or grasslands and closed to open and open forest; Leaf Area Index > 2; tropical climatic area; and without hydraulic infrastructures. Also, locations where river ice cover is seasonally present obtained higher skill scores. The work provides guidance on the best

  6. An algorithm to detect low incidence arrhythmic events in electrocardiographic records from ambulatory patients.

    Science.gov (United States)

    Hungenahally, S K; Willis, R J

    1994-11-01

    An algorithm was devised to detect low incidence arrhythmic events in electrocardiograms obtained during ambulatory monitoring. The algorithm incorporated baseline correction and R wave detection. The RR interval was used to identify tachycardia, bradycardia, and premature ventricular beats. Only a few beats before and after the arrhythmic event were stored. The software was evaluated on a prototype hardware system which consisted of an Intel 86/30 single board computer with a suitable analog pre-processor and an analog to digital converter. The algorithm was used to determine the incidence and type of arrhythmia in records from an ambulatory electrocardiogram (ECG) database and from a cardiac exercise laboratory. These results were compared to annotations on the records which were assumed to be correct. Standard criteria used previously to evaluate algorithms designed for arrhythmia detection were sensitivity, specificity, and diagnostic accuracy. Sensitivities ranging from 77 to 100%, specificities from 94 to 100%, and diagnostic accuracies from 92 to 100% were obtained on the different data sets. These results compare favourably with published results based on more elaborate algorithms. By circumventing the need to make a continuous record of the ECG, the algorithm could form the basis for a compact monitoring device for the detection of arrhythmic events which are so infrequent that standard 24-h Holter monitoring is insufficient.

  7. Detection of anthropogenic influence on the evolution of record-breaking temperatures over Europe

    Science.gov (United States)

    Bador, Margot; Terray, Laurent; Boé, Julien

    2016-05-01

    Changes in temperature extreme events are expected as a result of anthropogenic climate change, but uncertainties exist in when and how these changes will be manifest regionally. This is especially the case over Europe due to different methodologies and definitions of temperature extreme events. An alternative approach is to examine changes in record-breaking temperatures. Datasets of observed temperature combined with ensembles of climate model simulations are used to assess the possible causes and significance of record-breaking temperature changes over the late twentieth and twenty-first centuries. A simple detection methodology is first applied to evaluate the extent to which the effect of anthropogenic forcing can be detected in present-day observed and simulated changes in record-breaking temperature. We then study the projected evolution of record-breaking daily minimum and maximum temperatures over the twenty-first century in Europe with a climate model. The same detection approach is used to identify the time of emergence of the anthropogenic signal relative to a model-derived estimate of internal variability. From the 1980s onwards, a change in the evolution of cold and warm records is observed and simulated, but it still remains in the range of internal variability until the end of the twentieth century. Minimum and maximum record-breaking temperatures tend to occur (respectively) less and more often than during the 1960s and 1970s taken as representative of a stationary climate. Model simulations with natural forcing only fail to reproduce the observed changes after the 1980s while the latter are compatible with simulations constrained by anthropogenic forcings. The deviation from the characteristic behavior of a stationary climate record-wise initiated in the 1980s is projected to accentuate during the twenty-first century. Annual changes become inconsistent with the model-derived internal variability between the 2020s and 2030s. Over the last three

  8. Applicability of logistic model and integrated satellite data for rice crop phenology detection

    Science.gov (United States)

    Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru; Chang, Ly-Yu; Chiang, Shou-Hao

    2016-04-01

    Changes in climate condition through global warming locally altered climatic and hydrological conditions and likely trigger the increase of insect populations and diseases, causing the potential loss of rice yields. Because the rice fields damaged by diseases or insects may affect neighbouring fields, monitoring the cropping progress was important to provide agronomic planners with valuable information that could be used to timely devise strategies to mitigate possible impacts on the potential yield. This study aimed to develop an approach to monitor rice sowing and harvesting progress from the integrated Moderate Resolution Imaging Spectroradiometer (MODIS)-Landsat satellite data. We processed for the 2007 winter-spring and summer-autumn cropping seasons in 2007, following four main steps: (1) constructing a set of MODIS-Landsat fusion data using the spatiotemporal adaptive reflectance fusion model (STARFM), (2) creating smooth time-series enhanced vegetation 2 (EVI2) data using the commonly-used empirical mode decomposition (EMD), (3) detecting key phenological stages of rice crops the double logistic algorithm, and (4) error verification of the detected sowing and harvesting dates using field data. The comparison results between the EVI2 data derived from the fusion data and that from the Landsat yielded close agreement between these two datasets (R2 > 0.9). The double logistic algorithm applied to the filtered time-series EVI2 data to estimate phenological events of rice crops indicated the validity of our approach for monitoring the progress of sowing and harvesting activities in the region. The results obtained by comparisons between the estimated sowing/ harvesting dates and the field survey data indicated that the root mean squared error (RMSE) values archived for the winter-spring crop were respectively 8.4 and 5.5 days, while those for the summer-autumn crop were 9.4 and 12.8 days, respectively. The results obtained from this study could provide decision

  9. The Detection of Change in the Arctic Using Satellite and Buoy Data

    Science.gov (United States)

    Comiso, Josefino C.; Yang, J.; Honjo, S.; Krishfield, R.; Koblinsky, Chester J. (Technical Monitor)

    2001-01-01

    The decade of the 1990s is the warmest decade of the last century while the year 1998 is the warmest year ever observed by modern techniques with 9 out of 12 months of the year being the warmest month. Since the Arctic is expected to provide early signals of a possible warming scenario, detailed examination of changes in the Arctic environment is important. In this study, we examined available satellite ice cover and surface temperature data, wind and pressure data, and ocean hydrographic data to gain insights into the warming phenomenon. The areas of open water in both western and eastern regions of the Arctic were found to follow a cyclical pattern with approximately decadal period but with a lag of about three years between the two regions. The pattern was interrupted by unusually large anomalies in open water area in the western region in 1993 and 1998 and in the eastern region in 1995. The big 1998 open water anomaly occurred at the same time when a large surface temperature anomaly was also occurring in the area and adjacent regions. The infrared temperature data show for the first time the complete spatial scope of the warming anomalies and it is apparent that despite the magnitude of the 1998 anomaly, it is basically confined to North America and the Western Arctic. The large increases in open water areas in the Western Sector form 1996 to 1998 were observed to be coherent with changing wind directions which was predominantly cyclonic in 1996 and anti-cyclonic in 1997 and 1998. Detailed hydrography measurements up to 500 m depth over the same general area in April 1996 and April 1997 also indicate significant freshening and warming in the upper part of the mixed layer suggesting increases in ice melt. Continuous ocean temperature and salinity data from ocean buoys confirm this result and show significant seasonal changes from 1996 to 1998, at depths of 8 m, 45 m, and 75 m. Long data records of temperature and hydrography were also examined and the potential

  10. 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.

  11. Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

    Science.gov (United States)

    NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

    2015-12-01

    Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising

  12. When can decreasing diversification rates be detected with molecular phylogenies and the fossil record?

    Science.gov (United States)

    Liow, Lee Hsiang; Quental, Tiago B; Marshall, Charles R

    2010-12-01

    Traditionally, patterns and processes of diversification could only be inferred from the fossil record. However, there are an increasing number of tools that enable diversification dynamics to be inferred from molecular phylogenies. The application of these tools to new data sets has renewed interest in the question of the prevalence of diversity-dependent diversification. However, there is growing recognition that the absence of extinct species in molecular phylogenies may prevent accurate inferences about the underlying diversification dynamics. On the other hand, even though the fossil record provides direct data on extinct species, its incompleteness can also mask true diversification processes. Here, using computer-generated diversity-dependent phylogenies, we mimicked molecular phylogenies by eliminating extinct lineages. We also simulated the fossil record by converting the temporal axis into discrete intervals and imposing a variety of preservation processes on the lineages. Given the lack of reliable phylogenies for many fossil marine taxa, we also stripped away phylogenetic information from the computer-generated phylogenies. For the simulated molecular phylogenies, we examined the efficacy of the standard metric (the γ statistic) for identifying decreasing rates of diversification. We find that the underlying decreasing rate of diversification is detected only when the rate of change in the diversification rate is high, and if the molecular phylogeny happens to capture the diversification process as the equilibrium diversity is first reached or shortly thereafter. In contrast, estimating rates of diversification from the simulated fossil record captures the expected zero rate of diversification after equilibrium is reached under a wide range of preservation scenarios. The ability to detect the initial decreasing rate of diversification is lost as the temporal resolution of the fossil record drops and with a decreased quality of preservation. When the

  13. 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 approximately the same position over the past similar to 50 years. There is no evidence of a change in ice motion between 1968 and 2001, based on a comparison of velocities derived from terrestrial surveying and feature tracking using sequential satellite images. Estimates of flux near the entrance to the fjord...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

  14. 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...... vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier....

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

    Directory of Open Access Journals (Sweden)

    Khalil Mohamad

    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.

  16. Detection of the short-term preseizure changes in EEG recordings using complexity and synchrony analysis

    Institute of Scientific and Technical Information of China (English)

    JIA Wenyan; KONG Na; MA Jun; LIU Hesheng; GAO Xiaorong; GAO Shangkai; YANG Fusheng

    2006-01-01

    An important consideration in epileptic seizure prediction is proving the existence of a pre-seizure state that can be detected using various signal processing algorithms. In the analyses of intracranial electroencephalographic (EEG)recordings of four epilepsy patients, the short-term changes in the measures of complexity and synchrony were detected before the majority of seizure events across the sample patient population. A decrease in complexity and increase in phase synchrony appeared several minutes before seizure onset and the changes were more pronounced in the focal region than in the remote region. This result was also validated statistically using a surrogate data method.

  17. A Robust Method for Detecting Interdependences Application to Intracranially Recorded EEG

    CERN Document Server

    Arnhold, J; Lehnertz, K; Elger, C E

    1999-01-01

    We present a measure for characterizing statistical relationships between two time sequences. In contrast to commonly used measures like cross-correlations, coherence and mutual information, the proposed measure is non-symmetric and provides information about the direction of interdependence. It is closely related to recent attempts to detect generalized synchronization. However, we do not assume a strict functional relationship between the two time sequences and try to define the measure so as to be robust against noise, and to detect also weak interdependences. We apply our measure to intracranially recorded electroencephalograms of patients suffering from severe epilepsies.

  18. Improved sea level record over the satellite altimetry era (1993-2010) from the Climate Change Initiative project

    DEFF Research Database (Denmark)

    Ablain, M.; Cazenave, A.; Larnicol, G.

    2015-01-01

    Sea level is one of the 50 Essential Climate Variables (ECVs) listed by the Global Climate Observing System (GCOS) in climate change monitoring. In the past two decades, sea level has been routinely measured from space using satellite altimetry techniques. In order to address a number of importan...... present preliminary independent validations of the SL_cci products, based on tide gauges comparison and a sea level budget closure approach, as well as comparisons with ocean reanalyses and climate model outputs....

  19. Frequency based detection and monitoring of small scale explosive activity by comparing satellite and ground based infrared observations at Stromboli Volcano, Italy

    Science.gov (United States)

    Worden, Anna; Dehn, Jonathan; Ripepe, Maurizio; Donne, Dario Delle

    2014-08-01

    Thermal activity is a common precursor to explosive volcanic activity. The ability to use these thermal precursors to monitor the volcano and obtain early warning about upcoming activity is beneficial for both human safety and infrastructure security. By using a very reliably active volcano, Stromboli Volcano in Italy, a method has been developed and tested to look at changes in the frequency of small scale explosive activity and how this activity changes prior to larger, ash producing explosive events. Thermal camera footage was used to designate parameters for typical explosions at Stromboli (size of spatter field, cooling rate, frequency of explosions) and this information was applied to characterize explosions in satellite imagery. Satellite data from The National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer (MODIS) and US/Japan designed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for numerous periods in 2002 to 2009 were analyzed for thermal features which were used to calculate an estimate of the level of activity during the given time period. The results at Stromboli showed a high level of small scale explosions which stop completely prior to large paroxysmal eruptive episodes. This activity also corresponds well to seismic and infrasonic records at Stromboli, indicating that this thermal infrared monitoring method may be used in conjunction with other detection methods where available, and also indicates that it may be a useful method for volcano monitoring when other methods (e.g. seismic instrumentation, infrasound arrays, etc.) are not available.

  20. Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

    Science.gov (United States)

    Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

    2012-01-01

    Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

  1. 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.

  2. 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

    2013-01-01

    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. PMID:23429197

  3. 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.

  4. Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

    Science.gov (United States)

    Wang, Shifeng; So, Emily; Smith, Pete

    2015-04-01

    Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.

  5. Image jitter detection and compensation using a high-frequency angular displacement method for Yaogan-26 remote sensing satellite

    Science.gov (United States)

    Wang, Mi; Fan, Chengcheng; Pan, Jun; Jin, Shuying; Chang, Xueli

    2017-08-01

    Satellite platform jitter is an important factor restricting the imaging quality of high-resolution (HR) optical satellite images. To address the critical issue of compensation for attitude jitter in HR images, this paper proposes a steady-state reimaging model using high-frequency angular displacement data to detect and compensate for the attitude jitter of HR images. The bidirectional Kalman filter and overall weighted smoothing method helps realizing information fusion of star sensor and angular displacement sensor and obtaining the high-frequency attitude for image jitter detection. Then, the steady reimaging model is used to correct the distorted image with geolocation consistency based on a rigorous geometric model. The Yaogan-26 remote sensing satellite's distorted panchromatic images of airports, targets and calibration fields affected by platform jitter were used to validate the effectiveness and accuracy of the proposed method. The compensation results show that the proposed method can effectively improve the relative geometric quality of images affected by platform jitter, with the images' jitter distortion being clearly eliminated. Compared to the conventional compensation method that bundle adjustment with GCPs, the absolute geometric accuracy can also be improved.

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

    Science.gov (United States)

    Despins, Laurel A

    2016-09-13

    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.

  7. 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......RNA and DSN-assisted target recycling, the core-satellite magnetic superstructures release their "satellites" to the suspension, which subsequently can be quantified accurately in a low-cost and user-friendly optomagnetic setup. Target miRNAs are preserved in the cleaving reaction and can thereby trigger more...... cleavage and release of "satellites". For singleplex detection of let-7b, a linear detection range between 10 fM and 10 nM was observed, and a detection limit of 4.8 fM was obtained within a total assay time of 70 min. Multiplexing was achieved by releasing nanoparticles of different sizes in the presence...

  8. Status of AIS Frequencies Nationally and Internationally: Improving Satellite Detection of AIS

    Science.gov (United States)

    2008-09-04

    about AIS slot congestion? ITU-R Report M.2084 – JSC, Target ship located in the mid Atlantic Ocean Norwegian Defence Research Establishment RTCM 2008...Observation 6 Satellites; 4 Hour Observation Six Satellites; 12 Hour Observation How solid is Bjørn Narheim’s ”wall”? NDRE’s RTCM 2008 presentation “AIS...composition 96Total number of bits Set to zero, to preserve byte boundaries1Spare 0 = Position is the current GNSS position; 1 = Reported position is

  9. 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.

  10. Automatic Detection of Omega Signals Captured by the Poynting Flux Analyzer (PFX) on Board the Akebono Satellite

    CERN Document Server

    Suarjaya, I Made Agus Dwi; Goto, Yoshitaka

    2016-01-01

    The Akebono satellite was launched in 1989 to observe the Earth's magnetosphere and plasmasphere. Omega was a navigation system with 8 ground stations transmitter and had transmission pattern that repeats every 10 s. From 1989 to 1997, the PFX on board the Akebono satellite received signals at 10.2 kHz from these stations. Huge amounts of PFX data became valuable for studying the propagation characteristics of VLF waves in the ionosphere and plasmasphere. In this study, we introduce a method for automatic detection of Omega signals from the PFX data in a systematic way, it involves identifying a transmission station, calculating the delay time, and estimating the signal intensity. We show the reliability of the automatic detection system where we able to detect the omega signal and confirmed its propagation to the opposite hemisphere along the Earth's magnetic field lines. For more than three years (39 months), we detected 43,734 and 111,049 signals in the magnetic and electric field, respectively, and demons...

  11. Automatic Detection of Omega Signals Captured by the Poynting Flux Analyzer (PFX on Board the Akebono Satellite

    Directory of Open Access Journals (Sweden)

    Made Agus Dwi Suarjaya

    2016-10-01

    Full Text Available The Akebono satellite was launched in 1989 to observe the Earth’s magnetosphere and plasmasphere. Omega was a navigation system with 8 ground stations transmitter and had transmission pattern that repeats every 10 s. From 1989 to 1997, the PFX on board the Akebono satellite received signals at 10.2 kHz from these stations. Huge amounts of PFX data became valuable for studying the propagation characteristics of VLF waves in the ionosphere and plasmasphere. In this study, we introduce a method for automatic detection of Omega signals from the PFX data in a systematic way, it involves identifying a transmission station, calculating the delay time, and estimating the signal intensity. We show the reliability of the automatic detection system where we able to detect the omega signal and confirmed its propagation to the opposite hemisphere along the Earth’s magnetic field lines. For more than three years (39 months, we detected 43,734 and 111,049 signals in the magnetic and electric field, respectively, and demonstrated that the proposed method is powerful enough for the statistical analyses.

  12. 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.

  13. 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.

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

    Science.gov (United States)

    2003-03-01

    1-9 ACTEX · · · Advanced Controls Technology Experiment . . . . . . . . 2-2 ETS-VI · · · Engineering Test Satellite-VI...Technology Experiment ( ACTEX ), Stetson’s on-orbit ID work on NOAA-2 [33], and Wertz and Lee’s operational MOI estimation of the Cassini spacecraft. 2.1.2

  15. Near real-time disturbance detection using satellite image time series

    NARCIS (Netherlands)

    Verbesselt, J.P.; Zeileis, A.; Herold, M.

    2012-01-01

    Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic

  16. Gravitational detection of a low-mass dark satellite galaxy at cosmological distance

    NARCIS (Netherlands)

    Vegetti, S.; Lagattuta, D. J.; McKean, J. P.; Auger, M. W.; Fassnacht, C. D.; Koopmans, L. V. E.

    2012-01-01

    The mass function of dwarf satellite galaxies that are observed around Local Group galaxies differs substantially from simulations(1-5) based on cold dark matter: the simulations predict many more dwarf galaxies than are seen. The Local Group, however, may be anomalous in this regard(6,7). A massive

  17. Gravitational detection of a low-mass dark satellite galaxy at cosmological distance

    NARCIS (Netherlands)

    Vegetti, S.; Lagattuta, D. J.; McKean, J. P.; Auger, M. W.; Fassnacht, C. D.; Koopmans, L. V. E.

    2012-01-01

    The mass function of dwarf satellite galaxies that are observed around Local Group galaxies differs substantially from simulations based on cold dark matter: the simulations predict many more dwarf galaxies than are seen. The Local Group, however, may be anomalous in this regard. A massive dark sate

  18. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

  19. Satellite-based phenology detection in broadleaf forests in South-Western Germany

    Science.gov (United States)

    Misra, Gourav; Buras, Allan; Menzel, Annette

    2016-04-01

    Many techniques exist for extracting phenological information from time series of satellite data. However, there have been only a few successful attempts to temporarily match satellite-derived observations with ground based phenological observations (Fisher et al., 2006; Hamunyela et al., 2013; Galiano et al., 2015). Such studies are primarily plagued with problems relating to shorter time series of satellite data including spatial and temporal resolution issues. A great challenge is to correlate spatially continuous and pixel-based satellite information with spatially discontinuous and point-based, mostly species-specific, ground observations of phenology. Moreover, the minute differences in phenology observed by ground volunteers might not be sufficient to produce changes in satellite-measured reflectance of vegetation, which also exposes the difference in the definitions of phenology (Badeck et al., 2004; White et al., 2014). In this study Start of Season (SOS) was determined for broadleaf forests at a site in south-western Germany using MODIS-sensor time series of Normalised Difference Vegetation Index (NDVI) data for the years covering 2001 to 2013. The NDVI time series raster data was masked for broadleaf forests using Corine Land Cover dataset, filtered and corrected for snow and cloud contaminations, smoothed with a Gaussian filter and interpolated to daily values. Several SOS techniques cited in literature, namely thresholds of amplitudes (20%, 50%, 60% and 75%), rates of change (1st, 2nd and 3rd derivative) and delayed moving average (DMA) were tested for determination of satellite SOS. The different satellite SOS were then compared with a species-rich ground based phenology information (e.g. understory leaf unfolding, broad leaf unfolding and greening of evergreen tree species). Working with all the pixels at a finer resolution, it is seen that the temporal trends in understory and broad leaf species are well captured. Initial analyses show promising

  20. High speed detection of R-R intervals for universal Holter recordings.

    Science.gov (United States)

    Sekioka, K; Takaba, H; Nakano, T

    1997-01-01

    Heart rate variability (HRV) has been gaining popularity for its potential to estimate the autonomic nerve function and prognosis of patients with cardiovascular diseases. Holter recordings have been used for the measurement of R-R intervals in out-patients and for the estimation of circadian variations of HRV. However, when the manufacturer of the Holter tape recorder is not the same as that of the Holter analyzer a correction of the tape speed error for the accurate measurement of the R-R intervals is abandoned. The simultaneous assessment of additional physical parameters recorded on the Holter recorder and R-R interval is not possible with commercial software. To overcome these problems, we developed a system to detect R-R intervals at the playback speed of a Holter analyzer 500 times real-time with the correction of tape speed error from a system clock recorded on the Holter tape. High- and low-pass filter processed ECG signals and a comparator provided digital signals representing the R-R intervals. The R-R intervals and system clock intervals (tape speed) were measured simultaneously by interrupt-driven software, using timer-counters in a personal computer. The measured R-R intervals were corrected with the system clock intervals. The power spectra of the tape speed error showed that tape speed error significantly affects the power spectra of HRV, if not corrected. This method is applicable to Holter tape recorders of any manufacturer. This system also enables the simultaneous measurement of HRV and other physical parameters to evaluate their relations.

  1. An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS Satellite Data Record.

    Science.gov (United States)

    Schaeffer, Blake A; Hagy, James D; Conmy, Robyn N; Lehrter, John C; Stumpf, Richard P

    2012-01-17

    Human activities on land increase nutrient loads to coastal waters, which can increase phytoplankton production and biomass and associated ecological impacts. Numeric nutrient water quality standards are needed to protect coastal waters from eutrophication impacts. The Environmental Protection Agency determined that numeric nutrient criteria were necessary to protect designated uses of Florida's waters. The objective of this study was to evaluate a reference condition approach for developing numeric water quality criteria for coastal waters, using data from Florida. Florida's coastal waters have not been monitored comprehensively via field sampling to support numeric criteria development. However, satellite remote sensing had the potential to provide adequate data. Spatial and temporal measures of SeaWiFS OC4 chlorophyll-a (Chl(RS)-a, mg m(-3)) were resolved across Florida's coastal waters between 1997 and 2010 and compared with in situ measurements. Statistical distributions of Chl(RS)-a were evaluated to determine a quantitative reference baseline. A binomial approach was implemented to consider how new data could be assessed against the criteria. The proposed satellite remote sensing approach to derive numeric criteria may be generally applicable to other coastal waters.

  2. Development and validation of algorithms for the detection of statin myopathy signals from electronic medical records.

    Science.gov (United States)

    Chan, S L; Tham, M Y; Tan, S H; Loke, C; Foo, Bpq; Fan, Y; Ang, P S; Brunham, L R; Sung, C

    2017-05-01

    The purpose of this study was to develop and validate sensitive algorithms to detect hospitalized statin-induced myopathy (SIM) cases from electronic medical records (EMRs). We developed four algorithms on a training set of 31,211 patient records from a large tertiary hospital. We determined the performance of these algorithms against manually curated records. The best algorithm used a combination of elevated creatine kinase (>4× the upper limit of normal (ULN)), discharge summary, diagnosis, and absence of statin in discharge medications. This algorithm achieved a positive predictive value of 52-71% and a sensitivity of 72-78% on two validation sets of >30,000 records each. Using this algorithm, the incidence of SIM was estimated at 0.18%. This algorithm captured three times more rhabdomyolysis cases than spontaneous reports (95% vs. 30% of manually curated gold standard cases). Our results show the potential power of utilizing data and text mining of EMRs to enhance pharmacovigilance activities. © 2016 American Society for Clinical Pharmacology and Therapeutics.

  3. Anomalous Signals Prior to Wenchuan Earthquake Detected by Superconducting Gravimeter and Broadband Seismometers Records

    Institute of Scientific and Technical Information of China (English)

    Wenbin Shen; Dijin Wang; Cheinway Hwang

    2011-01-01

    Using 1 Hz sampling records at one superconducting gravimeter (SG) station and 11 broadband seismometer stations,we found anomalous signals prior to the 2008 Wenchuan(汶川)earthquake event.The tides are removed from the original SG records to obtain the gravity residuals.Applying the Hilbert-Huang transform (HHT) and the wavelet analysis to the SG gravity residuals leads to time-frequency spectra,which suggests that there is an anomalous signal series around 39 h prior to the event.The period and the magnitude of the anomalous signal series are about 8 s and 3×10-8 m/s2 (3 μGal),respectively.In another aspect,applying HHT analysis technique to 11 records at broadband seismometer stations shows that most of them contain anomalous signals prior to the Wenchuan event,and the marginal spectra of 8 inland stations show an apparent characteristic of double peaks in anomalous days compared to the only one peak of the marginal spectra in quiet days.Preliminary investigations suggest that the anomalous signals prior to the earthquake are closely related to the low-frequency earthquake (LFE).We concluded that the SG data as well as the broadband seismometers records might be significant information sources in detecting the anomalous signals prior to large earthquakes.

  4. A NEW OBJECT-BASED FRAMEWORK TO DETECT SHODOWS IN HIGH-RESOLUTION SATELLITE IMAGERY OVER URBAN AREAS

    Directory of Open Access Journals (Sweden)

    N. Tatar

    2015-12-01

    Full Text Available In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

  5. Hole burning, Stark effect, and data storage: 2: holographic recording and detection of spectral holes.

    Science.gov (United States)

    Caro, C D; Renn, A; Wild, U P

    1991-07-10

    The properties of holographic recording and detection of spectral holes in the frequency and electric-field dimension are investigated. To optimize the storage properties of optical memory devices, based on spectral hole burning and holography, cross-talk effects between adjacent holograms have to be minimized. These interactions depend on the relative phases of the holograms chosen during the recording stage. Using free-base chlorin (2,3-dihydroporphyrin) in polyvinyl butyral as host at a temperature of 1.7 K, the influence of the relative phase difference between holograms is demonstrated in both the frequency and the electric-field dimension. Experimental results are presented for rows and columns of holograms stored either in the laser frequency or the electric-field dimension and compared to transmission data. Using both dimensions a 10 x 10 matrix of holograms has been stored within the range of a single wave number.

  6. Using Single Sensillum Recording to Detect Olfactory Neuron Responses of Bed Bugs to Semiochemicals.

    Science.gov (United States)

    Liu, Feng; Liu, Nannan

    2016-01-18

    The insect olfactory system plays an important role in detecting semiochemicals in the environment. In particular, the antennal sensilla which house single or multiple neurons inside, are considered to make the major contribution in responding to the chemical stimuli. By directly recording action potential in the olfactory sensillum after exposure to stimuli, single sensillum recording (SSR) technique provides a powerful approach for investigating the neural responses of insects to chemical stimuli. For the bed bug, which is a notorious human parasite, multiple types of olfactory sensillum have been characterized. In this study, we demonstrated neural responses of bed bug olfactory sensilla to two chemical stimuli and the dose-dependent responses to one of them using the SSR method. This approach enables researchers to conduct early screening for individual chemical stimuli on the bed bug olfactory sensilla, which would provide valuable information for the development of new bed bug attractants or repellents and benefits the bed bug control efforts.

  7. Multiband array detection and location of seismic sources recorded by dense seismic networks

    Science.gov (United States)

    Poiata, Natalia; Satriano, Claudio; Vilotte, Jean-Pierre; Bernard, Pascal; Obara, Kazushige

    2016-06-01

    We present a new methodology for detection and space-time location of seismic sources based on multiscale, frequency-selective coherence of the wave field recorded by dense large-scale seismic networks and local antennas. The method is designed to enhance coherence of the signal statistical features across the array of sensors and consists of three steps: signal processing, space-time imaging, and detection and location. The first step provides, for each station, a simplified representation of seismic signal by extracting multiscale non-stationary statistical characteristics, through multiband higher-order statistics or envelopes. This signal processing scheme is designed to account for a priori unknown transients, potentially associated with a variety of sources (e.g. earthquakes, tremors), and to prepare data for a better performance in posterior steps. Following space-time imaging is carried through 3-D spatial mapping and summation of station-pair time-delay estimate functions. This step produces time-series of 3-D spatial images representing the likelihood that each pixel makes part of a source. Detection and location is performed in the final step by extracting the local maxima from the 3-D spatial images. We demonstrate the efficiency of the method in detecting and locating seismic sources associated with low signal-to-noise ratio on an example of the aftershock earthquake records from local stations of International Maule Aftershock Deployment in Central Chile. The performance and potential of the method to detect, locate and characterize the energy release associated with possibly mixed seismic radiation from earthquakes and low-frequency tectonic tremors is further tested on continuous data from southwestern Japan.

  8. A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

    Science.gov (United States)

    Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

    2013-08-01

    Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short

  9. Contribution of ground surface altitude difference to thermal anomaly detection using satellite images: Application to volcanic/geothermal complexes in the Andes of Central Chile

    Science.gov (United States)

    Gutiérrez, Francisco J.; Lemus, Martín; Parada, Miguel A.; Benavente, Oscar M.; Aguilera, Felipe A.

    2012-09-01

    Detection of thermal anomalies in volcanic-geothermal areas using remote sensing methodologies requires the subtraction of temperatures, not provided by geothermal manifestations (e.g. hot springs, fumaroles, active craters), from satellite image kinetic temperature, which is assumed to correspond to the ground surface temperature. Temperatures that have been subtracted in current models include those derived from the atmospheric transmittance, reflectance of the Earth's surface (albedo), topography effect, thermal inertia and geographic position effect. We propose a model that includes a new parameter (K) that accounts for the variation of temperature with ground surface altitude difference in areas where steep relief exists. The proposed model was developed and applied, using ASTER satellite images, in two Andean volcanic/geothermal complexes (Descabezado Grande-Cerro Azul Volcanic Complex and Planchón-Peteroa-Azufre Volcanic Complex) where field data of atmosphere and ground surface temperature as well as radiation for albedo calibration were obtained in 10 selected sites. The study area was divided into three zones (Northern, Central and Southern zones) where the thermal anomalies were obtained independently. K value calculated for night images of the three zones are better constrained and resulted to be very similar to the Environmental Lapse Rate (ELR) determined for a stable atmosphere (ELR > 7 °C/km). Using the proposed model, numerous thermal anomalies in areas of ≥ 90 m × 90 m were identified that were successfully cross-checked in the field. Night images provide more reliable information for thermal anomaly detection than day images because they record higher temperature contrast between geothermal areas and its surroundings and correspond to more stable atmospheric condition at the time of image acquisition.

  10. 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.

  11. Observation results of relativistic electrons detected by Fengyun-1 satellite and analysis of relativistic electron enhancement (REE) events

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The space particle component detector on Fengyun-1 satellite which works at the sun-synchronous orbit of about 870 km altitude has detected relativistic electrons for a long time. In comparison with the SAMPEX satellite observations during 1999 -2004, the relativistic electron data from Fengyun-1 satellite from June 1999 to 2005 are used to analyze the relativistic electron enhancement (REE) events at the low earth orbit, and the possible correlation among REE events at the low earth orbit, high-speed solar wind and geomagnetic storms is discussed. The statistical result presents that 45 REE events are found in total during this time period, and the strong REE events with the maximum daily average flux > 400 cm?2·sr?1·s?1 occur mostly during the transition period from solar maximum to solar minimum. Among these 45 REE events, four strong REE events last a longer time period from 26- to 51-day and correlate closely with high speed solar wind and strong geo- magnetic storms. Meanwhile, several strong geomagnetic storms occur continu- ously before these REE events, and these continuous geomagnetic storms would be an important factor causing these long-lasting strong REE events. The correlation analysis for overall 45 events indicates that the strength of the REE events corre- lates with the solar wind speed and the strength of the geomagnetic storm, and the correlation for strong REE events is much stronger than that for weak REE events.

  12. Effects of Shared Electronic Health Record Systems on Drug-Drug Interaction and Duplication Warning Detection

    Directory of Open Access Journals (Sweden)

    Christoph Rinner

    2015-01-01

    Full Text Available Shared electronic health records (EHRs systems can offer a complete medication overview of the prescriptions of different health care providers. We use health claims data of more than 1 million Austrians in 2006 and 2007 with 27 million prescriptions to estimate the effect of shared EHR systems on drug-drug interaction (DDI and duplication warnings detection and prevention. The Austria Codex and the ATC/DDD information were used as a knowledge base to detect possible DDIs. DDIs are categorized as severe, moderate, and minor interactions. In comparison to the current situation where only DDIs between drugs issued by a single health care provider can be checked, the number of warnings increases significantly if all drugs of a patient are checked: severe DDI warnings would be detected for 20% more persons, and the number of severe DDI warnings and duplication warnings would increase by 17%. We show that not only do shared EHR systems help to detect more patients with warnings but DDIs are also detected more frequently. Patient safety can be increased using shared EHR systems.

  13. Status and Future of a Real-time Global Flood Detection and Forecasting System Using Satellite Rainfall Information

    Science.gov (United States)

    Adler, R. F.; Wu, H.; Hong, Y.; Policelli, F.; Pierce, H.

    2011-12-01

    Over the last several years a Global Flood Monitoring System (GFMS) has been running in real-time to detect the occurrence of floods (see trmm.gsfc.nasa.gov and click on "Floods and Landslides"). The system uses 3-hr resolution composite rainfall analyses (TRMM Multi-satellite Precipitation Analysis [TMPA]) as input into a hydrological model that calculates water depth at each grid (at 0.25 degree latitude-longitude) over the tropics and mid-latitudes. These calculations can provide information useful to national and international agencies in understanding the location, intensity, timeline and impact on populations of these significant hazard events. The status of these flood calculations will be shown by case study examples and a statistical comparison against a global flood event database. The validation study indicates that results improve with longer duration (> 3 days) floods and that the statistics are impacted by the presence of dams, which are not accounted for in the model calculations. Limitations in the flood calculations that are related to the satellite rainfall estimates include space and time resolution limitations and underestimation of shallow orographic and monsoon system rainfall. The current quality of these flood estimations is at the level of being useful, but there is a potential for significant improvement, mainly through improved and more timely satellite precipitation information and improvement in the hydrological models being used. NASA's Global Precipitation Measurement (GPM) program should lead to better precipitation analyses utilizing space-time interpolations that maintain accurate intensity distributions along with methods to disaggregate the rain information research should lead to improved rain estimation for shallow, orographic rainfall systems and some types of monsoon rainfall, a current problem area for satellite rainfall. Higher resolution flood models with accurate routing and regional calibration, and the use of satellite

  14. Delay analysis of an integrated voice and data access protocol with collision detection for multimedia satellite networks

    Science.gov (United States)

    Poon, Charles C. K.; Suda, Tatsuya

    1992-03-01

    The novel multiple-access scheme for multimedia satellite networks presented is based on a combination of FDMA and TDMA, integrating both circuit and packet-switching techniques. While the circuit-switching method is used to transmit such stream-type traffic as real-time voice communications, packet-switching is used to transmit such 'bursty' traffic as interactive data. A ground radio network is assumed for control signaling; the tone sense multiple access/partial collision detection scheme is implemented on this network to enhance the integrated access scheme's performance.

  15. Design of volume hologram filters for suppression of daytime sky brightness in artificial satellite detection.

    Science.gov (United States)

    Gao, Hanhong; Watson, Jonathan M; Stuart, Joseph Scott; Barbastathis, George

    2013-03-11

    We present a design methodology for volume hologram filters (VHFs) with telephoto objectives to improve contrast of solar-illuminated artificial satellites observed with a ground-based optical telescope and camera system operating in daytime. VHFs provide the ability to selectively suppress incoming light based on the range to the source, and are used to suppress the daylight background noise since signal (satellite) and noise (daylight scatterers) are located at different altitudes. We derive the overall signal-to-noise ratio (SNR) enhancement as the system metric, and balance main design parameters over two key performance considerations--daylight attenuation and spectral bandwidth--to optimize the functioning of VHFs. Overall SNR enhancement of 7.5 has been achieved. Usage of multi-pixel cameras can potentially further refine this system.

  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. Multi-Spectral Satellite Imagery and Land Surface Modeling Supporting Dust Detection and Forecasting

    Science.gov (United States)

    Molthan, A.; Case, J.; Zavodsky, B.; Naeger, A. R.; LaFontaine, F.; Smith, M. R.

    2014-12-01

    Current and future multi-spectral satellite sensors provide numerous means and methods for identifying hazards associated with polluting aerosols and dust. For over a decade, the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center in Huntsville has focused on developing new applications from near real-time data sources in support of the operational weather forecasting community. The SPoRT Center achieves these goals by matching appropriate analysis tools, modeling outputs, and other products to forecast challenges, along with appropriate training and end-user feedback to ensure a successful transition. As a spinoff of these capabilities, the SPoRT Center has recently focused on developing collaborations to address challenges with the public health community, specifically focused on the identification of hazards associated with dust and pollution aerosols. Using multispectral satellite data from the SEVIRI instrument on the Meteosat series, the SPoRT team has leveraged EUMETSAT techniques for identifying dust through false color (RGB) composites, which have been used by the National Hurricane Center and other meteorological centers to identify, monitor, and predict the movement of dust aloft. Similar products have also been developed from the MODIS and VIIRS instruments onboard the Terra and Aqua, and Suomi-NPP satellites, respectively, and transitioned for operational forecasting use by offices within NOAA's National Weather Service. In addition, the SPoRT Center incorporates satellite-derived vegetation information and land surface modeling to create high-resolution analyses of soil moisture and other land surface conditions relevant to the lofting of wind-blown dust and identification of other, possible public-health vectors. Examples of land surface modeling and relevant predictions are shown in the context of operational decision making by forecast centers with potential future applications to public health arenas.

  18. 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.

  19. Automatic Real-Time Embedded QRS Complex Detection for a Novel Patch-Type Electrocardiogram Recorder.

    Science.gov (United States)

    Saadi, Dorthe B; Tanev, George; Flintrup, Morten; Osmanagic, Armin; Egstrup, Kenneth; Hoppe, Karsten; Jennum, Poul; Jeppesen, Jørgen L; Iversen, Helle K; Sorensen, Helge B D

    2015-01-01

    Cardiovascular diseases are projected to remain the single leading cause of death globally. Timely diagnosis and treatment of these diseases are crucial to prevent death and dangerous complications. One of the important tools in early diagnosis of arrhythmias is analysis of electrocardiograms (ECGs) obtained from ambulatory long-term recordings. The design of novel patch-type ECG recorders has increased the accessibility of these long-term recordings. In many applications, it is furthermore an advantage for these devices that the recorded ECGs can be analyzed automatically in real time. The purpose of this study was therefore to design a novel algorithm for automatic heart beat detection, and embed the algorithm in the CE marked ePatch heart monitor. The algorithm is based on a novel cascade of computationally efficient filters, optimized adaptive thresholding, and a refined search back mechanism. The design and optimization of the algorithm was performed on two different databases: The MIT-BIH arrhythmia database ([Formula: see text]%, [Formula: see text]) and a private ePatch training database ([Formula: see text]%, [Formula: see text]%). The offline validation was conducted on the European ST-T database ([Formula: see text]%, [Formula: see text]%). Finally, a double-blinded validation of the embedded algorithm was conducted on a private ePatch validation database ([Formula: see text]%, [Formula: see text]%). The algorithm was thus validated with high clinical performance on more than 300 ECG records from 189 different subjects with a high number of different abnormal beat morphologies. This demonstrates the strengths of the algorithm, and the potential for this embedded algorithm to improve the possibilities of early diagnosis and treatment of cardiovascular diseases.

  20. Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record

    Science.gov (United States)

    van der Schalie, Robin; de Jeu, Richard; Kerr, Yann; Wigneron, Jean-Pierre; Rodríguez-Fernández, Nemesio; Al-Yaari, Amen; Drusch, Matthias; Mecklenburg, Susanne; Dolman, Han

    2016-04-01

    Datasets that are derived from satellite observations are becoming increasingly important for measuring key parameters of the Earth's climate and are therefore crucial in research on climate change, giving the opportunity to researchers to detect anomalies and long-term trends globally. One of these key parameters is soil moisture (SM), which has a large impact on water, energy and biogeochemical cycles worldwide. A long-term SM data record from active and passive microwave satellite observations was developed as part of ESA's Climate Change Initiative (ESA-CCI-SM, http://www.esa-soilmoisture-cci.org/). Currently the dataset covers a period from 1978 to 2014 and is updated regularly, observations from a several microwave satellites including: ERS-1, ERS-2, METOP-A, Nimbus 7 SMMR, DMSP SSM/I, TRMM TMI, Aqua AMSRE, Coriolis WindSat, and GCOM-W1 AMSR2. In 2009, ESA launched the Soil Moisture and Ocean Salinity (SMOS, Kerr et al., 2010) mission, carrying onboard a unique L-band radiometer, but its SM retrievals are not yet part of this dataset. Due to the different radiometric characteristics of SMOS, integrating SMOS into the ESA-CCI-SM dataset is not straight forward. Therefore several approaches have been tested to fuse soil moisture retrievals from SMOS and AMSRE, which currently forms the basis of the passive microwave part within ESA-CCI-SM project. These approaches are: 1. A Neural Network Fusion approach (Rodríguez-Fernández et al., 2015), 2. A regression approach (Wigneron et al., 2004; Al-Yaari et al., 2015) and 3. A radiative transfer based approach, using the Land Parameter Retrieval Model (Van der Schalie et al., 2016). This study evaluates the three different approaches and tests their skills against multiple datasets, including MERRA-Land, ERA-Interim/Land, the current ESA-CCI-SM v2.2 and in situ measurements from the International Soil Moisture Network and present a recommendation for the potential integration of SMOS soil moisture into the ESA

  1. Heart rate detection in low amplitude non-invasive fetal ECG recordings.

    Science.gov (United States)

    Peters, Chris; Vullings, Rik; Bergmans, Jan; Oei, Guid; Wijn, Pieter

    2006-01-01

    Multi-electrode electrical measurements on the maternal abdomen may provide a valuable alternative to standard fetal monitoring. Removal of the maternal ECG from these recordings by means of subtracting a weighted linear combination of segments from preceding maternal ECG complexes, results in fetal ECG traces from which the fetal heart rate can be determined. Unfortunately, these traces often contain too much noise to determine the heart rate by R-peak detection. To overcome this limitation, an algorithm has been developed that calculates the heart rate based on cross-correlation. To validate the algorithm, noise was added to a fetal scalp ECG recording to simulate low amplitude abdominal recordings. Heart rates calculated by the algorithm were compared to the heart rates from the original scalp ECG. For simulated signals with a signal to noise ratio of 2, the coefficient of correlation was 0.99 (pheart rate, multi-electrode electrical measurements on the maternal abdomen now can be used for fetal monitoring in relatively early stages of pregnancy or other situations where ECG amplitudes are low or noise levels are high.

  2. Detection of Seagrass Distribution Changes from 1991 to 2006 in Xincun Bay, Hainan, with Satellite Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chaoyu Yang

    2009-02-01

    Full Text Available Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides,Thalassia hemperichii distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI. Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.

  3. Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

    Directory of Open Access Journals (Sweden)

    M. Marghany

    2015-06-01

    Full Text Available Oil spill pollution has a substantial role in damaging the marine ecosystem. Oil spill that floats on top of water, as well as decreasing the fauna populations, affects the food chain in the ecosystem. In fact, oil spill is reducing the sunlight penetrates the water, limiting the photosynthesis of marine plants and phytoplankton. Moreover, marine mammals for instance, disclosed to oil spills their insulating capacities are reduced, and so making them more vulnerable to temperature variations and much less buoyant in the seawater. This study has demonstrated a design tool for oil spill detection in SAR satellite data using optimization of Entropy based Multi-Objective Evolutionary Algorithm (E-MMGA which based on Pareto optimal solutions. The study also shows that optimization entropy based Multi-Objective Evolutionary Algorithm provides an accurate pattern of oil slick in SAR data. This shown by 85 % for oil spill, 10 % look-alike and 5 % for sea roughness using the receiver-operational characteristics (ROC curve. The E-MMGA also shows excellent performance in SAR data. In conclusion, E-MMGA can be used as optimization for entropy to perform an automatic detection of oil spill in SAR satellite data.

  4. Detection of seagrass distribution changes from 1991 to 2006 in xincun bay, hainan, with satellite remote sensing.

    Science.gov (United States)

    Yang, Dingtian; Yang, Chaoyu

    2009-01-01

    Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.

  5. A methodology for near real-time change detection between Unmanned Aerial Vehicle and wide area satellite images

    Science.gov (United States)

    Fytsilis, Anastasios L.; Prokos, Anthony; Koutroumbas, Konstantinos D.; Michail, Dimitrios; Kontoes, Charalambos C.

    2016-09-01

    In this paper a novel integrated hybrid methodology for unsupervised change detection between Unmanned Aerial Vehicle (UAV) and satellite images, which can be utilized in various fields like security applications (e.g. border surveillance) and damage assessment, is proposed. This is a challenging problem mainly due to the difference in geographic coverage and the spatial resolution of the two images, as well as to the acquisition modes which lead to misregistration errors. The methodology consists of the following steps: (a) pre-processing, where the part of the satellite image that corresponds to the UAV image is determined and the UAV image is ortho-rectified using information provided by a Digital Terrain Model, (b) the detection of potential changes, which is based exclusively on intensity and image gradient information, (c) the generation of the region map, where homogeneous regions are produced by the previous potential changes via a seeded region growing algorithm and placed on the region map, and (d) the evaluation of the above regions, in order to characterize them as true changes or not. The methodology has been applied on demanding real datasets with very encouraging results. Finally, its robustness to the misregistration errors is assessed via extensive experimentation.

  6. Using records from submarine, aircraft and satellite to evaluate climate model simulations of Arctic sea ice thickness

    Directory of Open Access Journals (Sweden)

    J. Stroeve

    2014-04-01

    Full Text Available Arctic sea ice thickness distributions from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 are evaluated against observations from submarines, aircraft and satellites. While it's encouraging that the mean thickness distributions from the models are in general agreement with observations, the spatial patterns of sea ice thickness are poorly represented in most models. The poor spatial representation of thickness patterns is associated with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea ice. The climate models as a whole also tend to underestimate the rate of ice volume loss from 1979 to 2013, though the multi-model ensemble mean trend remains within the uncertainty of that from the Pan-Arctic Ice Ocean Modeling and Assimilation System. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea ice and project the timing of when a seasonally ice-free Arctic may be realized.

  7. Emergency Locator Signal Detection and Geolocation Small Satellite Constellation Feasibility Study

    OpenAIRE

    Gunderson, Adam; Byers, Celena; Klumpar, David

    2011-01-01

    Aircraft Emergency Locator Transmitters (ELTs) are vital in helping search and rescue (SAR) teams in locating downed aircraft. Currently there are two types of ELTs available; one transmits at 121.5 MHz and the other at 406 MHz. The transmitters operating at 121.5 MHz have since been abandoned by satellite tracking systems even though these beacons are still available for non-commercial aviation use. Space based receiver decommissioning of 121.5 MHz systems was largely due to an inefficiency ...

  8. 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.

  9. 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.

  10. 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

  11. An extended global Earth system data record on daily landscape freeze-thaw status determined from satellite passive microwave remote sensing

    Science.gov (United States)

    Kim, Youngwook; Kimball, John S.; Glassy, Joseph; Du, Jinyang

    2017-02-01

    The landscape freeze-thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979-2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow- and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow- and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts

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

    OpenAIRE

    Gustavo A. Carvalho; 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 chlor...

  13. Variability of Yellow River turbid plume detected with satellite remote sensing during water-sediment regulation

    Science.gov (United States)

    Guo, Kai; Zou, Tao; Jiang, Dejuan; Tang, Cheng; Zhang, Hua

    2017-03-01

    Water Sediment Regulations (WSRs) of the Yellow River (YR) have fundamentally altered the dynamics of freshwater and sediment transport in YR estuary and might profoundly affect water quality and ecosystem of the adjacent Bohai Sea. In this study, empirical algorithms were established to infer sea surface salinity and turbidity of YR plume using on surface reflectance products of MODIS and GOCI satellites in combination with observations from hydrographic surveys during the 2014 WSR event. Inter- and intraday variability of salinity and turbidity were quantitatively assessed and correlated with external forces including river discharge, tides, Coriolis force, and wind-driven circulation. The results revealed the enhanced offshore extension of turbid plume as WSR drastically increased freshwater and sediment discharge to river mouth. During WSR event, the area of low salinity plume (0.12sr-1) occupied a maximum area of 162 km2. Intraday variation observed from geostationary GOCI data clearly illustrated the dominance of tidal current on short term dispersal pattern of freshwater and sediment plume. In comparison, wind field dominated the seasonal variation in flume transport but had insignificant impact on short term river plume dynamic during WSR. Overall, this study demonstrated that the spatial and temporal dynamic of YR plume was successfully captured by satellite remote sensing, which provided an effective tool for evaluating the environmental and ecological impact of WSRs.

  14. Detecting extrasolar moons akin to Solar System satellites with an Orbital Sampling Effect

    CERN Document Server

    Heller, René

    2014-01-01

    Despite years of high accuracy observations, none of the available theoretical techniques has yet allowed the confirmation of a moon beyond the Solar System. Methods are currently limited to masses about an order of magnitude higher than the mass of any moon in the Solar System. I here present a new method sensitive to exomoons similar to the known moons. Due to the projection of transiting exomoon orbits onto the celestial plane, satellites appear more often at larger separations from their planet. After about a dozen randomly sampled observations, a photometric orbital sampling effect (OSE) starts to appear in the phase-folded transit light curve, indicative of the moons' radii and planetary distances. Two additional outcomes of the OSE emerge in the planet's transit timing variations (TTV-OSE) and transit duration variations (TDV-OSE), both of which permit measurements of a moon's mass. The OSE is the first effect that permits characterization of multi-satellite systems. I derive and apply analytical OSE d...

  15. Extending the Record of Greenland Ice Sheet Subsurface Meltwater: Exploring New Applications of Satellite Remote Sensing Data

    Science.gov (United States)

    Carter, Margeaux Louise

    The discovery of pervasive year-round englacial meltwater in southeastern Greenland by Forster et. al. [2014] has significantly changed the understanding of meltwater retention, energy balance models and Greenland hydrology. This perennial firn aquifer contained an estimated 140 +/- 20 GT of water prior to the beginning of the 2011 melt season, an amount two to three times the average annual discharge of the Greenland Ice Sheet between 1993 and 2010 Vaughn et. al. [2012]. Prior to this, retained meltwater was not considered a significant portion of the water budget in Greenland. The current most extensive observational dataset, either spatially or temporally, is from the NASA Operation Ice Bridge (OIB) Program. Due to environmental and time constraints, data is limited to a few months each year beginning in 2009. This leaves a significant need to explore new methods of monitoring retained meltwater both throughout the year and over time in order to improve the understanding of meltwater retention drivers and hydrologic consequences. Low Frequency Microwave (LFM) satellite remote sensing observations appear to be capable of revealing information regarding subsurface features in ice sheets. Polarization Difference (PD) at 6.9 and 10.7 GHz, in particular, provided useful classification of known subsurface water features, including both firn aquifers and buried supraglacial lakes, during winter 2009-2011. From 2002-2011, PD is associated with previously published meteorological drivers of these subsurface water features and the ice sheet percolation zone, where these features tend to form. Observational datasets with greater temporal and areal scope will contribute significantly to the scientific community's understanding of meltwater retention, its impact on Greenland hydrology, and possible consequences to the Arctic Climate System in an already changing climate.

  16. 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

    2012-09-01

    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 (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 operations 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, kriging, has been developed and 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 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 to both reanalysis is approximately 2 kg m−2. As SSM/I WVPA and radiances are assimilated in JMA and all

  17. 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

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

    Science.gov (United States)

    Fernández-Llamazares, Alvaro; 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.

  19. Satellite detection of Northern Hemisphere Non-Frozen season changes and associated impacts to vegetation growing seasons

    Science.gov (United States)

    Kim, Y.; Kimball, J. S.; Zhang, K.; McDonald, K. C.

    2011-12-01

    The landscape freeze-thaw (FT) signal from satellite microwave remote sensing is closely linked to vegetation phenology, productivity and land-atmosphere trace gas exchange where seasonal frozen temperatures are a major constraint to plant growth. We applied a temporal change classification of 37 GHz, vertically polarized brightness temperature (Tb) measurements from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) to classify daily FT status over global land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 year) FT record was created ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The resulting FT record showed mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to air temperature measurements from global weather stations. The FT results were also compared against other measures of biosphere activity including satellite derived vegetation greenness (NDVI) and terrestrial net primary productivity (NPP), tower CO2 flux measurements and seasonal patterns of atmospheric CO2 concentrations from northern (>50°N) monitoring sites. A strong (P45°N) latitudes and upper elevations. The FT record also shows a positive (0.199 days yr-1) trend in the number of transitional (AM frozen and PM non-frozen) frost days, resulting in reduced photosynthetic activity inferred from tower and NDVI measurements. The relative benefits of earlier and longer non-frozen seasons for vegetation growth and productivity under global warming may be declining due to opposing increases in disturbance, drought and frost damage related impacts. Portions of this work were conducted at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space

  20. Observation results of relativistic electrons detected by Fengyun-1 satellite and analysis of relativistic electron enhancement (REE) events

    Institute of Scientific and Technical Information of China (English)

    YANG XiaoChao; WANG Shidin

    2008-01-01

    The space particle component detector on Fengyun-1 satellite which works at the sun-synchronous orbit of about 870 km altitude has detected relativistic electrons for a long time.In comparison with the SAMPEX satellite observations during 1999--2004,the relativistic electron data from Fengyun-1 satellite from June 1999 to 2005 are used to analyze the relativistic electron enhancement (REE) events at the low earth orbit,and the possible correlation among REE events at the low earth orbit,high-speed solar wind and geomagnetic storms is discussed.The statistical result presents that 45 REE events are found in total during this time period,and the strong REE events with the maximum daily average flux > 400 cm-2.sr-1.s-1 occur mostly during the transition period from solar maximum to solar minimum.Among these 45 REE events,four strong REE events last a longer time period from 26- to 51-day and correlate closely with high speed solar wind and strong geo-magnetic storms.Meanwhile,several strong geomagnetic storms occur continu-ously before these REE events,and these continuous geomagnetic storms would be an important factor causing these long-lasting strong REE events.The correlation analysis for overall 45 events indicates that the strength of the REE events corre-lates with the solar wind speed and the strength of the geomagnetic storm,and the correlation for strong REE events is much stronger than that for weak REE events.

  1. Identifying drought-induced correlations in the satellite time series of hot pixels recorded in the Brazilian Amazon by means of the detrended fluctuation analysis

    Science.gov (United States)

    Stosic, Tatijana; Telesca, Luciano; Lemos da Costa, Simara Lúcia; Stosic, Borko

    2016-02-01

    In this work we study the long-term correlations in the satellite daily number of hot pixels recorded in the Brazilian Amazon during the period 1999-2012. While the highest peak in daily hot pixel frequencies occurred in 2007, coincident with a severe drought, for other intense droughts such as that occurred in 2005 (one-in-a-hundred year event for its high severity) and 2010, the corresponding number of hot pixels recorded was compatible or lower than that reached during e.g. 2004, with no reported severe drought. On the other hand, we find that the most severe droughts coincide with the peaks of the Detrended Fluctuation Analysis (DFA) scaling exponent of the time series of the daily anomalies in hot pixels. This finding is striking because it highlights the effectiveness of the DFA in disclosing that long-term hot pixel anomaly correlations are clearly associated with the drought events, that were not identifiable by examining hot pixel frequencies of the original time series. The dynamics of the time series of daily anomalies in hot pixels is, therefore, influenced by drought events. The coincidence of the peaks of the scaling exponent with drought events suggests the increase of the persistence of the hot pixel time series during the driest periods.

  2. A multimodal micro-optrode combining field and single unit recording, multispectral detection and photolabeling capabilities.

    Science.gov (United States)

    Dufour, Suzie; Lavertu, Guillaume; Dufour-Beauséjour, Sophie; Juneau-Fecteau, Alexandre; Calakos, Nicole; Deschênes, Martin; Vallée, Réal; De Koninck, Yves

    2013-01-01

    Microelectrodes have been very instrumental and minimally invasive for in vivo functional studies from deep brain structures. However they are limited in the amount of information they provide. Here, we describe a, aluminum-coated, fibre optic-based glass microprobe with multiple electrical and optical detection capabilities while retaining tip dimensions that enable single cell measurements (diameter ≤10 µm). The probe enables optical separation from individual cells in transgenic mice expressing multiple fluorescent proteins in distinct populations of neurons within the same deep brain nucleus. It also enables color conversion of photoswitchable fluorescent proteins, which can be used for post-hoc identification of the recorded cells. While metal coating did not significantly improve the optical separation capabilities of the microprobe, the combination of metal on the outside of the probe and of a hollow core within the fiber yields a microelectrode enabling simultaneous single unit and population field potential recordings. The extended range of functionalities provided by the same microprobe thus opens several avenues for multidimensional structural and functional interrogation of single cells and their surrounding deep within the intact nervous system.

  3. A multimodal micro-optrode combining field and single unit recording, multispectral detection and photolabeling capabilities.

    Directory of Open Access Journals (Sweden)

    Suzie Dufour

    Full Text Available Microelectrodes have been very instrumental and minimally invasive for in vivo functional studies from deep brain structures. However they are limited in the amount of information they provide. Here, we describe a, aluminum-coated, fibre optic-based glass microprobe with multiple electrical and optical detection capabilities while retaining tip dimensions that enable single cell measurements (diameter ≤10 µm. The probe enables optical separation from individual cells in transgenic mice expressing multiple fluorescent proteins in distinct populations of neurons within the same deep brain nucleus. It also enables color conversion of photoswitchable fluorescent proteins, which can be used for post-hoc identification of the recorded cells. While metal coating did not significantly improve the optical separation capabilities of the microprobe, the combination of metal on the outside of the probe and of a hollow core within the fiber yields a microelectrode enabling simultaneous single unit and population field potential recordings. The extended range of functionalities provided by the same microprobe thus opens several avenues for multidimensional structural and functional interrogation of single cells and their surrounding deep within the intact nervous system.

  4. 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.

  5. A Spatio-Temporal Model for Forest Fire Detection Using HJ-IRS Satellite Data

    Directory of Open Access Journals (Sweden)

    Lei Lin

    2016-05-01

    Full Text Available Fire detection based on multi-temporal remote sensing data is an active research field. However, multi-temporal detection processes are usually complicated because of the spatial and temporal variability of remote sensing imagery. This paper presents a spatio-temporal model (STM based forest fire detection method that uses multiple images of the inspected scene. In STM, the strong correlation between an inspected pixel and its neighboring pixels is considered, which can mitigate adverse impacts of spatial heterogeneity on background intensity predictions. The integration of spatial contextual information and temporal information makes it a more robust model for anomaly detection. The proposed algorithm was applied to a forest fire in 2009 in the Yinanhe forest, Heilongjiang province, China, using two-month HJ-1B infrared camera sensor (IRS images. A comparison of detection results demonstrate that the proposed algorithm described in this paper are useful to represent the spatio-temporal information contained in multi-temporal remotely sensed data, and the STM detection method can be used to obtain a higher detection accuracy than the optimized contextual algorithm.

  6. On the Use of a Feedback Tracking Architecture for Satellite Navigation Spoofing Detection

    Science.gov (United States)

    Garbin Manfredini, Esteban; Dovis, Fabio

    2016-01-01

    In this paper, the Extended Coupled Amplitude Delay Lock Loop (ECADLL) architecture, previously introduced as a solution able to deal with a multipath environment, is revisited and improved to tailor it to spoofing detection purposes. Exploiting a properly-defined decision algorithm, the architecture is able to effectively detect a spoofer attack, as well as distinguish it from other kinds of interference events. The new algorithm is used to classify them according to their characteristics. We also introduce the use of a ratio metric detector in order to reduce the detection latency and the computational load of the architecture. PMID:27918415

  7. Rule-based semi-automated approach for the detection of landslides induced by 18 September 2011 Sikkim, Himalaya, earthquake using IRS LISS3 satellite images

    Directory of Open Access Journals (Sweden)

    Sajad Siyahghalati

    2016-01-01

    Full Text Available Landslide is considered as one of the most devastating and most costly natural hazards in highlands, which is triggered mainly by rainfalls or earthquakes. In comparison with other methods, landslide mapping and monitoring via remote sensing data products are considered as the least expensive method of data collection. The current research attempts to detect landslides which occurred due to a 6.9 magnitude earthquake in Sikkim Himalaya, India, on 18 September 2011 and also to establish the spatial relationship between landslides and the slope of the terrain. To detect the landslides, decision tree method was applied on two Indian remote sensing satellites linear imaging self-scanning sensor (LISS III images acquired from 2007 and 2011 which were taken before and after the earthquake. As the study area was relatively huge for identifying the landslides, the region was separated into two parts: “tested study area” and “real study area”. The overall accuracy of landslide detection was 76%, and 75% for tested and real study area, respectively. Then, the spatial relationship between the landslides and the slope of the terrain was conducted using the digital elevation model. The results revealed that most of the landslides occurred between the slope of 25° and 45° covering 2.3 km2 and no landslide recorded in the slope of 65°–90° in the real study area. The results obtained in this study may be useful for decision-making and policy support towards reconstruction effort after the landslide occurrence. In addition, the information can be useful for reducing the risk of potential damages to substructures and properties by developing new and efficient strategies.

  8. 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...

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

    Science.gov (United States)

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

    2013-05-01

    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.

  10. Detection of segments with fetal QRS complex from abdominal maternal ECG recordings using support vector machine

    Science.gov (United States)

    Delgado, Juan A.; Altuve, Miguel; Nabhan Homsi, Masun

    2015-12-01

    This paper introduces a robust method based on the Support Vector Machine (SVM) algorithm to detect the presence of Fetal QRS (fQRS) complexes in electrocardiogram (ECG) recordings provided by the PhysioNet/CinC challenge 2013. ECG signals are first segmented into contiguous frames of 250 ms duration and then labeled in six classes. Fetal segments are tagged according to the position of fQRS complex within each one. Next, segment features extraction and dimensionality reduction are obtained by applying principal component analysis on Haar-wavelet transform. After that, two sub-datasets are generated to separate representative segments from atypical ones. Imbalanced class problem is dealt by applying sampling without replacement on each sub-dataset. Finally, two SVMs are trained and cross-validated using the two balanced sub-datasets separately. Experimental results show that the proposed approach achieves high performance rates in fetal heartbeats detection that reach up to 90.95% of accuracy, 92.16% of sensitivity, 88.51% of specificity, 94.13% of positive predictive value and 84.96% of negative predictive value. A comparative study is also carried out to show the performance of other two machine learning algorithms for fQRS complex estimation, which are K-nearest neighborhood and Bayesian network.

  11. Spectrally Enhanced Cloud Objects—A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 1. Multispectral analysis

    Science.gov (United States)

    Pavolonis, Michael J.; Sieglaff, Justin; Cintineo, John

    2015-08-01

    While satellites are a proven resource for detecting and tracking volcanic ash and dust clouds, existing algorithms for automatically detecting volcanic ash and dust either exhibit poor overall skill or can only be applied to a limited number of sensors and/or geographic regions. As such, existing techniques are not optimized for use in real-time applications like volcanic eruption alerting and data assimilation. In an effort to significantly improve upon existing capabilities, the Spectrally Enhanced Cloud Objects (SECO) algorithm was developed. The SECO algorithm utilizes a combination of radiative transfer theory, a statistical model, and image processing techniques to identify volcanic ash and dust clouds in satellite imagery with a very low false alarm rate. This fully automated technique is globally applicable (day and night) and can be adapted to a wide range of low earth orbit and geostationary satellite sensors or even combinations of satellite sensors. The SECO algorithm consists of four primary components: conversion of satellite measurements into robust spectral metrics, application of a Bayesian method to estimate the probability that a given satellite pixel contains volcanic ash and/or dust, construction of cloud objects, and the selection of cloud objects deemed to have the physical attributes consistent with volcanic ash and/or dust clouds. The first two components of the SECO algorithm are described in this paper, while the final two components are described in a companion paper.

  12. Satellite-based multi-spectral detection of the Widespread and Persistent Winter Fog over the Indo-Gangetic Plains

    Science.gov (United States)

    Gautam, R.; Rizvi, S.

    2015-12-01

    The Indo-Gangetic Plains (IGP), in the northern parts of south Asia, are subjected to dense haze/fog during winter months, on an annual basis. The thick fog prevalent during December/January months is both persistent and widespread in nature, often covering the entire IGP which stretches over 1500km in length. This study used multi-spectral imagery from MODIS data, to develop algorithms for daytime as well as nighttime detection of fog during winter 2000 to 2014 over the IGP. Specifically, our nighttime detection algorithm employs a bispectral thresholding technique, involving brightness temperature difference (BTD) between two spectral channels- 3.9 and 11.02μm. The theoretical basis for the detection using the 3.9 μm and 11.02 μm channels rely on the particular emissive properties of the two channels for fog droplets (Bendix and Bachmann, 1991). The small droplets found in fog are less emissive at 3.9 μm than at 11.02 μm. Brightness temperatures computed from corresponding radiance data (MODIS Level-1B) of band 22 (3.9 μm) and band 31 (11.02 μm), in conjunction with theoretical calculations from a radiative transfer (RT) model, were utilized to evaluate threshold value of BTD. Using theoretical RT calculations and automated analysis of hundreds of moderately high resolution satellite imagery (pixel resolution of 1km), our threshold cutoff for foggy pixels results in BTD value of 4 (deg) K. Additionally, to minimize contamination, we apply a spatial variability filter to discriminate the uniform texture of fog from other low-level clouds. A similar methodology based on BTD is also tested for daytime fog detection and separation from other cloud types. Furthermore, on the basis of operational multispectral retrievals of cloud properties (cloud effective radius, cloud top pressure, and cloud fraction) from MODIS, we have also processed spatial occurrences of fog climatology from 2000 to 2014. To validate our satellite retrieval algorithm of fog detection from

  13. Estimating babassu palm density using automatic palm tree detection with very high spatial resolution satellite images.

    Science.gov (United States)

    Dos Santos, Alessio Moreira; Mitja, Danielle; Delaître, Eric; Demagistri, Laurent; de Souza Miranda, Izildinha; Libourel, Thérèse; Petit, Michel

    2017-05-15

    High spatial resolution images as well as image processing and object detection algorithms are recent technologies that aid the study of biodiversity and commercial plantations of forest species. This paper seeks to contribute knowledge regarding the use of these technologies by studying randomly dispersed native palm tree. Here, we analyze the automatic detection of large circular crown (LCC) palm tree using a high spatial resolution panchromatic GeoEye image (0.50 m) taken on the area of a community of small agricultural farms in the Brazilian Amazon. We also propose auxiliary methods to estimate the density of the LCC palm tree Attalea speciosa (babassu) based on the detection results. We used the "Compt-palm" algorithm based on the detection of palm tree shadows in open areas via mathematical morphology techniques and the spatial information was validated using field methods (i.e. structural census and georeferencing). The algorithm recognized individuals in life stages 5 and 6, and the extraction percentage, branching factor and quality percentage factors were used to evaluate its performance. A principal components analysis showed that the structure of the studied species differs from other species. Approximately 96% of the babassu individuals in stage 6 were detected. These individuals had significantly smaller stipes than the undetected ones. In turn, 60% of the stage 5 babassu individuals were detected, showing significantly a different total height and a different number of leaves from the undetected ones. Our calculations regarding resource availability indicate that 6870 ha contained 25,015 adult babassu palm tree, with an annual potential productivity of 27.4 t of almond oil. The detection of LCC palm tree and the implementation of auxiliary field methods to estimate babassu density is an important first step to monitor this industry resource that is extremely important to the Brazilian economy and thousands of families over a large scale.

  14. CubeSats as pathfinders for planetary detection: the FIRST-S satellite

    Science.gov (United States)

    Lacour, S.; Lapeyrère, V.; Gauchet, L.; Arroud, S.; Gourgues, R.; Martin, G.; Heidmann, S.; Haubois, X.; Perrin, G.

    2014-08-01

    The idea behind FIRST (Fibered Imager foR a Single Telescope) is to use single-mode fibers to combine multiple apertures in a pupil plane as such as to synthesize a bigger aperture. The advantages with respect to a pure imager are i) relaxed tolerance on the pointing and cophasing, ii) higher accuracy in phase measurement, and iii) availability of compact, precise, and active single-mode optics like Lithium Niobate. The latter point being a huge asset in the context of a space mission. One of the problems of DARWIN or SIM-like projects was the difficulty to find low cost pathfinders missions. But the fact that Lithium Niobate optic is small and compact makes it easy to test through small nanosats missions. Moreover, they are commonly used in the telecom industry, and have already been tested on communication satellites. The idea of the FIRST-S demonstrator is to spatialize a 3U CubeSat with a Lithium Niobate nulling interferometer. The technical challenges of the project are: star tracking, beam combination, and nulling capabilities. The optical baseline of the interferometer would be 30 cm, giving a 2.2AU spatial resolution at distance of 10 pc. The scientific objective of this mission would be to study the visible emission of exozodiacal light in the habitable zone around the closest stars.

  15. CubeSats as pathfinders for planetary detection: the FIRST-S satellite

    CERN Document Server

    Lacour, S; Gauchet, L; Arroud, S; Gourgues, R; Martin, G; Heidmann, S; Haubois, X; Perrin, G

    2014-01-01

    The idea behind FIRST (Fibered Imager foR a Single Telescope) is to use single-mode fibers to combine multiple apertures in a pupil plane as such as to synthesize a bigger aperture. The advantages with respect to a pure imager are i) relaxed tolerance on the pointing and cophasing, ii) higher accuracy in phase measurement, and iii) availability of compact, precise, and active single-mode optics like Lithium Niobate. The latter point being a huge asset in the context of a space mission. One of the problems of DARWIN or SIM-like projects was the difficulty to find low cost pathfinders missions. But the fact that Lithium Niobate optic is small and compact makes it easy to test through small nanosats missions. Moreover, they are commonly used in the telecom industry, and have already been tested on communication satellites. The idea of the FIRST-S demonstrator is to spatialize a 3U CubeSat with a Lithium Niobate nulling interferometer. The technical challenges of the project are: star tracking, beam combination, ...

  16. Satellite detection of rising maize yield heterogeneity in the U.S. Midwest

    Science.gov (United States)

    Lobell, David B.; Azzari, George

    2017-01-01

    The future trajectory of crop yields in the United States will influence food supply and land use worldwide. We examine maize and soybean yields for 2000-2015 in the Midwestern U.S. using a new satellite-based dataset on crop yields at 30m resolution. We quantify heterogeneity both within and between fields, and find that the difference between average and top yielding fields is typically below 30% for both maize and soybean, as expected in advanced agricultural regions. In most counties, within-field heterogeneity is at least half as large as overall heterogeneity, illustrating the importance of non-management factors such as soil and landscape position. Surprisingly, we find that yield heterogeneity is rising in maize, both between and within fields, with average yield differences between the best and worst soils more than doubling since 2000. Heterogeneity trends were insignificant for soybean. The findings are consistent both with recent adoption of precision agriculture technologies and with recent trends toward denser sowing in maize, which disproportionately raise yields on better soils. The results imply that yield gains in the region are increasingly derived from the more productive land, and that sub-field precision management of nutrients and other inputs is increasingly warranted.

  17. On the Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Sengupta, S K; Poland, D; Futterman, J A H

    2003-01-10

    The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this next stage. These features can be more representative of human settlements, and also more time consuming to extract from the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band and panchromatic images, and compare it with the straight-forward processing of the entire image.

  18. Scattered Light from Close-in Extrasolar Planets: Prospects of Detection with the MOST Satellite

    CERN Document Server

    Green, D; Seager, S; Kuschnig, R; Green, Daniel; Matthews, Jaymie; Seager, Sara; Kuschnig, Rainer

    2003-01-01

    The ultra-precise photometric space satellite MOST (Microvariability and Oscillations of STars) will provide the first opportunity to measure the albedos and scattered light curves from known short-period extrasolar planets. Due to the changing phases of an extrasolar planet as it orbits its parent star, the combined light of the planet-star system will vary on the order of tens of micromagnitudes. The amplitude and shape of the resulting light curve is sensitive to the planet's radius and orbital inclination, as well as the composition and size distribution of the scattering particles in the planet's atmosphere. To predict the capabilities of MOST and other planned space missions, we have constructed a series of models of such light curves, improving upon earlier work by incorporating more realistic details such as: limb darkening of the star, intrinsic granulation noise in the star itself, tidal distortion and back-heating, higher angular resolution of the light scattering from the planet, and exploration o...

  19. Detecting snowfall over land by satellite high-frequency microwave observations: The lack of scattering signature and a statistical approach

    Science.gov (United States)

    Liu, Guosheng; Seo, Eun-Kyoung

    2013-02-01

    has been long believed that the dominant microwave signature of snowfall over land is the brightness temperature decrease caused by ice scattering. However, our analysis of multiyear satellite data revealed that on most of occasions, brightness temperatures are rather higher under snowfall than nonsnowfall conditions, likely due to the emission by cloud liquid water. This brightness temperature increase masks the scattering signature and complicates the snowfall detection problem. In this study, we propose a statistical method for snowfall detection, which is developed by using CloudSat radar to train high-frequency passive microwave observations. To capture the major variations of the brightness temperatures and reduce the dimensionality of independent variables, the detection algorithm is designed to use the information contained in the first three principal components resulted from Empirical Orthogonal Function (EOF) analysis, which capture ~99% of the total variances of brightness temperatures. Given a multichannel microwave observation, the algorithm first transforms the brightness temperature vector into EOF space and then retrieves a probability of snowfall by using the CloudSat radar-trained look-up table. Validation has been carried out by case studies and averaged horizontal snowfall fraction maps. The result indicated that the algorithm has clear skills in identifying snowfall areas even over mountainous regions.

  20. 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.

  1. Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests

    Science.gov (United States)

    Yu, Yongtao; Guan, Haiyan; Zai, Dawei; Ji, Zheng

    2016-02-01

    This paper proposes a rotation-and-scale-invariant method for detecting airplanes from high-resolution satellite images. To improve feature representation capability, a multi-layer feature generation model is created to produce high-order feature representations for local image patches through deep learning techniques. To effectively estimate airplane centroids, a Hough forest model is trained to learn mappings from high-order patch features to the probabilities of an airplane being present at specific locations. To handle airplanes with varying orientations, patch orientation is defined and integrated into the Hough forest to augment Hough voting. The scale invariance is achieved by using a set of scale factors embedded in the Hough forest. Quantitative evaluations on the images collected from Google Earth service show that the proposed method achieves a completeness, correctness, quality, and F1-measure of 0.968, 0.972, 0.942, and 0.970, respectively, in detecting airplanes with arbitrary orientations and sizes. Comparative studies also demonstrate that the proposed method outperforms the other three existing methods in accurately and completely detecting airplanes in high-resolution remotely sensed images.

  2. Multiple-Symbol combined differential detection for satellite-based AIS Signals

    Science.gov (United States)

    Hao, Jingsong; Ma, Shexiang; Wang, Junfeng; Meng, Xin

    2015-12-01

    In this paper, a multiple-symbol combined differential Viterbi decoding algorithm which is insensitive to frequency offset is proposed. According to the theories of multiple-symbol differential detection and maximum-likelihood detection, we combine the multiple-order differential information with the Viterbi algorithm. The phase shift caused by the frequency offset is estimated and compensated from the above information in the process of decoding. The simulation results show that the bit error rate (BER) of 2 bits combined differential Viterbi algorithm is below 10-3 when the normalized signal-to-noise ratio (NSNR) is 11 dB, and the decoding performances approach those of the coherent detection as the length of the combined differential symbols increases. The proposed method is simple and its performance remains stable under different frequency offsets.

  3. Detection of satellite remnants in the Galactic Halo with Gaia III. Detection limits for Ultra Faint Dwarf Galaxies

    CERN Document Server

    Antoja, Teresa; Aguilar, Luis; Figueras, Francesca; Antiche, Erika; Hernandez-Perez, Fabiola; Brown, Anthony; Valenzuela, Octavio; Aparicio, Antonio; Hidalgo, Sebastian; Velazquez, Hector

    2015-01-01

    We present a method to identify Ultra Faint Dwarf Galaxy (UFDG) candidates in the halo of the Milky Way using the future Gaia catalogue and we explore its detection limits and completeness. The method is based on the Wavelet Transform and searches for over-densities in the combined space of sky coordinates and proper motions, using kinematics in the search for the first time. We test the method with a Gaia mock catalogue that has the Gaia Universe Model Snapshot (GUMS) as a background, and use a library of around 30 000 UFDGs simulated as Plummer spheres with a single stellar population. For the UFDGs we use a wide range of structural and orbital parameters that go beyond the range spanned by real systems, where some UFDGs may remain undetected. We characterize the detection limits as function of the number of observable stars by Gaia in the UFDGs with respect to that of the background and their apparent sizes in the sky and proper motion planes. We find that the addition of proper motions in the search impro...

  4. 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...

  5. 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...

  6. Comments on "Failures in detecting volcanic ash from a satellite-based technique"

    Science.gov (United States)

    Prata, F.; Bluth, G.; Rose, B.; Schneider, D.; Tupper, A.

    2001-01-01

    The recent paper by Simpson et al. [Remote Sens. Environ. 72 (2000) 191.] on failures to detect volcanic ash using the 'reverse' absorption technique provides a timely reminder of the danger that volcanic ash presents to aviation and the urgent need for some form of effective remote detection. The paper unfortunately suffers from a fundamental flaw in its methodology and numerous errors of fact and interpretation. For the moment, the 'reverse' absorption technique provides the best means for discriminating volcanic ash clouds from meteorological clouds. The purpose of our comment is not to defend any particular algorithm; rather, we point out some problems with Simpson et al.'s analysis and re-state the conditions under which the 'reverse' absorption algorithm is likely to succeed. ?? 2001 Elsevier Science Inc. All rights reserved.

  7. 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.

  8. Detection of Neolithic Settlements in Thessaly (Greece Through Multispectral and Hyperspectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Dimitrios Alexakis

    2009-02-01

    Full Text Available Thessaly is a low relief region in Greece where hundreds of Neolithic settlements/tells called magoules were established from the Early Neolithic period until the Bronze Age (6,000 – 3,000 BC. Multi-sensor remote sensing was applied to the study area in order to evaluate its potential to detect Neolithic settlements. Hundreds of sites were geo-referenced through systematic GPS surveying throughout the region. Data from four primary sensors were used, namely Landsat ETM, ASTER, EO1 - HYPERION and IKONOS. A range of image processing techniques were originally applied to the hyperspectral imagery in order to detect the settlements and validate the results of GPS surveying. Although specific difficulties were encountered in the automatic classification of archaeological features composed by a similar parent material with the surrounding landscape, the results of the research suggested a different response of each sensor to the detection of the Neolithic settlements, according to their spectral and spatial resolution.

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

    Directory of Open Access Journals (Sweden)

    Marghany Maged

    2016-10-01

    Full Text Available 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 receiver-operating 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.

  10. Audio Recording Device Data for Assessing Avian Detectability, Seward Peninsula, Alaska, 2013-2014

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data set contains information from recording devices that were set to record regularly during summer breeding seasons. A single observer listened to 2692...

  11. 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.

  12. 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

  13. Evidence for a slow subsidence of the Tahiti Island from GPS, DORIS, GRACE, and combined satellite altimetry and tide gauge sea level records

    Science.gov (United States)

    Fadil, A.; Barriot, J.; Sichoix, L.; Ortega, P.; Willis, P.; Serafini, J.

    2010-12-01

    Monitoring vertical land motion is of crucial interest in observations of long-term sea level change and its reconstruction, but is among of the most, yet highly challenging, tasks of space geodesy. The aim of the paper is to compare the vertical velocity estimates of Tahiti Island obtained from six independent geophysical measurements, namely a decade of GPS, DORIS, and GRACE data, 17 years sea level difference (altimeter minus tide gauge (TG)) time series, ICE-5G (VM2 L90) Post-Glacial Rebound (PGR) model predictions, and coral reef stratigraphy. Except The Glacial Isostatic Adjustment (GIA also known as PGR) model, all the techniques are in a good agreement and reveal a very slow subsidence of the Tahiti Island averaged at -0.3 mm/yr which is barely significant. Neverthless, despite of that vertical motion, Tahiti remains an ideal location for the calibration of satellite altimeter measurements.Estimated vertical crustal motions from GPS, DORIS, GRACE, (altimetry - tide-gauge) sea level records, coral reef stratigraphy, and GIA. GG = GAMIT-GLOBK software packageGOA= GIPSY-OASIS II software package

  14. A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies

    Science.gov (United States)

    Banzon, Viva; Smith, Thomas M.; Chin, Toshio Mike; Liu, Chunying; Hankins, William

    2016-04-01

    This paper describes a blended sea-surface temperature (SST) data set that is part of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) program product suite. Using optimum interpolation (OI), in situ and satellite observations are combined on a daily and 0.25° spatial grid to form an SST analysis, i.e., a spatially complete field. A large-scale bias adjustment of the input infrared SSTs is made using buoy and ship observations as a reference. This is particularly important for the time periods when volcanic aerosols from the El Chichón and Mt. Pinatubo eruptions are widespread globally. The main source of SSTs is the Advanced Very High Resolution Radiometer (AVHRR), available from late 1981 to the present, which is also the temporal span of this CDR. The input and processing choices made to ensure a consistent data set that meets the CDR requirements are summarized. A brief history and an explanation of the forward production schedule for the preliminary and science-quality final product are also provided. The data set is produced and archived at the newly formed National Centers for Environmental Information (NCEI) in Network Common Data Form (netCDF) at doi:10.7289/V5SQ8XB5.

  15. Remote heartbeat signal detection from visible spectrum recordings based on blind deconvolution

    Science.gov (United States)

    Kaur, Balvinder; Moses, Sophia; Luthra, Megha; Ikonomidou, Vasiliki N.

    2016-05-01

    While recent advances have shown that it is possible to acquire a signal equivalent to the heartbeat from visual spectrum video recordings of the human skin, extracting the heartbeat's exact timing information from it, for the purpose of heart rate variability analysis, remains a challenge. In this paper, we explore two novel methods to estimate the remote cardiac signal peak positions, aiming at a close representation of the R-peaks of the ECG signal. The first method is based on curve fitting (CF) using a modified filtered least mean square (LMS) optimization and the second method is based on system estimation using blind deconvolution (BDC). To prove the efficacy of the developed algorithms, we compared results obtained with the ground truth (ECG) signal. Both methods achieved a low relative error between the peaks of the two signals. This work, performed under an IRB approved protocol, provides initial proof that blind deconvolution techniques can be used to estimate timing information of the cardiac signal closely correlated to the one obtained by traditional ECG. The results show promise for further development of a remote sensing of cardiac signals for the purpose of remote vital sign and stress detection for medical, security, military and civilian applications.

  16. 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.

  17. Summit-to-sea mapping and change detection using satellite imagery: tools for conservation and management of coral reefs.

    Science.gov (United States)

    Shapiro, A C; Rohmann, S O

    2005-05-01

    Continuous summit-to-sea maps showing both land features and shallow-water coral reefs have been completed in Puerto Rico and the U.S. Virgin Islands, using circa 2000 Landsat 7 Enhanced Thematic Mapper (ETM+) Imagery. Continuous land/sea terrain was mapped by merging Digital Elevation Models (DEM) with satellite-derived bathymetry. Benthic habitat characterizations were created by unsupervised classifications of Landsat imagery clustered using field data, and produced maps with an estimated overall accuracy of>75% (Tau coefficient >0.65). These were merged with Geocover-LC (land use/land cover) data to create continuous land/ sea cover maps. Image pairs from different dates were analyzed using Principle Components Analysis (PCA) in order to detect areas of change in the marine environment over two different time intervals: 2000 to 2001, and 1991 to 2003. This activity demonstrates the capabilities of Landsat imagery to produce continuous summit-to-sea maps, as well as detect certain changes in the shallow-water marine environment, providing a valuable tool for efficient coastal zone monitoring and effective management and conservation.

  18. 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.

  19. A Search for Prompt Very High Energy Emission from Satellite-detected Gamma-ray Bursts using Milagro

    CERN Document Server

    Parkinson, P M Saz

    2007-01-01

    Gamma-ray bursts (GRBs) have been detected up to GeV energies and are predicted by many models to emit in the very high energy (VHE, > 100 GeV) regime too. Detection of such emission would allow us to constrain GRB models. Since its launch, in late 2004, the Swift satellite has been locating GRBs at a rate of approximately 100 per year. The rapid localization and follow-up in many wavelengths has revealed new and unexpected phenomena, such as delayed emission in the form of bright X-ray flares. The Milagro gamma-ray observatory is a wide field of view (2 sr) instrument employing a water Cherenkov detector to continuously ($>$ 90% duty cycle) observe the overhead sky in the 100 GeV to 100 TeV energy range. Over 100 GRBs are known to have been in the field of view of Milagro since January 2000, including 57 since the launch of Swift (through May 2007). We discuss the results of the searches for prompt emission from these bursts, as well as for delayed emission from the X-ray flares observed in some of the Swift...

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

    Science.gov (United States)

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

    2008-09-01

    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 and land-cover map (University of Maryland) from Advanced Very High Resolution Radiometer (AVHRR) and 2001 products from Moderate Resolution Imaging Spectroradiometer (MODIS) at 1-km resolution for the region; and 30-m resolution land-cover maps from the National Land Cover Data (NLCD) for a subarea to conduct nine simulations to address our questions. Sensitivity analysis showed that (1) AVHRR data tended to underestimate AGB density by 11%, on average, compared to that estimated using MODIS data; (2) regional mean AGB density increased slightly from 124 (1992) to 126 Mg ha(-1) (2001) by 1.6%; (3) a substantial decrease in total forest AGB across the region was detected, from 2,507 (1992) to 1,961 Tg (2001), an annual rate of -2.4%; and (4) in the subarea, while NLCD-based estimates suggested a 26% decrease in total AGB from 1992 to 2001, AVHRR/MODIS-based estimates indicated a 36% increase. The major source of uncertainty in change detection of total forest AGB over large areas was due to area differences from using land-cover maps produced by different sources. Scaling up 30-m land-cover map to 1-km resolution caused a mean difference of 8% (in absolute value) in forest area estimates at the county-level ranging from 0 to 17% within a 95% confidence interval.

  1. Analysis of Fade Detection and Compensation Experimental Results in a Ka-Band Satellite System. Degree awarded by Akron Univ., May 2000

    Science.gov (United States)

    Johnson, Sandra

    2001-01-01

    The frequency bands being used for new satellite communication systems are constantly increasing to accommodate the requirements for additional capacity. At these higher frequencies, propagation impairments that did not significantly affect the signal at lower frequencies begin to have considerable impact. In Ka-band, the next logical commercial frequency band to be used for satellite communication, attenuation of the signal due to rain is a primary concern. An experimental satellite built by NASA, the Advanced Communication Technology Satellite (ACTS), launched in September 1993, is the first US communication satellite operating in the Ka-band. In addition to higher carrier frequencies, a number of other new technologies, including onboard baseband processing, multiple beam antennas, and rain fade detection and compensation techniques, were designed into the ACTS. Verification experiments have been conducted since the launch to characterize the new technologies. The focus of this thesis is to describe and validate the method used by the ACTS Very Small Aperture Terminal (VSAT) ground stations in detecting the presence of fade in the communication signal and to adaptively compensate for it by the addition of burst rate reduction and forward error correction. Measured data obtained from the ACTS program is used to validate the compensation technique. In this thesis, models in MATLAB are developed to statistically characterize the increased availability achieved by the compensation techniques in terms of the bit error rate time enhancement factor. Several improvements to the ACTS technique are discussed and possible implementations for future Ka-band systems are also presented.

  2. Vegetation Cover Change in the Upper Kings River Basin of the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.

  3. Northwestern Black Sea coastal zone environmental changes detection by satellite remote sensing data

    Science.gov (United States)

    Zoran, Maria A.

    2004-02-01

    The Romanian North Western coastal and shelf zones of the Black Sea and Danube delta are a mosaic of complex, interacting ecosystems, rich natural resources and socio-economic activity. Dramatic changes in the Black Sea's ecosystem and resources are due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). A scientific management system for protection, conservation and restoration must be based on reliable information on bio-geophysical and geomorphologic processes, coastal erosion, sedimentation dynamics, mapping of macrophyte fields, water quality, climatic change effects. A multitemporal data set consisting of LANDSAT MSS, TM and SAR ERS-1 images was used for comparing and mapping landcover change via change detection. Synergetic use of quasi-simultaneously acquired multi-sensor data may therefore allow for a better approach of change detection of coastal area. The main aim of this paper is to conduct a comprehensive analysis based on existing historical and more recent in situ and remote sensing data to establish the link between phytoplankton bloom development, increasing erosion and diminishing of beaches and related coastal zone harmful phenomena.

  4. Satellite Detection of Phaeocystis Globosa Blooms in the Eastern English Channel

    Science.gov (United States)

    Lubac, B.; Loisel, H.; Poteau, A.; Guiselin, N.

    2006-12-01

    Detecting phytoplankton species from remote sensing is essential to map and monitor algal blooms in coastal waters, but stays a challenge because of the interference of suspended sediments and dissolved organic matter with the phytoplankton signal. In the eastern English Channel and the south North Sea, a more or less intensive bloom of prymnesiophyceae Phaeocystis globosa occurs almost every spring and follows generally a first bloom of diatoms. From hyperspectral radiometric measurements (TRIOS; 350-950 nm, with a 3 nm resolution) concurrently performed with absorption, and backscattering measurements, as well as with phytoplankton species diversity determination, a spectral signature based on a derivative analysis was observed to discriminate the P. globosa blooms. In this study, we develop a multispectral approach to detect P. globosa blooms and investigate the possibility to apply this method to "ocean color" sensors (SeaWIFS). Then, we examine the impact of the bloom of P. globosa on the restitution of ocean color standard products, in particularly the chlorophyll a concentration (Chl), and examine new approaches to improve the restitution of Chl in this complex coastal environment.

  5. A low-power configurable neural recording system for epileptic seizure detection.

    Science.gov (United States)

    Qian, Chengliang; Shi, Jess; Parramon, Jordi; Sánchez-Sinencio, Edgar

    2013-08-01

    This paper describes a low-power configurable neural recording system capable of capturing and digitizing both neural action-potential (AP) and fast-ripple (FR) signals. It demonstrates the functionality of epileptic seizure detection through FR recording. This system features a fixed-gain, variable-bandwidth (BW) front-end circuit and a sigma-delta ADC with scalable bandwidth and power consumption. The ADC employs a 2nd-order single-bit sigma-delta modulator (SDM) followed by a low-power decimation filter. Direct impulse-response implementation of a sinc(3) filter and 8-cycle data pipelining in an IIR filter are proposed for the decimation filter design to improve the power and area efficiency. In measurements, the front end exhibits 39.6-dB DC gain, 0.8 Hz to 5.2 kHz of BW, 5.86- μVrms input-referred noise, and 2.4- μW power consumption in AP mode, while showing 38.5-dB DC gain, 250 to 486 Hz of BW, 2.48- μVrms noise, and 4.5- μW power consumption in FR mode. The noise efficiency factor (NEF) is 2.93 and 7.6 for the AP and FR modes, respectively. At 77-dB dynamic range (DR), the ADC has a peak SNR and SNDR of 75.9 dB and 67 dB, respectively, while consuming 2.75-mW power in AP mode. It achieves 78-dB DR, 76.2-dB peak SNR, 73.2-dB peak SNDR, and 588- μW power consumption in FR mode. Both analog and digital power supply voltages are 2.8 V. The chip is fabricated in a standard 0.6- μm CMOS process. The die size is 11.25 mm(2).

  6. Abrupt climate changes of the last deglaciation detected in a Western Mediterranean forest record

    Directory of Open Access Journals (Sweden)

    W. J. Fletcher

    2010-04-01

    Full Text Available Abrupt changes in Western Mediterranean climate during the last deglaciation (20 to 6 cal ka BP are detected in marine core MD95-2043 (Alboran Sea through the investigation of high-resolution pollen data and pollen-based climate reconstructions by the modern analogue technique (MAT for annual precipitation (Pann and mean temperatures of the coldest and warmest months (MTCO and MTWA. Changes in temperate Mediterranean forest development and composition and MAT reconstructions indicate major climatic shifts with parallel temperature and precipitation changes at the onsets of Heinrich stadial 1 (equivalent to the Oldest Dryas, the Bölling-Allerød (BA, and the Younger Dryas (YD. Multi-centennial-scale oscillations in forest development occurred throughout the BA, YD, and early Holocene. Shifts in vegetation composition and (Pann reconstructions indicate that forest declines occurred during dry, and generally cool, episodes centred at 14.0, 13.3, 12.9, 11.8, 10.7, 10.1, 9.2, 8.3 and 7.4 cal ka BP. The forest record also suggests multiple, low-amplitude Preboreal (PB climate oscillations, and a marked increase in moisture availability for forest development at the end of the PB at 10.6 cal ka BP. Dry atmospheric conditions in the Western Mediterranean occurred in phase with Lateglacial events of high-latitude cooling including GI-1d (Older Dryas, GI-1b (Intra-Allerød Cold Period and GS-1 (YD, and during Holocene events associated with high-latitude cooling, meltwater pulses and N. Atlantic ice-rafting. A possible climatic mechanism for the recurrence of dry intervals and an opposed regional precipitation pattern with respect to Western-central Europe relates to the dynamics of the westerlies and the prevalence of atmospheric blocking highs. Comparison of radiocarbon and ice-core ages for well-defined climatic transitions in the forest record suggests possible enhancement of marine reservoir ages in the Alboran

  7. 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.

  8. Detecting Rock Glacier Dynamics in Southern Carpathians Mountains Using High-Resolution Optical and Multi-Temporal SAR Satellite Imagery .....

    Science.gov (United States)

    Necsoiu, M.; Onaca, A.

    2015-12-01

    This research provided the first documented assessment of the dynamics of rock glaciers in Southern Carpathian Mountains over almost half a century (1968-2014). The dynamics of four representative rock glaciers were assessed using complementary satellite-based optical and radar remote sensing techniques. We investigated the dynamics of the area using co-rectification of paired optical satellite datasets acquired by SPOT5, WV-1, Pléiades, and Corona to estimate short term (7 years) and longer term changes (44 years). Accurately rectifying and co-registering Corona KH-4B imagery allowed us to expand the time horizon over which changes in this alpine environment could be analyzed. The displacements revealed by this analysis correlate with variations in local slope of the rock glaciers, and presence or absence of permafrost. For radar analysis, nine ascending ALOS-1 PALSAR images were used based clear sky and absence of snow groundcover (i.e. June-October). Although decorrelation limits the ability to perform quantitative InSAR analyses, loss of coherence was useful in detecting subtle changes in active rock glacier environments, as well as other mass movements including rock falls, rock avalanches, debris flows, creep of permafrost, and solifluction. Small Baseline Subset (SBAS) InSAR analysis successfully quantified rates of change for unstable areas. The results of this investigation, although based on limited archived imagery, demonstrate that correlation analysis, coherence analysis, and multitemporal InSAR techniques can yield useful information for detecting creeping permafrost in a complex mountain environment, such as Retezat Mountains. Our analyses showed that rock glaciers in the Southern Carpathian Mountains are experiencing very slow annual movement of only a few cm per year. Results of the remote sensing analyses are consistent with field observations of permafrost occurrence at these sites (for more, please see Abstract ID# 68413). The combined optical

  9. 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.

  10. 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.

  11. Neural recording front-end IC using action potential detection and analog buffer with digital delay for data compression.

    Science.gov (United States)

    Liu, Lei; Yao, Lei; Zou, Xiaodan; Goh, Wang Ling; Je, Minkyu

    2013-01-01

    This paper presents a neural recording analog front-end IC intended for simultaneous neural recording with action potential (AP) detection for data compression in wireless multichannel neural implants. The proposed neural recording front-end IC detects the neural spikes and sends only the preserved AP information for wireless transmission in order to reduce the overall power consumption of the neural implant. The IC consists of a low-noise neural amplifier, an AP detection circuit and an analog buffer with digital delay. The neural amplifier makes use of a current-reuse technique to maximize the transconductance efficiency for attaining a good noise efficiency factor. The AP detection circuit uses an adaptive threshold voltage to generate an enable signal for the subsequent functional blocks. The analog buffer with digital delay is employed using a finite impulse response (FIR) filter which preserves the AP waveform before the enable signal as well as provides low-pass filtering. The neural recording front-end IC has been designed using standard CMOS 0.18-µm technology occupying a core area of 220 µm by 820 µm.

  12. Detecting Agro-Droughts in Southwest of China Using MODIS Satellite Data

    Institute of Scientific and Technical Information of China (English)

    ZHANG Feng; ZHANG Li-wen; WANG Xiu-zhen; HUNG Jing-feng

    2013-01-01

    The normalized difference vegetation index (NDVI) has proven to be typically employed to assess terrestrial vegetation conditions. However, one limitation of NDVI for drought monitoring is the apparent time lag between rainfall deficit and NDVI response. To better understand this relationship, time series NDVI (2000-2010) during the growing season in Sichuan Province and Chongqing City were analyzed. The vegetation condition index (VCI) was used to construct a new drought index, time-integrated vegetation condition index (TIVCI), and was then compared with meteorological drought indices-standardized precipitation index (SPI), a multiple-time scale meteorological-drought index based on precipitation, to examine the sensitivity on droughts. Our research findings indicate the followings:(1) farmland NDVI sensitivity to precipitation in study area has a time lag of 16-24 d, and it maximally responds to the temperature with a lag of about 16 d. (2) We applied the approach to Sichuan Province and Chongqing City for extreme drought monitoring in 2006 and 2003, and the results show that the monitoring results from TIVCI are closer to the published China agricultural statistical data than VCI. Compared to VCI, the best results from TIVCI3 were found with the relative errors of-4.5 and 6.36%in 2006 for drought affected area and drought disaster area respectively, and 5.11 and-5.95%in 2003. (3) Compared to VCI, TIVCI has better correlation with the SPI, which indicates the lag and cumulative effects of precipitation on vegetation. Our finding proved that TIVCI is an effective indicator of drought detection when the time lag effects between NDVI and climate factors are taken into consideration.

  13. 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.

  14. Satellite thermal monitoring of the 2010 - 2013 eruption of Kizimen volcano (Kamchatka) using MIROVA hot-spot detection system

    Science.gov (United States)

    Massimetti, Francesco; Coppola, Diego; Laiolo, Marco; Cigolini, Corrado

    2017-04-01

    After 81 years of rest, the Holocenic stratovolcano of Kizimen (Kamchatka, Russia) began a new eruptive phase on December 2010. The eruption was preceded by a year-long seismic unrest and fumarole activity, and persisted for 3 years showing a transition from explosive to effusive style. The initial explosive phase caused the partial disruption of the volcano summit and was followed by the effusion of andesitic lava flow along the eastern side of the edifice. Here we used an automatic hot-spot detection system named MIROVA (Middle InfraRed Observation of Volcanic Activity), in order to track the thermal evolution of the eruption and to understand the eruptive dynamic. MIROVA is based on the analysis IR images acquired by the MODIS sensor (Moderate Resolution Imaging Spectroradiometer) and is able to provide thermal maps (1 km resolution) and Volcanic Radiative Power (VRP, in Watt) time series in near real time (1-4 hours from satellite overpass). Each image with a thermal alert has been classified, distinguishing different quality level of the data based on cloud cover, viewing geometry and coherence with the VRP trend. The analysis of VRP variation show different thermal phases that have been correlated with independent observations of KVERT (Kamchatka Volcanic Eruption Response Team). Finally, we show that the relation between total thermal energy radiated (VRE, in Joule) and erupted lava volume is consistent with the typical radiant density of an intermediate-silicic lava flow (Coppola et al., 2013).

  15. Psychotropics and weak opioid analgesics in plasma samples of older hip fracture patients - detection frequencies and consistency with drug records.

    Science.gov (United States)

    Waade, Ragnhild Birkeland; Molden, Espen; Martinsen, Mette Irene; Hermann, Monica; Ranhoff, Anette Hylen

    2017-07-01

    To determine use of psychotropic drugs and weak opioids in hip fracture patients by analysing plasma samples at admission, and compare detected drug frequencies with prescription registry data and drug records. Plasma from 250 hip fracture patients aged ≥65 years sampled at hospital admission were analysed by ultra-performance liquid chromatography-tandem mass spectrometry methods for detection of psychotropic drugs and weak opioid analgesics (alcohol also determined). Odds ratios for drugs detected in plasma of hip fracture patients vs. prescription frequencies of the same drugs in an age-, time- and region-matched reference population were calculated. Moreover, recorded and measured drugs were compared. Psychotropic drugs and/or weak opioid analgesics were detected in 158 (63%) of the patients (median age 84 years; 76% females), while alcohol was found in 19 patients (7.6%). The occurrence of diazepam (odds ratio 1.6; 95% confidence interval 1.1-2.4), nitrazepam (2.3; 1.3-4.1), selective serotonin reuptake inhibitors (1.9; 1.3-2.9) and mirtazapine (2.3; 1.2-4.3) was significantly higher in plasma samples of hip fracture patients than in prescription data from the reference population. Poor consistency between recorded and measured drugs was disclosed for z-hypnotics and benzodiazepines; e.g. diazepam was detected in 29 (11.6%), but only recorded in six (2.4%) of the patients. Plasma analysis shows that use of antidepressants and benzodiazepines in hip fracture patients is significantly more frequent than respective prescription frequencies in the general elderly population. Moreover, consistency between recorded and actual use of psychotropic fall-risk drugs is poor at hospital admission of hip fracture patients. © 2017 The British Pharmacological Society.

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

    Science.gov (United States)

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

    2011-12-01

    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 "MIT 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.

  17. Statistical modeling and trend detection of extreme sea level records in the Pearl River Estuary

    Science.gov (United States)

    Wang, Weiwen; Zhou, Wen

    2017-03-01

    Sea level rise has become an important issue in global climate change studies. This study investigates trends in sea level records, particularly extreme records, in the Pearl River Estuary, using measurements from two tide gauge stations in Macau and Hong Kong. Extremes in the original sea level records (daily higher high water heights) and in tidal residuals with and without the 18.6-year nodal modulation are investigated separately. Thresholds for defining extreme sea levels are calibrated based on extreme value theory. Extreme events are then modeled by peaks-over-threshold models. The model applied to extremes in original sea level records does not include modeling of their durations, while a geometric distribution is added to model the duration of extremes in tidal residuals. Realistic modeling results are recommended in all stationary models. Parametric trends of extreme sea level records are then introduced to nonstationary models through a generalized linear model framework. The result shows that, in recent decades, since the 1960s, no significant trends can be found in any type of extreme at any station, which may be related to a reduction in the influence of tropical cyclones in the region. For the longer-term record since the 1920s at Macau, a regime shift of tidal amplitudes around the 1970s may partially explain the diverse trend of extremes in original sea level records and tidal residuals.

  18. 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.

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

    Science.gov (United States)

    Dorazio, Robert; Karanth, K. Ullas

    2017-01-01

    MotivationSeveral 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.Model and data analysisWe 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.BenefitsOur 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

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

    Science.gov (United States)

    Dorazio, Robert M; Karanth, K Ullas

    2017-01-01

    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 cases where

  1. Automatic Real-Time Embedded QRS Complex Detection for a Novel Patch-Type Electrocardiogram Recorder

    DEFF Research Database (Denmark)

    Saadi, Dorthe Bodholt; Tanev, George; Flintrup, Morten

    2015-01-01

    Cardiovascular diseases are projected to remain the single leading cause of death globally. Timely diagnosis and treatment of these diseases are crucial to prevent death and dangerous complications. One of the important tools in early diagnosis of arrhythmias is analysis of electrocardiograms (ECGs......) obtained from ambulatory long-term recordings. The design of novel patch-type ECG recorders has increased the accessibility of these long-term recordings. In many applications, it is furthermore an advantage for these devices that the recorded ECGs can be analyzed automatically in real time. The purpose....... The design and optimization of the algorithm was performed on two different databases: The MIT-BIH arrhythmia database ( $Se=99.90$ %, $P^{+}=99.87$ ) and a private ePatch training database ( $Se=99.88$ %, $P^{+}=99.37$ %). The offline validation was conducted on the European ST-T database ( $Se=99.84$ %, $P...

  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. Lake ice records used to detect historical and future climatic changes

    Science.gov (United States)

    Robertson, Dale M.; Ragotzkie, R.A.; Magnuson, John J.

    1992-01-01

    Historical ice records, such as freeze and breakup dates and the total duration of ice cover, can be used as a quantitative indicator of climatic change if long homogeneous records exist and if the records can be calibrated in terms of climatic changes. Lake Mendota, Wisconsin, has the longest uninterrupted ice records available for any lake in North America dating back to 1855. These records extend back prior to any reliable air temperature data in the midwestern region of the U.S. and demonstrate significant warming of approximately 1.5 °C in fall and early winter temperatures and 2.5 °C in winter and spring temperatures during the past 135 years. These changes are not completely monotonie, but rather appear as two shorter periods of climatic change in the longer record. The first change was between 1875 and 1890, when fall, winter, and spring air temperatures increased by approximately 1.5 °C. The second change, earlier ice breakup dates since 1979, was caused by a significant increase in winter and early spring air temperatures of approximately 1.3 °C. This change may be indicative of shifts in regional climatic patterns associated with global warming, possibly associated with the ‘Greenhouse Effect’.

  4. Eyelid contour detection and tracking for startle research related eye-blink measurements from high-speed video records.

    Science.gov (United States)

    Bernard, Florian; Deuter, Christian Eric; Gemmar, Peter; Schachinger, Hartmut

    2013-10-01

    Using the positions of the eyelids is an effective and contact-free way for the measurement of startle induced eye-blinks, which plays an important role in human psychophysiological research. To the best of our knowledge, no methods for an efficient detection and tracking of the exact eyelid contours in image sequences captured at high-speed exist that are conveniently usable by psychophysiological researchers. In this publication a semi-automatic model-based eyelid contour detection and tracking algorithm for the analysis of high-speed video recordings from an eye tracker is presented. As a large number of images have been acquired prior to method development it was important that our technique is able to deal with images that are recorded without any special parametrisation of the eye tracker. The method entails pupil detection, specular reflection removal and makes use of dynamic model adaption. In a proof-of-concept study we could achieve a correct detection rate of 90.6%. With this approach, we provide a feasible method to accurately assess eye-blinks from high-speed video recordings.

  5. Research of solid state recorder for spacecraft

    OpenAIRE

    Shirakura, Masashi; Ichikawa, Satoshi; Sasada, Takeshi; Ohashi, Eiji; 白倉 政志; 市川 愉; 笹田 武志; 大橋 永嗣

    2006-01-01

    This research is to develop advanced, small, light-weight and low power consumption Solid State Recorder (SSR) on spacecraft utilizing the newest commercial semi-conductor memory device. We have manufactured, tested and evaluated next generation solid state recorder, researched high-efficient Error Detection And Correction code (EDAC). And also experimented and analyzed mission data of SSR on Mission Demonstration Satellite-1 (MDS-1) on orbit.

  6. Research of solid state recorder on spacecraft

    OpenAIRE

    Ichikawa, Satoshi; Shirakura, Masashi; Sasada, Takeshi; 市川 愉; 白倉 政志; 笹田 武志

    2004-01-01

    This research is to develop advanced, small, light-weight and low power consumption solid state recorder (SSR) on spacecraft utilizing the newest commercial semi-conductor memory device. Next generation solid state recorder has been manufactured, tested and evaluated, high-efficient error detection and correction code (EDAC) have been researched, and also mission data of SSR on Mission Demonstration Satellite-1 (MDS-1) on orbit has been experimented and analyzed.

  7. Land use change detection and impact assessment in Anzali international coastal wetland using multi-temporal satellite images.

    Science.gov (United States)

    Mousazadeh, Roya; Ghaffarzadeh, Hamidreza; Nouri, Jafar; Gharagozlou, Alireza; Farahpour, Mehdi

    2015-12-01

    Anzali is one of the 18 Iranian wetlands of international importance listed in Ramsar Convention. This unique ecosystem in the world with high ecological diversity is highly threatened by various factors such as pollutants, sedimentation, unauthorized development of urban infrastructure, over-harvesting of wetland resources, land use changes, and invasive species. Among which, one of the most challenging destructive factors, land use change, was scrutinized in this study. For this, remotely sensed data and Geographical Information System (GIS) were used to detect land changes and corresponding impacts on the study area over a 38-year period from 1975 to 2013.. Changes in the study area were traced in five dominant land-use classes at four time intervals of 1975, 1989, 2007, and 2013. Accordingly, changes in different categories were quantified using satellite images. The methodology adopted in this study includes an integrated approach of supervised classification, zonal and object-oriented image analyses. According to the Kappa coefficient of 0.84 for the land use map of 2013, the overall accuracy of the method was estimated at 89%, which indicated that this method can be useful for monitoring and behavior analysis of other Iranian wetlands. The obtained results revealed extensive land use changes over the study period. As the results suggest, between the years 1975 to 2013, approximately 6500 ha (∼69%) rangeland area degraded. Further, urban and agricultural areas have been extended by 2982 ha (∼74%) and 2228 ha (∼6%), respectively. This could leave a negative impact on water quality of the wetland.

  8. Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2011-01-01

    Full Text Available Vegetation phenology refers to the timing of seasonal biological events (for example, bud burst, leaf unfolding, vegetation growth and leaf senescence) and biotic and abiotic forces that control these. Daily, coarse-resolution satellite imagery...

  9. Strategies for handling missing clinical data for automated surgical site infection detection from the electronic health record.

    Science.gov (United States)

    Hu, Zhen; Melton, Genevieve B; Arsoniadis, Elliot G; Wang, Yan; Kwaan, Mary R; Simon, Gyorgy J

    2017-03-16

    Proper handling of missing data is important for many secondary uses of electronic health record (EHR) data. Data imputation methods can be used to handle missing data, but their use for analyzing EHR data is limited and specific efficacy for postoperative complication detection is unclear. Several data imputation methods were used to develop data models for automated detection of three types (i.e., superficial, deep, and organ space) of surgical site infection (SSI) and overall SSI using American College of Surgeons National Surgical Quality Improvement Project (NSQIP) Registry 30-day SSI occurrence data as a reference standard. Overall, models with missing data imputation almost always outperformed reference models without imputation that included only cases with complete data for detection of SSI overall achieving very good average area under the curve values. Missing data imputation appears to be an effective means for improving postoperative SSI detection using EHR clinical data.

  10. Catecholaminergic polymorphic ventricular tachycardia detected by an implantable loop recorder in a child.

    Science.gov (United States)

    Ergül, Yakup; Kıplapınar, Neslihan; Akdeniz, Celal; Tuzcu, Volkan

    2013-07-01

    We present a six-year-old boy with a history of recurrent syncope whose physical examination and family history were inconclusive. Laboratory findings, 12-lead ECG, chest radiography, Holter monitoring, event recorder monitoring, echocardiography, coronary computed tomography (CT) angiography, Brugada challenge test (ajmaline), cranial magnetic resonance imaging, and awake/sleep electroencephalogram were all unremarkable. Since syncope was exercise-induced, an electrophysiology study was also performed, but revealed no inducible ventricular arrhythmias. Implantable loop recorder (ILR) was implanted. Three weeks later, bidirectional ventricular tachycardia was found in ILR record during presyncope that was related to exercise. The patient, with the diagnosis of catecholaminergic polymorphic ventricular tachycardia, was started on high-dose beta-blocker therapy. Due to the recurrence of syncopes despite the presence of beta-blockers, an implantable cardioverter defibrillator was implanted.

  11. 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.

  12. 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

  13. Satellite Communication.

    Science.gov (United States)

    Technology Teacher, 1985

    1985-01-01

    Presents a discussion of communication satellites: explains the principles of satellite communication, describes examples of how governments and industries are currently applying communication satellites, analyzes issues confronting satellite communication, links mathematics and science to the study of satellite communication, and applies…

  14. Detection of error related neuronal responses recorded by electrocorticography in humans during continuous movements.

    Directory of Open Access Journals (Sweden)

    Tomislav Milekovic

    Full Text Available BACKGROUND: Brain-machine interfaces (BMIs can translate the neuronal activity underlying a user's movement intention into movements of an artificial effector. In spite of continuous improvements, errors in movement decoding are still a major problem of current BMI systems. If the difference between the decoded and intended movements becomes noticeable, it may lead to an execution error. Outcome errors, where subjects fail to reach a certain movement goal, are also present during online BMI operation. Detecting such errors can be beneficial for BMI operation: (i errors can be corrected online after being detected and (ii adaptive BMI decoding algorithm can be updated to make fewer errors in the future. METHODOLOGY/PRINCIPAL FINDINGS: Here, we show that error events can be detected from human electrocorticography (ECoG during a continuous task with high precision, given a temporal tolerance of 300-400 milliseconds. We quantified the error detection accuracy and showed that, using only a small subset of 2×2 ECoG electrodes, 82% of detection information for outcome error and 74% of detection information for execution error available from all ECoG electrodes could be retained. CONCLUSIONS/SIGNIFICANCE: The error detection method presented here could be used to correct errors made during BMI operation or to adapt a BMI algorithm to make fewer errors in the future. Furthermore, our results indicate that smaller ECoG implant could be used for error detection. Reducing the size of an ECoG electrode implant used for BMI decoding and error detection could significantly reduce the medical risk of implantation.

  15. Can we Detect Ecosystem Critical Transitions and Early Warning Signals of Catastrophic Shifts from Palaeo-Ecological Records?

    Science.gov (United States)

    Perga, M. E.; Taranu, Z. E.; Gregory-Eaves, I.; Frossard, V.; Thomas, Z.; Legendre, P.; Anderson, N. J.; Leavitt, P.; Gell, P.

    2015-12-01

    The observation that managed ecosystems often fail to respond smoothly to changing external pressures has shed some light on their complex non-linear dynamics. The concept of critical transitions (i.e., ecosystem regime shifts), thresholds and alternative stable states has since spread to the ecological and environmental management literature. Most recently, however, reviews have raised some skepticism about whether these catastrophic transitions are the exceptions rather than the rule. Overall, a better understanding of the occurrence and processes of such critical transitions requires more empirical testing and evidence on the mechanistic links between pressures and consequent ecological change. Many of the changes observed, or modeled, by ecologists extend beyond the monitoring record. Palaeo-ecological records thus represent a unique opportunity to extend our temporal perspective to the relevancy of critical transitions. Yet, paleo-ecological records have their own biases and shortcomings, such as sediment focusing, irregular temporal integration and often studied in a semi-quantitative way. As such, palaeo-ecological time series are not strictly analogous to instrumental datasets. In this work, we aimed to test, using both modeled and actual records, how different properties that are common in palaeo-ecological records affect our ability to detect past non-linear dynamics, such as early-warning signals of catastrophic shifts.

  16. 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.

  17. AIS Modeling and a Satellite for AIS Observations in the High North + Draft New ITU-R Report "Improved Satellite Detection of AIS"

    Science.gov (United States)

    2008-09-01

    Std Z39-18 Contents Contributions From FFI (Presentation to RTCM 2008) • Short overview of the space-based AIS challenge • Updated global detection... GNSS position 1 0 = Position is the current GNSS position; 1 = Reported position is not the current GNSS position = default Spare 1 Set to zero, to

  18. 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. 

  19. 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.

  20. Usefulness of an Implantable Loop Recorder to Detect Clinically Relevant Arrhythmias in Patients With Advanced Fabry Cardiomyopathy.

    Science.gov (United States)

    Weidemann, Frank; Maier, Sebastian K G; Störk, Stefan; Brunner, Thomas; Liu, Dan; Hu, Kai; Seydelmann, Nora; Schneider, Andreas; Becher, Jan; Canan-Kühl, Sima; Blaschke, Daniela; Bijnens, Bart; Ertl, Georg; Wanner, Christoph; Nordbeck, Peter

    2016-07-15

    Patients with genetic cardiomyopathy that involves myocardial hypertrophy often develop clinically relevant arrhythmias that increase the risk of sudden death. Consequently, guidelines for medical device therapy were established for hypertrophic cardiomyopathy, but not for conditions with only anecdotal evidence of arrhythmias, like Fabry cardiomyopathy. Patients with Fabry cardiomyopathy progressively develop myocardial fibrosis, and sudden cardiac death occurs regularly. Because 24-hour Holter electrocardiograms (ECGs) might not detect clinically important arrhythmias, we tested an implanted loop recorder for continuous heart rhythm surveillance and determined its impact on therapy. This prospective study included 16 patients (12 men) with advanced Fabry cardiomyopathy, relevant hypertrophy, and replacement fibrosis in "loco typico." No patients previously exhibited clinically relevant arrhythmias on Holter ECGs. Patients received an implantable loop recorder and were prospectively followed with telemedicine for a median of 1.2 years (range 0.3 to 2.0 years). The primary end point was a clinically meaningful event, which required a therapy change, captured with the loop recorder. Patients submitted data regularly (14 ± 11 times per month). During follow-up, 21 events were detected (including 4 asystole, i.e., ECG pauses ≥3 seconds) and 7 bradycardia events; 5 episodes of intermittent atrial fibrillation (>3 minutes) and 5 episodes of ventricular tachycardia (3 sustained and 2 nonsustained). Subsequently, as defined in the primary end point, 15 events leaded to a change of therapy. These patients required therapy with a pacemaker or cardioverter-defibrillator implantation and/or anticoagulation therapy for atrial fibrillation. In conclusion, clinically relevant arrhythmias that require further device and/or medical therapy are often missed with Holter ECGs in patients with advanced stage Fabry cardiomyopathy, but they can be detected by telemonitoring with

  1. Deep-turbulence wavefront sensing using digital-holographic detection in the off-axis image plane recording geometry

    Science.gov (United States)

    Spencer, Mark F.; Raynor, Robert A.; Banet, Matthias T.; Marker, Dan K.

    2017-03-01

    This paper develops wave-optics simulations which explore the estimation accuracy of digital-holographic detection for wavefront sensing in the presence of distributed-volume or "deep" turbulence and detection noise. Specifically, the analysis models spherical-wave propagation through varying deep-turbulence conditions along a horizontal propagation path and formulates the field-estimated Strehl ratio as a function of the diffraction-limited sampling quotient and signal-to-noise ratio. Such results will allow the reader to assess the number of pixels, pixel field of view, pixel-well depth, and read-noise standard deviation needed from a focal-plane array when using digital-holographic detection in the off-axis image plane recording geometry for deep-turbulence wavefront sensing.

  2. Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery

    Science.gov (United States)

    Nguyen, Hoang Hai; Tran, Hien; Sunwoo, Wooyeon; Yi, Jong-hyuk; Kim, Dongkyun; Choi, Minha

    2017-04-01

    A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.

  3. Satellite-based detection of 16.76 MeV γ-ray from H-bomb D-T fusion

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Based on the high energy γ-ray yield from the H-bomb D-T fusion reaction,it brings forward the idea applying the 16.76 MeV γ-ray to judge whether the H-bomb happens or not,and to deduce the explosion TNT equivalent accurately.The Monte Carlo N-Particle was applied to simulate the high energy γ-ray radiation characteristics reaching the geosynchronous orbit satellite,and the CVD diamond detector suit for the requirements was researched.A series of experiments were carried out to testify the capabilities of the diamond detector.It provides a brand-new approach to satellite-based nuclear explosion detection.

  4. Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

    DEFF Research Database (Denmark)

    Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

    relevant satellite and “ground-truth” data, building the Round-Robin Data Package for testing the algorithms, and finally selection of the most promising algorithm(s) for processing of a new sea ice drift climate dataset. Specific efforts are dedicated to the definition of per-grid-cell uncertainties...

  5. Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

    DEFF Research Database (Denmark)

    Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

    relevant satellite and “ground-truth” data, building the Round-Robin Data Package for testing the algorithms, and finally selection of the most promising algorithm(s) for processing of a new sea ice drift climate dataset. Specific efforts are dedicated to the definition of per-grid-cell uncertainties...

  6. Dark-bellied Brent Geese Branta bernicla bernicla, as recorded by satellite telemetry, do not minimize flight distance during spring migration

    NARCIS (Netherlands)

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

    2002-01-01

    Nine Dark-bellied Brent Geese Branta bernicla bernicla were equipped with satellite transmitters during spring staging in the Dutch Wadden Sea in 1998 and 1999. The transmitters (in all cases less than 3% of body mass) were attached to the back by a flexible elastic harness. One juvenile female was

  7. Useful Interplay Between Spontaneous ADR Reports and Electronic Healthcare Records in Signal Detection

    NARCIS (Netherlands)

    A.C. Pacurariu (Alexandra C.); S.M.J.M. Straus (Sabine); G. Trifirò (Gianluca); M.J. Schuemie (Martijn); R. Gini (Rosa); R.M.C. Herings (Ron); G. Mazzaglia (Giampiero); G. Picelli (Gino); L. Scotti (Lorenza); L. Pedersen (Lars); P. Arlett (Peter); J. van der Lei (Johan); M.C.J.M. Sturkenboom (Miriam); P.M. Coloma (Preciosa)

    2015-01-01

    textabstractBackground and Objective: Spontaneous reporting systems (SRSs) remain the cornerstone of post-marketing drug safety surveillance despite their well-known limitations. Judicious use of other available data sources is essential to enable better detection, strengthening and validation of si

  8. Optimizing Detection Rate and Characterization of Subtle Paroxysmal Neonatal Abnormal Facial Movements with Multi-Camera Video-Electroencephalogram Recordings.

    Science.gov (United States)

    Pisani, Francesco; Pavlidis, Elena; Cattani, Luca; Ferrari, Gianluigi; Raheli, Riccardo; Spagnoli, Carlotta

    2016-06-01

    Objectives We retrospectively analyze the diagnostic accuracy for paroxysmal abnormal facial movements, comparing one camera versus multi-camera approach. Background Polygraphic video-electroencephalogram (vEEG) recording is the current gold standard for brain monitoring in high-risk newborns, especially when neonatal seizures are suspected. One camera synchronized with the EEG is commonly used. Methods Since mid-June 2012, we have started using multiple cameras, one of which point toward newborns' faces. We evaluated vEEGs recorded in newborns in the study period between mid-June 2012 and the end of September 2014 and compared, for each recording, the diagnostic accuracies obtained with one-camera and multi-camera approaches. Results We recorded 147 vEEGs from 87 newborns and found 73 episodes of paroxysmal facial abnormal movements in 18 vEEGs of 11 newborns with the multi-camera approach. By using the single-camera approach, only 28.8% of these events were identified (21/73). Ten positive vEEGs with multicamera with 52 paroxysmal facial abnormal movements (52/73, 71.2%) would have been considered as negative with the single-camera approach. Conclusions The use of one additional facial camera can significantly increase the diagnostic accuracy of vEEGs in the detection of paroxysmal abnormal facial movements in the newborns.

  9. PAN in the eastern Pacific free troposphere: A satellite view of the sources, seasonality, interannual variability, and timeline for trend detection

    Science.gov (United States)

    Zhu, Liye; Payne, Vivienne H.; Walker, Thomas W.; Worden, John R.; Jiang, Zhe; Kulawik, Susan S.; Fischer, Emily V.

    2017-03-01

    Peroxyacetyl nitrate (PAN) is an important trace gas that serves to transport nitrogen oxide radicals throughout the troposphere. We present an analysis of satellite observations of PAN from the Tropospheric Emission Spectrometer (TES) over the eastern Pacific Ocean for April and July 2006-2010 and the spring-to-summer seasonal transition for 2006. TES can provide quantitative estimates of free tropospheric PAN in clear-sky or thin cloud conditions where elevated PAN (>0.2 ppbv) is present. The percentage of successful PAN detections increases from April to July and then decreases in August and September. However, there are no significant differences in the tropospheric average PAN either interannually or between these months. Plumes containing elevated PAN are present almost every day in July. Elevated PAN observed in July has multiple sources, including fires in Siberia, anthropogenic sources in eastern China, and recirculated pollution from the continental U.S. We combined the observed variability in the TES PAN retrievals over the eastern Pacific Ocean with a range of possible trends in PAN to determine the observational requirements to detect such trends. Based on the variability observed in the PAN retrievals over this region, we predict that 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 in situ surface observations and that a trend of a given magnitude would be more quickly detected in summer than spring.

  10. Detecting drought trends with expanded meteorological records based on Reanalysis data

    Science.gov (United States)

    Meza, F. J.; Morales, D.

    2013-12-01

    In Mediterranean regions, droughts are a recurrent phenomenon that cause significant economic losses and affect ecosystem functioning. The need to better monitor drought and study changes in their main properties is important for disaster risk management. An objective identification of drought and dry spell sequences depends on consistent, reliable and readily derived indicators. The Standardized Precipitation Evapotranspiration Index (SPEI) corresponds to one of these indicators as it is based in a water balance approach, facilitating drought analysis and monitoring since it allows the user to examine wet and dry periods over different time scales. SPEI has been used to characterize recent drought in the arid regions that experienced significant warming over the last century. Thus it becomes an effective tool to assess whether trends in drought events are present. The main objective of this work is to apply the SPEI and study trends of droughts of different magnitude as well as to describe their association with El Niño phenomenon in the Maipo Region (Central Chile). To circumvent problems of insufficient record length we applied a novel method for record expansion based on Reanalysis data. This method was used for data filling as well as to produce a regionally consistent database that started in 1950. Data shows that the occurrence of dry conditions of different magnitude has increased over the last decades, and the duration of extreme climatic events has slightly increased as well. These results are consistent with future climatic projections and represent a major challenge for water resources management.

  11. STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery

    Science.gov (United States)

    Schiaffino, L.; Rosado Muñoz, A.; Guerrero Martínez, J.; Francés Villora, J.; Gutiérrez, A.; Martínez Torres, I.; Kohan, y. D. R.

    2016-04-01

    Deep Brain Stimulation (DBS) applies electric pulses into the subthalamic nucleus (STN) improving tremor and other symptoms associated to Parkinson’s disease. Accurate STN detection for proper location and implant of the stimulating electrodes is a complex task and surgeons are not always certain about final location. Signals from the STN acquired during DBS surgery are obtained with microelectrodes, having specific characteristics differing from other brain areas. Using supervised learning, a trained model based on previous microelectrode recordings (MER) can be obtained, being able to successfully classify the STN area for new MER signals. The K Nearest Neighbours (K-NN) algorithm has been successfully applied to STN detection. However, the use of the fuzzy form of the K-NN algorithm (KNN-F) has not been reported. This work compares the STN detection algorithm of K-NN and KNN-F. Real MER recordings from eight patients where previously classified by neurophysiologists, defining 15 features. Sensitivity and specificity for the classifiers are obtained, Wilcoxon signed rank non-parametric test is used as statistical hypothesis validation. We conclude that the performance of KNN-F classifier is higher than K-NN with p<0.01 in STN specificity.

  12. QRS classification and spatial combination for robust heart rate detection in low-quality fetal ECG recordings.

    Science.gov (United States)

    Warmerdam, G; Vullings, R; Van Pul, C; Andriessen, P; Oei, S G; Wijn, P

    2013-01-01

    Non-invasive fetal electrocardiography (ECG) can be used for prolonged monitoring of the fetal heart rate (FHR). However, the signal-to-noise-ratio (SNR) of non-invasive ECG recordings is often insufficient for reliable detection of the FHR. To overcome this problem, source separation techniques can be used to enhance the fetal ECG. This study uses a physiology-based source separation (PBSS) technique that has already been demonstrated to outperform widely used blind source separation techniques. Despite the relatively good performance of PBSS in enhancing the fetal ECG, PBSS is still susceptible to artifacts. In this study an augmented PBSS technique is developed to reduce the influence of artifacts. The performance of the developed method is compared to PBSS on multi-channel non-invasive fetal ECG recordings. Based on this comparison, the developed method is shown to outperform PBSS for the enhancement of the fetal ECG.

  13. 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

  14. DETECTION OF QRS COMPLEXES OF ECG RECORDING BASED ON WAVELET TRANSFORM USING MATLAB

    Directory of Open Access Journals (Sweden)

    Ruchita Gautam,

    2010-07-01

    Full Text Available The electrocardiogram (ECG is quite important tool to find out more information about the heart. The main tasks in ECG signal analysis are the detection of QRS complex (i.e. R wave, and the estimation ofinstantaneous heart rate by measuring the time interval between two consecutive R-waves. After recognizing R wave, other components like P, Q, S and T can be detected by using window method. In this paper, we describe a QRS complex detector based on the Dyadic wavelet transform (DyWT which is robust in comparison with time- varying QRS complex morphology and to noise. We illustrate the performance of the DyWT-based QRS detector by considering problematic ECG signals from Common Standard for Electrocardiography (CSE database. We also compare and analyze its performance to some of the QRS detectors developed in the past.

  15. Radiometric Short-Term Fourier Transform analysis of photonic Doppler velocimetry recordings and detectivity limit

    Science.gov (United States)

    Prudhomme, G.; Berthe, L.; Bénier, J.; Bozier, O.; Mercier, P.

    2017-01-01

    Photonic Doppler Velocimetry is a plug-and-play and versatile diagnostic used in dynamic physic experiments to measure velocities. When signals are analyzed using a Short-Time Fourier Transform, multiple velocities can be distinguished: for example, the velocities of moving particle-cloud appear on spectrograms. In order to estimate the back-scattering fluxes of target, we propose an original approach "PDV Radiometric analysis" resulting in an expression of time-velocity spectrograms coded in power units. Experiments involving micron-sized particles raise the issue of detection limit; particle-size limit is very difficult to evaluate. From the quantification of noise sources, we derive an estimation of the spectrogram noise leading to a detectivity limit, which may be compared to the fraction of the incoming power which has been back-scattered by the particle and then collected by the probe. This fraction increases with their size. At last, some results from laser-shock accelerated particles using two different PDV systems are compared: it shows the improvement of detectivity with respect to the Effective Number of Bits (ENOB) of the digitizer.

  16. Risk factor detection for heart disease by applying text analytics in electronic medical records.

    Science.gov (United States)

    Torii, Manabu; Fan, Jung-Wei; Yang, Wei-Li; Lee, Theodore; Wiley, Matthew T; Zisook, Daniel S; Huang, Yang

    2015-12-01

    In the United States, about 600,000 people die of heart disease every year. The annual cost of care services, medications, and lost productivity reportedly exceeds 108.9 billion dollars. Effective disease risk assessment is critical to prevention, care, and treatment planning. Recent advancements in text analytics have opened up new possibilities of using the rich information in electronic medical records (EMRs) to identify relevant risk factors. The 2014 i2b2/UTHealth Challenge brought together researchers and practitioners of clinical natural language processing (NLP) to tackle the identification of heart disease risk factors reported in EMRs. We participated in this track and developed an NLP system by leveraging existing tools and resources, both public and proprietary. Our system was a hybrid of several machine-learning and rule-based components. The system achieved an overall F1 score of 0.9185, with a recall of 0.9409 and a precision of 0.8972.

  17. Abrupt climate changes of the last deglaciation detected in a western Mediterranean forest record

    Directory of Open Access Journals (Sweden)

    W. J. Fletcher

    2009-01-01

    Full Text Available Evidence for abrupt changes in western Mediterranean climate between 20 and 6 cal ka BP is examined in marine core MD95-2043 (Alborán Sea, using pollen data for temperate Mediterranean forest development and pollen-based climate reconstructions using the modern analogue technique (MAT for annual precipitation (Pann and mean temperatures of the coldest and warmest months (MTCO and MTWA. Major climatic shifts with parallel temperature and precipitation changes occurred at the onsets of Heinrich Event 1 (equivalent to the Oldest Dryas, the Bölling-Allerød (BA, and the Younger Dryas (YD. Multi-centennial-scale oscillations in forest development related to regional precipitation (Pann variability occurred throughout the BA, YD, and early Holocene, with drier atmospheric conditions in phase with Lateglacial events of high-latitude cooling including GI-1d (Older Dryas, GI-1b (Intra-Allerød Cold Period and GS-1 (YD, and during Holocene events associated with high-latitude cooling, meltwater pulses and N. Atlantic ice-rafting (events at 11.4, 10.1, 9.3, 8.2 and 7.4 cal ka BP. The forest record also indicates multi-centennial variability within the YD interval and multiple Preboreal climate oscillations. A possible climatic mechanism for the recurrence of dry intervals and an opposed regional precipitation pattern with respect to western-central Europe relates to the dynamics of the jet stream and the prevalence of atmospheric blocking highs. Comparison of radiocarbon and ice-core ages for well-defined climatic transitions in the forest record suggests possible enhancement of marine reservoir ages in the Alborán Sea by ~200 years (surface water age ~600 years during the Lateglacial.

  18. Gamma-ray detection efficiency of the microchannel plate installed as an ion detector in the low energy particle instrument onboard the GEOTAIL satellite.

    Science.gov (United States)

    Tanaka, Y T; Yoshikawa, I; Yoshioka, K; Terasawa, T; Saito, Y; Mukai, T

    2007-03-01

    A microchannel plate (MCP) assembly has been used as an ion detector in the low energy particle (LEP) instrument onboard the magnetospheric satellite GEOTAIL. Recently the MCP assembly has detected gamma rays emitted from an astronomical object and has been shown to provide unique information of gamma rays if they are intense enough. However, the detection efficiency for gamma rays was not measured before launch, and therefore we could not analyze the LEP data quantitatively. In this article, we report the gamma-ray detection efficiency of the MCP assembly. The measured efficiencies are 1.29%+/-0.71% and 0.21%+/-0.14% for normal incidence 60 and 662 keV gamma rays, respectively. The incident angle dependence is also presented. Our calibration is crucial to study high energy astrophysical phenomena by using the LEP.

  19. 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

  20. 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

    2010-06-01

    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 ≥1.5×10(4) 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.

  1. 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.

  2. A NOVEL SHIP DETECTION METHOD FOR LARGE-SCALE OPTICAL SATELLITE IMAGES BASED ON VISUAL LBP FEATURE AND VISUAL ATTENTION MODEL

    Directory of Open Access Journals (Sweden)

    S. Haigang

    2016-06-01

    Full Text Available 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.

  3. 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.

  4. Image and Processing Models for Satellite Detection in Images Acquired by Space-based Surveillance-of-Space Sensors

    Science.gov (United States)

    2010-09-01

    software. Résumé …..... Dans le cadre de la surveillance de l’espace, les objets spatiaux connus en orbite (OSO), i.e., satellites actifs ou débris...SAPPHIRE et NEOSSat. Ce document contient des modèles qui décrivent la formation des images et le processus d’acquisition de capteurs , basés au sol ou dans

  5. Method for detecting moment connection fracture using high-frequency transients in recorded accelerations

    Science.gov (United States)

    Rodgers, J.E.; Elebi, M.

    2011-01-01

    The 1994 Northridge earthquake caused brittle fractures in steel moment frame building connections, despite causing little visible building damage in most cases. Future strong earthquakes are likely to cause similar damage to the many un-retrofitted pre-Northridge buildings in the western US and elsewhere. Without obvious permanent building deformation, costly intrusive inspections are currently the only way to determine if major fracture damage that compromises building safety has occurred. Building instrumentation has the potential to provide engineers and owners with timely information on fracture occurrence. Structural dynamics theory predicts and scale model experiments have demonstrated that sudden, large changes in structure properties caused by moment connection fractures will cause transient dynamic response. A method is proposed for detecting the building-wide level of connection fracture damage, based on observing high-frequency, fracture-induced transient dynamic responses in strong motion accelerograms. High-frequency transients are short (Elsevier B.V. All rights reserved.

  6. 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 STT RMS was also observed from the P-lead in comparison to lead II (668 versus 573 μV, p 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.

  7. New Generation Meteorological Satellite Imager Aviation Decision Support Applications for Detection of Convection, Turbulence, and Volcanic Ash

    Science.gov (United States)

    Feltz, Wayne

    2016-04-01

    A suite of aviation related decision support products have been in development to meet GOES-R science requirements since 2008 and are being evaluated to assess meteorological hazards to aircraft in flight derived from the current generation of European Spinning Enhanced Visible and Infrared Imager (SEVIRI) imager data. This presentation will focus on GOES-R Advanced Baseline Imager (ABI) measurement requirements relating to satellite-based aviation convective, turbulence, and volcanic ash/SO2 products that can be applied globally on next generation geostationary imagers including the Japanese Himawari, South Korean COMS (AMI), and European Metop-SG imagers. These new methodologies have relevance on current generation GOES and SEVIRI imagers, and overview will include discussion on how product utility has been improved through satellite GOES-R/JPSS Proving Ground NOAA testbed activities. Satellite-based decision support for aviation context toward improvement of future air transportation route planning and warning for the general public with emphasis on successfully bridging research to operations will also be discussed with anticipated October 2016 launch of GOES-R.

  8. 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.

  9. Declassified intelligence satellite photographs

    Science.gov (United States)

    ,

    1998-01-01

    Recently declassified photographs from spy satellites are an important addition to the record of the Earth?s land surface held by the U.S. Geological Survey (USGS). More than 800,000 high-resolution photos taken between 1959 through 1972 were made available by Executive Order of the President. The collection is held at the USGS EROS Data Center, near Sioux Falls, S. Dak., and are offered for public sale. For some purposes in earth science studies, these photos extend the record of changes in the land surface another decade back in time from the advent of the Landsat earth-observing satellite program.

  10. SNR changes of VLF radio signals detected onboard the DEMETER satellite and their possible relationship to the Wenchuan earthquake

    Institute of Scientific and Technical Information of China (English)

    M.; Parrot

    2009-01-01

    Here we used the VLF signal data received by the DEMETER satellite, transmitted from various ground VLF transmitters which are located around China, to study the changes in the signal to noise ratio (SNR) before and after the Wenchuan earthquake, which had a magnitude of 8.0. We also found that the SNRs of different frequency signals decreased significantly over the epicenter region before the earthquake, and reverted to their original levels after the earthquake. This phenomenon may be related to the earthquake.

  11. 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

  12. 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.

  13. Detecting Spatial Patterns of Disease in Large Collections of Electronic Medical Records Using Neighbor-Based Bootstrapping.

    Science.gov (United States)

    Patterson, Maria T; Grossman, Robert L

    2017-09-01

    We introduce a method called neighbor-based bootstrapping (NB2) that can be used to quantify the geospatial variation of a variable. We applied this method to an analysis of the incidence rates of disease from electronic medical record data (International Classification of Diseases, Ninth Revision codes) for ∼100 million individuals in the United States over a period of 8 years. We considered the incidence rate of disease in each county and its geospatially contiguous neighbors and rank ordered diseases in terms of their degree of geospatial variation as quantified by the NB2 method. We show that this method yields results in good agreement with established methods for detecting spatial autocorrelation (Moran's I method and kriging). Moreover, the NB2 method can be tuned to identify both large area and small area geospatial variations. This method also applies more generally in any parameter space that can be partitioned to consist of regions and their neighbors.

  14. 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

  15. Globally Gridded Satellite observations for climate studies

    Science.gov (United States)

    Knapp, K.R.; Ansari, S.; Bain, C.L.; Bourassa, M.A.; Dickinson, M.J.; Funk, C.; Helms, C.N.; Hennon, C.C.; Holmes, C.D.; Huffman, G.J.; Kossin, J.P.; Lee, H.-T.; Loew, A.; Magnusdottir, G.

    2011-01-01

    Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them that no central archive of geostationary data for all international satellites exists, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multisatellite climate studies. The International Satellite Cloud Climatology Project (ISCCP) set the stage for overcoming these issues by archiving a subset of the full-resolution geostationary data at ~10-km resolution at 3-hourly intervals since 1983. Recent efforts at NOAA's National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in Network Common Data Format (netCDF) using standards that permit a wide variety of tools and libraries to process the data quickly and easily. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

  16. Emergency Department Chief Complaint and Diagnosis Data to Detect Influenza-Like Illness with an Electronic Medical Record

    Directory of Open Access Journals (Sweden)

    May, Larissa S

    2010-02-01

    Full Text Available 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

  17. 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.

  18. Ground settlement of Chek Lap Kok Airport, Hong Kong,detected by satellite synthetic aperture radar interferometry

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Satellite synthetic aperture radar (SAR) interferometry is used to investigate the slowly accumulating ground settlement at the new Chek Lap Kok Airport in Hong Kong. Most of the land occupied by the airport was reclaimed from the sea and therefore certain ground settlement in the area has been expected. A pair of ERS-2 SAR images spanning nearly a year is used in the study. The high spatial resolution (20 m× 20 m) ground settlement map derived indicates that the settlement that occurred in the area over the time period is as large as 50 mm. The SAR measurement results agree with the levelling measurements at some benchmarks in the area to well within 1 cm(rms error),and the overall correlation between the two types of results is 0.89. The paper presents some brief background of interferometric SAR, and outlines the data processing methods and results.

  19. Development of a Climate Record of Tropospheric and Stratospheric Column Ozone from Satellite Remote Sensing: Evidence of an Early Recovery of Global Stratospheric Ozone

    Science.gov (United States)

    Ziemke, Jerald R.; Chandra, Sushil

    2012-01-01

    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.

  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. Geographic Object-Based Image Analysis Using Optical Satellite Imagery and GIS Data for the Detection of Mining Sites in the Democratic Republic of the Congo

    Directory of Open Access Journals (Sweden)

    Fritjof Luethje

    2014-07-01

    Full Text Available Earth observation is an important source of information in areas that are too remote, too insecure or even both for traditional field surveys. A multi-scale analysis approach is developed to monitor the Kivu provinces in the Democratic Republic of the Congo (DRC to identify hot spots of mining activities and provide reliable information about the situation in and around two selected mining sites, Mumba-Bibatama and Bisie. The first is the test case for the approach and the detection of unknown mining sites, whereas the second acts as reference case since it is the largest and most well-known location for cassiterite extraction in eastern Congo. Thus it plays a key-role within the context of the conflicts in this region. Detailed multi-temporal analyses of very high-resolution (VHR satellite data demonstrates the capabilities of Geographic Object-Based Image Analysis (GEOBIA techniques for providing information about the situation during a mining ban announced by the Congolese President between September 2010 and March 2011. Although the opening of new surface patches can serve as an indication for activities in the area, the pure change between the two satellite images does not in itself produce confirming evidence. However, in combination with observations on the ground, it becomes evident that mining activities continued in Bisie during the ban, even though the production volume went down considerably.

  2. Estimating Arctic sea-ice freeze-up and break-up from the satellite record: A comparison of different approaches in the Chukchi and Beaufort Seas

    Directory of Open Access Journals (Sweden)

    Mark Johnson

    2016-09-01

    Full Text Available 1. Abstract The recognized importance of the annual cycle of sea ice in the Arctic to heat budgets, human behavior, and ecosystem functions, requires consistent definitions of such key events in the ice cycle as break-up and freeze-up. An internally consistent and reproducible approach to characterize the timing of these events in the annual sea-ice cycle is described. An algorithm was developed to calculate the start and end dates of freeze-up and break-up and applied to time series of satellite-derived sea-ice concentration from 1979 to 2013. Our approach builds from discussions with sea-ice experts having experience observing and working on the sea ice in the Bering, Chukchi and Beaufort Seas. Applying the algorithm to the 1979–2013 satellite data reveals that freeze-up is delayed by two weeks per decade for the Chukchi coast and one week per decade for the Beaufort coast. For both regions, break-up start is arriving earlier by 5–7 days per decade and break-up end is arriving earlier by 10–12 days per decade. In the Chukchi Sea, “early” break-up is arriving earlier by one month over the 34-year period and alternates with a “late” break-up. The calculated freeze-up and break-up dates provide information helpful to understanding the dynamics of the annual sea-ice cycle and identifying the drivers that modify this cycle. The algorithm presented here, and potential refinements, can help guide future work on changes in the seasonal cycle of sea ice. The sea-ice phenology of freeze-up and break-up that results from our approach is consistent with observations of sea-ice use. It may be applied to advancing our understanding and prediction of the timing of seasonal navigation, availability of ice as a biological habitat, and assessment of numerical models.

  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. Satellite RNAs and Satellite Viruses.

    Science.gov (United States)

    Palukaitis, Peter

    2016-03-01

    Satellite RNAs and satellite viruses are extraviral components that can affect either the pathogenicity, the accumulation, or both of their associated viruses while themselves being dependent on the associated viruses as helper viruses for their infection. Most of these satellite RNAs are noncoding RNAs, and in many cases, have been shown to alter the interaction of their helper viruses with their hosts. In only a few cases have the functions of these satellite RNAs in such interactions been studied in detail. In particular, work on the satellite RNAs of Cucumber mosaic virus and Turnip crinkle virus have provided novel insights into RNAs functioning as noncoding RNAs. These effects are described and potential roles for satellite RNAs in the processes involved in symptom intensification or attenuation are discussed. In most cases, models describing these roles involve some aspect of RNA silencing or its suppression, either directly or indirectly involving the particular satellite RNA.

  5. Oceanic whitecaps: Sea surface features detectable via satellite that are indicators of the magnitude of the air-sea gas transfer coefficient

    Indian Academy of Sciences (India)

    E C Monahan

    2002-09-01

    Stage A whitecaps (spilling wave crests) have a microwave emissivity of close to 1. Thus if even a small fraction of the sea surface is covered by these features there will be a detectable enhancement in the apparent microwave brightness temperature of that surface as determined by satellite-borne microwave radiometers. This increase in the apparent microwave brightness temperature can as a consequence be routinely used to estimate the fraction of the sea surface covered by stage A whitecaps. For all but the very lowest wind speeds it has been shown in a series of controlled experiments that the air-sea gas transfer coeffcient for each of a wide range of gases, including carbon dioxide and oxygen, is directly proportional to the fraction of the sea surface covered by these stage A whitecaps.

  6. Rapid, High-Resolution Detection of Environmental Change over Continental Scales from Satellite Data - the Earth Observation Data Cube

    Science.gov (United States)

    Lewis, Adam; Lymburner, Leo; Purss, Matthew B. J.; Brooke, Brendan; Evans, Ben; Ip, Alex; Dekker, Arnold G.; Irons, James R.; Minchin, Stuart; Mueller, Norman

    2015-01-01

    The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.

  7. 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%).

  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. Satellite detection of IR precursors using bi-angular advanced along-track scanning radiometer data: a case study of Yushu earthquake

    Institute of Scientific and Technical Information of China (English)

    Pan Xiong; Xuhui Shen; Xingfa Gu; Qingyan Meng; Yaxin Bi; Liming Zhao; Yanhua Zhao

    2015-01-01

    The paper has developed and proposed a synthesis analysis method based on the robust satellite data analysis technique (RST) to detect seismic anomalies within the bi-angular advanced along-track scanning radiometer (AATSR) gridded brightness temperature (BT)data based on spatial/temporal continuity analysis.The proposed methods have been applied to analyze the Yushu (Qinghai,China) earthquake occurred on 14th April 2010,and a full AATSR data-set of 8 years data from March 2003 to May 2010 with longitude from 91°E to 101°E and latitude from 28°N to 38°N has been analyzed.Combining with the tectonic explanation of spatial and temporal continuity of the abnormal phenomena,the analyzed results indicate that the infrared radiation anomalies detected by the AATSR BT data with nadir view appear and enhance gradually along with the development and occurring of the earthquake,especially along the Ganzi-Yushu fault,Nu River fault and Jiali-Chayu fault;more infrared anomalies along the earthquake fault zone (Lancangjiang fault and Ning Karma Monastery-Deqin fault) are detected using the proposed synthesis analysis method,which can also characterize the activity of seismic faults more precisely.

  10. 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....

  11. Inter-satellite links for satellite autonomous integrity monitoring

    Science.gov (United States)

    Rodríguez-Pérez, Irma; García-Serrano, Cristina; Catalán Catalán, Carlos; García, Alvaro Mozo; Tavella, Patrizia; Galleani, Lorenzo; Amarillo, Francisco

    2011-01-01

    A new integrity monitoring mechanisms to be implemented on-board on a GNSS taking advantage of inter-satellite links has been introduced. This is based on accurate range and Doppler measurements not affected neither by atmospheric delays nor ground local degradation (multipath and interference). By a linear combination of the Inter-Satellite Links Observables, appropriate observables for both satellite orbits and clock monitoring are obtained and by the proposed algorithms it is possible to reduce the time-to-alarm and the probability of undetected satellite anomalies.Several test cases have been run to assess the performances of the new orbit and clock monitoring algorithms in front of a complete scenario (satellite-to-satellite and satellite-to-ground links) and in a satellite-only scenario. The results of this experimentation campaign demonstrate that the Orbit Monitoring Algorithm is able to detect orbital feared events when the position error at the worst user location is still under acceptable limits. For instance, an unplanned manoeuvre in the along-track direction is detected (with a probability of false alarm equals to 5 × 10-9) when the position error at the worst user location is 18 cm. The experimentation also reveals that the clock monitoring algorithm is able to detect phase jumps, frequency jumps and instability degradation on the clocks but the latency of detection as well as the detection performances strongly depends on the noise added by the clock measurement system.

  12. Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: combining a new passive microwave vegetation density record with reflective greenness data

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-05-01

    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 use 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 seems 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, bringing new insights on vegetation dynamics.

  13. 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.

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

    Science.gov (United States)

    Marghany, Maged

    2014-12-15

    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.

  15. Satellite theory

    Science.gov (United States)

    Kozai, Y.

    1981-04-01

    The dynamical characteristics of the natural satellite of Mars, Jupiter, Saturn, Uranus and Neptune are analyzed on the basis of the solar tidal perturbation factor and the oblateness factor of the primary planet for each satellite. For the inner satellites, for which the value of the solar tidal factor is much smaller than the planetary oblateness factor, it is shown that the eccentricity and inclination of satellite orbits are generally very small and almost constant; several pairs of inner satellites are also found to exhibit commensurable mean motions, or secular accelerations in mean longitude. In the case of the outer satellites, for which solar perturbations are dominant, secular perturbations and long-period perturbations may be derived by the solution of equations of motion reduced to one degree of freedom. The existence of a few satellites, termed intermediary satellites, for which the solar tidal perturbation is on the order of the planetary oblateness factor, is also observed, and the pole of the orbital plane of the satellite is noted to execute a complex motion around the pole of the planet or the orbital plane of the planet.

  16. Space Environment Deteation of Chinese Meteorological Satellites

    Institute of Scientific and Technical Information of China (English)

    XU Ying; WANG Shijin; ZHU Guangwu; LIANG Jinbao

    2004-01-01

    This paper presents the space environment detection of Chinese geosynchronous and sun-synchronous meteorological satellites and gives a short perspective of space environment observations on board meteorological satellites.

  17. 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.

  18. 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

  19. Algorithm for Satellite Detection Capability Based on Fuzzy AHP Assessment%基于模糊层次分析法的卫星探测效能评估算法

    Institute of Scientific and Technical Information of China (English)

    王玉菊; 岳丽军

    2012-01-01

    Taking remote sensing satellites as an example, performance assessment techniques of satellite detection were studied. First, a satellite-based practical detection capability assessment hierarchy was established, and then the integrating use of motion simulation, probability theory, and continuous Markov chain and Monte Carlo methods, the corresponding algorithm model was established for assessment of satellite detection of individual targets. Then, based on fuzzy analytic hierarchy process, satellite-ship target of evaluation index weights was determined. The final adoption of an application example verifies superiority of the algorithm in the program's priority selection.%以遥感卫星为例研究了卫星探测效能评估技术。首先建立基于实用化的卫星探测能力评估递阶层次结构,接着综合运用运动仿真、概率论、连续马尔科夫链和蒙特卡罗法等方法对卫星探测评估中的单项指标建立相应的算法模型,然后基于模糊层次分析法确定卫星探测舰船目标的各评价指标权重,最后通过一个应用实例验证该算法在方案选优中的优越性。

  20. Declassified Intelligence Satellite Photographs

    Science.gov (United States)

    ,

    2008-01-01

    Declassified photographs from U.S. intelligence satellites provide an important worldwide addition to the public record of the Earth's land surface. This imagery was released to the National Archives and Records Administration (NARA) and the U.S. Geological Survey (USGS) in accordance with Executive Order 12951 on February 23, 1995. The NARA has the original declassified film and a viewing copy. The USGS has another copy of the film to complement the Landsat archive. The declassified collection involves more than 990,000 photographs taken from 1959 through 1980 and was released on two separate occasions: February 1995 (Declass 1) and September 2002 (Declass 2). The USGS copy is maintained by the Earth Resources Observation and Science (EROS) Center, near Sioux Falls, South Dakota. Both the NARA and EROS provide public access to this unique collection that extends the record of land-surface change back another decade from the advent of the Landsat program that began satellite operations in 1972.

  1. Neptunian Satellites observed with Keck AO system

    Science.gov (United States)

    Marchis, F.; Urata, R.; de Pater, I.; Gibbard, S.; Hammel, H. B.; Berthier, J.

    2004-05-01

    The Neptunian system was observed on 9 different nights between July 2002 and October 2003 with the 10-m Keck telescope on Mauna Kea, Hawaii, and its facility instrument NIRC2 coupled with the Adaptive Optics system. Data were recorded in J (1.2μ m), and H (2.2μ m) bands. The angular resolution achieved on a one-minute integration time image is 0.50 arcsec, corresponding to a spatial resolution of 1100 km. The images display small structures such as the rings (de Pater et al. 2004), clouds in the atmosphere (Gibbard et al. 2003), and inner satellites, mainly Proteus, Larissa, Galatea, Despina, and Thalassa. On the 40 images, the positions and intensities of the satellites detected were accurately measured fitting the signal with a gaussian profile. The center of Neptune was obtained by fitting the disk position with an ellipse. After correcting for the detector distortion, we compared the satellite positions with the predicted ones delivered by several ephemerides. We used the JPL (NEP016 + NEP022 + DE405) and two IMCCE ephemerides, an old version (VSOP87+Owen et al., 1991) and a more recent one (DE405+Le Guyader et al., 1993). All cases, we confirmed the presence of an apparent shift between the predicted and the observed positions. Table 1 (see http://astron.berkeley.edu/ fmarchis/Science/Neptune/Satellites/) summarizes the mean distance of the shift for satellites most frequently observed and the various ephemerides. In this presentation, we will report the positions of the satellites, and present their color and possible photometric variations derived from the observations. This work has been partially supported by the National Science Foundation Science and Technology Center for Adaptive Optics, managed by the University of California at Santa Cruz under cooperative agreement No. AST - 9876783.

  2. Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River basin of China

    Science.gov (United States)

    Pan, Yun; Zhang, Chong; Gong, Hui