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Sample records for elevation models remote

  1. Validating firn compaction model with remote sensing data

    DEFF Research Database (Denmark)

    Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland shows a clear layering. The observed layers from the radar data can be used as an in-situ validation...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...

  2. Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

    Science.gov (United States)

    Byrd, Kristin B.; Windham-Myers, Lisamarie; Leeuw, Thomas; Downing, Bryan D.; Morris, James T.; Ferner, Matthew C.

    2016-01-01

    Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors

  3. Optimization of the resolution of remotely sensed digital elevation model to facilitate the simulation and spatial propagation of flood events in flat areas

    Science.gov (United States)

    Karapetsas, Nikolaos; Skoulikaris, Charalampos; Katsogiannos, Fotis; Zalidis, George; Alexandridis, Thomas

    2013-04-01

    The use of satellite remote sensing products, such as Digital Elevation Models (DEMs), under specific computational interfaces of Geographic Information Systems (GIS) has fostered and facilitated the acquisition of data on specific hydrologic features, such as slope, flow direction and flow accumulation, which are crucial inputs to hydrology or hydraulic models at the river basin scale. However, even though DEMs of different resolution varying from a few km up to 20m are freely available for the European continent, these remotely sensed elevation data are rather coarse in cases where large flat areas are dominant inside a watershed, resulting in an unsatisfactory representation of the terrain characteristics. This scientific work aims at implementing a combing interpolation technique for the amelioration of the analysis of a DEM in order to be used as the input ground model to a hydraulic model for the assessment of potential flood events propagation in plains. More specifically, the second version of the ASTER Global Digital Elevation Model (GDEM2), which has an overall accuracy of around 20 meters, was interpolated with a vast number of aerial control points available from the Hellenic Mapping and Cadastral Organization (HMCO). The uncertainty that was inherent in both the available datasets (ASTER & HMCO) and the appearance of uncorrelated errors and artifacts was minimized by incorporating geostatistical filtering. The resolution of the produced DEM was approximately 10 meters and its validation was conducted with the use of an external dataset of 220 geodetic survey points. The derived DEM was then used as an input to the hydraulic model InfoWorks RS, whose operation is based on the relief characteristics contained in the ground model, for defining, in an automated way, the cross section parameters and simulating the flood spatial distribution. The plain of Serres, which is located in the downstream part of the Struma/Strymon transboundary river basin shared

  4. A technique of the structural-tectonic elevations prediction using Earth remote sensing data

    Science.gov (United States)

    Tishaev, I. V.; Zatserkovnyi, V. I.; Yagorlytska, K. P.

    2016-12-01

    We consider an approach of using methods of Earth remote sensing data (RSD) classification for solving tasks of exploration geology and geophysics. Information obtained from the remote sensing data gives a possibility to clarify the structure of investigated areas and to determine neotectonic elevations, which act as certain indicators of promising areas with hydra-carbons contents. Reasonability of using such methods of RSD classification is based on connection between deep structure of surface resources (structural-tectonic setting) with current landscape, character of hydrologic network, geo-morphological, geo-botanical and other features. The advantage of Bayes classificator is not only in determination of object belonging to certain class, but also in calculation of probability of such belonging. For the formulated task this lets to forecast a presence of structural-tectonic elevations, which are potentially promising areas for hydra-carbons contents, using a formali! zed quantitative criterion. contents.

  5. Near-field Oblique Remote Sensing of Stream Water-surface Elevation, Slope, and Surface Velocity

    Science.gov (United States)

    Minear, J. T.; Kinzel, P. J.; Nelson, J. M.; McDonald, R.; Wright, S. A.

    2014-12-01

    A major challenge for estimating discharges during flood events or in steep channels is the difficulty and hazard inherent in obtaining in-stream measurements. One possible solution is to use near-field remote sensing to obtain simultaneous water-surface elevations, slope, and surface velocities. In this test case, we utilized Terrestrial Laser Scanning (TLS) to remotely measure water-surface elevations and slope in combination with surface velocities estimated from particle image velocimetry (PIV) obtained by video-camera and/or infrared camera. We tested this method at several sites in New Mexico and Colorado using independent validation data consisting of in-channel measurements from survey-grade GPS and Acoustic Doppler Current Profiler (ADCP) instruments. Preliminary results indicate that for relatively turbid or steep streams, TLS collects tens of thousands of water-surface elevations and slopes in minutes, much faster than conventional means and at relatively high precision, at least as good as continuous survey-grade GPS measurements. Estimated surface velocities from this technique are within 15% of measured velocity magnitudes and within 10 degrees from the measured velocity direction (using extrapolation from the shallowest bin of the ADCP measurements). Accurately aligning the PIV results into Cartesian coordinates appears to be one of the main sources of error, primarily due to the sensitivity at these shallow oblique look angles and the low numbers of stationary objects for rectification. Combining remotely-sensed water-surface elevations, slope, and surface velocities produces simultaneous velocity measurements from a large number of locations in the channel and is more spatially extensive than traditional velocity measurements. These factors make this technique useful for improving estimates of flow measurements during flood flows and in steep channels while also decreasing the difficulty and hazard associated with making measurements in these

  6. Informing a hydrological model of the Ogooué with multi-mission remote sensing data

    DEFF Research Database (Denmark)

    Kittel, Cecile Marie Margaretha; Nielsen, Karina; Tøttrup, C.

    2018-01-01

    with publicly available and free remote sensing observations. We used a rainfall–runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from......Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa...... model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin...

  7. Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

    Science.gov (United States)

    Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

    2009-01-01

    The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

  8. Antarctic 1 km Digital Elevation Model (DEM) from Combined ERS-1 Radar and ICESat Laser Satellite Altimetry

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a 1 km resolution Digital Elevation Model (DEM) of Antarctica. The DEM combines measurements from the European Remote Sensing Satellite-1...

  9. Elevation change and remote-sensing mass-balance methods on the Greenland ice sheet

    DEFF Research Database (Denmark)

    Ahlstrøm, Andreas P.; Reeh, Niels; Christensen, Erik Lintz

    The mass balance of the Greenland Ice Sheet is virtually impossible to obtain with traditional ground-based methods alone due to its vast size. It is thus desirable to develop mass-balance methods depending on remote sensing instead and this field has experienced a dramatic development within...... of measured surface elevation change over a 50x50~km part of the western Greenland Ice-Sheet margin near Kangerlussuaq. In this region, the mean observed elevation change has been -0.5~m from 2000 to 2003. However, the change is unevenly distributed with the northern and central part generally in balance...... the last decade. Large amounts of data have been collected from satellite and airborne platforms, yielding surface elevation changes and surface velocity fields. Here we present data from the Greenland Ice-Sheet margin acquired with a new small-scale airborne system, designed for regional high...

  10. Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

    Science.gov (United States)

    Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

    2018-03-01

    Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

  11. Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

    Science.gov (United States)

    Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

    2003-01-01

    We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

  12. Efficient extraction of drainage networks from massive, radar-based elevation models with least cost path search

    Directory of Open Access Journals (Sweden)

    M. Metz

    2011-02-01

    Full Text Available The availability of both global and regional elevation datasets acquired by modern remote sensing technologies provides an opportunity to significantly improve the accuracy of stream mapping, especially in remote, hard to reach regions. Stream extraction from digital elevation models (DEMs is based on computation of flow accumulation, a summary parameter that poses performance and accuracy challenges when applied to large, noisy DEMs generated by remote sensing technologies. Robust handling of DEM depressions is essential for reliable extraction of connected drainage networks from this type of data. The least-cost flow routing method implemented in GRASS GIS as the module r.watershed was redesigned to significantly improve its speed, functionality, and memory requirements and make it an efficient tool for stream mapping and watershed analysis from large DEMs. To evaluate its handling of large depressions, typical for remote sensing derived DEMs, three different methods were compared: traditional sink filling, impact reduction approach, and least-cost path search. The comparison was performed using the Shuttle Radar Topographic Mission (SRTM and Interferometric Synthetic Aperture Radar for Elevation (IFSARE datasets covering central Panama at 90 m and 10 m resolutions, respectively. The accuracy assessment was based on ground control points acquired by GPS and reference points digitized from Landsat imagery along segments of selected Panamanian rivers. The results demonstrate that the new implementation of the least-cost path method is significantly faster than the original version, can cope with massive datasets, and provides the most accurate results in terms of stream locations validated against reference points.

  13. Prognostic Significance of Remote Myocardium Alterations Assessed by Quantitative Noncontrast T1 Mapping in ST-Segment Elevation Myocardial Infarction.

    Science.gov (United States)

    Reinstadler, Sebastian J; Stiermaier, Thomas; Liebetrau, Johanna; Fuernau, Georg; Eitel, Charlotte; de Waha, Suzanne; Desch, Steffen; Reil, Jan-Christian; Pöss, Janine; Metzler, Bernhard; Lücke, Christian; Gutberlet, Matthias; Schuler, Gerhard; Thiele, Holger; Eitel, Ingo

    2018-03-01

    This study assessed the prognostic significance of remote zone native T1 alterations for the prediction of clinical events in a population with ST-segment elevation myocardial infarction (STEMI) who were treated by primary percutaneous coronary intervention (PPCI) and compared it with conventional markers of infarct severity. The exact role and incremental prognostic relevance of remote myocardium native T1 mapping alterations assessed by cardiac magnetic resonance (CMR) after STEMI remains unclear. We included 255 consecutive patients with STEMI who were reperfused within 12 h after symptom onset. CMR core laboratory analysis was performed to assess left ventricular (LV) function, standard infarct characteristics, and native T1 values of the remote, noninfarcted myocardium. The primary endpoint was a composite of death, reinfarction, and new congestive heart failure within 6 months (major adverse cardiac events [MACE]). Patients with increased remote zone native T1 values (>1,129 ms) had significantly larger infarcts (p = 0.012), less myocardial salvage (p = 0.002), and more pronounced LV dysfunction (p = 0.011). In multivariable analysis, remote zone native T1 was independently associated with MACE after adjusting for clinical risk factors (p = 0.001) or other CMR variables (p = 0.007). In C-statistics, native T1 of remote myocardium provided incremental prognostic information beyond clinical risk factors, LV ejection fraction, and other markers of infarct severity (all p remote zone native T1 to a model of prognostic CMR parameters (ejection fraction, infarct size, and myocardial salvage index) led to net reclassification improvement of 0.82 (95% confidence interval: 0.46 to 1.17; p remote zone alterations by quantitative noncontrast T1 mapping provided independent and incremental prognostic information in addition to clinical risk factors and traditional CMR outcome markers. Remote zone alterations may thus represent a novel therapeutic target and a

  14. Integrated Application of Remote Sensing, GIS and Hydrological Modeling to Estimate the Potential Impact Area of Earthquake-Induced Dammed Lakes

    Directory of Open Access Journals (Sweden)

    Bo Cao

    2017-10-01

    Full Text Available Dammed lakes are an important secondary hazard caused by earthquakes. They can induce further damage to nearby humans. Current hydrology calculation research on dammed lakes usually lacks spatial expressive ability and cannot accurately conduct impact assessment without the support of remote sensing, which obtains important characteristic information of dammed lakes. The current study aims to address the issues of the potential impact area estimate of earthquake-induced dammed lakes by combining remote sensing (RS, a geographic information system (GIS, and hydrological modeling. The Tangjiashan dammed lake induced by the Wenchuan earthquake was selected as the case for study. The elevation-versus-reservoir capacity curve was first calculated using the seed-growing algorithm based on digital elevation model (DEM data. The simulated annealing algorithm was applied to train the hydrological modeling parameters according to the historical hydrologic data. Then, the downstream water elevation variational process under different collapse capacity conditions was performed based on the obtained parameters. Finally, the downstream potential impact area was estimated by the highest water elevation values at different hydrologic sections. Results show that a flood with a collapse elevation of at least 680 m will impact the entire downstream region of Beichuan town. We conclude that spatial information technology combined with hydrological modeling can accurately predict and demonstrate the potential impact area with limited data resources. This paper provides a better guide for future immediate responses to dammed lake hazard mitigation.

  15. Modeling river discharge and sediment transport in the Wax Lake-Atchafalaya basin with remote sensing parametrization.

    Science.gov (United States)

    Simard, M.; Liu, K.; Denbina, M. W.; Jensen, D.; Rodriguez, E.; Liao, T. H.; Christensen, A.; Jones, C. E.; Twilley, R.; Lamb, M. P.; Thomas, N. A.

    2017-12-01

    Our goal is to estimate the fluxes of water and sediments throughout the Wax Lake-Atchafalaya basin. This was achieved by parametrization of a set of 1D (HEC-RAS) and 2D (DELFT3D) hydrology models with state of the art remote sensing measurements of water surface elevation, water surface slope and total suspended sediment (TSS) concentrations. The model implementations are spatially explicit, simulating river currents, lateral flows to distributaries and marshes, and spatial variations of sediment concentrations. Three remote sensing instruments were flown simultaneously to collect data over the Wax Lake-Atchafalaya basin, and along with in situ field data. A Riegl Lidar was used to measure water surface elevation and slope, while the UAVSAR L-band radar collected data in repeat-pass interferometric mode to measure water level change within adjacent marshes and islands. These data were collected several times as the tide rose and fell. AVRIS-NG instruments measured water surface reflectance spectra, used to estimate TSS. Bathymetry was obtained from sonar transects and water level changes were recorded by 19 water level pressure transducers. We used several Acoustic Doppler Current Profiler (ADCP) transects to estimate river discharge. The remotely sensed measurements of water surface slope were small ( 1cm/km) and varied slightly along the channel, especially at the confluence with bayous and the intra-coastal waterway. The slope also underwent significant changes during the tidal cycle. Lateral fluxes to island marshes were mainly observed by UAVSAR close to the distributaries. The extensive remote sensing measurements showed significant disparity with the hydrology model outputs. Observed variations in water surface slopes were unmatched by the model and tidal wave propagation was much faster than gauge measurements. The slope variations were compensated for in the models by tuning local lateral fluxes, bathymetry and riverbed friction. Overall, the simpler 1D

  16. Remote Sensing Data in Wind Velocity Field Modelling: a Case Study from the Sudetes (SW Poland)

    Science.gov (United States)

    Jancewicz, Kacper

    2014-06-01

    The phenomena of wind-field deformation above complex (mountainous) terrain is a popular subject of research related to numerical modelling using GIS techniques. This type of modelling requires, as input data, information on terrain roughness and a digital terrain/elevation model. This information may be provided by remote sensing data. Consequently, its accuracy and spatial resolution may affect the results of modelling. This paper represents an attempt to conduct wind-field modelling in the area of the Śnieżnik Massif (Eastern Sudetes). The modelling process was conducted in WindStation 2.0.10 software (using the computable fluid dynamics solver Canyon). Two different elevation models were used: the Global Land Survey Digital Elevation Model (GLS DEM) and Digital Terrain Elevation Data (DTED) Level 2. The terrain roughness raster was generated on the basis of Corine Land Cover 2006 (CLC 2006) data. The output data were post-processed in ArcInfo 9.3.1 software to achieve a high-quality cartographic presentation. Experimental modelling was conducted for situations from 26 November 2011, 25 May 2012, and 26 May 2012, based on a limited number of field measurements and using parameters of the atmosphere boundary layer derived from the aerological surveys provided by the closest meteorological stations. The model was run in a 100-m and 250-m spatial resolution. In order to verify the model's performance, leave-one-out cross-validation was used. The calculated indices allowed for a comparison with results of former studies pertaining to WindStation's performance. The experiment demonstrated very subtle differences between results in using DTED or GLS DEM elevation data. Additionally, CLC 2006 roughness data provided more noticeable improvements in the model's performance, but only in the resolution corresponding to the original roughness data. The best input data configuration resulted in the following mean values of error measure: root mean squared error of velocity

  17. Integrating remote sensing and terrain data in forest fire modeling

    Science.gov (United States)

    Medler, Michael Johns

    Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy

  18. Dynamic multibody modeling for tethered space elevators

    Science.gov (United States)

    Williams, Paul

    2009-08-01

    This paper presents a fundamental modeling strategy for dealing with powered and propelled bodies moving along space tethers. The tether is divided into a large number of discrete masses, which are connected by viscoelastic springs. The tether is subject to the full range of forces expected in Earth orbit in a relatively simple manner. Two different models of the elevator dynamics are presented. In order to capture the effect of the elevator moving along the tether, the elevator dynamics are included as a separate body in both models. One model treats the elevator's motion dynamically, where propulsive and friction forces are applied to the elevator body. The second model treats the elevator's motion kinematically, where the distance along the tether is determined by adjusting the lengths of tether on either side of the elevator. The tether model is used to determine optimal configurations for the space elevator. A modal analysis of two different configurations is presented which show that the fundamental mode of oscillation is a pendular one around the anchor point with a period on the order of 160 h for the in-plane motion, and 24 h for the out-of-plane motion. Numerical simulation results of the effects of the elevator moving along the cable are presented for different travel velocities and different elevator masses.

  19. Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

    Science.gov (United States)

    Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

    2017-12-01

    Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

  20. Early identification and preventive care for elevated cardiovascular disease risk within a remote Australian Aboriginal primary health care service

    Directory of Open Access Journals (Sweden)

    O'Dea Kerin

    2011-01-01

    Full Text Available Abstract Background Cardiovascular disease (CVD is the single greatest contributor to the gap in life expectancy between Indigenous and non-Indigenous Australians. Our objective is to determine if holistic CVD risk assessment, introduced as part of the new Aboriginal and Torres Strait Islander Adult Health Check (AHC, results in better identification of elevated CVD risk, improved delivery of preventive care for CVD and improvements in the CVD risk profile for Aboriginal adults in a remote community. Methods Interrupted time series study over six years in a remote primary health care (PHC service involving Aboriginal adults identified with elevated CVD risk (N = 64. Several process and outcome measures were audited at 6 monthly intervals for three years prior to the AHC (the intervention and three years following: (i the proportion of guideline scheduled CVD preventive care services delivered, (ii mean CVD medications prescribed and dispensed, (iii mean PHC consultations, (iv changes in participants' CVD risk factors and estimated absolute CVD risk and (v mean number of CVD events and iatrogenic events. Results Twenty-five percent of AHC participants were identified as having elevated CVD risk. Of these, 84% had not been previously identified during routine care. Following the intervention, there were significant improvements in the recorded delivery of preventive care services for CVD (30% to 53%, and prescription of CVD related medications (28% to 89% (P P = 0.004 following the intervention. However, there were no significant changes in the mean number of PHC consultations or mean number of CVD events or iatrogenic events. Conclusions Holistic CVD risk assessment during an AHC can lead to better and earlier identification of elevated CVD risk, improvement in the recorded delivery of preventive care services for CVD, intensification of treatment for CVD, and improvements in participants' CVD risk profile. Further research is required on

  1. Mapping radioactivity in groundwater to identify elevated exposure in remote and rural communities

    Energy Technology Data Exchange (ETDEWEB)

    Kleinschmidt, Ross, E-mail: ross_kleinschmidt@health.qld.gov.a [Queensland University of Technology, Faculty of Science and Technology, Discipline of Physics, 2 George Street, Brisbane, Queensland 4000 (Australia); Health Physics Unit, Queensland Health Forensic and Scientific Services, 39 Kessels Road, Coopers Plains, Queensland 4108 (Australia); Black, Jeffrey [Health Physics Unit, Queensland Health Forensic and Scientific Services, 39 Kessels Road, Coopers Plains, Queensland 4108 (Australia); Akber, Riaz [Queensland University of Technology, Faculty of Science and Technology, Discipline of Physics, 2 George Street, Brisbane, Queensland 4000 (Australia)

    2011-03-15

    A survey of radioactivity in groundwater (110 sites) was conducted as a precursor to providing a baseline of radiation exposure in rural and remote communities in Queensland, Australia, that may be impacted upon by exposure pathways associated with the supply, treatment, use and wastewater treatment of the resource. Radionuclides in groundwater, including {sup 238}U, {sup 226}Ra, {sup 222}Rn, {sup 228}Ra, {sup 224}Ra and {sup 40}K were measured and found to contain activity concentration levels of up to 0.71 BqL{sup -1}, 0.96 BqL{sup -1}, 108 BqL{sup -1}, 2.8 BqL{sup -1}, 0.11 BqL{sup -1} and 0.19 BqL{sup -1} respectively. Activity concentration results were classified by aquifer lithology, showing correlation between increased radium isotope concentration and basic volcanic host rock. The groundwater survey and mapping results were further assessed using an investigation assessment tool to identify seven remote or rural communities that may require additional radiation dose assessment beyond that attributed to ingestion of potable water. - Research highlights: {yields} We studied the concentration of naturally occurring radioactivity in groundwater in Queensland, Australia. {yields} Groundwater radioactivity concentrations were classified by aquifer type, location and magnitude. {yields} Radioactivity concentration in groundwater was used to develop a tool to determine the potential for elevated radiation exposure to rural and remote communities, based on a case study of a reference site. {yields} Of 110 groundwater bores tested, seven were assessed as requiring further community dose assessment.

  2. Remote Zone Extracellular Volume and Left Ventricular Remodeling in Survivors of ST-Elevation Myocardial Infarction

    Science.gov (United States)

    Carberry, Jaclyn; Carrick, David; Haig, Caroline; Rauhalammi, Samuli M.; Ahmed, Nadeem; Mordi, Ify; McEntegart, Margaret; Petrie, Mark C.; Eteiba, Hany; Hood, Stuart; Watkins, Stuart; Lindsay, Mitchell; Davie, Andrew; Mahrous, Ahmed; Ford, Ian; Sattar, Naveed; Welsh, Paul; Radjenovic, Aleksandra; Oldroyd, Keith G.

    2016-01-01

    The natural history and pathophysiological significance of tissue remodeling in the myocardial remote zone after acute ST-elevation myocardial infarction (STEMI) is incompletely understood. Extracellular volume (ECV) in myocardial regions of interest can now be measured with cardiac magnetic resonance imaging. Patients who sustained an acute STEMI were enrolled in a cohort study (BHF MR-MI [British Heart Foundation Magnetic Resonance Imaging in Acute ST-Segment Elevation Myocardial Infarction study]). Cardiac magnetic resonance was performed at 1.5 Tesla at 2 days and 6 months post STEMI. T1 modified Look-Locker inversion recovery mapping was performed before and 15 minutes after contrast (0.15 mmol/kg gadoterate meglumine) in 140 patients at 2 days post STEMI (mean age: 59 years, 76% male) and in 131 patients at 6 months post STEMI. Remote zone ECV was lower than infarct zone ECV (25.6±2.8% versus 51.4±8.9%; Premote zone ECV (Premote zone ECV (P=0.010). No ST-segment resolution (P=0.034) and extent of ischemic area at risk (Premote zone ECV at 6 months (ΔECV). ΔECV was a multivariable associate of the change in left ventricular end-diastolic volume at 6 months (regression coefficient [95% confidence interval]: 1.43 (0.10–2.76); P=0.036). ΔECV is implicated in the pathophysiology of left ventricular remodeling post STEMI, but because the effect size is small, ΔECV has limited use as a clinical biomarker of remodeling. Clinical Trial Registration— URL: https://www.clinicaltrials.gov. Unique identifier: NCT02072850. PMID:27354423

  3. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978-1987

    DEFF Research Database (Denmark)

    Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat Abbas

    2016-01-01

    Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling...... in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978-1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM...... is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps....

  4. Digitial Elevation Model (DEM) 100K

    Data.gov (United States)

    Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USG to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

  5. Digtial Elevation Model (DEM) 250K

    Data.gov (United States)

    Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

  6. Digital Elevation Model (DEM) 24K

    Data.gov (United States)

    Kansas Data Access and Support Center — Digital Elevation Model (DEM) is the terminology adopted by the USGS to describe terrain elevation data sets in a digital raster form. The standard DEM consists of a...

  7. The Importance of Precise Digital Elevation Models (DEM) in Modelling Floods

    Science.gov (United States)

    Demir, Gokben; Akyurek, Zuhal

    2016-04-01

    Digital elevation Models (DEM) are important inputs for topography for the accurate modelling of floodplain hydrodynamics. Floodplains have a key role as natural retarding pools which attenuate flood waves and suppress flood peaks. GPS, LIDAR and bathymetric surveys are well known surveying methods to acquire topographic data. It is not only time consuming and expensive to obtain topographic data through surveying but also sometimes impossible for remote areas. In this study it is aimed to present the importance of accurate modelling of topography for flood modelling. The flood modelling for Samsun-Terme in Blacksea region of Turkey is done. One of the DEM is obtained from the point observations retrieved from 1/5000 scaled orthophotos and 1/1000 scaled point elevation data from field surveys at x-sections. The river banks are corrected by using the orthophotos and elevation values. This DEM is named as scaled DEM. The other DEM is obtained from bathymetric surveys. 296 538 number of points and the left/right bank slopes were used to construct the DEM having 1 m spatial resolution and this DEM is named as base DEM. Two DEMs were compared by using 27 x-sections. The maximum difference at thalweg of the river bed is 2m and the minimum difference is 20 cm between two DEMs. The channel conveyance capacity in base DEM is larger than the one in scaled DEM and floodplain is modelled in detail in base DEM. MIKE21 with flexible grid is used in 2- dimensional shallow water flow modelling. The model by using two DEMs were calibrated for a flood event (July 9, 2012). The roughness is considered as the calibration parameter. From comparison of input hydrograph at the upstream of the river and output hydrograph at the downstream of the river, the attenuation is obtained as 91% and 84% for the base DEM and scaled DEM, respectively. The time lag in hydrographs does not show any difference for two DEMs and it is obtained as 3 hours. Maximum flood extents differ for the two DEMs

  8. Cokriging model for estimation of water table elevation

    International Nuclear Information System (INIS)

    Hoeksema, R.J.; Clapp, R.B.; Thomas, A.L.; Hunley, A.E.; Farrow, N.D.; Dearstone, K.C.

    1989-01-01

    In geological settings where the water table is a subdued replica of the ground surface, cokriging can be used to estimate the water table elevation at unsampled locations on the basis of values of water table elevation and ground surface elevation measured at wells and at points along flowing streams. The ground surface elevation at the estimation point must also be determined. In the proposed method, separate models are generated for the spatial variability of the water table and ground surface elevation and for the dependence between these variables. After the models have been validated, cokriging or minimum variance unbiased estimation is used to obtain the estimated water table elevations and their estimation variances. For the Pits and Trenches area (formerly a liquid radioactive waste disposal facility) near Oak Ridge National Laboratory, water table estimation along a linear section, both with and without the inclusion of ground surface elevation as a statistical predictor, illustrate the advantages of the cokriging model

  9. Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database

    Science.gov (United States)

    Danielson, Jeffrey J.; Poppenga, Sandra K.; Brock, John C.; Evans, Gayla A.; Tyler, Dean; Gesch, Dean B.; Thatcher, Cindy A.; Barras, John

    2016-01-01

    During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastalinundation flooding from disastrous events. Because physical processes in coastal environments are controlled by the geomorphology of over-the-land topography and underwater bathymetry, many applications of geospatial data in coastal environments require detailed knowledge of the near-shore topography and bathymetry. In this paper, an updated methodology used by the U.S. Geological Survey Coastal National Elevation Database (CoNED) Applications Project is presented for developing coastal topobathymetric elevation models (TBDEMs) from multiple topographic data sources with adjacent intertidal topobathymetric and offshore bathymetric sources to generate seamlessly integrated TBDEMs. This repeatable, updatable, and logically consistent methodology assimilates topographic data (land elevation) and bathymetry (water depth) into a seamless coastal elevation model. Within the overarching framework, vertical datum transformations are standardized in a workflow that interweaves spatially consistent interpolation (gridding) techniques with a land/water boundary mask delineation approach. Output gridded raster TBDEMs are stacked into a file storage system of mosaic datasets within an Esri ArcGIS geodatabase for efficient updating while maintaining current and updated spatially referenced metadata. Topobathymetric data provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, and tsunami impact assessment. These detailed coastal elevation data are critical to depict regions prone to climate change impacts and are essential to planners and managers responsible for mitigating the associated risks and costs to both human communities and ecosystems. The CoNED methodology approach has been used to construct integrated TBDEM models

  10. Comparing live and remote models in eating conformity research.

    Science.gov (United States)

    Feeney, Justin R; Polivy, Janet; Pliner, Patricia; Sullivan, Margot D

    2011-01-01

    Research demonstrates that people conform to how much other people eat. This conformity occurs in the presence of other people (live model) and when people view information about how much food prior participants ate (remote models). The assumption in the literature has been that remote models produce a similar effect to live models, but this has never been tested. To investigate this issue, we randomly paired participants with a live or remote model and compared their eating to those who ate alone. We found that participants exposed to both types of model differed significantly from those in the control group, but there was no significant difference between the two modeling procedures. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

  11. A MULTI-RESOLUTION FUSION MODEL INCORPORATING COLOR AND ELEVATION FOR SEMANTIC SEGMENTATION

    Directory of Open Access Journals (Sweden)

    W. Zhang

    2017-05-01

    Full Text Available In recent years, the developments for Fully Convolutional Networks (FCN have led to great improvements for semantic segmentation in various applications including fused remote sensing data. There is, however, a lack of an in-depth study inside FCN models which would lead to an understanding of the contribution of individual layers to specific classes and their sensitivity to different types of input data. In this paper, we address this problem and propose a fusion model incorporating infrared imagery and Digital Surface Models (DSM for semantic segmentation. The goal is to utilize heterogeneous data more accurately and effectively in a single model instead of to assemble multiple models. First, the contribution and sensitivity of layers concerning the given classes are quantified by means of their recall in FCN. The contribution of different modalities on the pixel-wise prediction is then analyzed based on visualization. Finally, an optimized scheme for the fusion of layers with color and elevation information into a single FCN model is derived based on the analysis. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset. Comprehensive evaluations demonstrate the potential of the proposed approach.

  12. Group Elevator Peak Scheduling Based on Robust Optimization Model

    Directory of Open Access Journals (Sweden)

    ZHANG, J.

    2013-08-01

    Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.

  13. Modeling and Analysis of Remote, Off-grid Microgrids

    Science.gov (United States)

    Madathil, Sreenath Chalil

    Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids, to deliver power. Power distribution in most of these remote communities often depend on a type of microgrid called "off-grid microgrids". However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk to experience extended blackouts. Recent trends have also shown an increased use of renewable energy resources in power systems for remote communities. The increased penetration of renewable resources in power generation will require complex decision making when designing a resilient power system. This is mainly due to the stochastic nature of renewable resources that can lead to loss of load or line overload during their operations. In the first part of this thesis, we develop an optimization model and accompanying solution algorithm for capacity planning and operating microgrids that include N-1 security and other practical modeling features (e.g., AC power flow physics, component efficiencies and thermal limits). We demonstrate the effectiveness of our model and solution approach on two test systems: a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote Alaskan community. Once a tractable algorithm was identified to solve the above problem, we develop a mathematical model that includes topology design of microgrids. The topology design includes building new lines, making redundant lines, and analyzing N-1 contingencies on generators and lines. We develop a rolling horizon algorithm to efficiently analyze the model and demonstrate the strength of our algorithm in the same network. Finally, we develop a stochastic model that

  14. CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

    Directory of Open Access Journals (Sweden)

    A. İ. Durmaz

    2017-11-01

    Full Text Available DEM (Digital Elevation Models is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

  15. Innovative use of soft data for the validation of a rainfall-runoff model forced by remote sensing data

    Science.gov (United States)

    van Emmerik, Tim; Eilander, Dirk; Piet, Marijn; Mulder, Gert

    2013-04-01

    The Chamcar Bei catchment in southern Cambodia is a typical ungauged basin. Neither meteorological data or discharge measurements are available. In this catchment, local farmers are highly dependent on the irrigation system. However, due to the unreliability of the water supply, it was required to make a hydrological model, with which further improvements of the irrigation system could be planned. First, we used knowledge generated in the IAHS decade on Predictions in Ungauged Basins (PUB) to estimate the annual water balance of the Chamcar Bei catchment. Next, using remotely sensed precipitation, vegetation, elevation and transpiration data, a monthly rainfall-runoff model has been developed. The rainfall-runoff model was linked to the irrigation system reservoir, which allowed to validate the model based on soft data such as historical knowledge of the reservoir water level and groundwater levels visible in wells. This study shows that combining existing remote sensing data and soft ground data can lead to useful modeling results. The approach presented in this study can be applied in other ungauged basins, which can be extremely helpful in managing water resources in developing countries.

  16. A remote sensing driven distributed hydrological model of the Senegal River basin

    DEFF Research Database (Denmark)

    Stisen, Simon; Jensen, Karsten Høgh; Sandholt, Inge

    2008-01-01

    outputs of AET from both model setups was carried out. This revealed substantial differences in the spatial patterns of AET for the examined subcatchment, in spite of similar values of predicted discharge and average AET. The potential for driving large scale hydrological models using remote sensing data......Distributed hydrological models require extensive data amounts for driving the models and for parameterization of the land surface and subsurface. This study investigates the potential of applying remote sensing (RS) based input data in a hydrological model for the 350,000 km2 Senegal River basin...... in West Africa. By utilizing remote sensing data to estimate precipitation, potential evapotranspiration (PET) and leaf area index (LAI) the model was driven entirely by remote sensing based data and independent of traditional meteorological data. The remote sensing retrievals were based on data from...

  17. Coastal Digital Elevation Models (DEMs)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Digital elevation models (DEMs) of U.S. and other coasts that typically integrate ocean bathymetry and land topography. The DEMs support NOAA's mission to understand...

  18. Informing a hydrological model of the Ogooué with multi-mission remote sensing data

    Science.gov (United States)

    Kittel, Cecile M. M.; Nielsen, Karina; Tøttrup, Christian; Bauer-Gottwein, Peter

    2018-02-01

    Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall-runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953-1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling

  19. A Robust Algorithm of Multiquadric Method Based on an Improved Huber Loss Function for Interpolating Remote-Sensing-Derived Elevation Data Sets

    Directory of Open Access Journals (Sweden)

    Chuanfa Chen

    2015-03-01

    Full Text Available Remote-sensing-derived elevation data sets often suffer from noise and outliers due to various reasons, such as the physical limitations of sensors, multiple reflectance, occlusions and low contrast of texture. Outliers generally have a seriously negative effect on DEM construction. Some interpolation methods like ordinary kriging (OK are capable of smoothing noise inherent in sample points, but are sensitive to outliers. In this paper, a robust algorithm of multiquadric method (MQ based on an Improved Huber loss function (MQ-IH has been developed to decrease the impact of outliers on DEM construction. Theoretically, the improved Huber loss function is null for outliers, quadratic for small errors, and linear for others. Simulated data sets drawn from a mathematical surface with different error distributions were employed to analyze the robustness of MQ-IH. Results indicate that MQ-IH obtains a good balance between efficiency and robustness. Namely, the performance of MQ-IH is comparative to those of the classical MQ and MQ based on the Classical Huber loss function (MQ-CH when sample points follow a normal distribution, and the former outperforms the latter two when sample points are subject to outliers. For example, for the Cauchy error distribution with the location parameter of 0 and scale parameter of 1, the root mean square errors (RMSEs of MQ-CH and the classical MQ are 0.3916 and 1.4591, respectively, whereas that of MQ-IH is 0.3698. The performance of MQ-IH is further evaluated by qualitative and quantitative analysis through a real-world example of DEM construction with the stereo-images-derived elevation points. Results demonstrate that compared with the classical interpolation methods, including natural neighbor (NN, OK and ANUDEM (a program that calculates regular grid digital elevation models (DEMs with sensible shape and drainage structure from arbitrarily large topographic data sets, and two versions of MQ, including the

  20. Landslide hazard assessment along a mountain highway in the Indian Himalayan Region (IHR) using remote sensing and computational models

    Science.gov (United States)

    Krishna, Akhouri P.; Kumar, Santosh

    2013-10-01

    Landslide hazard assessments using computational models, such as artificial neural network (ANN) and frequency ratio (FR), were carried out covering one of the important mountain highways in the Central Himalaya of Indian Himalayan Region (IHR). Landslide influencing factors were either calculated or extracted from spatial databases including recent remote sensing data of LANDSAT TM, CARTOSAT digital elevation model (DEM) and Tropical Rainfall Measuring Mission (TRMM) satellite for rainfall data. ANN was implemented using the multi-layered feed forward architecture with different input, output and hidden layers. This model based on back propagation algorithm derived weights for all possible parameters of landslides and causative factors considered. The training sites for landslide prone and non-prone areas were identified and verified through details gathered from remote sensing and other sources. Frequency Ratio (FR) models are based on observed relationships between the distribution of landslides and each landslide related factor. FR model implementation proved useful for assessing the spatial relationships between landslide locations and factors contributing to its occurrence. Above computational models generated respective susceptibility maps of landslide hazard for the study area. This further allowed the simulation of landslide hazard maps on a medium scale using GIS platform and remote sensing data. Upon validation and accuracy checks, it was observed that both models produced good results with FR having some edge over ANN based mapping. Such statistical and functional models led to better understanding of relationships between the landslides and preparatory factors as well as ensuring lesser levels of subjectivity compared to qualitative approaches.

  1. Remote sensing approach to structural modelling

    International Nuclear Information System (INIS)

    El Ghawaby, M.A.

    1989-01-01

    Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs

  2. A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Xiuhong Zhang

    2018-01-01

    Full Text Available With the rapid development of remote sensing technology, the quantity and variety of remote sensing images are growing so quickly that proactive and personalized access to data has become an inevitable trend. One of the active approaches is remote sensing image recommendation, which can offer related image products to users according to their preference. Although multiple studies on remote sensing retrieval and recommendation have been performed, most of these studies model the user profiles only from the perspective of spatial area or image features. In this paper, we propose a spatiotemporal recommendation method for remote sensing data based on the probabilistic latent topic model, which is named the Space-Time Periodic Task model (STPT. User retrieval behaviors of remote sensing images are represented as mixtures of latent tasks, which act as links between users and images. Each task is associated with the joint probability distribution of space, time and image characteristics. Meanwhile, the von Mises distribution is introduced to fit the distribution of tasks over time. Then, we adopt Gibbs sampling to learn the random variables and parameters and present the inference algorithm for our model. Experiments show that the proposed STPT model can improve the capability and efficiency of remote sensing image data services.

  3. Optical Remote Sensing of Glacier Characteristics: A Review with Focus on the Himalaya

    Science.gov (United States)

    Racoviteanu, Adina E.; Williams, Mark W.; Barry, Roger G.

    2008-01-01

    The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya. PMID:27879883

  4. An evaluation of onshore digital elevation models for tsunami inundation modelling

    Science.gov (United States)

    Griffin, J.; Latief, H.; Kongko, W.; Harig, S.; Horspool, N.; Hanung, R.; Rojali, A.; Maher, N.; Fountain, L.; Fuchs, A.; Hossen, J.; Upi, S.; Dewanto, S. E.; Cummins, P. R.

    2012-12-01

    Tsunami inundation models provide fundamental information about coastal areas that may be inundated in the event of a tsunami along with additional parameters such as flow depth and velocity. This can inform disaster management activities including evacuation planning, impact and risk assessment and coastal engineering. A fundamental input to tsunami inundation models is adigital elevation model (DEM). Onshore DEMs vary widely in resolution, accuracy, availability and cost. A proper assessment of how the accuracy and resolution of DEMs translates into uncertainties in modelled inundation is needed to ensure results are appropriately interpreted and used. This assessment can in turn informdata acquisition strategies depending on the purpose of the inundation model. For example, lower accuracy elevation data may give inundation results that are sufficiently accurate to plan a community's evacuation route but not sufficient to inform engineering of a vertical evacuation shelters. A sensitivity study is undertaken to assess the utility of different available onshore digital elevation models for tsunami inundation modelling. We compare airborne interferometric synthetic aperture radar (IFSAR), ASTER and SRTM against high resolution (historical tsunami run-up data. Large vertical errors (> 10 m) and poor resolution of the coastline in the ASTER and SRTM elevation models cause modelled inundation to be much less compared with models using better data and with observations. Therefore we recommend that ASTER and SRTM should not be used for modelling tsunami inundation in order to determine tsunami extent or any other measure of onshore tsunami hazard. We suggest that for certain disaster management applications where the important factor is the extent of inundation, such as evacuation planning, airborne IFSAR provides a good compromise between cost and accuracy; however the representation of flow parameters such as depth and velocity is not sufficient to inform detailed

  5. An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

    Science.gov (United States)

    Jones, J.W.; Desmond, G.B.; Henkle, C.; Glover, R.

    2012-01-01

    Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (??15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data. ?? 2012 Taylor & Francis.

  6. Estimating Coastal Digital Elevation Model (DEM) Uncertainty

    Science.gov (United States)

    Amante, C.; Mesick, S.

    2017-12-01

    Integrated bathymetric-topographic digital elevation models (DEMs) are representations of the Earth's solid surface and are fundamental to the modeling of coastal processes, including tsunami, storm surge, and sea-level rise inundation. Deviations in elevation values from the actual seabed or land surface constitute errors in DEMs, which originate from numerous sources, including: (i) the source elevation measurements (e.g., multibeam sonar, lidar), (ii) the interpolative gridding technique (e.g., spline, kriging) used to estimate elevations in areas unconstrained by source measurements, and (iii) the datum transformation used to convert bathymetric and topographic data to common vertical reference systems. The magnitude and spatial distribution of the errors from these sources are typically unknown, and the lack of knowledge regarding these errors represents the vertical uncertainty in the DEM. The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) has developed DEMs for more than 200 coastal communities. This study presents a methodology developed at NOAA NCEI to derive accompanying uncertainty surfaces that estimate DEM errors at the individual cell-level. The development of high-resolution (1/9th arc-second), integrated bathymetric-topographic DEMs along the southwest coast of Florida serves as the case study for deriving uncertainty surfaces. The estimated uncertainty can then be propagated into the modeling of coastal processes that utilize DEMs. Incorporating the uncertainty produces more reliable modeling results, and in turn, better-informed coastal management decisions.

  7. A new, accurate, global hydrography data for remote sensing and modelling of river hydrodynamics

    Science.gov (United States)

    Yamazaki, D.

    2017-12-01

    A high-resolution hydrography data is an important baseline data for remote sensing and modelling of river hydrodynamics, given the spatial scale of river network is much smaller than that of land hydrology or atmosphere/ocean circulations. For about 10 years, HydroSHEDS, developed based on the SRTM3 DEM, has been the only available global-scale hydrography data. However, the data availability at the time of HydroSHEDS development limited the quality of the represented river networks. Here, we developed a new global hydrography data using latest geodata such as the multi-error-removed elevation data (MERIT DEM), Landsat-based global water body data (GSWO & G3WBM), cloud-sourced open geography database (OpenStreetMap). The new hydrography data covers the entire globe (including boreal regions above 60N), and it represents more detailed structure of the world river network and contains consistent supplementary data layers such as hydrologically adjusted elevations and river channel width. In the AGU meeting, the developing methodology, assessed quality, and potential applications of the new global hydrography data will be introduced.

  8. Digital elevation modeling via curvature interpolation for lidar data

    Science.gov (United States)

    Digital elevation model (DEM) is a three-dimensional (3D) representation of a terrain's surface - for a planet (including Earth), moon, or asteroid - created from point cloud data which measure terrain elevation. Its modeling requires surface reconstruction for the scattered data, which is an ill-p...

  9. Modeling of AlMg Sheet Forming at Elevated Temperatures

    NARCIS (Netherlands)

    van den Boogaard, Antonius H.; Bolt, P.; Werkhoven, R.

    2001-01-01

    The process limits of aluminum sheet forming processes can be improved by control-ling local flow behavior by means of elevated temperatures and temperature gradients. In order to accurately model the deep drawing or stretching of aluminum sheet at elevated temperatures, a model is required that

  10. Galveston, Texas Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  11. Savannah, Georgia Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  12. Biloxi, Mississippi Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Hilo, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. Hanalei, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  16. Taholah, Washington Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. Chignik, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  18. Monterey, California Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  19. Garibaldi, Oregon Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Keauhou, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Atka, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. Lahaina, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Kawaihae, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Nikolski, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Shemya, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Portland, Maine Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Craig, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Midway Atoll Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. Adak, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Cordova, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  11. Nantucket, Massachusetts Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  12. Oahu, Hawaii Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. Central Oregon Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Southeast Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  15. Tatitlek, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  16. Hoonah, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  17. Whittier, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  18. Gustavus, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  19. Chenega, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  20. Juneau, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  1. Mariana Trench Bathymetric Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) created a bathymetric digital elevation model (DEM) for the Mariana Trench and adjacent seafloor in the Western...

  2. Unalaska, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  3. Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5

    Science.gov (United States)

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Lei; Lee, Wonjin; Lee, Chang-Wook

    2012-01-01

    An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.

  4. Remote object authentication: confidence model, cryptosystem and protocol

    Science.gov (United States)

    Lancrenon, Jean; Gillard, Roland; Fournel, Thierry

    2009-04-01

    This paper follows a paper by Bringer et al.3 to adapt a security model and protocol used for remote biometric authentication to the case of remote morphometric object authentication. We use a different type of encryption technique that requires smaller key sizes and has a built-in mechanism to help control the integrity of the messages received by the server. We also describe the optical technology used to extract the morphometric templates.

  5. Complex motion of elevators in piecewise map model combined with circle map

    Science.gov (United States)

    Nagatani, Takashi

    2013-11-01

    We study the dynamic behavior in the elevator traffic controlled by capacity when the inflow rate of passengers into elevators varies periodically with time. The dynamics of elevators is described by the piecewise map model combined with the circle map. The motion of the elevators depends on the inflow rate, its period, and the number of elevators. The motion in the piecewise map model combined with the circle map shows a complex behavior different from the motion in the piecewise map model.

  6. ASTER Digital Elevation Model V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The ASTER Digital Elevation Model (DEM) product is generated using bands 3N (nadir-viewing) and 3B (backward-viewing) of an ASTER Level-1A image acquired by the...

  7. Space Station tethered elevator system

    Science.gov (United States)

    Haddock, Michael H.; Anderson, Loren A.; Hosterman, K.; Decresie, E.; Miranda, P.; Hamilton, R.

    1989-01-01

    The optimized conceptual engineering design of a space station tethered elevator is presented. The tethered elevator is an unmanned, mobile structure which operates on a ten-kilometer tether spanning the distance between Space Station Freedom and a platform. Its capabilities include providing access to residual gravity levels, remote servicing, and transportation to any point along a tether. The report discusses the potential uses, parameters, and evolution of the spacecraft design. Emphasis is placed on the elevator's structural configuration and three major subsystem designs. First, the design of elevator robotics used to aid in elevator operations and tethered experimentation is presented. Second, the design of drive mechanisms used to propel the vehicle is discussed. Third, the design of an onboard self-sufficient power generation and transmission system is addressed.

  8. Remote measurement of canopy reflectance shows the effects of elevated carbon dioxide and ozone on the structure and functioning of soybeans in a field setting.

    Science.gov (United States)

    Gray, S.; Dermody, O.; Delucia, E.

    2006-12-01

    By altering physiological processes and modifying canopy structure, elevated atmospheric CO2 and O3 directly and indirectly change the productivity of agroecosystems. Remote sensing of canopy reflectance can be used to monitor physiological and structural changes in an ecosystem over a growing season. To examine effects of changing tropospheric chemistry on water content, chlorophyll content, and changes in leaf area index (LAI), Free-Air Concentration Enrichment (FACE) technology was used to expose large plots of soybean (Glycine max) to elevated atmospheric CO2, elevated O3 (1.5 x ambient), and combined elevated CO2 and O3. The following indices were calculated from weekly measurements of reflectance: water index (WI), photochemical reflectance index (PRI), chlorophyll index, near-infrared/ red (NIR/red), and normalized difference vegetation index (NDVI). NIR/red and LAI were strongly correlated throughout the growth season; however NDVI and LAI were highly correlated only up to LAI of 3. Exposure to elevated CO2 accelerated early-season canopy development and delayed late-season senescence. Growth in elevated O3 had the opposite effect. Additionally, elevated CO2 compensated for negative effects of O3 when the canopy was exposed to both gases simultaneously. Reflectance indices revealed several physiological and structural responses of this agroecosystem to tropospheric change, and ultimately that elevated CO2 and O3 significantly affected this system's productivity and period for carbon gain.

  9. Bearing load distribution studies in a multi bearing rotor system and a remote computing method based on the internet

    International Nuclear Information System (INIS)

    Yang, Zhao Jian; Peng, Ze Jun; Kim, Seock Sam

    2004-01-01

    A model in the form of a Bearing Load Distribution (BLD) matrix in the Multi Bearing Rotor System (MBRS) is established by a transfer matrix equation with the consideration of a bearing load, elevation and uniform load distribution. The concept of Bearing Load Sensitivity (BLS) is proposed and matrices for load and elevation sensitivity are obtained. In order to share MBRS design resources on the internet with remote customers, the basic principle of Remote Computing (RC) based on the internet is introduced ; the RC of the BLD and BLS is achieved by Microsoft Active Server Pages (ASP) technology

  10. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987

    Science.gov (United States)

    Korsgaard, Niels J.; Nuth, Christopher; Khan, Shfaqat A.; Kjeldsen, Kristian K.; Bjørk, Anders A.; Schomacker, Anders; Kjær, Kurt H.

    2016-01-01

    Digital Elevation Models (DEMs) play a prominent role in glaciological studies for the mass balance of glaciers and ice sheets. By providing a time snapshot of glacier geometry, DEMs are crucial for most glacier evolution modelling studies, but are also important for cryospheric modelling in general. We present a historical medium-resolution DEM and orthophotographs that consistently cover the entire surroundings and margins of the Greenland Ice Sheet 1978–1987. About 3,500 aerial photographs of Greenland are combined with field surveyed geodetic ground control to produce a 25 m gridded DEM and a 2 m black-and-white digital orthophotograph. Supporting data consist of a reliability mask and a photo footprint coverage with recording dates. Through one internal and two external validation tests, this DEM shows an accuracy better than 10 m horizontally and 6 m vertically while the precision is better than 4 m. This dataset proved successful for topographical mapping and geodetic mass balance. Other uses include control and calibration of remotely sensed data such as imagery or InSAR velocity maps. PMID:27164457

  11. The use of remote sensing and GIS techniques with special emphasis on the use of Arc hydro data model in characterizing Atbara River watershed

    International Nuclear Information System (INIS)

    Adam, M. H. M.

    2010-11-01

    Remote sensing and GIS techniques were used successfully to establish hydrological information platform for Atbara sub-basin which drains from Ethiopia and Eretria to Sudan with entire area of about 224299 Km 2 . The study area have strategic importance, for many reasons; rich in minerals wealth, agricultural resources, and endowed with a substantial amount of water resources but the spatial and temporal distribution of water resources is imbalance. Remote Sensing and Digital elevation models (DEMs) are known to be very useful data sources for the automated delineation of flow paths, sub watersheds and flow networks for hydrologic modeling and watershed characterization, Landsat ETM + 30 m and Digital Elevation Models SRTM 90 m data used in this project, many digital image processing techniques used to enhanced images, interpretation and extracted information from satellite images by using ERDAS imagine, wile Arc GIS and arc hydro tools were used to processing and extract information from DEMs, stream network and catchment delineation and creation of geo database. It is the main output of this project, ready made GIS layers used to complete watershed characterizations view. The results of this research present in creation Arc hydro data model, and many thematic maps for Atbara sub-basin characteristics. The use of remote sensing in the study give efficient qualitative and quantitative detailed information about geomorphologic features drainage patterns, addition to general overview for land cover and land use. Moreover, the use of Digital Elevation Models in addition to the delineation of stream network and catchment give valuable information on the pale-geography and pale-climate of the study area. River network and watersheds delineations proved that El Gash River was once joining the Atbara River and it was a part of Nile Basin System. This might indicate that pale climatic conditions in the area were wet than the present. Geo database and Arc hydro data model

  12. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    Science.gov (United States)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  13. Model Checking the Remote Agent Planner

    Science.gov (United States)

    Khatib, Lina; Muscettola, Nicola; Havelund, Klaus; Norvig, Peter (Technical Monitor)

    2001-01-01

    This work tackles the problem of using Model Checking for the purpose of verifying the HSTS (Scheduling Testbed System) planning system. HSTS is the planner and scheduler of the remote agent autonomous control system deployed in Deep Space One (DS1). Model Checking allows for the verification of domain models as well as planning entries. We have chosen the real-time model checker UPPAAL for this work. We start by motivating our work in the introduction. Then we give a brief description of HSTS and UPPAAL. After that, we give a sketch for the mapping of HSTS models into UPPAAL and we present samples of plan model properties one may want to verify.

  14. ASTER Global Digital Elevation Model V002

    Data.gov (United States)

    National Aeronautics and Space Administration — The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the U.S. National...

  15. Supervised Gaussian mixture model based remote sensing image ...

    African Journals Online (AJOL)

    Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

  16. Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing.

    Science.gov (United States)

    Walz, Yvonne; Wegmann, Martin; Dech, Stefan; Vounatsou, Penelope; Poda, Jean-Noël; N'Goran, Eliézer K; Utzinger, Jürg; Raso, Giovanna

    2015-11-01

    Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health. We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d'Ivoire and validated against readily available survey data from school-aged children. Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d'Ivoire. A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail

  17. Remote sensing sensors and applications in environmental resources mapping and modeling

    Science.gov (United States)

    Melesse, Assefa M.; Weng, Qihao; Thenkabail, Prasad S.; Senay, Gabriel B.

    2007-01-01

    The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling.

  18. Real-time remote sensing driven river basin modeling using radar altimetry

    DEFF Research Database (Denmark)

    Pereira Cardenal, Silvio Javier; Riegels, Niels; Bauer-Gottwein, Peter

    2011-01-01

    Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS) data have been recognized as an alternative to in-situ hydrometeorological data in remote...

  19. Kachemak Bay, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Virginia Beach, Virginia Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Santa Barbara, California Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. Ocean City, Maryland Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. King Cove, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Panama City, Florida Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Montauk, New York Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Sand Point, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. La Push, Washington Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Arena Cove, California Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. Port Orford, Oregon Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Arecibo, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  11. Grenada Digital Elevation Model - 1 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  12. Guayama, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. Fajardo, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Corpus Christi, Texas Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. Dutch Harbor, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  16. Ponce, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. Daytona Beach, Florida Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  18. Port Alexander Alaska Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  19. Digital Elevation Models (DEMs) for the main 8 Hawaiian Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Digital elevation model (DEM) data are arrays of regularly spaced elevation values referenced horizontally either to a Universal Transverse Mercator (UTM) projection...

  20. Renoprotective effect of remote ischemic postconditioning in patients with ST-elevation myocardial infarction undergoing primary percutaneous coronary intervention

    Directory of Open Access Journals (Sweden)

    Cao B

    2018-02-01

    Full Text Available Bangming Cao,* Chi Zhang,* Haipeng Wang, Ming Xia, Xiangjun Yang Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China *These authors contributed equally to this work Background: Whether upper arm remote ischemic postconditioning (RIPostC exerts protection to kidney in patients with ST-elevation myocardial infarction (STEMI undergoing primary percutaneous coronary intervention (PPCI remains unknown. Methods: Sixty-four patients with STEMI were randomized to PPCI + RIPostC (n=29 and PPCI (n=35 groups. RIPostC consisting of 4 cycles of 5 minutes occlusion/reperfusion by cuff inflation/deflation of the upper arm was started within 1 minute after the first balloon dilatation. Peripheral venous blood samples were collected before PPCI and at 0.5, 8, 24, 48, and 72 hours after PPCI to detect serum creatinine (SCr and creatine kinase-MB (CK-MB. Acute kidney injury (AKI rate and estimated glomerular filtration rate (eGFR were calculated. The transthoracic echocardiography was performed 7 days after PPCI to assess left ventricular ejection fraction (LVEF. Results: The patients in the PPCI + RIPostC group had a lower AKI rate compared with those in the PPCI group (P=0.04. The eGFR after PPCI increased in the PPCI + RIPostC group compared to the PPCI group (P<0.01. The peak of CK-MB concentration in the PPCI + RIPostC group was significantly lower than that in the PPCI group (P<0.01. The area under the curve of CK-MB decreased in the PPCI + RIPostC group compared with that in the PPCI group. LVEF in the PPCI + RIPostC group was significantly higher than that in the PPCI group (P=0.04. Conclusion: Upper arm RIPostC exerts renal and cardiac protection following cardiac ischemia–reperfusion in patients with STEMI. Keywords: myocardial ischemia reperfusion, ST-segmental elevation myocardial infarction, primary percutaneous coronary intervention, remote ischemic postconditioning

  1. Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

    Science.gov (United States)

    Hadley, Brian Christopher

    This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

  2. New Orleans, Louisiana Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  3. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  4. A Citizen Science Campaign to Validate Snow Remote-Sensing Products

    Science.gov (United States)

    Wikstrom Jones, K.; Wolken, G. J.; Arendt, A. A.; Hill, D. F.; Crumley, R. L.; Setiawan, L.; Markle, B.

    2017-12-01

    The ability to quantify seasonal water retention and storage in mountain snow packs has implications for an array of important topics, including ecosystem function, water resources, hazard mitigation, validation of remote sensing products, climate modeling, and the economy. Runoff simulation models, which typically rely on gridded climate data and snow remote sensing products, would be greatly improved if uncertainties in estimates of snow depth distribution in high-elevation complex terrain could be reduced. This requires an increase in the spatial and temporal coverage of observational snow data in high-elevation data-poor regions. To this end, we launched Community Snow Observations (CSO). Participating citizen scientists use Mountain Hub, a multi-platform mobile and web-based crowdsourcing application that allows users to record, submit, and instantly share geo-located snow depth, snow water equivalence (SWE) measurements, measurement location photos, and snow grain information with project scientists and other citizen scientists. The snow observations are used to validate remote sensing products and modeled snow depth distribution. The project's prototype phase focused on Thompson Pass in south-central Alaska, an important infrastructure corridor that includes avalanche terrain and the Lowe River drainage and is essential to the City of Valdez and the fisheries of Prince William Sound. This year's efforts included website development, expansion of the Mountain Hub tool, and recruitment of citizen scientists through a combination of social media outreach, community presentations, and targeted recruitment of local avalanche professionals. We also conducted two intensive field data collection campaigns that coincided with an aerial photogrammetric survey. With more than 400 snow depth observations, we have generated a new snow remote-sensing product that better matches actual SWE quantities for Thompson Pass. In the next phase of the citizen science portion of

  5. How processing digital elevation models can affect simulated water budgets

    Science.gov (United States)

    Kuniansky, E.L.; Lowery, M.A.; Campbell, B.G.

    2009-01-01

    For regional models, the shallow water table surface is often used as a source/sink boundary condition, as model grid scale precludes simulation of the water table aquifer. This approach is appropriate when the water table surface is relatively stationary. Since water table surface maps are not readily available, the elevation of the water table used in model cells is estimated via a two-step process. First, a regression equation is developed using existing land and water table elevations from wells in the area. This equation is then used to predict the water table surface for each model cell using land surface elevation available from digital elevation models (DEM). Two methods of processing DEM for estimating the land surface for each cell are commonly used (value nearest the cell centroid or mean value in the cell). This article demonstrates how these two methods of DEM processing can affect the simulated water budget. For the example presented, approximately 20% more total flow through the aquifer system is simulated if the centroid value rather than the mean value is used. This is due to the one-third greater average ground water gradients associated with the centroid value than the mean value. The results will vary depending on the particular model area topography and cell size. The use of the mean DEM value in each model cell will result in a more conservative water budget and is more appropriate because the model cell water table value should be representative of the entire cell area, not the centroid of the model cell.

  6. Remote sensing inputs to water demand modeling

    Science.gov (United States)

    Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

    1975-01-01

    In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

  7. International Digital Elevation Model Service (IDEMS): A Revived IAG Service

    Science.gov (United States)

    Kelly, K. M.; Hirt, C., , Dr; Kuhn, M.; Barzaghi, R.

    2017-12-01

    A newly developed International Digital Elevation Model Service (IDEMS) is now available under the umbrella of the International Gravity Field Service of the International Association of Geodesy. Hosted and operated by Environmental Systems Research Institute (Esri) (http://www.esri.com/), the new IDEMS website is available at: https://idems.maps.arcgis.com/home/index.html. IDEMS provides a focus for distribution of data and information about various digital elevation models, including spherical-harmonic models of Earth's global topography and lunar and planetary DEM. Related datasets, such as representation of inland water within DEMs, and relevant software which are available in the public domain are also provided. Currently, IDEMS serves as repository of links to providers of global terrain and bathymetry, terrain related Earth models and datasets such as digital elevation data services managed and maintained by Esri (Terrain and TopoBathy), Bedmap2-Ice thickness and subglacial topographic model of Antarctica and Ice, Cloud, and Land Elevation ICESat/GLAS Data, as well as planetary terrain data provided by PDS Geosciences Node at Washington University, St. Louis. These services provide online access to a collection of multi-resolution and multi-source elevation and bathymetry data, including metadata and source information. In addition to IDEMS current holdings of terrestrial and planetary DEMs, some topography related products IDEMS may include in future are: dynamic ocean topography, 3D crustal density models, Earth's dynamic topography, etc. IDEMS may also consider terrain related products such as quality assessments, global terrain corrections, global height anomaly-to-geoid height corrections and other geodesy-relevant studies and products. IDEMS encourages contributions to the site from the geodetic community in any of the product types listed above. Please contact the authors if you would like to contribute or recommend content you think appropriate for

  8. Challenges of Microgrids in Remote Communities: A STEEP Model Application

    Directory of Open Access Journals (Sweden)

    Daniel Akinyele

    2018-02-01

    Full Text Available There is a growing interest in the application of microgrids around the world because of their potential for achieving a flexible, reliable, efficient and smart electrical grid system and supplying energy to off-grid communities, including their economic benefits. Several research studies have examined the application issues of microgrids. However, a lack of in-depth considerations for the enabling planning conditions has been identified as a major reason why microgrids fail in several off-grid communities. This development requires research efforts that consider better strategies and framework for sustainable microgrids in remote communities. This paper first presents a comprehensive review of microgrid technologies and their applications. It then proposes the STEEP model to examine critically the failure factors based on the social, technical, economic, environmental and policy (STEEP perspectives. The model details the key dimensions and actions necessary for addressing the challenge of microgrid failure in remote communities. The study uses remote communities within Nigeria, West Africa, as case studies and demonstrates the need for the STEEP approach for better understanding of microgrid planning and development. Better insights into microgrid systems are expected to address the drawbacks and improve the situation that can lead to widespread and sustainable applications in off-grid communities around the world in the future. The paper introduces the sustainable planning framework (SPF based on the STEEP model, which can form a general basis for planning microgrids in any remote location.

  9. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

    Science.gov (United States)

    Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

    2018-04-01

    With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

  10. Remote information service access system based on a client-server-service model

    Science.gov (United States)

    Konrad, A.M.

    1996-08-06

    A local host computing system, a remote host computing system as connected by a network, and service functionalities: a human interface service functionality, a starter service functionality, and a desired utility service functionality, and a Client-Server-Service (CSS) model is imposed on each service functionality. In one embodiment, this results in nine logical components and three physical components (a local host, a remote host, and an intervening network), where two of the logical components are integrated into one Remote Object Client component, and that Remote Object Client component and the other seven logical components are deployed among the local host and remote host in a manner which eases compatibility and upgrade problems, and provides an illusion to a user that a desired utility service supported on a remote host resides locally on the user`s local host, thereby providing ease of use and minimal software maintenance for users of that remote service. 16 figs.

  11. Remote Sensing Technologies and Geospatial Modelling Hierarchy for Smart City Support

    Science.gov (United States)

    Popov, M.; Fedorovsky, O.; Stankevich, S.; Filipovich, V.; Khyzhniak, A.; Piestova, I.; Lubskyi, M.; Svideniuk, M.

    2017-12-01

    The approach to implementing the remote sensing technologies and geospatial modelling for smart city support is presented. The hierarchical structure and basic components of the smart city information support subsystem are considered. Some of the already available useful practical developments are described. These include city land use planning, urban vegetation analysis, thermal condition forecasting, geohazard detection, flooding risk assessment. Remote sensing data fusion approach for comprehensive geospatial analysis is discussed. Long-term city development forecasting by Forrester - Graham system dynamics model is provided over Kiev urban area.

  12. Method for Measuring the Information Content of Terrain from Digital Elevation Models

    Directory of Open Access Journals (Sweden)

    Lujin Hu

    2015-10-01

    Full Text Available As digital terrain models are indispensable for visualizing and modeling geographic processes, terrain information content is useful for terrain generalization and representation. For terrain generalization, if the terrain information is considered, the generalized terrain may be of higher fidelity. In other words, the richer the terrain information at the terrain surface, the smaller the degree of terrain simplification. Terrain information content is also important for evaluating the quality of the rendered terrain, e.g., the rendered web terrain tile service in Google Maps (Google Inc., Mountain View, CA, USA. However, a unified definition and measures for terrain information content have not been established. Therefore, in this paper, a definition and measures for terrain information content from Digital Elevation Model (DEM, i.e., a digital model or 3D representation of a terrain’s surface data are proposed and are based on the theory of map information content, remote sensing image information content and other geospatial information content. The information entropy was taken as the information measuring method for the terrain information content. Two experiments were carried out to verify the measurement methods of the terrain information content. One is the analysis of terrain information content in different geomorphic types, and the results showed that the more complex the geomorphic type, the richer the terrain information content. The other is the analysis of terrain information content with different resolutions, and the results showed that the finer the resolution, the richer the terrain information. Both experiments verified the reliability of the measurements of the terrain information content proposed in this paper.

  13. Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

    International Nuclear Information System (INIS)

    Seinfeld, J.H.

    1982-01-01

    The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The data assimilation problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three-dimensional concentration fields from atmospheric diffusion models. General conditions were derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data was developed

  14. Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

    International Nuclear Information System (INIS)

    Seinfeld, J.H.

    1982-01-01

    The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the reconstructability of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed

  15. "One-Stop Shopping" for Ocean Remote-Sensing and Model Data

    Science.gov (United States)

    Li, P. Peggy; Vu, Quoc; Chao, Yi; Li, Zhi-Jin; Choi, Jei-Kook

    2006-01-01

    OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the

  16. San Juan Islands, Washington Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. San Juan, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  18. U.S. Virgin Islands Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  19. Cape Hatteras, North Carolina Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Sand Point, Alaska MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Port San Luis, California Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. Rarotonga 1 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Eastern Canada Digital Elevation Model - 3 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Central Oregon Coastal Digital Elevation Model NAVD 88

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Atlantic City, New Jersey Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Galapagos Islands, Ecuador 1 sec Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Galapagos Islands, Ecuador 3 sec Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Microstructure-based multiscale modeling of elevated temperature deformation in aluminum alloys

    International Nuclear Information System (INIS)

    Krajewski, Paul E.; Hector, Louis G.; Du Ningning; Bower, Allan F.

    2010-01-01

    A multiscale model for predicting elevated temperature deformation in Al-Mg alloys is presented. Constitutive models are generated from a theoretical methodology and used to investigate the effects of grain size on formability. Flow data are computed with a polycrystalline, microstructure-based model which accounts for grain boundary sliding, stress-induced diffusion, and dislocation creep. Favorable agreement is found between the computed flow data and elevated temperature tensile measurements. A creep constitutive model is then fit to the computed flow data and used in finite-element simulations of two simple gas pressure forming processes, where favorable results are observed. These results are fully consistent with gas pressure forming experiments, and suggest a greater role for constitutive models, derived largely from theoretical methodologies, in the design of Al alloys with enhanced elevated temperature formability. The methodology detailed herein provides a framework for incorporation of results from atomistic-scale models of dislocation creep and diffusion.

  9. Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data

    Directory of Open Access Journals (Sweden)

    Jingyi Zhang

    2018-06-01

    Full Text Available This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF method to estimate ground PM2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM2.5 analysis and prediction.

  10. Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data.

    Science.gov (United States)

    Zhang, Jingyi; Li, Bin; Chen, Yumin; Chen, Meijie; Fang, Tao; Liu, Yongfeng

    2018-06-11

    This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF) method to estimate ground PM 2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR) models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM 2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM 2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM 2.5 analysis and prediction.

  11. ASTER Orthorectified Digital Elevation Model (DEM) V003

    Data.gov (United States)

    National Aeronautics and Space Administration — The ASTER L3 DEM and Orthorectified Images form a multi-file product that contains both the Digital Elevation Model (DEM), and the Orthorectified Image products....

  12. Minnesota Digital Elevation Model - Tiled 93 Meter Resolution

    Data.gov (United States)

    Minnesota Department of Natural Resources — Digital Elevation Model (DEM) at a resolution of 93 meters. Original data resolution was 3 arc seconds which corresponds (approximately) to a matrix of points at a...

  13. ALTIMETRY ASSESSMENT OF ASTER GDEM v2 AND SRTM v3 DIGITAL ELEVATION MODELS: A CASE STUDY IN URBAN AREA OF BELO HORIZONTE, MG, BRAZIL

    Directory of Open Access Journals (Sweden)

    Josyceyla Duarte Morais

    Full Text Available Abstract: This work is an altimetry evaluation study involving Digital Elevation Models ASTER GDEM version 2 and SRTM version 3. Both models are readily available free of charge, however as they are built from different remote sensing methods it is also expected that they present different data qualities. LIDAR data with 25 cm vertical accuracy were used as reference for assessment validation. The evaluation study, carried out in urbanized area, investigated the distribution of the residuals and the relationship between the observed errors with land slope classes. Remote sensing principles, quantitative statistical methods and the Cartographic Accuracy Standard of Digital Mapping Products (PEC-PCD were considered. The results indicated strong positive linear correlation and the existence of a functional relationship between the evaluated models and the reference model. Residuals between -4.36 m and 3.11 m grouped 47.7% of samples corresponding to ASTER GDEM and 63.7% of samples corresponding to SRTM. In both evaluated models, Root Mean Square Error values increased with increasing of land slope. Considering 1: 50,000 mapping scale the PEC-PCD classification indicated class B standard for SRTM and class C for ASTER GDEM. In all analyzes, SRTM presented smaller altimetry errors compared to ASTER GDEM, except in areas with steep relief.

  14. Modelling Periglacial Processes on Low-Relief High-Elevation Surfaces

    DEFF Research Database (Denmark)

    Andersen, Jane Lund; Knudsen, Mads Faurschou; Egholm, D.L.

    history in many regions of the world. The glacial buzzsaw concept suggests that intense glacial erosion focused at the equilibrium-line altitude (ELA) leads to a concentration in surface area close to the ELA. However, even in predominantly glacial landscapes, such as the Scandinavian Mountains, the high...... as a function of mean annual air temperature and sediment thickness. This allows us to incorporate periglacial processes into a long-term landscape evolution model where surface elevation, sediment thickness, and climate evolve over time. With this model we are able to explore the slow feedbacks between...... evolution model can be used for obtaining more insight into the conditions needed for formation of low-relief surfaces at high elevation. Anderson, R. S. Modeling the tor-dotted crests, bedrock edges, and parabolic profiles of high alpine surfaces of the Wind River Range, Wyoming. Geomorphology, 46, 35...

  15. CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole

    2010-01-01

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.......0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models.......3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is...

  16. Complex motion in nonlinear-map model of elevators in energy-saving traffic

    International Nuclear Information System (INIS)

    Nagatani, Takashi

    2011-01-01

    We have studied the dynamic behavior and dynamic transitions of elevators in a system for reducing energy consumption. We present a nonlinear-map model for the dynamics of M elevators. The motion of elevators depends on the loading parameter and their number M. The dependence of the fixed points on the loading parameter is derived. The dynamic transitions occur at 2(M-1) stages with increasing the value of loading parameter. At the dynamic transition point, the motion of elevators changes from a stable state to an unstable state and vice versa. The elevators display periodic motions with various periods in the unstable state. In the unstable state, the number of riding passengers fluctuates in a complex manner over various trips. - Highlights: → We propose the nonlinear-map model in energy-saving traffic of elevators. → We study the dynamical behavior and dynamical transitions in the system of elevators. → We derive the fixed point of the nonlinear map analytically. → We clarify the dependence of the motion on the loading parameter and the number.

  17. Complex motion in nonlinear-map model of elevators in energy-saving traffic

    Energy Technology Data Exchange (ETDEWEB)

    Nagatani, Takashi, E-mail: tmtnaga@ipc.shizuoka.ac.j [Department of Mechanical Engineering, Division of Thermal Science, Shizuoka University, Hamamatsu 432-8561 (Japan)

    2011-05-16

    We have studied the dynamic behavior and dynamic transitions of elevators in a system for reducing energy consumption. We present a nonlinear-map model for the dynamics of M elevators. The motion of elevators depends on the loading parameter and their number M. The dependence of the fixed points on the loading parameter is derived. The dynamic transitions occur at 2(M-1) stages with increasing the value of loading parameter. At the dynamic transition point, the motion of elevators changes from a stable state to an unstable state and vice versa. The elevators display periodic motions with various periods in the unstable state. In the unstable state, the number of riding passengers fluctuates in a complex manner over various trips. - Highlights: We propose the nonlinear-map model in energy-saving traffic of elevators. We study the dynamical behavior and dynamical transitions in the system of elevators. We derive the fixed point of the nonlinear map analytically. We clarify the dependence of the motion on the loading parameter and the number.

  18. Improving maps of ice-sheet surface elevation change using combined laser altimeter and stereoscopic elevation model data

    DEFF Research Database (Denmark)

    Fredenslund Levinsen, Joanna; Howat, I. M.; Tscherning, C. C.

    2013-01-01

    We combine the complementary characteristics of laser altimeter data and stereoscopic digital elevation models (DEMs) to construct high-resolution (_100 m) maps of surface elevations and elevation changes over rapidly changing outlet glaciers in Greenland. Measurements from spaceborne and airborne...... laser altimeters have relatively low errors but are spatially limited to the ground tracks, while DEMs have larger errors but provide spatially continuous surfaces. The principle of our method is to fit the DEM surface to the altimeter point clouds in time and space to minimize the DEM errors and use...... that surface to extrapolate elevations away from altimeter flight lines. This reduces the DEM registration errors and fills the gap between the altimeter paths. We use data from ICESat and ATM as well as SPOT 5 DEMs from 2007 and 2008 and apply them to the outlet glaciers Jakobshavn Isbræ (JI...

  19. Analysis of laser remote fusion cutting based on a mathematical model

    Energy Technology Data Exchange (ETDEWEB)

    Matti, R. S. [Department of Engineering Sciences and Mathematics, Luleå University of Technology, S-971 87 Luleå (Sweden); Department of Mechanical Engineering, College of Engineering, University of Mosul, Mosul (Iraq); Ilar, T.; Kaplan, A. F. H. [Department of Engineering Sciences and Mathematics, Luleå University of Technology, S-971 87 Luleå (Sweden)

    2013-12-21

    Laser remote fusion cutting is analyzed by the aid of a semi-analytical mathematical model of the processing front. By local calculation of the energy balance between the absorbed laser beam and the heat losses, the three-dimensional vaporization front can be calculated. Based on an empirical model for the melt flow field, from a mass balance, the melt film and the melting front can be derived, however only in a simplified manner and for quasi-steady state conditions. Front waviness and multiple reflections are not modelled. The model enables to compare the similarities, differences, and limits between laser remote fusion cutting, laser remote ablation cutting, and even laser keyhole welding. In contrast to the upper part of the vaporization front, the major part only slightly varies with respect to heat flux, laser power density, absorptivity, and angle of front inclination. Statistical analysis shows that for high cutting speed, the domains of high laser power density contribute much more to the formation of the front than for low speed. The semi-analytical modelling approach offers flexibility to simplify part of the process physics while, for example, sophisticated modelling of the complex focused fibre-guided laser beam is taken into account to enable deeper analysis of the beam interaction. Mechanisms like recast layer generation, absorptivity at a wavy processing front, and melt film formation are studied too.

  20. Analysis of laser remote fusion cutting based on a mathematical model

    International Nuclear Information System (INIS)

    Matti, R. S.; Ilar, T.; Kaplan, A. F. H.

    2013-01-01

    Laser remote fusion cutting is analyzed by the aid of a semi-analytical mathematical model of the processing front. By local calculation of the energy balance between the absorbed laser beam and the heat losses, the three-dimensional vaporization front can be calculated. Based on an empirical model for the melt flow field, from a mass balance, the melt film and the melting front can be derived, however only in a simplified manner and for quasi-steady state conditions. Front waviness and multiple reflections are not modelled. The model enables to compare the similarities, differences, and limits between laser remote fusion cutting, laser remote ablation cutting, and even laser keyhole welding. In contrast to the upper part of the vaporization front, the major part only slightly varies with respect to heat flux, laser power density, absorptivity, and angle of front inclination. Statistical analysis shows that for high cutting speed, the domains of high laser power density contribute much more to the formation of the front than for low speed. The semi-analytical modelling approach offers flexibility to simplify part of the process physics while, for example, sophisticated modelling of the complex focused fibre-guided laser beam is taken into account to enable deeper analysis of the beam interaction. Mechanisms like recast layer generation, absorptivity at a wavy processing front, and melt film formation are studied too

  1. LBA-ECO LC-01 SRTM 90-Meter Digital Elevation Model, Northern Ecuadorian Amazon

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set, LBA-ECO LC-01 SRTM 90-Meter Digital Elevation Model, Northern Ecuadorian Amazon, provides 90-meter resolution Digital Elevation Model data used in the...

  2. Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

    Science.gov (United States)

    Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

    2017-12-01

    Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological

  3. Using optical remote sensing model to estimate oil slick thickness based on satellite image

    International Nuclear Information System (INIS)

    Lu, Y C; Tian, Q J; Lyu, C G; Fu, W X; Han, W C

    2014-01-01

    An optical remote sensing model has been established based on two-beam interference theory to estimate marine oil slick thickness. Extinction coefficient and normalized reflectance of oil are two important parts in this model. Extinction coefficient is an important inherent optical property and will not vary with the background reflectance changed. Normalized reflectance can be used to eliminate the background differences between in situ measured spectra and remotely sensing image. Therefore, marine oil slick thickness and area can be estimated and mapped based on optical remotely sensing image and extinction coefficient

  4. Integrating remote sensing and spatially explicit epidemiological modeling

    Science.gov (United States)

    Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

    2015-04-01

    Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

  5. Global multi-resolution terrain elevation data 2010 (GMTED2010)

    Science.gov (United States)

    Danielson, Jeffrey J.; Gesch, Dean B.

    2011-01-01

    In 1996, the U.S. Geological Survey (USGS) developed a global topographic elevation model designated as GTOPO30 at a horizontal resolution of 30 arc-seconds for the entire Earth. Because no single source of topographic information covered the entire land surface, GTOPO30 was derived from eight raster and vector sources that included a substantial amount of U.S. Defense Mapping Agency data. The quality of the elevation data in GTOPO30 varies widely; there are no spatially-referenced metadata, and the major topographic features such as ridgelines and valleys are not well represented. Despite its coarse resolution and limited attributes, GTOPO30 has been widely used for a variety of hydrological, climatological, and geomorphological applications as well as military applications, where a regional, continental, or global scale topographic model is required. These applications have ranged from delineating drainage networks and watersheds to using digital elevation data for the extraction of topographic structure and three-dimensional (3D) visualization exercises (Jenson and Domingue, 1988; Verdin and Greenlee, 1996; Lehner and others, 2008). Many of the fundamental geophysical processes active at the Earth's surface are controlled or strongly influenced by topography, thus the critical need for high-quality terrain data (Gesch, 1994). U.S. Department of Defense requirements for mission planning, geographic registration of remotely sensed imagery, terrain visualization, and map production are similarly dependent on global topographic data. Since the time GTOPO30 was completed, the availability of higher-quality elevation data over large geographic areas has improved markedly. New data sources include global Digital Terrain Elevation Data (DTEDRegistered) from the Shuttle Radar Topography Mission (SRTM), Canadian elevation data, and data from the Ice, Cloud, and land Elevation Satellite (ICESat). Given the widespread use of GTOPO30 and the equivalent 30-arc

  6. Use of remote sensing data in distributed hydrological models: applications in the Senegal River basin

    DEFF Research Database (Denmark)

    Sandholt, Inge; Andersen, Jens Asger; Gybkjær, Gorm

    1999-01-01

    Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she......Earth observation, remote sensing, hydrology, distributed hydrological modelling, West Africa, Senegal river basin, land cover, soil moisture, NOAA AVHRR, SPOT, Mike-she...

  7. Shoreline Erosion and Slope Failure Detection over Southwest Lakeshore Michigan using Temporal Radar and Digital Elevation Model

    Science.gov (United States)

    Sataer, G.; Sultan, M.; Yellich, J. A.; Becker, R.; Emil, M. K.; Palaseanu, M.

    2017-12-01

    Throughout the 20th century and into the 21st century, significant losses of residential, commercial and governmental property were reported along the shores of the Great Lakes region due to one or more of the following factors: high lake levels, wave actions, groundwater discharge. A collaborative effort (Western Michigan University, University of Toledo, Michigan Geological Survey [MGS], United States Geological Survey [USGS], National Oceanographic and Atmospheric Administration [NOAA]) is underway to examine the temporal topographic variations along the shoreline and the adjacent bluff extending from the City of South Haven in the south to the City of Saugatuck in the north within the Allegan County. Our objectives include two main tasks: (1) identification of the timing of, and the areas, witnessing slope failure and shoreline erosion, and (2) investigating the factors causing the observed failures and erosion. This is being accomplished over the study area by: (1) detecting and measuring slope subsidence rates (velocities along line of site) and failures using radar interferometric persistent scatter (PS) techniques applied to ESA's European Remote Sensing (ERS) satellites, ERS-1 and -2 (spatial resolution: 25 m) that were acquired in 1995 to 2007, (2) extracting temporal high resolution (20 cm) digital elevation models (DEM) for the study area from temporal imagery acquired by Unmanned Aerial Vehicles (UAVs), and applying change detection techniques to the extracted DEMs, (3) detecting change in elevation and slope profiles extracted from two LIDAR Coastal National Elevation Database (CoNED) DEMs (spatial resolution: 0.5m), acquired on 2008 and 2012, and (4) spatial and temporal correlation of the detected changes in elevation with relevant data sets (e.g., lake levels, precipitation, groundwater levels) in search of causal effects.

  8. Remote sensing of the Canadian Arctic: Modelling biophysical variables

    Science.gov (United States)

    Liu, Nanfeng

    It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic

  9. On-chip remote charger model using plasmonic island circuit

    Directory of Open Access Journals (Sweden)

    J. Ali

    2018-06-01

    Full Text Available We propose the remote charger model using the light fidelity (LiFi transmission and integrate microring resonator circuit. It consists of the stacked layers of silicon-graphene-gold materials known as a plasmonic island placed at the center of the modified add-drop filter. The input light power from the remote LiFi can enter into the island via a silicon waveguide. The optimized input power is obtained by the coupled micro-lens on the silicon surface. The induced electron mobility generated in the gold layer by the interfacing layer between silicon-graphene. This is the reversed interaction of the whispering gallery mode light power of the microring system, in which the generated power is fed back into the microring circuit. The electron mobility is the required output and obtained at the device ports and characterized for the remote current source applications. The obtained calculation results have shown that the output current of ∼2.5 × 10−11 AW−1, with the gold height of 1.0 µm and the input power of 5.0 W is obtained at the output port, which is shown the potential application for a short range free pace remote charger.

  10. Modelling runoff and glacier melt in the Hunza basin in northern Pakistan using satellite remote sensing techniques

    International Nuclear Information System (INIS)

    Shafiq, M.

    2011-01-01

    The glaciers in western Karakoram are important for freshwater supply in the rivers of Pakistan. Global warming influences the future water supply from glaciers. In order to study the hydrological conditions and possible impacts of climate change, runoff simulations are performed for the Hunza basin. The hydrological modelling system SRM (Snowmelt Runoff Model) is customized and applied to the Hunza basin. Various data obtained from satellite remote sensing imagery and meteorological stations in the study area are processed, prepared and used as input to SRM. For runoff simulations the basin is divided into five sub-basins. The (sub-) basins are defined by the hydrological response units (HRU) based on the elevation zones and land-cover types. The spatially distributed data are aggregated HRU-wise as input for the model simulations. The energy available for snow and glacier melt is parameterized in SRM by degree day factors which are defined separately for seasonal snow, ice and debris covered glaciers. The model is calibrated for the Hunza basin using the meteorological and remote sensing data from years 2002 and 2003. The daily runoff is simulated and compared with the measured discharge data obtained from the power company. The Nash-Sutcliffe correlation coefficient of simulated versus measured runoff data is 0.87 for year 2002 and 0.96 for year 2003 which indicates a good agreement. An estimation of mass balance of Baltoro glacier is made using the meteorological data from Shigar station applying the hydrological method to estimate accumulation and melt. Based on these data is found that Baltoro glacier has slightly negative mass balance. The ablation rates of debris covered parts of Baltoro glacier at 4150 m elevation are estimated to be between 3 and 4 cm per day. However, the uncertainty in mass balance modelling is high due to poor knowledge of accumulation inferred by spatial extrapolation from station data.Keeping the glacier area unchanged, for the 2002

  11. The protective effects of pomegranate on liver and remote organs caused by experimental obstructive jaundice model.

    Science.gov (United States)

    Yilmaz, E E; Arikanoğlu, Z; Turkoğlu, A; Kiliç, E; Yüksel, H; Gümüş, M

    2016-01-01

    We aimed to investigate the protective potential of pomegranate extract on the liver and remote organs in rats with obstructive jaundice. The rats were split into 4 groups. In Group 1 (G1) (sham group) rats, the common bile duct was mobilized without any ligation. Group 2 (G2) received a combination of the sham operation and synchronous treatment with pomegranate. Group 3 (G3) received common bile duct ligation (CBDL). Group 4 (G4) were subjected to CBDL and treatment with pomegranate. After 8 days, we measured total oxidative status (TOS) and antioxidant capacity in the rats' liver tissue and remote organs, and evaluated blood levels of malondialdehyde and total antioxidant capacity (TAC). G3 rats showed significantly raised malondialdehyde level as compared to G1 rats (p pomegranate therapy, a decrease in malondialdehyde was observed (p = 0.015). TAC levels were significantly raised in the G3 rats compared to the G1 rats (p = 0.004). TAC levels dropped after pomegranate therapy (p = 0.011). CBDL caused elevated TOS levels in the liver and remote organs, with a statistically significant increase in the lung tissue (p = 0.002). TOS levels in the CBDL groups decreased after pomegranate treatment (p pomegranate on the liver and remote organs in obstructive jaundice.

  12. Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2

    Data.gov (United States)

    National Aeronautics and Space Administration — The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent...

  13. A material model for aluminium sheet forming at elevated temperatures

    NARCIS (Netherlands)

    van den Boogaard, Antonius H.; Werkhoven, R.J.; Bolt, P.J.

    2001-01-01

    In order to accurately simulate the deep drawing or stretching of aluminum sheet at elevated temperatures, a model is required that incorporates the temperature and strain-rate dependency of the material. In this paper two models are compared: a phenomenological material model in which the

  14. A new bed elevation model for the Weddell Sea sector of the West Antarctic Ice Sheet

    Directory of Open Access Journals (Sweden)

    H. Jeofry

    2018-04-01

    Full Text Available We present a new digital elevation model (DEM of the bed, with a 1 km gridding, of the Weddell Sea (WS sector of the West Antarctic Ice Sheet (WAIS. The DEM has a total area of ∼ 125 000 km2 covering the Institute, Möller and Foundation ice streams, as well as the Bungenstock ice rise. In comparison with the Bedmap2 product, our DEM includes new aerogeophysical datasets acquired by the Center for Remote Sensing of Ice Sheets (CReSIS through the NASA Operation IceBridge (OIB program in 2012, 2014 and 2016. We also improve bed elevation information from the single largest existing dataset in the region, collected by the British Antarctic Survey (BAS Polarimetric radar Airborne Science Instrument (PASIN in 2010–2011, from the relatively crude measurements determined in the field for quality control purposes used in Bedmap2. While the gross form of the new DEM is similar to Bedmap2, there are some notable differences. For example, the position and size of a deep subglacial trough (∼ 2 km below sea level between the ice-sheet interior and the grounding line of the Foundation Ice Stream have been redefined. From the revised DEM, we are able to better derive the expected routing of basal water and, by comparison with that calculated using Bedmap2, we are able to assess regions where hydraulic flow is sensitive to change. Given the potential vulnerability of this sector to ocean-induced melting at the grounding line, especially in light of the improved definition of the Foundation Ice Stream trough, our revised DEM will be of value to ice-sheet modelling in efforts to quantify future glaciological changes in the region and, from this, the potential impact on global sea level. The new 1 km bed elevation product of the WS sector can be found at https://doi.org/10.5281/zenodo.1035488.

  15. A new bed elevation model for the Weddell Sea sector of the West Antarctic Ice Sheet

    Science.gov (United States)

    Jeofry, Hafeez; Ross, Neil; Corr, Hugh F. J.; Li, Jilu; Morlighem, Mathieu; Gogineni, Prasad; Siegert, Martin J.

    2018-04-01

    We present a new digital elevation model (DEM) of the bed, with a 1 km gridding, of the Weddell Sea (WS) sector of the West Antarctic Ice Sheet (WAIS). The DEM has a total area of ˜ 125 000 km2 covering the Institute, Möller and Foundation ice streams, as well as the Bungenstock ice rise. In comparison with the Bedmap2 product, our DEM includes new aerogeophysical datasets acquired by the Center for Remote Sensing of Ice Sheets (CReSIS) through the NASA Operation IceBridge (OIB) program in 2012, 2014 and 2016. We also improve bed elevation information from the single largest existing dataset in the region, collected by the British Antarctic Survey (BAS) Polarimetric radar Airborne Science Instrument (PASIN) in 2010-2011, from the relatively crude measurements determined in the field for quality control purposes used in Bedmap2. While the gross form of the new DEM is similar to Bedmap2, there are some notable differences. For example, the position and size of a deep subglacial trough (˜ 2 km below sea level) between the ice-sheet interior and the grounding line of the Foundation Ice Stream have been redefined. From the revised DEM, we are able to better derive the expected routing of basal water and, by comparison with that calculated using Bedmap2, we are able to assess regions where hydraulic flow is sensitive to change. Given the potential vulnerability of this sector to ocean-induced melting at the grounding line, especially in light of the improved definition of the Foundation Ice Stream trough, our revised DEM will be of value to ice-sheet modelling in efforts to quantify future glaciological changes in the region and, from this, the potential impact on global sea level. The new 1 km bed elevation product of the WS sector can be found at https://doi.org/10.5281/zenodo.1035488" target="_blank">https://doi.org/10.5281/zenodo.1035488.

  16. Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

    Science.gov (United States)

    Mendiguren, Gorka; Koch, Julian; Stisen, Simon

    2017-11-01

    Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

  17. Modeling Remote I/O versus Staging Tradeoff in Multi-Data Center Computing

    International Nuclear Information System (INIS)

    Suslu, Ibrahim H

    2014-01-01

    In multi-data center computing, data to be processed is not always local to the computation. This is a major challenge especially for data-intensive Cloud computing applications, since large amount of data would need to be either moved the local sites (staging) or accessed remotely over the network (remote I/O). Cloud application developers generally chose between staging and remote I/O intuitively without making any scientific comparison specific to their application data access patterns since there is no generic model available that they can use. In this paper, we propose a generic model for the Cloud application developers which would help them to choose the most appropriate data access mechanism for their specific application workloads. We define the parameters that potentially affect the end-to-end performance of the multi-data center Cloud applications which need to access large datasets over the network. To test and validate our models, we implemented a series of synthetic benchmark applications to simulate the most common data access patterns encountered in Cloud applications. We show that our model provides promising results in different settings with different parameters, such as network bandwidth, server and client capabilities, and data access ratio

  18. Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

    Science.gov (United States)

    Yueh, Simon H.

    2004-01-01

    Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

  19. Improvements in irrigation system modelling when using remotely sensed ET for calibration

    Science.gov (United States)

    van Opstal, J. D.; Neale, C. M. U.; Lecina, S.

    2014-10-01

    Irrigation system modelling is often used to aid decision-makers in the agricultural sector. It gives insight on the consequences of potential management and infrastructure changes. However, simulating an irrigation district requires a considerable amount of input data to properly represent the system, which is not easily acquired or available. During the simulation process, several assumptions have to be made and the calibration is usually performed only with flow measurements. The advancement of estimating evapotranspiration (ET) using remote sensing is a welcome asset for irrigation system modelling. Remotely-sensed ET can be used to improve the model accuracy in simulating the water balance and the crop production. This study makes use of the Ador-Simulation irrigation system model, which simulates water flows in irrigation districts in both the canal infrastructure and on-field. ET is estimated using an energy balance model, namely SEBAL, which has been proven to function well for agricultural areas. The seasonal ET by the Ador model and the ET from SEBAL are compared. These results determine sub-command areas, which perform well under current assumptions or, conversely, areas that need re-evaluation of assumptions and a re-run of the model. Using a combined approach of the Ador irrigation system model and remote sensing outputs from SEBAL, gives great insights during the modelling process and can accelerate the process. Additionally cost-savings and time-savings are apparent due to the decrease in input data required for simulating large-scale irrigation areas.

  20. Easter Island, Chile Digital Elevation Model 3 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Automated identification of potential snow avalanche release areas based on digital elevation models

    Directory of Open Access Journals (Sweden)

    Y. Bühler

    2013-05-01

    Full Text Available The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.

  2. Automated identification of potential snow avalanche release areas based on digital elevation models

    Science.gov (United States)

    Bühler, Y.; Kumar, S.; Veitinger, J.; Christen, M.; Stoffel, A.; Snehmani

    2013-05-01

    The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.

  3. Comparison between remote sensing and a dynamic vegetation model for estimating terrestrial primary production of Africa.

    Science.gov (United States)

    Ardö, Jonas

    2015-12-01

    Africa is an important part of the global carbon cycle. It is also a continent facing potential problems due to increasing resource demand in combination with climate change-induced changes in resource supply. Quantifying the pools and fluxes constituting the terrestrial African carbon cycle is a challenge, because of uncertainties in meteorological driver data, lack of validation data, and potentially uncertain representation of important processes in major ecosystems. In this paper, terrestrial primary production estimates derived from remote sensing and a dynamic vegetation model are compared and quantified for major African land cover types. Continental gross primary production estimates derived from remote sensing were higher than corresponding estimates derived from a dynamic vegetation model. However, estimates of continental net primary production from remote sensing were lower than corresponding estimates from the dynamic vegetation model. Variation was found among land cover classes, and the largest differences in gross primary production were found in the evergreen broadleaf forest. Average carbon use efficiency (NPP/GPP) was 0.58 for the vegetation model and 0.46 for the remote sensing method. Validation versus in situ data of aboveground net primary production revealed significant positive relationships for both methods. A combination of the remote sensing method with the dynamic vegetation model did not strongly affect this relationship. Observed significant differences in estimated vegetation productivity may have several causes, including model design and temperature sensitivity. Differences in carbon use efficiency reflect underlying model assumptions. Integrating the realistic process representation of dynamic vegetation models with the high resolution observational strength of remote sensing may support realistic estimation of components of the carbon cycle and enhance resource monitoring, providing suitable validation data is available.

  4. Chignik, Alaska 1 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  5. Akutan, Alaska 8 Arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  6. Remote programming of cochlear implants: a telecommunications model.

    Science.gov (United States)

    McElveen, John T; Blackburn, Erin L; Green, J Douglas; McLear, Patrick W; Thimsen, Donald J; Wilson, Blake S

    2010-09-01

    Evaluate the effectiveness of remote programming for cochlear implants. Retrospective review of the cochlear implant performance for patients who had undergone mapping and programming of their cochlear implant via remote connection through the Internet. Postoperative Hearing in Noise Test and Consonant/Nucleus/Consonant word scores for 7 patients who had undergone remote mapping and programming of their cochlear implant were compared with the mean scores of 7 patients who had been programmed by the same audiologist over a 12-month period. Times required for remote and direct programming were also compared. The quality of the Internet connection was assessed using standardized measures. Remote programming was performed via a virtual private network with a separate software program used for video and audio linkage. All 7 patients were programmed successfully via remote connectivity. No untoward patient experiences were encountered. No statistically significant differences could be found in comparing postoperative Hearing in Noise Test and Consonant/Nucleus/Consonant word scores for patients who had undergone remote programming versus a similar group of patients who had their cochlear implant programmed directly. Remote programming did not require a significantly longer programming time for the audiologist with these 7 patients. Remote programming of a cochlear implant can be performed safely without any deterioration in the quality of the programming. This ability to remotely program cochlear implant patients gives the potential to extend cochlear implantation to underserved areas in the United States and elsewhere.

  7. Digital elevation models for site investigation programme in Oskarshamn. Site description version 1.2

    International Nuclear Information System (INIS)

    Brydsten, Lars; Stroemgren, Maarten

    2005-06-01

    In the Oskarshamn area, a digital elevation model has been produced using elevation data from many elevation sources on both land and sea. Many elevation model users are only interested in elevation models over land, so the model has been designed in three versions: Version 1 describes land surface, lake water surface, and sea bottom. Version 2 describes land surface, sediment levels at lake bottoms, and sea bottoms. Version 3 describes land surface, sediment levels at lake bottoms, and sea surface. In cases where the different sources of data were not in point form 'such as existing elevation models of land or depth lines from nautical charts' they have been converted to point values using GIS software. Because data from some sources often overlaps with data from other sources, several tests were conducted to determine if both sources of data or only one source would be included in the dataset used for the interpolation procedure. The tests resulted in the decision to use only the source judged to be of highest quality for most areas with overlapping data sources. All data were combined into a database of approximately 3.3 million points unevenly spread over an area of about 800 km 2 . The large number of data points made it difficult to construct the model with a single interpolation procedure, the area was divided into 28 sub-models that were processed one by one and finally merged together into one single model. The software ArcGis 8.3 and its extension Geostatistical Analysis were used for the interpolation. The Ordinary Kriging method was used for interpolation. This method allows both a cross validation and a validation before the interpolation is conducted. Cross validation with different Kriging parameters were performed and the model with the most reasonable statistics was chosen. Finally, a validation with the most appropriate Kriging parameters was performed in order to verify that the model fit unmeasured localities. Since both the quality and the

  8. Assessing uncertainty in SRTM elevations for global flood modelling

    Science.gov (United States)

    Hawker, L. P.; Rougier, J.; Neal, J. C.; Bates, P. D.

    2017-12-01

    The SRTM DEM is widely used as the topography input to flood models in data-sparse locations. Understanding spatial error in the SRTM product is crucial in constraining uncertainty about elevations and assessing the impact of these upon flood prediction. Assessment of SRTM error was carried out by Rodriguez et al (2006), but this did not explicitly quantify the spatial structure of vertical errors in the DEM, and nor did it distinguish between errors over different types of landscape. As a result, there is a lack of information about spatial structure of vertical errors of the SRTM in the landscape that matters most to flood models - the floodplain. Therefore, this study attempts this task by comparing SRTM, an error corrected SRTM product (The MERIT DEM of Yamazaki et al., 2017) and near truth LIDAR elevations for 3 deltaic floodplains (Mississippi, Po, Wax Lake) and a large lowland region (the Fens, UK). Using the error covariance function, calculated by comparing SRTM elevations to the near truth LIDAR, perturbations of the 90m SRTM DEM were generated, producing a catalogue of plausible DEMs. This allows modellers to simulate a suite of plausible DEMs at any aggregated block size above native SRTM resolution. Finally, the generated DEM's were input into a hydrodynamic model of the Mekong Delta, built using the LISFLOOD-FP hydrodynamic model, to assess how DEM error affects the hydrodynamics and inundation extent across the domain. The end product of this is an inundation map with the probability of each pixel being flooded based on the catalogue of DEMs. In a world of increasing computer power, but a lack of detailed datasets, this powerful approach can be used throughout natural hazard modelling to understand how errors in the SRTM DEM can impact the hazard assessment.

  9. Comparison of digital elevation models for aquatic data development.

    Science.gov (United States)

    Sharon Clarke; Kelly. Burnett

    2003-01-01

    Thirty-meter digital elevation models (DEMs) produced by the U.S. Geological Survey (USGS) are widely available and commonly used in analyzing aquatic systems. However, these DEMs are of relatively coarse resolution, were inconsistently produced (i.e., Level 1 versus Level 2 DEMs), and lack drainage enforcement. Such issues may hamper efforts to accurately model...

  10. Mobile, Alabama 1/3 MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  11. Advancements in Modelling of Land Surface Energy Fluxes with Remote Sensing at Different Spatial Scales

    DEFF Research Database (Denmark)

    Guzinski, Radoslaw

    uxes, such as sensible heat ux, ground heat ux and net radiation, are also necessary. While it is possible to measure those uxes with ground-based instruments at local scales, at region scales they usually need to be modelled or estimated with the help of satellite remote sensing data. Even though...... to increase the spatial resolution of the reliable DTD-modelled fluxes from 1 km to 30 m. Furthermore, synergies between remote sensing based models and distributed hydrological models were studied with the aim of improving spatial performance of the hydrological models through incorporation of remote sensing...... of this study was to look at, and improve, various approaches for modelling the land-surface energy uxes at different spatial scales. The work was done using physically-based Two-Source Energy Balance (TSEB) approach as well as semi-empirical \\Triangle" approach. The TSEB-based approach was the main focus...

  12. Effects of Remote Ischemic Conditioning Methods on Ischemia-Reperfusion Injury in Muscle Flaps: An Experimental Study in Rats

    Directory of Open Access Journals (Sweden)

    Durdane Keskin

    2017-09-01

    Full Text Available Background The aim of this study was to investigate the effects of remote ischemic conditioning on ischemia-reperfusion injury in rat muscle flaps histopathologically and biochemically. Methods Thirty albino rats were divided into 5 groups. No procedure was performed in the rats in group 1, and only blood samples were taken. A gracilis muscle flap was elevated in all the other groups. Microclamps were applied to the vascular pedicle for 4 hours in order to achieve tissue ischemia. In group 2, no additional procedure was performed. In groups 3, 4, and 5, the right hind limb was used and 3 cycles of ischemia-reperfusion for 5 minutes each (total, 30 minutes was applied with a latex tourniquet (remote ischemic conditioning. In group 3, this procedure was performed before flap elevation (remote ischemic preconditoning. In group 4, the procedure was performed 4 hours after flap ischemia (remote ischemic postconditioning. In group 5, the procedure was performed after the flap was elevated, during the muscle flap ischemia episode (remote ischemic perconditioning. Results The histopathological damage score in all remote conditioning ischemia groups was lower than in the ischemic-reperfusion group. The lowest histopathological damage score was observed in group 5 (remote ischemic perconditioning. Conclusions The nitric oxide levels were higher in the blood samples obtained from the remote ischemic perconditioning group. This study showed the effectiveness of remote ischemic conditioning procedures and compared their usefulness for preventing ischemia-reperfusion injury in muscle flaps.

  13. Effects of Remote Ischemic Conditioning Methods on Ischemia-Reperfusion Injury in Muscle Flaps: An Experimental Study in Rats.

    Science.gov (United States)

    Keskin, Durdane; Unlu, Ramazan Erkin; Orhan, Erkan; Erkilinç, Gamze; Bogdaycioglu, Nihal; Yilmaz, Fatma Meric

    2017-09-01

    The aim of this study was to investigate the effects of remote ischemic conditioning on ischemia-reperfusion injury in rat muscle flaps histopathologically and biochemically. Thirty albino rats were divided into 5 groups. No procedure was performed in the rats in group 1, and only blood samples were taken. A gracilis muscle flap was elevated in all the other groups. Microclamps were applied to the vascular pedicle for 4 hours in order to achieve tissue ischemia. In group 2, no additional procedure was performed. In groups 3, 4, and 5, the right hind limb was used and 3 cycles of ischemia-reperfusion for 5 minutes each (total, 30 minutes) was applied with a latex tourniquet (remote ischemic conditioning). In group 3, this procedure was performed before flap elevation (remote ischemic preconditoning). In group 4, the procedure was performed 4 hours after flap ischemia (remote ischemic postconditioning). In group 5, the procedure was performed after the flap was elevated, during the muscle flap ischemia episode (remote ischemic perconditioning). The histopathological damage score in all remote conditioning ischemia groups was lower than in the ischemic-reperfusion group. The lowest histopathological damage score was observed in group 5 (remote ischemic perconditioning). The nitric oxide levels were higher in the blood samples obtained from the remote ischemic perconditioning group. This study showed the effectiveness of remote ischemic conditioning procedures and compared their usefulness for preventing ischemia-reperfusion injury in muscle flaps.

  14. A Global Remote Laboratory Experimentation Network and the Experiment Service Provider Business Model and Plans

    Directory of Open Access Journals (Sweden)

    Tor Ivar Eikaas

    2003-07-01

    Full Text Available This paper presents results from the IST KAII Trial project ReLAX - Remote LAboratory eXperimentation trial (IST 1999-20827, and contributes with a framework for a global remote laboratory experimentation network supported by a new business model. The paper presents this new Experiment Service Provider business model that aims at bringing physical experimentation back into the learning arena, where remotely operable laboratory experiments used in advanced education and training schemes are made available to a global education and training market in industry and academia. The business model is based on an approach where individual experiment owners offer remote access to their high-quality laboratory facilities to users around the world. The usage can be for research, education, on-the-job training etc. The access to these facilities is offered via an independent operating company - the Experiment Service Provider. The Experiment Service Provider offers eCommerce services like booking, access control, invoicing, dispute resolution, quality control, customer evaluation services and a unified Lab Portal.

  15. Microwave propagation and remote sensing atmospheric influences with models and applications

    CERN Document Server

    Karmakar, Pranab Kumar

    2011-01-01

    Because prevailing atmospheric/troposcopic conditions greatly influence radio wave propagation above 10 GHz, the unguided propagation of microwaves in the neutral atmosphere can directly impact many vital applications in science and engineering. These include transmission of intelligence, and radar and radiometric applications used to probe the atmosphere, among others. Where most books address either one or the other, Microwave Propagation and Remote Sensing: Atmospheric Influences with Models and Applications melds coverage of these two subjects to help readers develop solutions to the problems they present. This reference offers a brief, elementary account of microwave propagation through the atmosphere and discusses radiometric applications in the microwave band used to characterize and model atmospheric constituents, which is also known as remote sensing. Summarizing the latest research results in the field, as well as radiometric models and measurement methods, this book covers topics including: Free sp...

  16. Integration of Remote Sensing Data In Operational Flood Forecast In Southwest Germany

    Science.gov (United States)

    Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.

    Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the

  17. Creating high-resolution digital elevation model using thin plate spline interpolation and Monte Carlo simulation

    International Nuclear Information System (INIS)

    Pohjola, J.; Turunen, J.; Lipping, T.

    2009-07-01

    In this report creation of the digital elevation model of Olkiluoto area incorporating a large area of seabed is described. The modeled area covers 960 square kilometers and the apparent resolution of the created elevation model was specified to be 2.5 x 2.5 meters. Various elevation data like contour lines and irregular elevation measurements were used as source data in the process. The precision and reliability of the available source data varied largely. Digital elevation model (DEM) comprises a representation of the elevation of the surface of the earth in particular area in digital format. DEM is an essential component of geographic information systems designed for the analysis and visualization of the location-related data. DEM is most often represented either in raster or Triangulated Irregular Network (TIN) format. After testing several methods the thin plate spline interpolation was found to be best suited for the creation of the elevation model. The thin plate spline method gave the smallest error in the test where certain amount of points was removed from the data and the resulting model looked most natural. In addition to the elevation data the confidence interval at each point of the new model was required. The Monte Carlo simulation method was selected for this purpose. The source data points were assigned probability distributions according to what was known about their measurement procedure and from these distributions 1 000 (20 000 in the first version) values were drawn for each data point. Each point of the newly created DEM had thus as many realizations. The resulting high resolution DEM will be used in modeling the effects of land uplift and evolution of the landscape in the time range of 10 000 years from the present. This time range comes from the requirements set for the spent nuclear fuel repository site. (orig.)

  18. Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

    Science.gov (United States)

    Dong, Chunyu

    2018-06-01

    Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

  19. The space station tethered elevator system

    Science.gov (United States)

    Anderson, Loren A.

    1989-01-01

    The optimized conceptual engineering design of a space station tethered elevator is presented. The elevator is an unmanned mobile structure which operates on a ten kilometer tether spanning the distance between the Space Station and a tethered platform. Elevator capabilities include providing access to residual gravity levels, remote servicing, and transportation to any point along a tether. The potential uses, parameters, and evolution of the spacecraft design are discussed. Engineering development of the tethered elevator is the result of work conducted in the following areas: structural configurations; robotics, drive mechanisms; and power generation and transmission systems. The structural configuration of the elevator is presented. The structure supports, houses, and protects all systems on board the elevator. The implementation of robotics on board the elevator is discussed. Elevator robotics allow for the deployment, retrieval, and manipulation of tethered objects. Robotic manipulators also aid in hooking the elevator on a tether. Critical to the operation of the tethered elevator is the design of its drive mechanisms, which are discussed. Two drivers, located internal to the elevator, propel the vehicle along a tether. These modular components consist of endless toothed belts, shunt-wound motors, regenerative power braking, and computer controlled linear actuators. The designs of self-sufficient power generation and transmission systems are reviewed. Thorough research indicates all components of the elevator will operate under power provided by fuel cells. The fuel cell systems will power the vehicle at seven kilowatts continuously and twelve kilowatts maximally. A set of secondary fuel cells provides redundancy in the unlikely event of a primary system failure. Power storage exists in the form of Nickel-Hydrogen batteries capable of powering the elevator under maximum loads.

  20. A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

    Science.gov (United States)

    Gleason, Colin J.; Wada, Yoshihide; Wang, Jida

    2018-01-01

    Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1-2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

  1. Remote Sensing of Cryosphere: Estimation of Mass Balance Change in Himalayan Glaciers

    Science.gov (United States)

    Ambinakudige, Shrinidhi; Joshi, Kabindra

    2012-07-01

    Glacial changes are an important indicator of climate change. Our understanding mass balance change in Himalayan glaciers is limited. This study estimates mass balance of some major glaciers in the Sagarmatha National Park (SNP) in Nepal using remote sensing applications. Remote sensing technique to measure mass balance of glaciers is an important methodological advance in the highly rugged Himalayan terrain. This study uses ASTER VNIR, 3N (nadir view) and 3B (backward view) bands to generate Digital Elevation Models (DEMs) for the SNP area for the years 2002, 2003, 2004 and 2005. Glacier boundaries were delineated using combination of boundaries available in the Global land ice measurement (GLIMS) database and various band ratios derived from ASTER images. Elevation differences, glacial area, and ice densities were used to estimate the change in mass balance. The results indicated that the rate of glacier mass balance change was not uniform across glaciers. While there was a decrease in mass balance of some glaciers, some showed increase. This paper discusses how each glacier in the SNP area varied in its annual mass balance measurement during the study period.

  2. Digital elevation models for site investigation programme in Oskarshamn. Site description version 1.2

    Energy Technology Data Exchange (ETDEWEB)

    Brydsten, Lars; Stroemgren, Maarten [Umeaa Univ. (Sweden). Dept. of Biology and Environmental Science

    2005-06-01

    In the Oskarshamn area, a digital elevation model has been produced using elevation data from many elevation sources on both land and sea. Many elevation model users are only interested in elevation models over land, so the model has been designed in three versions: Version 1 describes land surface, lake water surface, and sea bottom. Version 2 describes land surface, sediment levels at lake bottoms, and sea bottoms. Version 3 describes land surface, sediment levels at lake bottoms, and sea surface. In cases where the different sources of data were not in point form 'such as existing elevation models of land or depth lines from nautical charts' they have been converted to point values using GIS software. Because data from some sources often overlaps with data from other sources, several tests were conducted to determine if both sources of data or only one source would be included in the dataset used for the interpolation procedure. The tests resulted in the decision to use only the source judged to be of highest quality for most areas with overlapping data sources. All data were combined into a database of approximately 3.3 million points unevenly spread over an area of about 800 km{sup 2}. The large number of data points made it difficult to construct the model with a single interpolation procedure, the area was divided into 28 sub-models that were processed one by one and finally merged together into one single model. The software ArcGis 8.3 and its extension Geostatistical Analysis were used for the interpolation. The Ordinary Kriging method was used for interpolation. This method allows both a cross validation and a validation before the interpolation is conducted. Cross validation with different Kriging parameters were performed and the model with the most reasonable statistics was chosen. Finally, a validation with the most appropriate Kriging parameters was performed in order to verify that the model fit unmeasured localities. Since both the

  3. Remote RemoteRemoteRemote sensing potential for sensing ...

    African Journals Online (AJOL)

    Remote RemoteRemoteRemote sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing potential for sensing p. A Ngie, F Ahmed, K Abutaleb ...

  4. The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

    Science.gov (United States)

    Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

    2014-08-01

    Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

  5. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  6. Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

    Science.gov (United States)

    Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

    2013-01-01

    In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

  7. Elevated temperature alters carbon cycling in a model microbial community

    Science.gov (United States)

    Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

    2013-12-01

    Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other

  8. Modeling Elevation Equilibrium and Human Adaptation in the Ganges-Brahmaputra Delta

    Science.gov (United States)

    Tasich, C. M.; Gilligan, J. M.; Goodbred, S. L., Jr.; Hale, R. P.; Wilson, C.

    2017-12-01

    The communities living in the low-lying tidal reaches of the Ganges-Brahmaputra delta rely on a system of polders (earthen-embanked landscapes) to prevent against tidal inundation and storm surge. These communities initially thrived as a result of poldering due to the increase in the total arable land, which presently helps sustain a population of 20 million people. However, poldering led to the unintended consequence of reducing water and sediment exchange between the polders and the tidal network, which has resulted in a significant elevation offset of 1-1.5 m relative to that of the natural landscape. This offset causes significant waterlogging which is problematic for rice cultivation. Engineering solutions, such as Tidal River Management (TRM), have been proposed to help alleviate this offset. Previous work suggests with proper implementation of TRM, polder elevations can successfully be reequilibrated to that of the natural elevation on timescales of 5-20 years. However, TRM implementation requires community commitment to allowing controlled tidal inundation. Here, we expand previous numerical simulations of sediment accumulation through field-based constraints of grain size, compaction, and sea level rise. We then model human decision-making for implementation of TRM practices using an agent-based model. Our sediment model employs a mass balance of sediment accumulation as a function of tidal height, suspended sediment concentration, settling velocity, and dry bulk density. We couple this sediment model to an agent-based model of human decision making. We model a hypothetical 500 x 300 m polder community with the lowest elevations in the middle and the highest elevations adjacent to the tidal channels. Landowners assess their risk and profit for future scenarios with and without TRM. All landowner decisions are aggregated and then a community decision is made on whether to implement TRM. Initial findings suggest that basic voting (majority rule) results in

  9. Modelling groundwater discharge areas using only digital elevation models as input data

    International Nuclear Information System (INIS)

    Brydsten, Lars

    2006-10-01

    Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the

  10. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling

    Science.gov (United States)

    Dorigo, W. A.; Zurita-Milla, R.; de Wit, A. J. W.; Brazile, J.; Singh, R.; Schaepman, M. E.

    2007-05-01

    During the last 50 years, the management of agroecosystems has been undergoing major changes to meet the growing demand for food, timber, fibre and fuel. As a result of this intensified use, the ecological status of many agroecosystems has been severely deteriorated. Modeling the behavior of agroecosystems is, therefore, of great help since it allows the definition of management strategies that maximize (crop) production while minimizing the environmental impacts. Remote sensing can support such modeling by offering information on the spatial and temporal variation of important canopy state variables which would be very difficult to obtain otherwise. In this paper, we present an overview of different methods that can be used to derive biophysical and biochemical canopy state variables from optical remote sensing data in the VNIR-SWIR regions. The overview is based on an extensive literature review where both statistical-empirical and physically based methods are discussed. Subsequently, the prevailing techniques of assimilating remote sensing data into agroecosystem models are outlined. The increasing complexity of data assimilation methods and of models describing agroecosystem functioning has significantly increased computational demands. For this reason, we include a short section on the potential of parallel processing to deal with the complex and computationally intensive algorithms described in the preceding sections. The studied literature reveals that many valuable techniques have been developed both for the retrieval of canopy state variables from reflective remote sensing data as for assimilating the retrieved variables in agroecosystem models. However, for agroecosystem modeling and remote sensing data assimilation to be commonly employed on a global operational basis, emphasis will have to be put on bridging the mismatch between data availability and accuracy on one hand, and model and user requirements on the other. This could be achieved by

  11. Complex motion in nonlinear-map model of elevators in energy-saving traffic

    Science.gov (United States)

    Nagatani, Takashi

    2011-05-01

    We have studied the dynamic behavior and dynamic transitions of elevators in a system for reducing energy consumption. We present a nonlinear-map model for the dynamics of M elevators. The motion of elevators depends on the loading parameter and their number M. The dependence of the fixed points on the loading parameter is derived. The dynamic transitions occur at 2(M-1) stages with increasing the value of loading parameter. At the dynamic transition point, the motion of elevators changes from a stable state to an unstable state and vice versa. The elevators display periodic motions with various periods in the unstable state. In the unstable state, the number of riding passengers fluctuates in a complex manner over various trips.

  12. Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

    Science.gov (United States)

    Ben-David, Avishai; Davidson, Charles E

    2012-04-23

    A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

  13. Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

    Science.gov (United States)

    Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

    2013-01-01

    Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra

  14. Remotely Sensed Based Lake/Reservoir Routing in Congo River Basin

    Science.gov (United States)

    Raoufi, R.; Beighley, E.; Lee, H.

    2017-12-01

    Lake and reservoir dynamics can influence local to regional water cycles but are often not well represented in hydrologic models. One challenge that limits their inclusion in models is the need for detailed storage-discharge behavior that can be further complicated in reservoirs where specific operation rules are employed. Here, the Hillslope River Routing (HRR) model is combined with a remotely sensed based Reservoir Routing (RR) method and applied to the Congo River Basin. Given that topographic data are often continuous over the entire terrestrial surface (i.e., does not differentiate between land and open water), the HRR-RR model integrates topographic derived river networks and catchment boundaries (e.g., HydroSHEDs) with water boundary extents (e.g., Global Lakes and Wetlands Database) to develop the computational framework. The catchments bordering lakes and reservoirs are partitioned into water and land portions, where representative flowpath characteristics are determined and vertical water balance and lateral routings is performed separately on each partition based on applicable process models (e.g., open water evaporation vs. evapotranspiration). To enable reservoir routing, remotely sensed water surface elevations and extents are combined to determine the storage change time series. Based on the available time series, representative storage change patterns are determined. Lake/reservoir routing is performed by combining inflows from the HRR-RR model and the representative storage change patterns to determine outflows. In this study, a suite of storage change patterns derived from remotely sensed measurements are determined representative patterns for wet, dry and average conditions. The HRR-RR model dynamically selects and uses the optimal storage change pattern for the routing process based on these hydrologic conditions. The HRR-RR model results are presented to highlight the importance of lake attenuation/routing in the Congo Basin.

  15. Visible-infrared remote-sensing model and applications for ocean waters. Ph.D. Thesis

    Science.gov (United States)

    Lee, Zhongping

    1994-01-01

    Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape

  16. [Hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status].

    Science.gov (United States)

    Tan, Chang-Wei; Zhou, Qing-Bo; Qi, La; Zhuang, Heng-Yang

    2008-06-01

    The correlations of rice plant nitrogen content with raw hyperspectral reflectance, first derivative hyperspectral reflectance, and hyperspectral characteristic parameters were analyzed, and the hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status with these remote sensing parameters as independent variables were constructed and validated. The results indicated that the nitrogen content in rice plant organs had a variation trend of stem plant nitrogen nutritional status, with the decisive coefficients (R2) being 0.7996 and 0.8606, respectively; while the model with vegetation index (SDr - SDb) / (SDr + SDb) as independent variable, i. e., y = 365.871 + 639.323 ((SDr - SDb) / (SDr + SDb)), was most fit rice plant nitrogen content, with R2 = 0.8755, RMSE = 0.2372 and relative error = 11.36%, being able to quantitatively diagnose the nitrogen nutritional status of rice.

  17. An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

    Directory of Open Access Journals (Sweden)

    Chuli Hu

    2014-01-01

    Full Text Available In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.

  18. CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

    Science.gov (United States)

    Nielsen, Morten; Lundegaard, Claus; Lund, Ole; Petersen, Thomas Nordahl

    2010-07-01

    CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

  19. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  20. St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Wake Island 3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. Barkley Sound, Canada 1 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Miami 1/3 arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Midway Atoll 3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Society Islands, French Polynesia Digital Elevation Model - 3 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Sitka, Alaska 3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Kodiak, Alaska 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Central California 1 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

    Science.gov (United States)

    Qiu, Guo Yu; Zhao, Ming

    2010-03-01

    Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

  10. Akutan, Alaska 8/3 Arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  11. Nikolski, Alaska 1 arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  12. Yakutat, Alaska 8 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  13. King Cove, Alaska 8 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  14. Akutan, Alaska 8/15 Arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  15. Chiniak, Alaska 8/15 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  16. Cold Bay, Alaska 8 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  17. Chignik, Alaska 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  18. Extraction and representation of nested catchment areas from digital elevation models in lake-dominated topography

    Science.gov (United States)

    Mackay, D. Scott; Band, Lawrence E.

    1998-04-01

    This paper presents a new method for extracting flow directions, contributing (upslope) areas, and nested catchments from digital elevation models in lake-dominated areas. Existing tools for acquiring descriptive variables of the topography, such as surface flow directions and contributing areas, were developed for moderate to steep topography. These tools are typically difficult to apply in gentle topography owing to limitations in explicitly handling lakes and other flat areas. This paper addresses the problem of accurately representing general topographic features by first identifying distinguishing features, such as lakes, in gentle topography areas and then using these features to guide the search for topographic flow directions and catchment marking. Lakes are explicitly represented in the topology of a watershed for use in water routing. Nonlake flat features help guide the search for topographic flow directions in areas of low signal to noise. This combined feature-based and grid-based search for topographic features yields improved contributing areas and watershed boundaries where there are lakes and other flat areas. Lakes are easily classified from remotely sensed imagery, which makes automated representation of lakes as subsystems within a watershed system tractable with widely available data sets.

  19. 1 Arc-second Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This is a tiled collection of the 3D Elevation Program (3DEP) and is 1 arc-second (approximately 30 m) resolution.The elevations in this Digital Elevation Model...

  20. Derivation of groundwater flow-paths based on semi-automatic extraction of lineaments from remote sensing data

    OpenAIRE

    U. Mallast; R. Gloaguen; S. Geyer; T. Rödiger; C. Siebert

    2011-01-01

    In this paper we present a semi-automatic method to infer groundwater flow-paths based on the extraction of lineaments from digital elevation models. This method is especially adequate in remote and inaccessible areas where in-situ data are scarce. The combined method of linear filtering and object-based classification provides a lineament map with a high degree of accuracy. Subsequently, lineaments are differentiated into geological and morphological lineaments using auxili...

  1. Northern Gulf 1 Arc-second MHW Coast Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  2. Mobile, Alabama 1/3 NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  3. Modeling Global Urbanization Supported by Nighttime Light Remote Sensing

    Science.gov (United States)

    Zhou, Y.

    2015-12-01

    Urbanization, a major driver of global change, profoundly impacts our physical and social world, for example, altering carbon cycling and climate. Understanding these consequences for better scientific insights and effective decision-making unarguably requires accurate information on urban extent and its spatial distributions. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the nighttime light remote sensing data, extended this method to the global domain by developing a computational method (parameterization) to estimate the key parameters in the cluster-based method, and built a consistent 20-year global urban map series to evaluate the time-reactive nature of global urbanization (e.g. 2000 in Fig. 1). Supported by urban maps derived from nightlights remote sensing data and socio-economic drivers, we developed an integrated modeling framework to project future urban expansion by integrating a top-down macro-scale statistical model with a bottom-up urban growth model. With the models calibrated and validated using historical data, we explored urban growth at the grid level (1-km) over the next two decades under a number of socio-economic scenarios. The derived spatiotemporal information of historical and potential future urbanization will be of great value with practical implications for developing adaptation and risk management measures for urban infrastructure, transportation, energy, and water systems when considered together with other factors such as climate variability and change, and high impact weather events.

  4. NET remote workstation

    International Nuclear Information System (INIS)

    Leinemann, K.

    1990-10-01

    The goal of this NET study was to define the functionality of a remote handling workstation and its hardware and software architecture. The remote handling workstation has to fulfill two basic functions: (1) to provide the man-machine interface (MMI), that means the interface to the control system of the maintenance equipment and to the working environment (telepresence) and (2) to provide high level (task level) supporting functions (software tools) during the maintenance work and in the preparation phase. Concerning the man-machine interface, an important module of the remote handling workstation besides the standard components of man-machine interfacing is a module for graphical scene presentation supplementing viewing by TV. The technique of integrated viewing is well known from JET BOOM and TARM control using the GBsim and KISMET software. For integration of equipment dependent MMI functions the remote handling workstation provides a special software module interface. Task level support of the operator is based on (1) spatial (geometric/kinematic) models, (2) remote handling procedure models, and (3) functional models of the equipment. These models and the related simulation modules are used for planning, programming, execution monitoring, and training. The workstation provides an intelligent handbook guiding the operator through planned procedures illustrated by animated graphical sequences. For unplanned situations decision aids are available. A central point of the architectural design was to guarantee a high flexibility with respect to hardware and software. Therefore the remote handling workstation is designed as an open system based on widely accepted standards allowing the stepwise integration of the various modules starting with the basic MMI and the spatial simulation as standard components. (orig./HP) [de

  5. Acetone photophysics at 282 nm excitation at elevated pressure and temperature. II: Fluorescence modeling

    Science.gov (United States)

    Hartwig, Jason; Raju, Mandhapati; Sung, Chih-Jen

    2017-07-01

    This is the second in a series of two papers that presents an updated fluorescence model and compares with the new experimental data reported in the first paper, as well as the available literature data, to extend the range of acetone photophysics to elevated pressure and temperature conditions. This work elucidates the complete acetone photophysical model in terms of each and every competing radiative and non-radiative rate. The acetone fluorescence model is then thoroughly examined and optimized based on disparity with recently conducted elevated pressure and temperature photophysical calibration experiments. The current work offers insight into the competition between non-radiative and vibrational energy decay rates at elevated temperature and pressure and proposes a global optimization of model parameters from the photophysical model developed by Thurber (Acetone Laser-Induced Fluorescence for Temperature and Multiparameter Imaging in Gaseous Flows. PhD thesis, Stanford University Mechanical Engineering Department, 1999). The collisional constants of proportionality, which govern vibrational relaxation, are shown to be temperature dependent at elevated pressures. A new oxygen quenching rate is proposed which takes into account collisions with oxygen as well as the oxygen-assisted intersystem crossing component. Additionally, global trends in ketone photophysics are presented and discussed.

  6. Climate change and plant distribution: local models predict high-elevation persistence

    DEFF Research Database (Denmark)

    Randin, Christophe F.; Engler, Robin; Normand, Signe

    2009-01-01

    Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates...

  7. Remote radio control of insect flight

    Directory of Open Access Journals (Sweden)

    Hirotaka Sato

    2009-10-01

    Full Text Available We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely-controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.

  8. Remote radio control of insect flight.

    Science.gov (United States)

    Sato, Hirotaka; Berry, Christopher W; Peeri, Yoav; Baghoomian, Emen; Casey, Brendan E; Lavella, Gabriel; Vandenbrooks, John M; Harrison, Jon F; Maharbiz, Michel M

    2009-01-01

    We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.

  9. The use of soil moisture - remote sensing products for large-scale groundwater modeling and assessment

    NARCIS (Netherlands)

    Sutanudjaja, E.H.

    2012-01-01

    In this thesis, the possibilities of using spaceborne remote sensing for large-scale groundwater modeling are explored. We focus on a soil moisture product called European Remote Sensing Soil Water Index (ERS SWI, Wagner et al., 1999) - representing the upper profile soil moisture. As a test-bed, we

  10. Optical Modeling of Spectral Backscattering and Remote Sensing Reflectance From Emiliania huxleyi Blooms

    Directory of Open Access Journals (Sweden)

    Griet Neukermans

    2018-05-01

    Full Text Available In this study we develop an analytical model for spectral backscattering and ocean color remote sensing of blooms of the calcifying phytoplankton species Emiliania huxleyi. Blooms of this coccolithophore species are ubiquitous and particularly intense in temperate and subpolar ocean waters. We first present significant improvements to our previous analytical light backscattering model for E. huxleyi coccoliths and coccospheres by accounting for the elliptical shape of coccoliths and the multi-layered coccosphere architecture observed on detailed imagery of E. huxleyi liths and coccospheres. Our new model also includes a size distribution function that closely matches measured E. huxleyi size distributions. The model for spectral backscattering is then implemented in an analytical radiative transfer model to evaluate the variability of spectral remote sensing reflectance with respect to changes in the size distribution of the coccoliths and during a hypothetical E. huxleyi bloom decay event in which coccospheres shed their liths. Our modeled remote sensing reflectance spectra reproduced well the bright milky turquoise coloring of the open ocean typically associated with the final stages of E. huxleyi blooms, with peak reflectance at a wavelength of 0.49 μm. Our results also show that the magnitude of backscattering from coccoliths when attached to or freed from the coccosphere does not differ much, contrary to what is commonly assumed, and that the spectral shape of backscattering is mainly controlled by the size and morphology of the coccoliths, suggesting that they may be estimated from spectral backscattering.

  11. Comparison of different digital elevation models and satellite imagery for lineament analysis: Implications for identification and spatial arrangement of fault zones in crystalline basement rocks of the southern Black Forest (Germany)

    Science.gov (United States)

    Meixner, J.; Grimmer, J. C.; Becker, A.; Schill, E.; Kohl, T.

    2018-03-01

    GIS-based remote sensing techniques and lineament mapping provide additional information on the spatial arrangement of faults and fractures in large areas with variable outcrop conditions. Due to inherent censoring and truncation bias mapping of lineaments is still a challenging task. In this study we show how statistical evaluations help to improve the reliability of lineament mappings by comparing two digital elevation models (ASTER, LIDAR) and satellite imagery data sets in the seismically active southern Black Forest. A statistical assessment of the orientation, average length, and the total length of mapped lineaments reveals an impact of the different resolutions of the data sets that allow to define maximum (censoring bias) and minimum (truncation bias) observable lineament length for each data set. The increase of the spatial resolution of the digital elevation model from 30 m × 30 m to 5 m × 5 m results in a decrease of total lineament length by about 40% whereby the average lineament lengths decrease by about 60%. Lineament length distributions of both data sets follow a power law distribution as documented elsewhere for fault and fracture systems. Predominant NE-, N-, NNW-, and NW-directions of the lineaments are observed in all data sets and correlate with well-known, mappable large-scale structures in the southern Black Forest. Therefore, mapped lineaments can be correlated with faults and hence display geological significance. Lineament density in the granite-dominated areas is apparently higher than in the gneiss-dominated areas. Application of a slip- and dilation tendency analysis on the fault pattern reveals largest reactivation potentials for WNW-ESE and N-S striking faults as strike-slip faults whereas normal faulting may occur along NW-striking faults within the ambient stress field. Remote sensing techniques in combination with highly resolved digital elevation models and a slip- and dilation tendency analysis thus can be used to quickly get

  12. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

    OpenAIRE

    West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-01-01

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tama...

  13. Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

    Science.gov (United States)

    Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

    2013-01-01

    Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

  14. Evaluation of Design Models of Process Equipment for Use in PRIDE: Remote Operability and Maintainability

    International Nuclear Information System (INIS)

    Kim, Ki Ho; Kim, Sung Hyun; Yu, Seung Nam; Lee, Jong Kwang; Park, Byung Suk; Han, Jong Hui; Cho, Il Je; Lee, Han Soo

    2012-01-01

    Process equipment for pyroprocessing are being developed at KAERI (Korea Atomic Energy Research Institute). Those equipment should be operated and maintained in a fully remote manner in the argon gas filled cell of PRIDE (PyRoprocess Integrated inactive DEmonstration facility) at KAERI because direct human access to the in-cell is not possible during an operation due to the high toxicity of the argon gas. To make such process equipment remotely operable and maintainable, their design developments have been tested and evaluated in a simulator before they are constructed. A simulator as a means of evaluating the remote operability and maintainability of the design models of process equipment for pyroprocessing is described, and results of the design models tested and evaluated in a simulator are presented

  15. Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM).

    Science.gov (United States)

    West, Amanda M; Evangelista, Paul H; Jarnevich, Catherine S; Young, Nicholas E; Stohlgren, Thomas J; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-10-11

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

  16. Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

    Science.gov (United States)

    West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Young, Nicholas E.; Stohlgren, Thomas J.; Talbert, Colin; Talbert, Marian; Morisette, Jeffrey; Anderson, Ryan

    2016-01-01

    Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk (Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

  17. Assimilation of remote sensing observations into a sediment transport model of China's largest freshwater lake: spatial and temporal effects.

    Science.gov (United States)

    Zhang, Peng; Chen, Xiaoling; Lu, Jianzhong; Zhang, Wei

    2015-12-01

    Numerical models are important tools that are used in studies of sediment dynamics in inland and coastal waters, and these models can now benefit from the use of integrated remote sensing observations. This study explores a scheme for assimilating remotely sensed suspended sediment (from charge-coupled device (CCD) images obtained from the Huanjing (HJ) satellite) into a two-dimensional sediment transport model of Poyang Lake, the largest freshwater lake in China. Optimal interpolation is used as the assimilation method, and model predictions are obtained by combining four remote sensing images. The parameters for optimal interpolation are determined through a series of assimilation experiments evaluating the sediment predictions based on field measurements. The model with assimilation of remotely sensed sediment reduces the root-mean-square error of the predicted sediment concentrations by 39.4% relative to the model without assimilation, demonstrating the effectiveness of the assimilation scheme. The spatial effect of assimilation is explored by comparing model predictions with remotely sensed sediment, revealing that the model with assimilation generates reasonable spatial distribution patterns of suspended sediment. The temporal effect of assimilation on the model's predictive capabilities varies spatially, with an average temporal effect of approximately 10.8 days. The current velocities which dominate the rate and direction of sediment transport most likely result in spatial differences in the temporal effect of assimilation on model predictions.

  18. A global digital elevation model - GTOP030

    Science.gov (United States)

    1999-01-01

    GTOP030, the U.S. Geological Survey's (USGS) digital elevation model (DEM) of the Earth, provides the flrst global coverage of moderate resolution elevation data.  The original GTOP30 data set, which was developed over a 3-year period through a collaborative effort led by the USGS, was completed in 1996 at the USGS EROS Data Center in Sioux Falls, South Dakota.  The collaboration involved contributions of staffing, funding, or source data from cooperators including the National Aeronautics and Space Administration (NASA), the United Nations Environment Programme Global Resource Information Database (UNEP/GRID), the U.S. Agency for International Development (USAID), the Instituto Nacional de Estadistica Geografia e Informatica (INEGI) of Mexico, the Geographical Survey Institute (GSI) of Japan, Manaaki Whenua Landcare Research of New Zealand, and the Scientific Committee on Antarctic Research (SCAR). In 1999, work was begun on an update to the GTOP030 data set. Additional data sources are being incorporated into GTOP030 with an enhanced and improved data set planned for release in 2000.

  19. Investigating the Potential Range Expansion of the Vector Mosquito Aedes aegypti in Mexico with NASA Earth Science Remote Sensing Results

    Science.gov (United States)

    Crosson, W. L.; Eisen, L.; Estes, M. G.; Estes, S. M.; Hayden, M.; Lozano-Fuentes, S.; Monaghan, A. J.; Moreno Madriñán, M. J.; Ochoa, C.; Quattrochi, D.; Tapia, B.; Welsh-Rodriguez, C. M.

    2012-12-01

    In tropical and sub-tropical regions, the mosquito Aedes aegypti is the major vector for the virus causing dengue, a serious public health issue in these areas. Through ongoing NSF- and NASA-funded studies, field surveys of Aedes aegypti and an integrated modeling approach are being used to improve our understanding of the potential range of the mosquito to expand toward heavily populated high elevation areas such as Mexico City under various climate change and socio-economic scenarios. This work serves three primary objectives: (1) Employ NASA remotely-sensed data to supplement the environmental monitoring and modeling component of the project. These data -- for example, surface temperature, precipitation, vegetation indices, soil moisture and elevation -- are critical for understanding the habitat necessary for mosquito survival and abundance; (2) Implement training sessions to instruct scientists and students from Mexico and the U.S. on how to use remote sensing and implement the NASA SERVIR Regional Visualization and Monitoring System; (3) Employ the SERVIR framework to optimize the dissemination of key project results in order to increase their societal relevance and benefits in developing climate adaptation strategies. Field surveys of larval, pupal and adult Aedes aegypti, as well as detailed physical and social household characteristics, were conducted in the summers of 2011and 2012 at geographic scales from the household to the community along a transect from sea level to 2400 m ASL. These data are being used in models to estimate Aedes aegypti habitat suitability. In 2011, Aedes aegypti were identified at an elevation of over 2150 m in Puebla, the highest elevation at which this species has been observed.

  20. Modelling groundwater discharge areas using only digital elevation models as input data

    Energy Technology Data Exchange (ETDEWEB)

    Brydsten, Lars [Umeaa Univ. (Sweden). Dept. of Biology and Environmental Science

    2006-10-15

    Advanced geohydrological models require data on topography, soil distribution in three dimensions, vegetation, land use, bedrock fracture zones. To model present geohydrological conditions, these factors can be gathered with different techniques. If a future geohydrological condition is modelled in an area with positive shore displacement (say 5,000 or 10,000 years), some of these factors can be difficult to measure. This could include the development of wetlands and the filling of lakes. If the goal of the model is to predict distribution of groundwater recharge and discharge areas in the landscape, the most important factor is topography. The question is how much can topography alone explain the distribution of geohydrological objects in the landscape. A simplified description of the distribution of geohydrological objects in the landscape is that groundwater recharge areas occur at local elevation curvatures and discharge occurs in lakes, brooks, and low situated slopes. Areas in-between these make up discharge areas during wet periods and recharge areas during dry periods. A model that could predict this pattern only using topography data needs to be able to predict high ridges and future lakes and brooks. This study uses GIS software with four different functions using digital elevation models as input data, geomorphometrical parameters to predict landscape ridges, basin fill for predicting lakes, flow accumulations for predicting future waterways, and topographical wetness indexes for dividing in-between areas based on degree of wetness. An area between the village of and Forsmarks' Nuclear Power Plant has been used to calibrate the model. The area is within the SKB 10-metre Elevation Model (DEM) and has a high-resolution orienteering map for wetlands. Wetlands are assumed to be groundwater discharge areas. Five hundred points were randomly distributed across the wetlands. These are potential discharge points. Model parameters were chosen with the

  1. St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 1/3 arc-second St. Croix, U.S. Virgin Islands Coastal Digital Elevation Model will be used to support NOAA's tsunami forecast system and for tsunami inundation...

  2. Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

    Science.gov (United States)

    Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

    2018-04-26

    With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

  3. Remote vehicle survey tool

    International Nuclear Information System (INIS)

    Armstrong, G.A.; Burks, B.L.; Kress, R.L.; Wagner, D.G.; Ward, C.R.

    1993-01-01

    The Remote Vehicle Survey Tool (RVS7) is a color graphical display tool for viewing remotely acquired scientific data. The RVST displays the data in the form of a color two-dimensional world model map. The world model map allows movement of the remote vehicle to be tracked by the operator and the data from sensors to be graphically depicted in the interface. Linear and logarithmic meters, dual channel oscilloscopes, and directional compasses are used to display sensor information. The RVST is user-configurable by the use of ASCII text files. The operator can configure the RVST to work with any remote data acquisition system and teleoperated or autonomous vehicle. The modular design of the RVST and its ability to be quickly configured for varying system requirements make the RVST ideal for remote scientific data display in all environmental restoration and waste management programs

  4. TRMM-3B43 Bias Correction over the High Elevations of the Contiguous United States

    Science.gov (United States)

    Hashemi, H.; Nordin, K. M.; Lakshmi, V.; Knight, R. J.

    2016-12-01

    Precipitation can be quantified using a rain gauge network, or a remotely sensed precipitation product. Ultimately, the choice of dataset depends on the particular application, the catchment size, climate and the time period of study. In a region with a long record and a dense rain gauge network, the elevation-modified ground-based precipitation product, PRISM, has been found to work well. However, in poorly gauged regions the use of remotely sensed precipitation products is an absolute necessity. The Tropical Rainfall Measuring Mission (TRMM) has provided valuable precipitation datasets for hydrometeorological studies over the past two decades (1998-2015). One concern regarding the usage of TRMM data is the accuracy of the precipitation estimates, when compared to those obtained using PRISM. The reason for this concern is that TRMM and PRISM do not always agree and, typically, TRMM underestimates PRISM over the mountainous regions of the United States. In this study, we develop a correction function to improve the accuracy of the TRMM monthly product (TRMM-3B43) by estimating and removing the bias in the satellite data using the ground-based precipitation product, PRISM. We observe a strong relationship between the bias and land surface elevation; TRMM-3B43 tends to underestimate the PRISM product at altitudes greater than 1500 m above mean sea level (m.amsl) in the contiguous United States. A relationship is developed between TRMM-PRISM bias and elevation. The correction function is used to adjust the TRMM monthly precipitation using PRISM and elevation data. The model is calibrated using 25% of the available time period and the remaining 75% of the time period is used for validation. The corrected TRMM-3B43 product is verified for the high elevations over the contiguous United States and two local regions in the mountainous areas of the western United States. The results show a significant improvement in the accuracy of the TRMM product in the high elevations of

  5. High Resolution Digital Elevation Models of Pristine Explosion Craters

    Science.gov (United States)

    Farr, T. G.; Krabill, W.; Garvin, J. B.

    2004-01-01

    In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements

  6. Using remote sensing and machine learning for the spatial modelling of a bluetongue virus vector

    Science.gov (United States)

    Van doninck, J.; Peters, J.; De Baets, B.; Ducheyne, E.; Verhoest, N. E. C.

    2012-04-01

    Bluetongue is a viral vector-borne disease transmitted between hosts, mostly cattle and small ruminants, by some species of Culicoides midges. Within the Mediterranean basin, C. imicola is the main vector of the bluetongue virus. The spatial distribution of this species is limited by a number of environmental factors, including temperature, soil properties and land cover. The identification of zones at risk of bluetongue outbreaks thus requires detailed information on these environmental factors, as well as appropriate epidemiological modelling techniques. We here give an overview of the environmental factors assumed to be constraining the spatial distribution of C. imicola, as identified in different studies. Subsequently, remote sensing products that can be used as proxies for these environmental constraints are presented. Remote sensing data are then used together with species occurrence data from the Spanish Bluetongue National Surveillance Programme to calibrate a supervised learning model, based on Random Forests, to model the probability of occurrence of the C. imicola midge. The model will then be applied for a pixel-based prediction over the Iberian peninsula using remote sensing products for habitat characterization.

  7. Element size and other restrictions in finite-element modeling of reinforced concrete at elevated temperatures

    DEFF Research Database (Denmark)

    Carstensen, Josephine Voigt; Jomaas, Grunde; Pankaj, Pankaj

    2013-01-01

    to extend this approach for RC at elevated temperatures. Prior to the extension, the approach is investigated for associated modeling issues and a set of limits of application are formulated. The available models of the behavior of plain concrete at elevated temperatures were used to derive inherent......One of the accepted approaches for postpeak finite-element modeling of RC comprises combining plain concrete, reinforcement, and interaction behaviors. In these, the postpeak strain-softening behavior of plain concrete is incorporated by the use of fracture energy concepts. This study attempts...... fracture energy variation with temperature. It is found that the currently used tensile elevated temperature model assumes that the fracture energy decays with temperature. The existing models in compression also show significant decay of fracture energy at higher temperatures (>400°) and a considerable...

  8. Ship detection using STFT sea background statistical modeling for large-scale oceansat remote sensing image

    Science.gov (United States)

    Wang, Lixia; Pei, Jihong; Xie, Weixin; Liu, Jinyuan

    2018-03-01

    Large-scale oceansat remote sensing images cover a big area sea surface, which fluctuation can be considered as a non-stationary process. Short-Time Fourier Transform (STFT) is a suitable analysis tool for the time varying nonstationary signal. In this paper, a novel ship detection method using 2-D STFT sea background statistical modeling for large-scale oceansat remote sensing images is proposed. First, the paper divides the large-scale oceansat remote sensing image into small sub-blocks, and 2-D STFT is applied to each sub-block individually. Second, the 2-D STFT spectrum of sub-blocks is studied and the obvious different characteristic between sea background and non-sea background is found. Finally, the statistical model for all valid frequency points in the STFT spectrum of sea background is given, and the ship detection method based on the 2-D STFT spectrum modeling is proposed. The experimental result shows that the proposed algorithm can detect ship targets with high recall rate and low missing rate.

  9. Vertical dispersion from surface and elevated releases: An investigation of a Non-Gaussian plume model

    International Nuclear Information System (INIS)

    Brown, M.J.; Arya, S.P.; Snyder, W.H.

    1993-01-01

    The vertical diffusion of a passive tracer released from surface and elevated sources in a neutrally stratified boundary layer has been studied by comparing field and laboratory experiments with a non-Gaussian K-theory model that assumes power-law profiles for the mean velocity and vertical eddy diffusivity. Several important differences between model predictions and experimental data were discovered: (1) the model overestimated ground-level concentrations from surface and elevated releases at distances beyond the peak concentration; (2) the model overpredicted vertical mixing near elevated sources, especially in the upward direction; (3) the model-predicted exponent α in the exponential vertical concentration profile for a surface release [bar C(z)∝ exp(-z α )] was smaller than the experimentally measured exponent. Model closure assumptions and experimental short-comings are discussed in relation to their probable effect on model predictions and experimental measurements. 42 refs., 13 figs., 3 tabs

  10. Handbook on advances in remote sensing and geographic information systems paradigms and applications in forest landscape modeling

    CERN Document Server

    Favorskaya, Margarita N

    2017-01-01

    This book presents the latest advances in remote-sensing and geographic information systems and applications. It is divided into four parts, focusing on Airborne Light Detection and Ranging (LiDAR) and Optical Measurements of Forests; Individual Tree Modelling; Landscape Scene Modelling; and Forest Eco-system Modelling. Given the scope of its coverage, the book offers a valuable resource for students, researchers, practitioners, and educators interested in remote sensing and geographic information systems and applications.

  11. Analysis the Accuracy of Digital Elevation Model (DEM) for Flood Modelling on Lowland Area

    Science.gov (United States)

    Zainol Abidin, Ku Hasna Zainurin Ku; Razi, Mohd Adib Mohammad; Bukari, Saifullizan Mohd

    2018-04-01

    Flood is one type of natural disaster that occurs almost every year in Malaysia. Commonly the lowland areas are the worst affected areas. This kind of disaster is controllable by using an accurate data for proposing any kinds of solutions. Elevation data is one of the data used to produce solutions for flooding. Currently, the research about the application of Digital Elevation Model (DEM) in hydrology was increased where this kind of model will identify the elevation for required areas. University of Tun Hussein Onn Malaysia is one of the lowland areas which facing flood problems on 2006. Therefore, this area was chosen in order to produce DEM which focussed on University Health Centre (PKU) and drainage area around Civil and Environment Faculty (FKAAS). Unmanned Aerial Vehicle used to collect aerial photos data then undergoes a process of generating DEM according to three types of accuracy and quality from Agisoft PhotoScan software. The higher the level of accuracy and quality of DEM produced, the longer time taken to generate a DEM. The reading of the errors created while producing the DEM shows almost 0.01 different. Therefore, it has been identified there are some important parameters which influenced the accuracy of DEM.

  12. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-01-01

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

  13. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-11-17

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  14. Optimization and modeling of the remote loading of luciferin into liposomes.

    Science.gov (United States)

    Hansen, Anders Højgaard; Lomholt, Michael A; Hansen, Per Lyngs; Mouritsen, Ole G; Arouri, Ahmad

    2016-07-11

    We carried out a mechanistic study to characterize and optimize the remote loading of luciferin into preformed liposomes of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine/1,2-dipalmitoyl-sn-glycero-3-phosphoglycerol (DPPC/DPPG) 7:3 mixtures. The influence of the loading agent (acetate, propionate, butyrate), the metal counterion (Na(+), K(+), Ca(+2), Mg(+2)), and the initial extra-liposomal amount of luciferin (nL(add)) on the luciferin Loading Efficiency (LE%) and luciferin-to-lipid weight ratio, i.e., Loading Capacity (LC), in the final formulation was determined. In addition, the effect of the loading process on the colloidal stability and phase behavior of the liposomes was monitored. Based on our experimental results, a theoretical model was developed to describe the course of luciferin remote loading. It was found that the highest luciferin loading was obtained with magnesium acetate. The use of longer aliphatic carboxylates or inorganic proton donors pronouncedly reduced luciferin loading, whereas the effect of the counterion was modest. The remote-loading process barely affected the colloidal stability and drug retention of the liposomes, albeit with moderate luciferin-induced membrane perturbations. The correlation between luciferin loading, expressed as LE% and LC, and nL(add) was established, and under our conditions the maximum LC was attained using an nL(add) of around 2.6μmol. Higher amounts of luciferin tend to pronouncedly perturb the liposome stability and luciferin retention. Our theoretical model furnishes a fair quantitative description of the correlation between nL(add) and luciferin loading, and a membrane permeability coefficient for uncharged luciferin of 1×10(-8)cm/s could be determined. We believe that our study will prove very useful to optimize the remote-loading strategies of moderately polar carboxylic acid drugs in general. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

    Directory of Open Access Journals (Sweden)

    TAO Feixiang

    2015-08-01

    Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

  16. Marquesas Islands, French Polynesia 3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. Port Alberni, Canada 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  18. Digital Elevation Model of Kauai, Hawaii, Integrating Bathymetric and Topographic Datasets

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  19. Crescent City, California 1/3 Arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Cordova, Alaska 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Tutuila, American Samoa 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. Eureka, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Central Florida 1/3 arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Puget Sound 1/3 arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Society Islands (Leeward), French Polynesia Digital Elevation Model - 1 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Midway Atoll 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Society Islands (Windward), French Polynesia Digital Elevation Model - 1 arc-second

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Miami 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. Central California 1 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Wake Island 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  11. Monterey, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  12. Tampa Bay 1/3 arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. Garibaldi, Oregon 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Sitka, Alaska 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. Kent mixture model for classification of remote sensing data on spherical manifolds

    CSIR Research Space (South Africa)

    Lunga, D

    2011-10-01

    Full Text Available Modern remote sensing imaging sensor technology provides detailed spectral and spatial information that enables precise analysis of land cover usage. From a research point of view, traditional widely used statistical models are often limited...

  16. Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

    Directory of Open Access Journals (Sweden)

    Yvonne Walz

    2015-11-01

    Full Text Available Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

  17. Research on Remote Sensing recognition features of Yuan Yang Terraces in Yunnan Province (China)

    Science.gov (United States)

    Xiang, Jie; Chen, Jianping; Lai, ZiLi; Yang, Wei

    2016-04-01

    Yuan Yang terraces is one of the most famous terraces in China, and it was successfully listed in the world heritage list at the 37th world heritage convention. On the one hand, Yuan Yang terraces retain more soil and water, to reduce both hydrological connectivity and erosion, and to support irrigation. On the other hand, It has the important tourism value, bring the huge revenue to local residents. In order to protect and make use of Yuan Yang terraces better, This study analyzed the spatial distribution and spectral characteristics of terraces:(1) Through visual interpretation, the study recognized the terraces based on the spatial adjusted remote sensing image (2010 Geoeye-1 with resolution of 1m/pix), and extracted topographic feature (elevation, slope, aspect, etc.) based on the digital elevation model with resolution of 20m/pix. The terraces cover a total area of about 11.58Km2, accounted for 24.4% of the whole study area. The terraces appear at range from 1400m to 1800m in elevation, 10°to 20°in slope, northwest to northeast in aspect; (2) Using the method of weight of evidence, this study assessed the importance of different topographic feature. The results show that the sort of importance: elevation>slope>aspect; (3) The study counted the Normalized Difference Vegetation Index (NDVI) changes of terraces throughout the year, based on the landsat-5 image with resolution of 30m/pix. The results show that the changes of terraces' NDVI are bigger than other stuff (e.g. forest, road, house, etc.). Those work made a good preparations for establishing the dynamic remote sensing monitoring system of Yuan Yang terraces.

  18. False Pass, Alaska 8/15 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  19. Yakutat, Alaska 8/15 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  20. Elfin Cove Alaska 1/3 Arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  1. Cordova, Alaska 8/15 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  2. King Cove, Alaska 8/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  3. King Cove, Alaska 8/15 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  4. Nikolski, Alaska 1/3 arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  5. Port Lions, Alaska 8/15 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  6. Yakutat, Alaska 8/3 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  7. Digital Elevation Model of Southeast Alaska, Integrating Bathymetric and Topographic Datasets

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  8. Cold Bay, Alaska 8/15 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  9. The ASTER Global Digital Elevation Model (GDEM) -for societal benefit -

    Science.gov (United States)

    Hato, M.; Tsu, H.; Tachikawa, T.; Abrams, M.; Bailey, B.

    2009-12-01

    The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the Ministry of Economy, Trade and Industry (METI) of Japan and the United States National Aeronautics and Space Administration (NASA) under the agreement of contribution to GEOSS and a public release was started on June 29th. ASTER GDEM can be downloaded to users from the Earth Remote Sensing Data Analysis Center (ERSDAC) of Japan and NASA’s Land Processes Distributed Active Archive Center (LP DAAC) free of charge. The ASTER instrument was built by METI and launched onboard NASA’s Terra spacecraft in December 1999. It has an along-track stereoscopic capability using its near infrared spectral band (NIR) and its nadir-viewing and backward-viewing telescopes to acquire stereo image data with a base-to-height ratio of 0.6. The ASTER GDEM was produced by applying newly-developed automated algorithm to more than 1.2 million NIR data Produced DEMs of all scene data was stacked after cloud masking and finally partitioned into 1° x 1°unit (called ‘tile’) data for convenience of distribution and handling by users. Before start of public distribution, ERSDAC and USGS/NASA together with many volunteers did validation and characterization by using a preliminary product of the ASTER GDEM. As a result of validation, METI and NASA evaluated that Version 1 of the ASTER GDEM has enough quality to be used as “experimental” or “research grade” data and consequently decided to release it. The ASTER GDEM covering almost all land area of from 83N to 83S on the earth represents as an important contribution to the global earth observation community. We will show our effort of development of ASTER GDEM and its accuracy and character.

  10. Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

    Science.gov (United States)

    Jana, Raghavendra B.; Mohanty, Binayak P.

    2011-03-01

    SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support

  11. Cascading water underneath Wilkes Land, East Antarctic ice sheet, observed using altimetry and digital elevation models

    Science.gov (United States)

    Flament, T.; Berthier, E.; Rémy, F.

    2014-04-01

    We describe a major subglacial lake drainage close to the ice divide in Wilkes Land, East Antarctica, and the subsequent cascading of water underneath the ice sheet toward the coast. To analyse the event, we combined altimetry data from several sources and subglacial topography. We estimated the total volume of water that drained from Lake CookE2 by differencing digital elevation models (DEM) derived from ASTER and SPOT5 stereo imagery acquired in January 2006 and February 2012. At 5.2 ± 1.5 km3, this is the largest single subglacial drainage event reported so far in Antarctica. Elevation differences between ICESat laser altimetry spanning 2003-2009 and the SPOT5 DEM indicate that the discharge started in November 2006 and lasted approximately 2 years. A 13 m uplift of the surface, corresponding to a refilling of about 0.6 ± 0.3 km3, was observed between the end of the discharge in October 2008 and February 2012. Using the 35-day temporal resolution of Envisat radar altimetry, we monitored the subsequent filling and drainage of connected subglacial lakes located downstream of CookE2. The total volume of water traveling within the theoretical 500-km-long flow paths computed with the BEDMAP2 data set is similar to the volume that drained from Lake CookE2, and our observations suggest that most of the water released from Lake CookE2 did not reach the coast but remained trapped underneath the ice sheet. Our study illustrates how combining multiple remote sensing techniques allows monitoring of the timing and magnitude of subglacial water flow beneath the East Antarctic ice sheet.

  12. Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models

    DEFF Research Database (Denmark)

    Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith

    2010-01-01

    the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature...... field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v......) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME...

  13. Northern Gulf 1 Arc-second NAVD 88 Coast Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  14. Mathematical methods to model rodent behavior in the elevated plus-maze.

    Science.gov (United States)

    Arantes, Rafael; Tejada, Julián; Bosco, Geraldine G; Morato, Silvio; Roque, Antonio C

    2013-11-15

    The elevated plus maze is a widely used experimental test to study anxiety-like rodent behavior. It is made of four arms, two open and two closed, connected at a central area forming a plus shaped maze. The whole apparatus is elevated 50 cm from the floor. The anxiety of the animal is usually assessed by the number of entries and duration of stay in each arm type during a 5-min period. Different mathematical methods have been proposed to model the mechanisms that control the animal behavior in the maze, such as factor analysis, statistical inference on Markov chains and computational modeling. In this review we discuss these methods and propose possible extensions of them as a direction for future research. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Remote sensing applied to numerical modelling. [water resources pollution

    Science.gov (United States)

    Sengupta, S.; Lee, S. S.; Veziroglu, T. N.; Bland, R.

    1975-01-01

    Progress and remaining difficulties in the construction of predictive mathematical models of large bodies of water as ecosystems are reviewed. Surface temperature is at present the only variable than can be measured accurately and reliably by remote sensing techniques, but satellite infrared data are of sufficient resolution for macro-scale modeling of oceans and large lakes, and airborne radiometers are useful in meso-scale analysis (of lakes, bays, and thermal plumes). Finite-element and finite-difference techniques applied to the solution of relevant coupled time-dependent nonlinear partial differential equations are compared, and the specific problem of the Biscayne Bay and environs ecosystem is tackled in a finite-differences treatment using the rigid-lid model and a rigid-line grid system.

  16. Modeling of a remote inspection system for NSSS components

    International Nuclear Information System (INIS)

    Choi, Yoo Rark; Kim, Jae Hee; Lee, Jae Cheol

    2003-03-01

    Safety inspection for safety-critical unit of nuclear power plant has been processed using off-line technology. Thus we can not access safety inspection system and inspection data via network such as internet. We are making an on-line control and data access system based on WWW and JAVA technologies which can be used during plant operation to overcome these problems. Users can access inspection systems and inspection data only using web-browser. This report discusses about analysis of the existing remote system and essential techniques such as Web, JAVA, client/server model, and multi-tier model. This report also discusses about a system modeling that we have been developed using these techniques and provides solutions for developing an on-line control and data access system

  17. Graphics metafile interface to ARAC emergency response models for remote workstation study

    International Nuclear Information System (INIS)

    Lawver, B.S.

    1985-01-01

    The Department of Energy's Atmospheric Response Advisory Capability models are executed on computers at a central computer center with the output distributed to accident advisors in the field. The output of these atmospheric diffusion models are generated as contoured isopleths of concentrations. When these isopleths are overlayed with local geography, they become a useful tool to the accident site advisor. ARAC has developed a workstation that is located at potential accident sites. The workstation allows the accident advisor to view color plots of the model results, scale those plots and print black and white hardcopy of the model results. The graphics metafile, also known as Virtual Device Metafile (VDM) allows the models to generate a single device independent output file that is partitioned into geography, isoopleths and labeling information. The metafile is a very compact data storage technique that is output device independent. The metafile frees the model from either generating output for all known graphic devices or requiring the model to be rerun for additional graphic devices. With the partitioned metafile ARAC can transmit to the remote workstation the isopleths and labeling for each model. The geography database may not change and can be transmitted only when needed. This paper describes the important features of the remote workstation and how these features are supported by the device independent graphics metafile

  18. Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

    Science.gov (United States)

    Christopher D. Lippitt; Douglas A. Stow; Philip J. Riggan

    2016-01-01

    Remote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication...

  19. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    Science.gov (United States)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2017-07-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  20. Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling

    Directory of Open Access Journals (Sweden)

    Wenkai Zhang

    2017-12-01

    Full Text Available In recent years, Fully Convolutional Networks (FCN have led to a great improvement of semantic labeling for various applications including multi-modal remote sensing data. Although different fusion strategies have been reported for multi-modal data, there is no in-depth study of the reasons of performance limits. For example, it is unclear, why an early fusion of multi-modal data in FCN does not lead to a satisfying result. In this paper, we investigate the contribution of individual layers inside FCN and propose an effective fusion strategy for the semantic labeling of color or infrared imagery together with elevation (e.g., Digital Surface Models. The sensitivity and contribution of layers concerning classes and multi-modal data are quantified by recall and descent rate of recall in a multi-resolution model. The contribution of different modalities to the pixel-wise prediction is analyzed explaining the reason of the poor performance caused by the plain concatenation of different modalities. Finally, based on the analysis an optimized scheme for the fusion of layers with image and elevation information into a single FCN model is derived. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset (infrared and RGB imagery as well as elevation and the Potsdam dataset (RGB imagery and elevation. Comprehensive evaluations demonstrate the potential of the proposed approach.

  1. A DNA-based semantic fusion model for remote sensing data.

    Directory of Open Access Journals (Sweden)

    Heng Sun

    Full Text Available Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  2. A DNA-based semantic fusion model for remote sensing data.

    Science.gov (United States)

    Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

    2013-01-01

    Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

  3. Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model

    Science.gov (United States)

    Wu, Z.; Chen, X.; Gao, Y.; Li, Y.

    2018-04-01

    Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.

  4. Using remotely sensed data and stochastic models to simulate realistic flood hazard footprints across the continental US

    Science.gov (United States)

    Bates, P. D.; Quinn, N.; Sampson, C. C.; Smith, A.; Wing, O.; Neal, J. C.

    2017-12-01

    Remotely sensed data has transformed the field of large scale hydraulic modelling. New digital elevation, hydrography and river width data has allowed such models to be created for the first time, and remotely sensed observations of water height, slope and water extent has allowed them to be calibrated and tested. As a result, we are now able to conduct flood risk analyses at national, continental or even global scales. However, continental scale analyses have significant additional complexity compared to typical flood risk modelling approaches. Traditional flood risk assessment uses frequency curves to define the magnitude of extreme flows at gauging stations. The flow values for given design events, such as the 1 in 100 year return period flow, are then used to drive hydraulic models in order to produce maps of flood hazard. Such an approach works well for single gauge locations and local models because over relatively short river reaches (say 10-60km) one can assume that the return period of an event does not vary. At regional to national scales and across multiple river catchments this assumption breaks down, and for a given flood event the return period will be different at different gauging stations, a pattern known as the event `footprint'. Despite this, many national scale risk analyses still use `constant in space' return period hazard layers (e.g. the FEMA Special Flood Hazard Areas) in their calculations. Such an approach can estimate potential exposure, but will over-estimate risk and cannot determine likely flood losses over a whole region or country. We address this problem by using a stochastic model to simulate many realistic extreme event footprints based on observed gauged flows and the statistics of gauge to gauge correlations. We take the entire USGS gauge data catalogue for sites with > 45 years of record and use a conditional approach for multivariate extreme values to generate sets of flood events with realistic return period variation in

  5. A Study of Flood Evacuation Center Using GIS and Remote Sensing Technique

    Science.gov (United States)

    Mustaffa, A. A.; Rosli, M. F.; Abustan, M. S.; Adib, R.; Rosli, M. I.; Masiri, K.; Saifullizan, B.

    2016-07-01

    This research demonstrated the use of Remote Sensing technique and GIS to determine the suitability of an evacuation center. This study was conducted in Batu Pahat areas that always hit by a series of flood. The data of Digital Elevation Model (DEM) was obtained by ASTER database that has been used to delineate extract contour line and elevation. Landsat 8 image was used for classification purposes such as land use map. Remote Sensing incorporate with GIS techniques was used to determined the suitability location of the evacuation center from contour map of flood affected areas in Batu Pahat. GIS will calculate the elevation of the area and information about the country of the area, the road access and percentage of the affected area. The flood affected area map may provide the suitability of the flood evacuation center during the several levels of flood. The suitability of evacuation centers can be determined based on several criteria and the existing data of the evacuation center will be analysed. From the analysis among 16 evacuation center listed, there are only 8 evacuation center suitable for the usage during emergency situation. The suitability analysis was based on the location and the road access of the evacuation center toward the flood affected area. There are 10 new locations with suitable criteria of evacuation center proposed on the study area to facilitate the process of rescue and evacuating flood victims to much safer and suitable locations. The results of this study will help in decision making processes and indirectly will help organization such as fire-fighter and the Department of Social Welfare in their work. Thus, this study can contribute more towards the society.

  6. Risk assessment of storm surge disaster based on numerical models and remote sensing

    Science.gov (United States)

    Liu, Qingrong; Ruan, Chengqing; Zhong, Shan; Li, Jian; Yin, Zhonghui; Lian, Xihu

    2018-06-01

    Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

  7. ACE2 Global Digital Elevation Model : User Analysis

    Science.gov (United States)

    Smith, R. G.; Berry, P. A. M.; Benveniste, J.

    2013-12-01

    Altimeter Corrected Elevations 2 (ACE2), first released in October 2009, is the Global Digital Elevation Model (GDEM) created by fusing the high accuracy of over 100 million altimeter retracked height estimates, derived primarily from the ERS-1 Geodetic Mission, with the high frequency content available within the near-global Shuttle Radar Topography Mission. This novel ACE2 GDEM is freely available at 3”, 9”, 30” and 5' and has been distributed via the web to over 680 subscribers. This paper presents the results of a detailed analysis of geographical distribution of subscribed users, along with fields of study and potential uses. Investigations have also been performed to determine the most popular spatial resolutions and the impact these have on the scope of data downloaded. The analysis has shown that, even though the majority of users have come from Europe and America, a significant number of website hits have been received from South America, Africa and Asia. Registered users also vary widely, from research institutions and major companies down to individual hobbyists looking at data for single projects.

  8. Appending High-Resolution Elevation Data to GPS Speed Traces for Vehicle Energy Modeling and Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Wood, E.; Burton, E.; Duran, A.; Gonder, J.

    2014-06-01

    Accurate and reliable global positioning system (GPS)-based vehicle use data are highly valuable for many transportation, analysis, and automotive considerations. Model-based design, real-world fuel economy analysis, and the growing field of autonomous and connected technologies (including predictive powertrain control and self-driving cars) all have a vested interest in high-fidelity estimation of powertrain loads and vehicle usage profiles. Unfortunately, road grade can be a difficult property to extract from GPS data with consistency. In this report, we present a methodology for appending high-resolution elevation data to GPS speed traces via a static digital elevation model. Anomalous data points in the digital elevation model are addressed during a filtration/smoothing routine, resulting in an elevation profile that can be used to calculate road grade. This process is evaluated against a large, commercially available height/slope dataset from the Navteq/Nokia/HERE Advanced Driver Assistance Systems product. Results will show good agreement with the Advanced Driver Assistance Systems data in the ability to estimate road grade between any two consecutive points in the contiguous United States.

  9. The Use of Remote Sensing Data for Modeling Air Quality in the Cities

    Science.gov (United States)

    Putrenko, V. V.; Pashynska, N. M.

    2017-12-01

    Monitoring of environmental pollution in the cities by the methods of remote sensing of the Earth is actual area of research for sustainable development. Ukraine has a poorly developed network of monitoring stations for air quality, the technical condition of which is deteriorating in recent years. Therefore, the possibility of obtaining data about the condition of air by remote sensing methods is of great importance. The paper considers the possibility of using the data about condition of atmosphere of the project AERONET to assess the air quality in Ukraine. The main pollution indicators were used data on fine particulate matter (PM2.5) and nitrogen dioxide (NO2) content in the atmosphere. The main indicator of air quality in Ukraine is the air pollution index (API). We have built regression models the relationship between indicators of NO2, which are measured by remote sensing methods and ground-based measurements of indicators. There have also been built regression models, the relationship between the data given to the land of NO2 and API. To simulate the relationship between the API and PM2.5 were used geographically weighted regression model, which allows to take into account the territorial differentiation between these indicators. As a result, the maps that show the distribution of the main types of pollution in the territory of Ukraine, were constructed. PM2.5 data modeling is complicated with using existing indicators, which requires a separate organization observation network for PM2.5 content in the atmosphere for sustainable development in cities of Ukraine.

  10. A remote sensing computer-assisted learning tool developed using the unified modeling language

    Science.gov (United States)

    Friedrich, J.; Karslioglu, M. O.

    The goal of this work has been to create an easy-to-use and simple-to-make learning tool for remote sensing at an introductory level. Many students struggle to comprehend what seems to be a very basic knowledge of digital images, image processing and image arithmetic, for example. Because professional programs are generally too complex and overwhelming for beginners and often not tailored to the specific needs of a course regarding functionality, a computer-assisted learning (CAL) program was developed based on the unified modeling language (UML), the present standard for object-oriented (OO) system development. A major advantage of this approach is an easier transition from modeling to coding of such an application, if modern UML tools are being used. After introducing the constructed UML model, its implementation is briefly described followed by a series of learning exercises. They illustrate how the resulting CAL tool supports students taking an introductory course in remote sensing at the author's institution.

  11. Detecting Mountain Peaks and Delineating Their Shapes Using Digital Elevation Models, Remote Sensing and Geographic Information Systems Using Autometric Methodological Procedures

    Directory of Open Access Journals (Sweden)

    Tomaž Podobnikar

    2012-03-01

    Full Text Available The detection of peaks (summits as the upper parts of mountains and the delineation of their shape is commonly confirmed by inspections carried out by mountaineers. In this study the complex task of peak detection and shape delineation is solved by autometric methodological procedures, more precisely, by developing relatively simple but innovative image-processing and spatial-analysis techniques (e.g., developing inventive variables using an annular moving window in remote sensing and GIS domains. The techniques have been integrated into automated morphometric methodological procedures. The concepts of peaks and their shapes (sharp, blunt, oblong, circular and conical were parameterized based on topographic and morphologic criteria. A geomorphologically high quality DEM was used as a fundamental dataset. The results, detected peaks with delineated shapes, have been integratively enriched with numerous independent datasets (e.g., with triangulated spot heights and information (e.g., etymological information, and mountaineering criteria have been implemented to improve the judgments. This holistic approach has proved the applicability of both highly standardized and universal parameters for the geomorphologically diverse Kamnik Alps case study area. Possible applications of this research are numerous, e.g., a comprehensive quality control of DEM or significantly improved models for the spatial planning proposes.

  12. Research plan for integrated ecosystem and pollutant monitoring at remote wilderness study sites

    International Nuclear Information System (INIS)

    Bruns, D.A.; Wiersma, G.B.

    1988-03-01

    This research plan outlines an approach to the measurement of pollutants and ecosystem parameters at remote, high-elevation, wilderness study sites. A multimedia, systems approach to environmental monitoring is emphasized. The primary purpose of the research is to apply and field test a technical report entitled ''Guidelines for measuring the physical, chemical, and biological condition of wilderness ecosystems.'' This document intended to provide Federal Land Managers with information to establish environmental monitoring programs in wilderness areas. To date, this monitoring document has yet to be evaluated under rigorous field conditions at a remote, high-elevation Rocky Mountain site. For the purpose of field testing approaches to monitoring of pollutants and ecosystems in remote, wilderness areas, evaluation criteria were developed. These include useability, cost-effectiveness, data variability, alternative approaches, ecosystems conceptual approach, and quality assurance. Both the Forest Service and INEL environmental monitoring techniques will be evaluated with these criteria. Another objective of this research plan is to obtain an integrated data base on pollutants and ecosystem structure and function at a remote study site. The methods tested in this project will be used to acquire these data from a systems approach. This includes multimedia monitoring of air and water quality, soils, and forest, stream, and lake ecosystems. 71 refs., 1 fig., 9 tabs

  13. Quantification of soil losses from tourist trails - use of Digital Elevation Models

    Science.gov (United States)

    Tomczyk, Aleksandra

    2010-05-01

    Tourism impacts in protected mountain areas are one of the main concerns for land managers. Impact to environment is most visible at locations of highly concentrated activities like tourist trails, campsites etc. The main indicators of the tourist trail degradation are: vegetation loss (trampling of vegetation cover), change of vegetation type and composition, widening of the trails, muddiness and soil erosion. The last one is especially significant, since it can cause serious transformation of the land surface. Such undesirable changes cannot be repaired without high-cost management activities, and, in some cases they can made the trails difficult and unsafe to use. Scientific understanding of soil erosion related to human impact can be useful for more effective management of the natural protected areas. The aim of this study was to use of digital elevation models (DEMs) to precisely quantify of soil losses from tourist trails. In the study precise elevation data were gathered in several test fields of 4 by 5 m spatial dimension. Measurements were taken in 13 test fields, located in two protected natural areas in south Poland: Gorce National Park and Popradzki Landscape Park. The measuring places were located on trails characterized by different slope, type of vegetation and type of use. Each test field was established by four special marks, firmly dug into the ground. Elevation data were measured with the electronic total station. Irregular elevation points were surveying with essential elements of surrounding terrain surface being included. Moreover, surveys in fixed profile lines were done. For each test field a set of 30 measurements in control points has been collected and these data provide the base for verification of digital elevation models. Average density of the surveying was 70 points per square meter (1000 - 1500 elevation points per each test fields). Surveys in each test field were carried out in August and September of 2008, June 2009 and August

  14. Modelling size-fractionated primary production in the Atlantic Ocean from remote sensing

    Science.gov (United States)

    Brewin, Robert J. W.; Tilstone, Gavin H.; Jackson, Thomas; Cain, Terry; Miller, Peter I.; Lange, Priscila K.; Misra, Ankita; Airs, Ruth L.

    2017-11-01

    Marine primary production influences the transfer of carbon dioxide between the ocean and atmosphere, and the availability of energy for the pelagic food web. Both the rate and the fate of organic carbon from primary production are dependent on phytoplankton size. A key aim of the Atlantic Meridional Transect (AMT) programme has been to quantify biological carbon cycling in the Atlantic Ocean and measurements of total primary production have been routinely made on AMT cruises, as well as additional measurements of size-fractionated primary production on some cruises. Measurements of total primary production collected on the AMT have been used to evaluate remote-sensing techniques capable of producing basin-scale estimates of primary production. Though models exist to estimate size-fractionated primary production from satellite data, these have not been well validated in the Atlantic Ocean, and have been parameterised using measurements of phytoplankton pigments rather than direct measurements of phytoplankton size structure. Here, we re-tune a remote-sensing primary production model to estimate production in three size fractions of phytoplankton (10 μm) in the Atlantic Ocean, using measurements of size-fractionated chlorophyll and size-fractionated photosynthesis-irradiance experiments conducted on AMT 22 and 23 using sequential filtration-based methods. The performance of the remote-sensing technique was evaluated using: (i) independent estimates of size-fractionated primary production collected on a number of AMT cruises using 14C on-deck incubation experiments and (ii) Monte Carlo simulations. Considering uncertainty in the satellite inputs and model parameters, we estimate an average model error of between 0.27 and 0.63 for log10-transformed size-fractionated production, with lower errors for the small size class (10 μm), and errors generally higher in oligotrophic waters. Application to satellite data in 2007 suggests the contribution of cells 2 μm to total

  15. Accounting for disturbance history in models: using remote sensing to constrain carbon and nitrogen pool spin-up.

    Science.gov (United States)

    Hanan, Erin J; Tague, Christina; Choate, Janet; Liu, Mingliang; Kolden, Crystal; Adam, Jennifer

    2018-03-24

    Disturbances such as wildfire, insect outbreaks, and forest clearing, play an important role in regulating carbon, nitrogen, and hydrologic fluxes in terrestrial watersheds. Evaluating how watersheds respond to disturbance requires understanding mechanisms that interact over multiple spatial and temporal scales. Simulation modeling is a powerful tool for bridging these scales; however, model projections are limited by uncertainties in the initial state of plant carbon and nitrogen stores. Watershed models typically use one of two methods to initialize these stores: spin-up to steady state or remote sensing with allometric relationships. Spin-up involves running a model until vegetation reaches equilibrium based on climate. This approach assumes that vegetation across the watershed has reached maturity and is of uniform age, which fails to account for landscape heterogeneity and non-steady-state conditions. By contrast, remote sensing, can provide data for initializing such conditions. However, methods for assimilating remote sensing into model simulations can also be problematic. They often rely on empirical allometric relationships between a single vegetation variable and modeled carbon and nitrogen stores. Because allometric relationships are species- and region-specific, they do not account for the effects of local resource limitation, which can influence carbon allocation (to leaves, stems, roots, etc.). To address this problem, we developed a new initialization approach using the catchment-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spin-up with the spatial fidelity of remote sensing. It uses remote sensing to define spatially explicit targets for one or several vegetation state variables, such as leaf area index, across a watershed. The model then simulates the growth of carbon and nitrogen stores until the defined targets are met for all locations. We evaluated this approach in a mixed pine-dominated watershed in

  16. Development of fatigue crack propagation models for engineering applications at elevated temperatures

    Energy Technology Data Exchange (ETDEWEB)

    Tomkins, B.

    1975-05-01

    The value of modelling the fatigue crack propagation process is discussed and current models are examined in the light of increasing knowledge of crack tip deformation. Elevated temperature fatigue is examined in detail as an area in which models could contribute significantly to engineering design. A model is developed which examines the role of time-dependent creep cavitation on the failure process in an interactive creep-fatigue situation. (auth)

  17. High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

    Science.gov (United States)

    Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

    2017-01-01

    Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness

  18. Eureka, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  19. Myrtle Beach, South Carolina 1/ Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Bar Harbor, Maine 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Santa Monica, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  2. San Diego, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Pago Pago, American Samoa 3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  4. Central Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Fort Bragg, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Port Townsend, Washington 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Tampa Bay 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Puget Sound 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. Key West, Florida 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Pensacola, Florida 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

  11. Palm Beach, Florida 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  12. Garibaldi, Oregon 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. Monterey, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Central Washington Coast 1/3 arc-second NAVD 88 Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. Robust Initial Wetness Condition Framework of an Event-Based Rainfall–Runoff Model Using Remotely Sensed Soil Moisture

    Directory of Open Access Journals (Sweden)

    Wooyeon Sunwoo

    2017-01-01

    Full Text Available Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC prior to a rainfall event. Soil moisture is one of the most important variables in rainfall–runoff modeling, and remotely sensed soil moisture is recognized as an effective way to improve the accuracy of runoff prediction. In this study, the IWC was evaluated based on remotely sensed soil moisture by using the Soil Conservation Service-Curve Number (SCS-CN method, which is one of the representative event-based models used for reducing the uncertainty of runoff prediction. Four proxy variables for the IWC were determined from the measurements of total rainfall depth (API5, ground-based soil moisture (SSMinsitu, remotely sensed surface soil moisture (SSM, and soil water index (SWI provided by the advanced scatterometer (ASCAT. To obtain a robust IWC framework, this study consists of two main parts: the validation of remotely sensed soil moisture, and the evaluation of runoff prediction using four proxy variables with a set of rainfall–runoff events in the East Asian monsoon region. The results showed an acceptable agreement between remotely sensed soil moisture (SSM and SWI and ground based soil moisture data (SSMinsitu. In the proxy variable analysis, the SWI indicated the optimal value among the proposed proxy variables. In the runoff prediction analysis considering various infiltration conditions, the SSM and SWI proxy variables significantly reduced the runoff prediction error as compared with API5 by 60% and 66%, respectively. Moreover, the proposed IWC framework with

  16. Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

    Science.gov (United States)

    Elmasri, B.; Rahman, A. F.

    2010-12-01

    Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation

  17. Destin, Florida 1/3 arc-second NAVD88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  18. Elfin Cove Alaska 1/3 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  19. Prince William Sound, Alaska 8 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  20. Simulation of spring wheat responses to elevated CO2 and temperature by using CERES-wheat crop model

    Directory of Open Access Journals (Sweden)

    H. LAURILA

    2008-12-01

    Full Text Available The CERES-wheat crop simulation model was used to estimate the changes in phenological development and yield production of spring wheat (Triticum aestivum L., cv. Polkka under different temperature and CO2 growing conditions. The effects of elevated temperature (3-4°C and CO2 concentration (700 ppm as expected for Finland in 2100 were simulated. The model was calibrated for long-day growing conditions in Finland. The CERES-wheat genetic coefficients for cv. Polkka were calibrated by using the MTT Agrifood Research Finland (MTT official variety trial data (1985-1990. Crop phenological development and yield measurements from open-top chamber experiments with ambient and elevated temperature and CO2 treatments were used to validate the model. Simulated mean grain yield under ambient temperature and CO2 conditions was 6.16 t ha-1 for potential growth (4.49 t ha-1 non-potential and 5.47 t ha-1 for the observed average yield (1992-1994 in ambient open-top chamber conditions. The simulated potential grain yield increased under elevated CO2 (700 ppm to 142% (167% non-potential from the simulated reference yield (100%, ambient temperature and CO2 350 ppm. Simulations for current sowing date and elevated temperature (3°C indicate accelerated anthesis and full maturity. According to the model estimations, potential yield decreased on average to 80.4% (76.8% non-potential due to temperature increase from the simulated reference. When modelling the concurrent elevated temperature and CO2 interaction, the increase in grain yield due to elevated CO2 was reduced by the elevated temperature. The combined CO2 and temperature effect increased the grain yield to 106% for potential growth (122% non-potential compared to the reference. Simulating the effects of earlier sowing, the potential grain yield increased under elevated temperature and CO2 conditions to 178% (15 days earlier sowing from 15 May, 700 ppm CO2, 3°C from the reference. Simulation results suggest

  1. Method and apparatus for positioning a satellite antenna from a remote well logging location

    International Nuclear Information System (INIS)

    Toellner, R.L.; Copland, G.V.

    1987-01-01

    An automatic system for positioning a Ku band microwave antenna accurately to within approximately 0.1 degrees to point at a particular satellite located among others having as close as 2 degree angular spacing in geosynchronous earth orbit from a remote location for establishing a Ku band microwave communication link from the remote location via the satellite is described comprising: a Ku band microwave antenna having a gimbal mount adapted to move in at least azimuth and elevation; means for driving the gimbal mount in azimuth and means for driving the gimbal mount in elevation; means for sensing a satellite signal detected by the antenna and for producing an output signal representative of the strength of the satellite signal and a separate output signal indicative of a satellite code or signature; inclinometer means for measuring the actual elevation angle of the elevation gimbal with respect to vertical and for generating an output signal representative thereof; means for measuring the azimuth angle of the azimuth gimbal relative to a fixed reference and for generating an output signal representative thereof; computer means capable of receiving input data comprising the earth latitude and longitude of a remote location and a satellite position and capable of receiving as inputs the strength representative signal; means for pointing the elevation gimbal to a fixed direction and for scanning the azimuth gimbal to a computed direction based on the earth latitude and longitude and the satellite position signals; and wherein the computer means further includes means capable of receiving the input signal indicative of a satellite code or signature and means for comparing the code or signature input signal with a predetermined reference code or signature signal in the memory of the computer means

  2. Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection

    Science.gov (United States)

    Rueda-Velasquez, Carlos Alberto

    Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources. Although various approaches formulated to model multidimensional data can in principle be applied to the inherent complexity of remotely sensed geospatial data, there are still challenging peculiarities that demand a precise characterization in the context of change detection, particularly in scenarios of fast changes. In the same vein, geospatial image streams do not fit appropriately in the standard Data Stream Management System (DSMS) approach because these systems mainly deal with tuple-based streams. Recognizing the necessity for a systematic effort to address the above issues, the work presented in this thesis is a concrete step toward the foundation and construction of an integrated Geospatial Image Stream Processing framework, GISP. First, we present a data and metadata model for remotely sensed image streams. We introduce a precise characterization of images and image streams in the context of remotely sensed geospatial data. On this foundation, we define spatially-aware temporal operators with a consistent semantics for change analysis tasks. We address the change detection problem in settings where multiple image stream sources are available, and thus we introduce an architectural design for the processing of geospatial image streams from multiple sources. With the aim of targeting collaborative scientific environments, we construct a realization of our architecture based on Kepler, a robust and widely used scientific workflow management system, as the underlying computational support; and open data and Web interface standards, as a means to facilitate the interoperability of GISP instances with other processing infrastructures and client applications. We demonstrate our

  3. Use of Remote Sensing and Dust Modelling to Evaluate Ecosystem Phenology and Pollen Dispersal

    Science.gov (United States)

    Luvall, Jeffrey C.; Sprigg, William A.; Watts, Carol; Shaw, Patrick

    2007-01-01

    The impact of pollen release and downwind concentrations can be evaluated utilizing remote sensing. Previous NASA studies have addressed airborne dust prediction systems PHAiRS (Public Health Applications in Remote Sensing) which have determined that pollen forecasts and simulations are possible. By adapting the deterministic dust model (as an in-line system with the National Weather Service operational forecast model) used in PHAiRS to simulate downwind dispersal of pollen, initializing the model with pollen source regions from MODIS, assessing the results a rapid prototype concept can be produced. We will present the results of our effort to develop a deterministic model for predicting and simulating pollen emission and downwind concentration to study details or phenology and meteorology and their dependencies, and the promise of a credible real time forecast system to support public health and agricultural science and service. Previous studies have been done with PHAiRS research, the use of NASA data, the dust model and the PHAiRS potential to improve public health and environmental services long into the future.

  4. Calibration of a semi-distributed hydrological model using discharge and remote sensing data

    NARCIS (Netherlands)

    Muthuwatta, L.P.; Muthuwatta, Lal P.; Booij, Martijn J.; Rientjes, T.H.M.; Rientjes, Tom H.M.; Bos, M.G.; Gieske, A.S.M.; Ahmad, Mobin-Ud-Din; Yilmaz, Koray; Yucel, Ismail; Gupta, Hoshin V.; Wagener, Thorsten; Yang, Dawen; Savenije, Hubert; Neale, Christopher; Kunstmann, Harald; Pomeroy, John

    2009-01-01

    The objective of this study is to present an approach to calibrate a semi-distributed hydrological model using observed streamflow data and actual evapotranspiration time series estimates based on remote sensing data. First, daily actual evapotranspiration is estimated using available MODIS

  5. New Orleans, Louisiana 1/3 Arc-second MLLW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  6. New Orleans, Louisiana 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  7. Panama City, Florida 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  8. Development of a remote controlled fatigue testing apparatus at elevated temperature in controlled environment

    International Nuclear Information System (INIS)

    Ohmi, Masao; Mimura, Hideaki; Ishii, Toshimitsu

    1996-02-01

    The fatigue characteristics of reactor structural materials at high temperature are necessary to be evaluated for ensuring the safety of the High Temperature engineering Test Reactor (HTTR). Especially, the high temperature test data on safety research such as low cycle fatigue property and crack propagation property for reactor pressure vessel material are important for the development of the HTTR. Responding to these needs, a remote controlled type fatigue testing machine has been developed and installed in a hot cell of JMTR Hot Laboratory to get the fatigue data of irradiated materials. The machine was developed modifying a commercially available electro-hydraulic servo type fatigue testing machine to withstand radiation and be remotely operated, and mainly consists of a testing machine frame, environment chamber, extensometer, actuator and vacuum exhaust system. It has been confirmed that the machine has good performance to obtain low cycle fatigue data through many demonstration tests on unirradiated and irradiated specimens. (author)

  9. Modeling Elevation and Aspect Controls on Emerging Ecohydrologic Processes and Ecosystem Patterns Using the Component-based Landlab Framework

    Science.gov (United States)

    Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

    2014-12-01

    Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.

  10. NOAA Coastal Services Center Coastal Inundation Digital Elevation Model: Philadelphia WFO - Pennsylvania

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Coastal Services Center's Sea Level...

  11. Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

    Science.gov (United States)

    Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

    2018-01-01

    In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

  12. Evaluating the Quality and Accuracy of TanDEM-X Digital Elevation Models at Archaeological Sites in the Cilician Plain, Turkey

    Directory of Open Access Journals (Sweden)

    Stefan Erasmi

    2014-10-01

    Full Text Available Satellite remote sensing provides a powerful instrument for mapping and monitoring traces of historical settlements and infrastructure, not only in distant areas and crisis regions. It helps archaeologists to embed their findings from field surveys into the broader context of the landscape. With the start of the TanDEM-X mission, spatially explicit 3D-information is available to researchers at an unprecedented resolution worldwide. We examined different experimental TanDEM-X digital elevation models (DEM that were processed from two different imaging modes (Stripmap/High Resolution Spotlight using the operational alternating bistatic acquisition mode. The quality and accuracy of the experimental DEM products was compared to other available DEM products and a high precision archaeological field survey. The results indicate the potential of TanDEM-X Stripmap (SM data for mapping surface elements at regional scale. For the alluvial plain of Cilicia, a suspected palaeochannel could be reconstructed. At the local scale, DEM products from TanDEM-X High Resolution Spotlight (HS mode were processed at 2 m spatial resolution using a merge of two monostatic/bistatic interferograms. The absolute and relative vertical accuracy of the outcome meet the specification of high resolution elevation data (HRE standards from the National System for Geospatial Intelligence (NSG at the HRE20 level.

  13. Site specific N application and remote sensing of cotton crop

    Science.gov (United States)

    A spatial variable nitrogen (N) rate trial and remote sensing of cotton crop was conducted during 2003 at Paul Good Farms, Mississippi, USA. The N rate trial consisted of three, 8-row transects at the east and west side of the field that were selected to represent variable soil and elevation feature...

  14. HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

    Science.gov (United States)

    Heumann, B. W.; Guichard, F.; Seaquist, J. W.

    2005-05-01

    The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

  15. Flood susceptibility analysis through remote sensing, GIS and frequency ratio model

    Science.gov (United States)

    Samanta, Sailesh; Pal, Dilip Kumar; Palsamanta, Babita

    2018-05-01

    Papua New Guinea (PNG) is saddled with frequent natural disasters like earthquake, volcanic eruption, landslide, drought, flood etc. Flood, as a hydrological disaster to humankind's niche brings about a powerful and often sudden, pernicious change in the surface distribution of water on land, while the benevolence of flood manifests in restoring the health of the thalweg from excessive siltation by redistributing the fertile sediments on the riverine floodplains. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in PNG. This research was conducted to investigate the usefulness of remote sensing, geographic information system and the frequency ratio (FR) for flood susceptibility mapping. FR model was used to handle different independent variables via weighted-based bivariate probability values to generate a plausible flood susceptibility map. This study was conducted in the Markham riverine precinct under Morobe province in PNG. A historical flood inventory database of PNG resource information system (PNGRIS) was used to generate 143 flood locations based on "create fishnet" analysis. 100 (70%) flood sample locations were selected randomly for model building. Ten independent variables, namely land use/land cover, elevation, slope, topographic wetness index, surface runoff, landform, lithology, distance from the main river, soil texture and soil drainage were used into the FR model for flood vulnerability analysis. Finally, the database was developed for areas vulnerable to flood. The result demonstrated a span of FR values ranging from 2.66 (least flood prone) to 19.02 (most flood prone) for the study area. The developed database was reclassified into five (5) flood vulnerability zones segmenting on the FR values, namely very low (less that 5.0), low (5.0-7.5), moderate (7.5-10.0), high (10.0-12.5) and very high susceptibility (more than 12.5). The result indicated that about 19.4% land area as `very high

  16. A Remote Sensing-Derived Corn Yield Assessment Model

    Science.gov (United States)

    Shrestha, Ranjay Man

    be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield

  17. Iowa Bedrock Surface Elevation

    Data.gov (United States)

    Iowa State University GIS Support and Research Facility — This Digital Elevation Model (DEM) of the bedrock surface elevation in Iowa was compiled using all available data, principally information from GEOSAM, supplemented...

  18. An Alternative Approach of Coastal Sea-Level Observation from Remote Sensing Imageries

    Science.gov (United States)

    Peng, H. Y.; Tseng, K. H.; Chung-Yen, K.; Lin, T. H.; Liao, W. H.; Chen, C. F.

    2017-12-01

    Coastal sea level can be observed as waterline changes along a coastal digital elevation model (DEM). However, most global DEMs, such as the Shuttle Radar Topography Mission (SRTM) DEM with 30 m resolution, provide limited coverage over coastal area due to the impermeability of radar signal over water and the lack of low-tide coincidence. Therefore, we aim to extend to coverage of SRTM DEM for the determination of intertidal zone and to monitor sea-level changes along the entire coastline of Taiwan (>1200km). We firstly collect historical cloud-free images since the 1980s, including Landsat series, SPOT series and Sentinel-2, and then calculate the Modified Normalized Difference Water Index (MNDWI) to identify water pixels. After computing water appearance probability of each pixel, it is converted into actual elevation by introducing the DTU10 tide model for high tide and low tide boundaries. A coastal DEM of intertidal zone is reconstructed and the accuracy is at 50 cm level as compared with in situ DEM built by an unmanned aerial vehicle (UAV). Finally, we use this product to define the up-to-date intertidal zone and estimate sea-level changes by using remote sensing snapshots.

  19. USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response

    Science.gov (United States)

    Jones, B. K.

    2014-12-01

    The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.

  20. The application of remote sensing to the development and formulation of hydrologic planning models

    Science.gov (United States)

    Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

    1977-01-01

    The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

  1. Evaluating the role of evapotranspiration remote sensing data in improving hydrological modeling predictability

    Science.gov (United States)

    Herman, Matthew R.; Nejadhashemi, A. Pouyan; Abouali, Mohammad; Hernandez-Suarez, Juan Sebastian; Daneshvar, Fariborz; Zhang, Zhen; Anderson, Martha C.; Sadeghi, Ali M.; Hain, Christopher R.; Sharifi, Amirreza

    2018-01-01

    As the global demands for the use of freshwater resources continues to rise, it has become increasingly important to insure the sustainability of this resources. This is accomplished through the use of management strategies that often utilize monitoring and the use of hydrological models. However, monitoring at large scales is not feasible and therefore model applications are becoming challenging, especially when spatially distributed datasets, such as evapotranspiration, are needed to understand the model performances. Due to these limitations, most of the hydrological models are only calibrated for data obtained from site/point observations, such as streamflow. Therefore, the main focus of this paper is to examine whether the incorporation of remotely sensed and spatially distributed datasets can improve the overall performance of the model. In this study, actual evapotranspiration (ETa) data was obtained from the two different sets of satellite based remote sensing data. One dataset estimates ETa based on the Simplified Surface Energy Balance (SSEBop) model while the other one estimates ETa based on the Atmosphere-Land Exchange Inverse (ALEXI) model. The hydrological model used in this study is the Soil and Water Assessment Tool (SWAT), which was calibrated against spatially distributed ETa and single point streamflow records for the Honeyoey Creek-Pine Creek Watershed, located in Michigan, USA. Two different techniques, multi-variable and genetic algorithm, were used to calibrate the SWAT model. Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73-0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error - observations standard deviation ratio (RSR) values <0.7 (0.39-0.52). However, the genetic algorithm technique was more effective with the ETa calibration while significantly

  2. Salinity modeling by remote sensing in central and southern Iraq

    Science.gov (United States)

    Wu, W.; Mhaimeed, A. S.; Platonov, A.; Al-Shafie, W. M.; Abbas, A. M.; Al-Musawi, H. H.; Khalaf, A.; Salim, K. A.; Chrsiten, E.; De Pauw, E.; Ziadat, F.

    2012-12-01

    Salinization, leading to a significant loss of cultivated land and crop production, is one of the most active land degradation phenomena in the Mesopotamian region in Iraq. The objectives of this study (under the auspices of ACIAR and Italian Government) are to investigate the possibility to use remote sensing technology to establish salinity-sensitive models which can be further applied to local and regional salinity mapping and assessment. Case studies were conducted in three pilot sites namely Musaib, Dujaila and West Garraf in the central and southern Iraq. Fourteen spring (February - April), seven June and four summer Landsat ETM+ images in the period 2009-2012, RapidEye data (April 2012), and 95 field EM38 measurements undertaken in this spring and summer, 16 relevant soil laboratory analysis result (Dujaila) were employed in this study. The procedure we followed includes: (1) Atmospheric correction using FLAASH model; (2) Multispectral transformation of a set of vegetation and non-vegetation indices such as GDVI (Generalized Difference Vegetation Index), NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), SAVI (Soil Adjusted Vegetation Index), SARVI (Soil Adjusted and Atmospherically Resistant Vegetation Index), NDII (Normalized Difference Infrared Index), Principal Components and surface temperature (T); (3) Derivation of the spring maximum (Musaib) and annual maximum (Dujaila and West Garraf) value in each pixel of each index of the observed period to avoid problems related to crop rotation (e.g. fallow) and the SLC-Off gaps in ETM+ images; (4) Extraction of the values of each vegetation and non-vegetation index corresponding to the field sampling locations (about 3 to 5 controversial samples very close to the roads or located in fallow were excluded); and (5) Coupling remote sensing indices with the available EM38 and soil electrical conductivity (EC) data using multiple linear least-square regression model at the confidence

  3. SU-E-T-675: Remote Dosimetry with a Novel PRESAGE Formulation

    International Nuclear Information System (INIS)

    Mein, S; Juang, T; Malcolm, J; Adamovics, J; Oldham, M

    2015-01-01

    Purpose: 3D-gel dosimetry provides high-resolution treatment validation; however, scanners aren’t widely available. In remote dosimetry, dosimeters are shipped out from a central base institution to a remote site for irradiation, then shipped back for scanning and analysis, affording a convenient service for treatment validation to institutions lacking the necessary equipment and resources. Previous works demonstrated the high-resolution performance and temporal stability of PRESAGE. Here the newest formulation is investigated for remote dosimetry use. Methods: A new formulation of PRESAGE was created with the aim of improved color stability post irradiation. Dose sensitivity was determined by irradiating cuvettes on a Varian Linac (6MV) from 0–15Gy and measuring change in optical density at 633nm. Sensitivity readings were tracked over time in a temperature control study to determine long-term stability. A large volume study was performed to evaluate the accuracy for remote dosimetry. A 1kg dosimeter was pre-scanned, irradiated on-site with an 8Gy 4field box treatment, post-scanned and shipped to Princess Margaret Hospital for remote reading on an identical scanner. Results: Dose sensitivities ranged from 0.0194–0.0295 ΔOD/(Gy*cm)—similar to previous formulations. Post-irradiated cuvettes stored at 10°C retained 100% initial sensitivity over 5 days and 98.6% over 10 weeks while cuvettes stored at room temperature fell to 95.8% after 5 days and 37.4% after 10 weeks. The immediate and 5-day scans of the 4field box dosimeter data was reconstructed, registered to the corresponding eclipse dose-distribution, and compared with analytical tools in CERR. Immediate and 5-day scans looked visually similar. Line profiles revealed close agreement aside from a slight elevation in dose at the edge in the 5-day readout. Conclusion: The remote dosimetry formulation exhibits excellent temporal stability in small volumes. While immediate and 5-day readout scans of large

  4. Developing the remote sensing-based water environmental model for monitoring alpine river water environment over Plateau cold zone

    Science.gov (United States)

    You, Y.; Wang, S.; Yang, Q.; Shen, M.; Chen, G.

    2017-12-01

    Alpine river water environment on the Plateau (such as Tibetan Plateau, China) is a key indicator for water security and environmental security in China. Due to the complex terrain and various surface eco-environment, it is a very difficult to monitor the water environment over the complex land surface of the plateau. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring river water environment on the Plateau, particularly in remote and inaccessible areas where are lack of in situ observations. In this study, we propose a remote sense-based monitoring model by using multi-platform remote sensing data for monitoring alpine river environment. In this study some parameterization methodologies based on satellite remote sensing data and field observations have been proposed for monitoring the water environmental parameters (including chlorophyll-a concentration (Chl-a), water turbidity (WT) or water clarity (SD), total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC)) over the china's southwest highland rivers, such as the Brahmaputra. First, because most sensors do not collect multiple observations of a target in a single pass, data from multiple orbits or acquisition times may be used, and varying atmospheric and irradiance effects must be reconciled. So based on various types of satellite data, at first we developed the techniques of multi-sensor data correction, atmospheric correction. Second, we also built the inversion spectral database derived from long-term remote sensing data and field sampling data. Then we have studied and developed a high-precision inversion model over the southwest highland river backed by inversion spectral database through using the techniques of multi-sensor remote sensing information optimization and collaboration. Third, take the middle reaches of the Brahmaputra river as the study area, we validated the key

  5. DARLA: Data Assimilation and Remote Sensing for Littoral Applications

    Science.gov (United States)

    Jessup, A.; Holman, R. A.; Chickadel, C.; Elgar, S.; Farquharson, G.; Haller, M. C.; Kurapov, A. L.; Özkan-Haller, H. T.; Raubenheimer, B.; Thomson, J. M.

    2012-12-01

    DARLA is 5-year collaborative project that couples state-of-the-art remote sensing and in situ measurements with advanced data assimilation (DA) modeling to (a) evaluate and improve remote sensing retrieval algorithms for environmental parameters, (b) determine the extent to which remote sensing data can be used in place of in situ data in models, and (c) infer bathymetry for littoral environments by combining remotely-sensed parameters and data assimilation models. The project uses microwave, electro-optical, and infrared techniques to characterize the littoral ocean with a focus on wave and current parameters required for DA modeling. In conjunction with the RIVET (River and Inlets) Project, extensive in situ measurements provide ground truth for both the remote sensing retrieval algorithms and the DA modeling. Our goal is to use remote sensing to constrain data assimilation models of wave and circulation dynamics in a tidal inlet and surrounding beaches. We seek to improve environmental parameter estimation via remote sensing fusion, determine the success of using remote sensing data to drive DA models, and produce a dynamically consistent representation of the wave, circulation, and bathymetry fields in complex environments. The objectives are to test the following three hypotheses: 1. Environmental parameter estimation using remote sensing techniques can be significantly improved by fusion of multiple sensor products. 2. Data assimilation models can be adequately constrained (i.e., forced or guided) with environmental parameters derived from remote sensing measurements. 3. Bathymetry on open beaches, river mouths, and at tidal inlets can be inferred from a combination of remotely-sensed parameters and data assimilation models. Our approach is to conduct a series of field experiments combining remote sensing and in situ measurements to investigate signature physics and to gather data for developing and testing DA models. A preliminary experiment conducted at

  6. Soil-landscape modelling using fuzzy c-means clustering of attribute data derived from a Digital Elevation Model (DEM).

    NARCIS (Netherlands)

    Bruin, de S.; Stein, A.

    1998-01-01

    This study explores the use of fuzzy c-means clustering of attribute data derived from a digital elevation model to represent transition zones in the soil-landscape. The conventional geographic model used for soil-landscape description is not able to properly deal with these. Fuzzy c-means

  7. An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

    International Nuclear Information System (INIS)

    Lebed, L; Qi, J; Heilman, P

    2012-01-01

    The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation. (letter)

  8. Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

    Science.gov (United States)

    Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

    2013-01-01

    In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

  9. Use of the Brandley-Terry Model to Quantify Association in Remotely Sensed Images

    NARCIS (Netherlands)

    Stein, A.; Aryal, J.; Gort, G.

    2005-01-01

    Thematic maps prepared from remotely sensed images require a statistical accuracy assessment. For this purpose, the$kappa$-statistic is often used. This statistic does not distinguish between whether one unit is classified as another, or vice versa. In this paper, the Bradley-Terry (BT) model is

  10. PROCESSING OF UAV BASED RANGE IMAGING DATA TO GENERATE DETAILED ELEVATION MODELS OF COMPLEX NATURAL STRUCTURES

    Directory of Open Access Journals (Sweden)

    T. K. Kohoutek

    2012-07-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre

  11. LBA-ECO LC-01 SRTM 90-Meter Digital Elevation Model, Northern Ecuadorian Amazon

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador...

  12. LBA-ECO LC-01 SRTM 90-Meter Digital Elevation Model, Northern Ecuadorian Amazon

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects....

  13. FAO-56 Dual Model Combined with Multi-Sensor Remote Sensing for Regional Evapotranspiration Estimations

    Directory of Open Access Journals (Sweden)

    Rim Amri

    2014-06-01

    Full Text Available The main goal of this study is to evaluate the potential of the FAO-56 dual technique for the estimation of regional evapotranspiration (ET and its constituent components (crop transpiration and soil evaporation, for two classes of vegetation (olives trees and cereals in the semi-arid region of the Kairouan plain in central Tunisia. The proposed approach combines the FAO-56 technique with remote sensing (optical and microwave, not only for vegetation characterization, as proposed in other studies but also for the estimation of soil evaporation, through the use of satellite moisture products. Since it is difficult to use ground flux measurements to validate remotely sensed data at regional scales, comparisons were made with the land surface model ISBA-A-gs which is a physical SVAT (Soil–Vegetation–Atmosphere Transfer model, an operational tool developed by Météo-France. It is thus shown that good results can be obtained with this relatively simple approach, based on the FAO-56 technique combined with remote sensing, to retrieve temporal variations of ET. The approach proposed for the daily mapping of evapotranspiration at 1 km resolution is approved in two steps, for the period between 1991 and 2007. In an initial step, the ISBA-A-gs soil moisture outputs are compared with ERS/WSC products. Then, the output of the FAO-56 technique is compared with the output generated by the SVAT ISBA-A-gs model.

  14. Optimisation modelling to assess cost of dietary improvement in remote Aboriginal Australia.

    Science.gov (United States)

    Brimblecombe, Julie; Ferguson, Megan; Liberato, Selma C; O'Dea, Kerin; Riley, Malcolm

    2013-01-01

    The cost and dietary choices required to fulfil nutrient recommendations defined nationally, need investigation, particularly for disadvantaged populations. We used optimisation modelling to examine the dietary change required to achieve nutrient requirements at minimum cost for an Aboriginal population in remote Australia, using where possible minimally-processed whole foods. A twelve month cross-section of population-level purchased food, food price and nutrient content data was used as the baseline. Relative amounts from 34 food group categories were varied to achieve specific energy and nutrient density goals at minimum cost while meeting model constraints intended to minimise deviation from the purchased diet. Simultaneous achievement of all nutrient goals was not feasible. The two most successful models (A & B) met all nutrient targets except sodium (146.2% and 148.9% of the respective target) and saturated fat (12.0% and 11.7% of energy). Model A was achieved with 3.2% lower cost than the baseline diet (which cost approximately AUD$13.01/person/day) and Model B at 7.8% lower cost but with a reduction in energy of 4.4%. Both models required very large reductions in sugar sweetened beverages (-90%) and refined cereals (-90%) and an approximate four-fold increase in vegetables, fruit, dairy foods, eggs, fish and seafood, and wholegrain cereals. This modelling approach suggested population level dietary recommendations at minimal cost based on the baseline purchased diet. Large shifts in diet in remote Aboriginal Australian populations are needed to achieve national nutrient targets. The modeling approach used was not able to meet all nutrient targets at less than current food expenditure.

  15. Optimisation modelling to assess cost of dietary improvement in remote Aboriginal Australia.

    Directory of Open Access Journals (Sweden)

    Julie Brimblecombe

    Full Text Available The cost and dietary choices required to fulfil nutrient recommendations defined nationally, need investigation, particularly for disadvantaged populations.We used optimisation modelling to examine the dietary change required to achieve nutrient requirements at minimum cost for an Aboriginal population in remote Australia, using where possible minimally-processed whole foods.A twelve month cross-section of population-level purchased food, food price and nutrient content data was used as the baseline. Relative amounts from 34 food group categories were varied to achieve specific energy and nutrient density goals at minimum cost while meeting model constraints intended to minimise deviation from the purchased diet.Simultaneous achievement of all nutrient goals was not feasible. The two most successful models (A & B met all nutrient targets except sodium (146.2% and 148.9% of the respective target and saturated fat (12.0% and 11.7% of energy. Model A was achieved with 3.2% lower cost than the baseline diet (which cost approximately AUD$13.01/person/day and Model B at 7.8% lower cost but with a reduction in energy of 4.4%. Both models required very large reductions in sugar sweetened beverages (-90% and refined cereals (-90% and an approximate four-fold increase in vegetables, fruit, dairy foods, eggs, fish and seafood, and wholegrain cereals.This modelling approach suggested population level dietary recommendations at minimal cost based on the baseline purchased diet. Large shifts in diet in remote Aboriginal Australian populations are needed to achieve national nutrient targets. The modeling approach used was not able to meet all nutrient targets at less than current food expenditure.

  16. Volcanic Plume Elevation Model Derived From Landsat 8: examples on Holuhraun (Iceland) and Mount Etna (Italy)

    Science.gov (United States)

    de Michele, Marcello; Raucoules, Daniel; Arason, Þórður; Spinetti, Claudia; Corradini, Stefano; Merucci, Luca

    2016-04-01

    The retrieval of both height and velocity of a volcanic plume is an important issue in volcanology. As an example, it is known that large volcanic eruptions can temporarily alter the climate, causing global cooling and shifting precipitation patterns; the ash/gas dispersion in the atmosphere, their impact and lifetime around the globe, greatly depends on the injection altitude. Plume height information is critical for ash dispersion modelling and air traffic security. Furthermore, plume height during explosive volcanism is the primary parameter for estimating mass eruption rate. Knowing the plume altitude is also important to get the correct amount of SO2 concentration from dedicated spaceborne spectrometers. Moreover, the distribution of ash deposits on ground greatly depends on the ash cloud altitude, which has an impact on risk assessment and crisis management. Furthermore, a spatially detailed plume height measure could be used as a hint for gas emission rate estimation and for ash plume volume researches, which both have an impact on climate research, air quality assessment for aviation and finally for the understanding of the volcanic system itself as ash/gas emission rates are related to the state of pressurization of the magmatic chamber. Today, the community mainly relies on ground based measurements but often they can be difficult to collect as by definition volcanic areas are dangerous areas (presence of toxic gases) and can be remotely situated and difficult to access. Satellite remote sensing offers a comprehensive and safe way to estimate plume height. Conventional photogrammetric restitution based on satellite imagery fails in precisely retrieving a plume elevation model as the plume own velocity induces an apparent parallax that adds up to the standard parallax given by the stereoscopic view. Therefore, measurements based on standard satellite photogrammeric restitution do not apply as there is an ambiguity in the measurement of the plume position

  17. Application of a two-pool model to soil carbon dynamics under elevated CO2.

    Science.gov (United States)

    van Groenigen, Kees Jan; Xia, Jianyang; Osenberg, Craig W; Luo, Yiqi; Hungate, Bruce A

    2015-12-01

    Elevated atmospheric CO2 concentrations increase plant productivity and affect soil microbial communities, with possible consequences for the turnover rate of soil carbon (C) pools and feedbacks to the atmosphere. In a previous analysis (Van Groenigen et al., 2014), we used experimental data to inform a one-pool model and showed that elevated CO2 increases the decomposition rate of soil organic C, negating the storage potential of soil. However, a two-pool soil model can potentially explain patterns of soil C dynamics without invoking effects of CO2 on decomposition rates. To address this issue, we refit our data to a two-pool soil C model. We found that CO2 enrichment increases decomposition rates of both fast and slow C pools. In addition, elevated CO2 decreased the carbon use efficiency of soil microbes (CUE), thereby further reducing soil C storage. These findings are consistent with numerous empirical studies and corroborate the results from our previous analysis. To facilitate understanding of C dynamics, we suggest that empirical and theoretical studies incorporate multiple soil C pools with potentially variable decomposition rates. © 2015 John Wiley & Sons Ltd.

  18. San Francisco Bay, California 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  19. Palm Beach, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  20. Key West, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  1. Orange County, California 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

  2. Pago Pago, American Samoa 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  3. Astoria, Oregon 1/3 arc-second MHW Coastal Digital Elevation Model Vers.3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

  4. Port Townsend, Washington 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  5. Santa Monica, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  6. Mayaguez, Puerto Rico 2006 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  7. Fort Bragg, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  8. Myrtle Beach, South Carolina 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  9. South Padre Island, Texas 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  10. Crescent City, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  11. San Juan, Puerto Rico 1/9 arc-second PRVD Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Centers for Environmental Information (NCEI) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These...

  12. San Diego, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  13. St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Mayaguez, Puerto Rico 2007 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. Morehead City, North Carolina 1/3 Arc-second MHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  16. Port San Luis, California 1/3 Arc-second MWH Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. Bar Harbor, Maine 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  18. A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

    Science.gov (United States)

    Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

    2017-06-22

    With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

  19. Synergistic linkage between remote sensing and biophysical models for estimating plant ecophysiological and ecosystem processes

    International Nuclear Information System (INIS)

    Inoue, Y.; Olioso, A.

    2004-01-01

    Abstract Information on the ecological and physiological status of crops is essential for growth diagnostics and yield prediction. Within-field or between-field spatial information is required, especially with the recent trend toward precision agriculture, which seeks the efficient use of agrochemicals, water, and energy. The study of carbon and nitrogen cycles as well as environmental management on local and regional scales requires assessment of the spatial variability of biophysical and ecophysiological variables, scaling up of which is also needed for scientific and decision-making purposes. Remote sensing has great potential for these applications because it enables wide-area non-destructive, and real-time acquisition of information about ecophysiological conditions of vegetation. With recent advances in sensor technology, a variety of electromagnetic signatures, such as hyperspectral reflectance, thermal-infrared temperature, and microwave backscattering coefficients, can be acquired for both plants and ecosystems using ground-based, airborne, and satellite platforms. Their spatial and temporal resolutions have both recently been improved. This article reviews the state of the art in the remote sensing of plant ecophysiological data, with special emphasis on the synergy between remote sensing signatures and biophysical and ecophysiological process models. Several case studies for the optical, thermal, and microwave domains have demonstrated the potential of this synergistic linkage. Remote sensing and process modeling methods complement each other when combined synergistically. Further research on this approach is needed f or a wide range of ecophysiological and ecosystem studies, as well as for practical crop management

  20. Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches

    Directory of Open Access Journals (Sweden)

    Daniel Asare-Kyei

    2015-07-01

    Full Text Available Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI. Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.

  1. A coupled remote sensing and the Surface Energy Balance with Topography Algorithm (SEBTA to estimate actual evapotranspiration over heterogeneous terrain

    Directory of Open Access Journals (Sweden)

    Z. Q. Gao

    2011-01-01

    Full Text Available Evapotranspiration (ET may be used as an ecological indicator to address the ecosystem complexity. The accurate measurement of ET is of great significance for studying environmental sustainability, global climate changes, and biodiversity. Remote sensing technologies are capable of monitoring both energy and water fluxes on the surface of the Earth. With this advancement, existing models, such as SEBAL, S_SEBI and SEBS, enable us to estimate the regional ET with limited temporal and spatial coverage in the study areas. This paper extends the existing modeling efforts with the inclusion of new components for ET estimation at different temporal and spatial scales under heterogeneous terrain with varying elevations, slopes and aspects. Following a coupled remote sensing and surface energy balance approach, this study emphasizes the structure and function of the Surface Energy Balance with Topography Algorithm (SEBTA. With the aid of the elevation and landscape information, such as slope and aspect parameters derived from the digital elevation model (DEM, and the vegetation cover derived from satellite images, the SEBTA can account for the dynamic impacts of heterogeneous terrain and changing land cover with some varying kinetic parameters (i.e., roughness and zero-plane displacement. Besides, the dry and wet pixels can be recognized automatically and dynamically in image processing thereby making the SEBTA more sensitive to derive the sensible heat flux for ET estimation. To prove the application potential, the SEBTA was carried out to present the robust estimates of 24 h solar radiation over time, which leads to the smooth simulation of the ET over seasons in northern China where the regional climate and vegetation cover in different seasons compound the ET calculations. The SEBTA was validated by the measured data at the ground level. During validation, it shows that the consistency index reached 0.92 and the correlation coefficient was 0.87.

  2. Preface: Remote Sensing in Coastal Environments

    Directory of Open Access Journals (Sweden)

    Deepak R. Mishra

    2016-08-01

    Full Text Available The Special Issue (SI on “Remote Sensing in Coastal Environments” presents a wide range of articles focusing on a variety of remote sensing models and techniques to address coastal issues and processes ranging for wetlands and water quality to coral reefs and kelp habitats. The SI is comprised of twenty-one papers, covering a broad range of research topics that employ remote sensing imagery, models, and techniques to monitor water quality, vegetation, habitat suitability, and geomorphology in the coastal zone. This preface provides a brief summary of each article published in the SI.

  3. Modelling population distribution using remote sensing imagery and location-based data

    Science.gov (United States)

    Song, J.; Prishchepov, A. V.

    2017-12-01

    Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models

  4. Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

    Science.gov (United States)

    Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

    2010-12-01

    There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

  5. Prince William Sound, Alaska 8/3 Arc-second MHHW Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  6. Perryville and Ivanof Bay, Alaska 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) to support individual coastal States as part of the...

  7. Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks

    Science.gov (United States)

    Su, Jin-He; Piao, Ying-Chao; Luo, Ze; Yan, Bao-Ping

    2018-01-01

    Simple Summary The understanding of the spatio-temporal distribution of the species habitats would facilitate wildlife resource management and conservation efforts. Existing methods have poor performance due to the limited availability of training samples. More recently, location-aware sensors have been widely used to track animal movements. The aim of the study was to generate suitability maps of bar-head geese using movement data coupled with environmental parameters, such as remote sensing images and temperature data. Therefore, we modified a deep convolutional neural network for the multi-scale inputs. The results indicate that the proposed method can identify the areas with the dense goose species around Qinghai Lake. In addition, this approach might also be interesting for implementation in other species with different niche factors or in areas where biological survey data are scarce. Abstract With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results

  8. Use of upscaled elevation and surface roughness data in two-dimensional surface water models

    Science.gov (United States)

    Hughes, J.D.; Decker, J.D.; Langevin, C.D.

    2011-01-01

    In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.

  9. Where’s the Ground Surface? – Elevation Bias in LIDAR-derived Digital Elevation Models Due to Dense Vegetation in Oregon Tidal Marshes

    Science.gov (United States)

    Light Detection and Ranging (LIDAR) is a powerful resource for coastal and wetland managers and its use is increasing. Vegetation density and other land cover characteristics influence the accuracy of LIDAR-derived ground surface digital elevation models; however the degree to wh...

  10. Remote Sensing Estimates of Glacier Mass Balance Changes in the Himalayas of Nepal

    Science.gov (United States)

    Ambinakudige, S.; Joshi, K.

    2011-12-01

    Mass balance changes of glaciers are important indicators of climate change. There are only 30 'reference' glaciers in the world that have continuous mass balance data with world glacier monitoring service since 1976. Especially, Himalayan glaciers are conspicuously absent from global mass balance records. This shows the urgent need for mass balance data for glaciers throughout the world. In this study, we estimated mass balance of some major glaciers in the Sagarmatha National Park (SNP) in Nepal using remote sensing applications. The SNP is one of the densest glaciated regions in the Himalayan range consisting approximately 296 glacial lakes. The region has experienced several glacial lake outburst floods (GLOFs) in recent years, causing extensive damage to local infrastructure and loss of human life. In general, mass balance is determined at seasonal or yearly intervals. Because of the rugged and difficult terrain of the Himalayan region, there are only a few field based measurements of mass balance available. Moreover, there are only few cases where the applications of remote sensing methods were used to calculate mass balance of the Himalayan glaciers due to the lack of accurate elevation data. Studies have shown that estimations of mass balance using remote sensing applications were within the range of field-based mass balance measurements from the same period. This study used ASTER VNIR, 3N (nadir view) and 3B (backward view) bands to generate Digital Elevation Models (DEMs) for the SNP area. 3N and 3B bands generate an along track stereo pair with a base-to-height (B/H) ratio of about 0.6. Accurate measurement of ground control points (GCPs), their numbers and distribution are important inputs in creating accurate DEMs. Because of the availability of topographic maps for this area, we were able to provide very accurate GCPs, in sufficient numbers and distribution. We created DEMs for the years 2002, 2003, 2004 and 2005 using ENVI DEM extraction tool. Bands

  11. Characterizing the Surface Connectivity of Depressional Wetlands: Linking Remote Sensing and Hydrologic Modeling Approaches

    Science.gov (United States)

    Christensen, J.; Evenson, G. R.; Vanderhoof, M.; Wu, Q.; Golden, H. E.; Lane, C.

    2017-12-01

    Surface connectivity of wetlands in the 700,000 km2 Prairie Pothole Region of North America (PPR) can occur through fill-spill and fill-merge mechanisms, with some wetlands eventually spilling into stream/river systems. These wetland-to-wetland and wetland-to-stream connections vary both spatially and temporally in PPR watersheds and are important to understanding hydrologic and biogeochemical processes in the landscape. To explore how to best characterize spatial and temporal variability in aquatic connectivity, we compared three approaches, 1) hydrological modeling alone, 2) remotely-sensed data alone, and 3) integrating remotely-sensed data into a hydrological model. These approaches were tested in the Pipestem Creek Watershed, North Dakota across a drought to deluge cycle (1990-2011). A Soil and Water Assessment Tool (SWAT) model was modified to include the water storage capacity of individual non-floodplain wetlands identified in the National Wetland Inventory (NWI) dataset. The SWAT-NWI model simulated the water balance and storage of each wetland and the temporal variability of their hydrologic connections between wetlands during the 21-year study period. However, SWAT-NWI only accounted for fill-spill, and did not allow for the expansion and merging of wetlands situated within larger depressions. Alternatively, we assessed the occurrence of fill-merge mechanisms using inundation maps derived from Landsat images on 19 cloud-free days during the 21 years. We found fill-merge mechanisms to be prevalent across the Pipestem watershed during times of deluge. The SWAT-NWI model was then modified to use LiDAR-derived depressions that account for the potential maximum depression extent, including the merging of smaller wetlands. The inundation maps were used to evaluate the ability of the SWAT-depression model to simulate fill-merge dynamics in addition to fill-spill dynamics throughout the study watershed. Ultimately, using remote sensing to inform and validate

  12. Modeling and measurement of boiling point elevation during water vaporization from aqueous urea for SCR applications

    International Nuclear Information System (INIS)

    Dan, Ho Jin; Lee, Joon Sik

    2016-01-01

    Understanding of water vaporization is the first step to anticipate the conversion process of urea into ammonia in the exhaust stream. As aqueous urea is a mixture and the urea in the mixture acts as a non-volatile solute, its colligative properties should be considered during water vaporization. The elevation of boiling point for urea water solution is measured with respect to urea mole fraction. With the boiling-point elevation relation, a model for water vaporization is proposed underlining the correction of the heat of vaporization of water in the urea water mixture due to the enthalpy of urea dissolution in water. The model is verified by the experiments of water vaporization as well. Finally, the water vaporization model is applied to the water vaporization of aqueous urea droplets. It is shown that urea decomposition can begin before water evaporation finishes due to the boiling-point elevation

  13. Modeling and measurement of boiling point elevation during water vaporization from aqueous urea for SCR applications

    Energy Technology Data Exchange (ETDEWEB)

    Dan, Ho Jin; Lee, Joon Sik [Seoul National University, Seoul (Korea, Republic of)

    2016-03-15

    Understanding of water vaporization is the first step to anticipate the conversion process of urea into ammonia in the exhaust stream. As aqueous urea is a mixture and the urea in the mixture acts as a non-volatile solute, its colligative properties should be considered during water vaporization. The elevation of boiling point for urea water solution is measured with respect to urea mole fraction. With the boiling-point elevation relation, a model for water vaporization is proposed underlining the correction of the heat of vaporization of water in the urea water mixture due to the enthalpy of urea dissolution in water. The model is verified by the experiments of water vaporization as well. Finally, the water vaporization model is applied to the water vaporization of aqueous urea droplets. It is shown that urea decomposition can begin before water evaporation finishes due to the boiling-point elevation.

  14. Remote ischaemic preconditioning and prevention of cerebral injury.

    Science.gov (United States)

    Rehni, Ashish K; Shri, Richa; Singh, Manjeet

    2007-03-01

    Bilateral carotid artery occlusion of 10 min followed by reperfusion for 24 hr was employed in present study to produce ischaemia and reperfusion induced cerebral injury in mice. Cerebral infarct size was measured using triphenyltetrazolium chloride staining. Short-term memory was evaluated using elevated plus maze. Inclined beam walking test was employed to assess motor incoordination. Bilateral carotid artery occlusion followed by reperfusion produced cerebral infarction and impaired short-term memory, motor co-ordination and lateral push response. A preceding episode of mesenteric artery occlusion for 15 min and reperfusion of 15 min (remote mesenteric ischaemic preconditioning) prevented markedly ischaemia-reperfusion-induced cerebral injury measured in terms of infarct size, loss of short-term memory, motor coordination and lateral push response. Glibenclamide (5 mg/kg, iv) a KATP channel blocker and caffeine (7 mg/kg, iv) an adenosine receptor blocker attenuated the neuroprotective effect of remote mesenteric ischaemic preconditioning. It may be concluded that neuroprotective effect of remote mesenteric ischaemic preconditioning may be due to activation of adenosine receptors and consequent activation of KATP channels in mice.

  15. A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

    Science.gov (United States)

    Slater, Thomas; Shepherd, Andrew; McMillan, Malcolm; Muir, Alan; Gilbert, Lin; Hogg, Anna E.; Konrad, Hannes; Parrinello, Tommaso

    2018-05-01

    We present a new digital elevation model (DEM) of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are -0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m - a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

  16. Rapid Prototyping Modules for Remote Engineering Applications

    Directory of Open Access Journals (Sweden)

    Karsten Henke

    2008-07-01

    Full Text Available This contribution describes the concept and implementation for an integration of microcontroller and FPGA based Rapid Prototyping modules into a Remote Lab system. This implementation enables a Web-based access to electro-mechanical models. A student uploads a source file implementation to the Remote Lab server in order to test an implementation directly within a hardware environment. The Remote Lab server offers the interfaces to integrate specific project and hardware plug-ins. These plug-ins access a hardware specific software environment to automatically compile and program the resulting firmware. To stimulate this design, the Remote Lab server exchanges digital signals via a serial interface. To allow the student to compare architectures of different designs using the same hardware model, a specific controller (using the Remote Lab interface can be selected. For this, an IP-based multiplexer provides the control connection between the respective controller and the hardware model. In our contribution we would like to give examples of such a complex design task and how the students can use different tools during several design steps.

  17. Impact of atmospheric components on solar clear-sky models at different elevation: Case study Canary Islands

    International Nuclear Information System (INIS)

    Antonanzas-Torres, F.; Antonanzas, J.; Urraca, R.; Alia-Martinez, M.; Martinez-de-Pison, F.J.

    2016-01-01

    Highlights: • Assessment on the performance of solar clear-sky models at different altitude. • SOLIS and REST2 clear-sky models were superior with fine atmospheric inputs. • ESRA proved more robust with low spatial resolution atmospheric inputs. • Over-estimation occurred at the lower site when using inputs from the upper site. - Abstract: The estimation of clear-sky solar irradiance via clear-sky models depends on reliable values of aerosol optical depth, water vapor and ozone content. These atmospheric variables are rarely on-site measured and are generally provided as gridded estimates in very low spatial resolution (1°). The high spatial variability of atmospheric variables within the grid resolution (pixel) leads to important errors in those areas with great atmospheric variability, such as in mountainous regions. In this paper, the performance of three clear-sky solar irradiance models was evaluated in a site with especially great elevation range, the Izana station from the Baseline Surface Radiation Network (Tenerife, Canary Islands) located at a high elevation (2373 m) and just 14 km from the ocean. Aerosols data were obtained from measurements from the Aerosol Robotic Network (AERONET) at the same site. The evaluation was also compared with global horizontal irradiance estimations with clear-sky models in the Guimar station, located at a lower elevation (156 m) and only 11.5 km away from Izana. Results showed a strong influence of elevation on solar radiation estimation under clear-sky conditions.

  18. A Distributed Multi-dimensional SOLAP Model of Remote Sensing Data and Its Application in Drought Analysis

    Directory of Open Access Journals (Sweden)

    LI Jiyuan

    2014-06-01

    Full Text Available SOLAP (Spatial On-Line Analytical Processing has been applied to multi-dimensional analysis of remote sensing data recently. However, its computation performance faces a considerable challenge from the large-scale dataset. A geo-raster cube model extended by Map-Reduce is proposed, which refers to the application of Map-Reduce (a data-intensive computing paradigm in the OLAP field. In this model, the existing methods are modified to adapt to distributed environment based on the multi-level raster tiles. Then the multi-dimensional map algebra is introduced to decompose the SOLAP computation into multiple distributed parallel map algebra functions on tiles under the support of Map-Reduce. The drought monitoring by remote sensing data is employed as a case study to illustrate the model construction and application. The prototype is also implemented, and the performance testing shows the efficiency and scalability of this model.

  19. Panama City, Florida 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico....

  20. Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing

    Science.gov (United States)

    Twigt, Daniel J.; de Goede, Erik D.; Schrama, Ernst J. O.; Gerritsen, Herman

    2007-10-01

    The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow

  1. Classification of permafrost active layer depth from remotely sensed and topographic evidence

    International Nuclear Information System (INIS)

    Peddle, D.R.; Franklin, S.E.

    1993-01-01

    The remote detection of permafrost (perennially frozen ground) has important implications to environmental resource development, engineering studies, natural hazard prediction, and climate change research. In this study, the authors present results from two experiments into the classification of permafrost active layer depth within the zone of discontinuous permafrost in northern Canada. A new software system based on evidential reasoning was implemented to permit the integrated classification of multisource data consisting of landcover, terrain aspect, and equivalent latitude, each of which possessed different formats, data types, or statistical properties that could not be handled by conventional classification algorithms available to this study. In the first experiment, four active layer depth classes were classified using ground based measurements of the three variables with an accuracy of 83% compared to in situ soil probe determination of permafrost active layer depth at over 500 field sites. This confirmed the environmental significance of the variables selected, and provided a baseline result to which a remote sensing classification could be compared. In the second experiment, evidence for each input variable was obtained from image processing of digital SPOT imagery and a photogrammetric digital elevation model, and used to classify active layer depth with an accuracy of 79%. These results suggest the classification of evidence from remotely sensed measures of spectral response and topography may provide suitable indicators of permafrost active layer depth

  2. A new, high-resolution digital elevation model of Greenland fully validated with airborne laser altimeter data

    DEFF Research Database (Denmark)

    Bamber, J.L.; Ekholm, Simon; Krabill, W.B.

    2001-01-01

    were corrected for a slope-dependent bias that had been identified in a previous study. The radar altimetry was supplemented with stereophotogrammetric data sets, synthetic aperture radar interferometry, and digitized cartographic maps over regions of bare rock and where gaps in the satellite altimeter...... the bare rock areas the accuracy ranged from 20 to 200 m, dependent on the data source available. The new digital elevation model was used as an input data set for a positive degree day model of ablation. The new elevation model was found to reduce ablation by only 2% compared with using an older, 2.5-km...

  3. Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

    KAUST Repository

    Lellmann, Jan

    2013-01-01

    We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.

  4. High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

    Directory of Open Access Journals (Sweden)

    Gerald Forkuor

    Full Text Available Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat, terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC, soil organic carbon (SOC and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR, random forest regression (RFR, support vector machine (SVM, stochastic gradient boosting (SGB-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices

  5. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Charleston WFO (Georgia)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

  6. RADAR INTERFEROMETRY APPLICATION FOR DIGITAL ELEVATION MODEL IN MOUNT BROMO, INDONESIA

    Directory of Open Access Journals (Sweden)

    Noorlaila Hayati

    2015-06-01

    Full Text Available This paper reviewed the result and processing of digital elevation model (DEM using L-Band ALOS PALSAR data and two-pass radar interferometry method in Bromo Mountain region. Synthetic Aperture Radar is an advanced technology that has been used to monitor deformation, land cover change, image detection and especially topographic information such as DEM.  We used two scenes of SAR imageries to generate DEM extraction which assumed there is no deformation effect between two acquisitions. We could derive topographic information using phase difference by combining two single looks complex (SLC images called focusing process. The next steps were doing interferogram generation, phase unwrapping and geocoding. DEM-InSAR was compared to SRTM 90m that there were significant elevation differences between two DEMs such as smoothing surface and detail topographic. Particularly for hilly areas, DEM-InSAR showed better quality than SRTM 90 m where the elevation could have 25.94 m maximum gap. Although the processing involved adaptive filter to amplify the phase signal, we concluded that InSAR DEM result still had error noise because of signal wavelength, incidence angle, SAR image relationship, and only using ascending orbit direction.

  7. Synergistic effects of remote perconditioning with terminal blood cardioplegia in an in vivo piglet model.

    Science.gov (United States)

    Abe, Takayuki; Morita, Kiyozo; Shinohara, Gen; Hashimoto, Kazuhiro; Nishikawa, Masako

    2017-09-01

    This study tested the hypothesis that remote perconditioning offers effective and synergistic cardioprotection to terminal warm blood cardioplegia for prompt ventricular recovery after prolonged cardioplegic arrest in an in vivo piglet model. Twenty-four piglets were subjected to 120 min of single-dose cardioplegic arrest and were divided into 4 groups according to the mode of reperfusion: control (simple aortic unclamp), remote perconditioning, terminal warm blood cardioplegia or remote perconditioning + terminal warm blood cardioplegia; remote perconditioning (4 cycles of 5-min ischaemia-reperfusion of the lower limb) was applied prior to aortic unclamping. Left ventricular systolic and diastolic functions were assessed by pressure-volume loop analysis at baseline and after 60 min of reperfusion. Biochemical injury was evaluated by plasma troponin T level. The control group showed decreased end-systolic elastance, preload recruitable stroke work and inverse of end-diastolic pressure-volume relationship of 51.3 ± 14.0%, 46.1 ± 22.5% and 34.8 ± 14.9%, respectively. Percentage recovery of end-systolic elastance and preload recruitable stroke work were significantly better with terminal warm blood cardioplegia (with or without remote perconditioning) (end-systolic elastance: 95% confidence interval, 38.6-84.1; preload recruitable stroke work: 95% confidence interval, 0.4-54.3). Percentage recovery of inverse of end-diastolic pressure-volume relationship was significantly better in the remote perconditioning groups (with or without terminal warm blood cardioplegia) (95% confidence interval, 1.6-41.6). No synergistic effects of remote perconditioning and terminal warm blood cardioplegia on troponin T release were noted. Remote perconditioning offers promising synergistic cardioprotection to terminal warm blood cardioplegia, implicating potential clinical benefit by contributing to prompt left ventricular functional recovery during paediatric open

  8. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    2007-01-01

    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  9. Remote sensing and modeling to fill the “gap” in missing natural capital

    Science.gov (United States)

    Bagstad, Kenneth J.; Willcock, Simon; Lange, Glenn-Marie

    2018-01-01

    This chapter reviews recent advances in remote sensing and environmental modeling that address the first step in ecosystem accounting: biophysical quantification of ecosystem services. The chapter focuses on those ecosystem services in which the most rapid advances are likely, including crop pollination, sediment regulation, carbon sequestration and storage, and coastal flood regulation. The discussion highlights data sources and modeling approaches that can support wealth accounting, next steps for mapping and biophysical modeling of ecosystem services, and considerations for integrating biophysical modeling and monetary valuation. These approaches could make the inclusion of some ecosystem services increasingly feasible in future versions of wealth accounts.

  10. Adaptable imaging package for remote vehicles

    Directory of Open Access Journals (Sweden)

    Jean-Luc Liardon

    2017-10-01

    Full Text Available An easy-to-customize, low-cost solution for remote imagery is described. The system, denoted ImPROV (Imaging Package for Remote Vehicles, supports multiple cameras, live streaming, long-range encrypted communication using mobile networks, positioning and time-stamped imagery, etc. The adaptability of the system is demonstrated by its deployment on different remotely operated or autonomous vehicles, which include model aircraft, drones, balloon, kite and a submarine.

  11. Calibration of a distributed hydrologic model for six European catchments using remote sensing data

    Science.gov (United States)

    Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

    2017-12-01

    While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

  12. Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images

    Directory of Open Access Journals (Sweden)

    Monica Pinardi

    2015-04-01

    Full Text Available Shallow fluvial lakes are dynamic ecosystems shaped by physical and biological factors and characterized by the coexistence of phytoplankton and macrophytes. Due to multiple interplaying factors, understanding the distribution of phytoplankton in fluvial lakes is a complex but fundamental issue, in the context of increasing eutrophication, climate change, and multiple water uses. We analyze the distribution of phytoplankton by combining remotely sensed maps of chlorophyll-a with a hydrodynamic model in a dammed fluvial lake (Mantua Superior Lake, Northern Italy. The numerical simulation of different conditions shows that the main hydrodynamic effects which influence algal distribution are related to the combined effect of advection due to wind forces and local currents, as well as to the presence of large gyres which induce recirculation and stagnation regions, favoring phytoplankton accumulation. Therefore, the general characters of the phytoplankton horizontal patchiness can be inferred from the results of the hydrodynamic model. Conversely, hyperspectral remote-sensing products can be used to validate this model, as they provide chlorophyll-a distribution maps. The integration of ecological, hydraulic, and remote-sensing techniques may therefore help the monitoring and protection of inland water quality, with important improvements in management actions by policy makers.

  13. Physics-electrical hybrid model for real time impedance matching and remote plasma characterization in RF plasma sources.

    Science.gov (United States)

    Sudhir, Dass; Bandyopadhyay, M; Chakraborty, A

    2016-02-01

    Plasma characterization and impedance matching are an integral part of any radio frequency (RF) based plasma source. In long pulse operation, particularly in high power operation where plasma load may vary due to different reasons (e.g. pressure and power), online tuning of impedance matching circuit and remote plasma density estimation are very useful. In some cases, due to remote interfaces, radio activation and, due to maintenance issues, power probes are not allowed to be incorporated in the ion source design for plasma characterization. Therefore, for characterization and impedance matching, more remote schemes are envisaged. Two such schemes by the same authors are suggested in these regards, which are based on air core transformer model of inductive coupled plasma (ICP) [M. Bandyopadhyay et al., Nucl. Fusion 55, 033017 (2015); D. Sudhir et al., Rev. Sci. Instrum. 85, 013510 (2014)]. However, the influence of the RF field interaction with the plasma to determine its impedance, a physics code HELIC [D. Arnush, Phys. Plasmas 7, 3042 (2000)] is coupled with the transformer model. This model can be useful for both types of RF sources, i.e., ICP and helicon sources.

  14. Amazon rainforest responses to elevated CO2: Deriving model-based hypotheses for the AmazonFACE experiment

    Science.gov (United States)

    Rammig, A.; Fleischer, K.; Lapola, D.; Holm, J.; Hoosbeek, M.

    2017-12-01

    Increasing atmospheric CO2 concentration is assumed to have a stimulating effect ("CO2 fertilization effect") on forest growth and resilience. Empirical evidence, however, for the existence and strength of such a tropical CO2 fertilization effect is scarce and thus a major impediment for constraining the uncertainties in Earth System Model projections. The implications of the tropical CO2 effect are far-reaching, as it strongly influences the global carbon and water cycle, and hence future global climate. In the scope of the Amazon Free Air CO2 Enrichment (FACE) experiment, we addressed these uncertainties by assessing the CO2 fertilization effect at ecosystem scale. AmazonFACE is the first FACE experiment in an old-growth, highly diverse tropical rainforest. Here, we present a priori model-based hypotheses for the experiment derived from a set of 12 ecosystem models. Model simulations identified key uncertainties in our understanding of limiting processes and derived model-based hypotheses of expected ecosystem responses to elevated CO2 that can directly be tested during the experiment. Ambient model simulations compared satisfactorily with in-situ measurements of ecosystem carbon fluxes, as well as carbon, nitrogen, and phosphorus stocks. Models consistently predicted an increase in photosynthesis with elevated CO2, which declined over time due to developing limitations. The conversion of enhanced photosynthesis into biomass, and hence ecosystem carbon sequestration, varied strongly among the models due to different assumptions on nutrient limitation. Models with flexible allocation schemes consistently predicted an increased investment in belowground structures to alleviate nutrient limitation, in turn accelerating turnover rates of soil organic matter. The models diverged on the prediction for carbon accumulation after 10 years of elevated CO2, mainly due to contrasting assumptions in their phosphorus cycle representation. These differences define the expected

  15. Remote Sensing Dynamic Monitoring of Biological Invasive Species Based on Adaptive PCNN and Improved C-V Model

    Directory of Open Access Journals (Sweden)

    PENG Gang

    2014-12-01

    Full Text Available Biological species invasion problem bring serious damage to the ecosystem, and have become one of the six major enviromental problems that affect the future economic development, also have become one of the hot topic in domestic and foreign scholars. Remote sensing technology has been successfully used in the investigation of coastal zone resources, dynamic monitoring of the resources and environment, and other fields. It will cite a new remote sensing image change detection algorithm based on adaptive pulse coupled neural network (PCNN and improved C-V model, for remote sensing dynamic monitoring of biological species invasion. The experimental results show that the algorithm is effective in the test results of biological species invasions.

  16. Development of airborne remote sensing data assimilation system

    International Nuclear Information System (INIS)

    Gudu, B R; Bi, H Y; Wang, H Y; Qin, S X; Ma, J W

    2014-01-01

    In this paper, an airborne remote sensing data assimilation system for China Airborne Remote Sensing System is introduced. This data assimilation system is composed of a land surface model, data assimilation algorithms, observation data and fundamental parameters forcing the land surface model. In this data assimilation system, Variable Infiltration Capacity hydrologic model is selected as the land surface model, which also serves as the main framework of the system. Three-dimensional variation algorithm, four-dimensional variation algorithms, ensemble Kalman filter and Particle filter algorithms are integrated in this system. Observation data includes ground observations and remotely sensed data. The fundamental forcing parameters include soil parameters, vegetation parameters and the meteorological data

  17. Remote ischemic preconditioning does not increase circulating or effector organ concentrations of proopiomelanocortin derivates

    DEFF Research Database (Denmark)

    Birkelund, Thomas; Obad, Damir; Matejec, Reginald

    2015-01-01

    Objectives. The aim of the present study was to compare changes in circulating levels of proopiomelanocortin (POMC) derivates and lactate after remote ischemic preconditioning (IPC) and physical exercise. Introduction. Remote IPC (rIPC) is cardioprotective following acute myocardial infarction....... Results. While rIPC was not associated with any significant increase in circulating POMC derivates or lactate, exercise induced significant elevation of both compared with baseline. Conclusions. We were not able to demonstrate a detectable increase in circulating POMC derivates by a standard rIPC stimulus...

  18. Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa

    Directory of Open Access Journals (Sweden)

    Dambach Peter

    2012-03-01

    Full Text Available Abstract Introduction The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM, precipitation (Tropical Rainfall Measurement Mission = TRMM, land surface temperatures (LST. Results The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI within the 500 m buffer zone around capture points. Conclusions Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines

  19. St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 1/3 arc-second St. Thomas and St. John, U.S. Virgin Islands Coastal Digital Elevation Model will be used to support NOAA's tsunami forecast system and for...

  20. OPEN-SOURCE DIGITAL ELEVATION MODEL (DEMs EVALUATION WITH GPS AND LiDAR DATA

    Directory of Open Access Journals (Sweden)

    N. F. Khalid

    2016-09-01

    Full Text Available Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM, Shuttle Radar Topography Mission (SRTM, and Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010 are freely available Digital Elevation Model (DEM datasets for environmental modeling and studies. The quality of spatial resolution and vertical accuracy of the DEM data source has a great influence particularly on the accuracy specifically for inundation mapping. Most of the coastal inundation risk studies used the publicly available DEM to estimated the coastal inundation and associated damaged especially to human population based on the increment of sea level. In this study, the comparison between ground truth data from Global Positioning System (GPS observation and DEM is done to evaluate the accuracy of each DEM. The vertical accuracy of SRTM shows better result against ASTER and GMTED10 with an RMSE of 6.054 m. On top of the accuracy, the correlation of DEM is identified with the high determination of coefficient of 0.912 for SRTM. For coastal zone area, DEMs based on airborne light detection and ranging (LiDAR dataset was used as ground truth data relating to terrain height. In this case, the LiDAR DEM is compared against the new SRTM DEM after applying the scale factor. From the findings, the accuracy of the new DEM model from SRTM can be improved by applying scale factor. The result clearly shows that the value of RMSE exhibit slightly different when it reached 0.503 m. Hence, this new model is the most suitable and meets the accuracy requirement for coastal inundation risk assessment using open source data. The suitability of these datasets for further analysis on coastal management studies is vital to assess the potentially vulnerable areas caused by coastal inundation.

  1. A NEW HIGH-RESOLUTION ELEVATION MODEL OF GREENLAND DERIVED FROM TANDEM-X

    Directory of Open Access Journals (Sweden)

    B. Wessel

    2016-06-01

    Full Text Available In this paper we present for the first time the new digital elevation model (DEM for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite elevations as ground control points (GCPs are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.

  2. Analysis of potential debris flow source areas on Mount Shasta, California, by using airborne and satellite remote sensing data

    Science.gov (United States)

    Crowley, J.K.; Hubbard, B.E.; Mars, J.C.

    2003-01-01

    Remote sensing data from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the first spaceborne imaging spectrometer, Hyperion, show hydrothermally altered rocks mainly composed of natroalunite, kaolinite, cristobalite, and gypsum on both the Mount Shasta and Shastina cones. Field observations indicate that much of the visible altered rock consists of talus material derived from fractured rock zones within and adjacent to dacitic domes and nearby lava flows. Digital elevation data were utilized to distinguish steeply sloping altered bedrock from more gently sloping talus materials. Volume modeling based on the imagery and digital elevation data indicate that Mount Shasta drainage systems contain moderate volumes of altered rock, a result that is consistent with Mount Shasta's Holocene record of mostly small to moderate debris flows. Similar modeling for selected areas at Mount Rainier and Mount Adams, Washington, indicates larger altered rock volumes consistent with the occurrence of much larger Holocene debris flows at those volcanoes. The availability of digital elevation and spectral data from spaceborne sensors, such as Hyperion and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), greatly expands opportunities for studying potential debris flow source characteristics at stratovolcanoes around the world. ?? 2003 Elsevier Inc. All rights reserved.

  3. Suitability Evaluation for Products Generation from Multisource Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Jining Yan

    2016-12-01

    Full Text Available With the arrival of the big data era in Earth observation, the remote sensing communities have accumulated a large amount of invaluable and irreplaceable data for global monitoring. These massive remote sensing data have enabled large-area and long-term series Earth observation, and have, in particular, made standard, automated product generation more popular. However, there is more than one type of data selection for producing a certain remote sensing product; no single remote sensor can cover such a large area at one time. Therefore, we should automatically select the best data source from redundant multisource remote sensing data, or select substitute data if data is lacking, during the generation of remote sensing products. However, the current data selection strategy mainly adopts the empirical model, and has a lack of theoretical support and quantitative analysis. Hence, comprehensively considering the spectral characteristics of ground objects and spectra differences of each remote sensor, by means of spectrum simulation and correlation analysis, we propose a suitability evaluation model for product generation. The model will enable us to obtain the Production Suitability Index (PSI of each remote sensing data. In order to validate the proposed model, two typical value-added information products, NDVI and NDWI, and two similar or complementary remote sensors, Landsat-OLI and HJ1A-CCD1, were chosen, and the verification experiments were performed. Through qualitative and quantitative analysis, the experimental results were consistent with our model calculation results, and strongly proved the validity of the suitability evaluation model. The proposed production suitability evaluation model could assist with standard, automated, serialized product generation. It will play an important role in one-station, value-added information services during the big data era of Earth observation.

  4. Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

    Science.gov (United States)

    Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

    2008-01-01

    This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

  5. Making Digital Elevation ModelsAccessible, Comprehensible, and Engaging through Real-Time Visualization

    DEFF Research Database (Denmark)

    Kjeldsen, Thomas Kim; Mikkelsen, Peter Trier; Mosegaard, Jesper

    2015-01-01

    In this paper we present our initial experiments with the new high quality digital elevation model, “Danmarks Højdemodel-2015” (DHM) exposed as an interactive 3D visualization on web and in virtual reality. We argue that such data has great opportunities to spawn new business and new insight...

  6. Assessment of long-term channel changes in the Mekong River using remote sensing and a channel-evolution model

    Science.gov (United States)

    Miyazawa, N.

    2011-12-01

    River-channel changes are a key factor affecting physical, ecological and management issues in the fluvial environment. In this study, long-term channel changes in the Mekong River were assessed using remote sensing and a channel-evolution model. A channel-evolution model for calculating long-term channel changes of a measndering river was developed using a previous fluid-dynamic model [Zolezzi and Seminara, 2001], and was applied in order to quantify channel changes of two meandering reaches in the Mekong River. Quite few attempts have been made so far to combine remote sensing observation of meandering planform change with the application of channel evolution models within relatively small-scale gravel-bed systems in humid temperate regions. The novel point of the present work is to link state-of-art meandering planform evolution model with observed morphological changes within large-scale sand-bed rivers with higher bank height in tropical monsoonal climate regions, which are the highly dynamic system, and assess the performance. Unstable extents of the reaches could be historically identified using remote-sensing technique. The instability caused i) bank erosion and accretion of meander bends and ii) movement or development of bars and changes in the flow around the bars. The remote sensing measurements indicate that maximum erosion occurred downstream of the maximum curvature of the river-center line in both reaches. The model simulations indicates that under the mean annual peak discharge the maximum of excess longitudinal velocity near the banks occurs downstream of the maximum curvature in both reaches. The channel migration coefficients of the reaches were calibrated by comparing remote-sensing measurements and model simulations. The diffrence in the migration coefficients between both reaches depends on the diffrence in bank height rather than the geotechnical properties of floodplain sediments. Possible eroded floodplain areas and accreted floodplain

  7. Evaluation of Clear-Sky Incoming Radiation Estimating Equations Typically Used in Remote Sensing Evapotranspiration Algorithms

    Directory of Open Access Journals (Sweden)

    Ted W. Sammis

    2013-09-01

    Full Text Available Net radiation is a key component of the energy balance, whose estimation accuracy has an impact on energy flux estimates from satellite data. In typical remote sensing evapotranspiration (ET algorithms, the outgoing shortwave and longwave components of net radiation are obtained from remote sensing data, while the incoming shortwave (RS and longwave (RL components are typically estimated from weather data using empirical equations. This study evaluates the accuracy of empirical equations commonly used in remote sensing ET algorithms for estimating RS and RL radiation. Evaluation is carried out through comparison of estimates and observations at five sites that represent different climatic regions from humid to arid. Results reveal (1 both RS and RL estimates from all evaluated equations well correlate with observations (R2 ≥ 0.92, (2 RS estimating equations tend to overestimate, especially at higher values, (3 RL estimating equations tend to give more biased values in arid and semi-arid regions, (4 a model that parameterizes the diffuse component of radiation using two clearness indices and a simple model that assumes a linear increase of atmospheric transmissivity with elevation give better RS estimates, and (5 mean relative absolute errors in the net radiation (Rn estimates caused by the use of RS and RL estimating equations varies from 10% to 22%. This study suggests that Rn estimates using recommended incoming radiation estimating equations could improve ET estimates.

  8. Evaluating LMA and CLAMP: Using information criteria to choose a model for estimating elevation

    Science.gov (United States)

    Miller, I.; Green, W.; Zaitchik, B.; Brandon, M.; Hickey, L.

    2005-12-01

    The morphology of leaves and composition of the flora respond strongly to the moisture and temperature of their environment. Elevation and latitude correlate, at first order, to these atmospheric parameters. An obvious modern example of this relationship between leaf morphology and environment is the tree line, where boreal forests give way to artic (high latitude) or alpine (high elevation) tundra. Several quantitative methods, all of which rely on uniformitarianism, have been developed to estimate paleoelevation using fossil leaf morphology. These include 1) the univariate leaf-margin analysis (LMA), which estimates mean annual temperature (MAT) by the positive linear correlation between MAT and P, the proportion of entire or smooth to non-entire or toothed margined woody dicot angiosperm leaves within a flora and 2) the Climate Leaf Analysis Multivariate Program (CLAMP) which uses Canonical Correspondence Analysis (CCA) to estimate MAT, moist enthalpy, and other atmospheric parameters using 31 explanatory leaf characters from woody dicot angiosperms. Given a difference in leaf-estimated MAT or moist enthalpy between contemporaneous, synlatitudinal fossil floras-one at sea-level, the other at an unknown paleoelevation-paleoelevation may be estimated. These methods have been widely applied to orogenic settings and concentrate particularly in the Western US. We introduce the use of information criteria to compare different models for estimating elevation and show how the additional complexity of the CLAMP analytical methodology does not necessarily improve on the elevation estimates produced by simpler regression models. In addition, we discuss the signal-to-noise ratio in the data, give confidence intervals for detecting elevations, and address the problem of spatial autocorrelation and irregular sampling in the data.

  9. A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

    Directory of Open Access Journals (Sweden)

    T. Slater

    2018-05-01

    Full Text Available We present a new digital elevation model (DEM of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are −0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m – a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

  10. Some technical notes on using UAV-based remote sensing for post disaster assessment

    Science.gov (United States)

    Rokhmana, Catur Aries; Andaru, Ruli

    2017-07-01

    Indonesia is located in an area prone to disasters, which are various kinds of natural disasters happen. In disaster management, the geoinformation data are needed to be able to evaluate the impact area. The UAV (Unmanned Aerial Vehicle)-Based remote sensing technology is a good choice to produce a high spatial resolution of less than 15 cm, while the current resolution of the satellite imagery is still greater than 50 cm. This paper shows some technical notes that should be considered when using UAV-Based remote sensing system in post disaster for rapid assessment. Some cases are Aceh Earthquake in years 2013 for seeing infrastructure damages, Banjarnegara landslide in year 2014 for seeing the impact; and Kelud volcano eruption in year 2014 for seeing the impact and volumetric material calculation. The UAV-Based remote sensing system should be able to produce the Orthophoto image that can provide capabilities for visual interpretation the individual damage objects, and the changes situation. Meanwhile the DEM (digital Elevation model) product can derive terrain topography, and volumetric calculation with accuracy 3-5 pixel or sub-meter also. The UAV platform should be able for working remotely and autonomously in dangerous area and limited infrastructures. In mountainous or volcano area, an unconventional flight plan should implemented. Unfortunately, not all impact can be seen from above such as wall crack, some parcel boundaries, and many objects that covered by others higher object. The previous existing geoinformation data are also needed to be able to evaluate the change detection automatically.

  11. ESTIMATION OF INSULATOR CONTAMINATIONS BY MEANS OF REMOTE SENSING TECHNIQUE

    Directory of Open Access Journals (Sweden)

    G. Han

    2016-06-01

    Full Text Available The accurate estimation of deposits adhering on insulators is critical to prevent pollution flashovers which cause huge costs worldwide. The traditional evaluation method of insulator contaminations (IC is based sparse manual in-situ measurements, resulting in insufficient spatial representativeness and poor timeliness. Filling that gap, we proposed a novel evaluation framework of IC based on remote sensing and data mining. Varieties of products derived from satellite data, such as aerosol optical depth (AOD, digital elevation model (DEM, land use and land cover and normalized difference vegetation index were obtained to estimate the severity of IC along with the necessary field investigation inventory (pollution sources, ambient atmosphere and meteorological data. Rough set theory was utilized to minimize input sets under the prerequisite that the resultant set is equivalent to the full sets in terms of the decision ability to distinguish severity levels of IC. We found that AOD, the strength of pollution source and the precipitation are the top 3 decisive factors to estimate insulator contaminations. On that basis, different classification algorithm such as mahalanobis minimum distance, support vector machine (SVM and maximum likelihood method were utilized to estimate severity levels of IC. 10-fold cross-validation was carried out to evaluate the performances of different methods. SVM yielded the best overall accuracy among three algorithms. An overall accuracy of more than 70% was witnessed, suggesting a promising application of remote sensing in power maintenance. To our knowledge, this is the first trial to introduce remote sensing and relevant data analysis technique into the estimation of electrical insulator contaminations.

  12. An automotive vehicle dynamics prototyping platform based on a remote control model car

    OpenAIRE

    SOLMAZ, Selim; COŞKUN, Türker

    2013-01-01

    The use of a modified remote control (RC) model car as a vehicle dynamics testing and development platform is detailed. Vehicle dynamics testing is an important aspect of automotive engineering and it plays a key role during the design and tuning of active safety control systems. Considering the fact that such tests are conductedi at great expense, scaled model cars can potentially be used to help with the process to reduce the costs. With this view, we instrument and develop a stand...

  13. South Padre Island, Texas 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  14. Port San Luis, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  15. San Francisco Bay, California 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  16. Morehead City, North Carolina 1/3 Arc-second NAVD 88 Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated...

  17. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

    DEFF Research Database (Denmark)

    Andersen, J.; Dybkjær, G.; Jensen, Karsten Høgh

    2002-01-01

    Remotely sensed precipitation from METEOSAT data and leaf area index (LAI) from NOAA AVHRR data is used as input data to the distributed hydrological modelling of three sub catchments (82.000 km(2)) in the Senegal River Basin. Further, root depths of annual vegetation are related to the temporal...

  18. Europium sorption on zirconia at elevated temperatures: experimental study and modeling

    International Nuclear Information System (INIS)

    Eglizaud, N.; Catalette, H.

    2005-01-01

    Full text of publication follows: Direct disposal of spent nuclear fuel in deep underground repository is being considered by several countries. The waste package maintains an elevated temperature for thousands of years. As sorption is one of the main phenomenon limiting the dispersion of radionuclides in the environment, it has to be studied at elevated temperatures. Zirconia is an oxide produced by cladding oxidation which is suspected in the near field of a nuclear repository. It then could possibly be in contact with waste elements as Europium (III), the sorption of which is therefore studied on zirconia. Experiments were performed by the batch method at a solid/liquid ratio of 10 g.L-1. The sorption edges were recorded in the pH-range from 2 to 10 at 2.10 -5 mol.L -1 Eu(NO 3 ) 3 (I = 0.1 mol.L -1 KNO 3 ). An over-pressure device in an autoclave with an incorporated filtering system allowed the experiments, carbonate free, at 25 deg. C, 50 deg. C, 80 deg. C, 120 deg. C and 150 deg. C and in situ pH measurements. Filtrates were analyzed by the ICP-AES method. Sorption isotherms show an increase in the sorption phenomenon when the temperature raises. The half sorption pH decreases from 7 at 25 deg. C to 3,6 at 150 deg. C. The distribution coefficients that were obtained at elevated temperatures enriched the databases of integrated performance assessment codes. Raw data were modeled with the surface complexation theory using the double layer model (DLM). Several possible surface complexes were examined and discussed, taking into account aqueous hydrolyzed and precipitated species of Europium. A good agreement between experimental values and modeled isotherms was found at all studied temperatures. Results were consistent with a bidentate complex formed by Europium (III) on the zirconia surface. Associated formation constants were then determined with the geochemical computer code CHESS. (authors)

  19. Real-time remote sensing driven river basin modeling using radar altimetry

    Directory of Open Access Journals (Sweden)

    S. J. Pereira-Cardenal

    2011-01-01

    Full Text Available Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models.

    In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA, temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat measurements of reservoir water levels. The modeling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is located in Central Asia and shared between 4 countries with conflicting water management interests.

    The modeling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean absolute error of the simulated reservoir water levels from 4.7 to 1.9 m, and

  20. Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

    Science.gov (United States)

    Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

    2010-01-01

    This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

  1. Monocular Elevation Deficiency - Double Elevator Palsy

    Science.gov (United States)

    ... Español Condiciones Chinese Conditions Monocular Elevation Deficiency/ Double Elevator Palsy En Español Read in Chinese What is monocular elevation deficiency (Double Elevator Palsy)? Monocular Elevation Deficiency, also known by the ...

  2. Remote community electrification in Sarawak, Malaysia

    Energy Technology Data Exchange (ETDEWEB)

    Anyi, Martin; Kirke, Brian [Sustainable Energy Centre, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, South Australia 5095 (Australia); Ali, Sam [School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, South Australia 5095 (Australia)

    2010-07-15

    It is usually uneconomic to provide mains power to small remote communities even when high voltage lines pass by a village. Local authorities normally resort to diesel-powered generators which require expensive fuel which is difficult to bring into remote areas. Furthermore they are noisy and require frequent maintenance which is often neglected in remote areas due to limited resources and know-how. Neither wind nor sun provides reliable power in humid tropical regions where there is a lot of still and overcast weather. Towers are found to attract lightning strikes which can destroy electronic controls, fungus grows on solar panels, and the multiple electrical connections on photovoltaic arrays corrode away in hot, humid climates. Micro hydro is an attractive option in mountainous areas, and a 30 kW high head and a 3 kW low head plant have been built, using village labour and surplus and discarded materials. Both are operating satisfactorily. However conventional micro hydro is not possible in flat country where there is little elevation, and work is now in progress to evaluate suitable hydrokinetic turbines on rivers in the humid tropics. Numerous companies around the world are now developing hydrokinetic turbines to harvest tidal and river flows, but a major problem with most designs is clogging by floating debris, especially in tropical rivers. (author)

  3. Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, northwest China

    Science.gov (United States)

    Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.

    2017-12-01

    Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.

  4. A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods

    Directory of Open Access Journals (Sweden)

    Elahe Akbari

    2017-12-01

    Full Text Available Oceans/Seas are important components of Earth that are affected by global warming and climate change. Recent studies have indicated that the deeper oceans are responsible for climate variability by changing the Earth’s ecosystem; therefore, assessing them has become more important. Remote sensing can provide sea surface data at high spatial/temporal resolution and with large spatial coverage, which allows for remarkable discoveries in the ocean sciences. The deep layers of the ocean/sea, however, cannot be directly detected by satellite remote sensors. Therefore, researchers have examined the relationships between salinity, height, and temperature of the oceans/Seas to estimate their subsurface water temperature using dynamical models and model-based data assimilation (numerical based and statistical approaches, which simulate these parameters by employing remotely sensed data and in situ measurements. Due to the requirements of comprehensive perception and the importance of global warming in decision making and scientific studies, this review provides comprehensive information on the methods that are used to estimate ocean/sea subsurface water temperature from remotely and non-remotely sensed data. To clarify the subsurface processes, the challenges, limitations, and perspectives of the existing methods are also investigated.

  5. Basic Remote Sensing Investigations for Beach Reconnaissance.

    Science.gov (United States)

    Progress is reported on three tasks designed to develop remote sensing beach reconnaissance techniques applicable to the benthic, beach intertidal...and beach upland zones. Task 1 is designed to develop remote sensing indicators of important beach composition and physical parameters which will...ultimately prove useful in models to predict beach conditions. Task 2 is designed to develop remote sensing techniques for survey of bottom features in

  6. Potential of biogas production to reduce firewood consumption in remote high-elevation Himalayan communities in Nepal

    Directory of Open Access Journals (Sweden)

    Gross Thomas

    2017-01-01

    Full Text Available Remote communities in the Nepalese mountains above 2500 m a.s.l. belong to the most precarious in the world. Inhabitants struggle for the minimum in terms of safe drinking water, food and sanitation. Reliable, affordable and clean energy for cooking, room heating and warm water for personal hygiene is often lacking and dependency on firewood very high. The remoteness and unlikeliness of electric grid connection in the coming decades make a diversified energy supply from renewable local resources crucial. Small-scale anaerobic digestion (AD of organic substrates has been used for long in rural areas of developing countries to produce biogas as energy source and recover residue as organic fertilizer. AD is challenging at high elevations due to year around lower ambient temperatures and lower annual biomass production per area compared to lowlands. Nevertheless, examples of operational household AD exist even above 3000 m a.s.l. in the Andes. Here we compare firewood consumption with biogas potential from organic substrates in a community with 39 households at 3150 m a.s.l. in Jumla District, Nepal. In five households with varying numbers of members and animals kept, mean firewood use and its energy content per capita (cap and day (d were 2.1 kg or ca. 25 MJ in spring and 2.3 kg or ca. 28 MJ in winter. Easily available substrates include cow, sheep and horse dung from overnight shelters and human excrements from pit latrines, amounting on average to 1.7 kg wet weight (kgww cap−1 d−1 in spring and 2.2 kgww cap−1 d−1 in winter. Adjusted to normal conditions (Nm3 at 0 °C, 1013.15 hPa, these substrates yielded on average 0.08 Nm3 cap−1 d−1 biogas in spring and 0.12 Nm3 cap−1 d−1 in winter (35–60% methane content in biochemical methane potential (BMPs tests at 36 °C. This could provide up to 60% of basic cooking needs on average and up to 75% in a “typical” household in terms of members

  7. Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

    2015-04-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

  8. Exploring the Role of Genetic Algorithms and Artificial Neural Networks for Interpolation of Elevation in Geoinformation Models

    Science.gov (United States)

    Bagheri, H.; Sadjadi, S. Y.; Sadeghian, S.

    2013-09-01

    One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous applications in the fields of sciences, engineering, design and various project administrations. One of the most significant events in DTM technique is the interpolation of elevation to create a continuous surface. There are several methods for interpolation, which have shown many results due to the environmental conditions and input data. The usual methods of interpolation used in this study along with Genetic Algorithms (GA) have been optimised and consisting of polynomials and the Inverse Distance Weighting (IDW) method. In this paper, the Artificial Intelligent (AI) techniques such as GA and Neural Networks (NN) are used on the samples to optimise the interpolation methods and production of Digital Elevation Model (DEM). The aim of entire interpolation methods is to evaluate the accuracy of interpolation methods. Universal interpolation occurs in the entire neighbouring regions can be suggested for larger regions, which can be divided into smaller regions. The results obtained from applying GA and ANN individually, will be compared with the typical method of interpolation for creation of elevations. The resulting had performed that AI methods have a high potential in the interpolation of elevations. Using artificial networks algorithms for the interpolation and optimisation based on the IDW method with GA could be estimated the high precise elevations.

  9. Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment

    NARCIS (Netherlands)

    Curnel, Y.; Wit, de A.J.W.; Duveiller, G.; Defourny, P.

    2011-01-01

    An Observing System Simulation Experiment (OSSE) has been defined to assess the potentialities of assimilating winter wheat leaf area index (LAI) estimations derived from remote sensing into the crop growth model WOFOST. Two assimilation strategies are considered: one based on Ensemble Kalman Filter

  10. Preparation of the Digital Elevation Model for Orthophoto CR Production

    Science.gov (United States)

    Švec, Z.; Pavelka, K.

    2016-06-01

    The Orthophoto CR is produced in co-operation with the Land Survey Office and the Military Geographical and Hydrometeorological Office. The product serves to ensure a defence of the state, integrated crisis management, civilian tasks in support of the state administration and the local self-government of the Czech Republic as well. It covers the whole area of the Republic and for ensuring its up-to-datedness is reproduced in the biennial period. As the project is countrywide, it keeps the project within the same parameters in urban and rural areas as well. Due to economic reasons it cańt be produced as a true ortophoto because it requires large side and forward overlaps of the aerial photographs and a preparation of the digital surface model instead of the digital terrain model. Use of DTM without some objects of DSM for orthogonalization purposes cause undesirable image deformations in the Orthophoto. There are a few data sets available for forming a suitable elevation model. The principal source should represent DTMs made from data acquired by the airborne laser scanning of the entire area of the Czech Republic that was carried out in the years 2009-2013, the DMR4G in the grid form and the DMR5G in TIN form respectively. It can be replenished by some vector objects (bridges, dams, etc.) taken from the geographic base data of the Czech Republic or obtained by new stereo plotting. It has to be taken into account that the option of applying DSM made from image correlation is also available. The article focuses on the possibilities of DTM supplement for ortogonalization. It looks back to the recent transition from grid to hybrid elevation models, problems that occurred, its solution and getting some practical remarks. Afterwards it assesses the current state and deals with the options for updating the model. Some accuracy analysis are included.

  11. PREPARATION OF THE DIGITAL ELEVATION MODEL FOR ORTHOPHOTO CR PRODUCTION

    Directory of Open Access Journals (Sweden)

    Z. Švec

    2016-06-01

    Full Text Available The Orthophoto CR is produced in co-operation with the Land Survey Office and the Military Geographical and Hydrometeorological Office. The product serves to ensure a defence of the state, integrated crisis management, civilian tasks in support of the state administration and the local self-government of the Czech Republic as well. It covers the whole area of the Republic and for ensuring its up-to-datedness is reproduced in the biennial period. As the project is countrywide, it keeps the project within the same parameters in urban and rural areas as well. Due to economic reasons it can´t be produced as a true ortophoto because it requires large side and forward overlaps of the aerial photographs and a preparation of the digital surface model instead of the digital terrain model. Use of DTM without some objects of DSM for orthogonalization purposes cause undesirable image deformations in the Orthophoto. There are a few data sets available for forming a suitable elevation model. The principal source should represent DTMs made from data acquired by the airborne laser scanning of the entire area of the Czech Republic that was carried out in the years 2009-2013, the DMR4G in the grid form and the DMR5G in TIN form respectively. It can be replenished by some vector objects (bridges, dams, etc. taken from the geographic base data of the Czech Republic or obtained by new stereo plotting. It has to be taken into account that the option of applying DSM made from image correlation is also available. The article focuses on the possibilities of DTM supplement for ortogonalization. It looks back to the recent transition from grid to hybrid elevation models, problems that occurred, its solution and getting some practical remarks. Afterwards it assesses the current state and deals with the options for updating the model. Some accuracy analysis are included.

  12. Economic optimization and evolutionary programming when using remote sensing data

    OpenAIRE

    Shamin Roman; Alberto Gabriel Enrike; Uryngaliyeva Ayzhana; Semenov Aleksandr

    2018-01-01

    The article considers the issues of optimizing the use of remote sensing data. Built a mathematical model to describe the economic effect of the use of remote sensing data. It is shown that this model is incorrect optimisation task. Given a numerical method of solving this problem. Also discusses how to optimize organizational structure by using genetic algorithm based on remote sensing. The methods considered allow the use of remote sensing data in an optimal way. The proposed mathematical m...

  13. Modelling desertification risk in the north-west of Jordan using geospatial and remote sensing techniques

    Directory of Open Access Journals (Sweden)

    Jawad T. Al-Bakri

    2016-03-01

    Full Text Available Remote sensing, climate, and ground data were used within a geographic information system (GIS to map desertification risk in the north-west of Jordan. The approach was based on modelling wind and water erosion and incorporating the results with a map representing the severity of drought. Water erosion was modelled by the universal soil loss equation, while wind erosion was modelled by a dust emission model. The extent of drought was mapped using the evapotranspiration water stress index (EWSI which incorporated actual and potential evapotranspiration. Output maps were assessed within GIS in terms of spatial patterns and the degree of correlation with soil surficial properties. Results showed that both topography and soil explained 75% of the variation in water erosion, while soil explained 25% of the variation in wind erosion, which was mainly controlled by natural factors of topography and wind. Analysis of the EWSI map showed that drought risk was dominating most of the rainfed areas. The combined effects of soil erosion and drought were reflected on the desertification risk map. The adoption of these geospatial and remote sensing techniques is, therefore, recommended to map desertification risk in Jordan and in similar arid environments.

  14. Hydrodynamic and Inundation Modeling of China’s Largest Freshwater Lake Aided by Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2015-04-01

    Full Text Available China’s largest freshwater lake, Poyang Lake, is characterized by rapid changes in its inundation area and hydrodynamics, so in this study, a hydrodynamic model of Poyang Lake was established to simulate these long-term changes. Inundation information was extracted from Moderate Resolution Imaging Spectroradiometer (MODIS remote sensing data and used to calibrate the wetting and drying parameter by assessing the accuracy of the simulated inundation area and its boundary. The bottom friction parameter was calibrated using current velocity measurements from Acoustic Doppler Current Profilers (ADCP. The results show the model is capable of predicting the inundation area dynamic through cross-validation with remotely sensed inundation data, and can reproduce the seasonal dynamics of the water level, and water discharge through a comparison with hydrological data. Based on the model results, the characteristics of the current velocities of the lake in the wet season and the dry season of the lake were explored, and the potential effect of the current dynamic on water quality patterns was discussed. The model is a promising basic tool for prediction and management of the water resource and water quality of Poyang Lake.

  15. Developments in remote sensing technology enable more detailed urban flood risk analysis.

    Science.gov (United States)

    Denniss, A.; Tewkesbury, A.

    2009-04-01

    Spaceborne remote sensors have been allowing us to build up a profile of planet earth for many years. With each new satellite launched we see the capabilities improve: new bands of data, higher resolution imagery, the ability to derive better elevation information. The combination of this geospatial data to create land cover and usage maps, all help inform catastrophe modelling systems. From Landsat 30m resolution to 2.44m QuickBird multispectral imagery; from 1m radar data collected by TerraSAR-X which enables rapid tracking of the rise and fall of a flood event, and will shortly have a twin satellite launched enabling elevation data creation; we are spoilt for choice in available data. However, just what is cost effective? It is always a question of choosing the appropriate level of input data detail for modelling, depending on the value of the risk. In the summer of 2007, the cost of the flooding in the UK was approximately £3bn and affected over 58,000 homes and businesses. When it comes to flood risk, we have traditionally considered rising river levels and surge tides, but with climate change and variations in our own construction behaviour, there are other factors to be taken into account. During those summer 2007 events, the Environment Agency suggested that around 70% of the properties damaged were the result of pluvial flooding, where high localised rainfall events overload localised drainage infrastructure, causing widespread flooding of properties and infrastructure. To create a risk model that is able to simulate such an event requires much more accurate source data than can be provided from satellite or radar. As these flood events cause considerable damage within relatively small, complex urban environments, therefore new high resolution remote sensing techniques have to be applied to better model these events. Detailed terrain data of England and Wales, plus cities in Scotland, have been produced by combining terrain measurements from the latest

  16. Object-oriented classification of drumlins from digital elevation models

    Science.gov (United States)

    Saha, Kakoli

    Drumlins are common elements of glaciated landscapes which are easily identified by their distinct morphometric characteristics including shape, length/width ratio, elongation ratio, and uniform direction. To date, most researchers have mapped drumlins by tracing contours on maps, or through on-screen digitization directly on top of hillshaded digital elevation models (DEMs). This paper seeks to utilize the unique morphometric characteristics of drumlins and investigates automated extraction of the landforms as objects from DEMs by Definiens Developer software (V.7), using the 30 m United States Geological Survey National Elevation Dataset DEM as input. The Chautauqua drumlin field in Pennsylvania and upstate New York, USA was chosen as a study area. As the study area is huge (approximately covers 2500 sq.km. of area), small test areas were selected for initial testing of the method. Individual polygons representing the drumlins were extracted from the elevation data set by automated recognition, using Definiens' Multiresolution Segmentation tool, followed by rule-based classification. Subsequently parameters such as length, width and length-width ratio, perimeter and area were measured automatically. To test the accuracy of the method, a second base map was produced by manual on-screen digitization of drumlins from topographic maps and the same morphometric parameters were extracted from the mapped landforms using Definiens Developer. Statistical comparison showed a high agreement between the two methods confirming that object-oriented classification for extraction of drumlins can be used for mapping these landforms. The proposed method represents an attempt to solve the problem by providing a generalized rule-set for mass extraction of drumlins. To check that the automated extraction process was next applied to a larger area. Results showed that the proposed method is as successful for the bigger area as it was for the smaller test areas.

  17. Cost-effectiveness of remote ischaemic conditioning as an adjunct to primary percutaneous coronary intervention in patients with ST-elevation myocardial infarction

    DEFF Research Database (Denmark)

    Sloth, Astrid D; Schmidt, Michael R; Munk, Kim

    2016-01-01

    AIMS: Remote ischaemic conditioning seems to improve long-term clinical outcomes in patients undergoing primary percutaneous coronary intervention. Remote ischaemic conditioning can be applied with cycles of alternating inflation and deflation of a blood-pressure cuff. We evaluated the cost...

  18. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: San Diego (CA) WFO

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

  19. Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

    Science.gov (United States)

    Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; Veblen, Thomas T; Smith, Jeremy M.; Kueppers, Lara M.

    2017-01-01

    Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively.Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers.Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forest and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine.Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.

  20. Quantifying the carbon uptake by vegetation for Europe on a 1 km2 resolution using a remote sensing driven vegetation model

    Science.gov (United States)

    Wißkirchen, K.; Tum, M.; Günther, K. P.; Niklaus, M.; Eisfelder, C.; Knorr, W.

    2013-04-01

    In this study we compare monthly gross primary productivity (GPP) time series (2000-2007), computed for Europe with the Biosphere Energy Transfer Hydrology (BETHY/DLR) model with monthly data from the eddy covariance measurements network FLUXNET. BETHY/DLR with a spatial resolution of 1 km2 is designed for regional and continental applications (here Europe) and operated at the German Aerospace Center (DLR). It was adapted from the BETHY scheme to be driven by remote sensing data and meteorology. Time series of Leaf Area Index (LAI) are used to control the development of vegetation. These are taken from the CYCLOPES database. Meteorological time series are used to regulate meteorological seasonality. These comprise daily information on temperature, precipitation, wind-speed and radiation. Additionally, static maps such as land cover, elevation, and soil type are used. To validate our model results we used eddy covariance measurements from the FLUXNET network of 74 towers across Europe. For forest sites we found that our model predicts between 20% and 40% higher annual GPP sums. In contrast, for cropland sites BETHY/DLR results show about 18% less GPP than eddy covariance measurements. For grassland sites, between 10% more and 16% less GPP was calculated with BETHY/DLR. A mean total carbon uptake of 2.5 Pg C yr-1 (±0.17 Pg) was found for Europe. In addition, this study states on risks that arise from the comparison of modeled data to FLUXNET measurements and their interpretation width.

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