WorldWideScience

Sample records for satellite datasets thought

  1. SatelliteDL: a Toolkit for Analysis of Heterogeneous Satellite Datasets

    Science.gov (United States)

    Galloy, M. D.; Fillmore, D.

    2014-12-01

    SatelliteDL is an IDL toolkit for the analysis of satellite Earth observations from a diverse set of platforms and sensors. The core function of the toolkit is the spatial and temporal alignment of satellite swath and geostationary data. The design features an abstraction layer that allows for easy inclusion of new datasets in a modular way. Our overarching objective is to create utilities that automate the mundane aspects of satellite data analysis, are extensible and maintainable, and do not place limitations on the analysis itself. IDL has a powerful suite of statistical and visualization tools that can be used in conjunction with SatelliteDL. Toward this end we have constructed SatelliteDL to include (1) HTML and LaTeX API document generation,(2) a unit test framework,(3) automatic message and error logs,(4) HTML and LaTeX plot and table generation, and(5) several real world examples with bundled datasets available for download. For ease of use, datasets, variables and optional workflows may be specified in a flexible format configuration file. Configuration statements may specify, for example, a region and date range, and the creation of images, plots and statistical summary tables for a long list of variables. SatelliteDL enforces data provenance; all data should be traceable and reproducible. The output NetCDF file metadata holds a complete history of the original datasets and their transformations, and a method exists to reconstruct a configuration file from this information. Release 0.1.0 distributes with ingest methods for GOES, MODIS, VIIRS and CERES radiance data (L1) as well as select 2D atmosphere products (L2) such as aerosol and cloud (MODIS and VIIRS) and radiant flux (CERES). Future releases will provide ingest methods for ocean and land surface products, gridded and time averaged datasets (L3 Daily, Monthly and Yearly), and support for 3D products such as temperature and water vapor profiles. Emphasis will be on NPP Sensor, Environmental and

  2. Satellite-Based Precipitation Datasets

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    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  3. Condensing Massive Satellite Datasets For Rapid Interactive Analysis

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    Grant, G.; Gallaher, D. W.; Lv, Q.; Campbell, G. G.; Fowler, C.; LIU, Q.; Chen, C.; Klucik, R.; McAllister, R. A.

    2015-12-01

    Our goal is to enable users to interactively analyze massive satellite datasets, identifying anomalous data or values that fall outside of thresholds. To achieve this, the project seeks to create a derived database containing only the most relevant information, accelerating the analysis process. The database is designed to be an ancillary tool for the researcher, not an archival database to replace the original data. This approach is aimed at improving performance by reducing the overall size by way of condensing the data. The primary challenges of the project include: - The nature of the research question(s) may not be known ahead of time. - The thresholds for determining anomalies may be uncertain. - Problems associated with processing cloudy, missing, or noisy satellite imagery. - The contents and method of creation of the condensed dataset must be easily explainable to users. The architecture of the database will reorganize spatially-oriented satellite imagery into temporally-oriented columns of data (a.k.a., "data rods") to facilitate time-series analysis. The database itself is an open-source parallel database, designed to make full use of clustered server technologies. A demonstration of the system capabilities will be shown. Applications for this technology include quick-look views of the data, as well as the potential for on-board satellite processing of essential information, with the goal of reducing data latency.

  4. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

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    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  5. Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

    Science.gov (United States)

    Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

    2018-04-01

    Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

  6. Climatic Analysis of Oceanic Water Vapor Transports Based on Satellite E-P Datasets

    Science.gov (United States)

    Smith, Eric A.; Sohn, Byung-Ju; Mehta, Vikram

    2004-01-01

    Understanding the climatically varying properties of water vapor transports from a robust observational perspective is an essential step in calibrating climate models. This is tantamount to measuring year-to-year changes of monthly- or seasonally-averaged, divergent water vapor transport distributions. This cannot be done effectively with conventional radiosonde data over ocean regions where sounding data are generally sparse. This talk describes how a methodology designed to derive atmospheric water vapor transports over the world oceans from satellite-retrieved precipitation (P) and evaporation (E) datasets circumvents the problem of inadequate sampling. Ultimately, the method is intended to take advantage of the relatively complete and consistent coverage, as well as continuity in sampling, associated with E and P datasets obtained from satellite measurements. Independent P and E retrievals from Special Sensor Microwave Imager (SSM/I) measurements, along with P retrievals from Tropical Rainfall Measuring Mission (TRMM) measurements, are used to obtain transports by solving a potential function for the divergence of water vapor transport as balanced by large scale E - P conditions.

  7. Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2013-12-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

  8. Appraising city-scale pollution monitoring capabilities of multi-satellite datasets using portable pollutant monitors

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    Aliyu, Yahaya A.; Botai, Joel O.

    2018-04-01

    The retrieval characteristics for a city-scale satellite experiment was explored over a Nigerian city. The study evaluated carbon monoxide and aerosol contents in the city atmosphere. We utilized the MSA Altair 5× gas detector and CW-HAT200 particulate counter to investigate the city-scale monitoring capabilities of satellite pollution observing instruments; atmospheric infrared sounder (AIRS), measurement of pollution in the troposphere (MOPITT), moderate resolution imaging spectroradiometer (MODIS), multi-angle imaging spectroradiometer (MISR) and ozone monitoring instrument (OMI). To achieve this, we employed the Kriging interpolation technique to collocate the satellite pollutant estimations over 19 ground sample sites for the period of 2015-2016. The portable pollutant devices were validated using the WHO air filter sampling model. To determine the city-scale performance of the satellite datasets, performance indicators: correlation coefficient, model efficiency, reliability index and root mean square error, were adopted as measures. The comparative analysis revealed that MOPITT carbon monoxide (CO) and MODIS aerosol optical depth (AOD) estimates are the appropriate satellite measurements for ground equivalents in Zaria, Nigeria. Our findings were within the acceptable limits of similar studies that utilized reference stations. In conclusion, this study offers direction to Nigeria's air quality policy organizers about available alternative air pollution measurements for mitigating air quality effects within its limited resource environment.

  9. Improving Satellite Observation Utilization for Model Initialization with Machine Learning: An Introduction and Tackling the "Labeled Dataset" Challenge for Cyclones Around the World

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    Bonfanti, C. E.; Stewart, J.; Lee, Y. J.; Govett, M.; Trailovic, L.; Etherton, B.

    2017-12-01

    One of the National Oceanic and Atmospheric Administration (NOAA) goals is to provide timely and reliable weather forecasts to support important decisions when and where people need it for safety, emergencies, planning for day-to-day activities. Satellite data is essential for areas lacking in-situ observations for use as initial conditions in Numerical Weather Prediction (NWP) Models, such as spans of the ocean or remote areas of land. Currently only about 7% of total received satellite data is selected for use and from that, an even smaller percentage ever are assimilated into NWP models. With machine learning, the computational and time costs needed for satellite data selection can be greatly reduced. We study various machine learning approaches to process orders of magnitude more satellite data in significantly less time allowing for a greater quantity and more intelligent selection of data to be used for assimilation purposes. Given the future launches of satellites in the upcoming years, machine learning is capable of being applied for better selection of Regions of Interest (ROI) in the magnitudes more of satellite data that will be received. This paper discusses the background of machine learning methods as applied to weather forecasting and the challenges of creating a "labeled dataset" for training and testing purposes. In the training stage of supervised machine learning, labeled data are important to identify a ROI as either true or false so that the model knows what signatures in satellite data to identify. Authors have selected cyclones, including tropical cyclones and mid-latitude lows, as ROI for their machine learning purposes and created a labeled dataset of true or false for ROI from Global Forecast System (GFS) reanalysis data. A dataset like this does not yet exist and given the need for a high quantity of samples, is was decided this was best done with automation. This process was done by developing a program similar to the National Center for

  10. Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

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    Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.; hide

    2012-01-01

    Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

  11. Evaluating the Long-term Water Cycle Trends at a Global-scale using Satellite and Assimilation Datasets

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    Kim, H.; Lakshmi, V.

    2017-12-01

    Global-scale soil moisture and rainfall products retrieved from remotely sensed and assimilation datasets provide an effective way to monitor near surface soil moisture content and precipitation with sub-daily temporal resolution. In the present study, we employed the concept of the stored precipitation fraction Fp(f) in order to examine the long-term water cycle trends at a global-scale. The analysis was done for Fp(f) trends with the various geophysical aspects such as climate zone, land use classifications, amount of vegetation, and soil properties. Furthermore, we compared a global-scale Fp(f) using different microwave-based satellite soil moisture datasets. The Fp(f) is calculated by utilized surface soil moisture dataset from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity, Advanced Scatterometer, Advanced Microwave Scanning Radiometer 2, and precipitation information from Global Precipitation Measurement Mission and Global Land Data Assimilation System. Different results from microwave-based soil moisture dataset showed discordant results particularly over arid and highly vegetated regions. The results of this study provide us new insights of the long-term water cycle trends over different land surface areas. Thereby also highlighting the advantages of the recently available GPM and SMAP datasets for the uses in various hydrometeorological applications.

  12. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  13. Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

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    Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

    2017-04-01

    The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

  14. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2014-10-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

  15. The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

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    Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

    1997-01-01

    The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

  16. Fine-tuning satellite-based rainfall estimates

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    Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

    2018-05-01

    Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

  17. Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets.

    Directory of Open Access Journals (Sweden)

    Kristofer Lasko

    Full Text Available Air pollution is one of the major environmental concerns in Vietnam. In this study, we assess the current status of air pollution over Hanoi, Vietnam using multiple different satellite datasets and weather information, and assess the potential to capture rice residue burning emissions with satellite data in a cloud-covered region. We used a timeseries of Ozone Monitoring Instrument (OMI Ultraviolet Aerosol Index (UVAI satellite data to characterize absorbing aerosols related to biomass burning. We also tested a timeseries of 3-hourly MERRA-2 reanalysis Black Carbon (BC concentration data for 5 years from 2012-2016 and explored pollution trends over time. We then used MODIS active fires, and synoptic wind patterns to attribute variability in Hanoi pollution to different sources. Because Hanoi is within the Red River Delta where rice residue burning is prominent, we explored trends to see if the residue burning signal is evident in the UVAI or BC data. Further, as the region experiences monsoon-influenced rainfall patterns, we adjusted the BC data based on daily rainfall amounts. Results indicated forest biomass burning from Northwest Vietnam and Laos impacts Hanoi air quality during the peak UVAI months of March and April. Whereas, during local rice residue burning months of June and October, no increase in UVAI is observed, with slight BC increase in October only. During the peak BC months of December and January, wind patterns indicated pollutant transport from southern China megacity areas. Results also indicated severe pollution episodes during December 2013 and January 2014. We observed significantly higher BC concentrations during nighttime than daytime with peaks generally between 2130 and 0030 local time. Our results highlight the need for better air pollution monitoring systems to capture episodic pollution events and their surface-level impacts, such as rice residue burning in cloud-prone regions in general and Hanoi, Vietnam in

  18. Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES

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    M. Kopacz

    2010-02-01

    Full Text Available We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005 global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD, and aircraft (MOZAIC are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a−1. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

  19. Development and Assessment of the Sand Dust Prediction Model by Utilizing Microwave-Based Satellite Soil Moisture and Reanalysis Datasets in East Asian Desert Areas

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    Hyunglok Kim

    2017-01-01

    Full Text Available For several decades, satellite-based microwave sensors have provided valuable soil moisture monitoring in various surface conditions. We have first developed a modeled aerosol optical depth (AOD dataset by utilizing Soil Moisture and Ocean Salinity (SMOS, Advanced Microwave Scanning Radiometer 2 (AMSR2, and the Global Land Data Assimilation System (GLDAS soil moisture datasets in order to estimate dust outbreaks over desert areas of East Asia. Moderate Resolution Imaging Spectroradiometer- (MODIS- based AOD products were used as reference datasets to validate the modeled AOD (MA. The SMOS-based MA (SMOS-MA dataset showed good correspondence with observed AOD (R-value: 0.56 compared to AMSR2- and GLDAS-based MA datasets, and it overestimated AOD compared to observed AOD. The AMSR2-based MA dataset was found to underestimate AOD, and it showed a relatively low R-value (0.35 with respect to observed AOD. Furthermore, SMOS-MA products were able to simulate the short-term AOD trends, having a high R-value (0.65. The results of this study may allow us to acknowledge the utilization of microwave-based soil moisture datasets for investigation of near-real time dust outbreak predictions and short-term dust outbreak trend analysis.

  20. A reanalysis dataset of the South China Sea

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    Zeng, Xuezhi; Peng, Shiqiu; Li, Zhijin; Qi, Yiquan; Chen, Rongyu

    2014-01-01

    Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992–2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability. PMID:25977803

  1. Climate Prediction Center IR 4km Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — CPC IR 4km dataset was created from all available individual geostationary satellite data which have been merged to form nearly seamless global (60N-60S) IR...

  2. Towards a climatology of tropical cyclone morphometric structures using a newly standardized passive microwave satellite dataset

    Science.gov (United States)

    Cossuth, J.; Hart, R. E.

    2013-12-01

    storm's rainband and eyewall organization. Ultimately, this project develops a consistent climatology of TC structures using a new database of research-quality historical TC satellite microwave observations. Not only can such data sets more accurately study TC structural evolution, but they may facilitate automated TC intensity estimates and provide methods to enhance current operational and research products, such as at the NRL TC webpage (http://www.nrlmry.navy.mil/TC.html). The process of developing the dataset and possible objective definitions of TC structures using passive microwave imagery will be described, with preliminary results suggesting new methods to identify TC structures that may interrogate and expand upon physical and dynamical theories. Structural metrics such as threshold analysis of the outlines of the TC shape as well as methods to diagnose the inner-core size, completion, and magnitude will be introduced.

  3. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

    Directory of Open Access Journals (Sweden)

    H. E. Beck

    2017-12-01

    Full Text Available We undertook a comprehensive evaluation of 22 gridded (quasi-global (sub-daily precipitation (P datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( <  50 000 km2 catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7 or near-surface soil moisture (SM2RAIN-ASCAT, and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS. Two of the three reanalyses (ERA-Interim and JRA-55 unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0 generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU, which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1. Our results highlight large differences in estimation accuracy

  4. CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data

    Directory of Open Access Journals (Sweden)

    K.-G. Karlsson

    2013-05-01

    Full Text Available A new satellite-derived climate dataset – denoted CLARA-A1 ("The CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data" – is described. The dataset covers the 28 yr period from 1982 until 2009 and consists of cloud, surface albedo, and radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer sensor carried by polar-orbiting operational meteorological satellites. Its content, anticipated accuracies, limitations, and potential applications are described. The dataset is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF project. The dataset has its strengths in the long duration, its foundation upon a homogenized AVHRR radiance data record, and in some unique features, e.g. the availability of 28 yr of summer surface albedo and cloudiness parameters over the polar regions. Quality characteristics are also well investigated and particularly useful results can be found over the tropics, mid to high latitudes and over nearly all oceanic areas. Being the first CM SAF dataset of its kind, an intensive evaluation of the quality of the datasets was performed and major findings with regard to merits and shortcomings of the datasets are reported. However, the CM SAF's long-term commitment to perform two additional reprocessing events within the time frame 2013–2018 will allow proper handling of limitations as well as upgrading the dataset with new features (e.g. uncertainty estimates and extension of the temporal coverage.

  5. Using Multiple Big Datasets and Machine Learning to Produce a New Global Particulate Dataset: A Technology Challenge Case Study

    Science.gov (United States)

    Lary, D. J.

    2013-12-01

    A BigData case study is described where multiple datasets from several satellites, high-resolution global meteorological data, social media and in-situ observations are combined using machine learning on a distributed cluster using an automated workflow. The global particulate dataset is relevant to global public health studies and would not be possible to produce without the use of the multiple big datasets, in-situ data and machine learning.To greatly reduce the development time and enhance the functionality a high level language capable of parallel processing has been used (Matlab). A key consideration for the system is high speed access due to the large data volume, persistence of the large data volumes and a precise process time scheduling capability.

  6. GPM GROUND VALIDATION COMPOSITE SATELLITE OVERPASSES MC3E V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Composite Satellite Overpasses MC3E dataset provides satellite overpasses from the AQUA satellite during the Midlatitude Continental...

  7. Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

    Directory of Open Access Journals (Sweden)

    Mathias Neumann

    2016-06-01

    Full Text Available Net primary production (NPP is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country and gradients (elevation, location, tree age, dominant species, etc.. The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.

  8. Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

    Science.gov (United States)

    Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

    2018-04-01

    Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For

  9. Analysis of Specular Reflections Off Geostationary Satellites

    Science.gov (United States)

    Jolley, A.

    2016-09-01

    Many photometric studies of artificial satellites have attempted to define procedures that minimise the size of datasets required to infer information about satellites. However, it is unclear whether deliberately limiting the size of datasets significantly reduces the potential for information to be derived from them. In 2013 an experiment was conducted using a 14 inch Celestron CG-14 telescope to gain multiple night-long, high temporal resolution datasets of six geostationary satellites [1]. This experiment produced evidence of complex variations in the spectral energy distribution (SED) of reflections off satellite surface materials, particularly during specular reflections. Importantly, specific features relating to the SED variations could only be detected with high temporal resolution data. An update is provided regarding the nature of SED and colour variations during specular reflections, including how some of the variables involved contribute to these variations. Results show that care must be taken when comparing observed spectra to a spectral library for the purpose of material identification; a spectral library that uses wavelength as the only variable will be unable to capture changes that occur to a material's reflected spectra with changing illumination and observation geometry. Conversely, colour variations with changing illumination and observation geometry might provide an alternative means of determining material types.

  10. Climate Prediction Center(CPC)Infra-Red (IR) 0.5 degree Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Climate Prediction Center 0.5 degree IR dataset was created from all available individual geostationary satellite data which have been merged to form nearly seamless...

  11. Total ozone trends from 1979 to 2016 derived from five merged observational datasets - the emergence into ozone recovery

    Science.gov (United States)

    Weber, Mark; Coldewey-Egbers, Melanie; Fioletov, Vitali E.; Frith, Stacey M.; Wild, Jeannette D.; Burrows, John P.; Long, Craig S.; Loyola, Diego

    2018-02-01

    We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978-present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995-present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013-2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (˜ 1996 globally and ˜ 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 % decade-1 that are barely statistically significant at the 2σ uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 % decade-1, while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend

  12. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Directory of Open Access Journals (Sweden)

    V. Pedinotti

    2012-06-01

    Full Text Available During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002–2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA. Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong

  13. Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

    OpenAIRE

    Neumann, Mathias; Moreno, Adam; Thurnher, Christopher; Mues, Volker; Härkönen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Cardellini, Giuseppe; Thivolle-Cazat, Alain; Bronisz, Karol; Merganic, Jan; Alberdi, Iciar; Astrup, Rasmus; Mohren, Frits

    2016-01-01

    Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily g...

  14. Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

    Science.gov (United States)

    Brown, I.; Wennbom, M.

    2013-12-01

    Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors

  15. Ground-Based Global Navigation Satellite System GLONASS (GLObal NAvigation Satellite System) Combined Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GLONASS Combined Broadcast Ephemeris Data (daily files of all distinct navigation...

  16. The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

    Science.gov (United States)

    Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

    2017-12-01

    The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

  17. Sea Surface Temperature for Climate Applications: A New Dataset from the European Space Agency Climate Change Initiative

    Science.gov (United States)

    Merchant, C. J.; Hulley, G. C.

    2013-12-01

    There are many datasets describing the evolution of global sea surface temperature (SST) over recent decades -- so why make another one? Answer: to provide observations of SST that have particular qualities relevant to climate applications: independence, accuracy and stability. This has been done within the European Space Agency (ESA) Climate Change Initative (CCI) project on SST. Independence refers to the fact that the new SST CCI dataset is not derived from or tuned to in situ observations. This matters for climate because the in situ observing network used to assess marine climate change (1) was not designed to monitor small changes over decadal timescales, and (2) has evolved significantly in its technology and mix of types of observation, even during the past 40 years. The potential for significant artefacts in our picture of global ocean surface warming is clear. Only by having an independent record can we confirm (or refute) that the work done to remove biases/trend artefacts in in-situ datasets has been successful. Accuracy is the degree to which SSTs are unbiased. For climate applications, a common accuracy target is 0.1 K for all regions of the ocean. Stability is the degree to which the bias, if any, in a dataset is constant over time. Long-term instability introduces trend artefacts. To observe trends of the magnitude of 'global warming', SST datasets need to be stable to <5 mK/year. The SST CCI project has produced a satellite-based dataset that addresses these characteristics relevant to climate applications. Satellite radiances (brightness temperatures) have been harmonised exploiting periods of overlapping observations between sensors. Less well-characterised sensors have had their calibration tuned to that of better characterised sensors (at radiance level). Non-conventional retrieval methods (optimal estimation) have been employed to reduce regional biases to the 0.1 K level, a target violated in most satellite SST datasets. Models for

  18. Operational use of open satellite data for marine water quality monitoring

    Science.gov (United States)

    Symeonidis, Panagiotis; Vakkas, Theodoros

    2017-09-01

    The purpose of this study was to develop an operational platform for marine water quality monitoring using near real time satellite data. The developed platform utilizes free and open satellite data available from different data sources like COPERNICUS, the European Earth Observation Initiative, or NASA, from different satellites and instruments. The quality of the marine environment is operationally evaluated using parameters like chlorophyll-a concentration, water color and Sea Surface Temperature (SST). For each parameter, there are more than one dataset available, from different data sources or satellites, to allow users to select the most appropriate dataset for their area or time of interest. The above datasets are automatically downloaded from the data provider's services and ingested to the central, spatial engine. The spatial data platform uses the Postgresql database with the PostGIS extension for spatial data storage and Geoserver for the provision of the spatial data services. The system provides daily, 10 days and monthly maps and time series of the above parameters. The information is provided using a web client which is based on the GET SDI PORTAL, an easy to use and feature rich geospatial visualization and analysis platform. The users can examine the temporal variation of the parameters using a simple time animation tool. In addition, with just one click on the map, the system provides an interactive time series chart for any of the parameters of the available datasets. The platform can be offered as Software as a Service (SaaS) to any area in the Mediterranean region.

  19. Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel

    OpenAIRE

    Stubenrauch , C.J.; Rossow , W.B.; Kinne , S.; Ackerman , S.; Cesana , G.; Chepfer , H.; Di Girolamo , L.; Getzewich , B.; Guignard , A.; Heidinger , A.; Maddux , B.C.; Menzel , W.P.; Minnis , P.; Pearl , C.; Platnick , S.

    2013-01-01

    International audience; The Global Energy and Water Cycle Experiment (GEWEX) Radiation Panel initiated the GEWEX Cloud Assessment in 2005 to compare available, global, long-term cloud data products with the International Satellite Cloud Climatology Project (ISCCP). The GEWEX Cloud Assessment database included cloud properties retrieved from different satellite sensor measurements, taken at various local times and over various time periods. The relevant passive satellite sensors measured radia...

  20. Operational Satellite-based Surface Oil Analyses (Invited)

    Science.gov (United States)

    Streett, D.; Warren, C.

    2010-12-01

    During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as

  1. GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS LPVEX V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Satellite Simulated Orbits LPVEx dataset is available in the Orbital database, which takes account for the atmospheric profiles, the...

  2. Ground-Based Global Navigation Satellite System (GNSS) GLONASS Broadcast Ephemeris Data (hourly files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GLObal NAvigation Satellite System (GLONASS) Broadcast Ephemeris Data (hourly files)...

  3. GLEAM version 3: Global Land Evaporation Datasets and Model

    Science.gov (United States)

    Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

    2015-12-01

    Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

  4. Dynamic interactions of the cortical networks during thought suppression.

    Science.gov (United States)

    Aso, Toshihiko; Nishimura, Kazuo; Kiyonaka, Takashi; Aoki, Takaaki; Inagawa, Michiyo; Matsuhashi, Masao; Tobinaga, Yoshikazu; Fukuyama, Hidenao

    2016-08-01

    Thought suppression has spurred extensive research in clinical and preclinical fields, particularly with regard to the paradoxical aspects of this behavior. However, the involvement of the brain's inhibitory system in the dynamics underlying the continuous effort to suppress thoughts has yet to be clarified. This study aims to provide a unified perspective for the volitional suppression of internal events incorporating the current understanding of the brain's inhibitory system. Twenty healthy volunteers underwent functional magnetic resonance imaging while they performed thought suppression blocks alternating with visual imagery blocks. The whole dataset was decomposed by group-independent component analysis into 30 components. After discarding noise components, the 20 valid components were subjected to further analysis of their temporal properties including task-relatedness and between-component residual correlation. Combining a long task period and a data-driven approach, we observed a right-side-dominant, lateral frontoparietal network to be strongly suppression related. This network exhibited increased fluctuation during suppression, which is compatible with the well-known difficulty of suppression maintenance. Between-network correlation provided further insight into the coordinated engagement of the executive control and dorsal attention networks, as well as the reciprocal activation of imagery-related components, thus revealing neural substrates associated with the rivalry between intrusive thoughts and the suppression process.

  5. Access NASA Satellite Global Precipitation Data Visualization on YouTube

    Science.gov (United States)

    Liu, Z.; Su, J.; Acker, J. G.; Huffman, G. J.; Vollmer, B.; Wei, J.; Meyer, D. J.

    2017-12-01

    Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. Satellite data at 12 NASA data centers can also be used for STEM activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programing languages, etc. Over the years, many efforts have been developed to improve satellite data access, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses the popular online video sharing web site, YouTube, to access visualization of global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without necessity to learn new software or download data. The dataset in this activity is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA). The video consists of over 50,000 data files collected since 1998 onwards, covering a zone between 50°N-S. The YouTube video will last 36 minutes for the entire dataset record (over 19 years). Since the time stamp is on each frame of the video, users can begin at any time by dragging the time progress bar. This precipitation animation will allow viewing precipitation events and processes (e.g., hurricanes, fronts, atmospheric rivers, etc.) on a global scale. The next plan is to develop a similar animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellitE Retrievals for GPM (IMERG). The IMERG provides precipitation on a near-global (60°N-S) coverage at half-hourly time interval, showing more details on precipitation processes and development, compared to the 3

  6. VIIRS satellite and ground pm2.5 monitoring data

    Data.gov (United States)

    U.S. Environmental Protection Agency — contains all satellite, pm2.5, and meteorological data used in statistical modeling effort to improve prediction of pm2.5. This dataset is associated with the...

  7. Global heating distributions for January 1979 calculated from GLA assimilated and simulated model-based datasets

    Science.gov (United States)

    Schaack, Todd K.; Lenzen, Allen J.; Johnson, Donald R.

    1991-01-01

    This study surveys the large-scale distribution of heating for January 1979 obtained from five sources of information. Through intercomparison of these distributions, with emphasis on satellite-derived information, an investigation is conducted into the global distribution of atmospheric heating and the impact of observations on the diagnostic estimates of heating derived from assimilated datasets. The results indicate a substantial impact of satellite information on diagnostic estimates of heating in regions where there is a scarcity of conventional observations. The addition of satellite data provides information on the atmosphere's temperature and wind structure that is important for estimation of the global distribution of heating and energy exchange.

  8. GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS TWP-ICE V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Satellite Simulated Orbits TWP-ICE dataset is available in the Orbital database, which takes account for the atmospheric profiles, the...

  9. Decision tree approach for classification of remotely sensed satellite

    Indian Academy of Sciences (India)

    DTC) algorithm for classification of remotely sensed satellite data (Landsat TM) using open source support. The decision tree is constructed by recursively partitioning the spectral distribution of the training dataset using WEKA, open source ...

  10. CHARMe Commentary metadata for Climate Science: collecting, linking and sharing user feedback on climate datasets

    Science.gov (United States)

    Blower, Jon; Lawrence, Bryan; Kershaw, Philip; Nagni, Maurizio

    2014-05-01

    The research process can be thought of as an iterative activity, initiated based on prior domain knowledge, as well on a number of external inputs, and producing a range of outputs including datasets, studies and peer reviewed publications. These outputs may describe the problem under study, the methodology used, the results obtained, etc. In any new publication, the author may cite or comment other papers or datasets in order to support their research hypothesis. However, as their work progresses, the researcher may draw from many other latent channels of information. These could include for example, a private conversation following a lecture or during a social dinner; an opinion expressed concerning some significant event such as an earthquake or for example a satellite failure. In addition, other sources of information of grey literature are important public such as informal papers such as the arxiv deposit, reports and studies. The climate science community is not an exception to this pattern; the CHARMe project, funded under the European FP7 framework, is developing an online system for collecting and sharing user feedback on climate datasets. This is to help users judge how suitable such climate data are for an intended application. The user feedback could be comments about assessments, citations, or provenance of the dataset, or other information such as descriptions of uncertainty or data quality. We define this as a distinct category of metadata called Commentary or C-metadata. We link C-metadata with target climate datasets using a Linked Data approach via the Open Annotation data model. In the context of Linked Data, C-metadata plays the role of a resource which, depending on its nature, may be accessed as simple text or as more structured content. The project is implementing a range of software tools to create, search or visualize C-metadata including a JavaScript plugin enabling this functionality to be integrated in situ with data provider portals

  11. Using NASA Satellite Aerosol Optical Depth to Enhance PM2.5 Concentration Datasets for Use in Human Health and Epidemiology Studies

    Science.gov (United States)

    Huff, A. K.; Weber, S.; Braggio, J.; Talbot, T.; Hall, E.

    2012-12-01

    Fine particulate matter (PM2.5) is a criterion air pollutant, and its adverse impacts on human health are well established. Traditionally, studies that analyze the health effects of human exposure to PM2.5 use concentration measurements from ground-based monitors and predicted PM2.5 concentrations from air quality models, such as the U.S. EPA's Community Multi-scale Air Quality (CMAQ) model. There are shortcomings associated with these datasets, however. Monitors are not distributed uniformly across the U.S., which causes spatially inhomogeneous measurements of pollutant concentrations. There are often temporal variations as well, since not all monitors make daily measurements. Air quality model output, while spatially and temporally uniform, represents predictions of PM2.5 concentrations, not actual measurements. This study is exploring the potential of combining Aerosol Optical Depth (AOD) data from the MODIS instrument on NASA's Terra and Aqua satellites with PM2.5 monitor data and CMAQ predictions to create PM2.5 datasets that more accurately reflect the spatial and temporal variations in ambient PM2.5 concentrations on the metropolitan scale, with the overall goal of enhancing capabilities for environmental public health decision-making. AOD data provide regional information about particulate concentrations that can fill in the spatial and temporal gaps in the national PM2.5 monitor network. Furthermore, AOD is a measurement, so it reflects actual concentrations of particulates in the atmosphere, in contrast to PM2.5 predictions from air quality models. Results will be presented from the Battelle/U.S. EPA statistical Hierarchical Bayesian Model (HBM), which was used to combine three PM2.5 concentration datasets: monitor measurements, AOD data, and CMAQ model predictions. The study is focusing on the Baltimore, MD and New York City, NY metropolitan regions for the period 2004-2006. For each region, combined monitor/AOD/CMAQ PM2.5 datasets generated by the HBM

  12. Creating a regional MODIS satellite-driven net primary production dataset for european forests

    NARCIS (Netherlands)

    Neumann, Mathias; Moreno, Adam; Thurnher, Christopher; Mues, Volker; Härkönen, Sanna; Mura, Matteo; Bouriaud, Olivier; Lang, Mait; Cardellini, Giuseppe; Thivolle-Cazat, Alain; Bronisz, Karol; Merganic, Jan; Alberdi, Iciar; Astrup, Rasmus; Mohren, Frits; Zhao, Maosheng; Hasenauer, Hubert

    2016-01-01

    Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm

  13. Capture of irregular satellites at Jupiter

    International Nuclear Information System (INIS)

    Nesvorný, David; Vokrouhlický, David; Deienno, Rogerio

    2014-01-01

    The irregular satellites of outer planets are thought to have been captured from heliocentric orbits. The exact nature of the capture process, however, remains uncertain. We examine the possibility that irregular satellites were captured from the planetesimal disk during the early solar system instability when encounters between the outer planets occurred. Nesvorný et al. already showed that the irregular satellites of Saturn, Uranus, and Neptune were plausibly captured during planetary encounters. Here we find that the current instability models present favorable conditions for capture of irregular satellites at Jupiter as well, mainly because Jupiter undergoes a phase of close encounters with an ice giant. We show that the orbital distribution of bodies captured during planetary encounters provides a good match to the observed distribution of irregular satellites at Jupiter. The capture efficiency for each particle in the original transplanetary disk is found to be (1.3-3.6) × 10 –8 . This is roughly enough to explain the observed population of jovian irregular moons. We also confirm Nesvorný et al.'s results for the irregular satellites of Saturn, Uranus, and Neptune.

  14. Early life predictors of adolescent suicidal thoughts and adverse outcomes in two population-based cohort studies.

    Directory of Open Access Journals (Sweden)

    Jennifer Dykxhoorn

    Full Text Available Understanding suicidality has proven challenging given the complex aetiology in early childhood. Being able to accurately predict groups at increased risk of developing suicidal thoughts may aid in the development of targeted prevention programs that mitigate increased vulnerability. Further, the predictors of suicidal thoughts may be shared with other outcomes in adolescence. Previous research has linked many factors to suicidality, so the objective of this study was to consider how these factors may act together to increase risk of suicidal thoughts and other non-mental health outcomes.Two longitudinal datasets were used in this analysis: the National Longitudinal Survey of Children and Youth (NLSCY and the Avon Longitudinal Survey of Parents and Children (ALSPAC. A Classification and Regression Tree model comprised of 75 factors describing early childhood was constructed to identify subgroups of adolescents at high risk of suicidal thoughts in the NLSCY and was validated in ALSPAC. These subgroups were investigated to see if they also had elevated rates of antisocial behaviour, substance misuse, poor physical health, poor mental health, risky health behaviours, and/or poor academic performance.The sensitivity was calculated to be 22·7%, specificity was 89·2%, positive predictive value 17·8%, and negative predictive value 91·8% and had similar accuracy in the validation dataset. The models were better at predicting other adverse outcomes compared to suicidal thoughts.There are groups of risk factors present in early life that can predict higher risk of suicidality in adolescence. Notably, these factors were also predictive of a range of adverse outcomes in adolescence.

  15. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  16. A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

    Directory of Open Access Journals (Sweden)

    N. M. Velpuri

    2012-01-01

    Full Text Available Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE of 0.80 during the validation period (2004–2009. Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated

  17. GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS C3VP V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Satellite Simulated Orbits C3VP dataset is available in the Orbital database, which takes account for the atmospheric profiles, the...

  18. GPM GROUND VALIDATION SATELLITE SIMULATED ORBITS MC3E V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation Satellite Simulated Orbits MC3E dataset is available in the Orbital database , which takes account for the atmospheric profiles, the...

  19. Description of Simulated Small Satellite Operation Data Sets

    Science.gov (United States)

    Kulkarni, Chetan S.; Guarneros Luna, Ali

    2018-01-01

    A set of two BP930 batteries (Identified as PK31 and PK35) were operated continuously for a simulated satellite operation profile completion for single cycle. The battery packs were charged to an initial voltage of around 8.35 V for 100% SOC before the experiment was started. This document explains the structure of the battery data sets. Please cite this paper when using this dataset: Z. Cameron, C. Kulkarni, A. Guarneros, K. Goebel, S. Poll, "A Battery Certification Testbed for Small Satellite Missions", IEEE AUTOTESTCON 2015, Nov 2-5, 2015, National Harbor, MA

  20. Global distribution of pauses observed with satellite measurements

    Indian Academy of Sciences (India)

    Here we study the commonality and differences observed in the variability of all the pauses. We also examined how good other datasets will represent these features among (and in between) different satellite measurements, re-analysis, and model data. Hemispheric differences observed in all the pauses are also reported.

  1. Technique for Geolocation of EMI Emitters by O3B Satellites

    Science.gov (United States)

    2016-06-01

    Communication Systems: An Introduction to Signals and Noise in Electrical Communications , 5th edition (New York: McGraw -Hill, 2011), 4. 6 system to...the only one caused by humans , that will be our focus—the others can be thought of as the cost of doing business in satellite communications and can...SATELLITE COMMUNICATIONS OVERVIEW ...............................2  B.  EMI AND JAMMING OVERVIEW .......................................................5

  2. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Yearly Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  3. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Seasonal Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  4. SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    A. Sharma

    2015-03-01

    Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

  5. Development and field testing of satellite-linked fluorometers for marine mammals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset includes telemetry data related to the development and testing of an animal-borne satellite-linked fluorometer tag, used on northern fur seals and...

  6. Solar resource assessment in complex orography: a comparison of available datasets for the Trentino region

    Science.gov (United States)

    Laiti, Lavinia; Giovannini, Lorenzo; Zardi, Dino

    2015-04-01

    The accurate assessment of the solar radiation available at the Earth's surface is essential for a wide range of energy-related applications, such as the design of solar power plants, water heating systems and energy-efficient buildings, as well as in the fields of climatology, hydrology, ecology and agriculture. The characterization of solar radiation is particularly challenging in complex-orography areas, where topographic shadowing and altitude effects, together with local weather phenomena, greatly increase the spatial and temporal variability of such variable. At present, approaches ranging from surface measurements interpolation to orographic down-scaling of satellite data, to numerical model simulations are adopted for mapping solar radiation. In this contribution a high-resolution (200 m) solar atlas for the Trentino region (Italy) is presented, which was recently developed on the basis of hourly observations of global radiation collected from the local radiometric stations during the period 2004-2012. Monthly and annual climatological irradiation maps were obtained by the combined use of a GIS-based clear-sky model (r.sun module of GRASS GIS) and geostatistical interpolation techniques (kriging). Moreover, satellite radiation data derived by the MeteoSwiss HelioMont algorithm (2 km resolution) were used for missing-data reconstruction and for the final mapping, thus integrating ground-based and remote-sensing information. The results are compared with existing solar resource datasets, such as the PVGIS dataset, produced by the Joint Research Center Institute for Energy and Transport, and the HelioMont dataset, in order to evaluate the accuracy of the different datasets available for the region of interest.

  7. A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

    Science.gov (United States)

    Velpuri, N.M.; Senay, G.B.; Asante, K.O.

    2012-01-01

    Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance

  8. How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

    Science.gov (United States)

    Jiang, C.; Ryu, Y.; Fang, H.

    2016-12-01

    Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

  9. Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

    Directory of Open Access Journals (Sweden)

    A. Loew

    2013-09-01

    Full Text Available Soil moisture is an essential climate variable (ECV of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture. The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

  10. First thoughts on MD priorities for 2012

    CERN Document Server

    Zimmermann, F; Assmann, R

    2012-01-01

    In 2012, 22 days of beam time will be allocated for LHC MDs. In this paper, after recalling the 2011 LHC MD experience, the MD rrequests for 2012 are reviewed. Three primary MD themes for 2012 can be identified: 1)pushing performance in 2012, 2)preparing for 2014/15, and 3)towards maximum luminosity. Example topics include emittance growth in collision or enhanced satellites for theme 1), 25 ns operation for 2), and ATS optics for 3). Structures lists of MD requests and topics for each theme as well as some initial thoughts on the MD priorities are presented. For certain topics, "start-of-fill MDs" are proposed in order to most efficiently use of the available beam time.

  11. Orbits of the inner satellites of Neptune

    Science.gov (United States)

    Brozovic, Marina; Showalter, Mark R.; Jacobson, Robert Arthur; French, Robert S.; de Pater, Imke; Lissauer, Jack

    2018-04-01

    We report on the numerically integrated orbits of seven inner satellites of Neptune, including S/2004 N1, the last moon of Neptune to be discovered by the Hubble Space Telescope (HST). The dataset includes Voyager imaging data as well as the HST and Earth-based astrometric data. The observations span time period from 1989 to 2016. Our orbital model accounts for the equatorial bulge of Neptune, perturbations from the Sun and the planets, and perturbations from Triton. The initial orbital integration assumed that the satellites are massless, but the residuals improved significantly as the masses adjusted toward values that implied that the density of the satellites is in the realm of 1 g/cm3. We will discuss how the integrated orbits compare to the precessing ellipses fits, mean orbital elements, current orbital uncertainties, and the need for future observations.

  12. Evolving hard problems: Generating human genetics datasets with a complex etiology

    Directory of Open Access Journals (Sweden)

    Himmelstein Daniel S

    2011-07-01

    Full Text Available Abstract Background A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Results Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. Conclusions This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

  13. USGS HYDRoacoustic dataset in support of the Surface Water Oceanographic Topography satellite mission (HYDRoSWOT)

    Data.gov (United States)

    Department of the Interior — HYDRoSWOT – HYDRoacoustic dataset in support of Surface Water Oceanographic Topography – is a data set that aggregates channel and flow data collected from the USGS...

  14. Handbook of satellite orbits from Kepler to GPS

    CERN Document Server

    Capderou, Michel

    2014-01-01

    Fifty years after Sputnik, artificial satellites have become indispensable monitors in many areas, such as economics, meteorology, telecommunications, navigation and remote sensing. The specific orbits are important for the proper functioning of the satellites. This book discusses the great variety of satellite orbits, both in shape (circular to highly elliptical) and properties (geostationary, Sun-synchronous, etc.). This volume starts with an introduction into geodesy. This is followed by a presentation of the fundamental equations of mechanics to explain and demonstrate the properties for all types of orbits. Numerous examples are included, obtained through IXION software developed by the author. The book also includes an exposition of the historical background that is necessary to help the reader understand the main stages of scientific thought from Kepler to GPS. This book is intended for researchers, teachers and students working in the field of satellite technology. Engineers, geographers and all those...

  15. Using kittens to unlock photo-sharing website datasets for environmental applications

    Science.gov (United States)

    Gascoin, Simon

    2016-04-01

    Mining photo-sharing websites is a promising approach to complement in situ and satellite observations of the environment, however a challenge is to deal with the large degree of noise inherent to online social datasets. Here I explored the value of the Flickr image hosting website database to monitor the snow cover in the Pyrenees. Using the Flickr application programming interface (API) I queried all the public images metadata tagged at least with one of the following words: "snow", "neige", "nieve", "neu" (snow in French, Spanish and Catalan languages). The search was limited to the geo-tagged pictures taken in the Pyrenees area. However, the number of public pictures available in the Flickr database for a given time interval depends on several factors, including the Flickr website popularity and the development of digital photography. Thus, I also searched for all Flickr images tagged with "chat", "gat" or "gato" (cat in French, Spanish and Catalan languages). The tag "cat" was not considered in order to exclude the results from North America where Flickr got popular earlier than in Europe. The number of "cat" images per month was used to fit a model of the number of images uploaded in Flickr with time. This model was used to remove this trend in the numbers of snow-tagged photographs. The resulting time series was compared to a time series of the snow cover area derived from the MODIS satellite over the same region. Both datasets are well correlated; in particular they exhibit the same seasonal evolution, although the inter-annual variabilities are less similar. I will also discuss which other factors may explain the main discrepancies in order to further decrease the noise in the Flickr dataset.

  16. Assessment of Wind Datasets for Estimating Offshore Wind Energy along the Central California Coast

    Science.gov (United States)

    Wang, Y. H.; Walter, R. K.; Ruttenberg, B.; White, C.

    2017-12-01

    Offshore renewable energy along the central California coastline has gained significant interest in recent years. We present a comprehensive analysis of near-surface wind datasets available in this region to facilitate future estimates of wind power generation potential. The analyses are based on local NDBC buoys, satellite-based measurements (QuickSCAT and CCMP V2.0), reanalysis products (NARR and MERRA), and a regional climate model (WRF). There are substantial differences in the diurnal signal during different months among the various products (i.e., satellite-based, reanalysis, and modeled) relative to the local buoys. Moreover, the datasets tended to underestimate wind speed under light wind conditions and overestimate under strong wind conditions. In addition to point-to-point comparisons against local buoys, the spatial variations of bias and error in both the reanalysis products and WRF model data in this region were compared against satellite-based measurements. NARR's bias and root-mean-square-error were generally small in the study domain and decreased with distance from coastlines. Although its smaller spatial resolution is likely to be insufficient to reveal local effects, the small bias and error in near-surface winds, as well as the availability of wind data at the proposed turbine hub heights, suggests that NARR is an ideal candidate for use in offshore wind energy production estimates along the central California coast. The framework utilized here could be applied in other site-specific regions where offshore renewable energy is being considered.

  17. Towards Improved Satellite-In Situ Oceanographic Data Interoperability and Associated Value Added Services at the Podaac

    Science.gov (United States)

    Tsontos, V. M.; Huang, T.; Holt, B.

    2015-12-01

    The earth science enterprise increasingly relies on the integration and synthesis of multivariate datasets from diverse observational platforms. NASA's ocean salinity missions, that include Aquarius/SAC-D and the SPURS (Salinity Processes in the Upper Ocean Regional Study) field campaign, illustrate the value of integrated observations in support of studies on ocean circulation, the water cycle, and climate. However, the inherent heterogeneity of resulting data and the disparate, distributed systems that serve them complicates their effective utilization for both earth science research and applications. Key technical interoperability challenges include adherence to metadata and data format standards that are particularly acute for in-situ data and the lack of a unified metadata model facilitating archival and integration of both satellite and oceanographic field datasets. Here we report on efforts at the PO.DAAC, NASA's physical oceanographic data center, to extend our data management and distribution support capabilities for field campaign datasets such as those from SPURS. We also discuss value-added services, based on the integration of satellite and in-situ datasets, which are under development with a particular focus on DOMS. The distributed oceanographic matchup service (DOMS) implements a portable technical infrastructure and associated web services that will be broadly accessible via the PO.DAAC for the dynamic collocation of satellite and in-situ data, hosted by distributed data providers, in support of mission cal/val, science and operational applications.

  18. Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

    Science.gov (United States)

    Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; hide

    2015-01-01

    Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

  19. Anti-jamming Technology in Small Satellite Communication

    Science.gov (United States)

    Jia, Zixiang

    2018-01-01

    Small satellite communication has an increasingly important position among the wireless communications due to the advantages of low cost and high technology. However, in view of the case that its relay station stays outside the earth, its uplink may face interference from malicious signal frequently. Here this paper classified enumerates existing interferences, and proposes channel signals as main interference by comparison. Based on a basic digital communication process, then this paper discusses the possible anti - jamming techniques that commonly be realized at all stages in diverse processes, and comes to the conclusion that regarding the spread spectrum technology and antenna anti-jamming technology as fundamental direction of future development. This work provides possible thought for the design of new small satellite communication system with the coexistence of multi - technologies. This basic popular science can be consulted for people interested in small satellite communication.

  20. A Novel Technique for Time-Centric Analysis of Massive Remotely-Sensed Datasets

    Directory of Open Access Journals (Sweden)

    Glenn E. Grant

    2015-04-01

    Full Text Available Analyzing massive remotely-sensed datasets presents formidable challenges. The volume of satellite imagery collected often outpaces analytical capabilities, however thorough analyses of complete datasets may provide new insights into processes that would otherwise be unseen. In this study we present a novel, object-oriented approach to storing, retrieving, and analyzing large remotely-sensed datasets. The objective is to provide a new structure for scalable storage and rapid, Internet-based analysis of climatology data. The concept of a “data rod” is introduced, a conceptual data object that organizes time-series information into a temporally-oriented vertical column at any given location. To demonstrate one possible use, we ingest 25 years of Greenland imagery into a series of pure-object databases, then retrieve and analyze the data. The results provide a basis for evaluating the database performance and scientific analysis capabilities. The project succeeds in demonstrating the effectiveness of the prototype database architecture and analysis approach, not because new scientific information is discovered, but because quality control issues are revealed in the source data that had gone undetected for years.

  1. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-05-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks.

  2. Exploring thought leadership, thought liberation and critical ...

    African Journals Online (AJOL)

    It is argued that any discussion of Africa's social and economic development has to take into account the three critical issues that remain pressing constraints for the further advancement of well-being in Africa: thought leadership, thought liberation and critical consciousness. These three 'ingredients' should anchor aspects ...

  3. The Added Utility of Hydrological Model and Satellite Based Datasets in Agricultural Drought Analysis over Turkey

    Science.gov (United States)

    Bulut, B.; Hüsami Afşar, M.; Yilmaz, M. T.

    2017-12-01

    Analysis of agricultural drought, which causes substantial socioeconomically costs in Turkey and in the world, is critical in terms of understanding this natural disaster's characteristics (intensity, duration, influence area) and research on possible precautions. Soil moisture is one of the most important parameters which is used to observe agricultural drought, can be obtained using different methods. The most common, consistent and reliable soil moisture datasets used for large scale analysis are obtained from hydrologic models and remote sensing retrievals. On the other hand, Normalized difference vegetation index (NDVI) and gauge based precipitation observations are also commonly used for drought analysis. In this study, soil moisture products obtained from different platforms, NDVI and precipitation datasets over several different agricultural regions under various climate conditions in Turkey are obtained in growth season period. These datasets are later used to investigate agricultural drought by the help of annual crop yield data of selected agricultural lands. The type of vegetation over these regions are obtained using CORINE Land Cover (CLC 2012) data. The crop yield data were taken from the record of related district's statistics which is provided by Turkish Statistical Institute (TÜİK). This project is supported by TÜBİTAK project number 114Y676.

  4. Arctic sea-level reconstruction analysis using recent satellite altimetry

    DEFF Research Database (Denmark)

    Svendsen, Peter Limkilde; Andersen, Ole Baltazar; Nielsen, Allan Aasbjerg

    2014-01-01

    We present a sea-level reconstruction for the Arctic Ocean using recent satellite altimetry data. The model, forced by historical tide gauge data, is based on empirical orthogonal functions (EOFs) from a calibration period; for this purpose, newly retracked satellite altimetry from ERS-1 and -2...... and Envisat has been used. Despite the limited coverage of these datasets, we have made a reconstruction up to 82 degrees north for the period 1950–2010. We place particular emphasis on determining appropriate preprocessing for the tide gauge data, and on validation of the model, including the ability...

  5. Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data

    Science.gov (United States)

    Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

    2011-01-01

    nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.

  6. Asian Dust Weather Categorization with Satellite and Surface Observations

    Science.gov (United States)

    Lin, Tang-Huang; Hsu, N. Christina; Tsay, Si-Chee; Huang, Shih-Jen

    2011-01-01

    This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with China s weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

  7. Ground-Based Global Navigation Satellite System Combined Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) Combined Broadcast Ephemeris Data (daily files of all distinct navigation messages...

  8. Evaluation of the Precision of Satellite-Derived Sea Surface Temperature Fields

    Science.gov (United States)

    Wu, F.; Cornillon, P. C.; Guan, L.

    2016-02-01

    A great deal of attention has been focused on the temporal accuracy of satellite-derived sea surface temperature (SST) fields with little attention being given to their spatial precision. Specifically, the primary measure of the quality of SST fields has been the bias and variance of selected values minus co-located (in space and time) in situ values. Contributing values, determined by the location of the in situ values and the necessity that the satellite-derived values be cloud free, are generally widely separated in space and time hence provide little information related to the pixel-to-pixel uncertainty in the retrievals. But the main contribution to the uncertainty in satellite-derived SST retrievals relates to atmospheric contamination and because the spatial scales of atmospheric features are, in general, large compared with the pixel separation of modern infra-red sensors, the pixel-to-pixel uncertainty is often smaller than the accuracy determined from in situ match-ups. This makes selection of satellite-derived datasets for the study of submesoscale processes, for which the spatial structure of the upper ocean is significant, problematic. In this presentation we present a methodology to characterize the spatial precision of satellite-derived SST fields. The method is based on an examination of the high wavenumber tail of the 2-D spectrum of SST fields in the Sargasso Sea, a low energy region of the ocean close to the track of the MV Oleander, a container ship making weekly roundtrips between New York and Bermuda, with engine intake temperatures sampled every 75 m along track. Important spectral characteristics are the point at which the satellite-derived spectra separate from the Oleander spectra and the spectral slope following separation. In this presentation a number of high resolution 375 m to 10 km SST datasets are evaluated based on this approach.

  9. Thought 2 Talk

    DEFF Research Database (Denmark)

    Hendricks, Vincent F.

    Thought2Talk is a crash course on argument, reasoning and logical method honoring the Swedish poet and Bishop of Lund, Esaias Tegnér, who once said: The words and thoughts of men are born together: To speak obscurely is to think obscurely. In 100 humorous yet erudite pages, Thought2Talk takes the...... the reader through key concepts like statement, argument, validity, fallacy, modality and demonstration.......Thought2Talk is a crash course on argument, reasoning and logical method honoring the Swedish poet and Bishop of Lund, Esaias Tegnér, who once said: The words and thoughts of men are born together: To speak obscurely is to think obscurely. In 100 humorous yet erudite pages, Thought2Talk takes...

  10. MSWEP : 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

    NARCIS (Netherlands)

    Beck, Hylke E.; Van Dijk, Albert I.J.M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; De Roo, Ad

    2017-01-01

    Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial

  11. Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

    Science.gov (United States)

    Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

    2016-12-01

    Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

  12. Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

    Science.gov (United States)

    Besha, A. A.; Steele, C. M.; Fernald, A.

    2014-12-01

    Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

  13. Global distribution of urban parameters derived from high-resolution global datasets for weather modelling

    Science.gov (United States)

    Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.

    2016-12-01

    Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a

  14. Evaluating the use of different precipitation datasets in simulating a flood event

    Science.gov (United States)

    Akyurek, Z.; Ozkaya, A.

    2016-12-01

    Floods caused by convective storms in mountainous regions are sensitive to the temporal and spatial variability of rainfall. Space-time estimates of rainfall from weather radar, satellites and numerical weather prediction models can be a remedy to represent pattern of the rainfall with some inaccuracy. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study aims to provide a comparison of gauge, radar, satellite (Hydro-Estimator (HE)) and numerical weather prediciton model (Weather Research and Forecasting (WRF)) precipitation datasets during an extreme flood event (22.11.2014) lasting 40 hours in Samsun-Turkey. For this study, hourly rainfall data from 13 ground observation stations were used in the analyses. This event having a peak discharge of 541 m3/sec created flooding at the downstream of Terme Basin. Comparisons were performed in two parts. First the analysis were performed in areal and point based manner. Secondly, a semi-distributed hydrological model was used to assess the accuracy of the rainfall datasets to simulate river flows for the flood event. Kalman Filtering was used in the bias correction of radar rainfall data compared to gauge measurements. Radar, gauge, corrected radar, HE and WRF rainfall data were used as model inputs. Generally, the HE product underestimates the cumulative rainfall amounts in all stations, radar data underestimates the results in cumulative sense but keeps the consistency in the results. On the other hand, almost all stations in WRF mean statistics computations have better results compared to the HE product but worse than the radar dataset. Results in point comparisons indicated that, trend of the rainfall is captured by the radar rainfall estimation well but radar underestimates the maximum values. According to cumulative gauge value, radar underestimated the cumulative rainfall amount by % 32. Contrary to other datasets, the bias of WRF is positive

  15. Error characterisation of global active and passive microwave soil moisture datasets

    Directory of Open Access Journals (Sweden)

    W. A. Dorigo

    2010-12-01

    Full Text Available Understanding the error structures of remotely sensed soil moisture observations is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available datasets is often hampered by the limited availability over space and time of reliable in-situ measurements. As an alternative, this study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT and passive (AMSR-E and SSM/I microwave sensors. The triple collocation is a powerful statistical tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three linearly related data sources with independent error structures. Prerequisite for this technique is the availability of a sufficiently large number of timely corresponding observations. In addition to the active and passive satellite-based datasets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture datasets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active, the use of different frequencies (C-, X-, and Ku-band for passive microwave observations, and the choice of the independent reference dataset (ERA-Interim versus GLDAS-NOAH. The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different

  16. Global High Resolution Sea Surface Flux Parameters From Multiple Satellites

    Science.gov (United States)

    Zhang, H.; Reynolds, R. W.; Shi, L.; Bates, J. J.

    2007-05-01

    datasets are constructed using co-located AMSU and buoy/ship data. Using the 2002 one-year data we will show that the RMSE for Ta is about 1.94°C. Data description, visualization, sub-setting and downloading in user preferred formats can be obtained at: http:nomads.ncdc.noaa.gov:8085/las/servlets/dataset; ftp:eclipse.ncdc.noaa.gov/pub; and http:www.ncdc.noaa.gov/oa/satellite.html.

  17. Ground-Based Global Navigation Satellite System (GNSS) GPS Broadcast Ephemeris Data (daily files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) GPS Broadcast Ephemeris Data (daily files) from the NASA Crustal Dynamics Data...

  18. Soil moisture datasets at five sites in the central Sierra Nevada and northern Coast Ranges, California

    Science.gov (United States)

    Stern, Michelle A.; Anderson, Frank A.; Flint, Lorraine E.; Flint, Alan L.

    2018-05-03

    In situ soil moisture datasets are important inputs used to calibrate and validate watershed, regional, or statewide modeled and satellite-based soil moisture estimates. The soil moisture dataset presented in this report includes hourly time series of the following: soil temperature, volumetric water content, water potential, and total soil water content. Data were collected by the U.S. Geological Survey at five locations in California: three sites in the central Sierra Nevada and two sites in the northern Coast Ranges. This report provides a description of each of the study areas, procedures and equipment used, processing steps, and time series data from each site in the form of comma-separated values (.csv) tables.

  19. Resolution testing and limitations of geodetic and tsunami datasets for finite fault inversions along subduction zones

    Science.gov (United States)

    Williamson, A.; Newman, A. V.

    2017-12-01

    Finite fault inversions utilizing multiple datasets have become commonplace for large earthquakes pending data availability. The mixture of geodetic datasets such as Global Navigational Satellite Systems (GNSS) and InSAR, seismic waveforms, and when applicable, tsunami waveforms from Deep-Ocean Assessment and Reporting of Tsunami (DART) gauges, provide slightly different observations that when incorporated together lead to a more robust model of fault slip distribution. The merging of different datasets is of particular importance along subduction zones where direct observations of seafloor deformation over the rupture area are extremely limited. Instead, instrumentation measures related ground motion from tens to hundreds of kilometers away. The distance from the event and dataset type can lead to a variable degree of resolution, affecting the ability to accurately model the spatial distribution of slip. This study analyzes the spatial resolution attained individually from geodetic and tsunami datasets as well as in a combined dataset. We constrain the importance of distance between estimated parameters and observed data and how that varies between land-based and open ocean datasets. Analysis focuses on accurately scaled subduction zone synthetic models as well as analysis of the relationship between slip and data in recent large subduction zone earthquakes. This study shows that seafloor deformation sensitive datasets, like open-ocean tsunami waveforms or seafloor geodetic instrumentation, can provide unique offshore resolution for understanding most large and particularly tsunamigenic megathrust earthquake activity. In most environments, we simply lack the capability to resolve static displacements using land-based geodetic observations.

  20. Ground-Based Global Navigation Satellite System Mixed Broadcast Ephemeris Data (sub-hourly files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) Mixed Broadcast Ephemeris Data (sub-hourly files) from the NASA Crustal Dynamics Data...

  1. Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study

    Science.gov (United States)

    Nguyen, Thanh T. N.; Bui, Hung Q.; Pham, Ha V.; Luu, Hung V.; Man, Chuc D.; Pham, Hai N.; Le, Ha T.; Nguyen, Thuy T.

    2015-09-01

    Particulate Matter (PM) pollution is one of the most important air quality concerns in Vietnam. In this study, we integrate ground-based measurements, meteorological and satellite data to map temporal PM concentrations at a 10 × 10 km grid for the entire of Vietnam. We specifically used MODIS Aqua and Terra data and developed statistically-significant regression models to map and extend the ground-based PM concentrations. We validated our models over diverse geographic provinces i.e., North East, Red River Delta, North Central Coast and South Central Coast in Vietnam. Validation suggested good results for satellite-derived PM2.5 data compared to ground-based PM2.5 (n = 285, r2 = 0.411, RMSE = 20.299 μg m-3 and RE = 39.789%). Further, validation of satellite-derived PM2.5 on two independent datasets for North East and South Central Coast suggested similar results (n = 40, r2 = 0.455, RMSE = 21.512 μg m-3, RE = 45.236% and n = 45, r2 = 0.444, RMSE = 8.551 μg m-3, RE = 46.446% respectively). Also, our satellite-derived PM2.5 maps were able to replicate seasonal and spatial trends of ground-based measurements in four different regions. Our results highlight the potential use of MODIS datasets for PM estimation at a regional scale in Vietnam. However, model limitation in capturing maximal or minimal PM2.5 peaks needs further investigations on ground data, atmospheric conditions and physical aspects.

  2. Thought-action fusion and thought suppression in obsessive-compulsive disorder.

    Science.gov (United States)

    Rassin, E; Diepstraten, P; Merckelbach, H; Muris, P

    2001-07-01

    To examine the significance of thought-action fusion (TAF) and thought suppression tendencies, the present study obtained pre- and post-treatment questionnaire data on these constructs in a sample of OCD patients (n=24) and non-OCD anxiety patients (n=20). Results indicate that TAF and suppression are correlated with severity of psychopathology. Yet, the associations between TAF and psychopathology are not typical for OCD, but do also occur in other anxiety disorders (e.g., panic disorder, post traumatic stress disorder, and social phobia). As well, mean scores on the TAF and thought suppression measures dropped significantly from pre- to post-treatment, indicating that TAF and thought suppression are susceptible to change during psychotherapy.

  3. A global gridded dataset of daily precipitation going back to 1950, ideal for analysing precipitation extremes

    Science.gov (United States)

    Contractor, S.; Donat, M.; Alexander, L. V.

    2017-12-01

    Reliable observations of precipitation are necessary to determine past changes in precipitation and validate models, allowing for reliable future projections. Existing gauge based gridded datasets of daily precipitation and satellite based observations contain artefacts and have a short length of record, making them unsuitable to analyse precipitation extremes. The largest limiting factor for the gauge based datasets is a dense and reliable station network. Currently, there are two major data archives of global in situ daily rainfall data, first is Global Historical Station Network (GHCN-Daily) hosted by National Oceanic and Atmospheric Administration (NOAA) and the other by Global Precipitation Climatology Centre (GPCC) part of the Deutsche Wetterdienst (DWD). We combine the two data archives and use automated quality control techniques to create a reliable long term network of raw station data, which we then interpolate using block kriging to create a global gridded dataset of daily precipitation going back to 1950. We compare our interpolated dataset with existing global gridded data of daily precipitation: NOAA Climate Prediction Centre (CPC) Global V1.0 and GPCC Full Data Daily Version 1.0, as well as various regional datasets. We find that our raw station density is much higher than other datasets. To avoid artefacts due to station network variability, we provide multiple versions of our dataset based on various completeness criteria, as well as provide the standard deviation, kriging error and number of stations for each grid cell and timestep to encourage responsible use of our dataset. Despite our efforts to increase the raw data density, the in situ station network remains sparse in India after the 1960s and in Africa throughout the timespan of the dataset. Our dataset would allow for more reliable global analyses of rainfall including its extremes and pave the way for better global precipitation observations with lower and more transparent uncertainties.

  4. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  5. Surface Turbulent Fluxes, 1x1 deg Daily Grid, Satellite F15 V2c

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version-2c (GSSTF 2c) Dataset recently produced through a MEaSURES funded project led by...

  6. Geolocation applications of the Gonets LEO messaging satellites

    Science.gov (United States)

    Vlasov, Vladimir N.; Ashjaee, Javad M.

    Geostationary satellites carry a majority of the international telecommunications traffic not carried by transoceanic cable. However, because the radio path links to and from geostationary satellites total at least 70,000 km and because of inherent on-board spacecraft power limitations, earth stations used in conjunction with geostationary satellites are usually large and expensive. This limits their installation to areas with a well-developed industrial and economic infrastructure. This reality helps perpetuate a chicken egg dilemma for the developing countries and isolated regions. Economic integration with the developed world requires being 'networked'. But for many developing entities, even the initial price of entry exceeds their modest resources. Exclusion from the global information highways virtually assures retardation of economic growth for developing nations, remote and isolated areas. Very Small Aperture Terminal (VSAT) earth stations are often thought of as a solution for networking developing regions. But economic considerations often forecloses this option. If VSAT size and cost is to be minimized, powerful spot beams from the satellite need to be focused on relatively small regions. This is not often feasible because of the high cost of the satellite itself. To dedicate a high power spot beam to a small region is usually not economically feasible.

  7. Does unconscious thought outperform conscious thought on complex decisions? A further examination

    Directory of Open Access Journals (Sweden)

    Todd J. Thorsteinson

    2009-04-01

    Full Text Available Two experiments examined the benefits of unconscious thought on complex decisions (Dijksterhuis, 2004. Experiment 1 attempted to replicate and extend past research by examining the effect of providing reasons prior to rating the options. Results indicated no significant differences between the conditions. Experiment 2 attempted to replicate the findings of Dijksterhuis, Bos, Nordgren, and van Baaren (2006 and determine if a memory aid could overcome the limitations of conscious thought on complex tasks. Results revealed that a memory aid improved decisions compared to the conscious thought condition. Participants in the unconscious thought condition did not perform significantly better than did participants in the conscious thought condition.

  8. Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

    Science.gov (United States)

    Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

    2018-04-01

    Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as

  9. EPA Nanorelease Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — EPA Nanorelease Dataset. This dataset is associated with the following publication: Wohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B....

  10. The global coastline dataset: the observed relation between erosion and sea-level rise

    Science.gov (United States)

    Donchyts, G.; Baart, F.; Luijendijk, A.; Hagenaars, G.

    2017-12-01

    Erosion of sandy coasts is considered one of the key risks of sea-level rise. Because sandy coastlines of the world are often highly populated, erosive coastline trends result in risk to populations and infrastructure. Most of our understanding of the relation between sea-level rise and coastal erosion is based on local or regional observations and generalizations of numerical and physical experiments. Until recently there was no reliable global scale assessment of the location of sandy coasts and their rate of erosion and accretion. Here we present the global coastline dataset that covers erosion indicators on a local scale with global coverage. The dataset uses our global coastline transects grid defined with an alongshore spacing of 250 m and a cross shore length extending 1 km seaward and 1 km landward. This grid matches up with pre-existing local grids where available. We present the latest results on validation of coastal-erosion trends (based on optical satellites) and classification of sandy versus non-sandy coasts. We show the relation between sea-level rise (based both on tide-gauges and multi-mission satellite altimetry) and observed erosion trends over the last decades, taking into account broken-coastline trends (for example due to nourishments).An interactive web application presents the publicly-accessible results using a backend based on Google Earth Engine. It allows both researchers and stakeholders to use objective estimates of coastline trends, particularly when authoritative sources are not available.

  11. Merged SAGE II, Ozone_cci and OMPS ozone profile dataset and evaluation of ozone trends in the stratosphere

    Directory of Open Access Journals (Sweden)

    V. F. Sofieva

    2017-10-01

    Full Text Available In this paper, we present a merged dataset of ozone profiles from several satellite instruments: SAGE II on ERBS, GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, ACE-FTS on SCISAT, and OMPS on Suomi-NPP. The merged dataset is created in the framework of the European Space Agency Climate Change Initiative (Ozone_cci with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The datasets from the individual instruments have been extensively validated and intercompared; only those datasets which are in good agreement, and do not exhibit significant drifts with respect to collocated ground-based observations and with respect to each other, are used for merging. The long-term SAGE–CCI–OMPS dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The merged SAGE–CCI–OMPS dataset consists of deseasonalized anomalies of ozone in 10° latitude bands from 90° S to 90° N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to July 2016. This newly created dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997. The upper stratospheric trends are statistically significant at midlatitudes and indicate ozone recovery, as expected from the decrease of stratospheric halogens that started in the middle of the 1990s and stratospheric cooling.

  12. A dataset mapping the potential biophysical effects of vegetation cover change

    Science.gov (United States)

    Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

    2018-02-01

    Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

  13. Overview of the CERES Edition-4 Multilayer Cloud Property Datasets

    Science.gov (United States)

    Chang, F. L.; Minnis, P.; Sun-Mack, S.; Chen, Y.; Smith, R. A.; Brown, R. R.

    2014-12-01

    Knowledge of the cloud vertical distribution is important for understanding the role of clouds on earth's radiation budget and climate change. Since high-level cirrus clouds with low emission temperatures and small optical depths can provide a positive feedback to a climate system and low-level stratus clouds with high emission temperatures and large optical depths can provide a negative feedback effect, the retrieval of multilayer cloud properties using satellite observations, like Terra and Aqua MODIS, is critically important for a variety of cloud and climate applications. For the objective of the Clouds and the Earth's Radiant Energy System (CERES), new algorithms have been developed using Terra and Aqua MODIS data to allow separate retrievals of cirrus and stratus cloud properties when the two dominant cloud types are simultaneously present in a multilayer system. In this paper, we will present an overview of the new CERES Edition-4 multilayer cloud property datasets derived from Terra as well as Aqua. Assessment of the new CERES multilayer cloud datasets will include high-level cirrus and low-level stratus cloud heights, pressures, and temperatures as well as their optical depths, emissivities, and microphysical properties.

  14. A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

    Science.gov (United States)

    Zorzetto, E.; Marani, M.

    2017-12-01

    The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

  15. Satellite Imagery Analysis for Automated Global Food Security Forecasting

    Science.gov (United States)

    Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

    2017-12-01

    The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

  16. Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

    Science.gov (United States)

    Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

    2014-12-01

    Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various

  17. Rays in the northern Gulf of Mexico: Aerial Survey and Satellite Telemetry 2008-2012 (NCEI Accession 0129495)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains distribution and abundance data for rays in the Gulf of Mexico collected through aerial surveys and satellite telemetry. Aerial survey data...

  18. Explore Earth Science Datasets for STEM with the NASA GES DISC Online Visualization and Analysis Tool, Giovanni

    Science.gov (United States)

    Liu, Z.; Acker, J.; Kempler, S.

    2016-01-01

    The NASA Goddard Earth Sciences (GES) Data and Information Services Center(DISC) is one of twelve NASA Science Mission Directorate (SMD) Data Centers that provide Earth science data, information, and services to users around the world including research and application scientists, students, citizen scientists, etc. The GESDISC is the home (archive) of remote sensing datasets for NASA Precipitation and Hydrology, Atmospheric Composition and Dynamics, etc. To facilitate Earth science data access, the GES DISC has been developing user-friendly data services for users at different levels in different countries. Among them, the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni, http:giovanni.gsfc.nasa.gov) allows users to explore satellite-based datasets using sophisticated analyses and visualization without downloading data and software, which is particularly suitable for novices (such as students) to use NASA datasets in STEM (science, technology, engineering and mathematics) activities. In this presentation, we will briefly introduce Giovanni along with examples for STEM activities.

  19. Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.; Zhu, Zhengyuan

    2018-03-01

    High spatiotemporal land surface temperature (LST) datasets are increasingly needed in a variety of fields such as ecology, hydrology, meteorology, epidemiology, and energy systems. Moderate Resolution Imaging Spectroradiometer (MODIS) LST is one of such high spatiotemporal datasets that are widely used. But, it has large amount of missing values primarily because of clouds. Gapfilling the missing values is an important approach to create high spatiotemporal LST datasets. However current gapfilling methods have limitations in terms of accuracy and time required to assemble the data over large areas (e.g., national and continental levels). In this study, we developed a 3-step hybrid method by integrating a combination of daily merging, spatiotemporal gapfilling, and temporal interpolation methods, to create a high spatiotemporal LST dataset using the four daily LST observations from the two MODIS instruments on Terra and Aqua satellites. We applied this method in urban and surrounding areas for the conterminous U.S. in 2010. The evaluation of the gapfilled LST product indicates that its root mean squared error (RMSE) to be 3.3K for mid-daytime (1:30 pm) and 2.7K for mid-13 nighttime (1:30 am) observations. The method can be easily extended to other years and regions and is also applicable to other satellite products. This seamless daily (mid-daytime and mid-nighttime) LST product with 1 km spatial resolution is of great value for studying effects of urbanization (e.g., urban heat island) and the related impacts on people, ecosystems, energy systems and other infrastructure for cities.

  20. Near-equatorial convective regimes over the Indian Ocean as revealed by synergistic analysis of satellite observations.

    Digital Repository Service at National Institute of Oceanography (India)

    Levy, G.; Geiss, A.; RameshKumar, M.R.

    We examine the organization and temporal evolution of deep convection in relation to the low level flow over the Indian Ocean by a synergistic analysis of several satellite datasets for wind, rainfall, Outgoing Longwave Radiation (OLR) and cloud...

  1. Enhancing Conservation with High Resolution Productivity Datasets for the Conterminous United States

    Science.gov (United States)

    Robinson, Nathaniel Paul

    Human driven alteration of the earth's terrestrial surface is accelerating through land use changes, intensification of human activity, climate change, and other anthropogenic pressures. These changes occur at broad spatio-temporal scales, challenging our ability to effectively monitor and assess the impacts and subsequent conservation strategies. While satellite remote sensing (SRS) products enable monitoring of the earth's terrestrial surface continuously across space and time, the practical applications for conservation and management of these products are limited. Often the processes driving ecological change occur at fine spatial resolutions and are undetectable given the resolution of available datasets. Additionally, the links between SRS data and ecologically meaningful metrics are weak. Recent advances in cloud computing technology along with the growing record of high resolution SRS data enable the development of SRS products that quantify ecologically meaningful variables at relevant scales applicable for conservation and management. The focus of my dissertation is to improve the applicability of terrestrial gross and net primary productivity (GPP/NPP) datasets for the conterminous United States (CONUS). In chapter one, I develop a framework for creating high resolution datasets of vegetation dynamics. I use the entire archive of Landsat 5, 7, and 8 surface reflectance data and a novel gap filling approach to create spatially continuous 30 m, 16-day composites of the normalized difference vegetation index (NDVI) from 1986 to 2016. In chapter two, I integrate this with other high resolution datasets and the MOD17 algorithm to create the first high resolution GPP and NPP datasets for CONUS. I demonstrate the applicability of these products for conservation and management, showing the improvements beyond currently available products. In chapter three, I utilize this dataset to evaluate the relationships between land ownership and terrestrial production

  2. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  3. Ground-Based Global Navigation Satellite System (GNSS) Compact Observation Data (1-second sampling, sub-hourly files) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset consists of ground-based Global Navigation Satellite System (GNSS) Observation Data (1-second sampling, sub-hourly files) from the NASA Crustal Dynamics...

  4. Evaluation of satellite-retrieved extreme precipitation using gauge observations

    Science.gov (United States)

    Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

    2012-04-01

    Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

  5. A Satellite Mortality Study to Support Space Systems Lifetime Prediction

    Science.gov (United States)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory

    2013-01-01

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  6. Introducing the VISAGE project - Visualization for Integrated Satellite, Airborne, and Ground-based data Exploration

    Science.gov (United States)

    Gatlin, P. N.; Conover, H.; Berendes, T.; Maskey, M.; Naeger, A. R.; Wingo, S. M.

    2017-12-01

    A key component of NASA's Earth observation system is its field experiments, for intensive observation of particular weather phenomena, or for ground validation of satellite observations. These experiments collect data from a wide variety of airborne and ground-based instruments, on different spatial and temporal scales, often in unique formats. The field data are often used with high volume satellite observations that have very different spatial and temporal coverage. The challenges inherent in working with such diverse datasets make it difficult for scientists to rapidly collect and analyze the data for physical process studies and validation of satellite algorithms. The newly-funded VISAGE project will address these issues by combining and extending nascent efforts to provide on-line data fusion, exploration, analysis and delivery capabilities. A key building block is the Field Campaign Explorer (FCX), which allows users to examine data collected during field campaigns and simplifies data acquisition for event-based research. VISAGE will extend FCX's capabilities beyond interactive visualization and exploration of coincident datasets, to provide interrogation of data values and basic analyses such as ratios and differences between data fields. The project will also incorporate new, higher level fused and aggregated analysis products from the System for Integrating Multi-platform data to Build the Atmospheric column (SIMBA), which combines satellite and ground-based observations into a common gridded atmospheric column data product; and the Validation Network (VN), which compiles a nationwide database of coincident ground- and satellite-based radar measurements of precipitation for larger scale scientific analysis. The VISAGE proof-of-concept will target "golden cases" from Global Precipitation Measurement Ground Validation campaigns. This presentation will introduce the VISAGE project, initial accomplishments and near term plans.

  7. Psychological effects of thought acceleration.

    Science.gov (United States)

    Pronin, Emily; Jacobs, Elana; Wegner, Daniel M

    2008-10-01

    Six experiments found that manipulations that increase thought speed also yield positive affect. These experiments varied in both the methods used for accelerating thought (i.e., instructions to brainstorm freely, exposure to multiple ideas, encouragement to plagiarize others' ideas, performance of easy cognitive tasks, narration of a silent video in fast-forward, and experimentally controlled reading speed) and the contents of the thoughts that were induced (from thoughts about money-making schemes to thoughts of five-letter words). The results suggested that effects of thought speed on mood are partially rooted in the subjective experience of thought speed. The results also suggested that these effects can be attributed to the joy-enhancing effects of fast thinking (rather than only to the joy-killing effects of slow thinking). This work is inspired by observations of a link between "racing thoughts" and euphoria in cases of clinical mania, and potential implications of that observed link are discussed. (c) 2008 APA, all rights reserved

  8. Thoughts in flight: automation use and pilots' task-related and task-unrelated thought.

    Science.gov (United States)

    Casner, Stephen M; Schooler, Jonathan W

    2014-05-01

    The objective was to examine the relationship between cockpit automation use and task-related and task-unrelated thought among airline pilots. Studies find that cockpit automation can sometimes relieve pilots of tedious control tasks and afford them more time to think ahead. Paradoxically, automation has also been shown to lead to lesser awareness. These results prompt the question of what pilots think about while using automation. A total of 18 airline pilots flew a Boeing 747-400 simulator while we recorded which of two levels of automation they used. As they worked, pilots were verbally probed about what they were thinking. Pilots were asked to categorize their thoughts as pertaining to (a) a specific task at hand, (b) higher-level flight-related thoughts (e.g.,planning ahead), or (c) thoughts unrelated to the flight. Pilots' performance was also measured. Pilots reported a smaller percentage of task-at-hand thoughts (27% vs. 50%) and a greater percentage of higher-level flight-related thoughts (56% vs. 29%) when using the higher level of automation. However, when all was going according to plan, using either level of automation, pilots also reported a higher percentage of task-unrelated thoughts (21%) than they did when in the midst of an unsuccessful performance (7%). Task-unrelated thoughts peaked at 25% when pilots were not interacting with the automation. Although cockpit automation may provide pilots with more time to think, it may encourage pilots to reinvest only some of this mental free time in thinking flight-related thoughts. This research informs the design of human-automation systems that more meaningfully engage the human operator.

  9. The satellite-based remote sensing of particulate matter (PM) in support to urban air quality: PM variability and hot spots within the Cordoba city (Argentina) as revealed by the high-resolution MAIAC-algorithm retrievals applied to a ten-years dataset (2

    Science.gov (United States)

    Della Ceca, Lara Sofia; Carreras, Hebe A.; Lyapustin, Alexei I.; Barnaba, Francesca

    2016-04-01

    Particulate matter (PM) is one of the major harmful pollutants to public health and the environment [1]. In developed countries, specific air-quality legislation establishes limit values for PM metrics (e.g., PM10, PM2.5) to protect the citizens health (e.g., European Commission Directive 2008/50, US Clean Air Act). Extensive PM measuring networks therefore exist in these countries to comply with the legislation. In less developed countries air quality monitoring networks are still lacking and satellite-based datasets could represent a valid alternative to fill observational gaps. The main PM (or aerosol) parameter retrieved from satellite is the 'aerosol optical depth' (AOD), an optical parameter quantifying the aerosol load in the whole atmospheric column. Datasets from the MODIS sensors on board of the NASA spacecrafts TERRA and AQUA are among the longest records of AOD from space. However, although extremely useful in regional and global studies, the standard 10 km-resolution MODIS AOD product is not suitable to be employed at the urban scale. Recently, a new algorithm called Multi-Angle Implementation of Atmospheric Correction (MAIAC) was developed for MODIS, providing AOD at 1 km resolution [2]. In this work, the MAIAC AOD retrievals over the decade 2003-2013 were employed to investigate the spatiotemporal variation of atmospheric aerosols over the Argentinean city of Cordoba and its surroundings, an area where a very scarce dataset of in situ PM data is available. The MAIAC retrievals over the city were firstly validated using a 'ground truth' AOD dataset from the Cordoba sunphotometer operating within the global AERONET network [3]. This validation showed the good performances of the MAIAC algorithm in the area. The satellite MAIAC AOD dataset was therefore employed to investigate the 10-years trend as well as seasonal and monthly patterns of particulate matter in the Cordoba city. The first showed a marked increase of AOD over time, particularly evident in

  10. Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study

    International Nuclear Information System (INIS)

    Nguyen, Thanh T N; Bui, Hung Q; Pham, Ha V; Luu, Hung V; Man, Chuc D; Pham, Hai N; Le, Ha T; Nguyen, Thuy T

    2015-01-01

    Particulate Matter (PM) pollution is one of the most important air quality concerns in Vietnam. In this study, we integrate ground-based measurements, meteorological and satellite data to map temporal PM concentrations at a 10 × 10 km grid for the entire of Vietnam. We specifically used MODIS Aqua and Terra data and developed statistically-significant regression models to map and extend the ground-based PM concentrations. We validated our models over diverse geographic provinces i.e., North East, Red River Delta, North Central Coast and South Central Coast in Vietnam. Validation suggested good results for satellite-derived PM 2.5 data compared to ground-based PM 2.5 (n = 285, r 2  = 0.411, RMSE = 20.299 μg m −3 and RE = 39.789%). Further, validation of satellite-derived PM 2.5 on two independent datasets for North East and South Central Coast suggested similar results (n = 40, r 2  = 0.455, RMSE = 21.512 μg m −3 , RE = 45.236% and n = 45, r 2  = 0.444, RMSE = 8.551 μg m −3 , RE = 46.446% respectively). Also, our satellite-derived PM 2.5 maps were able to replicate seasonal and spatial trends of ground-based measurements in four different regions. Our results highlight the potential use of MODIS datasets for PM estimation at a regional scale in Vietnam. However, model limitation in capturing maximal or minimal PM 2.5 peaks needs further investigations on ground data, atmospheric conditions and physical aspects. (letter)

  11. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

    OpenAIRE

    Xueke Li; Taixia Wu; Kai Liu; Yao Li; Lifu Zhang

    2016-01-01

    The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1) opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, ...

  12. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  13. Crisis Thought

    OpenAIRE

    Morris, Edwin Kent

    2016-01-01

    Crisis thought is an idea that gives a name to and accounts for some of the problematics of the sign crisis in political, social, cultural, and economic discourse. Specifically, crisis thought is a discursive formation, a concept used loosely here to refer to an assemblage of signs such as anxiety or fear that evoke or invoke similar, but inaccurate connotations as crisis in political and everyday usage. The general question this study grapples with is why political, social, cultural, and eco...

  14. Characterization Of Ocean Wind Vector Retrievals Using ERS-2 High-Resolution Long-Term Dataset And Buoy Measurements

    Science.gov (United States)

    Polverari, F.; Talone, M.; Crapolicchio, R. Levy, G.; Marzano, F.

    2013-12-01

    The European Remote-sensing Satellite (ERS)-2 scatterometer provides wind retrievals over Ocean. To satisfy the needs of high quality and homogeneous set of scatterometer measurements, the European Space Agency (ESA) has developed the project Advanced Scatterometer Processing System (ASPS) with which a long-term dataset of new ERS-2 wind products, with an enhanced resolution of 25km square, has been generated by the reprocessing of the entire ERS mission. This paper presents the main results of the validation work of such new dataset using in situ measurements provided by the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA). The comparison indicates that, on average, the scatterometer data agree well with buoys measurements, however the scatterometer tends to overestimates lower winds and underestimates higher winds.

  15. The effects of psychoeducation on thought-action fusion, thought suppression, and responsibility.

    Science.gov (United States)

    Marino-Carper, Teresa; Negy, Charles; Burns, Gillian; Lunt, Rachael A

    2010-09-01

    The current study examined the effects of a psychoeducational intervention designed to target thought-action fusion (TAF) on TAF, thought suppression, and responsibility cognitions. 139 undergraduate students (25 male; 114 female) who were relatively high in TAF with respect to their peers served as participants. Immediately following intervention, individuals who had received psychoeducation regarding TAF reported significantly lower morality TAF scores than individuals who had received psychoeducation regarding thoughts in general and individuals in the control group. At the two-week follow-up assessment, the likelihood TAF scores of those who had received psychoeducation regarding TAF were significantly lower than those of the control group. In addition, the group that received psychoeducation regarding TAF was the only group that did not experience a significant increase in thought suppression from baseline to post-intervention, and was also the only group to experience an increase in both frequency of and belief in low-responsibility thoughts from baseline to follow-up. Implications are discussed. (c) 2010 Elsevier Ltd. All rights reserved.

  16. Five Blind Men and an Elephant: Comparing Aura Ozone Datasets and Sonde with Model Simulations

    Science.gov (United States)

    Tang, Q.; Prather, M. J.

    2011-12-01

    The four Earth Observing System (EOS) Aura satellite ozone measurements (HIRDLS, MLS, OMI, and TES) as well as the coincident WOUDC sonde are the five ``blind men'' touching the ``elephant'' (ozone). They all measure ozone (O3) in the upper troposphere and lower stratosphere (UT/LS) region, providing the great opportunity to study how the tropospheric ozone is influenced by the stratospheric source, an important tropospheric ozone budget term with large uncertainties and discrepancies across different models and methods. Based upon the 2-D autocorrelation for the tropospheric column ozone anomalies of the OMI swaths, we show that the stratosphere-troposphere exchange (STE) processes occur on the scale of a few hundred kilometers. Applying the high resolution (1o±1o±40-layer±0.5 hr) atmospheric chemistry transport model (CTM) as a transfer standard, we compare the noncoincident Aura level 2 swath datasets with the exact matching simulations of each measurement to investigate the consistency of different instruments as well as evaluate the accuracy of modeled ozone. Different signs of the CTM biases against HIRDLS, MLS, and TES are found from tropics to northern hemisphere (NH) mid-latitudes in July 2005 at 215 hPa and over tropics at 147 hPa for July 2005 and January 2006, suggesting inconsistency across these Aura datasets. On the other hand, the CTM has great positive biases against satellite observations in the lower stratosphere of winter time southern hemisphere (SH) mid-latitudes, which is probably attributed to the problems in the stratospheric circulation of the driving met-fields. The model's ability of reproducing STE-related processes, such as tropospheric folds (TFs), is confirmed by the comparisons with WOUDC sonde. We found eight cases in year 2005 with all the four Aura measurements available and folding structures in the coincident sonde profile. The case studies indicate that all the four Aura instruments demonstrate some skills in catching the

  17. Satellite Data Support for the ARM Climate Research Facility, 8/01/2009 - 7/31/2015

    Energy Technology Data Exchange (ETDEWEB)

    Minnis, Patrick [NASA Langley Research Center, Hampton, VA (United States); Khaiyer, Mandana M [Science Systems and Applications, Inc., Hampton, VA (United States)

    2015-10-06

    This report summarizes the support provided by NASA Langley Research for the DOE ARM Program in the form of cloud and radiation products derived from satellite imager data for the period between 8/01/09 through 7/31/15. Cloud properties such as cloud amount, height, and optical depth as well as outgoing longwave and shortwave broadband radiative fluxes were derived from geostationary and low-earth orbiting satellite imager radiance measurements for domains encompassing ARM permanent sites and field campaigns during the performance period. Datasets provided and documents produced are listed.

  18. Satellite monitoring of cyanobacterial harmful algal bloom ...

    Science.gov (United States)

    Cyanobacterial harmful algal blooms (cyanoHABs) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern because of their dense biomass and the risk of exposure to toxins in both recreational waters and drinking source waters. Successful cyanoHAB assessment by satellites may provide a first-line of defense indicator for human and ecological health protection. In this study, assessment methods were developed to determine the utility of satellite technology for detecting cyanoHAB occurrence frequency at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent Sentinel-3 Ocean and Land Colour Imager (OLCI) launched in 2016. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, there were 275,897 lakes and reservoirs greater than 1 hectare in the 48 U.S. states. Results from this evaluation show that 5.6 % of waterbodies were resolvable by satellites with 300 m single pixel resolution and 0.7 % of waterbodies were resolvable when a 3x3 pixel array was applied based on minimum Euclidian distance from shore. Satellite data was also spatially joined to US public water surface intake (PWSI) locations, where single pixel resolution resolved 57% of PWSI and a 3x3 pixel array resolved 33% of

  19. An evaluation of satellite and in situ based sea surface temperature datasets in the North Indian Ocean region

    Digital Repository Service at National Institute of Oceanography (India)

    Sreejith, O.P.; Shenoi, S.S.C.

    for all three datasets. There was very little difference in the error statistics from one region to another. The error statistics differed significantly from year to year. The PFSST fields reported cooler SSTs approx. 0.5 degrees C, during August 1991...

  20. Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2016-11-01

    Full Text Available Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS and 18 descending images from the Environmental Satellite (ENVISAT have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface–parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

  1. From intrusive to oscillating thoughts.

    Science.gov (United States)

    Peirce, Anne Griswold

    2007-10-01

    This paper focused on the possibility that intrusive thoughts (ITs) are a form of an evolutionary, adaptive, and complex strategy to prepare for and resolve stressful life events through schema formation. Intrusive thoughts have been studied in relation to individual conditions, such as traumatic stress disorder and obsessive-compulsive disorder. They have also been documented in the average person experiencing everyday stress. In many descriptions of thought intrusion, it is accompanied by thought suppression. Several theories have been put forth to describe ITs, although none provides a satisfactory explanation as to whether ITs are a normal process, a normal process gone astray, or a sign of pathology. There is also no consistent view of the role that thought suppression plays in the process. I propose that thought intrusion and thought suppression may be better understood by examining them together as a complex and adaptive mechanism capable of escalating in times of need. The ability of a biological mechanism to scale up in times of need is one hallmark of a complex and adaptive system. Other hallmarks of complexity, including self-similarity across scales, sensitivity to initial conditions, presence of feedback loops, and system oscillation, are also discussed in this article. Finally, I propose that thought intrusion and thought suppression are better described together as an oscillatory cycle.

  2. Mapping the Brain’s Metaphor Circuitry:Is Abstract Thought Metaphorical Thought?

    Directory of Open Access Journals (Sweden)

    George eLakoff

    2014-12-01

    Full Text Available An overview of the basics of metaphorical thought and language from the perspective of Neurocognition, the integrated interdisciplinary study of how conceptual thought and language work in the brain. The paper outlines a theory of metaphor circuitry and discusses how everyday reason makes use of embodied metaphor circuitry.

  3. A global gas flaring black carbon emission rate dataset from 1994 to 2012

    Science.gov (United States)

    Huang, Kan; Fu, Joshua S.

    2016-11-01

    Global flaring of associated petroleum gas is a potential emission source of particulate matters (PM) and could be notable in some specific regions that are in urgent need of mitigation. PM emitted from gas flaring is mainly in the form of black carbon (BC), which is a strong short-lived climate forcer. However, BC from gas flaring has been neglected in most global/regional emission inventories and is rarely considered in climate modeling. Here we present a global gas flaring BC emission rate dataset for the period 1994-2012 in a machine-readable format. We develop a region-dependent gas flaring BC emission factor database based on the chemical compositions of associated petroleum gas at various oil fields. Gas flaring BC emission rates are estimated using this emission factor database and flaring volumes retrieved from satellite imagery. Evaluation using a chemical transport model suggests that consideration of gas flaring emissions can improve model performance. This dataset will benefit and inform a broad range of research topics, e.g., carbon budget, air quality/climate modeling, and environmental/human exposure.

  4. Evaluation of forest fires in Portugal Mainland during 2016 summer considering different satellite datasets

    Science.gov (United States)

    Teodoro, A. C.; Amaral, A.

    2017-10-01

    Portugal is one of the most affected countries in Europe by forest fires. Every year in the summer, hundreds of hectares burn, destroying goods and forests at an alarming rate. The objective of this work was to analyze the forest areas burned in Portugal in 2016 (summer) using different satellite data with different spatial resolution (Sentinel-2A MSI and Landsat 8 OLI) in two affected areas. Data from spring from 2016 and 2017 were chosen (pre-fire event and post-fire event) in order to maximize the Normalized Difference Vegetation Index (NDVI) values. The QGIS software's plugin - Semi- Automatic Classification Plugin- which allowed to obtain NDVI values for the Landsat 8 OLI and Sentinel- 2A was used. The results showed that the NDVI decreased considerably in Arouca and Vila Nova de Cerveira after de fire event, meaning a marked drop in vegetation level. In Sintra municipality this change was not verified because non forest fire was registered in this area during the study period. The results from the Sentinel-2A and Landsat 8 OLI data analysis are in agreement, however the Sentinel-2A satellite gives results more accurate than Landsat-8 OLI since it has best spatial resolution. This study could help the experts to understand both the causes and consequences of spatial variability of post-fire effects. Other vegetation spectral indices related with fire and burnt areas could also be calculated in order to discriminate burnt areas. Added to the best spatial resolution of Sentinel-2A (10 m), the temporal resolution of Sentinel- 2A (10 days) was increased with the launch of the twin Sentinel-2B (very recently) and therefore the frequency of the combined constellation revisit will be 5 days. However, for historical studies, the Landsat program remains the best option.

  5. Popper's Thought Experiment Reinvestigated

    Science.gov (United States)

    Richardson, Chris; Dowling, Jonathan

    2012-02-01

    Karl Popper posed an interesting thought experiment in 1934. With it, he meant to question the completeness of quantum mechanics. He claimed that the notion of quantum entanglement leads to absurd scenarios that cannot be true in real life and that an implementation of his thought experiment would not give the results that QM predicts. Unfortunately for Popper, it has taken until recently to perform experiments that test his claims. The results of the experiments do not refute QM as Popper predicted, but neither do they confirm what Popper claimed QM predicted. Kim and Shih implemented Popper's thought experiment in the lab. The results of the experiment are not clear and have instigated many interpretations of the results. The results show some correlation between entangled photons, but not in the way that Popper thought, nor in the way a simple application of QM might predict. A ghost-imaging experiment by Strekalov, et al. sheds light on the physics behind Popper's thought experiment, but does not try to directly test it. I will build the physics of Popper's thought experiment from the ground up and show how the results of both of these experiments agree with each other and the theory of QM, but disprove Popper.

  6. Merging Satellite Precipitation Products for Improved Streamflow Simulations

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

    2017-12-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

  7. A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing..

    Science.gov (United States)

    Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying...

  8. RARD: The Related-Article Recommendation Dataset

    OpenAIRE

    Beel, Joeran; Carevic, Zeljko; Schaible, Johann; Neusch, Gabor

    2017-01-01

    Recommender-system datasets are used for recommender-system evaluations, training machine-learning algorithms, and exploring user behavior. While there are many datasets for recommender systems in the domains of movies, books, and music, there are rather few datasets from research-paper recommender systems. In this paper, we introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains ...

  9. Modeling and Assessment of Precise Time Transfer by Using BeiDou Navigation Satellite System Triple-Frequency Signals

    Science.gov (United States)

    Zhang, Pengfei; Zhang, Rui; Liu, Jinhai; Lu, Xiaochun

    2018-01-01

    This study proposes two models for precise time transfer using the BeiDou Navigation Satellite System triple-frequency signals: ionosphere-free (IF) combined precise point positioning (PPP) model with two dual-frequency combinations (IF-PPP1) and ionosphere-free combined PPP model with a single triple-frequency combination (IF-PPP2). A dataset with a short baseline (with a common external time frequency) and a long baseline are used for performance assessments. The results show that IF-PPP1 and IF-PPP2 models can both be used for precise time transfer using BeiDou Navigation Satellite System (BDS) triple-frequency signals, and the accuracy and stability of time transfer is the same in both cases, except for a constant system bias caused by the hardware delay of different frequencies, which can be removed by the parameter estimation and prediction with long time datasets or by a priori calibration. PMID:29596330

  10. Satellites

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  11. A new bed elevation dataset for Greenland

    Directory of Open Access Journals (Sweden)

    J. L. Bamber

    2013-03-01

    Full Text Available We present a new bed elevation dataset for Greenland derived from a combination of multiple airborne ice thickness surveys undertaken between the 1970s and 2012. Around 420 000 line kilometres of airborne data were used, with roughly 70% of this having been collected since the year 2000, when the last comprehensive compilation was undertaken. The airborne data were combined with satellite-derived elevations for non-glaciated terrain to produce a consistent bed digital elevation model (DEM over the entire island including across the glaciated–ice free boundary. The DEM was extended to the continental margin with the aid of bathymetric data, primarily from a compilation for the Arctic. Ice thickness was determined where an ice shelf exists from a combination of surface elevation and radar soundings. The across-track spacing between flight lines warranted interpolation at 1 km postings for significant sectors of the ice sheet. Grids of ice surface elevation, error estimates for the DEM, ice thickness and data sampling density were also produced alongside a mask of land/ocean/grounded ice/floating ice. Errors in bed elevation range from a minimum of ±10 m to about ±300 m, as a function of distance from an observation and local topographic variability. A comparison with the compilation published in 2001 highlights the improvement in resolution afforded by the new datasets, particularly along the ice sheet margin, where ice velocity is highest and changes in ice dynamics most marked. We estimate that the volume of ice included in our land-ice mask would raise mean sea level by 7.36 m, excluding any solid earth effects that would take place during ice sheet decay.

  12. Beauty Requires Thought.

    Science.gov (United States)

    Brielmann, Aenne A; Pelli, Denis G

    2017-05-22

    The experience of beauty is a pleasure, but common sense and philosophy suggest that feeling beauty differs from sensuous pleasures such as eating or sex. Immanuel Kant [1, 2] claimed that experiencing beauty requires thought but that sensuous pleasure can be enjoyed without thought and cannot be beautiful. These venerable hypotheses persist in models of aesthetic processing [3-7] but have never been tested. Here, participants continuously rated the pleasure felt from a nominally beautiful or non-beautiful stimulus and then judged whether they had experienced beauty. The stimuli, which engage various senses, included seeing images, tasting candy, and touching a teddy bear. The observer reported the feelings that the stimulus evoked. The time course of pleasure, across stimuli, is well-fit by a model with one free parameter: pleasure amplitude. Pleasure amplitude increases linearly with the feeling of beauty. To test Kant's claim of a need for thought, we reduce cognitive capacity by adding a "two-back" task to distract the observer's thoughts. The distraction greatly reduces the beauty and pleasure experienced from stimuli that otherwise produce strong pleasure and spares that of less-pleasant stimuli. We also find that strong pleasure is always beautiful, whether produced reliably by beautiful stimuli or just occasionally by sensuous stimuli. In sum, we confirm Kant's claim that only the pleasure associated with feeling beauty requires thought and disprove his claim that sensuous pleasures cannot be beautiful. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. A theory of unconscious thought

    NARCIS (Netherlands)

    Dijksterhuis, A.J.; Nordgren, L.F.

    2006-01-01

    We present a theory about human thought named the unconscious-thought theory (UTT). The theory is applicable to decision making, impression formation, attitude formation and change, problem solving, and creativity. It distinguishes between two modes of thought: unconscious and conscious. Unconscious

  14. Isfahan MISP Dataset.

    Science.gov (United States)

    Kashefpur, Masoud; Kafieh, Rahele; Jorjandi, Sahar; Golmohammadi, Hadis; Khodabande, Zahra; Abbasi, Mohammadreza; Teifuri, Nilufar; Fakharzadeh, Ali Akbar; Kashefpoor, Maryam; Rabbani, Hossein

    2017-01-01

    An online depository was introduced to share clinical ground truth with the public and provide open access for researchers to evaluate their computer-aided algorithms. PHP was used for web programming and MySQL for database managing. The website was entitled "biosigdata.com." It was a fast, secure, and easy-to-use online database for medical signals and images. Freely registered users could download the datasets and could also share their own supplementary materials while maintaining their privacies (citation and fee). Commenting was also available for all datasets, and automatic sitemap and semi-automatic SEO indexing have been set for the site. A comprehensive list of available websites for medical datasets is also presented as a Supplementary (http://journalonweb.com/tempaccess/4800.584.JMSS_55_16I3253.pdf).

  15. Quantifying uncertainty in observational rainfall datasets

    Science.gov (United States)

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

    2015-04-01

    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  16. Nano-Satellite Secondary Spacecraft on Deep Space Missions

    Science.gov (United States)

    Klesh, Andrew T.; Castillo-Rogez, Julie C.

    2012-01-01

    NanoSat technology has opened Earth orbit to extremely low-cost science missions through a common interface that provides greater launch accessibility. They have also been used on interplanetary missions, but these missions have used one-off components and architectures so that the return on investment has been limited. A natural question is the role that CubeSat-derived NanoSats could play to increase the science return of deep space missions. We do not consider single instrument nano-satellites as likely to complete entire Discovery-class missions alone,but believe that nano-satellites could augment larger missions to significantly increase science return. The key advantages offered by these mini-spacecrafts over previous planetary probes is the common availability of advanced subsystems that open the door to a large variety of science experiments, including new guidance, navigation and control capabilities. In this paper, multiple NanoSat science applications are investigated, primarily for high risk/high return science areas. We also address the significant challenges and questions that remain as obstacles to the use of nano-satellites in deep space missions. Finally, we provide some thoughts on a development roadmap toward interplanetary usage of NanoSpacecraft.

  17. Aging and repeated thought suppression success.

    Directory of Open Access Journals (Sweden)

    Ann E Lambert

    Full Text Available Intrusive thoughts and attempts to suppress them are common, but while suppression may be effective in the short-term, it can increase thought recurrence in the long-term. Because intentional suppression involves controlled processing, and many aspects of controlled processing decline with age, age differences in thought suppression outcomes may emerge, especially over repeated thought suppression attempts as cognitive resources are expended. Using multilevel modeling, we examined age differences in reactions to thought suppression attempts across four thought suppression sequences in 40 older and 42 younger adults. As expected, age differences were more prevalent during suppression than during free monitoring periods, with younger adults indicating longer, more frequent thought recurrences and greater suppression difficulty. Further, younger adults' thought suppression outcomes changed over time, while trajectories for older adults' were relatively stable. Results are discussed in terms of older adults' reduced thought recurrence, which was potentially afforded by age-related changes in reactive control and distractibility.

  18. Computational Methods for Large Spatio-temporal Datasets and Functional Data Ranking

    KAUST Repository

    Huang, Huang

    2017-07-16

    This thesis focuses on two topics, computational methods for large spatial datasets and functional data ranking. Both are tackling the challenges of big and high-dimensional data. The first topic is motivated by the prohibitive computational burden in fitting Gaussian process models to large and irregularly spaced spatial datasets. Various approximation methods have been introduced to reduce the computational cost, but many rely on unrealistic assumptions about the process and retaining statistical efficiency remains an issue. We propose a new scheme to approximate the maximum likelihood estimator and the kriging predictor when the exact computation is infeasible. The proposed method provides different types of hierarchical low-rank approximations that are both computationally and statistically efficient. We explore the improvement of the approximation theoretically and investigate the performance by simulations. For real applications, we analyze a soil moisture dataset with 2 million measurements with the hierarchical low-rank approximation and apply the proposed fast kriging to fill gaps for satellite images. The second topic is motivated by rank-based outlier detection methods for functional data. Compared to magnitude outliers, it is more challenging to detect shape outliers as they are often masked among samples. We develop a new notion of functional data depth by taking the integration of a univariate depth function. Having a form of the integrated depth, it shares many desirable features. Furthermore, the novel formation leads to a useful decomposition for detecting both shape and magnitude outliers. Our simulation studies show the proposed outlier detection procedure outperforms competitors in various outlier models. We also illustrate our methodology using real datasets of curves, images, and video frames. Finally, we introduce the functional data ranking technique to spatio-temporal statistics for visualizing and assessing covariance properties, such as

  19. Integrating Satellite, Radar and Surface Observation with Time and Space Matching

    Science.gov (United States)

    Ho, Y.; Weber, J.

    2015-12-01

    The Integrated Data Viewer (IDV) from Unidata is a Java™-based software framework for analyzing and visualizing geoscience data. It brings together the ability to display and work with satellite imagery, gridded data, surface observations, balloon soundings, NWS WSR-88D Level II and Level III RADAR data, and NOAA National Profiler Network data, all within a unified interface. Applying time and space matching on the satellite, radar and surface observation datasets will automatically synchronize the display from different data sources and spatially subset to match the display area in the view window. These features allow the IDV users to effectively integrate these observations and provide 3 dimensional views of the weather system to better understand the underlying dynamics and physics of weather phenomena.

  20. Fusing Multiple Satellite Datasets Toward Defining and Understanding Organized Convection

    Science.gov (United States)

    Elsaesser, G.; Del Genio, A. D.

    2017-12-01

    How do we differentiate unorganized from organized convection? We might think of organized convection as being long lasting (at least longer than the lifetime of any individual cumulus cell), clustered at larger spatial scales (>100 km), and responsible for substantial rainfall accumulation. Organized convection is sustained on such scales due to the arrangement of moist/dry and buoyant/non-buoyant mesoscale circulations. The nature of these circulations is tied to system diabatic heating profiles; in particular, the 2nd baroclinic (top-heavy), stratiform heating mode is thought to be important for organized convection maintenance/propagation. We investigate the extent to which these characteristics are jointly found in propagating convective systems. Lifecycle information comes from hi-res IR data. Diabatic heating profiles, convective fractions and rainfall are provided by GPM retrievals mapped to convective system tracks. Moisture is provided by AIRS/AMSU and passive microwave retrievals. Instead of compositing heating profile information along a system track, where information is smoothed out, we sort system heating profile structures according to their "top heaviness" and then analyze PDFs of system rainfall, system sizes, durations, convective/stratiform ratios, etc. as a function of diabatic heating structure. Perhaps contrary to expectation, we find only small differences in PDFs of rainfall rates, system sizes, and system duration for different heating profile structures. If organization is defined according to heating structures, then one possible interpretation of these results is that organization is independent of system size, duration, and many times, even lifecycle stage. Is it possible that most systems "hobble" along and exhibit varying degrees of organization, dependent on local environment moisture/buoyancy variations, unlike the archetypical MCS paradigm? This presentation will also discuss the questions posed above within the context of

  1. Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

    Science.gov (United States)

    Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

    2009-01-01

    We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

  2. The effects of thoughts of survival and thoughts of death on recall in the adaptive memory paradigm.

    Science.gov (United States)

    Klein, Stanley B

    2014-01-01

    In a recent paper Hart and Burns (2012) presented evidence that conditions that prime thoughts of one's mortality benefit recall. Drawing on the conceptual relation between thoughts of death and thoughts of survival, Hart and Burns interpret their findings as suggestive of the possibility that death-related thoughts function in manner similar to survival-related thoughts in enhancing recall. In the present study I draw on evolutionary arguments to question whether a conceptual relation between thoughts of death and thoughts of survival translates into a functional relation. I then present data showing that while death-related thoughts can promote high levels of recall, (a) the level achieved does not match that produced by survival processing and (b) survival and death cognition likely rely on different mechanisms to achieve their effects.

  3. Improving AfriPop dataset with settlement extents extracted from RapidEye for the border region comprising South-Africa, Swaziland and Mozambique

    Directory of Open Access Journals (Sweden)

    Julie Deleu

    2015-11-01

    Full Text Available For modelling the spatial distribution of malaria incidence, accurate and detailed information on population size and distribution are of significant importance. Different, global, spatial, standard datasets of population distribution have been developed and are widely used. However, most of them are not up-to-date and the low spatial resolution of the input census data has limitations for contemporary, national- scale analyses. The AfriPop project, launched in July 2009, was initiated with the aim of producing detailed, contemporary and easily updatable population distribution datasets for the whole of Africa. High-resolution satellite sensors can help to further improve this dataset through the generation of high-resolution settlement layers at greater spatial details. In the present study, the settlement extents included in the MALAREO land use classification were used to generate an enhanced and updated version of the AfriPop dataset for the study area covering southern Mozambique, eastern Swaziland and the malarious part of KwaZulu-Natal in South Africa. Results show that it is possible to easily produce a detailed and updated population distribution dataset applying the AfriPop modelling approach with the use of high-resolution settlement layers and population growth rates. The 2007 and 2011 population datasets are freely available as a product of the MALAREO project and can be downloaded from the project website.

  4. Open University Learning Analytics dataset.

    Science.gov (United States)

    Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

    2017-11-28

    Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

  5. Are satellite products good proxies for gauge precipitation over Singapore?

    Science.gov (United States)

    Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

    2018-05-01

    The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate

  6. Goddard Satellite-Based Surface Turbulent Fluxes, 0.25x0.25 deg, Daily Grid, V3, (GSSTF_F14) V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr....

  7. An orbit determination algorithm for small satellites based on the magnitude of the earth magnetic field

    Science.gov (United States)

    Zagorski, P.; Gallina, A.; Rachucki, J.; Moczala, B.; Zietek, S.; Uhl, T.

    2018-06-01

    Autonomous attitude determination systems based on simple measurements of vector quantities such as magnetic field and the Sun direction are commonly used in very small satellites. However, those systems always require knowledge of the satellite position. This information can be either propagated from orbital elements periodically uplinked from the ground station or measured onboard by dedicated global positioning system (GPS) receiver. The former solution sacrifices satellite autonomy while the latter requires additional sensors which may represent a significant part of mass, volume, and power budget in case of pico- or nanosatellites. Hence, it is thought that a system for onboard satellite position determination without resorting to GPS receivers would be useful. In this paper, a novel algorithm for determining the satellite orbit semimajor-axis is presented. The methods exploit only the magnitude of the Earth magnetic field recorded onboard by magnetometers. This represents the first step toward an extended algorithm that can determine all orbital elements of the satellite. The method is validated by numerical analysis and real magnetic field measurements.

  8. Evaluating soil moisture retrievals from ESA’s SMOS and NASA’s SMAP brightness temperature datasets

    Science.gov (United States)

    Al-Yaari, A.; Wigneron, J.-P.; Kerr, Y.; Rodriguez-Fernandez, N.; O’Neill, P. E.; Jackson, T. J.; De Lannoy, G.J.M.; Al Bitar, A; Mialon, A.; Richaume, P.; Walker, JP; Mahmoodi, A.; Yueh, S.

    2018-01-01

    Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d’études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 – 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in

  9. Developing a Resource for Implementing ArcSWAT Using Global Datasets

    Science.gov (United States)

    Taggart, M.; Caraballo Álvarez, I. O.; Mueller, C.; Palacios, S. L.; Schmidt, C.; Milesi, C.; Palmer-Moloney, L. J.

    2015-12-01

    This project developed a comprehensive user manual outlining methods for adapting and implementing global datasets for use within ArcSWAT for international and worldwide applications. The Soil and Water Assessment Tool (SWAT) is a hydrologic model that looks at a number of hydrologic variables including runoff and the chemical makeup of water at a given location on the Earth's surface using Digital Elevation Models (DEM), land cover, soil, and weather data. However, the application of ArcSWAT for projects outside of the United States is challenging as there is no standard framework for inputting global datasets into ArcSWAT. This project aims to remove this obstacle by outlining methods for adapting and implementing these global datasets via the user manual. The manual takes the user through the processes of data conditioning while providing solutions and suggestions for common errors. The efficacy of the manual was explored using examples from watersheds located in Puerto Rico, Mexico and Western Africa. Each run explored the various options for setting up a ArcSWAT project as well as a range of satellite data products and soil databases. Future work will incorporate in-situ data for validation and calibration of the model and outline additional resources to assist future users in efficiently implementing the model for worldwide applications. The capacity to manage and monitor freshwater availability is of critical importance in both developed and developing countries. As populations grow and climate changes, both the quality and quantity of freshwater are affected resulting in negative impacts on the health of the surrounding population. The use of hydrologic models such as ArcSWAT can help stakeholders and decision makers understand the future impacts of these changes enabling informed and substantiated decisions.

  10. Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

    Directory of Open Access Journals (Sweden)

    Nobuoto Nojima

    2010-09-01

    Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

  11. Inter-satellite calibration of FengYun 3 medium energy electron fluxes with POES electron measurements

    Science.gov (United States)

    Zhang, Yang; Ni, Binbin; Xiang, Zheng; Zhang, Xianguo; Zhang, Xiaoxin; Gu, Xudong; Fu, Song; Cao, Xing; Zou, Zhengyang

    2018-05-01

    We perform an L-shell dependent inter-satellite calibration of FengYun 3 medium energy electron measurements with POES measurements based on rough orbital conjunctions within 5 min × 0.1 L × 0.5 MLT. By comparing electron flux data between the U.S. Polar Orbiting Environmental Satellites (POES) and Chinese sun-synchronous satellites including FY-3B and FY-3C for a whole year of 2014, we attempt to remove less reliable data and evaluate systematic uncertainties associated with the FY-3B and FY-3C datasets, expecting to quantify the inter-satellite calibration factors for the 150-350 keV energy channel at L = 2-7. Compared to the POES data, the FY-3B and FY-3C data generally exhibit a similar trend of electron flux variations but more or less underestimate them within a factor of 5 for the medium electron energy 150-350 keV channel. Good consistency in the flux conjunctions after the inter-calibration procedures gives us certain confidence to generalize our method to calibrate electron flux measurements from various satellite instruments.

  12. The survey on data format of Earth observation satellite data at JAXA.

    Science.gov (United States)

    Matsunaga, M.; Ikehata, Y.

    2017-12-01

    JAXA's earth observation satellite data are distributed by a portal web site for search and deliver called "G-Portal". Users can download the satellite data of GPM, TRMM, Aqua, ADEOS-II, ALOS (search only), ALOS-2 (search only), MOS-1, MOS-1b, ERS-1 and JERS-1 from G-Portal. However, these data formats are different by each satellite like HDF4, HDF5, NetCDF4, CEOS, etc., and which formats are not familiar to new data users. Although the HDF type self-describing format is very convenient and useful for big dataset information, old-type format product is not readable by open GIS tool nor apply OGC standard. Recently, the satellite data are widely used to be applied to the various needs such as disaster, earth resources, monitoring the global environment, Geographic Information System(GIS) and so on. In order to remove a barrier of using Earth Satellite data for new community users, JAXA has been providing the format-converted product like GeoTIFF or KMZ. In addition, JAXA provides format conversion tool itself. We investigate the trend of data format for data archive, data dissemination and data utilization, then we study how to improve the current product format for various application field users and make a recommendation for new product.

  13. Modeling and Assessment of Precise Time Transfer by Using BeiDou Navigation Satellite System Triple-Frequency Signals

    Directory of Open Access Journals (Sweden)

    Rui Tu

    2018-03-01

    Full Text Available This study proposes two models for precise time transfer using the BeiDou Navigation Satellite System triple-frequency signals: ionosphere-free (IF combined precise point positioning (PPP model with two dual-frequency combinations (IF-PPP1 and ionosphere-free combined PPP model with a single triple-frequency combination (IF-PPP2. A dataset with a short baseline (with a common external time frequency and a long baseline are used for performance assessments. The results show that IF-PPP1 and IF-PPP2 models can both be used for precise time transfer using BeiDou Navigation Satellite System (BDS triple-frequency signals, and the accuracy and stability of time transfer is the same in both cases, except for a constant system bias caused by the hardware delay of different frequencies, which can be removed by the parameter estimation and prediction with long time datasets or by a priori calibration.

  14. Manic thinking: independent effects of thought speed and thought content on mood.

    Science.gov (United States)

    Pronin, Emily; Wegner, Daniel M

    2006-09-01

    This experiment found that the speed of thought affects mood. Thought speed was manipulated via participants' paced reading of statements designed to induce either an elated or a depressed mood. Participants not only experienced more positive mood in response to elation than in response to depression statements, but also experienced an independent increase in positive mood when they had been thinking fast rather than slow--for both elation and depression statements. This effect of thought speed extended beyond mood to other experiences often associated with mania (i.e., feelings of power, feelings of creativity, a heightened sense of energy, and inflated self-esteem or grandiosity).

  15. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    Science.gov (United States)

    Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

    2014-12-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  16. Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

    Science.gov (United States)

    Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.; hide

    2014-01-01

    Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-­-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-­-real time globally from both geostationary (GEO) and low-­-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

  17. Extracting Prior Distributions from a Large Dataset of In-Situ Measurements to Support SWOT-based Estimation of River Discharge

    Science.gov (United States)

    Hagemann, M.; Gleason, C. J.

    2017-12-01

    The upcoming (2021) Surface Water and Ocean Topography (SWOT) NASA satellite mission aims, in part, to estimate discharge on major rivers worldwide using reach-scale measurements of stream width, slope, and height. Current formalizations of channel and floodplain hydraulics are insufficient to fully constrain this problem mathematically, resulting in an infinitely large solution set for any set of satellite observations. Recent work has reformulated this problem in a Bayesian statistical setting, in which the likelihood distributions derive directly from hydraulic flow-law equations. When coupled with prior distributions on unknown flow-law parameters, this formulation probabilistically constrains the parameter space, and results in a computationally tractable description of discharge. Using a curated dataset of over 200,000 in-situ acoustic Doppler current profiler (ADCP) discharge measurements from over 10,000 USGS gaging stations throughout the United States, we developed empirical prior distributions for flow-law parameters that are not observable by SWOT, but that are required in order to estimate discharge. This analysis quantified prior uncertainties on quantities including cross-sectional area, at-a-station hydraulic geometry width exponent, and discharge variability, that are dependent on SWOT-observable variables including reach-scale statistics of width and height. When compared against discharge estimation approaches that do not use this prior information, the Bayesian approach using ADCP-derived priors demonstrated consistently improved performance across a range of performance metrics. This Bayesian approach formally transfers information from in-situ gaging stations to remote-sensed estimation of discharge, in which the desired quantities are not directly observable. Further investigation using large in-situ datasets is therefore a promising way forward in improving satellite-based estimates of river discharge.

  18. Exploring Thought Leadership, Thought Liberation and Critical ...

    African Journals Online (AJOL)

    Council for the Development of Social Science Research in Africa, 2015 ... peripheral position that the African continent occupies in the global ... Gumede: Exploring Thought Leadership, and Critical Consciousness ... and seemingly incapable of creative endeavours. ...... origin', Journal of Peace Research 9 (2): 105–20.

  19. Psychopathology and Thought Suppression: A Quantitative Review

    Science.gov (United States)

    Magee, Joshua C.; Harden, K. Paige; Teachman, Bethany A.

    2012-01-01

    Recent theories of psychopathology have suggested that thought suppression intensifies the persistence of intrusive thoughts, and proposed that difficulty with thought suppression may differ between groups with and without psychopathology. The current meta-analytic review evaluates empirical evidence for difficulty with thought suppression as a function of the presence and specific type of psychopathology. Based on theoretical proposals from the psychopathology literature, diagnosed and analogue samples were expected to show greater recurrence of intrusive thoughts during thought suppression attempts than non-clinical samples. However, results showed no overall differences in the recurrence of thoughts due to thought suppression between groups with and without psychopathology. There was, nevertheless, variation in the recurrence of thoughts across different forms of psychopathology, including relatively less recurrence during thought suppression for samples with symptoms of Obsessive-Compulsive Disorder, compared to non-clinical samples. However, these differences were typically small and provided only mixed support for existing theories. Implications for cognitive theories of intrusive thoughts are discussed, including proposed mechanisms underlying thought suppression. PMID:22388007

  20. Applying NASA Imaging Radar Datasets to Investigate the Geomorphology of the Amazon's Planalto

    Science.gov (United States)

    McDonald, K. C.; Campbell, K.; Islam, R.; Alexander, P. M.; Cracraft, J.

    2016-12-01

    The Amazon basin is a biodiversity rich biome and plays a significant role into shaping Earth's climate, ocean and atmospheric gases. Understanding the history of the formation of this basin is essential to our understanding of the region's biodiversity and its response to climate change. During March 2013, the NASA/JPL L-band polarimetric airborne imaging radar, UAVSAR, conducted airborne studies over regions of South America including portions of the western Amazon basin. We utilize UAVSAR imagery acquired during that time over the Planalto, in the Madre de Dios region of southeastern Peru in an assessment of the underlying geomorphology, its relationship to the current distribution of vegetation, and its relationship to geologic processes through deep time. We employ UAVSAR data collections to assess the utility of these high quality imaging radar data for use in identifying geomorphologic features and vegetation communities within the context of improving the understanding of evolutionary processes, and their utility in aiding interpretation of datasets from Earth-orbiting satellites to support a basin-wide characterization across the Amazon. We derive maps of landcover and river branching structure from UAVSAR imagery. We compare these maps to those derived using imaging radar datasets from the Japanese Space Agency's ALOS PALSAR and Digital Elevation Models (DEMs) from NASA's Shuttle Radar Topography Mission (SRTM). Results provide an understanding of the underlying geomorphology of the Amazon planalto as well as its relationship to geologic processes and will support interpretation of the evolutionary history of the Amazon Basin. Portions of this work have been carried out within the framework of the ALOS Kyoto & Carbon Initiative. PALSAR data were provided by JAXA/EORC and the Alaska Satellite Facility.This work is carried out with support from the NASA Biodiversity Program and the NSF DIMENSIONS of Biodiversity Program.

  1. Applying Advances in GPM Radiometer Intercalibration and Algorithm Development to a Long-Term TRMM/GPM Global Precipitation Dataset

    Science.gov (United States)

    Berg, W. K.

    2016-12-01

    The Global Precipitation Mission (GPM) Core Observatory, which was launched in February of 2014, provides a number of advances for satellite monitoring of precipitation including a dual-frequency radar, high frequency channels on the GPM Microwave Imager (GMI), and coverage over middle and high latitudes. The GPM concept, however, is about producing unified precipitation retrievals from a constellation of microwave radiometers to provide approximately 3-hourly global sampling. This involves intercalibration of the input brightness temperatures from the constellation radiometers, development of an apriori precipitation database using observations from the state-of-the-art GPM radiometer and radars, and accounting for sensor differences in the retrieval algorithm in a physically-consistent way. Efforts by the GPM inter-satellite calibration working group, or XCAL team, and the radiometer algorithm team to create unified precipitation retrievals from the GPM radiometer constellation were fully implemented into the current version 4 GPM precipitation products. These include precipitation estimates from a total of seven conical-scanning and six cross-track scanning radiometers as well as high spatial and temporal resolution global level 3 gridded products. Work is now underway to extend this unified constellation-based approach to the combined TRMM/GPM data record starting in late 1997. The goal is to create a long-term global precipitation dataset employing these state-of-the-art calibration and retrieval algorithm approaches. This new long-term global precipitation dataset will incorporate the physics provided by the combined GPM GMI and DPR sensors into the apriori database, extend prior TRMM constellation observations to high latitudes, and expand the available TRMM precipitation data to the full constellation of available conical and cross-track scanning radiometers. This combined TRMM/GPM precipitation data record will thus provide a high-quality high

  2. Relationships between thought-action fusion, thought suppression and obsessive-compulsive symptoms: a structural equation modeling approach.

    Science.gov (United States)

    Rassin, E; Muris, P; Schmidt, H; Merckelbach, H

    2000-09-01

    Research has shown that there are strong similarities in content between the obsessions and compulsions that characterize obsessive-compulsive disorder and nonclinical obsessions and compulsions. However, clinical and nonclinical obsessions and compulsions do differ with respect to characteristics like frequency, intensity, discomfort and elicited resistance. Two separate concepts have been invoked to explain how normal obsessions and compulsions may develop into clinical phenomena. First, it is suggested that thought-action fusion (TAF) contributes to obsessive-compulsive symptoms. Second, thought suppression may intensify obsessive-compulsive symptoms due to its paradoxical effect on intrusive thoughts. Although both phenomena have been found to contribute to obsessive-compulsive symptoms, possible interactions between these two have never been investigated. The current study explored how TAF and thought suppression interact in the development of obsessive-compulsive symptoms. Undergraduate psychology students (N = 173) completed questionnaires pertaining to TAF, thought suppression and obsessive-compulsive symptoms. Covariances between the scores on these questionnaires were analyzed by means of structural equation modeling. Results suggest that TAF triggers thought suppression, while thought suppression, in turn, promotes obsessive-compulsive symptoms.

  3. The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

    Science.gov (United States)

    Wang, N.; Yang, R.

    2018-04-01

    Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

  4. Daily disaggregation of simulated monthly flows using different rainfall datasets in southern Africa

    Directory of Open Access Journals (Sweden)

    D.A. Hughes

    2015-09-01

    New hydrological insights for the region: There are substantial regional differences in the success of the monthly hydrological model, which inevitably affects the success of the daily disaggregation results. There are also regional differences in the success of using global rainfall data sets (Climatic Research Unit (CRU datasets for monthly, National Oceanic and Atmospheric Administration African Rainfall Climatology, version 2 (ARC2 satellite data for daily. The overall conclusion is that the disaggregation method presents a parsimonious approach to generating daily flow simulations from existing monthly simulations and that these daily flows are likely to be useful for some purposes (e.g. water quality modelling, but less so for others (e.g. peak flow analysis.

  5. How Does Mediterranean Basin's Atmosphere Become Weak Moisture Source During Negative Phase of NAO: Use of AIRS, AMSR, TOVS, & TRMM Satellite Datasets Over Last Two NAO Cycles to Examine Governing Controls on E-P

    Science.gov (United States)

    Smith, Eric A.; Mehta, Amita V.

    2008-01-01

    The Mediterranean Sea is a noted 'concentration" basin in that it almost continuously exhibits positive evaporation minus precipitation (E - P ) properties -- throughout the four seasons and from one year to the next. Nonetheless, according to the ECMWF Era-40 48-year (1958-2005) climate reanalysis dataset, for various phases of the North Atlantic Oscillation (NAO) when the pressure gradient between Portugal and Iceland becomes either very relaxed (large negative NAO-Index) or in transition (small positive or negative NAO-Index), the atmospheric moisture source properties of the basin become weak, at times even reversed for several months (i.e., negative E - P). This behavior poses numerous questions concerning how and why these events occur. Moreover, it begs the question of what it would take for the basin to reach its tipping point in which P would exceed E throughout the rainy season (some six months) on an annually persistent basis -- and the sea would possibly transform to a recurring "dilution" basin. This talk investigates these questions by: (1) establishing over a period from 1979 to present, based on detailed analyses of satellite retrieval products from a combination of NASA-AQUA, NOAA-LEO, NASA/JAXA Scatterometer, and NASA-TRMM platforms, plus additional specialized satellite data products and ancillary meteorological datasets, the actual observation-based behavior of E - P, (2) diagnosing the salient physical and meteorological mechanisms that lead to the weaker E - P events during the analysis period, partly based on analyzing surface and upper air data at discrete stations in the western and eastern Mediterranean -- while at the same time evaluating the quality of the ERA-40 data over this same time period, (3) conducting GCM and high-resolution regional modeling experiments to determine if perturbed but realistic meteorological background conditions could maintain Mediterranean as a "dilution" basin through the October to March rainy season on

  6. Responsibility, thought-action fusion, and thought suppression in Turkish patients with obsessive-compulsive disorder.

    Science.gov (United States)

    Yorulmaz, O; Karanci, A N; Bastug, B; Kisa, C; Goka, E

    2008-03-01

    Although an inflated sense of responsibility, thought-action fusion, and thought suppression are influential factors in cognitive models of obsessive-compulsive disorder (OCD), their impact on OCD has generally been demonstrated in samples from Western countries. The aim of the present study is to evaluate these cognitive factors in Turkish patients with OCD, other anxiety disorders, and community controls. Group comparisons showed that responsibility based on self-dangerousness and thought suppression significantly distinguished OCD patients from patients with other anxiety disorders and controls. Moreover, correlation and discriminant function analyses indicated that thought-action fusion in morality and likelihood was also associated with OCD symptoms. The present findings provide support for the international validity and specificity of cognitive factors and model for OCD.

  7. Gigantic Jets and the Tropical Paradigm: A Satellite Perspective

    Science.gov (United States)

    Lazarus, S. M.; Splitt, M. E.

    2017-12-01

    While not exclusively oceanic, gigantic jets (GJ) appear to have a preference for the tropical environment. In particular, a number of GJs have been observed in conjunction with tropical disturbances (i.e., weak tropical storms, depressions, and remnant lows). Given the remote aspect of TC convection and general lack of radar coverage, we explore this subset of events via analysis of their infrared and water vapor satellite presentations. The satellite perspective is relevant given that storm top mixing (dilution) of charge associated with storm-scale turbulence in this portion of the storm is thought to be connected to GJs. The thunderstorm overshoot, upper level divergence / outflow are examined in an effort to better understand the tropical paradigm. Specifically, an analysis of cloud top temperature, anvil expansion rates and asymmetries as well as placement of the GJ events with respect to the large (storm) scale circulation will be conducted.

  8. The role of satellite remote sensing in structured ecosystem risk assessments.

    Science.gov (United States)

    Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

    2018-04-01

    The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

    Science.gov (United States)

    Nedoluha, Gerald E.; Kiefer, Michael; Lossow, Stefan; Gomez, R. Michael; Kämpfer, Niklaus; Lainer, Martin; Forkman, Peter; Christensen, Ole Martin; Oh, Jung Jin; Hartogh, Paul; Anderson, John; Bramstedt, Klaus; Dinelli, Bianca M.; Garcia-Comas, Maya; Hervig, Mark; Murtagh, Donal; Raspollini, Piera; Read, William G.; Rosenlof, Karen; Stiller, Gabriele P.; Walker, Kaley A.

    2017-12-01

    As part of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically ˜ 1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0-1 % yr-1. In particular, MLS shows a trend of between 0.5 % yr-1 and 0.7 % yr-1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr-1 (at Mauna Loa, Hawaii) and -0.1 % yr-1 (at Lauder, New Zealand).

  10. The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

    Directory of Open Access Journals (Sweden)

    G. E. Nedoluha

    2017-12-01

    Full Text Available As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate water vapor assessment (WAVAS-II, we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii and −0.1 % yr−1 (at Lauder, New Zealand.

  11. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  12. Mridangam stroke dataset

    OpenAIRE

    CompMusic

    2014-01-01

    The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. /n/nA detailed description of the Mridangam and its strokes can be found in the paper below. A part of the dataset was used in the following paper. /nAkshay Anantapadman...

  13. 2008 TIGER/Line Nationwide Dataset

    Data.gov (United States)

    California Natural Resource Agency — This dataset contains a nationwide build of the 2008 TIGER/Line datasets from the US Census Bureau downloaded in April 2009. The TIGER/Line Shapefiles are an extract...

  14. A re-analysis of the Lake Suigetsu terrestrial radiocarbon calibration dataset

    International Nuclear Information System (INIS)

    Staff, R.A.; Bronk Ramsey, C.; Nakagawa, T.

    2010-01-01

    Lake Suigetsu, Honshu Island, Japan provides an ideal sedimentary sequence from which to derive a wholly terrestrial radiocarbon calibration curve back to the limits of radiocarbon detection (circa 60 ka bp). The presence of well-defined, annually-deposited laminae (varves) throughout the entirety of this period provides an independent, high resolution chronometer against which radiocarbon measurements of plant macrofossils from the sediment column can be directly related. However, data from the initial Lake Suigetsu project were found to diverge significantly from alternative, marine-based calibration datasets released around the same time (e.g. ). The main source of this divergence is thought to be the result of inaccuracies in the absolute age profile of the Suigetsu project, caused by both varve counting uncertainties and gaps in the sediment column of unknown duration between successively-drilled core sections. Here, a re-analysis of the previously-published Lake Suigetsu data is conducted. The most recent developments in Bayesian statistical modelling techniques (OxCal v4.1; ) are implemented to fit the Suigetsu data to the latest radiocarbon calibration datasets and thereby estimate the duration of the inter-core section gaps in the Suigetsu data. In this way, the absolute age of the Lake Suigetsu sediment profile is more accurately defined, providing significant information for both radiocarbon calibration and palaeoenvironmental reconstruction purposes.

  15. Design of an audio advertisement dataset

    Science.gov (United States)

    Fu, Yutao; Liu, Jihong; Zhang, Qi; Geng, Yuting

    2015-12-01

    Since more and more advertisements swarm into radios, it is necessary to establish an audio advertising dataset which could be used to analyze and classify the advertisement. A method of how to establish a complete audio advertising dataset is presented in this paper. The dataset is divided into four different kinds of advertisements. Each advertisement's sample is given in *.wav file format, and annotated with a txt file which contains its file name, sampling frequency, channel number, broadcasting time and its class. The classifying rationality of the advertisements in this dataset is proved by clustering the different advertisements based on Principal Component Analysis (PCA). The experimental results show that this audio advertisement dataset offers a reliable set of samples for correlative audio advertisement experimental studies.

  16. Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

    Science.gov (United States)

    Garraín, Daniel; Fazio, Simone; de la Rúa, Cristina; Recchioni, Marco; Lechón, Yolanda; Mathieux, Fabrice

    2015-01-01

    The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.

  17. An Attempt to automate the lithological classification of rocks using geological, gamma-spectrometric and satellite image datasets

    International Nuclear Information System (INIS)

    Fouad, M. K.; Mielik, M. L.; Gharieb, A. N.

    2004-01-01

    The present study aims essentially at proving that the application of the integrated airborne gamma spectrometric and satellite image data is capable of refining the mapped surface geology, and identification of anomalous zones of radioelement content that could provide favorable exploration targets for radioactive mineralizations.The application of the appropriate statistical technique to correlate between satellite image data and gamma-spectrometric data is of great significance in this respect. Experience shows that Landsat T M data in 7 spectral bands are successfully used in such studies rather than MSS. Multivariate statistical analysis techniques are applied to airborne spectrometric and different spectral Landsat T M data. Reduction of the data from n-dimensionality, both qualitatively as color composite image, and quantitatively, as principal component analysis, is performed using some statistical control parameters. This technique shows distinct efficiency in defining areas where different lit ho facies occur. An area located at the north of the Eastern Desert of Egypt, north of Hurgada town, was chosen to test the proposed technique of integrated interpretation of data of different physical nature. The reduced data are represented and interpreted both qualitatively and quantitatively. The advantages and limitations of applying such technique to the different airborne spectrometric, and Landsat T M data are identified. (authors)

  18. A European satellite-derived UV climatology available for impact studies

    International Nuclear Information System (INIS)

    Verdebout, J.

    2004-01-01

    This paper presents a satellite-derived climatology of the surface UV radiation, intended to support impact studies on the environment and human health. As of today, the dataset covers the period from 1 January 1984 to 31 August 2003, with daily dose maps covering Europe with a spatial resolution of 0.05 deg.. A comparison between the modelled erythemal daily dose and measurements in Ispra yields an r.m.s value with a relative difference of 29% and a bias of 3%. The seemingly large dispersion is, however, due to a restricted number of days for which the relative difference is very high. The climatological dataset documents systematic patterns in the geographical distribution of the surface UV radiation due to cloudiness, altitude and snow. It also shows a large year-to-year variability in monthly doses of up to ±50% in spring and ±30% in summer. (authors)

  19. Causal relationships between solar proton events and single event upsets for communication satellites

    Science.gov (United States)

    Lohmeyer, W. Q.; Cahoy, K.; Liu, Shiyang

    In this work, we analyze a historical archive of single event upsets (SEUs) maintained by Inmarsat, one of the world's leading providers of global mobile satellite communications services. Inmarsat has operated its geostationary communication satellites and collected extensive satellite anomaly and telemetry data since 1990. Over the course of the past twenty years, the satellites have experienced more than 226 single event upsets (SEUs), a catch-all term for anomalies that occur in a satellite's electronics such as bit-flips, trips in power supplies, and memory changes in attitude control systems. While SEUs are seemingly random and difficult to predict, we correlate their occurrences to space weather phenomena, and specifically show correlations between SEUs and solar proton events (SPEs). SPEs are highly energetic protons that originate from solar coronal mass ejections (CMEs). It is thought that when these particles impact geostationary (GEO) satellites they can cause SEUs as well as solar array degradation. We calculate the associated statistical correlations that each SEU occurs within one day, one week, two weeks, and one month of 10 MeV SPEs between 10 - 10,000 particle flux units (pfu). However, we find that SPEs are most prevalent at solar maximum and that the SEUs on Inmarsat's satellites occur out of phase with the solar maximum. Ultimately, this suggests that SPEs are not the primary cause of the Inmarsat SEUs. A better understanding of the causal relationship between SPEs and SEUs will help the satellite communications industry develop component and operational space weather mitigation techniques as well as help the space weather community to refine radiation models.

  20. The GTZAN dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge...... of GTZAN, and provide a catalog of its faults. We review how GTZAN has been used in MGR research, and find few indications that its faults have been known and considered. Finally, we rigorously study the effects of its faults on evaluating five different MGR systems. The lesson is not to banish GTZAN...

  1. Validation of a Meteosat Second Generation solar radiation dataset over the northeastern Iberian Peninsula

    Directory of Open Access Journals (Sweden)

    J. Cristóbal

    2013-01-01

    Full Text Available Solar radiation plays a key role in the Earth's energy balance and is used as an essential input data in radiation-based evapotranspiration (ET models. Accurate gridded solar radiation data at high spatial and temporal resolution are needed to retrieve ET over large domains. In this work we present an evaluation at hourly, daily and monthly time steps and regional scale (Catalonia, NE Iberian Peninsula of a satellite-based solar radiation product developed by the Land Surface Analysis Satellite Application Facility (LSA SAF using data from the Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI. Product performance and accuracy were evaluated for datasets segmented into two terrain classes (flat and hilly areas and two atmospheric conditions (clear and cloudy sky, as well as for the full dataset as a whole. Evaluation against measurements made with ground-based pyranometers yielded good results in flat areas with an averaged model RMSE of 65 W m−2 (19%, 34 W m−2 (9.7% and 21 W m−2 (5.6%, for hourly, daily and monthly-averaged solar radiation and including clear and cloudy sky conditions and snow or ice cover. Hilly areas yielded intermediate results with an averaged model RMSE (root mean square error of 89 W m−2 (27%, 48 W m−2 (14.5% and 32 W m−2 (9.3%, for hourly, daily and monthly time steps, suggesting the need of further improvements (e.g., terrain corrections required for retrieving localized variability in solar radiation in these areas. According to the literature, the LSA SAF solar radiation product appears to have sufficient accuracy to serve as a useful and operative input to evaporative flux retrieval models.

  2. Cross-Dataset Analysis and Visualization Driven by Expressive Web Services

    Science.gov (United States)

    Alexandru Dumitru, Mircea; Catalin Merticariu, Vlad

    2015-04-01

    The deluge of data that is hitting us every day from satellite and airborne sensors is changing the workflow of environmental data analysts and modelers. Web geo-services play now a fundamental role, and are no longer needed to preliminary download and store the data, but rather they interact in real-time with GIS applications. Due to the very large amount of data that is curated and made available by web services, it is crucial to deploy smart solutions for optimizing network bandwidth, reducing duplication of data and moving the processing closer to the data. In this context we have created a visualization application for analysis and cross-comparison of aerosol optical thickness datasets. The application aims to help researchers identify and visualize discrepancies between datasets coming from various sources, having different spatial and time resolutions. It also acts as a proof of concept for integration of OGC Web Services under a user-friendly interface that provides beautiful visualizations of the explored data. The tool was built on top of the World Wind engine, a Java based virtual globe built by NASA and the open source community. For data retrieval and processing we exploited the OGC Web Coverage Service potential: the most exciting aspect being its processing extension, a.k.a. the OGC Web Coverage Processing Service (WCPS) standard. A WCPS-compliant service allows a client to execute a processing query on any coverage offered by the server. By exploiting a full grammar, several different kinds of information can be retrieved from one or more datasets together: scalar condensers, cross-sectional profiles, comparison maps and plots, etc. This combination of technology made the application versatile and portable. As the processing is done on the server-side, we ensured that the minimal amount of data is transferred and that the processing is done on a fully-capable server, leaving the client hardware resources to be used for rendering the visualization

  3. Drought Early Warning and Agro-Meteorological Risk Assessment using Earth Observation Rainfall Datasets and Crop Water Budget Modelling

    Science.gov (United States)

    Tarnavsky, E.

    2016-12-01

    The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.

  4. On the origins of endogenous thoughts.

    Science.gov (United States)

    Tillas, Alexandros

    2017-05-01

    Endogenous thoughts are thoughts that we activate in a top-down manner or in the absence of the appropriate stimuli. We use endogenous thoughts to plan or recall past events. In this sense, endogenous thinking is one of the hallmarks of our cognitive lives. In this paper, I investigate how it is that we come to possess endogenous control over our thoughts. Starting from the close relation between language and thinking, I look into speech production-a process motorically controlled by the inferior frontal gyrus (IFG). Interestingly, IFG is also closely related to silent talking, as well as volition. The connection between IFG and volition is important given that endogenous thoughts are or at least greatly resemble voluntary actions. Against this background, I argue that IFG is key to understanding the origins of conscious endogenous thoughts. Furthermore, I look into goal-directed thinking and show that IFG plays a key role also in unconscious endogenous thinking.

  5. Beyond reliability, multi-state failure analysis of satellite subsystems: A statistical approach

    International Nuclear Information System (INIS)

    Castet, Jean-Francois; Saleh, Joseph H.

    2010-01-01

    Reliability is widely recognized as a critical design attribute for space systems. In recent articles, we conducted nonparametric analyses and Weibull fits of satellite and satellite subsystems reliability for 1584 Earth-orbiting satellites launched between January 1990 and October 2008. In this paper, we extend our investigation of failures of satellites and satellite subsystems beyond the binary concept of reliability to the analysis of their anomalies and multi-state failures. In reliability analysis, the system or subsystem under study is considered to be either in an operational or failed state; multi-state failure analysis introduces 'degraded states' or partial failures, and thus provides more insights through finer resolution into the degradation behavior of an item and its progression towards complete failure. The database used for the statistical analysis in the present work identifies five states for each satellite subsystem: three degraded states, one fully operational state, and one failed state (complete failure). Because our dataset is right-censored, we calculate the nonparametric probability of transitioning between states for each satellite subsystem with the Kaplan-Meier estimator, and we derive confidence intervals for each probability of transitioning between states. We then conduct parametric Weibull fits of these probabilities using the Maximum Likelihood Estimation (MLE) approach. After validating the results, we compare the reliability versus multi-state failure analyses of three satellite subsystems: the thruster/fuel; the telemetry, tracking, and control (TTC); and the gyro/sensor/reaction wheel subsystems. The results are particularly revealing of the insights that can be gleaned from multi-state failure analysis and the deficiencies, or blind spots, of the traditional reliability analysis. In addition to the specific results provided here, which should prove particularly useful to the space industry, this work highlights the importance

  6. Open and scalable analytics of large Earth observation datasets: From scenes to multidimensional arrays using SciDB and GDAL

    Science.gov (United States)

    Appel, Marius; Lahn, Florian; Buytaert, Wouter; Pebesma, Edzer

    2018-04-01

    Earth observation (EO) datasets are commonly provided as collection of scenes, where individual scenes represent a temporal snapshot and cover a particular region on the Earth's surface. Using these data in complex spatiotemporal modeling becomes difficult as soon as data volumes exceed a certain capacity or analyses include many scenes, which may spatially overlap and may have been recorded at different dates. In order to facilitate analytics on large EO datasets, we combine and extend the geospatial data abstraction library (GDAL) and the array-based data management and analytics system SciDB. We present an approach to automatically convert collections of scenes to multidimensional arrays and use SciDB to scale computationally intensive analytics. We evaluate the approach in three study cases on national scale land use change monitoring with Landsat imagery, global empirical orthogonal function analysis of daily precipitation, and combining historical climate model projections with satellite-based observations. Results indicate that the approach can be used to represent various EO datasets and that analyses in SciDB scale well with available computational resources. To simplify analyses of higher-dimensional datasets as from climate model output, however, a generalization of the GDAL data model might be needed. All parts of this work have been implemented as open-source software and we discuss how this may facilitate open and reproducible EO analyses.

  7. Thought and Language in Cognitive Science

    Directory of Open Access Journals (Sweden)

    Destéfano, Mariela

    2012-01-01

    Full Text Available In cognitive science, the discussion about the relations between language and thought is very heterogeneous. It involves developments on linguistics, philosophy, psychology, etc. Carruthers and Boucher (1998 identify different criteria that would organize the diversity of positions about language and thought assumed in linguistics, philosophy and psychology. One of them is the constitution thesis (CT, which establishes that language is constitutively involved in thought. In this paper I would like to show some problems of CT in order to understand the relation between language and thought in cognitive science.

  8. Combining forest inventory, satellite remote sensing, and geospatial data for mapping forest attributes of the conterminous United States

    Science.gov (United States)

    Mark Nelson; Greg Liknes; Charles H. Perry

    2009-01-01

    Analysis and display of forest composition, structure, and pattern provides information for a variety of assessments and management decision support. The objective of this study was to produce geospatial datasets and maps of conterminous United States forest land ownership, forest site productivity, timberland, and reserved forest land. Satellite image-based maps of...

  9. Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

    Science.gov (United States)

    Hlaing, Soe; Gilerson, Alexander; Harmal, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

    2012-01-01

    Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

  10. Understanding and Analyzing Latency of Near Real-time Satellite Data

    Science.gov (United States)

    Han, W.; Jochum, M.; Brust, J.

    2016-12-01

    Acquiring and disseminating time-sensitive satellite data in a timely manner is much concerned by researchers and decision makers of weather forecast, severe weather warning, disaster and emergency response, environmental monitoring, and so on. Understanding and analyzing the latency of near real-time satellite data is very useful and helpful to explore the whole data transmission flow, indentify the possible issues, and connect data providers and users better. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a central repository to acquire, manipulate, and disseminate various types of near real-time satellite datasets to internal and external users. In this system, important timestamps, including observation beginning/end, processing, uploading, downloading, and ingestion, are retrieved and organized in the database, so the time length of each transmission phase can be figured out easily. Open source NoSQL database MongoDB is selected to manage the timestamp information because of features of dynamic schema, aggregation and data processing. A user-friendly user interface is developed to visualize and characterize the latency interactively. Taking the Himawari-8 HSD (Himawari Standard Data) file as an example, the data transmission phases, including creating HSD file from satellite observation, uploading the file to HimawariCloud, updating file link in the webpage, downloading and ingesting the file to SCDR, are worked out from the above mentioned timestamps. The latencies can be observed by time of period, day of week, or hour of day in chart or table format, and the anomaly latencies can be detected and reported through the user interface. Latency analysis provides data providers and users actionable insight on how to improve the data transmission of near real-time satellite data, and enhance its acquisition and management.

  11. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying; Stein, Michael L.

    2014-01-01

    For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

  12. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying

    2014-11-07

    For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

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

    Science.gov (United States)

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

    2017-12-01

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

  14. Altered Satellite Cell Responsiveness and Denervation Implicated in Progression of Rotator-Cuff Injury.

    Directory of Open Access Journals (Sweden)

    Deanna Gigliotti

    Full Text Available Rotator-cuff injury (RCI is common and painful; even after surgery, joint stability and function may not recover. Relative contributions to atrophy from disuse, fibrosis, denervation, and satellite-cell responsiveness to activating stimuli are not known.Potential contributions of denervation and disrupted satellite cell responses to growth signals were examined in supraspinatus (SS and control (ipsilateral deltoid muscles biopsied from participants with RCI (N = 27. Biopsies were prepared for explant culture (to study satellite cell activity, immunostained to localize Pax7, BrdU, and Semaphorin 3A in satellite cells, sectioning to study blood vessel density, and western blotting to measure the fetal (γ subunit of acetylcholine receptor (γ-AchR. Principal component analysis (PCA for 35 parameters extracted components identified variables that contributed most to variability in the dataset. γ-AchR was higher in SS than control, indicating denervation. Satellite cells in SS had a low baseline level of activity (Pax7+ cells labelled in S-phase versus control; only satellite cells in SS showed increased proliferative activity after nitric oxide-donor treatment. Interestingly, satellite cell localization of Semaphorin 3A, a neuro-chemorepellent, was greater in SS (consistent with fiber denervation than control muscle at baseline. PCAs extracted components including fiber atrophy, satellite cell activity, fibrosis, atrogin-1, smoking status, vascular density, γAchR, and the time between symptoms and surgery. Use of deltoid as a control for SS was supported by PCA findings since "muscle" was not extracted as a variable in the first two principal components. SS muscle in RCI is therefore atrophic, denervated, and fibrotic, and has satellite cells that respond to activating stimuli.Since SS satellite cells can be activated in culture, a NO-donor drug combined with stretching could promote muscle growth and improve functional outcome after RCI. PCAs

  15. Altered Satellite Cell Responsiveness and Denervation Implicated in Progression of Rotator-Cuff Injury.

    Science.gov (United States)

    Gigliotti, Deanna; Leiter, Jeff R S; MacDonald, Peter B; Peeler, Jason; Anderson, Judy E

    Rotator-cuff injury (RCI) is common and painful; even after surgery, joint stability and function may not recover. Relative contributions to atrophy from disuse, fibrosis, denervation, and satellite-cell responsiveness to activating stimuli are not known. Potential contributions of denervation and disrupted satellite cell responses to growth signals were examined in supraspinatus (SS) and control (ipsilateral deltoid) muscles biopsied from participants with RCI (N = 27). Biopsies were prepared for explant culture (to study satellite cell activity), immunostained to localize Pax7, BrdU, and Semaphorin 3A in satellite cells, sectioning to study blood vessel density, and western blotting to measure the fetal (γ) subunit of acetylcholine receptor (γ-AchR). Principal component analysis (PCA) for 35 parameters extracted components identified variables that contributed most to variability in the dataset. γ-AchR was higher in SS than control, indicating denervation. Satellite cells in SS had a low baseline level of activity (Pax7+ cells labelled in S-phase) versus control; only satellite cells in SS showed increased proliferative activity after nitric oxide-donor treatment. Interestingly, satellite cell localization of Semaphorin 3A, a neuro-chemorepellent, was greater in SS (consistent with fiber denervation) than control muscle at baseline. PCAs extracted components including fiber atrophy, satellite cell activity, fibrosis, atrogin-1, smoking status, vascular density, γAchR, and the time between symptoms and surgery. Use of deltoid as a control for SS was supported by PCA findings since "muscle" was not extracted as a variable in the first two principal components. SS muscle in RCI is therefore atrophic, denervated, and fibrotic, and has satellite cells that respond to activating stimuli. Since SS satellite cells can be activated in culture, a NO-donor drug combined with stretching could promote muscle growth and improve functional outcome after RCI. PCAs suggest

  16. Editorial: Datasets for Learning Analytics

    NARCIS (Netherlands)

    Dietze, Stefan; George, Siemens; Davide, Taibi; Drachsler, Hendrik

    2018-01-01

    The European LinkedUp and LACE (Learning Analytics Community Exchange) project have been responsible for setting up a series of data challenges at the LAK conferences 2013 and 2014 around the LAK dataset. The LAK datasets consists of a rich collection of full text publications in the domain of

  17. The Geometry of Finite Equilibrium Datasets

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set...... of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely non collinear....

  18. Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

    Science.gov (United States)

    Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

    2016-04-01

    The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluate possibilities of using a wide-range of statistical modeling techniques to create synthetic archive dataset. Additionally, a robust tool for predicting the most distinguishable phenophases using only free of charge data as predictors was created. Study period covers the years 2007-2014 and contains only quality-controlled dataset of 10 species and 14 phenophases. Phenological data used in this study originates from the manual observations network run by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB). Three kind of data sources were used as predictors: (i) satellite derived products, (ii) preprocessed gridded meteorological data, and (iii) spatial properties (longitude, latitude, altitude) of the monitoring site. Moderate-Resolution Imaging Spectroradiometer (MODIS) level-3 vegetation products were used for detecting onset dates of particular phenophases. Following indices were used: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (fPAR). Additionally, Interactive Multisensor Snow and Ice Mapping System (IMS) products were chosen to detect occurrence of snow cover. Due to highly noisy data, authors decided to take into account pixel reliability information. Besides satellite derived products (NDVI, EVI, FPAR, LAI, Snow cover), a wide group of observational data and agrometeorological indices derived from the European Climate Assessment & Dataset (ECA&D) were used as a potential predictors: cumulative growing degree days (GDD), cumulative growing precipitation days (GPD

  19. Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

    Science.gov (United States)

    Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

    2016-12-01

    Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

  20. Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR Data for the Investigation of Buried Concealed Archaeological Remains

    Directory of Open Access Journals (Sweden)

    Athos Agapiou

    2017-06-01

    Full Text Available The paper investigates the superficial layers of an archaeological landscape based on the integration of various remote sensing techniques. It is well known in the literature that shallow depths may be rich in archeological remains, which generate different signal responses depending on the applied technique. In this study three main technologies are examined, namely ground-penetrating radar (GPR, ground spectroscopy, and multispectral satellite imagery. The study aims to propose a methodology to enhance optical remote sensing satellite images, intended for archaeological research, based on the integration of ground based and satellite datasets. For this task, a regression model between the ground spectroradiometer and GPR is established which is then projected to a high resolution sub-meter optical image. The overall methodology consists of nine steps. Beyond the acquirement of the in-situ measurements and their calibration (Steps 1–3, various regression models are examined for more than 70 different vegetation indices (Steps 4–5. The specific data analysis indicated that the red-edge position (REP hyperspectral index was the most appropriate for developing a local fusion model between ground spectroscopy data and GPR datasets (Step 6, providing comparable results with the in situ GPR measurements (Step 7. Other vegetation indices, such as the normalized difference vegetation index (NDVI, have also been examined, providing significant correlation between the two datasets (R = 0.50. The model is then projected to a high-resolution image over the area of interest (Step 8. The proposed methodology was evaluated with a series of field data collected from the Vésztő-Mágor Tell in the eastern part of Hungary. The results were compared with in situ magnetic gradiometry measurements, indicating common interpretation results. The results were also compatible with the preliminary archaeological investigations of the area (Step 9. The overall

  1. The merits of unconscious thought in rule detection.

    Science.gov (United States)

    Li, Jiansheng; Zhu, Yawen; Yang, Yang

    2014-01-01

    According to unconscious thought theory (UTT), unconscious thought is more adept at complex decision-making than is conscious thought. Related research has mainly focused on the complexity of decision-making tasks as determined by the amount of information provided. However, the complexity of the rules generating this information also influences decision making. Therefore, we examined whether unconscious thought facilitates the detection of rules during a complex decision-making task. Participants were presented with two types of letter strings. One type matched a grammatical rule, while the other did not. Participants were then divided into three groups according to whether they made decisions using conscious thought, unconscious thought, or immediate decision. The results demonstrated that the unconscious thought group was more accurate in identifying letter strings that conformed to the grammatical rule than were the conscious thought and immediate decision groups. Moreover, performance of the conscious thought and immediate decision groups was similar. We conclude that unconscious thought facilitates the detection of complex rules, which is consistent with UTT.

  2. The merits of unconscious thought in rule detection.

    Directory of Open Access Journals (Sweden)

    Jiansheng Li

    Full Text Available According to unconscious thought theory (UTT, unconscious thought is more adept at complex decision-making than is conscious thought. Related research has mainly focused on the complexity of decision-making tasks as determined by the amount of information provided. However, the complexity of the rules generating this information also influences decision making. Therefore, we examined whether unconscious thought facilitates the detection of rules during a complex decision-making task. Participants were presented with two types of letter strings. One type matched a grammatical rule, while the other did not. Participants were then divided into three groups according to whether they made decisions using conscious thought, unconscious thought, or immediate decision. The results demonstrated that the unconscious thought group was more accurate in identifying letter strings that conformed to the grammatical rule than were the conscious thought and immediate decision groups. Moreover, performance of the conscious thought and immediate decision groups was similar. We conclude that unconscious thought facilitates the detection of complex rules, which is consistent with UTT.

  3. Global Electric Circuit Diurnal Variation Derived from Storm Overflight and Satellite Optical Lightning Datasets

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, R. J.; Bateman, M. J.; Bailey, J. C.

    2011-01-01

    We have combined analyses of over 1000 high altitude aircraft observations of electrified clouds with diurnal lightning statistics from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to produce an estimate of the diurnal variation in the global electric circuit. Using basic assumptions about the mean storm currents as a function of flash rate and location, and the global electric circuit, our estimate of the current in the global electric circuit matches the Carnegie curve diurnal variation to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Mean contributions to the global electric circuit from land and ocean thunderstorms are 1.1 kA (land) and 0.7 kA (ocean). Contributions to the global electric circuit from ESCs are 0.22 kA for ocean storms and 0.04 kA for land storms. Using our analysis, the mean total conduction current for the global electric circuit is 2.0 kA.

  4. A Technique: Generating Alternative Thoughts

    Directory of Open Access Journals (Sweden)

    Serkan AKKOYUNLU

    2013-04-01

    Conclusion: Generating alternative explanations and balanced thoughts are the end point and important part of therapy work on automatic thoughts. When applied properly and rehearsed as homework between sessions, these methods may lead to improvement in many mental disorders. [JCBPR 2013; 2(1.000: 53-59

  5. How does thought-action fusion relate to responsibility attitudes and thought suppression to aggravate the obsessive-compulsive symptoms?

    Science.gov (United States)

    Altın, Müjgan; Gençöz, Tülin

    2011-01-01

    Comprehensive cognitive theories of obsessive compulsive disorder (OCD) propose that clinical obsessions and compulsions arise from specific sorts of dysfunctional beliefs and appraisals, such as inflated sense of responsibility, thought-action fusion (TAF), and thought suppression. The present study aimed to examine the mediator roles of responsibility and thought suppression between TAF and obsessive-compulsive symptoms. Specifically, it aimed to explore the relative effects of TAF factors (i.e. morality and likelihood) on inflated sense of responsibility and on thought suppression to increase the obsessive qualities of intrusions. Two hundred and eighty-three Turkish undergraduate students completed a battery of measures on responsibility, thought suppression, TAF, OC symptoms, and depression. A series of hierarchical regression analyses, where depressive symptoms were controlled for, indicated that TAF-morality and TAF-likelihood follow different paths toward OC symptoms. Although TAF-morality associated with inflated sense of responsibility, TAF-likelihood associated with thought suppression efforts, and in turn these factors increased OC symptoms. These findings provide support for the critical role of sense of responsibility and thought suppression between the relationship of TAF and OC symptoms. Findings were discussed in line with the literature.

  6. 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.

  7. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  8. An Annotated Dataset of 14 Meat Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given.......This note describes a dataset consisting of 14 annotated images of meat. Points of correspondence are placed on each image. As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  9. Hydrological simulation of the Brahmaputra basin using global datasets

    Science.gov (United States)

    Bhattacharya, Biswa; Conway, Crystal; Craven, Joanne; Masih, Ilyas; Mazzolini, Maurizio; Shrestha, Shreedeepy; Ugay, Reyne; van Andel, Schalk Jan

    2017-04-01

    Brahmaputra River flows through China, India and Bangladesh to the Bay of Bengal and is one of the largest rivers of the world with a catchment size of 580K km2. The catchment is largely hilly and/or forested with sparse population and with limited urbanisation and economic activities. The catchment experiences heavy monsoon rainfall leading to very high flood discharges. Large inter-annual variation of discharge leading to flooding, erosion and morphological changes are among the major challenges. The catchment is largely ungauged; moreover, limited availability of hydro-meteorological data limits the possibility of carrying out evidence based research, which could provide trustworthy information for managing and when needed, controlling, the basin processes by the riparian countries for overall basin development. The paper presents initial results of a current research project on Brahmaputra basin. A set of hydrological and hydraulic models (SWAT, HMS, RAS) are developed by employing publicly available datasets of DEM, land use and soil and simulated using satellite based rainfall products, evapotranspiration and temperature estimates. Remotely sensed data are compared with sporadically available ground data. The set of models are able to produce catchment wide hydrological information that potentially can be used in the future in managing the basin's water resources. The model predications should be used with caution due to high level of uncertainty because the semi-calibrated models are developed with uncertain physical representation (e.g. cross-section) and simulated with global meteorological forcing (e.g. TRMM) with limited validation. Major scientific challenges are seen in producing robust information that can be reliably used in managing the basin. The information generated by the models are uncertain and as a result, instead of using them per se, they are used in improving the understanding of the catchment, and by running several scenarios with varying

  10. Comparison of recent SnIa datasets

    International Nuclear Information System (INIS)

    Sanchez, J.C. Bueno; Perivolaropoulos, L.; Nesseris, S.

    2009-01-01

    We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization w(a) = w 0 +w 1 (1−a), according to their Figure of Merit (FoM), their consistency with the cosmological constant (ΛCDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with ΛCDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy (w 0 ,w 1 ) = (−1.4,2) crossing the phantom divide line w = −1 (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample

  11. SIMADL: Simulated Activities of Daily Living Dataset

    Directory of Open Access Journals (Sweden)

    Talal Alshammari

    2018-04-01

    Full Text Available With the realisation of the Internet of Things (IoT paradigm, the analysis of the Activities of Daily Living (ADLs, in a smart home environment, is becoming an active research domain. The existence of representative datasets is a key requirement to advance the research in smart home design. Such datasets are an integral part of the visualisation of new smart home concepts as well as the validation and evaluation of emerging machine learning models. Machine learning techniques that can learn ADLs from sensor readings are used to classify, predict and detect anomalous patterns. Such techniques require data that represent relevant smart home scenarios, for training, testing and validation. However, the development of such machine learning techniques is limited by the lack of real smart home datasets, due to the excessive cost of building real smart homes. This paper provides two datasets for classification and anomaly detection. The datasets are generated using OpenSHS, (Open Smart Home Simulator, which is a simulation software for dataset generation. OpenSHS records the daily activities of a participant within a virtual environment. Seven participants simulated their ADLs for different contexts, e.g., weekdays, weekends, mornings and evenings. Eighty-four files in total were generated, representing approximately 63 days worth of activities. Forty-two files of classification of ADLs were simulated in the classification dataset and the other forty-two files are for anomaly detection problems in which anomalous patterns were simulated and injected into the anomaly detection dataset.

  12. The NOAA Dataset Identifier Project

    Science.gov (United States)

    de la Beaujardiere, J.; Mccullough, H.; Casey, K. S.

    2013-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) initiated a project in 2013 to assign persistent identifiers to datasets archived at NOAA and to create informational landing pages about those datasets. The goals of this project are to enable the citation of datasets used in products and results in order to help provide credit to data producers, to support traceability and reproducibility, and to enable tracking of data usage and impact. A secondary goal is to encourage the submission of datasets for long-term preservation, because only archived datasets will be eligible for a NOAA-issued identifier. A team was formed with representatives from the National Geophysical, Oceanographic, and Climatic Data Centers (NGDC, NODC, NCDC) to resolve questions including which identifier scheme to use (answer: Digital Object Identifier - DOI), whether or not to embed semantics in identifiers (no), the level of granularity at which to assign identifiers (as coarsely as reasonable), how to handle ongoing time-series data (do not break into chunks), creation mechanism for the landing page (stylesheet from formal metadata record preferred), and others. Decisions made and implementation experience gained will inform the writing of a Data Citation Procedural Directive to be issued by the Environmental Data Management Committee in 2014. Several identifiers have been issued as of July 2013, with more on the way. NOAA is now reporting the number as a metric to federal Open Government initiatives. This paper will provide further details and status of the project.

  13. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  14. Providing Access and Visualization to Global Cloud Properties from GEO Satellites

    Science.gov (United States)

    Chee, T.; Nguyen, L.; Minnis, P.; Spangenberg, D.; Palikonda, R.; Ayers, J. K.

    2015-12-01

    Providing public access to cloud macro and microphysical properties is a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a tool and method that allows end users to easily browse and access cloud information that is otherwise difficult to acquire and manipulate. The core of the tool is an application-programming interface that is made available to the public. One goal of the tool is to provide a demonstration to end users so that they can use the dynamically generated imagery as an input into their own work flows for both image generation and cloud product requisition. This project builds upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product imagery accessible and easily searchable. As we see the increasing use of virtual supply chains that provide additional value at each link there is value in making satellite derived cloud product information available through a simple access method as well as allowing users to browse and view that imagery as they need rather than in a manner most convenient for the data provider. Using the Open Geospatial Consortium's Web Processing Service as our access method, we describe a system that uses a hybrid local and cloud based parallel processing system that can return both satellite imagery and cloud product imagery as well as the binary data used to generate them in multiple formats. The images and cloud products are sourced from multiple satellites and also "merged" datasets created by temporally and spatially matching satellite sensors. Finally, the tool and API allow users to access information that spans the time ranges that our group has information available. In the case of satellite imagery, the temporal range can span the entire lifetime of the sensor.

  15. Solar radio proxies for improved satellite orbit prediction

    Science.gov (United States)

    Yaya, Philippe; Hecker, Louis; Dudok de Wit, Thierry; Fèvre, Clémence Le; Bruinsma, Sean

    2017-12-01

    Specification and forecasting of solar drivers to thermosphere density models is critical for satellite orbit prediction and debris avoidance. Satellite operators routinely forecast orbits up to 30 days into the future. This requires forecasts of the drivers to these orbit prediction models such as the solar Extreme-UV (EUV) flux and geomagnetic activity. Most density models use the 10.7 cm radio flux (F10.7 index) as a proxy for solar EUV. However, daily measurements at other centimetric wavelengths have also been performed by the Nobeyama Radio Observatory (Japan) since the 1950's, thereby offering prospects for improving orbit modeling. Here we present a pre-operational service at the Collecte Localisation Satellites company that collects these different observations in one single homogeneous dataset and provides a 30 days forecast on a daily basis. Interpolation and preprocessing algorithms were developed to fill in missing data and remove anomalous values. We compared various empirical time series prediction techniques and selected a multi-wavelength non-recursive analogue neural network. The prediction of the 30 cm flux, and to a lesser extent that of the 10.7 cm flux, performs better than NOAA's present prediction of the 10.7 cm flux, especially during periods of high solar activity. In addition, we find that the DTM-2013 density model (Drag Temperature Model) performs better with (past and predicted) values of the 30 cm radio flux than with the 10.7 flux.

  16. Solar radio proxies for improved satellite orbit prediction

    Directory of Open Access Journals (Sweden)

    Yaya Philippe

    2017-01-01

    Full Text Available Specification and forecasting of solar drivers to thermosphere density models is critical for satellite orbit prediction and debris avoidance. Satellite operators routinely forecast orbits up to 30 days into the future. This requires forecasts of the drivers to these orbit prediction models such as the solar Extreme-UV (EUV flux and geomagnetic activity. Most density models use the 10.7 cm radio flux (F10.7 index as a proxy for solar EUV. However, daily measurements at other centimetric wavelengths have also been performed by the Nobeyama Radio Observatory (Japan since the 1950's, thereby offering prospects for improving orbit modeling. Here we present a pre-operational service at the Collecte Localisation Satellites company that collects these different observations in one single homogeneous dataset and provides a 30 days forecast on a daily basis. Interpolation and preprocessing algorithms were developed to fill in missing data and remove anomalous values. We compared various empirical time series prediction techniques and selected a multi-wavelength non-recursive analogue neural network. The prediction of the 30 cm flux, and to a lesser extent that of the 10.7 cm flux, performs better than NOAA's present prediction of the 10.7 cm flux, especially during periods of high solar activity. In addition, we find that the DTM-2013 density model (Drag Temperature Model performs better with (past and predicted values of the 30 cm radio flux than with the 10.7 flux.

  17. Control Measure Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EPA Control Measure Dataset is a collection of documents describing air pollution control available to regulated facilities for the control and abatement of air...

  18. Saturn satellites

    International Nuclear Information System (INIS)

    Ruskol, E.L.

    1981-01-01

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

  19. The Kinetics Human Action Video Dataset

    OpenAIRE

    Kay, Will; Carreira, Joao; Simonyan, Karen; Zhang, Brian; Hillier, Chloe; Vijayanarasimhan, Sudheendra; Viola, Fabio; Green, Tim; Back, Trevor; Natsev, Paul; Suleyman, Mustafa; Zisserman, Andrew

    2017-01-01

    We describe the DeepMind Kinetics human action video dataset. The dataset contains 400 human action classes, with at least 400 video clips for each action. Each clip lasts around 10s and is taken from a different YouTube video. The actions are human focussed and cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands. We describe the statistics of the dataset, how it was collected, and give some ...

  20. Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

    International Nuclear Information System (INIS)

    Hashim, M; Pour, A B; Onn, C H

    2014-01-01

    Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

  1. Comparison of CORA and EN4 in-situ datasets validation methods, toward a better quality merged dataset.

    Science.gov (United States)

    Szekely, Tanguy; Killick, Rachel; Gourrion, Jerome; Reverdin, Gilles

    2017-04-01

    CORA and EN4 are both global delayed time mode validated in-situ ocean temperature and salinity datasets distributed by the Met Office (http://www.metoffice.gov.uk/) and Copernicus (www.marine.copernicus.eu). A large part of the profiles distributed by CORA and EN4 in recent years are Argo profiles from the ARGO DAC, but profiles are also extracted from the World Ocean Database and TESAC profiles from GTSPP. In the case of CORA, data coming from the EUROGOOS Regional operationnal oserving system( ROOS) operated by European institutes no managed by National Data Centres and other datasets of profiles povided by scientific sources can also be found (Sea mammals profiles from MEOP, XBT datasets from cruises ...). (EN4 also takes data from the ASBO dataset to supplement observations in the Arctic). First advantage of this new merge product is to enhance the space and time coverage at global and european scales for the period covering 1950 till a year before the current year. This product is updated once a year and T&S gridded fields are alos generated for the period 1990-year n-1. The enhancement compared to the revious CORA product will be presented Despite the fact that the profiles distributed by both datasets are mostly the same, the quality control procedures developed by the Met Office and Copernicus teams differ, sometimes leading to different quality control flags for the same profile. Started in 2016 a new study started that aims to compare both validation procedures to move towards a Copernicus Marine Service dataset with the best features of CORA and EN4 validation.A reference data set composed of the full set of in-situ temperature and salinity measurements collected by Coriolis during 2015 is used. These measurements have been made thanks to wide range of instruments (XBTs, CTDs, Argo floats, Instrumented sea mammals,...), covering the global ocean. The reference dataset has been validated simultaneously by both teams.An exhaustive comparison of the

  2. Thought and Action in Education

    Science.gov (United States)

    Rømer, Thomas Aastrup

    2015-01-01

    In much theory there is a tendency to place thought above action, or the opposite, action over thought. The consequence of the first option is that philosophy or scientific evidence gains the upper hand in educational thinking. The consequence of the second view is that pragmatism and relativism become the dominant features. This article discusses…

  3. A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

    Science.gov (United States)

    Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

    2009-01-01

    Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

  4. A Penny for Your Thoughts: Dimensions of Thought Content and Relationships with Individual Differences in Emotional Well-Being

    Directory of Open Access Journals (Sweden)

    Jessica R Andrews-Hanna

    2013-11-01

    Full Text Available A core aspect of human cognition involves overcoming the constraints of the present environment by mentally simulating another time, place, or perspective. Although these self-generated processes confer many benefits, they can come at an important cost, and this cost is greater for some individuals than for others. Here we explore the possibility that the costs and benefits of self-generated thought depend, in part, upon its phenomenological content. To test these hypotheses, we first developed a novel thought sampling paradigm and explored normative ratings of multiple thought content variables (i.e. valence, specificity, self-relevance, etc. across a large sample of young adults. Next, we examined multi-level relationships among these content variables, and used a hierarchical clustering approach to partition self-generated thought into multiple dimensions. Finally, we investigated whether these content dimensions predicted individual differences in the costs and benefits of the experience, assessed with questionnaires measuring emotional health and wellbeing. Individuals who characterized their thoughts as more negative and more personally-significant exhibited scored higher on constructs associated with Depression and Trait Negative Affect, whereas those who characterized their thoughts as less specific scored higher on constructs linked to Rumination. In contrast, individuals who characterized their thoughts as more positive, less personally-significant, and more specific scored higher on constructs linked to improved wellbeing (Mindfulness. Collectively, these findings suggest that the content of people’s inner thoughts can 1 be productively examined, 2 be distilled into several major dimensions, and 3 account for a large portion of variability in their functional outcomes.

  5. Using modeling, satellite images and existing global datasets for rapid preliminary assessments of renewable energy resources: The case of Mali

    DEFF Research Database (Denmark)

    Nygaard, Ivan; Rasmussen, K.; Badger, Jake

    2010-01-01

    This paper presents a novel approach to the preliminary, low-cost, national-scale mapping of wind energy, solar energy and certain categories of bio-energy resources in developing countries, using Mali as an example. The methods applied make extensive use of satellite remote sensing and meteorolo...... that at the current price of about 70 US$/barrel for fossil fuels, renewable energy resources are becoming economically as well as environmentally attractive options.......This paper presents a novel approach to the preliminary, low-cost, national-scale mapping of wind energy, solar energy and certain categories of bio-energy resources in developing countries, using Mali as an example. The methods applied make extensive use of satellite remote sensing...... a competitive option. Solar energy resources are shown to be abundant in all of Mali, though the highest values are found in the south. The temporal variation is relatively limited. Bio-energy resources are also concentrated in the south, but there are small pockets of high vegetation productivity...

  6. Internationally coordinated glacier monitoring: strategy and datasets

    Science.gov (United States)

    Hoelzle, Martin; Armstrong, Richard; Fetterer, Florence; Gärtner-Roer, Isabelle; Haeberli, Wilfried; Kääb, Andreas; Kargel, Jeff; Nussbaumer, Samuel; Paul, Frank; Raup, Bruce; Zemp, Michael

    2014-05-01

    Internationally coordinated monitoring of long-term glacier changes provide key indicator data about global climate change and began in the year 1894 as an internationally coordinated effort to establish standardized observations. Today, world-wide monitoring of glaciers and ice caps is embedded within the Global Climate Observing System (GCOS) in support of the United Nations Framework Convention on Climate Change (UNFCCC) as an important Essential Climate Variable (ECV). The Global Terrestrial Network for Glaciers (GTN-G) was established in 1999 with the task of coordinating measurements and to ensure the continuous development and adaptation of the international strategies to the long-term needs of users in science and policy. The basic monitoring principles must be relevant, feasible, comprehensive and understandable to a wider scientific community as well as to policy makers and the general public. Data access has to be free and unrestricted, the quality of the standardized and calibrated data must be high and a combination of detailed process studies at selected field sites with global coverage by satellite remote sensing is envisaged. Recently a GTN-G Steering Committee was established to guide and advise the operational bodies responsible for the international glacier monitoring, which are the World Glacier Monitoring Service (WGMS), the US National Snow and Ice Data Center (NSIDC), and the Global Land Ice Measurements from Space (GLIMS) initiative. Several online databases containing a wealth of diverse data types having different levels of detail and global coverage provide fast access to continuously updated information on glacier fluctuation and inventory data. For world-wide inventories, data are now available through (a) the World Glacier Inventory containing tabular information of about 130,000 glaciers covering an area of around 240,000 km2, (b) the GLIMS-database containing digital outlines of around 118,000 glaciers with different time stamps and

  7. The Connection between the Thought of Progress and Philosophical Thinking in the West Case Study: Descartes’ Thought System

    Directory of Open Access Journals (Sweden)

    Seyed Mustafa Shahraeeni

    2015-03-01

    Full Text Available Thought of progress has been considered as one of the presuppositions of the West modernity. Having accepted this idea, we should regard it as one of the bases and foundations of early modern philosophy, and consider Descartes, known as the father of modern philosophy, as having a major role in its formation. There is a strong relationship between the West philosophical thought and the change of the idea of progress to one of the undisputed facts of the west civilization, and this issue can be seen clearly in Descartes thought system better than anywhere else. The present paper intends to show the leading position of Descartes’ thought system in the institutionalization of the concept of progress in the West philosophical system in three main parts: 1. Authority fighting and its relation with Cartesian’s Doubt, 2. The genuineness of the worldly life in Descartes’ thought system, and 3. Establishing the foundation of modern science. This article is based on the modern forerunners’ change of opinion about the philosophy mission in the world. It  makes attempt to demonstrate in order to achieve the thought of progress, some prerequisites are necessary; and these prerequisite, though not exclusively, in their best and most complete form are generally achieved in the West philosophical thought and are particularly accomplished in Descartes’ philosophy.

  8. Evaluation of the Performance of Three Satellite Precipitation Products over Africa

    Directory of Open Access Journals (Sweden)

    Aleix Serrat-Capdevila

    2016-10-01

    Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

  9. Non-erotic thoughts and sexual functioning.

    Science.gov (United States)

    Purdon, Christine; Watson, Chris

    2011-10-01

    This study sought to replicate and extend investigations of current models of sexual dysfunction (Barlow, 2002; Janssen, Everaerd, Spiering, & Janssen, 2000) which implicate factors such as spectatoring, failure to use ameliorative strategies, and information processing biases in the development and persistence of sexual difficulties. A sample of 165 (n = 71 men) undergraduates completed measures of sexual dysfunction and relationship satisfaction, and reported on the content and frequency of non-erotic thoughts during sex with a partner (i.e., spectatoring), the emotional impact of non-erotic thoughts, and the strategies used to manage them. They also reported on their main sexual functioning difficulties and the strategies they used to manage those difficulties. Finally, participants were presented with a series of hypothetical sexual scenarios and were asked to report their immediate interpretation of events in the scenario. The content of non-erotic thoughts was similar to previous work (Purdon & Holdaway, 2006), although gender differences in thought content were less pronounced. As in previous research, greater frequency of, and anxiety evoked by, non-erotic thoughts was associated with poorer sexual functioning, but we found that this was over and above relationship satisfaction. Participants both high and low in sexual functioning reported using a variety of strategies to manage their non-erotic thoughts, thought suppression being the least effective, and also used a variety of strategies to manage sexual difficulties. Poorer sexual functioning was associated with more negative interpretations of ambiguous sexual scenarios, but this was mediated by relationship satisfaction. However, positive interpretations were predicted by sexual functioning. Results were discussed in terms of their theoretical and clinical implications.

  10. Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

    Science.gov (United States)

    Sure, A.; Dikshit, O.

    2017-12-01

    Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

  11. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

    2017-04-01

    We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

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

    Science.gov (United States)

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

    2017-04-01

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

  13. Low-effort thought promotes political conservatism.

    Science.gov (United States)

    Eidelman, Scott; Crandall, Christian S; Goodman, Jeffrey A; Blanchar, John C

    2012-06-01

    The authors test the hypothesis that low-effort thought promotes political conservatism. In Study 1, alcohol intoxication was measured among bar patrons; as blood alcohol level increased, so did political conservatism (controlling for sex, education, and political identification). In Study 2, participants under cognitive load reported more conservative attitudes than their no-load counterparts. In Study 3, time pressure increased participants' endorsement of conservative terms. In Study 4, participants considering political terms in a cursory manner endorsed conservative terms more than those asked to cogitate; an indicator of effortful thought (recognition memory) partially mediated the relationship between processing effort and conservatism. Together these data suggest that political conservatism may be a process consequence of low-effort thought; when effortful, deliberate thought is disengaged, endorsement of conservative ideology increases.

  14. Using Online Citizen Science to Assess Giant Kelp Abundances Across the Globe with Satellite Imagery

    Science.gov (United States)

    Byrnes, J.; Cavanaugh, K. C.; Haupt, A. J.; Trouille, L.; Rosenthal, I.; Bell, T. W.; Rassweiler, A.; Pérez-Matus, A.; Assis, J.

    2017-12-01

    Global scale long-term data sets that document the patterns and variability of human impacts on marine ecosystems are rare. This lack is particularly glaring for underwater species - even moreso for ecologically important ones. Here we demonstrate how online Citizen Science combined with Landsat satellite imagery can help build a picture of change in the dynamics of giant kelp, an important coastal foundation species around the globe, from the 1984 to the present. Giant kelp canopy is visible from Landsat images, but these images defy easy machine classification. To get useful data, images must be processed by hand. While academic researchers have applied this method successfully at sub-regional scales, unlocking the value of the full global dataset has not been possible until given the massive effort required. Here we present Floating Forests (http://floatingforests.org), an international collaboration between kelp forest researchers and the citizen science organization Zooniverse. Floating Forests provides an interface that allows citizen scientists to identify canopy cover of giant kelp on Landsat images, enabling us to scale up the dataset to the globe. We discuss lessons learned from the initial version of the project launched in 2014, a prototype of an image processing pipeline to bring Landsat imagery to citizen science platforms, methods of assessing accuracy of citizen scientists, and preliminary data from our relaunch of the project. Through this project we have developed generalizable tools to facilitate citizen science-based analysis of Landsat and other satellite and aerial imagery. We hope that this create a powerful dataset to unlock our understanding of how global change has altered these critically important species in the sea.

  15. Underway Sampling of Marine Inherent Optical Properties on the Tara Oceans Expedition as a Novel Resource for Ocean Color Satellite Data Product Validation

    Science.gov (United States)

    Werdell, P. Jeremy; Proctor, Christopher W.; Boss, Emmanuel; Leeuw, Thomas; Ouhssain, Mustapha

    2013-01-01

    Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate-the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

  16. Oil palm mapping for Malaysia using PALSAR-2 dataset

    Science.gov (United States)

    Gong, P.; Qi, C. Y.; Yu, L.; Cracknell, A.

    2016-12-01

    Oil palm is one of the most productive vegetable oil crops in the world. The main oil palm producing areas are distributed in humid tropical areas such as Malaysia, Indonesia, Thailand, western and central Africa, northern South America, and central America. Increasing market demands, high yields and low production costs of palm oil are the primary factors driving large-scale commercial cultivation of oil palm, especially in Malaysia and Indonesia. Global demand for palm oil has grown exponentially during the last 50 years, and the expansion of oil palm plantations is linked directly to the deforestation of natural forests. Satellite remote sensing plays an important role in monitoring expansion of oil palm. However, optical remote sensing images are difficult to acquire in the Tropics because of the frequent occurrence of thick cloud cover. This problem has led to the use of data obtained by synthetic aperture radar (SAR), which is a sensor capable of all-day/all-weather observation for studies in the Tropics. In this study, the ALOS-2 (Advanced Land Observing Satellite) PALSAR-2 (Phased Array type L-band SAR) datasets for year 2015 were used as an input to a support vector machine (SVM) based machine learning algorithm. Oil palm/non-oil palm samples were collected using a hexagonal equal-area sampling design. High-resolution images in Google Earth and PALSAR-2 imagery were used in human photo-interpretation to separate oil palm from others (i.e. cropland, forest, grassland, shrubland, water, hard surface and bareland). The characteristics of oil palms from various aspects, including PALSAR-2 backscattering coefficients (HH, HV), terrain and climate by using this sample set were further explored to post-process the SVM output. The average accuracy of oil palm type is better than 80% in the final oil palm map for Malaysia.

  17. Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

    Science.gov (United States)

    Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

    2018-01-01

    Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

  18. Efforts in assimilating Indian satellite data in the NGFS and monitoring of their quality

    Science.gov (United States)

    Prasad, V. S.; Singh, Sanjeev Kumar

    2016-05-01

    Megha-Tropiques (MT) is an Indo-French Joint Satellite Mission, launched on 12 October 2011. MT-SAPHIR is a sounding instrument with 6 channels near the absorption band of water vapor at 183 GHz, for studying the water cycle and energy exchanges in the tropics. The main objective of this mission is to understand the life cycle of convective systems that influence the tropical weather and climate and their role in associated energy and moisture budget of the atmosphere in tropical regions. India also has a prestigious space programme and has launched the INSAT-3D satellite on 26 July 2013 which has an atmospheric sounder for the first time along with improved VHRR imager. NCMRWF (National Centre for Medium Range Weather Forecasting) is regularly receiving these new datasets and also making changes to its Global Data Assimilation Forecasting (GDAF) system from time-to-time to assimilate these new datasets. A well planned strategy involving various steps such as monitoring of data quality, development of observation operator and quality control procedures, and finally then studying its impact on forecasts is developed to include new observations in global data analysis system. By employing this strategy observations having positive impact on forecast quality such as MT-SAPHIR, and INSAT-3D Clear Sky Radiance (CSR) products are identified and being assimilated in the Global Data Assimilation and Forecasting (GDAF) system.

  19. Fluxnet Synthesis Dataset Collaboration Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deborah A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Humphrey, Marty [Univ. of Virginia, Charlottesville, VA (United States); van Ingen, Catharine [Microsoft. San Francisco, CA (United States); Beekwilder, Norm [Univ. of Virginia, Charlottesville, VA (United States); Goode, Monte [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rodriguez, Matt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Robin [Univ. of California, Berkeley, CA (United States)

    2008-02-06

    The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

  20. Simulation of Smart Home Activity Datasets

    Directory of Open Access Journals (Sweden)

    Jonathan Synnott

    2015-06-01

    Full Text Available A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  1. Simulation of Smart Home Activity Datasets.

    Science.gov (United States)

    Synnott, Jonathan; Nugent, Chris; Jeffers, Paul

    2015-06-16

    A globally ageing population is resulting in an increased prevalence of chronic conditions which affect older adults. Such conditions require long-term care and management to maximize quality of life, placing an increasing strain on healthcare resources. Intelligent environments such as smart homes facilitate long-term monitoring of activities in the home through the use of sensor technology. Access to sensor datasets is necessary for the development of novel activity monitoring and recognition approaches. Access to such datasets is limited due to issues such as sensor cost, availability and deployment time. The use of simulated environments and sensors may address these issues and facilitate the generation of comprehensive datasets. This paper provides a review of existing approaches for the generation of simulated smart home activity datasets, including model-based approaches and interactive approaches which implement virtual sensors, environments and avatars. The paper also provides recommendation for future work in intelligent environment simulation.

  2. Exploring Machine Learning to Correct Satellite-Derived Sea Surface Temperatures

    Directory of Open Access Journals (Sweden)

    Stéphane Saux Picart

    2018-02-01

    Full Text Available Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO, Generalised Additive Model (GAM and random forest. In the case of geostationary satellites for which a large number of collocations is available, results show that the random forest model is the best model to predict the systematic errors and it is computationally fast, making it a good candidate for operational processing. It is able to explain nearly 31% of the total variance of the bias (in comparison to about 24% for the multi-linear regression model.

  3. Datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates.

    Science.gov (United States)

    Carrea, Laura; Embury, Owen; Merchant, Christopher J

    2015-11-01

    Datasets containing information to locate and identify water bodies have been generated from data locating static-water-bodies with resolution of about 300 m (1/360 ∘ ) recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The LC CCI water-bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR on Envisat between 2005 and 2010. The new derived datasets provide coherently: distance to land, distance to water, water-body identifiers and lake-centre locations. The water-body identifier dataset locates the water bodies assigning the identifiers of the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). During the generation and validation of the datasets some limitations of the GLWD database and of the LC CCI water-bodies mask have been found. Some examples of the inaccuracies/limitations are presented and discussed. Temporal change in water-body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.

  4. Solar Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Solar Integration National Dataset Toolkit Solar Integration National Dataset Toolkit NREL is working on a Solar Integration National Dataset (SIND) Toolkit to enable researchers to perform U.S . regional solar generation integration studies. It will provide modeled, coherent subhourly solar power data

  5. Thought-action fusion in individuals with OCD symptoms.

    Science.gov (United States)

    Amir, N; Freshman, M; Ramsey, B; Neary, E; Brigidi, B

    2001-07-01

    Rachman (Rachman, S. (1993). Obsessions, responsibility, and guilt. Behaviour Research and Therapy, 31, 149-154) suggested that patients with OCD may interpret thoughts as having special importance, thus experiencing thought-action fusion (TAF). Shafran, Thordarson and Rachman (Shafran, R., Thordarson, D. S. & Rachman, S. (1996). Thought-action fusion in obsessive compulsive disorder. Journal of Anxiety Disorders, 710, 379-391) developed a questionnaire (TAF) and found that obsessives scored higher than non-obsessives on the measure. In the current study, we modified the TAF to include a scale that assessed the "likelihood of events happening to others" as well as ratings of the responsibility and cost for having these thoughts. Replicating previous findings, we found that individuals with OC symptoms gave higher ratings to the likelihood of negative events happening as a result of their negative thoughts. Individuals with OC symptoms also rated the likelihood that they would prevent harm by their positive thoughts higher than did individuals without OC symptoms. These results suggest that the role of thought-action fusion in OCs may extend to exaggerated beliefs about thoughts regarding the reduction of harm.

  6. PROVIDING GEOGRAPHIC DATASETS AS LINKED DATA IN SDI

    Directory of Open Access Journals (Sweden)

    E. Hietanen

    2016-06-01

    Full Text Available In this study, a prototype service to provide data from Web Feature Service (WFS as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF data format. Next, a Web Ontology Language (OWL ontology is created to describe the dataset information content using the Open Geospatial Consortium’s (OGC GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID. The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

  7. Wind Integration National Dataset Toolkit | Grid Modernization | NREL

    Science.gov (United States)

    Integration National Dataset Toolkit Wind Integration National Dataset Toolkit The Wind Integration National Dataset (WIND) Toolkit is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies. WIND

  8. Satellite and gauge rainfall merging using geographically weighted regression

    Directory of Open Access Journals (Sweden)

    Q. Hu

    2015-05-01

    Full Text Available A residual-based rainfall merging scheme using geographically weighted regression (GWR has been proposed. This method is capable of simultaneously blending various satellite rainfall data with gauge measurements and could describe the non-stationary influences of geographical and terrain factors on rainfall spatial distribution. Using this new method, an experimental study on merging daily rainfall from the Climate Prediction Center Morphing dataset (CMOROH and gauge measurements was conducted for the Ganjiang River basin, in Southeast China. We investigated the capability of the merging scheme for daily rainfall estimation under different gauge density. Results showed that under the condition of sparse gauge density the merging rainfall scheme is remarkably superior to the interpolation using just gauge data.

  9. Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

    Science.gov (United States)

    Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

    2018-04-09

    Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

  10. Project Roadkill: Linking European Hare vehicle collisions with landscape-structure using datasets from citizen scientists and professionals

    Science.gov (United States)

    Stretz, Carina; Heigl, Florian; Steiner, Wolfgang; Bauer, Thomas; Suppan, Franz; Zaller, Johann G.

    2015-04-01

    Road networks can implicate lots of negative effects for wildlife. One of the most important indication for strong landscape fragmentation are roadkills, i.e. collisions between motorised vehicles and wild animals. A species that is often involved in roadkills is the European hare (Lepus europaeus). European hare populations are in decline throughout Europe since the 1960s and classified as "potentially endangered" in the Red Data Book of Austria. Therefore, it is striking that in the hunting year 2013/14, 19,343 hares were killed on Austrian roads translating to 53 hare roadkills each day, or rather about two per hour. We hypothesized, that (I) hare-vehicle-collisions occur as an aggregation of events (hotspot), (II) the surrounding landscape influences the number of roadkilled hares and (III) roadkill data from citizen science projects and data from professionals (e.g. hunters, police) are convergent. Investigations on the surrounding landscape of the scenes of accidents will be carried out using land cover data derived from Landsat satellite images. Information on road kills are based on datasets from two different sources. One dataset stems from the citizen science project "Roadkill" (www.citizen-science.at/roadkill) where participants report roadkill findings via a web application. The second dataset is from a project where roadkill data were collected by the police and by hunters. Besides answering our research questions, findings of this project also allow the location of dangerous roadkill hotspots for animals and could be implemented in nature conservation actions.

  11. 3D reconstruction from multi-view VHR-satellite images in MicMac

    Science.gov (United States)

    Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

    2018-05-01

    This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

  12. Messianism in Latin American Environmental Thought

    International Nuclear Information System (INIS)

    Buitrago, Dairo

    2008-01-01

    One appears in the communication as one resorts for the social mobilization, towards the political pretensions of the messianic environmental thought, to symbiologies of body, psychic character and society of skeptical or relativist character. For the analysis of the symbiologies, we start from the criterion that when they are used politically in the environmental thought it is not done necessarily with an intention of strategic use I specify, but that its use can be by the implicit valuations that have these symbiologies in the world of the daily life, where the systems of environmental thought also interact of messianic type

  13. HIMAWARI-8 Geostationary Satellite Observation of the Internal Solitary Waves in the South China Sea

    Science.gov (United States)

    Gao, Q.; Dong, D.; Yang, X.; Husi, L.; Shang, H.

    2018-04-01

    The new generation geostationary meteorological satellite, Himawari-8 (H-8), was launched in 2015. Its main payload, the Advanced Himawari Imager (AHI), can observe the earth with 10-minute interval and as high as 500-m spatial resolution. This makes the H-8 satellite an ideal data source for marine and atmospheric phenomena monitoring. In this study, the propagation of internal solitary waves (ISWs) in the South China Sea is investigated using AHI imagery time series for the first time. Three ISWs cases were studied at 3:30-8:00 UTC on 30 May, 2016. In all, 28 ISWs were detected and tracked between the time series image pairs. The propagation direction and phase speeds of these ISWs are calculated and analyzed. The observation results show that the properties of ISW propagation not stable and maintains nonlinear during its lifetime. The resultant ISW speeds agree well with the theoretical values estimated from the Taylor-Goldstein equation using Argo dataset. This study has demonstrated that the new generation geostationary satellite can be a useful tool to monitor and investigate the oceanic internal waves.

  14. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  15. Thought Suppression Research Methods: Paradigms, Theories, Methodological Concerns

    Directory of Open Access Journals (Sweden)

    Niczyporuk Aneta

    2016-12-01

    Full Text Available It is hard to provide an unequivocal answer to the question of whether or not thought suppression is effective. Two thought suppression paradigms - the “white bear” paradigm and the think/no-think paradigm - give mixed results. Generally, “white bear” experiments indicate that thought suppression is counterproductive, while experiments in the think/no-think paradigm suggest that it is possible to effectively suppress a thought. There are also alternative methods used to study thought suppression, for instance the directed forgetting paradigm or the Stroop task. In the article, I describe the research methods used to explore thought suppression efficacy. I focus on the “white bear” and the think/no-think paradigms and discuss theories proposed to explain the results obtained. I also consider the internal and external validity of the methods used.

  16. Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

    Science.gov (United States)

    Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

    2008-01-01

    There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5

  17. A New Outlier Detection Method for Multidimensional Datasets

    KAUST Repository

    Abdel Messih, Mario A.

    2012-07-01

    This study develops a novel hybrid method for outlier detection (HMOD) that combines the idea of distance based and density based methods. The proposed method has two main advantages over most of the other outlier detection methods. The first advantage is that it works well on both dense and sparse datasets. The second advantage is that, unlike most other outlier detection methods that require careful parameter setting and prior knowledge of the data, HMOD is not very sensitive to small changes in parameter values within certain parameter ranges. The only required parameter to set is the number of nearest neighbors. In addition, we made a fully parallelized implementation of HMOD that made it very efficient in applications. Moreover, we proposed a new way of using the outlier detection for redundancy reduction in datasets where the confidence level that evaluates how accurate the less redundant dataset can be used to represent the original dataset can be specified by users. HMOD is evaluated on synthetic datasets (dense and mixed “dense and sparse”) and a bioinformatics problem of redundancy reduction of dataset of position weight matrices (PWMs) of transcription factor binding sites. In addition, in the process of assessing the performance of our redundancy reduction method, we developed a simple tool that can be used to evaluate the confidence level of reduced dataset representing the original dataset. The evaluation of the results shows that our method can be used in a wide range of problems.

  18. Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

    Directory of Open Access Journals (Sweden)

    T. Raziei

    2010-10-01

    Full Text Available Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR reanalysis and the Global Precipitation Climatology Centre (GPCC dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI on 24-month time scale, while Principal Component Analysis (PCA and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings.

    Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

  19. Observations of urban and suburban environments with global satellite scatterometer data

    Science.gov (United States)

    Nghiem, S. V.; Balk, D.; Rodriguez, E.; Neumann, G.; Sorichetta, A.; Small, C.; Elvidge, C. D.

    A global and consistent characterization of land use and land change in urban and suburban environments is crucial for many fundamental social and natural science studies and applications. Presented here is a dense sampling method (DSM) that uses satellite scatterometer data to delineate urban and intraurban areas at a posting scale of about 1 km. DSM results are analyzed together with information on population and housing censuses, with Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, and with Defense Meteorological Satellite Program (DMSP) night-light data. The analyses include Dallas-Fort Worth and Phoenix in the United States, Bogotá in Colombia, Dhaka in Bangladesh, Guangzhou in China, and Quito in Ecuador. Results show that scatterometer signatures correspond to buildings and infrastructures in urban and suburban environments. City extents detected by scatterometer data are significantly smaller than city light extents, but not all urban areas are detectable by the current SeaWinds scatterometer on the QuikSCAT satellite. Core commercial and industrial areas with high buildings and large factories are identified as high-backscatter centers. Data from DSM backscatter and DMSP nighttime lights have a good correlation with population density. However, the correlation relations from the two satellite datasets are different for different cities indicating that they contain complementary information. Together with night-light and census data, DSM and satellite scatterometer data provide new observations to study global urban and suburban environments and their changes. Furthermore, the capability of DSM to identify hydrological channels on the Greenland ice sheet and ecological biomes in central Africa demonstrates that DSM can be used to observe persistent structures in natural environments at a km scale, providing contemporaneous data to study human impacts beyond urban and suburban areas.

  20. NP-PAH Interaction Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  1. A dataset on tail risk of commodities markets.

    Science.gov (United States)

    Powell, Robert J; Vo, Duc H; Pham, Thach N; Singh, Abhay K

    2017-12-01

    This article contains the datasets related to the research article "The long and short of commodity tails and their relationship to Asian equity markets"(Powell et al., 2017) [1]. The datasets contain the daily prices (and price movements) of 24 different commodities decomposed from the S&P GSCI index and the daily prices (and price movements) of three share market indices including World, Asia, and South East Asia for the period 2004-2015. Then, the dataset is divided into annual periods, showing the worst 5% of price movements for each year. The datasets are convenient to examine the tail risk of different commodities as measured by Conditional Value at Risk (CVaR) as well as their changes over periods. The datasets can also be used to investigate the association between commodity markets and share markets.

  2. The contribution of thought-action fusion and thought suppression in the development of obsession-like intrusions in normal participants.

    Science.gov (United States)

    Rassin, E

    2001-09-01

    Both thought-action fusion (TAF: i.e., a cognitive bias implying an inflated sense of responsibility for one's own thoughts) and thought suppression have been claimed to contribute to the development of obsession-like intrusions. Therefore, it seems plausible that conjunction of these phenomena results in highly intense intrusions. However, possible interactions between TAF and thought suppression have not yet been investigated experimentally. In the current study, healthy volunteers were exposed to a TAF-like intrusion. They were, then, randomly assigned to a suppression (n=21) or non-suppression condition (n=19). Next, visual analogue scales (VASs) were completed measuring anxiety, feelings of responsibility and guilt, urge to neutralise and so on. Contrary to expectation, several VAS scores were lower for participants in the suppression group than for those in the non-suppression group. Hence, it is concluded that thought suppression may, at least in the short term, alleviate discomfort caused by TAF-like intrusions.

  3. Becoming Bombs: 3D Animated Satellite Imagery and the Weaponization of the Civic Eye

    Directory of Open Access Journals (Sweden)

    Roger Stahl

    2010-02-01

    Full Text Available This essay traces the recent history of 3D satellite animation from its military origins to its visibility in the civic sphere. Specifically, technologies unveiled in 2004 as Google Earth first received widespread public visibility in the television coverage of the 2003 U.S. invasion of Iraq. The essay first maps the political economy of the “military-media-geotech” complex, focusing mainly on the coverage of the Iraq War as an nexus of interests. Second, the essay analyzes the aesthetic uses of 3D satellite animation on the news during this period, including how these imaging practices meshed with existing discourses such as the clean war, the weaponization of the civic gaze, and others. The essay concludes with thoughts regarding what these practices mean for the efficacy of the deliberative citizen, public life, and the meaning of war.

  4. Monitoring Water Resources in Pastoral Areas of East Africa Using Satellite Data and Hydrologic Modeling

    Science.gov (United States)

    Alemu, H.; Senay, G. B.; Velpuri, N.; Asante, K. O.

    2008-12-01

    The nomadic pastoral communities in East Africa heavily depend on small water bodies and artificial lakes for domestic and livestock uses. The shortage of water in the region has made these water resources of great importance to them and sometimes even the reason for conflicts amongst rival communities in the region. Satellite-based data has significantly transformed the way we track and estimate hydrological processes such as precipitation and evapotranspiration. This approach has been particularly useful in remote places where conventional station-based weather networks are scarce. Tropical Rainfall Measuring Mission (TRMM) satellite data were extracted for the study region. National Oceanic and Atmospheric Administration's (NOAA) Global Data Assimilation System (GDAS) data were used to extract the climatic parameters needed to calculate reference evapotranspiration. The elevation data needed to delineate the watersheds were extracted from the Shuttle Radar Topography Mission (SRTM) with spatial resolution of 90m. The waterholes (most of which have average surface area less than a hectare) were identified using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images with a spatial resolution of 15 m. As part of National Aeronautics and Space Administration's (NASA) funded enhancement to a livestock early warning decision support system, a simple hydrologic water balance model was developed to estimate daily waterhole depth variations. The model was run for over 10 years from 1998 till 2008 for 10 representative waterholes in the region. Although there were no independent datasets to validate the results, the temporal patterns captured both the seasonal and inter-annual variations, depicting known drought and flood years. Future research includes the installation of staff-gauges for model calibration and validation. The simple modeling approach demonstrated the effectiveness of integrating dynamic coarse resolution datasets such as TRMM with

  5. Language, Thought and Memory in Linguistic Performance, A Thought View.

    Science.gov (United States)

    Lado, Robert

    The contrasting views of Saussure and Bloomfield ("mentalist" versus "mechanist"), the hypotheses of Whorf showing the influence of language on certain habits of thought, and Chomsky's notion of generative transformational grammar in the context of language use are reviewed. The author notes the limits of these systems and suggests that in dealing…

  6. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  7. Production of solar radiation bankable datasets from high-resolution solar irradiance derived with dynamical downscaling Numerical Weather prediction model

    Directory of Open Access Journals (Sweden)

    Yassine Charabi

    2016-11-01

    Full Text Available A bankable solar radiation database is required for the financial viability of solar energy project. Accurate estimation of solar energy resources in a country is very important for proper siting, sizing and life cycle cost analysis of solar energy systems. During the last decade an important progress has been made to develop multiple solar irradiance database (Global Horizontal Irradiance (GHI and Direct Normal Irradiance (DNI, using satellite of different resolution and sophisticated models. This paper assesses the performance of High-resolution solar irradiance derived with dynamical downscaling Numerical Weather Prediction model with, GIS topographical solar radiation model, satellite data and ground measurements, for the production of bankable solar radiation datasets. For this investigation, NWP model namely Consortium for Small-scale Modeling (COSMO is used for the dynamical downscaling of solar radiation. The obtained results increase confidence in solar radiation data base obtained from dynamical downscaled NWP model. The mean bias of dynamical downscaled NWP model is small, on the order of a few percents for GHI, and it could be ranked as a bankable datasets. Fortunately, these data are usually archived in the meteorological department and gives a good idea of the hourly, monthly, and annual incident energy. Such short time-interval data are valuable in designing and operating the solar energy facility. The advantage of the NWP model is that it can be used for solar radiation forecast since it can estimate the weather condition within the next 72–120 hours. This gives a reasonable estimation of the solar radiation that in turns can be used to forecast the electric power generation by the solar power plant.

  8. "Aid to Thought"--Just Simulate It!

    Science.gov (United States)

    Kinczkowski, Linda; Cardon, Phillip; Speelman, Pamela

    2015-01-01

    This paper provides examples of Aid-to-Thought uses in urban decision making, classroom laboratory planning, and in a ship antiaircraft defense system. Aid-to-Thought modeling and simulations are tools students can use effectively in a STEM classroom while meeting Standards for Technological Literacy Benchmarks O and R. These projects prepare…

  9. Discovering Supervisors' Thought Patterns through Journals.

    Science.gov (United States)

    Niemeyer, Roger C.; Moon, R. Arden

    This study focused on the thoughts, related schema, and decision-making of student teaching supervisors as they go about their work of supervision. Twelve practicing supervisors were asked to write their thoughts on a three-stage data gathering, circle instrument. These concepts were weighted to reflect the significance each concept had in the…

  10. Comparison of Shallow Survey 2012 Multibeam Datasets

    Science.gov (United States)

    Ramirez, T. M.

    2012-12-01

    The purpose of the Shallow Survey common dataset is a comparison of the different technologies utilized for data acquisition in the shallow survey marine environment. The common dataset consists of a series of surveys conducted over a common area of seabed using a variety of systems. It provides equipment manufacturers the opportunity to showcase their latest systems while giving hydrographic researchers and scientists a chance to test their latest algorithms on the dataset so that rigorous comparisons can be made. Five companies collected data for the Common Dataset in the Wellington Harbor area in New Zealand between May 2010 and May 2011; including Kongsberg, Reson, R2Sonic, GeoAcoustics, and Applied Acoustics. The Wellington harbor and surrounding coastal area was selected since it has a number of well-defined features, including the HMNZS South Seas and HMNZS Wellington wrecks, an armored seawall constructed of Tetrapods and Akmons, aquifers, wharves and marinas. The seabed inside the harbor basin is largely fine-grained sediment, with gravel and reefs around the coast. The area outside the harbor on the southern coast is an active environment, with moving sand and exposed reefs. A marine reserve is also in this area. For consistency between datasets, the coastal research vessel R/V Ikatere and crew were used for all surveys conducted for the common dataset. Using Triton's Perspective processing software multibeam datasets collected for the Shallow Survey were processed for detail analysis. Datasets from each sonar manufacturer were processed using the CUBE algorithm developed by the Center for Coastal and Ocean Mapping/Joint Hydrographic Center (CCOM/JHC). Each dataset was gridded at 0.5 and 1.0 meter resolutions for cross comparison and compliance with International Hydrographic Organization (IHO) requirements. Detailed comparisons were made of equipment specifications (transmit frequency, number of beams, beam width), data density, total uncertainty, and

  11. Monthly-Diurnal Water Budget Variability Over Gulf of Mexico-Caribbean Sea Basin from Satellite Observations

    Science.gov (United States)

    Smith, E. A.; Santos, P.

    2006-01-01

    This study presents results from a multi-satellite/multi-sensor retrieval system design d to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective in identifying problems in estimating vapor transports from a "leaky" operational radiosonde network than in

  12. Satellite Retrieval of Atmospheric Water Budget over Gulf of Mexico- Caribbean Basin: Seasonal Variability

    Science.gov (United States)

    Smith, Eric A.; Santos, Pablo; Einaudi, Franco (Technical Monitor)

    2001-01-01

    This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5 Imager and the DMSP 7-channel passive microwave radiometer (SSM/I) have been acquired for the Gulf of Mexico-Caribbean Sea basin. Whereas the methodology is being tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the SSM/I passive microwave signals in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, we have sought to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is partly validated by first cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. More fundamental validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithm to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin. Total columnar atmospheric water budget results will be presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98, October-98, and January-1999. These results are used to emphasize

  13. Personal identity and eastern thought

    Directory of Open Access Journals (Sweden)

    Correia Carlos João

    2009-01-01

    Full Text Available This paper aims to show that the problem of personal identity is a fundamental question of the classical Indian thought. Usually we tend to think that personal identity is a Western philosophical subject, and so we tend to forget the significance of the Self (Atman in Hinduism and even in Buddhism. The author shows how the Indian thought approached the question of personal identity and which was the singular solution outlined in the work consensually attributed to Gotama, the Buddha.

  14. National Hydrography Dataset (NHD)

    Data.gov (United States)

    Kansas Data Access and Support Center — The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the...

  15. A satellite simulator for TRMM PR applied to climate model simulations

    Science.gov (United States)

    Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

    2017-12-01

    Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

  16. The Harvard organic photovoltaic dataset.

    Science.gov (United States)

    Lopez, Steven A; Pyzer-Knapp, Edward O; Simm, Gregor N; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-09-27

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.

  17. Fast thought speed induces risk taking.

    Science.gov (United States)

    Chandler, Jesse J; Pronin, Emily

    2012-04-01

    In two experiments, we tested for a causal link between thought speed and risk taking. In Experiment 1, we manipulated thought speed by presenting neutral-content text at either a fast or a slow pace and having participants read the text aloud. In Experiment 2, we manipulated thought speed by presenting fast-, medium-, or slow-paced movie clips that contained similar content. Participants who were induced to think more quickly took more risks with actual money in Experiment 1 and reported greater intentions to engage in real-world risky behaviors, such as unprotected sex and illegal drug use, in Experiment 2. These experiments provide evidence that faster thinking induces greater risk taking.

  18. Tables and figure datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — Soil and air concentrations of asbestos in Sumas study. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D....

  19. Conscious and unconscious thought in risky choice: Testing the capacity principle and the appropriate weighting principle of Unconscious Thought Theory

    Directory of Open Access Journals (Sweden)

    Nathaniel James Siebert Ashby

    2011-10-01

    Full Text Available Daily we make decisions ranging from the mundane to the seemingly pivotal that shape our lives. Assuming rationality, all relevant information about one’s options should be thoroughly examined in order to make the best choice. However, some findings suggest that under specific circumstances thinking too much has disadvantageous effects on decision quality and that it might be best to let the unconscious do the busy work. In three studies we test the capacity assumption and the appropriate weighting principle of unconscious thought theory using a classic risky choice paradigm and including a ‘deliberation with information’ condition. Although we replicate an advantage for unconscious thought over ‘deliberation without information’, we find that ‘deliberation with information’ equals or outperforms unconscious thought in risky choices. These results speak against the generality of the assumption that unconscious thought has a higher capacity for information integration and show that this capacity assumption does not hold in all domains. We furthermore show that ‘deliberate thought with information’ leads to more differentiated knowledge compared to unconscious thought which speaks against the generality of the appropriate weighting assumption.

  20. A thought in the park: The influence of naturalness and low-level visual features on expressed thoughts

    Science.gov (United States)

    Kathryn E. Schertz; Sonya Sachdeva; Omid Kardan; Hiroki P. Kotabe; Kathleen L. Wolf; Marc G. Berman

    2018-01-01

    Prior research has shown that the physical characteristics of one's environment have wide ranging effects on affect and cognition. Other research has demonstrated that one's thoughts have impacts on mood and behavior, and in this three-part research program we investigated how physical features of the environment can alter thought content. In one study, we...

  1. Leveraging the NPS Femto Satellite for Alternative Satellite Communication Networks

    Science.gov (United States)

    2017-09-01

    programmed for eventual integration with the Iridium Network , which is then tested. C. THESIS ORGANIZATION The thesis addresses these questions...NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS by Faisal S. Alshaya September 2017 Co-Advisors: Steven J. Iatrou...TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE LEVERAGING THE NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS 5

  2. Evaluation of the shortwave cloud radiative effect over the ocean by use of ship and satellite observations

    Directory of Open Access Journals (Sweden)

    T. Hanschmann

    2012-12-01

    Full Text Available In this study the shortwave cloud radiative effect (SWCRE over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.

  3. Evaluation of the MiKlip decadal prediction system using satellite based cloud products

    Directory of Open Access Journals (Sweden)

    Thomas Spangehl

    2016-12-01

    Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

  4. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The first part of the Long Shutdown period has been dedicated to the preparation of the samples for the analysis targeting the summer conferences. In particular, the 8 TeV data acquired in 2012, including most of the “parked datasets”, have been reconstructed profiting from improved alignment and calibration conditions for all the sub-detectors. A careful planning of the resources was essential in order to deliver the datasets well in time to the analysts, and to schedule the update of all the conditions and calibrations needed at the analysis level. The newly reprocessed data have undergone detailed scrutiny by the Dataset Certification team allowing to recover some of the data for analysis usage and further improving the certification efficiency, which is now at 91% of the recorded luminosity. With the aim of delivering a consistent dataset for 2011 and 2012, both in terms of conditions and release (53X), the PPD team is now working to set up a data re-reconstruction and a new MC pro...

  5. Integrated Surface Dataset (Global)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Integrated Surface (ISD) Dataset (ISD) is composed of worldwide surface weather observations from over 35,000 stations, though the best spatial coverage is...

  6. Aaron Journal article datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman....

  7. Market Squid Ecology Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains ecological information collected on the major adult spawning and juvenile habitats of market squid off California and the US Pacific Northwest....

  8. Meteorological satellite systems

    CERN Document Server

    Tan, Su-Yin

    2014-01-01

    “Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.

  9. Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Yuxiang He

    2018-01-01

    Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

  10. Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

    Science.gov (United States)

    Siemann, Amanda Lynn

    The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the

  11. Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau

    Directory of Open Access Journals (Sweden)

    Alaa Alden Alazzy

    2017-01-01

    Full Text Available In the last few years, satellite-based precipitation datasets are believed to be a potential source for forcing inputs in driving hydrological models, which are important especially in complex terrain areas or ungauged basins where ground gauges are generally sparse or nonexistent. This study aims to comprehensively evaluate the satellite precipitation products, CMORPH-CRT, PERSIANN-CDR, 3B42RT, and 3B42 against gauge-based datasets and to infer their relative potential impacts on hydrological processes simulation using the HEC-HMS model in the Ganzi River Basin (GRB of the Tibetan Plateau. Results from a quantitative statistical comparison reveal that, at annual and seasonal scales, both CMORPH-CRT and 3B42 perform better than PERSIANN-CDR and 3B42RT. The CMORPH-CRT and 3B42 tend to underestimate values at the medium and high precipitation intensities ranges, whereas the opposite tendency is found for PERSIANN-CDR and 3B42RT. Overall, 3B42 exhibits the best performance for streamflow simulations over GRB and even outperforms simulation driven by gauge data during the validation period. PERSIANN-CDR shows the worst overall performance. After recalibrating with input-specific precipitation data, the performance of all satellite precipitation forced simulations is substantially improved, except for PERSIANN-CDR. Furthermore, 3B42 is more suitable to drive hydrological models and can be a potential alternative source of sparse data in Tibetan Plateau basins.

  12. Boomerang Satellites

    Science.gov (United States)

    Hesselbrock, Andrew; Minton, David A.

    2017-10-01

    We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.

  13. ATLAS File and Dataset Metadata Collection and Use

    CERN Document Server

    Albrand, S; The ATLAS collaboration; Lambert, F; Gallas, E J

    2012-01-01

    The ATLAS Metadata Interface (“AMI”) was designed as a generic cataloguing system, and as such it has found many uses in the experiment including software release management, tracking of reconstructed event sizes and control of dataset nomenclature. The primary use of AMI is to provide a catalogue of datasets (file collections) which is searchable using physics criteria. In this paper we discuss the various mechanisms used for filling the AMI dataset and file catalogues. By correlating information from different sources we can derive aggregate information which is important for physics analysis; for example the total number of events contained in dataset, and possible reasons for missing events such as a lost file. Finally we will describe some specialized interfaces which were developed for the Data Preparation and reprocessing coordinators. These interfaces manipulate information from both the dataset domain held in AMI, and the run-indexed information held in the ATLAS COMA application (Conditions and ...

  14. Norwegian Hydrological Reference Dataset for Climate Change Studies

    Energy Technology Data Exchange (ETDEWEB)

    Magnussen, Inger Helene; Killingland, Magnus; Spilde, Dag

    2012-07-01

    Based on the Norwegian hydrological measurement network, NVE has selected a Hydrological Reference Dataset for studies of hydrological change. The dataset meets international standards with high data quality. It is suitable for monitoring and studying the effects of climate change on the hydrosphere and cryosphere in Norway. The dataset includes streamflow, groundwater, snow, glacier mass balance and length change, lake ice and water temperature in rivers and lakes.(Author)

  15. Singular and combined effects of thought suppression and anxiety induction on frequency of threatening thoughts: An experimental investigation

    NARCIS (Netherlands)

    Cougle, J.R.; Smits, J.A.J.; Lee, H.J.; Powers, M.B.; Telch, M.J.

    2005-01-01

    The suppression of unwanted thoughts has been hypothesized to play an important role in the maintenance of clinical disorders such as OCD and PTSD. The present study sought to examine the singular and combined effects of thought suppression instructions and anxiety induction (as induced by an

  16. The Harvard organic photovoltaic dataset

    Science.gov (United States)

    Lopez, Steven A.; Pyzer-Knapp, Edward O.; Simm, Gregor N.; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R.; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-01-01

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications. PMID:27676312

  17. Synthetic and Empirical Capsicum Annuum Image Dataset

    NARCIS (Netherlands)

    Barth, R.

    2016-01-01

    This dataset consists of per-pixel annotated synthetic (10500) and empirical images (50) of Capsicum annuum, also known as sweet or bell pepper, situated in a commercial greenhouse. Furthermore, the source models to generate the synthetic images are included. The aim of the datasets are to

  18. Methodological pitfalls of the Unconscious Thought paradigm

    NARCIS (Netherlands)

    Waroquier, Laurent; Marchiori, David; Klein, Olivier; Cleeremans, Axel

    2009-01-01

    According to Unconscious Thought Theory (UTT: Dijksterhuis & Nordgren, 2006), complex decisions are best made after a period of distraction assumed to elicit "unconscious thought". Over three studies, respectively offering a conceptual, an identical and a methodologically improved replication of

  19. Possibility of continuous monitoring of environment around the nuclear plant using satellite remote sensing

    International Nuclear Information System (INIS)

    Sasaki, Takanori; Tanabu, Yoshimine; Fujita, Shigetaka; Zhao Wenhui

    2008-01-01

    Interest in nuclear power generation is increasing by rising of power demand and environmental concern. It is important more and more to confirm and show the safety operation of nuclear plants, which is useful to remove anxiety of residents. Satellite remote sensing is one of the way of it. Large observation width and long and continuous observation period are advantage of satellite remote sensing. In addition, it is very important to be able to monitor without visitation on the site. We have continued local area environmental analysis using various satellites. MODIS on Terra and Aqua which are NASA satellites received by Hachinohe Institute of Technology is mainly used. According to these results, we have shown that combined analysis of various information parameters such as land surface temperature, geographical changes, vegetation, etc. is very effective to monitor environmental changes. In these analyses, error detection is very important. Therefore, enough storage data with continuously monitoring in usual state is necessary. Moreover, it is thought that the confirmation of stable operation of plants by means of continuous monitoring can contribute to reduce residents' anxiety of nuclear power plant. Additionally, in the case that the change of influence on surroundings is detected, it is possible to grasp the situation and take measure in early stage by error detection. In this paper, as an possible example of continuous monitoring using satellite remote sensing, we introduce the result of analysis and investigation of which changes of sea surface temperature and chlorophyll concentration on the sea around power plant. (author)

  20. The antecedents and belief-polarized effects of thought confidence.

    Science.gov (United States)

    Chou, Hsuan-Yi; Lien, Nai-Hwa; Liang, Kuan-Yu

    2011-01-01

    This article investigates 2 possible antecedents of thought confidence and explores the effects of confidence induced before or during ad exposure. The results of the experiments indicate that both consumers' dispositional optimism and spokesperson attractiveness have significant effects on consumers' confidence in thoughts that are generated after viewing the advertisement. Higher levels of thought confidence will influence the quality of the thoughts that people generate, lead to either positively or negatively polarized message processing, and therefore induce better or worse advertising effectiveness, depending on the valence of thoughts. The authors posit the belief-polarization hypothesis to explain these findings.

  1. The Self-help Online against Suicidal thoughts (SOS) trial

    DEFF Research Database (Denmark)

    Mühlmann, Charlotte; Madsen, Trine; Hjorthøj, Carsten Rygaard

    2017-01-01

    -list assignment for 32 weeks. The primary outcomes are frequency and intensity of suicidal thoughts. Secondary outcome measures include depressive symptoms, hopelessness, worrying, quality of life, costs related to health care utilization and production loss. Number of deliberate self-harm episodes, suicides......BACKGROUND: Suicidal thoughts are common, causing distress for millions of people all over the world. However, people with suicidal thoughts might not access support due to financial restraints, stigma or a lack of available treatment offers. Self-help programs provided online could overcome...... these barriers, and previous efforts show promising results in terms of reducing suicidal thoughts. This study aims to examine the effectiveness of an online self-help intervention in reducing suicidal thoughts among people at risk of suicide. The Danish Self-help Online against Suicidal thoughts (SOS) trial...

  2. Role of thought-related beliefs and coping strategies in the escalation of intrusive thoughts: an analog to obsessive-compulsive disorder.

    Science.gov (United States)

    Marcks, Brook A; Woods, Douglas W

    2007-11-01

    Cognitive-behavioral models of obsessive-compulsive disorder (OCD) assume that obsessions have their origin in normal intrusive thoughts. These models propose that certain beliefs, such as thought-action fusion (TAF) beliefs, combined with the use of ineffective coping strategies, such as thought suppression, lead to the development of OCD. The purpose of the current study was to examine the relationship between these variables in a non-clinical sample in addition to exploring the effects of an alternative, acceptance-based coping strategy. This study explored the relationship between TAF beliefs, thought suppression, and OC-consistent symptoms via mediational analyses. Results showed that thought suppression mediated the relationship between TAF beliefs and OC-consistent symptoms. This study also experimentally examined the effects of various coping strategies (suppression, acceptance, or monitor-only) on the frequency of a distressing intrusion and appraisal ratings (e.g., anxiety, guilt, responsibility) after a TAF induction. Spontaneous suppression in the monitor-only group made comparisons of the experimental data difficult. However, analyses provided preliminary evidence suggesting that thought suppression is related to more intrusions, higher levels of anxiety, and negative appraisals, whereas an acceptance-based approach may be a useful alternative. Additional findings, limitations of the current study, and directions for future research are discussed.

  3. Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

    Science.gov (United States)

    Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

    2017-12-01

    Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

  4. Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

    Science.gov (United States)

    Hoder, Douglas; Bergamo, Marcos

    1996-01-01

    The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

  5. SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

    2016-04-01

    Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

  6. EEG datasets for motor imagery brain-computer interface.

    Science.gov (United States)

    Cho, Hohyun; Ahn, Minkyu; Ahn, Sangtae; Kwon, Moonyoung; Jun, Sung Chan

    2017-07-01

    Most investigators of brain-computer interface (BCI) research believe that BCI can be achieved through induced neuronal activity from the cortex, but not by evoked neuronal activity. Motor imagery (MI)-based BCI is one of the standard concepts of BCI, in that the user can generate induced activity by imagining motor movements. However, variations in performance over sessions and subjects are too severe to overcome easily; therefore, a basic understanding and investigation of BCI performance variation is necessary to find critical evidence of performance variation. Here we present not only EEG datasets for MI BCI from 52 subjects, but also the results of a psychological and physiological questionnaire, EMG datasets, the locations of 3D EEG electrodes, and EEGs for non-task-related states. We validated our EEG datasets by using the percentage of bad trials, event-related desynchronization/synchronization (ERD/ERS) analysis, and classification analysis. After conventional rejection of bad trials, we showed contralateral ERD and ipsilateral ERS in the somatosensory area, which are well-known patterns of MI. Finally, we showed that 73.08% of datasets (38 subjects) included reasonably discriminative information. Our EEG datasets included the information necessary to determine statistical significance; they consisted of well-discriminated datasets (38 subjects) and less-discriminative datasets. These may provide researchers with opportunities to investigate human factors related to MI BCI performance variation, and may also achieve subject-to-subject transfer by using metadata, including a questionnaire, EEG coordinates, and EEGs for non-task-related states. © The Authors 2017. Published by Oxford University Press.

  7. Not Merely Experiential: Unconscious Thought Can Be Rational

    Directory of Open Access Journals (Sweden)

    Katie E. Garrison

    2017-07-01

    Full Text Available Individuals often form more reasonable judgments from complex information after a period of distraction vs. deliberation. This phenomenon has been attributed to sophisticated unconscious thought during the distraction period that integrates and organizes the information (Unconscious Thought Theory; Dijksterhuis and Nordgren, 2006. Yet, other research suggests that experiential processes are strengthened during the distraction (relative to deliberation period, accounting for the judgment and decision benefit. We tested between these possibilities, hypothesizing that unconscious thought is distinct from experiential processes, and independently contributes to judgments and decisions during a distraction period. Using an established paradigm, Experiment 1 (N = 319 randomly induced participants into an experiential or rational mindset, after which participants received complex information describing three roommates to then consider consciously (i.e., deliberation or unconsciously (i.e., distraction. Results revealed superior roommate judgments (but not choices following distraction vs. deliberation, consistent with Unconscious Thought Theory. Mindset did not have an influence on roommate judgments. However, planned tests revealed a significant advantage of distraction only within the rational-mindset condition, which is contrary to the idea that experiential processing alone facilitates complex decision-making during periods of distraction. In a second experiment (N = 136, we tested whether effects of unconscious thought manifest for a complex analytical reasoning task for which experiential processing would offer no advantage. As predicted, participants in an unconscious thought condition outperformed participants in a control condition, suggesting that unconscious thought can be analytical. In sum, the current results support the existence of unconscious thinking processes that are distinct from experiential processes, and can be rational. Thus

  8. Not Merely Experiential: Unconscious Thought Can Be Rational.

    Science.gov (United States)

    Garrison, Katie E; Handley, Ian M

    2017-01-01

    Individuals often form more reasonable judgments from complex information after a period of distraction vs. deliberation. This phenomenon has been attributed to sophisticated unconscious thought during the distraction period that integrates and organizes the information (Unconscious Thought Theory; Dijksterhuis and Nordgren, 2006). Yet, other research suggests that experiential processes are strengthened during the distraction (relative to deliberation) period, accounting for the judgment and decision benefit. We tested between these possibilities, hypothesizing that unconscious thought is distinct from experiential processes, and independently contributes to judgments and decisions during a distraction period. Using an established paradigm, Experiment 1 ( N = 319) randomly induced participants into an experiential or rational mindset, after which participants received complex information describing three roommates to then consider consciously (i.e., deliberation) or unconsciously (i.e., distraction). Results revealed superior roommate judgments (but not choices) following distraction vs. deliberation, consistent with Unconscious Thought Theory. Mindset did not have an influence on roommate judgments. However, planned tests revealed a significant advantage of distraction only within the rational-mindset condition, which is contrary to the idea that experiential processing alone facilitates complex decision-making during periods of distraction. In a second experiment ( N = 136), we tested whether effects of unconscious thought manifest for a complex analytical reasoning task for which experiential processing would offer no advantage. As predicted, participants in an unconscious thought condition outperformed participants in a control condition, suggesting that unconscious thought can be analytical. In sum, the current results support the existence of unconscious thinking processes that are distinct from experiential processes, and can be rational. Thus, the

  9. Not Merely Experiential: Unconscious Thought Can Be Rational

    Science.gov (United States)

    Garrison, Katie E.; Handley, Ian M.

    2017-01-01

    Individuals often form more reasonable judgments from complex information after a period of distraction vs. deliberation. This phenomenon has been attributed to sophisticated unconscious thought during the distraction period that integrates and organizes the information (Unconscious Thought Theory; Dijksterhuis and Nordgren, 2006). Yet, other research suggests that experiential processes are strengthened during the distraction (relative to deliberation) period, accounting for the judgment and decision benefit. We tested between these possibilities, hypothesizing that unconscious thought is distinct from experiential processes, and independently contributes to judgments and decisions during a distraction period. Using an established paradigm, Experiment 1 (N = 319) randomly induced participants into an experiential or rational mindset, after which participants received complex information describing three roommates to then consider consciously (i.e., deliberation) or unconsciously (i.e., distraction). Results revealed superior roommate judgments (but not choices) following distraction vs. deliberation, consistent with Unconscious Thought Theory. Mindset did not have an influence on roommate judgments. However, planned tests revealed a significant advantage of distraction only within the rational-mindset condition, which is contrary to the idea that experiential processing alone facilitates complex decision-making during periods of distraction. In a second experiment (N = 136), we tested whether effects of unconscious thought manifest for a complex analytical reasoning task for which experiential processing would offer no advantage. As predicted, participants in an unconscious thought condition outperformed participants in a control condition, suggesting that unconscious thought can be analytical. In sum, the current results support the existence of unconscious thinking processes that are distinct from experiential processes, and can be rational. Thus, the

  10. From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

    KAUST Repository

    Raitsos, Dionysios E.

    2014-04-23

    Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

  11. From silk to satellite: Half a century of ocean colour anomalies in the Northeast Atlantic

    KAUST Repository

    Raitsos, Dionysios E.; Pradhan, Yaswant; Lavender, Sam; Hoteit, Ibrahim; McQuatters-Gollop, Abigail L.; Reid, Philip Chris; Richardson, Anthony J.

    2014-01-01

    Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites - the Coastal Zone Colour Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948. © 2013 John Wiley & Sons Ltd.

  12. Rocket and satellite observations of electric fields and ion convection in the dayside auroral ionosphere

    International Nuclear Information System (INIS)

    Marklund, G.; Heelis, R.A.

    1984-06-01

    Electric field observations from two high-altitude rocket flights in the polar cusp have been combined with satellite observations of ion drifts to infer details of the electric field and convection pattern of the dayside auroral ionosphere. A region of shear flow reversal can be inferred from the electric field observations on one flight near 15.30 MLT 20 minutes after the Dynamics Explorer 2 satellite crossed through the same region. The drift patterns observed by the two spacecrafts were very similar although shifted by 0.5 degrees, a shift which is expected from the observed change in the interplanetary magnetic field (IMF) B(sub)Z component during this time. A region of rotational flow reversal was covered by the other flight shortly after magnetic noon, at the same time the DE-2 satellite travelled along roughly the dawn-dusk meridian. By joining points of equal potential, integrated from the two datasets and assuming the reversal boundary to be an equipotential, the instantaneous convection pattern could be drawn showing crescent-shaped convection contours in the dusk cell and more circular shaped contours in the dawn cell. (author)

  13. A high-resolution European dataset for hydrologic modeling

    Science.gov (United States)

    Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

    2013-04-01

    There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as

  14. Propositions toward the development of a psychological theory of thought

    Directory of Open Access Journals (Sweden)

    Shadrikov, Vladimir D.

    2017-03-01

    Full Text Available Thought is considered a psychological concept associated with an individual’s mental ex- istence. It is apparent that a great deal of research has been focused on thought as an area of study. however, there is no psychological theory of thought which provides an expla- nation for its nature and structural organization. So far, researchers have mainly looked at the ways this concept is expressed, rather than investigating what it actually is. In this study, however, based on studies of the functions of the psyche, mental processes, and the neurophysiological bases of mental activity, thought is identified as a need-emotion- intentional substance existing in the human being’s inner world. In keeping with this understanding of thought, the hypothesis that thought generation is caused by desire and experience (feeling and emotion is put forward. An individual’s thought is linked to his behavior or motivation for activity, and is followed by an emotional experience. The process of thought generation is regarded through the mechanism of behavioral motiva- tion. The primary purpose of this mechanism is to define the qualities of the external objects that serve for need satisfaction and functionality in individuals. The ability to generate thoughts is a feature of thinking related to an individual’s mental ability or frame of mind. From this standpoint, a person’s mentality is considered to be the capacity of the individual to generate thoughts and work through thoughts. It is shown that the abil- ity to generate thoughts and establish relationships within a stream of consciousness is characteristic of human intelligence. Some basic propositions toward a development of a psychological theory of thought are introduced.

  15. Thought Speed, Mood, and the Experience of Mental Motion.

    Science.gov (United States)

    Pronin, Emily; Jacobs, Elana

    2008-11-01

    This article presents a theoretical account relating thought speed to mood and psychological experience. Thought sequences that occur at a fast speed generally induce more positive affect than do those that occur slowly. Thought speed constitutes one aspect of mental motion. Another aspect involves thought variability, or the degree to which thoughts in a sequence either vary widely from or revolve closely around a theme. Thought sequences possessing more motion (occurring fast and varying widely) generally produce more positive affect than do sequences possessing little motion (occurring slowly and repetitively). When speed and variability oppose each other, such that one is low and the other is high, predictable psychological states also emerge. For example, whereas slow, repetitive thinking can prompt dejection, fast, repetitive thinking can prompt anxiety. This distinction is related to the fact that fast thinking involves greater actual and felt energy than slow thinking does. Effects of mental motion occur independent of the specific content of thought. Their consequences for mood and energy hold psychotherapeutic relevance. © 2008 Association for Psychological Science.

  16. ASSISTments Dataset from Multiple Randomized Controlled Experiments

    Science.gov (United States)

    Selent, Douglas; Patikorn, Thanaporn; Heffernan, Neil

    2016-01-01

    In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

  17. A Meta-Analysis on Unconscious Thought Effects

    NARCIS (Netherlands)

    Strick, M.A.; Dijksterhuis, A.J.; Bos, M.W.; Sjoerdsma, A.; Baaren, R.B. van; Nordgren, L.F.

    2011-01-01

    A meta-analysis was performed on the unconscious thought effect (UTE). All available published and unpublished data on unconscious thought were included. Our aims were to provide a statistically robust estimate of the effect size of the UTE, to identify significant moderators, and to

  18. Would the ‘real’ observed dataset stand up? A critical examination of eight observed gridded climate datasets for China

    International Nuclear Information System (INIS)

    Sun, Qiaohong; Miao, Chiyuan; Duan, Qingyun; Kong, Dongxian; Ye, Aizhong; Di, Zhenhua; Gong, Wei

    2014-01-01

    This research compared and evaluated the spatio-temporal similarities and differences of eight widely used gridded datasets. The datasets include daily precipitation over East Asia (EA), the Climate Research Unit (CRU) product, the Global Precipitation Climatology Centre (GPCC) product, the University of Delaware (UDEL) product, Precipitation Reconstruction over Land (PREC/L), the Asian Precipitation Highly Resolved Observational (APHRO) product, the Institute of Atmospheric Physics (IAP) dataset from the Chinese Academy of Sciences, and the National Meteorological Information Center dataset from the China Meteorological Administration (CN05). The meteorological variables focus on surface air temperature (SAT) or precipitation (PR) in China. All datasets presented general agreement on the whole spatio-temporal scale, but some differences appeared for specific periods and regions. On a temporal scale, EA shows the highest amount of PR, while APHRO shows the lowest. CRU and UDEL show higher SAT than IAP or CN05. On a spatial scale, the most significant differences occur in western China for PR and SAT. For PR, the difference between EA and CRU is the largest. When compared with CN05, CRU shows higher SAT in the central and southern Northwest river drainage basin, UDEL exhibits higher SAT over the Southwest river drainage system, and IAP has lower SAT in the Tibetan Plateau. The differences in annual mean PR and SAT primarily come from summer and winter, respectively. Finally, potential factors impacting agreement among gridded climate datasets are discussed, including raw data sources, quality control (QC) schemes, orographic correction, and interpolation techniques. The implications and challenges of these results for climate research are also briefly addressed. (paper)

  19. Estimating parameters for probabilistic linkage of privacy-preserved datasets.

    Science.gov (United States)

    Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H

    2017-07-10

    Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher

  20. Viking Seismometer PDS Archive Dataset

    Science.gov (United States)

    Lorenz, R. D.

    2016-12-01

    The Viking Lander 2 seismometer operated successfully for over 500 Sols on the Martian surface, recording at least one likely candidate Marsquake. The Viking mission, in an era when data handling hardware (both on board and on the ground) was limited in capability, predated modern planetary data archiving, and ad-hoc repositories of the data, and the very low-level record at NSSDC, were neither convenient to process nor well-known. In an effort supported by the NASA Mars Data Analysis Program, we have converted the bulk of the Viking dataset (namely the 49,000 and 270,000 records made in High- and Event- modes at 20 and 1 Hz respectively) into a simple ASCII table format. Additionally, since wind-generated lander motion is a major component of the signal, contemporaneous meteorological data are included in summary records to facilitate correlation. These datasets are being archived at the PDS Geosciences Node. In addition to brief instrument and dataset descriptions, the archive includes code snippets in the freely-available language 'R' to demonstrate plotting and analysis. Further, we present examples of lander-generated noise, associated with the sampler arm, instrument dumps and other mechanical operations.

  1. Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

    Science.gov (United States)

    Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

    2016-12-01

    operationally by the Air Force to specify neutral densities. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200km to 700 km.

  2. 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....

  3. Satellite Phenology Observations Inform Peak Season of Allergenic Grass Pollen Aerobiology across Two Continents

    Science.gov (United States)

    Huete, A. R.; Devadas, R.; Davies, J.

    2015-12-01

    Pollen exposure and prevalence of allergenic diseases have increased in many parts of the world during the last 30 years, with exposure to aeroallergen grass pollen expected to intensify with climate change, raising increased concerns for allergic diseases. The primary contributing factors to higher allergenic plant species presence are thought to be climate change, land conversion, and biotic mixing of species. Conventional methods for monitoring airborne pollen are hampered by a lack of sampling sites and heavily rely on meteorology with less attention to land cover updates and monitoring of key allergenic species phenology stages. Satellite remote sensing offers an alternative method to overcome the restrictive coverage afforded by in situ pollen networks by virtue of its synoptic coverage and repeatability of measurements that enable timely updates of land cover and land use information and monitoring landscape dynamics and interactions with human activity and climate. In this study, we assessed the potential of satellite observations of urban/peri-urban environments to directly inform landscape conditions conducive to pollen emissions. We found satellite measurements of grass cover phenological evolution to be highly correlated with in situ aerobiological grass pollen concentrations in five urban centres located across two hemispheres (Australia and France). Satellite greenness data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were found to be strongly synchronous with grass pollen aerobiology in both temperate grass dominated sites (France and Melbourne), as well as in Sydney, where multiple pollen peaks coincided with the presence of subtropical grasses. Employing general additive models (GAM), the satellite phenology data provided strong predictive capabilities to inform airborne pollen levels and forecast periods of grass pollen emissions at all five sites. Satellite phenology offer promising opportunities of improving public health risk

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

    Science.gov (United States)

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

    2016-12-01

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

  5. Implicit and explicit appraisals of the importance of intrusive thoughts.

    Science.gov (United States)

    Teachman, Bethany A; Woody, Sheila R; Magee, Joshua C

    2006-06-01

    To evaluate cognitive theories of obsessions, the current study experimentally manipulated appraisals of the importance of intrusive thoughts. Undergraduate students (N = 156) completed measures of obsessive-compulsive disorder (OCD) symptoms and beliefs and were primed with a list of commonly reported unwanted thoughts. Participants were then informed that unwanted thoughts are either (1) significant and indicative of their personal values, or (2) meaningless, or participants (3) received no instructions about unwanted thoughts. Participants then completed implicit and explicit measures of self-evaluation and interpretations of their unwanted thoughts. Results indicated that the manipulation shifted implicit appraisals of unwanted thoughts in the expected direction, but not self-evaluations of morality or dangerousness. Interestingly, explicit self-esteem and beliefs about the significance of unwanted thoughts were associated with measures of OCD beliefs, whereas implicit self-evaluations of dangerousness were better predicted by the interaction of pre-existing OCD beliefs with the manipulation. Results are discussed in terms of divergent predictors of implicit and explicit responses to unwanted thoughts.

  6. The relation between language, culture, and thought.

    Science.gov (United States)

    Imai, Mutsumi; Kanero, Junko; Masuda, Takahiko

    2016-04-01

    The relationship between culture, language, and thought has long been one of the most important topics for those who wish to understand the nature of human cognition. This issue has been investigated for decades across a broad range of research disciplines. However, there has been scant communication across these different disciplines, a situation largely arising through differences in research interests and discrepancies in the definitions of key terms such as 'culture,' 'language,' and 'thought.' This article reviews recent trends in research on the relation between language, culture and thought to capture how cognitive psychology and cultural psychology have defined 'language' and 'culture,' and how this issue was addressed within each research discipline. We then review recent research conducted in interdisciplinary perspectives, which directly compared the roles of culture and language. Finally, we highlight the importance of considering the complex interplay between culture and language to provide a comprehensive picture of how language and culture affect thought. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Homogenised Australian climate datasets used for climate change monitoring

    International Nuclear Information System (INIS)

    Trewin, Blair; Jones, David; Collins; Dean; Jovanovic, Branislava; Braganza, Karl

    2007-01-01

    Full text: The Australian Bureau of Meteorology has developed a number of datasets for use in climate change monitoring. These datasets typically cover 50-200 stations distributed as evenly as possible over the Australian continent, and have been subject to detailed quality control and homogenisation.The time period over which data are available for each element is largely determined by the availability of data in digital form. Whilst nearly all Australian monthly and daily precipitation data have been digitised, a significant quantity of pre-1957 data (for temperature and evaporation) or pre-1987 data (for some other elements) remains to be digitised, and is not currently available for use in the climate change monitoring datasets. In the case of temperature and evaporation, the start date of the datasets is also determined by major changes in instruments or observing practices for which no adjustment is feasible at the present time. The datasets currently available cover: Monthly and daily precipitation (most stations commence 1915 or earlier, with many extending back to the late 19th century, and a few to the mid-19th century); Annual temperature (commences 1910); Daily temperature (commences 1910, with limited station coverage pre-1957); Twice-daily dewpoint/relative humidity (commences 1957); Monthly pan evaporation (commences 1970); Cloud amount (commences 1957) (Jovanovic etal. 2007). As well as the station-based datasets listed above, an additional dataset being developed for use in climate change monitoring (and other applications) covers tropical cyclones in the Australian region. This is described in more detail in Trewin (2007). The datasets already developed are used in analyses of observed climate change, which are available through the Australian Bureau of Meteorology website (http://www.bom.gov.au/silo/products/cli_chg/). They are also used as a basis for routine climate monitoring, and in the datasets used for the development of seasonal

  8. Introduction of a simple-model-based land surface dataset for Europe

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2015-04-01

    Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984-2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar

  9. Data Mining for Imbalanced Datasets: An Overview

    Science.gov (United States)

    Chawla, Nitesh V.

    A dataset is imbalanced if the classification categories are not approximately equally represented. Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced data. Additionally the distribution of the testing data may differ from that of the training data, and the true misclassification costs may be unknown at learning time. Predictive accuracy, a popular choice for evaluating performance of a classifier, might not be appropriate when the data is imbalanced and/or the costs of different errors vary markedly. In this Chapter, we discuss some of the sampling techniques used for balancing the datasets, and the performance measures more appropriate for mining imbalanced datasets.

  10. Answering the right question - integration of InSAR with other datasets

    Science.gov (United States)

    Holley, Rachel; McCormack, Harry; Burren, Richard

    2014-05-01

    The capabilities of satellite Interferometric Synthetic Aperture Radar (InSAR) are well known, and utilized across a wide range of academic and commercial applications. However there is a tendency, particularly in commercial applications, for users to ask 'What can we study with InSAR?'. When establishing a new technique this approach is important, but InSAR has been possible for 20 years now and, even accounting for new and innovative algorithms, this ground has been thoroughly explored. Too many studies conclude 'We show the ground is moving here, by this much', and mention the wider context as an afterthought. The focus needs to shift towards first asking the right questions - in fields as diverse as hazard awareness, resource optimization, financial considerations and pure scientific enquiry - and then working out how to achieve the best possible answers. Depending on the question, InSAR (and ground deformation more generally) may provide a large or small contribution to the overall solution, and there are usually benefits to integrating a number of techniques to capitalize on the complementary capabilities and provide the most useful measurements. However, there is still a gap between measurements and answers, and unlocking the value of the data relies heavily on appropriate visualization, integrated analysis, communication between technique and application experts, and appropriate use of modelling. We present a number of application examples, and demonstrate how their usefulness can be transformed by moving from a focus on data to answers - integrating complementary geodetic, geophysical and geological datasets and geophysical modeling with appropriate visualization, to enable comprehensive solution-focused interpretation. It will also discuss how forthcoming developments are likely to further advance realisation of the full potential satellite InSAR holds.

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

    Science.gov (United States)

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

    2017-12-01

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

  12. [An evaluation of a symposium via satellite on alcoholism and drug dependence].

    Science.gov (United States)

    Ríos-Espinosa, E; Martínez-Salgado, H; Ruíz-Tapia, R; Domínguez-Cherit, L

    1993-01-01

    Results of a test given to participants in a symposium on alcoholism and drug abuse are presented. The symposium was broadcast via satellite simultaneously to five cities in Mexico, and included 8 pretaped panels covering topics on alcoholism and drug abuse. The methodology used for broadcasting the symposium allowed the interactive exchange of information between expert lecturers and participants. The quantitative and qualitative evaluation used the pretest-posttest design. Most of the participants were physicians (28.9%) followed by psychologists (25.7%) and social workers (18.1%). The global cognitive change among participants was 6 per cent. Almost 77 per cent of participants had scores between 51 and 70 points (over a possible maximum score of 100) in the pre-evaluation test, and 76.4 per cent had scores between 61 and 80 points in the postevaluation test. Health professionals with 1-3 years of experience had the largest change in scores (9%), followed by those with 3 to 5 years experience (8%). Professionals with 5 to 10 years of experience had a change of 5 per cent. Physicians showed the greatest cognitive change (7%) followed by psychologists and social workers with 5 per cent change. In the qualitative evaluation, 87.6 per cent of participants thought that the educational method used was "Excellent" of "Good". With respect to the satellite transmission, 79.4 per cent of participants thought it was "Excellent" or "Good". It is concluded that this type of educational events are useful in reaching health professionals who otherwise would not have access to specialized and updated information.(ABSTRACT TRUNCATED AT 250 WORDS)

  13. Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

    Science.gov (United States)

    Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

    2018-06-01

    Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

  14. A hybrid organic-inorganic perovskite dataset

    Science.gov (United States)

    Kim, Chiho; Huan, Tran Doan; Krishnan, Sridevi; Ramprasad, Rampi

    2017-05-01

    Hybrid organic-inorganic perovskites (HOIPs) have been attracting a great deal of attention due to their versatility of electronic properties and fabrication methods. We prepare a dataset of 1,346 HOIPs, which features 16 organic cations, 3 group-IV cations and 4 halide anions. Using a combination of an atomic structure search method and density functional theory calculations, the optimized structures, the bandgap, the dielectric constant, and the relative energies of the HOIPs are uniformly prepared and validated by comparing with relevant experimental and/or theoretical data. We make the dataset available at Dryad Digital Repository, NoMaD Repository, and Khazana Repository (http://khazana.uconn.edu/), hoping that it could be useful for future data-mining efforts that can explore possible structure-property relationships and phenomenological models. Progressive extension of the dataset is expected as new organic cations become appropriate within the HOIP framework, and as additional properties are calculated for the new compounds found.

  15. Genomics dataset of unidentified disclosed isolates

    Directory of Open Access Journals (Sweden)

    Bhagwan N. Rekadwad

    2016-09-01

    Full Text Available Analysis of DNA sequences is necessary for higher hierarchical classification of the organisms. It gives clues about the characteristics of organisms and their taxonomic position. This dataset is chosen to find complexities in the unidentified DNA in the disclosed patents. A total of 17 unidentified DNA sequences were thoroughly analyzed. The quick response codes were generated. AT/GC content of the DNA sequences analysis was carried out. The QR is helpful for quick identification of isolates. AT/GC content is helpful for studying their stability at different temperatures. Additionally, a dataset on cleavage code and enzyme code studied under the restriction digestion study, which helpful for performing studies using short DNA sequences was reported. The dataset disclosed here is the new revelatory data for exploration of unique DNA sequences for evaluation, identification, comparison and analysis. Keywords: BioLABs, Blunt ends, Genomics, NEB cutter, Restriction digestion, Short DNA sequences, Sticky ends

  16. Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

    Science.gov (United States)

    Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

    2017-06-01

    Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

  17. IPCC Socio-Economic Baseline Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land...

  18. The LANDFIRE Refresh strategy: updating the national dataset

    Science.gov (United States)

    Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Martin, Charley

    2013-01-01

    The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

  19. Satellite imagery and the Department of Safeguards

    International Nuclear Information System (INIS)

    Chitumbo, K.; Bunney, J.; Leve, G.; Robb, S.

    2001-01-01

    Full text: The presentation examines some of the challenges the Satellite Imagery and Analysis Laboratory (SIAL) is facing in supporting Strengthened Safeguards. It focuses on the analytical process, starting with specifying initial tasking and continuing through to end products that are a direct result of in-house analysis. In addition it also evaluates the advantages and disadvantages of SIAL's mission and introduces external forces that the agency must consider, but cannot itself, predict or control. Although SIAL's contribution to tasks relating to Article 2a(iii) of the Additional Protocol are known and are presently of great benefit to operations areas, this is only one aspect of its work. SIAL's ability to identify and analyze historical satellite imagery data has the advantage of permitting operations to take a more in depth view of a particular area of interest's (AOI) development, and thus may permit operations to confirm or refute specific assertions relating to the AOI's function or abilities. These assertions may originate in-house or may be open source reports the agency feels it is obligated to explore. SIAL's mission is unique in the world of imagery analysis. Its aim is to support all operations areas equally and in doing so it must maintain global focus. The task is tremendous, but the resultant coverage and concentration of unique expertise will allow SIAL to develop and provide operations with datasets that can be exploited in standalone mode or be incorporated into new cutting edge tools to be developed in SGIT. At present SIAL relies on two remote sensors, IKONOS-2 and EROS-AI, for present high- resolution imagery data and is using numerous sources for historical, pre 1999, data. A multiplicity of sources for high-resolution data is very important to SIAL, but is something that it cannot influence. It is hoped that the planned launch of two new sensors by Summer 2002 will be successful and will offer greater flexibility for image collection

  20. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    Directory of Open Access Journals (Sweden)

    Patrick Marina

    2017-01-01

    Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

  1. Freight from Space: Evaluating Freight Activity and Emissions Trends from Satellite Data

    Science.gov (United States)

    Bickford, E.; Holloway, T.; Oberman, J.; Janssen, M.

    2012-12-01

    Heavy duty diesel freight trucks are the fastest growing source of highway emissions in the U.S., with domestic freight tonnage projected to double by 2050. Highway diesel vehicles currently account for 42% of on-road emissions of nitrogen oxides (NOx), 58% of on-road fine particulate (PM2.5) emissions, and 21% of on-road carbon dioxide emissions. Because most surface air quality monitors are located in densely populated areas and not rural highways, it is difficult to use ground-based observations to validate spatial trends in transportation emissions. Therefore, we have employed satellite retrievals from the OMI instrument to inform surface freight transportation inventory estimates by validating modeled tropospheric vertical column total nitrogen dioxide (NO2) against satellite observations. For this research we built a roadway-by-roadway bottom-up diesel truck emissions inventory using GIS, the U.S. Federal Highway Administration's Freight Analysis Framework (FAF) activity dataset, and the U.S. Environmental Protection Agency's MOVES emissions model. We use freight rail emissions from the Eastern Regional Technical Advisory Committee (ERTAC), inventory emissions from the Lake Michigan's Air Directors Consortium (LADCO) and the EPA's Community Multiscale Air Qualiy (CMAQ) model to simulate ground-level and tropospheric column concentrations of NO2. We also use the combination of models and satellite data to evaluate weekday-weekend patterns of NO2 concentrations and the relative contributions of highway diesel vehicles, highway gasoline vehicles, and freight rail to transportation-related pollution. This research presents the first evaluation of surface freight transport from space-based observations. We find satellite retrievals of surface pollutants provide a useful data tool for evaluating air quality models and constraining emissions sources.

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

    Science.gov (United States)

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

    2018-03-01

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

  3. The Concept of Paleologic Thought According to Arieti

    Directory of Open Access Journals (Sweden)

    João Carlos Melo

    2014-10-01

    Full Text Available The Aristotelic Logic, which is characterized by four laws, is commonly accepted as being representative of normal though, when considered in its formal aspect. Arieti defends the existence of another logic, one that he has designated "Paleological", which was dominant in human beings in the beginning of their evolution, and that also occurs in certain characteristics of infantile thought, as well as in the primary process (manner in which the unconscious operates. The same author considers that this logic, whoch is quiescent, emerges in schizophrenic thought, dominating and overlapping the Aristotelian logic. In order to escape from anguish, the shizophrenic patient abandons Aristotelian norms of thought and adopts the Paleological form, because by interpreting reality, in light of Aristotelian logic, it's felt to be threatening and unbearable. Finally, Arieti explains that the principles of Paleological thought don't explain the phenomenon dynamically, merely formally. The study of psychodinamic mechanisms reveals what and why (content and motivation, while the study of formal mechanims reveal how, thoughts and feelings are processed.

  4. Omicseq: a web-based search engine for exploring omics datasets

    Science.gov (United States)

    Sun, Xiaobo; Pittard, William S.; Xu, Tianlei; Chen, Li; Zwick, Michael E.; Jiang, Xiaoqian; Wang, Fusheng

    2017-01-01

    Abstract The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. PMID:28402462

  5. Satellite myths

    Science.gov (United States)

    Easton, Roger L.; Hall, David

    2008-01-01

    Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.

  6. Nanoparticle-organic pollutant interaction dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  7. Communication satellite applications

    Science.gov (United States)

    Pelton, Joseph N.

    The status and future of the technologies, numbers and services provided by communications satellites worldwide are explored. The evolution of Intelsat satellites and the associated earth terminals toward high-rate all-digital telephony, data, facsimile, videophone, videoconferencing and DBS capabilities are described. The capabilities, services and usage of the Intersputnik, Eutelsat, Arabsat and Palapa systems are also outlined. Domestic satellite communications by means of the Molniya, ANIK, Olympus, Intelsat and Palapa spacecraft are outlined, noting the fast growth of the market and the growing number of different satellite manufacturers. The technical, economic and service definition issues surrounding DBS systems are discussed, along with presently operating and planned maritime and aeronautical communications and positioning systems. Features of search and rescue and tracking, data, and relay satellite systems are summarized, and services offered or which will be offered by every existing or planned communication satellite worldwide are tabulated.

  8. Pharmacy student engagement, performance, and perception in a flipped satellite classroom.

    Science.gov (United States)

    McLaughlin, Jacqueline E; Griffin, LaToya M; Esserman, Denise A; Davidson, Christopher A; Glatt, Dylan M; Roth, Mary T; Gharkholonarehe, Nastaran; Mumper, Russell J

    2013-11-12

    To determine whether "flipping" a traditional basic pharmaceutics course delivered synchronously to 2 satellite campuses would improve student academic performance, engagement, and perception. In 2012, the basic pharmaceutics course was flipped and delivered to 22 satellite students on 2 different campuses. Twenty-five condensed, recorded course lectures were placed on the course Web site for students to watch prior to class. Scheduled class periods were dedicated to participating in active-learning exercises. Students also completed 2 course projects, 3 midterm examinations, 8 graded quizzes, and a cumulative and comprehensive final examination. Results of a survey administered at the beginning and end of the flipped course in 2012 revealed an increase in students' support for learning content prior to class and using class time for more applied learning (p=0.01) and in the belief that learning key foundational content prior to coming to class greatly enhanced in-class learning (p=0.001). Significantly more students preferred the flipped classroom format after completing the course (89.5%) than before completing the course (34.6%). Course evaluation responses and final examination performance did not differ significantly for 2011 when the course was taught using a traditional format and the 2012 flipped-course format. Qualitative findings suggested that the flipped classroom promoted student empowerment, development, and engagement. The flipped pharmacy classroom can enhance the quality of satellite students' experiences in a basic pharmaceutics course through thoughtful course design, enriched dialogue, and promotion of learner autonomy.

  9. Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Quaas, Johannes; Ming, Yi; Menon, Surabi; Takemura, Toshihiko; Wang, Minghuai; Penner, Joyce E.; Gettelman, Andrew; Lohmann, Ulrike; Bellouin, Nicolas; Boucher, Olivier; Sayer, Andrew M.; Thomas, Gareth E.; McComiskey, Allison; Feingold, Graham; Hoose, Corinna; Kristjansson, Jon Egill; Liu, Xiaohong; Balkanski, Yves; Donner, Leo J.; Ginoux, Paul A.; Stier, Philip; Feichter, Johann; Sednev, Igor; Bauer, Susanne E.; Koch, Dorothy; Grainger, Roy G.; Kirkevag, Alf; Iversen, Trond; Seland, Oyvind; Easter, Richard; Ghan, Steven J.; Rasch, Philip J.; Morrison, Hugh; Lamarque, Jean-Francois; Iacono, Michael J.; Kinne, Stefan; Schulz, Michael

    2009-04-10

    Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd

  10. Current trends in satellite based emergency mapping - the need for harmonisation

    Science.gov (United States)

    Voigt, Stefan

    2013-04-01

    During the past years, the availability and use of satellite image data to support disaster management and humanitarian relief organisations has largely increased. The automation and data processing techniques are greatly improving as well as the capacity in accessing and processing satellite imagery in getting better globally. More and more global activities via the internet and through global organisations like the United Nations or the International Charter Space and Major Disaster engage in the topic, while at the same time, more and more national or local centres engage rapid mapping operations and activities. In order to make even more effective use of this very positive increase of capacity, for the sake of operational provision of analysis results, for fast validation of satellite derived damage assessments, for better cooperation in the joint inter agency generation of rapid mapping products and for general scientific use, rapid mapping results in general need to be better harmonized, if not even standardized. In this presentation, experiences from various years of rapid mapping gained by the DLR Center for satellite based Crisis Information (ZKI) within the context of the national activities, the International Charter Space and Major Disasters, GMES/Copernicus etc. are reported. Furthermore, an overview on how automation, quality assurance and optimization can be achieved through standard operation procedures within a rapid mapping workflow is given. Building on this long term rapid mapping experience, and building on the DLR initiative to set in pace an "International Working Group on Satellite Based Emergency Mapping" current trends in rapid mapping are discussed and thoughts on how the sharing of rapid mapping information can be optimized by harmonizing analysis results and data structures are presented. Such an harmonization of analysis procedures, nomenclatures and representations of data as well as meta data are the basis to better cooperate within

  11. Framework for Interactive Parallel Dataset Analysis on the Grid

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, David A.; Ananthan, Balamurali; /Tech-X Corp.; Johnson, Tony; Serbo, Victor; /SLAC

    2007-01-10

    We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

  12. Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

    Science.gov (United States)

    Maskey, M.; Ramachandran, R.; Miller, J.

    2017-12-01

    Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

  13. An Affinity Propagation Clustering Algorithm for Mixed Numeric and Categorical Datasets

    Directory of Open Access Journals (Sweden)

    Kang Zhang

    2014-01-01

    Full Text Available Clustering has been widely used in different fields of science, technology, social science, and so forth. In real world, numeric as well as categorical features are usually used to describe the data objects. Accordingly, many clustering methods can process datasets that are either numeric or categorical. Recently, algorithms that can handle the mixed data clustering problems have been developed. Affinity propagation (AP algorithm is an exemplar-based clustering method which has demonstrated good performance on a wide variety of datasets. However, it has limitations on processing mixed datasets. In this paper, we propose a novel similarity measure for mixed type datasets and an adaptive AP clustering algorithm is proposed to cluster the mixed datasets. Several real world datasets are studied to evaluate the performance of the proposed algorithm. Comparisons with other clustering algorithms demonstrate that the proposed method works well not only on mixed datasets but also on pure numeric and categorical datasets.

  14. Thought Action Fusion in Obsessive Compulsive Disorder

    Directory of Open Access Journals (Sweden)

    Sahin CIFTCI

    2013-11-01

    Full Text Available Thought Action Fusion (TAF is defined as tought and action percieved as equivalent to each other or as an exaggerated power given to idea. With the usage of “Thought Action Fusion Scale” which is created by Shafran (1996, is began to investigate its role in psychopathologies. Researches about the three-component structure which has TAF-Likelihood-Self, TAF-Likelihood-Others, TAF-Moral, are concentrated especially around the obsessive compulsive disorder (OCD. TAF alleged including a certain level also in the normal population, was seen in the relationship with the inflated responsability in OCD, thought suppression and neutralising, was tried to explain the direction of this relationship in the mediationel model framework.

  15. Three-dimensional information extraction from GaoFen-1 satellite images for landslide monitoring

    Science.gov (United States)

    Wang, Shixin; Yang, Baolin; Zhou, Yi; Wang, Futao; Zhang, Rui; Zhao, Qing

    2018-05-01

    To more efficiently use GaoFen-1 (GF-1) satellite images for landslide emergency monitoring, a Digital Surface Model (DSM) can be generated from GF-1 across-track stereo image pairs to build a terrain dataset. This study proposes a landslide 3D information extraction method based on the terrain changes of slope objects. The slope objects are mergences of segmented image objects which have similar aspects; and the terrain changes are calculated from the post-disaster Digital Elevation Model (DEM) from GF-1 and the pre-disaster DEM from GDEM V2. A high mountain landslide that occurred in Wenchuan County, Sichuan Province is used to conduct a 3D information extraction test. The extracted total area of the landslide is 22.58 ha; the displaced earth volume is 652,100 m3; and the average sliding direction is 263.83°. The accuracies of them are 0.89, 0.87 and 0.95, respectively. Thus, the proposed method expands the application of GF-1 satellite images to the field of landslide emergency monitoring.

  16. Chemical product and function dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Merged product weight fraction and chemical function data. This dataset is associated with the following publication: Isaacs , K., M. Goldsmith, P. Egeghy , K....

  17. Advancing the capabilities of reservoir remote sensing by leveraging multi-source satellite data

    Science.gov (United States)

    Gao, H.; Zhang, S.; Zhao, G.; Li, Y.

    2017-12-01

    With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.

  18. Thought confidence as a determinant of persuasion: the self-validation hypothesis.

    Science.gov (United States)

    Petty, Richard E; Briñol, Pablo; Tormala, Zakary L

    2002-05-01

    Previous research in the domain of attitude change has described 2 primary dimensions of thinking that impact persuasion processes and outcomes: the extent (amount) of thinking and the direction (valence) of issue-relevant thought. The authors examined the possibility that another, more meta-cognitive aspect of thinking is also important-the degree of confidence people have in their own thoughts. Four studies test the notion that thought confidence affects the extent of persuasion. When positive thoughts dominate in response to a message, increasing confidence in those thoughts increases persuasion, but when negative thoughts dominate, increasing confidence decreases persuasion. In addition, using self-reported and manipulated thought confidence in separate studies, the authors provide evidence that the magnitude of the attitude-thought relationship depends on the confidence people have in their thoughts. Finally, the authors also show that these self-validation effects are most likely in situations that foster high amounts of information processing activity.

  19. History of Satellite TV Broadcasting and Satellite Broadcasting Market in Turkey

    Directory of Open Access Journals (Sweden)

    Mihalis KUYUCU

    2015-09-01

    Full Text Available The present study analyses the satellite broadcasting that is the first important development that emerged as a result of digitalization in communication technologies and its reflections in Turkey. As the first milestone in the globalization of television broadcasting, satellite broadcasting provided substantial contribution towards the development of the media. Satellite bro adcasting both increased the broadcasting quality and geographical coverage of the television media. A conceptual study was carried out in the first part of the study in connection with the history of satellite broadcasting in Turkey and across the world. In the research part of the study, an analysis was performed on 160 television channels that broadcast in Turkey via Turksat Satellite. Economic structure of the television channels broadcasting in Turkey via satellite was studied and an analysis was perfo rmed on the operational structure of the channels. As a result of the study, it was emphasized that the television channels broadcasting via satellite platform also use other platforms for the purpose of spreading their broadcasts and television channel ow ners make investments in different branches of the media, too. Capital owners invest in different business areas other than the media although television channels broadcasting via Turksat mostly focus on thematic broadcasting and make effort to generate ec onomic income from advertisements. Delays are encountered in the course of the convergence between the new media and television channels that broadcast only from the satellite platform and such television channels experience more economic problems than the other channels. New media and many TV broadcasting platforms emerged as a result of the developments in the communication technologies. In television broadcasting, satellite platform is not an effective platform on its own. Channels make effort to reach t o more people by using other platforms in addition to

  20. Relative tracking control of constellation satellites considering inter-satellite link

    Science.gov (United States)

    Fakoor, M.; Amozegary, F.; Bakhtiari, M.; Daneshjou, K.

    2017-11-01

    In this article, two main issues related to the large-scale relative motion of satellites in the constellation are investigated to establish the Inter Satellite Link (ISL) which means the dynamic and control problems. In the section related to dynamic problems, a detailed and effective analytical solution is initially provided for the problem of satellite relative motion considering perturbations. The direct geometric method utilizing spherical coordinates is employed to achieve this solution. The evaluation of simulation shows that the solution obtained from the geometric method calculates the relative motion of the satellite with high accuracy. Thus, the proposed analytical solution will be applicable and effective. In the section related to control problems, the relative tracking control system between two satellites will be designed in order to establish a communication link between the satellites utilizing analytical solution for relative motion of satellites with respect to the reference trajectory. Sliding mode control approach is employed to develop the relative tracking control system for body to body and payload to payload tracking control. Efficiency of sliding mode control approach is compared with PID and LQR controllers. Two types of payload to payload tracking control considering with and without payload degree of freedom are designed and suitable one for practical ISL applications is introduced. Also, Fuzzy controller is utilized to eliminate the control input in the sliding mode controller.

  1. Mobile satellite service communications tests using a NASA satellite

    Science.gov (United States)

    Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.

    1995-01-01

    Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.

  2. Cognitive restructuring of gambling-related thoughts: A systematic review.

    Science.gov (United States)

    Chrétien, Maxime; Giroux, Isabelle; Goulet, Annie; Jacques, Christian; Bouchard, Stéphane

    2017-12-01

    Gamblers' thoughts have a fundamental influence on their gambling problem. Cognitive restructuring is the intervention of choice to correct those thoughts. However, certain difficulties are noted in the application of cognitive restructuring techniques and the comprehension of their guidelines. Furthermore, the increase of skill game players (e.g. poker) entering treatment creates a challenge for therapists, as these gamblers present with different thoughts than those of the gamblers usually encountered in treatment (e.g. chance-only games like electronic gambling machines). This systematic review aims to describe how cognitive restructuring is carried out with gamblers based on the evidence available in empirical studies that include cognitive interventions for gambling. Of the 2607 studies collected, 39 were retained. The results highlight exposure as the most frequently used technique to facilitate identification of gambling-related thoughts (imaginal=28.2%; in vivo=10.3%). More than half of the studies (69.2%) clearly reported therapeutic techniques aimed to correct gamblers' thoughts, of which 37% involved visual support to challenge those thoughts (e.g. ABC log). Of the 39 studies retained, 48.7% included skill game players (i.e., poker, blackjack, sports betting) in their sample. However, none of these studies mentioned whether cognitive restructuring had been adapted for these gamblers. Several terms referring to gamblers' thoughts were used interchangeably (e.g. erroneous, dysfunctional or inadequate thoughts), although each of these terms could refer to specific content. Clinical implications of the results are discussed with regard to the needs of therapists. This review also suggests recommendations for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. General Purpose Multimedia Dataset - GarageBand 2008

    DEFF Research Database (Denmark)

    Meng, Anders

    This document describes a general purpose multimedia data-set to be used in cross-media machine learning problems. In more detail we describe the genre taxonomy applied at http://www.garageband.com, from where the data-set was collected, and how the taxonomy have been fused into a more human...... understandable taxonomy. Finally, a description of various features extracted from both the audio and text are presented....

  4. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....

  5. Educational Thoughts on "Three

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    With simple, light touches but deep philosophical thought, this article analyses the problems in China’s education, and at the same time, it probes into the problems of effectiveness of educational theories and methods from the considerations of THREE as the basic starting point.

  6. Omicseq: a web-based search engine for exploring omics datasets.

    Science.gov (United States)

    Sun, Xiaobo; Pittard, William S; Xu, Tianlei; Chen, Li; Zwick, Michael E; Jiang, Xiaoqian; Wang, Fusheng; Qin, Zhaohui S

    2017-07-03

    The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve 'findability' of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. GALAXIES IN X-RAY GROUPS. III. SATELLITE COLOR AND MORPHOLOGY TRANSFORMATIONS

    Energy Technology Data Exchange (ETDEWEB)

    George, Matthew R.; Ma, Chung-Pei [Department of Astronomy, University of California, Berkeley, CA 94720 (United States); Bundy, Kevin; Leauthaud, Alexie; Vulcani, Benedetta [Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU, WPI), Todai Institutes for Advanced Study, University of Tokyo, Kashiwa 277-8583 (Japan); Tinker, Jeremy [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Wechsler, Risa H. [Kavli Institute for Particle Astrophysics and Cosmology, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Finoguenov, Alexis, E-mail: mgeorge@astro.berkeley.edu [Department of Physics, University of Helsinki, Gustaf Haellstroemin katu 2a, FI-00014 Helsinki (Finland)

    2013-06-20

    While the star formation rates and morphologies of galaxies have long been known to correlate with their local environment, the process by which these correlations are generated is not well understood. Galaxy groups are thought to play an important role in shaping the physical properties of galaxies before entering massive clusters at low redshift, and transformations of satellite galaxies likely dominate the buildup of local environmental correlations. To illuminate the physical processes that shape galaxy evolution in dense environments, we study a sample of 116 X-ray selected galaxy groups at z = 0.2-1 with halo masses of 10{sup 13}-10{sup 14} M{sub Sun} and centroids determined with weak lensing. We analyze morphologies based on Hubble Space Telescope imaging and colors determined from 31 photometric bands for a stellar mass-limited population of 923 satellite galaxies and a comparison sample of 16,644 field galaxies. Controlling for variations in stellar mass across environments, we find significant trends in the colors and morphologies of satellite galaxies with group-centric distance and across cosmic time. Specifically at low stellar mass (log (M{sub *}/M{sub Sun }) = 9.8-10.3), the fraction of disk-dominated star-forming galaxies declines from >50% among field galaxies to <20% among satellites near the centers of groups. This decline is accompanied by a rise in quenched galaxies with intermediate bulge+disk morphologies, and only a weak increase in red bulge-dominated systems. These results show that both color and morphology are influenced by a galaxy's location within a group halo. We suggest that strangulation and disk fading alone are insufficient to explain the observed morphological dependence on environment, and that galaxy mergers or close tidal encounters must play a role in building up the population of quenched galaxies with bulges seen in dense environments at low redshift.

  8. GALAXIES IN X-RAY GROUPS. III. SATELLITE COLOR AND MORPHOLOGY TRANSFORMATIONS

    International Nuclear Information System (INIS)

    George, Matthew R.; Ma, Chung-Pei; Bundy, Kevin; Leauthaud, Alexie; Vulcani, Benedetta; Tinker, Jeremy; Wechsler, Risa H.; Finoguenov, Alexis

    2013-01-01

    While the star formation rates and morphologies of galaxies have long been known to correlate with their local environment, the process by which these correlations are generated is not well understood. Galaxy groups are thought to play an important role in shaping the physical properties of galaxies before entering massive clusters at low redshift, and transformations of satellite galaxies likely dominate the buildup of local environmental correlations. To illuminate the physical processes that shape galaxy evolution in dense environments, we study a sample of 116 X-ray selected galaxy groups at z = 0.2-1 with halo masses of 10 13 -10 14 M ☉ and centroids determined with weak lensing. We analyze morphologies based on Hubble Space Telescope imaging and colors determined from 31 photometric bands for a stellar mass-limited population of 923 satellite galaxies and a comparison sample of 16,644 field galaxies. Controlling for variations in stellar mass across environments, we find significant trends in the colors and morphologies of satellite galaxies with group-centric distance and across cosmic time. Specifically at low stellar mass (log (M * /M ☉ ) = 9.8-10.3), the fraction of disk-dominated star-forming galaxies declines from >50% among field galaxies to <20% among satellites near the centers of groups. This decline is accompanied by a rise in quenched galaxies with intermediate bulge+disk morphologies, and only a weak increase in red bulge-dominated systems. These results show that both color and morphology are influenced by a galaxy's location within a group halo. We suggest that strangulation and disk fading alone are insufficient to explain the observed morphological dependence on environment, and that galaxy mergers or close tidal encounters must play a role in building up the population of quenched galaxies with bulges seen in dense environments at low redshift.

  9. Genome-wide characterization of centromeric satellites from multiple mammalian genomes.

    Science.gov (United States)

    Alkan, Can; Cardone, Maria Francesca; Catacchio, Claudia Rita; Antonacci, Francesca; O'Brien, Stephen J; Ryder, Oliver A; Purgato, Stefania; Zoli, Monica; Della Valle, Giuliano; Eichler, Evan E; Ventura, Mario

    2011-01-01

    Despite its importance in cell biology and evolution, the centromere has remained the final frontier in genome assembly and annotation due to its complex repeat structure. However, isolation and characterization of the centromeric repeats from newly sequenced species are necessary for a complete understanding of genome evolution and function. In recent years, various genomes have been sequenced, but the characterization of the corresponding centromeric DNA has lagged behind. Here, we present a computational method (RepeatNet) to systematically identify higher-order repeat structures from unassembled whole-genome shotgun sequence and test whether these sequence elements correspond to functional centromeric sequences. We analyzed genome datasets from six species of mammals representing the diversity of the mammalian lineage, namely, horse, dog, elephant, armadillo, opossum, and platypus. We define candidate monomer satellite repeats and demonstrate centromeric localization for five of the six genomes. Our analysis revealed the greatest diversity of centromeric sequences in horse and dog in contrast to elephant and armadillo, which showed high-centromeric sequence homogeneity. We could not isolate centromeric sequences within the platypus genome, suggesting that centromeres in platypus are not enriched in satellite DNA. Our method can be applied to the characterization of thousands of other vertebrate genomes anticipated for sequencing in the near future, providing an important tool for annotation of centromeres.

  10. Interim Service ISDN Satellite (ISIS) simulator development for advanced satellite designs and experiments

    Science.gov (United States)

    Pepin, Gerard R.

    1992-01-01

    The simulation development associated with the network models of both the Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures is documented. The ISIS Network Model design represents satellite systems like the Advanced Communications Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) Program, moves all control and switching functions on-board the next generation ISDN communications satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete event simulation experiments will be performed with these models using various traffic scenarios, design parameters, and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.

  11. 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

  12. Turkey Run Landfill Emissions Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — landfill emissions measurements for the Turkey run landfill in Georgia. This dataset is associated with the following publication: De la Cruz, F., R. Green, G....

  13. Dsm Based Orientation of Large Stereo Satellite Image Blocks

    Science.gov (United States)

    d'Angelo, P.; Reinartz, P.

    2012-07-01

    High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

  14. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  15. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2017-01-01

    The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.

  16. Satellite image collection optimization

    Science.gov (United States)

    Martin, William

    2002-09-01

    Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

  17. An Analysis of the GTZAN Music Genre Dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2012-01-01

    Most research in automatic music genre recognition has used the dataset assembled by Tzanetakis et al. in 2001. The composition and integrity of this dataset, however, has never been formally analyzed. For the first time, we provide an analysis of its composition, and create a machine...

  18. Thought Action Fusion in Obsessive Compulsive Disorder

    Directory of Open Access Journals (Sweden)

    Þahin ÇÝFTÇÝ

    2013-12-01

    Full Text Available Thought Action Fusion (TAF is defined as tought and action percieved as equivalent to each other or as an exaggerated power given to idea. With the usage of “Thought Action Fusion Scale” which is created by Shafran (1996, is began to investigate its role in psychopathologies. Researches about the three-component structure which has TAF-Likelihood-Self, TAF-Likelihood-Others, TAF-Moral, are concentrated especially around the obsessive compulsive disorder (OCD. TAF alleged including a certain level also in the normal population, was seen in the relationship with the inflated responsability in OCD, thought suppression and neutralising, was tried to explain the direction of this relationship in the mediationel model framework. [JCBPR 2013; 2(3.000: 138-146

  19. Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

    Science.gov (United States)

    Parida, P. K.; Sanabada, M. K.; Tripathi, S.

    2014-11-01

    Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.

  20. Dataset definition for CMS operations and physics analyses

    Science.gov (United States)

    Franzoni, Giovanni; Compact Muon Solenoid Collaboration

    2016-04-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets and secondary datasets/dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concepts of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the LHC run I, and we discuss the plans for the run II.

  1. Dataset definition for CMS operations and physics analyses

    CERN Document Server

    AUTHOR|(CDS)2051291

    2016-01-01

    Data recorded at the CMS experiment are funnelled into streams, integrated in the HLT menu, and further organised in a hierarchical structure of primary datasets, secondary datasets, and dedicated skims. Datasets are defined according to the final-state particles reconstructed by the high level trigger, the data format and the use case (physics analysis, alignment and calibration, performance studies). During the first LHC run, new workflows have been added to this canonical scheme, to exploit at best the flexibility of the CMS trigger and data acquisition systems. The concept of data parking and data scouting have been introduced to extend the physics reach of CMS, offering the opportunity of defining physics triggers with extremely loose selections (e.g. dijet resonance trigger collecting data at a 1 kHz). In this presentation, we review the evolution of the dataset definition during the first run, and we discuss the plans for the second LHC run.

  2. Dataset of NRDA emission data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Emissions data from open air oil burns. This dataset is associated with the following publication: Gullett, B., J. Aurell, A. Holder, B. Mitchell, D. Greenwell, M....

  3. Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

    Science.gov (United States)

    Kohli, Marc D; Summers, Ronald M; Geis, J Raymond

    2017-08-01

    At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities.

  4. Discovery and Reuse of Open Datasets: An Exploratory Study

    Directory of Open Access Journals (Sweden)

    Sara

    2016-07-01

    Full Text Available Objective: This article analyzes twenty cited or downloaded datasets and the repositories that house them, in order to produce insights that can be used by academic libraries to encourage discovery and reuse of research data in institutional repositories. Methods: Using Thomson Reuters’ Data Citation Index and repository download statistics, we identified twenty cited/downloaded datasets. We documented the characteristics of the cited/downloaded datasets and their corresponding repositories in a self-designed rubric. The rubric includes six major categories: basic information; funding agency and journal information; linking and sharing; factors to encourage reuse; repository characteristics; and data description. Results: Our small-scale study suggests that cited/downloaded datasets generally comply with basic recommendations for facilitating reuse: data are documented well; formatted for use with a variety of software; and shared in established, open access repositories. Three significant factors also appear to contribute to dataset discovery: publishing in discipline-specific repositories; indexing in more than one location on the web; and using persistent identifiers. The cited/downloaded datasets in our analysis came from a few specific disciplines, and tended to be funded by agencies with data publication mandates. Conclusions: The results of this exploratory research provide insights that can inform academic librarians as they work to encourage discovery and reuse of institutional datasets. Our analysis also suggests areas in which academic librarians can target open data advocacy in their communities in order to begin to build open data success stories that will fuel future advocacy efforts.

  5. Trends in communications satellites

    CERN Document Server

    Curtin, Denis J

    1979-01-01

    Trends in Communications Satellites offers a comprehensive look at trends and advances in satellite communications, including experimental ones such as NASA satellites and those jointly developed by France and Germany. The economic aspects of communications satellites are also examined. This book consists of 16 chapters and begins with a discussion on the fundamentals of electrical communications and their application to space communications, including spacecraft, earth stations, and orbit and wavelength utilization. The next section demonstrates how successful commercial satellite communicati

  6. Visualization of conserved structures by fusing highly variable datasets.

    Science.gov (United States)

    Silverstein, Jonathan C; Chhadia, Ankur; Dech, Fred

    2002-01-01

    Skill, effort, and time are required to identify and visualize anatomic structures in three-dimensions from radiological data. Fundamentally, automating these processes requires a technique that uses symbolic information not in the dynamic range of the voxel data. We were developing such a technique based on mutual information for automatic multi-modality image fusion (MIAMI Fuse, University of Michigan). This system previously demonstrated facility at fusing one voxel dataset with integrated symbolic structure information to a CT dataset (different scale and resolution) from the same person. The next step of development of our technique was aimed at accommodating the variability of anatomy from patient to patient by using warping to fuse our standard dataset to arbitrary patient CT datasets. A standard symbolic information dataset was created from the full color Visible Human Female by segmenting the liver parenchyma, portal veins, and hepatic veins and overwriting each set of voxels with a fixed color. Two arbitrarily selected patient CT scans of the abdomen were used for reference datasets. We used the warping functions in MIAMI Fuse to align the standard structure data to each patient scan. The key to successful fusion was the focused use of multiple warping control points that place themselves around the structure of interest automatically. The user assigns only a few initial control points to align the scans. Fusion 1 and 2 transformed the atlas with 27 points around the liver to CT1 and CT2 respectively. Fusion 3 transformed the atlas with 45 control points around the liver to CT1 and Fusion 4 transformed the atlas with 5 control points around the portal vein. The CT dataset is augmented with the transformed standard structure dataset, such that the warped structure masks are visualized in combination with the original patient dataset. This combined volume visualization is then rendered interactively in stereo on the ImmersaDesk in an immersive Virtual

  7. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    International Nuclear Information System (INIS)

    Nikolov, Ned; Zeller, Karl

    2006-01-01

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale

  8. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    Energy Technology Data Exchange (ETDEWEB)

    Nikolov, Ned [Natural Resource Research Center, 2150 Centre Avenue, Building A, Room 368, Fort Collins, CO 80526 (United States)]. E-mail: nnikolov@fs.fed.us; Zeller, Karl [USDA FS Rocky Mountain Research Station, 240 W. Prospect Road, Fort Collins, CO 80526 (United States)]. E-mail: kzeller@fs.fed.us

    2006-06-15

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale.

  9. Use of satellite erythemal UV products in analysing the global UV changes

    Directory of Open Access Journals (Sweden)

    I. Ialongo

    2011-09-01

    Full Text Available Long term changes in solar UV radiation affect global bio-geochemistry and climate. The satellite-based dataset of TOMS (Total Ozone Monitoring System and OMI (Ozone Monitoring Instrument of erythemal UV product was applied for the first time to estimate the long-term ultraviolet (UV changes at the global scale. The analysis of the uncertainty related to the different input information is presented. OMI and GOME-2 (Global Ozone Monitoring Experiment-2 products were compared in order to analyse the differences in the global UV distribution and their effect on the linear trend estimation.

    The results showed that the differences in the inputs (mainly surface albedo and aerosol information used in the retrieval, affect significantly the UV change calculation, pointing out the importance of using a consistent dataset when calculating long term UV changes. The areas where these differences played a major role were identified using global maps of monthly UV changes. Despite the uncertainties, significant positive UV changes (ranging from 0 to about 5 %/decade were observed, with higher values in the Southern Hemisphere at mid-latitudes during spring-summer, where the largest ozone decrease was observed.

  10. An Annotated Dataset of 14 Cardiac MR Images

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2002-01-01

    This note describes a dataset consisting of 14 annotated cardiac MR images. Points of correspondence are placed on each image at the left ventricle (LV). As such, the dataset can be readily used for building statistical models of shape. Further, format specifications and terms of use are given....

  11. Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia

    Science.gov (United States)

    Melville, Bethany; Lucieer, Arko; Aryal, Jagannath

    2018-04-01

    This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be

  12. Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Bin Yong

    2015-01-01

    Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

  13. Mapping reference evapotranspiration from meteorological satellite data and applications

    Directory of Open Access Journals (Sweden)

    Ming-Hwi Yao

    2017-01-01

    Full Text Available Reference evapotranspiration (ETo is an agrometeorological variable widely used in hydrology and agriculture. The FAO-56 Penman-Monteith combination method (PM method is a standard for computing ETo for water management. However, this scheme is limited to areas where climatic data with good quality are available. Maps of 10-day averaged ETo at 5 km × 5 km grid spacing for the Taiwan region were produced by multiplying pan evaporation (Epan, derived from ground solar radiation (GSR retrieved from satellite images using the Heliosat-3 method, by a fixed pan coefficient (Kp. Validation results indicated that the overall mean absolute percentage error (MAPE and normalized root-mean-square deviation (NRMSD were 6.2 and 7.7%, respectively, when compared with ETo computed by the PM method using spatially interpolated 10-day averaged daily maximum and minimum temperature datasets and GSR derived from satellite inputs. Land coefficient (KL values based on the derived ETo estimates and long term latent heat flux measurements, were determined for the following landscapes: Paddy rice (Oryza sativa, subtropical cypress forest (Chamaecyparis obtusa var. formosana and Chamaecyparis formosensis, warm-to-temperate mixed rainforest (Cryptocarya chinensis, Engelhardtia roxburghiana, Tutcheria shinkoensis, and Helicia formosana, and grass marsh (Brachiaria mutica and Phragmites australis. The determined land coefficients are indispensable to scale ETo in estimating regional evapotranspiration.

  14. Theory of satellite geodesy applications of satellites to geodesy

    CERN Document Server

    Kaula, William M

    2000-01-01

    The main purpose of this classic text is to demonstrate how Newtonian gravitational theory and Euclidean geometry can be used and developed in the earth's environment. The second is to collect and explain some of the mathematical techniques developed for measuring the earth by satellite.Book chapters include discussions of the earth's gravitational field, with special emphasis on spherical harmonies and the potential of the ellipsoid; matrices and orbital geometry; elliptic motion, linear perturbations, resonance, and other aspects of satellite orbit dynamics; the geometry of satellite obser

  15. Dataset - Adviesregel PPL 2010

    NARCIS (Netherlands)

    Evert, van F.K.; Schans, van der D.A.; Geel, van W.C.A.; Slabbekoorn, J.J.; Booij, R.; Jukema, J.N.; Meurs, E.J.J.; Uenk, D.

    2011-01-01

    This dataset contains experimental data from a number of field experiments with potato in The Netherlands (Van Evert et al., 2011). The data are presented as an SQL dump of a PostgreSQL database (version 8.4.4). An outline of the entity-relationship diagram of the database is given in an

  16. Examining the Relationship between Food Thought Suppression and Binge Eating Disorder

    OpenAIRE

    Barnes, Rachel D.; Masheb, Robin M.; White, Marney A.; Grilo, Carlos M.

    2013-01-01

    Food thought suppression, or purposely attempting to avoid thoughts of food, is related to a number of unwanted eating- and weight-related consequences, particularly in dieting and obese individuals. Little is known about the possible significance of food thought suppression in clinical samples, particularly obese patients who binge eat. This study examined food thought suppression in 150 obese patients seeking treatment for binge eating disorder (BED). Food thought suppression was not associ...

  17. Tension in the recent Type Ia supernovae datasets

    International Nuclear Information System (INIS)

    Wei, Hao

    2010-01-01

    In the present work, we investigate the tension in the recent Type Ia supernovae (SNIa) datasets Constitution and Union. We show that they are in tension not only with the observations of the cosmic microwave background (CMB) anisotropy and the baryon acoustic oscillations (BAO), but also with other SNIa datasets such as Davis and SNLS. Then, we find the main sources responsible for the tension. Further, we make this more robust by employing the method of random truncation. Based on the results of this work, we suggest two truncated versions of the Union and Constitution datasets, namely the UnionT and ConstitutionT SNIa samples, whose behaviors are more regular.

  18. Viability of Controlling Prosthetic Hand Utilizing Electroencephalograph (EEG) Dataset Signal

    Science.gov (United States)

    Miskon, Azizi; A/L Thanakodi, Suresh; Raihan Mazlan, Mohd; Mohd Haziq Azhar, Satria; Nooraya Mohd Tawil, Siti

    2016-11-01

    This project presents the development of an artificial hand controlled by Electroencephalograph (EEG) signal datasets for the prosthetic application. The EEG signal datasets were used as to improvise the way to control the prosthetic hand compared to the Electromyograph (EMG). The EMG has disadvantages to a person, who has not used the muscle for a long time and also to person with degenerative issues due to age factor. Thus, the EEG datasets found to be an alternative for EMG. The datasets used in this work were taken from Brain Computer Interface (BCI) Project. The datasets were already classified for open, close and combined movement operations. It served the purpose as an input to control the prosthetic hand by using an Interface system between Microsoft Visual Studio and Arduino. The obtained results reveal the prosthetic hand to be more efficient and faster in response to the EEG datasets with an additional LiPo (Lithium Polymer) battery attached to the prosthetic. Some limitations were also identified in terms of the hand movements, weight of the prosthetic, and the suggestions to improve were concluded in this paper. Overall, the objective of this paper were achieved when the prosthetic hand found to be feasible in operation utilizing the EEG datasets.

  19. Technical note: An inorganic water chemistry dataset (1972–2011 ...

    African Journals Online (AJOL)

    A national dataset of inorganic chemical data of surface waters (rivers, lakes, and dams) in South Africa is presented and made freely available. The dataset comprises more than 500 000 complete water analyses from 1972 up to 2011, collected from more than 2 000 sample monitoring stations in South Africa. The dataset ...

  20. Adaptive topographic mass correction for satellite gravity and gravity gradient data

    Science.gov (United States)

    Holzrichter, Nils; Szwillus, Wolfgang; Götze, Hans-Jürgen

    2014-05-01

    Subsurface modelling with gravity data includes a reliable topographic mass correction. Since decades, this mandatory step is a standard procedure. However, originally methods were developed for local terrestrial surveys. Therefore, these methods often include defaults like a limited correction area of 167 km around an observation point, resampling topography depending on the distance to the station or disregard the curvature of the earth. New satellite gravity data (e.g. GOCE) can be used for large scale lithospheric modelling with gravity data. The investigation areas can include thousands of kilometres. In addition, measurements are located in the flight height of the satellite (e.g. ~250 km for GOCE). The standard definition of the correction area and the specific grid spacing around an observation point was not developed for stations located in these heights and areas of these dimensions. This asks for a revaluation of the defaults used for topographic correction. We developed an algorithm which resamples the topography based on an adaptive approach. Instead of resampling topography depending on the distance to the station, the grids will be resampled depending on its influence at the station. Therefore, the only value the user has to define is the desired accuracy of the topographic correction. It is not necessary to define the grid spacing and a limited correction area. Furthermore, the algorithm calculates the topographic mass response with a spherical shaped polyhedral body. We show examples for local and global gravity datasets and compare the results of the topographic mass correction to existing approaches. We provide suggestions how satellite gravity and gradient data should be corrected.

  1. Review: advances in in situ and satellite phenological observations in Japan

    Science.gov (United States)

    Nagai, Shin; Nasahara, Kenlo Nishida; Inoue, Tomoharu; Saitoh, Taku M.; Suzuki, Rikie

    2016-04-01

    To accurately evaluate the responses of spatial and temporal variation of ecosystem functioning (evapotranspiration and photosynthesis) and services (regulating and cultural services) to the rapid changes caused by global warming, we depend on long-term, continuous, near-surface, and satellite remote sensing of phenology over wide areas. Here, we review such phenological studies in Japan and discuss our current knowledge, problems, and future developments. In contrast with North America and Europe, Japan has been able to evaluate plant phenology along vertical and horizontal gradients within a narrow area because of the country's high topographic relief. Phenological observation networks that support scientific studies and outreach activities have used near-surface tools such as digital cameras and spectral radiometers. Differences in phenology among ecosystems and tree species have been detected by analyzing the seasonal variation of red, green, and blue digital numbers (RGB values) extracted from phenological images, as well as spectral reflectance and vegetation indices. The relationships between seasonal variations in RGB-derived indices or spectral characteristics and the ecological and CO2 flux measurement data have been well validated. In contrast, insufficient satellite remote-sensing observations have been conducted because of the coarse spatial resolution of previous datasets, which could not detect the heterogeneous plant phenology that results from Japan's complex topography and vegetation. To improve Japanese phenological observations, multidisciplinary analysis and evaluation will be needed to link traditional phenological observations with "index trees," near-surface and satellite remote-sensing observations, "citizen science" (observations by citizens), and results published on the Internet.

  2. Satellite Communications

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'

  3. Wind and wave dataset for Matara, Sri Lanka

    Science.gov (United States)

    Luo, Yao; Wang, Dongxiao; Priyadarshana Gamage, Tilak; Zhou, Fenghua; Madusanka Widanage, Charith; Liu, Taiwei

    2018-01-01

    We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1) is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017) is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447).

  4. Wind and wave dataset for Matara, Sri Lanka

    Directory of Open Access Journals (Sweden)

    Y. Luo

    2018-01-01

    Full Text Available We present a continuous in situ hydro-meteorology observational dataset from a set of instruments first deployed in December 2012 in the south of Sri Lanka, facing toward the north Indian Ocean. In these waters, simultaneous records of wind and wave data are sparse due to difficulties in deploying measurement instruments, although the area hosts one of the busiest shipping lanes in the world. This study describes the survey, deployment, and measurements of wind and waves, with the aim of offering future users of the dataset the most comprehensive and as much information as possible. This dataset advances our understanding of the nearshore hydrodynamic processes and wave climate, including sea waves and swells, in the north Indian Ocean. Moreover, it is a valuable resource for ocean model parameterization and validation. The archived dataset (Table 1 is examined in detail, including wave data at two locations with water depths of 20 and 10 m comprising synchronous time series of wind, ocean astronomical tide, air pressure, etc. In addition, we use these wave observations to evaluate the ERA-Interim reanalysis product. Based on Buoy 2 data, the swells are the main component of waves year-round, although monsoons can markedly alter the proportion between swell and wind sea. The dataset (Luo et al., 2017 is publicly available from Science Data Bank (https://doi.org/10.11922/sciencedb.447.

  5. Heuristics for Relevancy Ranking of Earth Dataset Search Results

    Science.gov (United States)

    Lynnes, Christopher; Quinn, Patrick; Norton, James

    2016-01-01

    As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

  6. QSAR ligand dataset for modelling mutagenicity, genotoxicity, and rodent carcinogenicity

    Directory of Open Access Journals (Sweden)

    Davy Guan

    2018-04-01

    Full Text Available Five datasets were constructed from ligand and bioassay result data from the literature. These datasets include bioassay results from the Ames mutagenicity assay, Greenscreen GADD-45a-GFP assay, Syrian Hamster Embryo (SHE assay, and 2 year rat carcinogenicity assay results. These datasets provide information about chemical mutagenicity, genotoxicity and carcinogenicity.

  7. COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

    Directory of Open Access Journals (Sweden)

    P. Agrafiotis

    2015-03-01

    Full Text Available This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO provided by NCMA S.A (Hellenic Cadastre from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  8. Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2014-03-01

    Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

  9. Road Network Extraction from VHR Satellite Images Using Context Aware Object Feature Integration and Tensor Voting

    Directory of Open Access Journals (Sweden)

    Mehdi Maboudi

    2016-08-01

    Full Text Available Road networks are very important features in geospatial databases. Even though high-resolution optical satellite images have already been acquired for more than a decade, tools for automated extraction of road networks from these images are still rare. One consequence of this is the need for manual interaction which, in turn, is time and cost intensive. In this paper, a multi-stage approach is proposed which integrates structural, spectral, textural, as well as contextual information of objects to extract road networks from very high resolution satellite images. Highlights of the approach are a novel linearity index employed for the discrimination of elongated road segments from other objects and customized tensor voting which is utilized to fill missing parts of the network. Experiments are carried out with different datasets. Comparison of the achieved results with the results of seven state-of-the-art methods demonstrated the efficiency of the proposed approach.

  10. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  11. Language as an instrument of thought

    Directory of Open Access Journals (Sweden)

    Eran Asoulin

    2016-11-01

    Full Text Available I show that there are good arguments and evidence to boot that support the language as an instrument of thought hypothesis. The underlying mechanisms of language, comprising of expressions structured hierarchically and recursively, provide a perspective (in the form of a conceptual structure on the world, for it is only via language that certain perspectives are available to us and to our thought processes. These mechanisms provide us with a uniquely human way of thinking and talking about the world that is different to the sort of thinking we share with other animals. If the primary function of language were communication then one would expect that the underlying mechanisms of language will be structured in a way that favours successful communication. I show that not only is this not the case, but that the underlying mechanisms of language are in fact structured in a way to maximise computational efficiency, even if it means causing communicative problems. Moreover, I discuss evidence from comparative, neuropathological, developmental, and neuroscientific evidence that supports the claim that language is an instrument of thought.

  12. The Dataset of Countries at Risk of Electoral Violence

    OpenAIRE

    Birch, Sarah; Muchlinski, David

    2017-01-01

    Electoral violence is increasingly affecting elections around the world, yet researchers have been limited by a paucity of granular data on this phenomenon. This paper introduces and describes a new dataset of electoral violence – the Dataset of Countries at Risk of Electoral Violence (CREV) – that provides measures of 10 different types of electoral violence across 642 elections held around the globe between 1995 and 2013. The paper provides a detailed account of how and why the dataset was ...

  13. Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

    Science.gov (United States)

    Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

    2010-06-30

    QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but

  14. Towards interoperable and reproducible QSAR analyses: Exchange of datasets

    Directory of Open Access Journals (Sweden)

    Spjuth Ola

    2010-06-01

    Full Text Available Abstract Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join

  15. VideoWeb Dataset for Multi-camera Activities and Non-verbal Communication

    Science.gov (United States)

    Denina, Giovanni; Bhanu, Bir; Nguyen, Hoang Thanh; Ding, Chong; Kamal, Ahmed; Ravishankar, Chinya; Roy-Chowdhury, Amit; Ivers, Allen; Varda, Brenda

    Human-activity recognition is one of the most challenging problems in computer vision. Researchers from around the world have tried to solve this problem and have come a long way in recognizing simple motions and atomic activities. As the computer vision community heads toward fully recognizing human activities, a challenging and labeled dataset is needed. To respond to that need, we collected a dataset of realistic scenarios in a multi-camera network environment (VideoWeb) involving multiple persons performing dozens of different repetitive and non-repetitive activities. This chapter describes the details of the dataset. We believe that this VideoWeb Activities dataset is unique and it is one of the most challenging datasets available today. The dataset is publicly available online at http://vwdata.ee.ucr.edu/ along with the data annotation.

  16. Toward computational cumulative biology by combining models of biological datasets.

    Science.gov (United States)

    Faisal, Ali; Peltonen, Jaakko; Georgii, Elisabeth; Rung, Johan; Kaski, Samuel

    2014-01-01

    A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative. We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field. The search is (i) data-driven to enable new findings, going beyond the state of the art of keyword searches in annotations, (ii) modeling-driven, to include both biological knowledge and insights learned from data, and (iii) scalable, as it is accomplished without building one unified grand model of all data. Assuming each dataset has been modeled beforehand, by the researchers or automatically by database managers, we apply a rapidly computable and optimizable combination model to decompose a new dataset into contributions from earlier relevant models. By using the data-driven decomposition, we identify a network of interrelated datasets from a large annotated human gene expression atlas. While tissue type and disease were major driving forces for determining relevant datasets, the found relationships were richer, and the model-based search was more accurate than the keyword search; moreover, it recovered biologically meaningful relationships that are not straightforwardly visible from annotations-for instance, between cells in different developmental stages such as thymocytes and T-cells. Data-driven links and citations matched to a large extent; the data-driven links even uncovered corrections to the publication data, as two of the most linked datasets were not highly cited and turned out to have wrong publication entries in the database.

  17. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; hide

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  18. Theory of geostationary satellites

    CERN Document Server

    Zee, Chong-Hung

    1989-01-01

    Geostationary or equatorial synchronous satellites are a daily reminder of our space efforts during the past two decades. The nightly television satellite weather picture, the intercontinental telecommunications of television transmissions and telephone conversations, and the establishrnent of educational programs in remote regions on Earth are constant reminders of the presence of these satellites. As used here, the term 'geo­ stationary' must be taken loosely because, in the long run, the satellites will not remain 'stationary' with respect to an Earth-fixed reference frame. This results from the fact that these satellites, as is true for all satellites, are incessantly subject to perturbations other than the central-body attraction of the Earth. Among the more predominant pertur­ bations are: the ellipticity of the Earth's equator, the Sun and Moon, and solar radiation pressure. Higher harmonics of the Earth's potential and tidal effects also influence satellite motion, but they are of second­ order whe...

  19. Horton Revisited: African Traditional Thought and Western Science ...

    African Journals Online (AJOL)

    Over the years Robin Horton has argued for what he refers to as the 'continuity thesis' according to which there are theoretical similarities between African traditional thought and modern Western science. Horton's thesis stands in contrast to the standard Western anthropological appraisal of traditional African thought.

  20. The appraisal of intrusive thoughts in relation to obsessional-compulsive symptoms.

    Science.gov (United States)

    Barrera, Terri L; Norton, Peter J

    2011-01-01

    Research has shown that although intrusive thoughts occur universally, the majority of individuals do not view intrusive thoughts as being problematic (Freeston, Ladouceur, Thibodeau, & Gagnon, 1991; Rachman & de Silva, 1978; Salkovskis & Harrison, 1984). Thus, it is not the presence of intrusive thoughts that leads to obsessional problems but rather some other factor that plays a role in the development of abnormal obsessions. According to the cognitive model of obsessive-compulsive disorder (OCD) put forth by Salkovskis (1985), the crucial factor that differentiates between individuals with OCD and those without is the individual's appraisal of the naturally occurring intrusive thoughts. This study aimed to test Salkovskis's model by examining the role of cognitive biases (responsibility, thought-action fusion, and thought control) as well as distress in the relationship between intrusive thoughts and obsessive-compulsive symptoms in an undergraduate sample of 326 students. An existing measure of intrusive thoughts (the Revised Obsessional Intrusions Inventory) was modified for this study to include a scale of distress associated with each intrusive thought in addition to the current frequency scale. When the Yale-Brown Obsessive-Compulsive Scale was used as the measure of OCD symptoms, a significant interaction effect of frequency and distress of intrusive thoughts resulted. Additionally, a significant three-way interaction of Frequency × Distress × Responsibility was found when the Obsessive Compulsive Inventory-Revised was used as the measure of OCD symptoms. These results indicate that the appraisal of intrusive thoughts is important in predicting OCD symptoms, thus providing support for Salkovskis's model of OCD.

  1. Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

    Science.gov (United States)

    Smith, Eric A.

    2004-01-01

    This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying

  2. Teaching thoughtful practice: narrative pedagogy in addictions education.

    Science.gov (United States)

    Vandermause, Roxanne K; Townsend, Ryan P

    2010-07-01

    Preparing practitioners for this rapidly changing and demanding health care environment is challenging. A surge in knowledge development and scientific advancement has placed a priority on technical skill and a focus on content driven educational processes that prepare students for evidence-based practice. However, the most difficult health care scenarios require thinking-in-action and thoughtfulness as well as didactic knowledge. It is our contention that interpretive educational methods, like narrative pedagogy, will promote judgment-based practice that includes use of evidence and delivery of thoughtful care. In this article, we describe and interpret a narrative approach to addictions content and teaching thoughtful practice. We present our pedagogical process, including observations and field notes, to show how interpretive pedagogies can be introduced into nursing curricula. By presenting this process, the reader is invited to consider interpretive methods as a way to inspire and habituate thoughtful practice and judgment-based care. Copyright 2009 Elsevier Ltd. All rights reserved.

  3. Space Solar Power Satellite Systems, Modern Small Satellites, and Space Rectenna

    Science.gov (United States)

    Bergsrud, Corey Alexis Marvin

    Space solar power satellite (SSPS) systems is the concept of placing large satellite into geostationary Earth orbit (GEO) to harvest and convert massive amounts of solar energy into microwave energy, and to transmit the microwaves to a rectifying antenna (rectenna) array on Earth. The rectenna array captures and converts the microwave power into usable power that is injected into the terrestrial electric grid for use. This work approached the microwave power beam as an additional source of power (with solar) for lower orbiting satellites. Assuming the concept of retrodirectivity, a GEO-SSPS antenna array system tracks and delivers microwave power to lower orbiting satellites. The lower orbiting satellites are equipped with a stacked photovoltaic (PV)/rectenna array hybrid power generation unit (HPGU) in order to harvest solar and/or microwave energy for on-board use during orbit. The area, and mass of the PV array part of the HPGU was reduced at about 32% beginning-of-life power in order to achieve the spacecraft power requirements. The HPGU proved to offer a mass decrease in the PGU, and an increase in mission life due to longer living component life of the rectenna array. Moreover, greater mission flexibility is achieved through a track and power delivery concept. To validate the potential advantages offered by a HPGU, a mission concept was presented that utilizes modern small satellites as technology demonstrators. During launch, a smaller power receiving "daughter" satellite sits inside a larger power transmitting "mother" satellite. Once separated from the launch vehicle the daughter satellite is ejected away from the mother satellite, and each satellite deploys its respective power transmitting or power receiving hardware's for experimentation. The concept of close proximity mission operations between the satellites is considered. To validate the technology of the space rectenna array part of the HPGU, six milestones were completed in the design. The first

  4. Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

    Science.gov (United States)

    Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

    2016-12-01

    Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general

  5. 3DSEM: A 3D microscopy dataset

    Directory of Open Access Journals (Sweden)

    Ahmad P. Tafti

    2016-03-01

    Full Text Available The Scanning Electron Microscope (SEM as a 2D imaging instrument has been widely used in many scientific disciplines including biological, mechanical, and materials sciences to determine the surface attributes of microscopic objects. However the SEM micrographs still remain 2D images. To effectively measure and visualize the surface properties, we need to truly restore the 3D shape model from 2D SEM images. Having 3D surfaces would provide anatomic shape of micro-samples which allows for quantitative measurements and informative visualization of the specimens being investigated. The 3DSEM is a dataset for 3D microscopy vision which is freely available at [1] for any academic, educational, and research purposes. The dataset includes both 2D images and 3D reconstructed surfaces of several real microscopic samples. Keywords: 3D microscopy dataset, 3D microscopy vision, 3D SEM surface reconstruction, Scanning Electron Microscope (SEM

  6. Active Semisupervised Clustering Algorithm with Label Propagation for Imbalanced and Multidensity Datasets

    Directory of Open Access Journals (Sweden)

    Mingwei Leng

    2013-01-01

    Full Text Available The accuracy of most of the existing semisupervised clustering algorithms based on small size of labeled dataset is low when dealing with multidensity and imbalanced datasets, and labeling data is quite expensive and time consuming in many real-world applications. This paper focuses on active data selection and semisupervised clustering algorithm in multidensity and imbalanced datasets and proposes an active semisupervised clustering algorithm. The proposed algorithm uses an active mechanism for data selection to minimize the amount of labeled data, and it utilizes multithreshold to expand labeled datasets on multidensity and imbalanced datasets. Three standard datasets and one synthetic dataset are used to demonstrate the proposed algorithm, and the experimental results show that the proposed semisupervised clustering algorithm has a higher accuracy and a more stable performance in comparison to other clustering and semisupervised clustering algorithms, especially when the datasets are multidensity and imbalanced.

  7. A dataset of forest biomass structure for Eurasia.

    Science.gov (United States)

    Schepaschenko, Dmitry; Shvidenko, Anatoly; Usoltsev, Vladimir; Lakyda, Petro; Luo, Yunjian; Vasylyshyn, Roman; Lakyda, Ivan; Myklush, Yuriy; See, Linda; McCallum, Ian; Fritz, Steffen; Kraxner, Florian; Obersteiner, Michael

    2017-05-16

    The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above- and below ground); green forest floor (above- and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930-2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.

  8. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  9. Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

    2014-01-01

    SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

  10. Interim Service ISDN Satellite (ISIS) network model for advanced satellite designs and experiments

    Science.gov (United States)

    Pepin, Gerard R.; Hager, E. Paul

    1991-01-01

    The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Network Model for Advanced Satellite Designs and Experiments describes a model suitable for discrete event simulations. A top-down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ISDN modeling abstractions are added to permit the determination and performance for the NASA Satellite Communications Research (SCAR) Program.

  11. Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014.

    Science.gov (United States)

    Yanto; Livneh, Ben; Rajagopalan, Balaji

    2017-05-23

    We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.

  12. An approach for real-time fast point positioning of the BeiDou Navigation Satellite System using augmentation information

    Science.gov (United States)

    Tu, Rui; Zhang, Rui; Zhang, Pengfei; Liu, Jinhai; Lu, Xiaochun

    2018-07-01

    This study proposes an approach to facilitate real-time fast point positioning of the BeiDou Navigation Satellite System (BDS) based on regional augmentation information. We term this as the precise positioning based on augmentation information (BPP) approach. The coordinates of the reference stations were highly constrained to extract the augmentation information, which contained not only the satellite orbit clock error correlated with the satellite running state, but also included the atmosphere error and unmodeled error, which are correlated with the spatial and temporal states. Based on these mixed augmentation corrections, a precise point positioning (PPP) model could be used for the coordinates estimation of the user stations, and the float ambiguity could be easily fixed for the single-difference between satellites. Thus, this technique provided a quick and high-precision positioning service. Three different datasets with small, medium, and large baselines (0.6 km, 30 km and 136 km) were used to validate the feasibility and effectiveness of the proposed BPP method. The validations showed that using the BPP model, 1–2 cm positioning service can be provided in a 100 km wide area after just 2 s of initialization. Thus, as the proposed approach not only capitalized on both PPP and RTK but also provided consistent application, it can be used for area augmentation positioning.

  13. The New world of ';Big Data' Analytics and High Performance Data: A Paradigm shift in the way we interact with very large Earth Observation datasets (Invited)

    Science.gov (United States)

    Purss, M. B.; Lewis, A.; Ip, A.; Evans, B.

    2013-12-01

    The next decade promises an exponential increase in volumes of open data from Earth observing satellites. The ESA Sentinels, the Japan Meteorological Agency's Himawari 8/9 geostationary satellites, various NASA missions, and of course the many EO satellites planned from China, will produce petabyte scale datasets of national and global significance. It is vital that we develop new ways of managing, accessing and using this ';big-data' from satellites, to produce value added information within realistic timeframes. A paradigm shift is required away from traditional ';scene based' (and labour intensive) approaches with data storage and delivery for processing at local sites, to emerging High Performance Data (HPD) models where the data are organised and co-located with High Performance Computational (HPC) infrastructures in a way that enables users to bring themselves, their algorithms and the HPC processing power to the data. Automated workflows, that allow the entire archive of data to be rapidly reprocessed from raw data to fully calibrated products, are a crucial requirement for the effective stewardship of these datasets. New concepts such as arranging and viewing data as ';data objects' which underpin the delivery of ';information as a service' are also integral to realising the transition into HPD analytics. As Australia's national remote sensing and geoscience agency, Geoscience Australia faces a pressing need to solve the problems of ';big-data', in particular around the 25-year archive of calibrated Landsat data. The challenge is to ensure standardised information can be extracted from the entire archive and applied to nationally significant problems in hazards, water management, land management, resource development and the environment. Ultimately, these uses justify government investment in these unique systems. A key challenge was how best to organise the archive of calibrated Landsat data (estimated to grow to almost 1 PB by the end of 2014) in a way

  14. The SSABLE system - Automated archive, catalog, browse and distribution of satellite data in near-real time

    Science.gov (United States)

    Simpson, James J.; Harkins, Daniel N.

    1993-01-01

    Historically, locating and browsing satellite data has been a cumbersome and expensive process. This has impeded the efficient and effective use of satellite data in the geosciences. SSABLE is a new interactive tool for the archive, browse, order, and distribution of satellite date based upon X Window, high bandwidth networks, and digital image rendering techniques. SSABLE provides for automatically constructing relational database queries to archived image datasets based on time, data, geographical location, and other selection criteria. SSABLE also provides a visual representation of the selected archived data for viewing on the user's X terminal. SSABLE is a near real-time system; for example, data are added to SSABLE's database within 10 min after capture. SSABLE is network and machine independent; it will run identically on any machine which satisfies the following three requirements: 1) has a bitmapped display (monochrome or greater); 2) is running the X Window system; and 3) is on a network directly reachable by the SSABLE system. SSABLE has been evaluated at over 100 international sites. Network response time in the United States and Canada varies between 4 and 7 s for browse image updates; reported transmission times to Europe and Australia typically are 20-25 s.

  15. Elemental Food for Thought

    Science.gov (United States)

    Cady, Susan

    2005-01-01

    One of the first tasks students learn in chemistry is to pronounce and spell the names of elements and learn their corresponding chemical symbols. Repetitive oral recitation is commonly used to learn this information, but games and puzzles can make this task creative, variable, and fun. Elemental Food for Thought is a puzzlelike activity that…

  16. Arctic Sea Level During the Satellite Altimetry Era

    DEFF Research Database (Denmark)

    Carret, A.; Johannessen, J. A.; Andersen, Ole Baltazar

    2017-01-01

    Results of the sea-level budget in the high latitudes (up to 80°N) and the Arctic Ocean during the satellite altimetry era. We investigate the closure of the sea-level budget since 2002 using two altimetry sea-level datasets based on the Envisat waveform retracking: temperature and salinity data....... However, in terms of regional average over the region ranging from 66°N to 80°N, the steric component contributes little to the observed sea-level trend, suggesting a dominant mass contribution in the Arctic region. This is confirmed by GRACE-based ocean mass time series that agree well with the altimetry......-based sea-level time series. Direct estimate of the mass component is not possible prior to GRACE. Thus, we estimated the mass contribution from the difference between the altimetry-based sea level and the steric component. We also investigate the coastal sea level with tide gauge records. Twenty coupled...

  17. The Content of Emotional Thoughts | Bloser | Philosophical Papers

    African Journals Online (AJOL)

    In this paper I examine Peter Goldie's theory of emotional thoughts and feelings, offered in his recent book The Emotions and subsequent articles. Goldie argues that emotional thoughts cannot be assimilated to belief or judgment, together with some added-on phenomenological component, and on this point I agree with ...

  18. A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

    Science.gov (United States)

    Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

    2014-12-01

    The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

  19. Comparative Evaluation of Five Fire Emissions Datasets Using the GEOS-5 Model

    Science.gov (United States)

    Ichoku, C. M.; Pan, X.; Chin, M.; Bian, H.; Darmenov, A.; Ellison, L.; Kucsera, T. L.; da Silva, A. M., Jr.; Petrenko, M. M.; Wang, J.; Ge, C.; Wiedinmyer, C.

    2017-12-01

    Wildfires and other types of biomass burning affect most vegetated parts of the globe, contributing 40% of the annual global atmospheric loading of carbonaceous aerosols, as well as significant amounts of numerous trace gases, such as carbon dioxide, carbon monoxide, and methane. Many of these smoke constituents affect the air quality and/or the climate system directly or through their interactions with solar radiation and cloud properties. However, fire emissions are poorly constrained in global and regional models, resulting in high levels of uncertainty in understanding their real impacts. With the advent of satellite remote sensing of fires and burned areas in the last couple of decades, a number of fire emissions products have become available for use in relevant research and applications. In this study, we evaluated five global biomass burning emissions datasets, namely: (1) GFEDv3.1 (Global Fire Emissions Database version 3.1); (2) GFEDv4s (Global Fire Emissions Database version 4 with small fires); (3) FEERv1 (Fire Energetics and Emissions Research version 1.0); (4) QFEDv2.4 (Quick Fire Emissions Dataset version 2.4); and (5) Fire INventory from NCAR (FINN) version 1.5. Overall, the spatial patterns of biomass burning emissions from these inventories are similar, although the magnitudes of the emissions can be noticeably different. The inventories derived using top-down approaches (QFEDv2.4 and FEERv1) are larger than those based on bottom-up approaches. For example, global organic carbon (OC) emissions in 2008 are: QFEDv2.4 (51.93 Tg), FEERv1 (28.48 Tg), FINN v1.5 (19.48 Tg), GFEDv3.1 (15.65 Tg) and GFEDv4s (13.76 Tg); representing a factor of 3.7 difference between the largest and the least. We also used all five biomass-burning emissions datasets to conduct aerosol simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5), and compared the resulting aerosol optical depth (AOD) output to the corresponding retrievals from MODIS

  20. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  1. Inferences of all-sky solar irradiance using Terra and Aqua MODIS satellite data

    DEFF Research Database (Denmark)

    Houborg, Rasmus Møller; Søgaard, Henrik; Emmerich, W.

    2007-01-01

    -sky solar irradiance components, which links a physically based clear-sky model with a neural network version of a rigorous radiative transfer model. The scheme exploits the improved cloud characterization and retrieval capabilities of the MODerate resolution Imaging Spectroradiometer (MODIS) onboard...... contrasting climates and cloud environments. Information on the atmospheric state was provided by MODIS data products and verifications against AErosol RObotic NETwork (AERONET) data demonstrated usefulness of MODIS aerosol optical depth and total precipitable water vapour retrievals for the delineation...... and become unusable above approximately 60° latitude. However, in principle, the scheme can be applied anywhere on the globe, and a synergistic use of MODIS and geostationary satellite datasets may be envisaged for some applications....

  2. Intercomparison and evaluation of satellite peroxyacetyl nitrate observations in the upper troposphere–lower stratosphere

    Directory of Open Access Journals (Sweden)

    R. J. Pope

    2016-11-01

    Full Text Available Peroxyacetyl nitrate (PAN is an important chemical species in the troposphere as it aids the long-range transport of NOx and subsequent formation of O3 in relatively clean remote regions. Over the past few decades observations from aircraft campaigns and surface sites have been used to better understand the regional distribution of PAN. However, recent measurements made by satellites allow for a global assessment of PAN in the upper troposphere–lower stratosphere (UTLS. In this study, we investigate global PAN distributions from two independent retrieval methodologies, based on measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS instrument, on board Envisat from the Institute of Meteorology and Climate Research (IMK, Karlsruhe Institute of Technology, and the Department of Physics and Astronomy, University of Leicester (UoL. Retrieving PAN from MIPAS is challenging due to the weak signal in the measurements and contamination from other species. Therefore, we compare the two MIPAS datasets with observations from the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS, in situ aircraft data and the 3-D chemical transport model TOMCAT. MIPAS shows peak UTLS PAN concentrations over the biomass burning regions (e.g. ranging from 150 to  >  200 pptv at 150 hPa and during the summertime Asian monsoon as enhanced convection aids the vertical transport of PAN from the lower atmosphere. At 150 hPa, we find significant differences between the two MIPAS datasets in the tropics, where IMK PAN concentrations are larger by 50–100 pptv. Comparisons between MIPAS and ACE-FTS show better agreement with the UoL MIPAS PAN concentrations at 200 hPa, but with mixed results above this altitude. TOMCAT generally captures the magnitude and structure of climatological aircraft PAN profiles within the observational variability allowing it to be used to investigate the MIPAS PAN differences

  3. The American Satellite Company (ASC) satellite deployed from payload bay

    Science.gov (United States)

    1985-01-01

    The American Satellite Company (ASC) communications satellite is deployed from the payload bay of the Shuttle Discovery. A portion of the cloudy surface of the earth can be seen to the left of the frame.

  4. SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

    Science.gov (United States)

    Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

    2015-12-01

    Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These

  5. Cognitive Defusion versus Thought Distraction: A Clinical Rationale, Training, and Experiential Exercise in Altering Psychological Impacts of Negative Self-Referential Thoughts

    Science.gov (United States)

    Masuda, Akihiko; Feinstein, Amanda B.; Wendell, Johanna W.; Sheehan, Shawn T.

    2010-01-01

    Using two modes of intervention delivery, the present study compared the effects of a cognitive defusion strategy with a thought distraction strategy on the emotional discomfort and believability of negative self-referential thoughts. One mode of intervention delivery consisted of a clinical rationale and training (i.e., Partial condition). The…

  6. Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

    Science.gov (United States)

    Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

    2015-04-01

    Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order

  7. An Analysis on Better Testing than Training Performances on the Iris Dataset

    NARCIS (Netherlands)

    Schutten, Marten; Wiering, Marco

    2016-01-01

    The Iris dataset is a well known dataset containing information on three different types of Iris flowers. A typical and popular method for solving classification problems on datasets such as the Iris set is the support vector machine (SVM). In order to do so the dataset is separated in a set used

  8. 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.

  9. Thought Action Fusion in Obsessive Compulsive Disorder

    OpenAIRE

    Þahin ÇÝFTÇÝ; Tacettin KURU

    2013-01-01

    Thought Action Fusion (TAF) is defined as tought and action percieved as equivalent to each other or as an exaggerated power given to idea. With the usage of “Thought Action Fusion Scale” which is created by Shafran (1996), is began to investigate its role in psychopathologies. Researches about the three-component structure which has TAF-Likelihood-Self, TAF-Likelihood-Others, TAF-Moral, are concentrated especially around the obsessive compulsive disorder (OCD). TAF alleged includi...

  10. Evaluation, Calibration and Comparison of the Precipitation-Runoff Modeling System (PRMS) National Hydrologic Model (NHM) Using Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) Gridded Datasets

    Science.gov (United States)

    Norton, P. A., II; Haj, A. E., Jr.

    2014-12-01

    The United States Geological Survey is currently developing a National Hydrologic Model (NHM) to support and facilitate coordinated and consistent hydrologic modeling efforts at the scale of the continental United States. As part of this effort, the Geospatial Fabric (GF) for the NHM was created. The GF is a database that contains parameters derived from datasets that characterize the physical features of watersheds. The GF was used to aggregate catchments and flowlines defined in the National Hydrography Dataset Plus dataset for more than 100,000 hydrologic response units (HRUs), and to establish initial parameter values for input to the Precipitation-Runoff Modeling System (PRMS). Many parameter values are adjusted in PRMS using an automated calibration process. Using these adjusted parameter values, the PRMS model estimated variables such as evapotranspiration (ET), potential evapotranspiration (PET), snow-covered area (SCA), and snow water equivalent (SWE). In order to evaluate the effectiveness of parameter calibration, and model performance in general, several satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) gridded datasets including ET, PET, SCA, and SWE were compared to PRMS-simulated values. The MODIS and SNODAS data were spatially averaged for each HRU, and compared to PRMS-simulated ET, PET, SCA, and SWE values for each HRU in the Upper Missouri River watershed. Default initial GF parameter values and PRMS calibration ranges were evaluated. Evaluation results, and the use of MODIS and SNODAS datasets to update GF parameter values and PRMS calibration ranges, are presented and discussed.

  11. Examining the Relationship between Food Thought Suppression and Binge Eating Disorder

    Science.gov (United States)

    Barnes, Rachel D.; Masheb, Robin M.; White, Marney A.; Grilo, Carlos M.

    2013-01-01

    Food thought suppression, or purposely attempting to avoid thoughts of food, is related to a number of unwanted eating- and weight-related consequences, particularly in dieting and obese individuals. Little is known about the possible significance of food thought suppression in clinical samples, particularly obese patients who binge eat. This study examined food thought suppression in 150 obese patients seeking treatment for binge eating disorder (BED). Food thought suppression was not associated with binge eating frequency or body mass index but was significantly associated with higher current levels of eating disorder psychopathology and variables pertaining to obesity, dieting, and binge eating. PMID:23751246

  12. Provenance of Earth Science Datasets - How Deep Should One Go?

    Science.gov (United States)

    Ramapriyan, H.; Manipon, G. J. M.; Aulenbach, S.; Duggan, B.; Goldstein, J.; Hua, H.; Tan, D.; Tilmes, C.; Wilson, B. D.; Wolfe, R.; Zednik, S.

    2015-12-01

    For credibility of scientific research, transparency and reproducibility are essential. This fundamental tenet has been emphasized for centuries, and has been receiving increased attention in recent years. The Office of Management and Budget (2002) addressed reproducibility and other aspects of quality and utility of information from federal agencies. Specific guidelines from NASA (2002) are derived from the above. According to these guidelines, "NASA requires a higher standard of quality for information that is considered influential. Influential scientific, financial, or statistical information is defined as NASA information that, when disseminated, will have or does have clear and substantial impact on important public policies or important private sector decisions." For information to be compliant, "the information must be transparent and reproducible to the greatest possible extent." We present how the principles of transparency and reproducibility have been applied to NASA data supporting the Third National Climate Assessment (NCA3). The depth of trace needed of provenance of data used to derive conclusions in NCA3 depends on how the data were used (e.g., qualitatively or quantitatively). Given that the information is diligently maintained in the agency archives, it is possible to trace from a figure in the publication through the datasets, specific files, algorithm versions, instruments used for data collection, and satellites, as well as the individuals and organizations involved in each step. Such trace back permits transparency and reproducibility.

  13. Interactive visualization and analysis of multimodal datasets for surgical applications.

    Science.gov (United States)

    Kirmizibayrak, Can; Yim, Yeny; Wakid, Mike; Hahn, James

    2012-12-01

    Surgeons use information from multiple sources when making surgical decisions. These include volumetric datasets (such as CT, PET, MRI, and their variants), 2D datasets (such as endoscopic videos), and vector-valued datasets (such as computer simulations). Presenting all the information to the user in an effective manner is a challenging problem. In this paper, we present a visualization approach that displays the information from various sources in a single coherent view. The system allows the user to explore and manipulate volumetric datasets, display analysis of dataset values in local regions, combine 2D and 3D imaging modalities and display results of vector-based computer simulations. Several interaction methods are discussed: in addition to traditional interfaces including mouse and trackers, gesture-based natural interaction methods are shown to control these visualizations with real-time performance. An example of a medical application (medialization laryngoplasty) is presented to demonstrate how the combination of different modalities can be used in a surgical setting with our approach.

  14. The effects of familiarity on thought--action fusion.

    Science.gov (United States)

    Berman, Noah C; Wheaton, Michael G; Fabricant, Laura E; Jacobson, Spenser R; Abramowitz, Jonathan S

    2011-10-01

    The present study examined whether beliefs about the importance of thoughts (i.e., thought--action fusion; TAF) are related to the target subject of the negative thought. One hundred and seven undergraduate students were randomly assigned to imagine either a beloved relative or a stranger being diagnosed with cancer and provided in vivo ratings of anxiety, likelihood, moral wrongness, urge to neutralize, and how upsetting the event would be if it occurred. Results indicated that thinking of a relative being diagnosed with cancer provoked more distress, urges to neutralize, and higher estimates of likelihood, as well greater use of mental neutralizing behaviors, compared to thinking of a stranger. Contrary to our prediction, the groups did not differ in their ratings of the moral wrongness. These findings broadly support the assertion that the more personally significant a negative intrusive thought, the more it will provoke distress and urges to neutralize. Results are discussed in terms of the cognitive model of obsessions and clinical implications are addressed. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. Trends in mobile satellite communication

    Science.gov (United States)

    Johannsen, Klaus G.; Bowles, Mike W.; Milliken, Samuel; Cherrette, Alan R.; Busche, Gregory C.

    1993-01-01

    Ever since the U.S. Federal Communication Commission opened the discussion on spectrum usage for personal handheld communication, the community of satellite manufacturers has been searching for an economically viable and technically feasible satellite mobile communication system. Hughes Aircraft Company and others have joined in providing proposals for such systems, ranging from low to medium to geosynchronous orbits. These proposals make it clear that the trend in mobile satellite communication is toward more sophisticated satellites with a large number of spot beams and onboard processing, providing worldwide interconnectivity. Recent Hughes studies indicate that from a cost standpoint the geosynchronous satellite (GEOS) is most economical, followed by the medium earth orbit satellite (MEOS) and then by the low earth orbit satellite (LEOS). From a system performance standpoint, this evaluation may be in reverse order, depending on how the public will react to speech delay and collision. This paper discusses the trends and various mobile satellite constellations in satellite communication under investigation. It considers the effect of orbital altitude and modulation/multiple access on the link and spacecraft design.

  16. Something From Nothing (There): Collecting Global IPv6 Datasets from DNS

    NARCIS (Netherlands)

    Fiebig, T.; Borgolte, Kevin; Hao, Shuang; Kruegel, Christopher; Vigna, Giovanny; Spring, Neil; Riley, George F.

    2017-01-01

    Current large-scale IPv6 studies mostly rely on non-public datasets, asmost public datasets are domain specific. For instance, traceroute-based datasetsare biased toward network equipment. In this paper, we present a new methodologyto collect IPv6 address datasets that does not require access to

  17. Automatic processing of multimodal tomography datasets.

    Science.gov (United States)

    Parsons, Aaron D; Price, Stephen W T; Wadeson, Nicola; Basham, Mark; Beale, Andrew M; Ashton, Alun W; Mosselmans, J Frederick W; Quinn, Paul D

    2017-01-01

    With the development of fourth-generation high-brightness synchrotrons on the horizon, the already large volume of data that will be collected on imaging and mapping beamlines is set to increase by orders of magnitude. As such, an easy and accessible way of dealing with such large datasets as quickly as possible is required in order to be able to address the core scientific problems during the experimental data collection. Savu is an accessible and flexible big data processing framework that is able to deal with both the variety and the volume of data of multimodal and multidimensional scientific datasets output such as those from chemical tomography experiments on the I18 microfocus scanning beamline at Diamond Light Source.

  18. JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

    Science.gov (United States)

    Folmer, Michael J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J.; Nelson, J.; Goldberg, M.; Sjoberg, W.

    2016-01-01

    The ocean prediction center at the national hurricane center's tropical analysis and forecast Branch, the Weather Prediction center and the Satellite analysis branch of NESDIS make up the Satellite Proving Ground for Marine, Precipitation and Satellite Analysis. These centers had early exposure to JPSS products using the S-NPP Satellite that was launched in 2011. Forecasters continue to evaluate new products in anticipation for the launch of JPSS-1 sometime in 2017.

  19. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

  20. The satellite situation center

    International Nuclear Information System (INIS)

    Teague, M.J.; Sawyer, D.M.; Vette, J.I.

    1982-01-01

    Considerations related to the early planning for the International Magnetospheric Study (IMS) took into account the desirability of an establishment of specific entities for generating and disseminating coordination information for both retrospective and predictive periods. The organizations established include the IMS/Satellite Situation Center (IMS/SSC) operated by NASA. The activities of the SSC are related to the preparation of reports on predicted and actually achieved satellite positions, the response to inquiries, the compilation of information on satellite experiments, and the issue of periodic status summaries. Attention is given to high-altitude satellite services, other correlative satellite services, non-IMS activities of the SSC, a summary of the SSC request activity, and post-IMS and future activities

  1. Plan of Time Management of Satellite Positioning System using Quasi-zenith Satellite

    Science.gov (United States)

    Takahashi, Yasuhiro; Fujieda, Miho; Amagai, Jun; Yokota, Shoichiro; Kimura, Kazuhiro; Ito, Hiroyuki; Hama, Shin'ichi; Morikawa, Takao; Kawano, Isao; Kogure, Satoshi

    The Quasi-Zenith satellites System (QZSS) is developed as an integrated satellite service system of communication, broadcasting and positioning for mobile users in specified regions of Japan from high elevation angle. Purposes of the satellite positioning system using Quasi-Zenith satellite (QZS) are to complement and augment the GPS. The national institutes concerned have been developing the positioning system using QZS since 2003 and will carry out experiments and researches in three years after the launch. In this system, National Institute of Information and Communications Technology (NICT) is mainly in charge of timing system for the satellite positioning system using QZS, such as onboard hydrogen maser atomic clock and precise time management system of the QZSS. We started to develop the engineering model of the time management system for the QZSS. The time management system for the QZSS will be used to compare time differences between QZS and earth station as well as to compare between three onboard atomic clocks. This paper introduces time management of satellite positioning system using the QZSS.

  2. GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in Healthcare.

    Science.gov (United States)

    Ali, Rahman; Siddiqi, Muhammad Hameed; Idris, Muhammad; Ali, Taqdir; Hussain, Shujaat; Huh, Eui-Nam; Kang, Byeong Ho; Lee, Sungyoung

    2015-07-02

    A wide array of biomedical data are generated and made available to healthcare experts. However, due to the diverse nature of data, it is difficult to predict outcomes from it. It is therefore necessary to combine these diverse data sources into a single unified dataset. This paper proposes a global unified data model (GUDM) to provide a global unified data structure for all data sources and generate a unified dataset by a "data modeler" tool. The proposed tool implements user-centric priority based approach which can easily resolve the problems of unified data modeling and overlapping attributes across multiple datasets. The tool is illustrated using sample diabetes mellitus data. The diverse data sources to generate the unified dataset for diabetes mellitus include clinical trial information, a social media interaction dataset and physical activity data collected using different sensors. To realize the significance of the unified dataset, we adopted a well-known rough set theory based rules creation process to create rules from the unified dataset. The evaluation of the tool on six different sets of locally created diverse datasets shows that the tool, on average, reduces 94.1% time efforts of the experts and knowledge engineer while creating unified datasets.

  3. Individual variation in the propensity for prospective thought is associated with functional integration between visual and retrosplenial cortex.

    Science.gov (United States)

    Villena-Gonzalez, Mario; Wang, Hao-Ting; Sormaz, Mladen; Mollo, Giovanna; Margulies, Daniel S; Jefferies, Elizabeth A; Smallwood, Jonathan

    2018-02-01

    It is well recognized that the default mode network (DMN) is involved in states of imagination, although the cognitive processes that this association reflects are not well understood. The DMN includes many regions that function as cortical "hubs", including the posterior cingulate/retrosplenial cortex, anterior temporal lobe and the hippocampus. This suggests that the role of the DMN in cognition may reflect a process of cortical integration. In the current study we tested whether functional connectivity from uni-modal regions of cortex into the DMN is linked to features of imaginative thought. We found that strong intrinsic communication between visual and retrosplenial cortex was correlated with the degree of social thoughts about the future. Using an independent dataset, we show that the same region of retrosplenial cortex is functionally coupled to regions of primary visual cortex as well as core regions that make up the DMN. Finally, we compared the functional connectivity of the retrosplenial cortex, with a region of medial prefrontal cortex implicated in the integration of information from regions of the temporal lobe associated with future thought in a prior study. This analysis shows that the retrosplenial cortex is preferentially coupled to medial occipital, temporal lobe regions and the angular gyrus, areas linked to episodic memory, scene construction and navigation. In contrast, the medial prefrontal cortex shows preferential connectivity with motor cortex and lateral temporal and prefrontal regions implicated in language, motor processes and working memory. Together these findings suggest that integrating neural information from visual cortex into retrosplenial cortex may be important for imagining the future and may do so by creating a mental scene in which prospective simulations play out. We speculate that the role of the DMN in imagination may emerge from its capacity to bind together distributed representations from across the cortex in a

  4. God's Thoughts: Practical Steps Toward a Theory of Everything

    Science.gov (United States)

    Lincoln, Don

    2017-04-01

    In 1922, Einstein was speaking to young Esther Salaman during a long walk; she was talking of her dreams and goals and he was sharing some of his thoughts. Among thoughts of travel, he described his core guiding intellectual principle when he said, "I want to know how God created this world [wie sich Gott die Welt beschaffen]. I'm not interested in this or that phenomenon, in the spectrum of this or that element. I want to know His thoughts; the rest are just details."

  5. Informing future NRT satellite distribution capabilities: Lessons learned from NASA's Land Atmosphere NRT capability for EOS (LANCE)

    Science.gov (United States)

    Davies, D.; Murphy, K. J.; Michael, K.

    2013-12-01

    NASA's Land Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) provides data and imagery from Terra, Aqua and Aura satellites in less than 3 hours from satellite observation, to meet the needs of the near real-time (NRT) applications community. This article describes the architecture of the LANCE and outlines the modifications made to achieve the 3-hour latency requirement with a view to informing future NRT satellite distribution capabilities. It also describes how latency is determined. LANCE is a distributed system that builds on the existing EOS Data and Information System (EOSDIS) capabilities. To achieve the NRT latency requirement, many components of the EOS satellite operations, ground and science processing systems have been made more efficient without compromising the quality of science data processing. The EOS Data and Operations System (EDOS) processes the NRT stream with higher priority than the science data stream in order to minimize latency. In addition to expediting transfer times, the key difference between the NRT Level 0 products and those for standard science processing is the data used to determine the precise location and tilt of the satellite. Standard products use definitive geo-location (attitude and ephemeris) data provided daily, whereas NRT products use predicted geo-location provided by the instrument Global Positioning System (GPS) or approximation of navigational data (depending on platform). Level 0 data are processed in to higher-level products at designated Science Investigator-led Processing Systems (SIPS). The processes used by LANCE have been streamlined and adapted to work with datasets as soon as they are downlinked from satellites or transmitted from ground stations. Level 2 products that require ancillary data have modified production rules to relax the requirements for ancillary data so reducing processing times. Looking to the future, experience gained from LANCE can provide valuable lessons on

  6. Weighing Photons Using Bathroom Scales: A Thought Experiment

    Science.gov (United States)

    Huggins, Elisha

    2010-01-01

    Jay Orear, in his introductory physics text, defined the weight of a person as the reading one gets when standing on a (properly calibrated) bathroom scale. Here we will use Jay's definition of weight in a thought experiment to measure the weight of a photon. The thought experiment uses the results of the Pound-Rebka-Snider experiments, Compton…

  7. Thoughts on environmental actinide research-future and present situation

    International Nuclear Information System (INIS)

    Yamamoto, Masayoshi

    2002-01-01

    Thoughts on environmental actinides, especially transuranium elements, are presented with emphasis on present situation and future researches. It is since 1945 that man has been in direct relationship to the significant quantities of such transuranium elements, although Pu was discovered in 1942 to exist in very small quantities in nature. Substantial amounts of these elements (Np, Pu, Am) have been distributed in the environment mainly as the result of nuclear weapon testing, followed by accident of satellite and release of radioactive substances from nuclear facilities. Chernobyl nuclear power plant accident might serve as a most recent example of such release. Considerable efforts have been devoted to the investigation of the processes involved in the transfer of radionuclides in the environment and how these can be influenced. And, many data (levels and distribution) and knowledge to understand these processes have been obtained and accumulated. The final purpose in all the research was the protection of the human being. The present trends for environmental radioactivity research (or radioecology) involves a further development of models, speciation of radionuclides, tracer studies and countermeasures of other species than man in radiological protection. Joint researches between radioecologists and specialists such as meteorology, oceanography, geology, botany, statistics and so on are more and more needed to make one of the most fascinating environmental sciences. Finally, an effort should be made to develop radioecology into a more hypothesis-oriented science, as mentioned by Platt. (author)

  8. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    Science.gov (United States)

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  9. A Research Graph dataset for connecting research data repositories using RD-Switchboard.

    Science.gov (United States)

    Aryani, Amir; Poblet, Marta; Unsworth, Kathryn; Wang, Jingbo; Evans, Ben; Devaraju, Anusuriya; Hausstein, Brigitte; Klas, Claus-Peter; Zapilko, Benjamin; Kaplun, Samuele

    2018-05-29

    This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures. The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants. The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation. Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

  10. Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

    Directory of Open Access Journals (Sweden)

    Julien Morel

    2014-07-01

    Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

  11. Process mining in oncology using the MIMIC-III dataset

    Science.gov (United States)

    Prima Kurniati, Angelina; Hall, Geoff; Hogg, David; Johnson, Owen

    2018-03-01

    Process mining is a data analytics approach to discover and analyse process models based on the real activities captured in information systems. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncology with a regular complaint being the limited availability and accessibility of datasets with suitable information for process mining. Publicly available datasets are one option and this paper describes the potential to use MIMIC-III, for process mining in oncology. MIMIC-III is a large open access dataset of de-identified patient records. There are 134 publications listed as using the MIMIC dataset, but none of them have used process mining. The MIMIC-III dataset has 16 event tables which are potentially useful for process mining and this paper demonstrates the opportunities to use MIMIC-III for process mining in oncology. Our research applied the L* lifecycle method to provide a worked example showing how process mining can be used to analyse cancer pathways. The results and data quality limitations are discussed along with opportunities for further work and reflection on the value of MIMIC-III for reproducible process mining research.

  12. Thoughts on categorising bloodstain patterns

    CSIR Research Space (South Africa)

    Cooper, Antony K

    2003-10-01

    Full Text Available A thought piece submitted to the European Network of Forensic Science Institutes (ENFSI), as part of their consideration of forming an European Bloodstain Pattern Analysis Group, and submitted by one of their experts to the Taxonomy and Terminology...

  13. 3D satellite puzzles for young and old kids

    Science.gov (United States)

    Biondi, Riccardo; Galoforo, Germana

    2017-04-01

    The Italian Space Agency (ASI) is active in outreach willing to increase the interest of young generations and general public toward the space activities. ASI proposes educational programmes for supporting and encouraging the development of European society based on knowledge, inspiring and motivating the young generations. One of the initiatives promoted by ASI on this regards is the 3D satellite puzzles. The idea was born in 2007 from the will to conceive an educational product for promoting and explaining to students the small all-Italian mission AGILE (Astrorivelatore Gamma ad Immagini ultra Leggero) thought as a tool for students aged 8-13. Working with this slot of students is very productive in terms of the imprints left on the kids, in fact it is useful to produce things they can use, touch and play with, with an active approach instead of a passive one. Therefore it was decided to produce something that kids could build and use at home with their parents or friends, or all together at school with teachers and mates. Other puzzles followed AGILE, one about the COSMO-SkyMED satellites about Earth Observation and also a broader one of the International Space Station. During these 10 years the puzzles were mostly used as outreach tools for school children, but they surprisingly received a great success also within older generations. So far the 3D puzzles have been printed in more than 10 thousand copies and distributed for free to students of hundreds of schools in Italy, and to the general public through science associations, planetaria and museums. Recently they have been used also during special events such as the international Geoscience Communication School (as best practice outreach tool), the EXPO 2015 and the European Researcheŕs Night at the Parlamentarium in Brussels 2016. While the students are building the puzzles, the tutor explains them the different components that they are assembling, what the importance of the satellite is and how it works

  14. The equilibrium of rubble-pile satellites: The Darwin and Roche ellipsoids for gravitationally held granular aggregates

    Science.gov (United States)

    Sharma, Ishan

    2009-04-01

    Many new small moons of the giant planets have been discovered recently. In parallel, satellites of several asteroids, e.g., Ida, have been found. Strikingly, a majority of these new-found planetary moons are estimated to have very low densities, which, along with their hypothesized accretionary origins, suggests a rubble internal structure. This, coupled to the fact that many asteroids are also thought to be particle aggregates held together principally by self-gravity, motivates the present investigation into the possible ellipsoidal shapes that a rubble-pile satellite may achieve as it orbits an aspherical primary. Conversely, knowledge of the shape will constrain the granular aggregate's orbit—the closer it gets to a primary, both primary's tidal effect and the satellite's spin are greater. We will assume that the primary body is sufficiently massive so as not to be influenced by the satellite. However, we will incorporate the primary's possible ellipsoidal shape, e.g., flattening at its poles in the case of a planet, and the proloidal shape of asteroids. In this, the present investigation is an extension of the first classical Darwin problem to granular aggregates. General equations defining an ellipsoidal rubble pile's equilibrium about an ellipsoidal primary are developed. They are then utilized to scrutinize the possible granular nature of small inner moons of the giant planets. It is found that most satellites satisfy constraints necessary to exist as equilibrated granular aggregates. Objects like Naiad, Metis and Adrastea appear to violate these limits, but in doing so, provide clues to their internal density and/or structure. We also recover the Roche limit for a granular satellite of a spherical primary, and employ it to study the martian satellites, Phobos and Deimos, as well as to make contact with earlier work of Davidsson [Davidsson, B., 2001. Icarus 149, 375-383]. The satellite's interior will be modeled as a rigid-plastic, cohesion-less material

  15. Veterans Affairs Suicide Prevention Synthetic Dataset

    Data.gov (United States)

    Department of Veterans Affairs — The VA's Veteran Health Administration, in support of the Open Data Initiative, is providing the Veterans Affairs Suicide Prevention Synthetic Dataset (VASPSD). The...

  16. Examining the relationship between food thought suppression and binge eating disorder.

    Science.gov (United States)

    Barnes, Rachel D; Masheb, Robin M; White, Marney A; Grilo, Carlos M

    2013-10-01

    Food thought suppression, or purposely attempting to avoid thoughts of food, is related to a number of unwanted eating- and weight-related consequences, particularly in dieting and obese individuals. Little is known about the possible significance of food thought suppression in clinical samples, particularly obese patients who binge eat. This study examined food thought suppression in 150 obese patients seeking treatment for binge eating disorder (BED). Food thought suppression was not associated with binge eating frequency or body mass index but was significantly associated with higher current levels of eating disorder psychopathology and variables pertaining to obesity, dieting, and binge eating. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. SAR image classification based on CNN in real and simulation datasets

    Science.gov (United States)

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  18. On sample size and different interpretations of snow stability datasets

    Science.gov (United States)

    Schirmer, M.; Mitterer, C.; Schweizer, J.

    2009-04-01

    Interpretations of snow stability variations need an assessment of the stability itself, independent of the scale investigated in the study. Studies on stability variations at a regional scale have often chosen stability tests such as the Rutschblock test or combinations of various tests in order to detect differences in aspect and elevation. The question arose: ‘how capable are such stability interpretations in drawing conclusions'. There are at least three possible errors sources: (i) the variance of the stability test itself; (ii) the stability variance at an underlying slope scale, and (iii) that the stability interpretation might not be directly related to the probability of skier triggering. Various stability interpretations have been proposed in the past that provide partly different results. We compared a subjective one based on expert knowledge with a more objective one based on a measure derived from comparing skier-triggered slopes vs. slopes that have been skied but not triggered. In this study, the uncertainties are discussed and their effects on regional scale stability variations will be quantified in a pragmatic way. An existing dataset with very large sample sizes was revisited. This dataset contained the variance of stability at a regional scale for several situations. The stability in this dataset was determined using the subjective interpretation scheme based on expert knowledge. The question to be answered was how many measurements were needed to obtain similar results (mainly stability differences in aspect or elevation) as with the complete dataset. The optimal sample size was obtained in several ways: (i) assuming a nominal data scale the sample size was determined with a given test, significance level and power, and by calculating the mean and standard deviation of the complete dataset. With this method it can also be determined if the complete dataset consists of an appropriate sample size. (ii) Smaller subsets were created with similar

  19. Really big data: Processing and analysis of large datasets

    Science.gov (United States)

    Modern animal breeding datasets are large and getting larger, due in part to the recent availability of DNA data for many animals. Computational methods for efficiently storing and analyzing those data are under development. The amount of storage space required for such datasets is increasing rapidl...

  20. A robust dataset-agnostic heart disease classifier from Phonocardiogram.

    Science.gov (United States)

    Banerjee, Rohan; Dutta Choudhury, Anirban; Deshpande, Parijat; Bhattacharya, Sakyajit; Pal, Arpan; Mandana, K M

    2017-07-01

    Automatic classification of normal and abnormal heart sounds is a popular area of research. However, building a robust algorithm unaffected by signal quality and patient demography is a challenge. In this paper we have analysed a wide list of Phonocardiogram (PCG) features in time and frequency domain along with morphological and statistical features to construct a robust and discriminative feature set for dataset-agnostic classification of normal and cardiac patients. The large and open access database, made available in Physionet 2016 challenge was used for feature selection, internal validation and creation of training models. A second dataset of 41 PCG segments, collected using our in-house smart phone based digital stethoscope from an Indian hospital was used for performance evaluation. Our proposed methodology yielded sensitivity and specificity scores of 0.76 and 0.75 respectively on the test dataset in classifying cardiovascular diseases. The methodology also outperformed three popular prior art approaches, when applied on the same dataset.