WorldWideScience

Sample records for elevation models remote

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. Using Remote Sensing and High-Resolution Digital Elevation Models to Identify Potential Erosional Hotspots Along River Channels During High Discharge Storm Events

    Science.gov (United States)

    Orland, E. D.; Amidon, W. H.

    2017-12-01

    As global warming intensifies, large precipitation events and associated floods are becoming increasingly common. Channel adjustments during floods can occur by both erosion and deposition of sediment, often damaging infrastructure in the process. There is thus a need for predictive models that can help managers identify river reaches that are most prone to adjustment during storms. Because rivers in post-glacial landscapes often flow over a mixture of bedrock and alluvial substrates, the identification of bedrock vs. alluvial channel reaches is an important first step in predicting vulnerability to channel adjustment during flood events, especially because bedrock channels are unlikely to adjust significantly, even during floods. This study develops a semi-automated approach to predicting channel substrate using a high-resolution LiDAR-derived digital elevation model (DEM). The study area is the Middlebury River in Middlebury, VT-a well-studied watershed with a wide variety of channel substrates, including reaches with documented channel adjustments during recent flooding events. Multiple metrics were considered for reference—such as channel width and drainage area—but the study utilized channel slope as a key parameter for identifying morphological variations within the Middlebury River. Using data extracted from the DEM, a power law was fit to selected slope and drainage area values for each branch in order to model idealized slope-drainage area relationships, which were then compared with measured slope-drainage area relationships. Differences in measured slope minus predicted slope (called delta-slope) are shown to help predict river channel substrate. Compared with field observations, higher delta-slope values correlate with more stable, boulder rich channels or bedrock gorges; conversely the lowest delta-slope values correlate with flat, sediment rich alluvial channels. The delta-slope metric thus serves as a reliable first-order predictor of channel

  6. 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...

  7. 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...

  8. 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...

  9. 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.

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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....

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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.

  7. 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...

  8. 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

  9. 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

  10. 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.

  11. 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...

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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...

  18. MORPHOLOGICAL FILLING OF DIGITAL ELEVATION MODELS

    Directory of Open Access Journals (Sweden)

    T. Krauß

    2012-09-01

    Full Text Available In this paper a new approach for a more detailed post processing and filling of digital elevation models (DEMs in urban areas is presented. To reach the required specifications in a first step the errors in digital surface models (DSMs generated by dense stereo algorithms are analyzed and methods for detection and classification of the different types of errors are implemented. Subsequently the classified erroneous areas are handled in separate manner to eliminate outliers and fill the DSM properly. The errors which can be detected in DSMs range from outliers – single pixels or small areas containing extremely high or low values – over noise from mismatches, single small holes to occlusions, where large areas are not visible in one of the images of the stereo pair. To validate the presented method artificial DSMs are generated and superimposed with all different kinds of described errors like noise (small holes cut in, outliers (small areas moved up/down, occlusions (larger areas beneath steep walls and so on. The method is subsequently applied to the artificial DSMs and the resulting filled DSMs are compared to the original artificial DSMs without the introduced errors. Also the method is applied to stereo satellite generated DSMs from the ISPRS Comission 1 WG4 benchmark dataset and the results are checked with the also provided first pulse laser DSM data. Finally the results are discussed, strengths and weaknesses of the approach are shown and suggestions for application and optimization are given.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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...

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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...

  15. 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...

  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. 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....

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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....

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. Gradient based filtering of digital elevation models

    DEFF Research Database (Denmark)

    Knudsen, Thomas; Andersen, Rune Carbuhn

    We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

  15. 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)

  16. 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

  17. 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

  18. 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

  19. Identifying urban sources as cause of elevated grass pollen concentrations using GIS and remote sensing

    DEFF Research Database (Denmark)

    Skjøth, Carsten Ambelas; Ørby, Pia Viuf; Becker, Thomas

    2013-01-01

    available remote sensing data combined with management information for local grass areas. The inventory has identified a number of grass pollen source areas present within the city domain. The comparison of the measured pollen concentrations with the inventory shows that the atmospheric concentrations......We examine here the hypothesis that during flowering, the grass pollen concentrations at a specific site reflect the distribution of grass pollen sources within a few kilometres of this site. We perform this analysis on data from a measurement campaign in the city of Aarhus (Denmark) using three...

  20. 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...

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Service models for remote healthcare monitoring systems.

    Science.gov (United States)

    Moorman, Bridget A

    2010-01-01

    These scenarios reflect where the future is heading for remote health monitoring technology and service expectations. Being able to manage a "system of systems" with timely service hand-off over seams of responsibility and system interfaces will become very important for a BMET or clinical engineer. These interfaces will include patient homes, clinician homes, commercial/civilian infrastructure, public utilities, vendor infrastructure as well as internal departmental domains. Concurrently, technology is changing rapidly resulting in newer software delivery modes and hardware appliances as well as infrastructure changes. Those who are able to de-construct the complex systems and identify infrastructure assumptions and seams of servicing responsibility will be able to better understand and communicate the expectations for service of these systems. Moreover, as identified in Case 1, prodigious use of underlying system monitoring tools (managing the "meta-data") could move servicing of these remote systems from a reactive approach to a proactive approach. A prepared healthcare organization will identify their current and proposed future service combination use cases and design service philosophies and expectations for those use cases, while understanding the infrastructure assumptions and seams of responsibility. This is the future of technical service to the healthcare clinicians and patients.

  6. 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

  7. Elevated atmospheric deposition and dynamics of mercury in a remote upland forest of southwestern China

    International Nuclear Information System (INIS)

    Fu Xuewu; Feng Xinbin; Zhu Wanze; Rothenberg, S.; Yao Heng; Zhang Hui

    2010-01-01

    Mt. Gongga area in southwest China was impacted by Hg emissions from industrial activities and coal combustion, and annual means of atmospheric TGM and PHg concentrations at a regional background station were 3.98 ng m -3 and 30.7 pg m -3 , respectively. This work presents a mass balance study of Hg in an upland forest in this area. Atmospheric deposition was highly elevated in the study area, with the annual mean THg deposition flux of 92.5 μg m -2 yr -1 . Total deposition was dominated by dry deposition (71.8%), and wet deposition accounted for the remaining 28.2%. Forest was a large pool of atmospheric Hg, and nearly 76% of the atmospheric input was stored in forest soil. Volatilization and stream outflow were identified as the two major pathways for THg losses from the forest, which yielded mean output fluxes of 14.0 and 8.6 μg m -2 yr -1 , respectively. - Upland forest ecosystem is a great sink of atmospheric mercury in southwest China.

  8. 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, ...

  9. 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....

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  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. 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...

  9. 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

  10. 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.

  11. 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.

  12. Elevated Temperature Testing and Modeling of Advanced Toughened Ceramic Materials

    Science.gov (United States)

    Keith, Theo G.

    2005-01-01

    The purpose of this report is to provide a final report for the period of 12/1/03 through 11/30/04 for NASA Cooperative Agreement NCC3-776, entitled "Elevated Temperature Testing and Modeling of Advanced Toughened Ceramic Materials." During this final period, major efforts were focused on both the determination of mechanical properties of advanced ceramic materials and the development of mechanical test methodologies under several different programs of the NASA-Glenn. The important research activities made during this period are: 1. Mechanical properties evaluation of two gas-turbine grade silicon nitrides. 2) Mechanical testing for fuel-cell seal materials. 3) Mechanical properties evaluation of thermal barrier coatings and CFCCs and 4) Foreign object damage (FOD) testing.

  13. 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.

  14. Hydrography-driven coarsening of grid digital elevation models

    Science.gov (United States)

    Moretti, G.; Orlandini, S.

    2017-12-01

    A new grid coarsening strategy, denoted as hydrography-driven (HD) coarsening, is developed in the present study. The HD coarsening strategy is designed to retain the essential hydrographic features of surface flow paths observed in high-resolution digital elevation models (DEMs): (1) depressions are filled in the considered high-resolution DEM, (2) the obtained topographic data are used to extract a reference grid network composed of all surface flow paths, (3) the Horton order is assigned to each link of the reference grid network, and (4) within each coarse grid cell, the elevation of the point lying along the highest-order path of the reference grid network and displaying the minimum distance to the cell center is assigned to this coarse grid cell center. The capabilities of the HD coarsening strategy to provide consistent surface flow paths with respect to those observed in high-resolution DEMs are evaluated over a synthetic valley and two real drainage basins located in the Italian Alps and in the Italian Apennines. The HD coarsening is found to yield significantly more accurate surface flow path profiles than the standard nearest neighbor (NN) coarsening. In addition, the proposed strategy is found to reduce drastically the impact of depression-filling procedures in coarsened topographic data. The HD coarsening strategy is therefore advocated for all those cases in which the relief of the extracted drainage network is an important hydrographic feature. The figure below reports DEMs of a synthetic valley and extracted surface flow paths. (a) 10-m grid DEM displaying no depressions and extracted surface flow path (gray line). (b) 1-km grid DEM obtained from NN coarsening. (c) 1-km grid DEM obtained from NN coarsening plus depression-filling and extracted surface flow path (light blue line). (d) 1-km grid DEM obtained from HD coarsening and extracted surface flow path (magenta line).

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. Budapest, Hungary, Perspective View, SRTM Elevation Model with Landsat Overlay

    Science.gov (United States)

    2004-01-01

    After draining the northern flank of the Alps Mountains in Germany and Austria, the Danube River flows east as it enters this west-looking scene (upper right) and forms the border between Slovakia and Hungary. The river then leaves the border as it enters Hungary and transects the Transdanubian Mountains, which trend southwest to northeast. Upon exiting the mountains, the river turns southward, flowing past Budapest (purplish blue area) and along the western margin of the Great Hungarian Plain.South and west of the Danube, the Transdanubian Mountains have at most only about 400 meters (about 1300 feet) of relief but they exhibit varied landforms, which include volcanic, tectonic, fluvial (river), and eolian (wind) features. A thick deposit of loess (dust deposits likely blown from ancient glacial outwash) covers much of this area, and winds from the northwest, funneled between the Alps and the Carpathian Mountains, are apparently responsible for a radial pattern of erosional streaks across the entire region.This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 3-times vertical exaggeration to enhance topographic expression. The false colors of the scene result from displaying Landsat bands 1, 4, and 7 in blue, green, and red, respectively. Band 1 is visible blue light, but bands 4 and 7 are reflected infrared light. This band combination maximizes color contrasts between the major land cover types, namely vegetation (green), bare ground (red), and water (blue). Shading of the elevation model was used to further highlight the topographic features.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. Modelling and interpretation of gas detection using remote laser pointers.

    Science.gov (United States)

    Hodgkinson, J; van Well, B; Padgett, M; Pride, R D

    2006-04-01

    We have developed a quantitative model of the performance of laser pointer style gas leak detectors, which are based on remote detection of backscattered radiation. The model incorporates instrumental noise limits, the reflectivity of the target background surface and a mathematical description of gas leak dispersion in constant wind speed and turbulence conditions. We have investigated optimum instrument performance and limits of detection in simulated leak detection situations. We predict that the optimum height for instruments is at eye level or above, giving an operating range of 10 m or more for most background surfaces, in wind speeds of up to 2.5 ms(-1). For ground based leak sources, we find laser pointer measurements are dominated by gas concentrations over a short distance close to the target surface, making their readings intuitive to end users in most cases. This finding is consistent with the results of field trials.

  10. Construction of a digital elevation model: methods and parallelization

    International Nuclear Information System (INIS)

    Mazzoni, Christophe

    1995-01-01

    The aim of this work is to reduce the computation time needed to produce the Digital Elevation Models (DEM) by using a parallel machine. It is made in collaboration between the French 'Institut Geographique National' (IGN) and the Laboratoire d'Electronique de Technologie et d'Instrumentation (LETI) of the French Atomic Energy Commission (CEA). The IGN has developed a system which provides DEM that is used to produce topographic maps. The kernel of this system is the correlator, a software which automatically matches pairs of homologous points of a stereo-pair of photographs. Nevertheless the correlator is expensive In computing time. In order to reduce computation time and to produce the DEM with same accuracy that the actual system, we have parallelized the IGN's correlator on the OPENVISION system. This hardware solution uses a SIMD (Single Instruction Multiple Data) parallel machine SYMPATI-2, developed by the LETI that is involved in parallel architecture and image processing. Our analysis of the implementation has demonstrated the difficulty of efficient coupling between scalar and parallel structure. So we propose solutions to reinforce this coupling. In order to accelerate more the processing we evaluate SYMPHONIE, a SIMD calculator, successor of SYMPATI-2. On an other hand, we developed a multi-agent approach for what a MIMD (Multiple Instruction, Multiple Data) architecture is available. At last, we describe a Multi-SIMD architecture that conciliates our two approaches. This architecture offers a capacity to apprehend efficiently multi-level treatment image. It is flexible by its modularity, and its communication network supplies reliability that interest sensible systems. (author) [fr

  11. 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.

  12. Modeling of Aerosol Vertical Profiles Using GIS and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Kwon Ho Lee

    2009-06-01

    Full Text Available The use of Geographic Information Systems (GIS and Remote Sensing (RS by climatologists, environmentalists and urban planners for three dimensional modeling and visualization of the landscape is well established. However no previous study has implemented these techniques for 3D modeling of atmospheric aerosols because air quality data is traditionally measured at ground points, or from satellite images, with no vertical dimension. This study presents a prototype for modeling and visualizing aerosol vertical profiles over a 3D urban landscape in Hong Kong. The method uses a newly developed technique for the derivation of aerosol vertical profiles from AERONET sunphotometer measurements and surface visibility data, and links these to a 3D urban model. This permits automated modeling and visualization of aerosol concentrations at different atmospheric levels over the urban landscape in near-real time. Since the GIS platform permits presentation of the aerosol vertical distribution in 3D, it can be related to the built environment of the city. Examples are given of the applications of the model, including diagnosis of the relative contribution of vehicle emissions to pollution levels in the city, based on increased near-surface concentrations around weekday rush-hour times. The ability to model changes in air quality and visibility from ground level to the top of tall buildings is also demonstrated, and this has implications for energy use and environmental policies for the tall mega-cities of the future.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Modelling of aluminium sheet forming at elevated temperatures

    NARCIS (Netherlands)

    van den Boogaard, Antonius H.; Huetink, Han

    2004-01-01

    The formability of Al–Mg sheet can be improved considerably, by increasing the temperature. By heating the sheet in areas with large shear strains, but cooling it on places where the risk of necking is high, the limiting drawing ratio can be increased to values above 2.5. At elevated temperatures,

  18. Generation of a new Greenland Ice Sheet Digital Elevation Model

    DEFF Research Database (Denmark)

    Nagarajan, Sudhagar; Csatho, Beata M; Schenk, Anton F

    conditions, by fusing a photoclinometry DEM, SPOT and ASTER DEMs as well as elevations from ICESat, ATM and LVIS laser altimetry. The new multi-resolution DEM has a resolution of 40 m x 40 m in the marginal ice sheet regions and 250 m elsewhere. The ice sheet margin is mapped from SPOT and Landsat imagery...

  19. AN INFORMATION SERVICE MODEL FOR REMOTE SENSING EMERGENCY SERVICES

    Directory of Open Access Journals (Sweden)

    Z. Zhang

    2017-09-01

    Full Text Available This paper presents a method on the semantic access environment, which can solve the problem about how to identify the correct natural disaster emergency knowledge and return to the demanders. The study data is natural disaster knowledge text set. Firstly, based on the remote sensing emergency knowledge database, we utilize the sematic network to extract the key words in the input documents dataset. Then, using the semantic analysis based on words segmentation and PLSA, to establish the sematic access environment to identify the requirement of users and match the emergency knowledge in the database. Finally, the user preference model was established, which could help the system to return the corresponding information to the different users. The results indicate that semantic analysis can dispose the natural disaster knowledge effectively, which will realize diversified information service, enhance the precision of information retrieval and satisfy the requirement of users.

  20. 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.

  1. 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.

  2. Monitoring Mediterranean marine pollution using remote sensing and hydrodynamic modelling

    Science.gov (United States)

    La Loggia, Goffredo; Capodici, Fulvio; Ciraolo, Giuseppe; Drago, Aldo; Maltese, Antonino

    2011-11-01

    Human activities contaminate both coastal areas and open seas, even though impacts are different in terms of pollutants, ecosystems and recovery time. In particular, Mediterranean offshore pollution is mainly related to maritime transport of oil, accounting for 25% of the global maritime traffic and, during the last 25 years, for nearly 7% of the world oil accidents, thus causing serious biological impacts on both open sea and coastal zone habitats. This paper provides a general review of maritime pollution monitoring using integrated approaches of remote sensing and hydrodynamic modeling; focusing on the main results of the MAPRES (Marine pollution monitoring and detection by aerial surveillance and satellite images) research project on the synergistic use of remote sensing, forecasting, cleanup measures and environmental consequences. The paper also investigates techniques of oil spill detection using SAR images, presenting the first results of "Monitoring of marine pollution due to oil slick", a COSMO-SkyMed funded research project where X-band SAR constellation images provided by the Italian Space Agency are used. Finally, the prospect of using real time observations of marine surface conditions is presented through CALYPSO project (CALYPSO-HF Radar Monitoring System and Response against Marine Oil Spills in the Malta Channel), partly financed by the EU under the Operational Programme Italia-Malta 2007-2013. The project concerns the setting up of a permanent and fully operational HF radar observing system, capable of recording surface currents (in real-time with hourly updates) in the stretch of sea between Malta and Sicily. A combined use of collected data and numerical models, aims to optimize intervention and response in the case of marine oil spills.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Receptor models for source apportionment of remote aerosols in Brazil

    International Nuclear Information System (INIS)

    Artaxo Netto, P.E.

    1985-11-01

    The PIXE (particle induced X-ray emission), and PESA (proton elastic scattering analysis) method were used in conjunction with receptor models for source apportionment of remote aerosols in Brazil. The PIXE used in the determination of concentration for elements with Z >- 11, has a detection limit of about 1 ng/m 3 . The concentrations of carbon, nitrogen and oxygen in the fine fraction of Amazon Basin aerosols was measured by PESA. We sampled in Jureia (SP), Fernando de Noronha, Arembepe (BA), Firminopolis (GO), Itaberai (GO) and Amazon Basin. For collecting the airbone particles we used cascade impactors, stacked filter units, and streaker samplers. Three receptor models were used: chemical mass balance, stepwise multiple regression analysis and principal factor analysis. The elemental and gravimetric concentrations were explained by the models within the experimental errors. Three sources of aerosol were quantitatively distinguished: marine aerosol, soil dust and aerosols related to forests. The emission of aerosols by vegetation is very clear for all the sampling sites. In Amazon Basin and Jureia it is the major source, responsible for 60 to 80% of airborne concentrations. (Author) [pt

  10. 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...

  11. 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...

  12. The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

    Energy Technology Data Exchange (ETDEWEB)

    Drover, Damion, Ryan

    2011-12-01

    One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a

  13. 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

  14. ENHANCED MODELING OF REMOTELY SENSED ANNUAL LAND SURFACE TEMPERATURE CYCLE

    Directory of Open Access Journals (Sweden)

    Z. Zou

    2017-09-01

    Full Text Available Satellite thermal remote sensing provides access to acquire large-scale Land surface temperature (LST data, but also generates missing and abnormal values resulting from non-clear-sky conditions. Given this limitation, Annual Temperature Cycle (ATC model was employed to reconstruct the continuous daily LST data over a year. The original model ATCO used harmonic functions, but the dramatic changes of the real LST caused by the weather changes remained unclear due to the smooth sine curve. Using Aqua/MODIS LST products, NDVI and meteorological data, we proposed enhanced model ATCE based on ATCO to describe the fluctuation and compared their performances for the Yangtze River Delta region of China. The results demonstrated that, the overall root mean square errors (RMSEs of the ATCE was lower than ATCO, and the improved accuracy of daytime was better than that of night, with the errors decreased by 0.64 K and 0.36 K, respectively. The improvements of accuracies varied with different land cover types: the forest, grassland and built-up areas improved larger than water. And the spatial heterogeneity was observed for performance of ATC model: the RMSEs of built-up area, forest and grassland were around 3.0 K in the daytime, while the water attained 2.27 K; at night, the accuracies of all types significantly increased to similar RMSEs level about 2 K. By comparing the differences between LSTs simulated by two models in different seasons, it was found that the differences were smaller in the spring and autumn, while larger in the summer and winter.

  15. 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.

  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. 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...

  18. 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

  19. 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.

  20. Modeling Silicate Weathering for Elevated CO2 and Temperature

    Science.gov (United States)

    Bolton, E. W.

    2016-12-01

    A reactive transport model (RTM) is used to assess CO2 drawdown by silicate weathering over a wide range of temperature, pCO2, and infiltration rates for basalts and granites. Although RTM's have been used extensively to model weathering of basalts and granites for present-day conditions, we extend such modeling to higher CO2 that could have existed during the Archean and Proterozoic. We also consider a wide range of surface temperatures and infiltration rates. We consider several model basalt and granite compositions. We normally impose CO2 in equilibrium with the various atmospheric ranges modeled and CO2 is delivered to the weathering zone by aqueous transport. We also consider models with fixed CO2 (aq) throughout the weathering zone as could occur in soils with partial water saturation or with plant respiration, which can strongly influence pH and mineral dissolution rates. For the modeling, we use Kinflow: a model developed at Yale that includes mineral dissolution and precipitation under kinetic control, aqueous speciation, surface erosion, dynamic porosity, permeability, and mineral surface areas via sub-grid-scale grain models, and exchange of volatiles at the surface. Most of the modeling is done in 1D, but some comparisons to 2D domains with heterogeneous permeability are made. We find that when CO2 is fixed only at the surface, the pH tends toward higher values for basalts than granites, in large part due to the presence of more divalent than monovalent cations in the primary minerals, tending to decrease rates of mineral dissolution. Weathering rates increase (as expected) with increasing CO2 and temperature. This modeling is done with the support of the Virtual Planetary Laboratory.

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  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. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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....

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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....

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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....

  12. 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....

  13. 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....

  14. 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....

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  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. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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....

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  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. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 5 Meter Alaska Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This dataset is comprised of 5-meter ifsar-derived Digital Elevation Models (DEMs) over Alaska only. It is distributed as one-degree blocks with overedge. Horizontal...

  8. 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.

  9. 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.)

  10. Remote Sensing and Modeling for Improving Operational Aquatic Plant Management

    Science.gov (United States)

    Bubenheim, Dave

    2016-01-01

    The California Sacramento-San Joaquin River Delta is the hub for California’s water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, water quality changes, and expansion of invasive aquatic plants threatens ecosystems, impedes ecosystem restoration, and is economically, environmentally, and sociologically detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California and local governments to develop science-based, adaptive-management strategies for the Sacramento-San Joaquin Delta. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and waterway managers make science-informed decisions regarding management and outcomes. The team provides a comprehensive understanding of agricultural and urban land use in the Delta and the major water sheds (San Joaquin/Sacramento) supplying the Delta and interaction with drought and climate impacts on the environment, water quality, and weed growth. The team recommends conservation and modified land-use practices and aids local Delta stakeholders in developing management strategies. New remote sensing tools have been developed to enhance ability to assess conditions, inform decision support tools, and monitor management practices. Science gaps in understanding how native and invasive plants respond to altered environmental conditions are being filled and provide critical biological response parameters for Delta-SWAT simulation modeling. Operational agencies such as the California Department of Boating and Waterways provide testing and act as initial adopter of decision support tools. Methods developed by the project can become routine land and water management tools in complex river delta systems.

  11. Business Model Canvas & Elevator pitch : 29-10-2013

    NARCIS (Netherlands)

    Eelco Bakker

    2013-01-01

    Presentatie bij de Workshop Business Model Canvas: de bouwstenen en het gebouw van de onderneming - workshopprogramma ViB050. In het kader van het programma Teach the Teacher. Gehouden op 29-10-2013..

  12. Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

    KAUST Repository

    Lellmann, Jan; Morel, Jean-Michel; Schö nlieb, Carola-Bibiane

    2013-01-01

    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

  13. Bermuda 3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 3 arc-second Bermuda DEM will be used to support NOAA's tsunami forecast system and for tsunami inundation modeling. This DEM encompasses the islands of Bermuda...

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

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 1 arc-second Virgin Islands DEM will be used to support NOAA's tsunami forecast system and for tsunami inundation modeling. This DEM encompasses the Virgin...

  15. Bermuda 1 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 1 arc-second Bermuda DEM will be used to support NOAA's tsunami forecast system and for tsunami inundation modeling. This DEM encompasses the islands of Bermuda...

  16. British Columbia 3 arc-second Bathymetric Digital Elevation Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 3 arc-second British Columbia DEM will be used to support NOAA's tsunami forecast system and for tsunami inundation modeling. This DEM covers the coastal area...

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. Remote sensing and modeling in the Adriatic Sea

    International Nuclear Information System (INIS)

    Bekkering, J.A.

    1989-01-01

    The final objective of the project is to cast the scientific and practical base for the creation of an operational system to trace and predict the pathway and fate of pollutants in the marine environment, based principally on Remote Sensing from space. 20 refs, 2 figs, 5 tabs

  10. A Conceptual Model for Remote Data Acquisition Using SMSLib ...

    African Journals Online (AJOL)

    This paper presents a design of a remote lake-water-level measurement data acquisition system via UMTS network. The system accomplishes the function of data processing and transmitting by the use of SMSlib software and a java application developed. A tree layer system is designed to achieve this work: a mobile ...

  11. Process-scale modeling of elevated wintertime ozone in Wyoming.

    Energy Technology Data Exchange (ETDEWEB)

    Kotamarthi, V. R.; Holdridge, D. J.; Environmental Science Division

    2007-12-31

    Measurements of meteorological variables and trace gas concentrations, provided by the Wyoming Department of Environmental Quality for Daniel, Jonah, and Boulder Counties in the state of Wyoming, were analyzed for this project. The data indicate that highest ozone concentrations were observed at temperatures of -10 C to 0 C, at low wind speeds of about 5 mph. The median values for nitrogen oxides (NOx) during these episodes ranged between 10 ppbv and 20 ppbv (parts per billion by volume). Measurements of volatile organic compounds (VOCs) during these periods were insufficient for quantitative analysis. The few available VOCs measurements indicated unusually high levels of alkanes and aromatics and low levels of alkenes. In addition, the column ozone concentration during one of the high-ozone episodes was low, on the order of 250 DU (Dobson unit) as compared to a normal column ozone concentration of approximately 300-325 DU during spring for this region. Analysis of this observation was outside the scope of this project. The data analysis reported here was used to establish criteria for making a large number of sensitivity calculations through use of a box photochemical model. Two different VOCs lumping schemes, RACM and SAPRC-98, were used for the calculations. Calculations based on this data analysis indicated that the ozone mixing ratios are sensitive to (a) surface albedo, (b) column ozone, (c) NOx mixing ratios, and (d) available terminal olefins. The RACM model showed a large response to an increase in lumped species containing propane that was not reproduced by the SAPRC scheme, which models propane as a nearly independent species. The rest of the VOCs produced similar changes in ozone in both schemes. In general, if one assumes that measured VOCs are fairly representative of the conditions at these locations, sufficient precursors might be available to produce ozone in the range of 60-80 ppbv under the conditions modeled.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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...

  17. 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

  18. 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

  19. 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.

  20. 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...

  1. 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...

  2. 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)

  3. 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

  4. 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.

  5. Parabolic Equation Modeling of Propagation over Terrain Using Digital Elevation Model

    Directory of Open Access Journals (Sweden)

    Xiao-Wei Guan

    2018-01-01

    Full Text Available The parabolic equation method based on digital elevation model (DEM is applied on propagation predictions over irregular terrains. Starting from a parabolic approximation to the Helmholtz equation, a wide-angle parabolic equation is deduced under the assumption of forward propagation and the split-step Fourier transform algorithm is used to solve it. The application of DEM is extended to the Cartesian coordinate system and expected to provide a precise representation of a three-dimensional surface with high efficiency. In order to validate the accuracy, a perfectly conducting Gaussian terrain profile is simulated and the results are compared with the shift map. As a consequence, a good agreement is observed. Besides, another example is given to provide a theoretical basis and reference for DEM selection. The simulation results demonstrate that the prediction errors will be obvious only when the resolution of the DEM used is much larger than the range step in the PE method.

  6. The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding.

    Science.gov (United States)

    Leitão, J P; Boonya-Aroonnet, S; Prodanović, D; Maksimović, C

    2009-01-01

    This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall-Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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...

  13. An algorithm for treating flat areas and depressions in digital elevation models using linear interpolation

    Science.gov (United States)

    F. Pan; M. Stieglitz; R.B. McKane

    2012-01-01

    Digital elevation model (DEM) data are essential to hydrological applications and have been widely used to calculate a variety of useful topographic characteristics, e.g., slope, flow direction, flow accumulation area, stream channel network, topographic index, and others. Except for slope, none of the other topographic characteristics can be calculated until the flow...

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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...

  19. 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.

  20. 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...

  1. 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

  2. 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...

  3. 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.

  4. 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.

  5. Modelling vertical error in LiDAR-derived digital elevation models

    Science.gov (United States)

    Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

    2010-01-01

    A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings

  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. 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.

  8. 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

  9. 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...

  10. 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.

  11. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

    Science.gov (United States)

    Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

    2016-01-01

    Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

  12. 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...

  13. 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...

  14. 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

  15. Elevating your elevator talk

    Science.gov (United States)

    An important and often overlooked item that every early career researcher needs to do is compose an elevator talk. The elevator talk, named because the talk should not last longer than an average elevator ride (30 to 60 seconds), is an effective method to present your research and yourself in a clea...

  16. 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

  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. 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.

  19. Challenges of assessing fire and burn severity using field measures, remote sensing and modelling

    Science.gov (United States)

    Penelope Morgan; Robert E. Keane; Gregory K. Dillon; Theresa B. Jain; Andrew T. Hudak; Eva C. Karau; Pamela G. Sikkink; Zachery A. Holden; Eva K. Strand

    2014-01-01

    Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models. We draw on diverse recent research for guidance on assessing...

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Temperature elevation in the eye of anatomically based human head models for plane-wave exposures

    International Nuclear Information System (INIS)

    Hirata, A; Watanabe, S; Fujiwara, O; Kojima, M; Sasaki, K; Shiozawa, T

    2007-01-01

    This study investigated the temperature elevation in the eye of anatomically based human head models for plane-wave exposures. The finite-difference time-domain method is used for analyzing electromagnetic absorption and temperature elevation. The eyes in the anatomic models have average dimensions and weight. Computational results show that the ratio of maximum temperature in the lens to the eye-average SAR (named 'heating factor for the lens') is almost uniform (0.112-0.147 deg. C kg W -1 ) in the frequency region below 3 GHz. Above 3 GHz, this ratio increases gradually with an increase of frequency, which is attributed to the penetration depth of an electromagnetic wave. Particular attention is paid to the difference in the heating factor for the lens between this study and earlier works. Considering causes clarified in this study, compensated heating factors in all these studies are found to be in good agreement

  8. 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.

  9. 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

  10. Value of using remotely sensed evapotranspiration for SWAT model calibration

    Science.gov (United States)

    Hydrologic models are useful management tools for assessing water resources solutions and estimating the potential impact of climate variation scenarios. A comprehensive understanding of the water budget components and especially the evapotranspiration (ET) is critical and often overlooked for adeq...

  11. 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.

  12. 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.

  13. 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

  14. Contours, This Layer was derived from the USGS National Elevation Dataset (NED) based on 7.5 minute Digital Elevation Model (DEM) image files., Published in 1999, 1:24000 (1in=2000ft) scale, Atlanta Regional Commission.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Contours dataset current as of 1999. This Layer was derived from the USGS National Elevation Dataset (NED) based on 7.5 minute Digital Elevation Model (DEM) image...

  15. 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.

  16. Remote sensing estimation of evapotranspiration for SWAT Model Calibration

    Science.gov (United States)

    Hydrological models are used to assess many water resource problems from water quantity to water quality issues. The accurate assessment of the water budget, primarily the influence of precipitation and evapotranspiration (ET), is a critical first-step evaluation, which is often overlooked in hydro...

  17. A radiosity model for heterogeneous canopies in remote sensing

    Science.gov (United States)

    GarcíA-Haro, F. J.; Gilabert, M. A.; Meliá, J.

    1999-05-01

    A radiosity model has been developed to compute bidirectional reflectance from a heterogeneous canopy approximated by an arbitrary configuration of plants or clumps of vegetation, placed on the ground surface in a prescribed manner. Plants are treated as porous cylinders formed by aggregations of layers of leaves. This model explicitly computes solar radiation leaving each individual surface, taking into account multiple scattering processes between leaves and soil, and occlusion of neighboring plants. Canopy structural parameters adopted in this study have served to simplify the computation of the geometric factors of the radiosity equation, and thus this model has enabled us to simulate multispectral images of vegetation scenes. Simulated images have shown to be valuable approximations of satellite data, and then a sensitivity analysis to the dominant parameters of discontinuous canopies (plant density, leaf area index (LAI), leaf angle distribution (LAD), plant dimensions, soil optical properties, etc.) and scene (sun/ view angles and atmospheric conditions) has been undertaken. The radiosity model has let us gain a deep insight into the radiative regime inside the canopy, showing it to be governed by occlusion of incoming irradiance, multiple scattering of radiation between canopy elements and interception of upward radiance by leaves. Results have indicated that unlike leaf distribution, other structural parameters such as LAI, LAD, and plant dimensions have a strong influence on canopy reflectance. In addition, concepts have been developed that are useful to understand the reflectance behavior of the canopy, such as an effective LAI related to leaf inclination.

  18. ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Na Li

    2018-03-01

    Full Text Available The diverse density (DD algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels. However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS sensor and the Push-broom Hyperspectral Imager (PHI are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively.

  19. 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...

  20. Towards the optimal fusion of high-resolution Digital Elevation Models for detailed urban flood assessment

    Science.gov (United States)

    Leitão, J. P.; de Sousa, L. M.

    2018-06-01

    Newly available, more detailed and accurate elevation data sets, such as Digital Elevation Models (DEMs) generated on the basis of imagery from terrestrial LiDAR (Light Detection and Ranging) systems or Unmanned Aerial Vehicles (UAVs), can be used to improve flood-model input data and consequently increase the accuracy of the flood modelling results. This paper presents the first application of the MBlend merging method and assesses the impact of combining different DEMs on flood modelling results. It was demonstrated that different raster merging methods can have different and substantial impacts on these results. In addition to the influence associated with the method used to merge the original DEMs, the magnitude of the impact also depends on (i) the systematic horizontal and vertical differences of the DEMs, and (ii) the orientation between the DEM boundary and the terrain slope. The greater water depth and flow velocity differences between the flood modelling results obtained using the reference DEM and the merged DEMs ranged from -9.845 to 0.002 m, and from 0.003 to 0.024 m s-1 respectively; these differences can have a significant impact on flood hazard estimates. In most of the cases investigated in this study, the differences from the reference DEM results were smaller for the MBlend method than for the results of the two conventional methods. This study highlighted the importance of DEM merging when conducting flood modelling and provided hints on the best DEM merging methods to use.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Revealing topographic lineaments through IHS enhancement of DEM data. [Digital Elevation Model

    Science.gov (United States)

    Murdock, Gary

    1990-01-01

    Intensity-hue-saturation (IHS) processing of slope (dip), aspect (dip direction), and elevation to reveal subtle topographic lineaments which may not be obvious in the unprocessed data are used to enhance digital elevation model (DEM) data from northwestern Nevada. This IHS method of lineament identification was applied to a mosiac of 12 square degrees using a Cray Y-MP8/864. Square arrays from 3 x 3 to 31 x 31 points were tested as well as several different slope enhancements. When relatively few points are used to fit the plane, lineaments of various lengths are observed and a mechanism for lineament classification is described. An area encompassing the gold deposits of the Carlin trend and including the Rain in the southeast to Midas in the northwest is investigated in greater detail. The orientation and density of lineaments may be determined on the gently sloping pediment surface as well as in the more steeply sloping ranges.

  10. Pembuatan Digital Elevation Model Resolusi 10m dari Peta RBI dan Survei GPS dengan Algoritma Anudem

    Directory of Open Access Journals (Sweden)

    Indarto

    2014-04-01

    Full Text Available This study proposes the generation of Digital Elevation Model (DEM with spatial resolution of 10m x 10m by re-interpolation of elevation data. Data input for this study includes: (1 digitized datum coordinate from RBI map, (2 sample points surveyed by GPS, (3 digitized contour data fromSRTM DEM and ASTER GDEM2, and (4 digitized stream-network layer from RBI. All collected data were converted to mass point coordinats. On the top of Topogrid-ArcGIS, all points data were interpolated to produce DEM. After that the produced DEM were compared and evaluated to the SRTM and ASTER DEMvisually. The result shows that produced DEM are more accurate to represent the detailed topography of the study areas.

  11. 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.

  12. Application of a Snow Growth Model to Radar Remote Sensing

    Science.gov (United States)

    Erfani, E.; Mitchell, D. L.

    2014-12-01

    Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves

  13. Modelling the descent of nitric oxide during the elevated stratopause event of January 2013

    Science.gov (United States)

    Orsolini, Yvan J.; Limpasuvan, Varavut; Pérot, Kristell; Espy, Patrick; Hibbins, Robert; Lossow, Stefan; Raaholt Larsson, Katarina; Murtagh, Donal

    2017-03-01

    Using simulations with a whole-atmosphere chemistry-climate model nudged by meteorological analyses, global satellite observations of nitrogen oxide (NO) and water vapour by the Sub-Millimetre Radiometer instrument (SMR), of temperature by the Microwave Limb Sounder (MLS), as well as local radar observations, this study examines the recent major stratospheric sudden warming accompanied by an elevated stratopause event (ESE) that occurred in January 2013. We examine dynamical processes during the ESE, including the role of planetary wave, gravity wave and tidal forcing on the initiation of the descent in the mesosphere-lower thermosphere (MLT) and its continuation throughout the mesosphere and stratosphere, as well as the impact of model eddy diffusion. We analyse the transport of NO and find the model underestimates the large descent of NO compared to SMR observations. We demonstrate that the discrepancy arises abruptly in the MLT region at a time when the resolved wave forcing and the planetary wave activity increase, just before the elevated stratopause reforms. The discrepancy persists despite doubling the model eddy diffusion. While the simulations reproduce an enhancement of the semi-diurnal tide following the onset of the 2013 SSW, corroborating new meteor radar observations at high northern latitudes over Trondheim (63.4°N), the modelled tidal contribution to the forcing of the mean meridional circulation and to the descent is a small portion of the resolved wave forcing, and lags it by about ten days.

  14. 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.

  15. 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.

  16. 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...

  17. 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

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. Advances in Data Management in Remote Sensing and Climate Modeling

    Science.gov (United States)

    Brown, P. G.

    2014-12-01

    Recent commercial interest in "Big Data" information systems has yielded little more than a sense of deja vu among scientists whose work has always required getting their arms around extremely large databases, and writing programs to explore and analyze it. On the flip side, there are some commercial DBMS startups building "Big Data" platform using techniques taken from earth science, astronomy, high energy physics and high performance computing. In this talk, we will introduce one such platform; Paradigm4's SciDB, the first DBMS designed from the ground up to combine the kinds of quality-of-service guarantees made by SQL DBMS platforms—high level data model, query languages, extensibility, transactions—with the kinds of functionality familiar to scientific users—arrays as structural building blocks, integrated linear algebra, and client language interfaces that minimize the learning curve. We will review how SciDB is used to manage and analyze earth science data by several teams of scientific users.

  5. Global existence of solutions to a tear film model with locally elevated evaporation rates

    Science.gov (United States)

    Gao, Yuan; Ji, Hangjie; Liu, Jian-Guo; Witelski, Thomas P.

    2017-07-01

    Motivated by a model proposed by Peng et al. (2014) for break-up of tear films on human eyes, we study the dynamics of a generalized thin film model. The governing equations form a fourth-order coupled system of nonlinear parabolic PDEs for the film thickness and salt concentration subject to non-conservative effects representing evaporation. We analytically prove the global existence of solutions to this model with mobility exponents in several different ranges and present numerical simulations that are in agreement with the analytic results. We also numerically capture other interesting dynamics of the model, including finite-time rupture-shock phenomenon due to the instabilities caused by locally elevated evaporation rates, convergence to equilibrium and infinite-time thinning.

  6. 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

  7. 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.

  8. 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

  9. 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)

  10. 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.

  11. [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.

  12. Modeling Water-Surface Elevations and Virtual Shorelines for the Colorado River in Grand Canyon, Arizona

    Science.gov (United States)

    Magirl, Christopher S.; Breedlove, Michael J.; Webb, Robert H.; Griffiths, Peter G.

    2008-01-01

    Using widely-available software intended for modeling rivers, a new one-dimensional hydraulic model was developed for the Colorado River through Grand Canyon from Lees Ferry to Diamond Creek. Solving one-dimensional equations of energy and continuity, the model predicts stage for a known steady-state discharge at specific locations, or cross sections, along the river corridor. This model uses 2,680 cross sections built with high-resolution digital topography of ground locations away from the river flowing at a discharge of 227 m3/s; synthetic bathymetry was created for topography submerged below the 227 m3/s water surface. The synthetic bathymetry was created by adjusting the water depth at each cross section up or down until the model?s predicted water-surface elevation closely matched a known water surface. This approach is unorthodox and offers a technique to construct one-dimensional hydraulic models of bedrock-controlled rivers where bathymetric data have not been collected. An analysis of this modeling approach shows that while effective in enabling a useful model, the synthetic bathymetry can differ from the actual bathymetry. The known water-surface profile was measured using elevation data collected in 2000 and 2002, and the model can simulate discharges up to 5,900 m3/s. In addition to the hydraulic model, GIS-based techniques were used to estimate virtual shorelines and construct inundation maps. The error of the hydraulic model in predicting stage is within 0.4 m for discharges less than 1,300 m3/s. Between 1,300-2,500 m3/s, the model accuracy is about 1.0 m, and for discharges between 2,500-5,900 m3/s, the model accuracy is on the order of 1.5 m. In the absence of large floods on the flow-regulated Colorado River in Grand Canyon, the new hydraulic model and the accompanying inundation maps are a useful resource for researchers interested in water depths, shorelines, and stage-discharge curves for flows within the river corridor with 2002 topographic

  13. Optimizing digital elevation models (DEMs) accuracy for planning and design of mobile communication networks

    Science.gov (United States)

    Hassan, Mahmoud A.

    2004-02-01

    Digital elevation models (DEMs) are important tools in the planning, design and maintenance of mobile communication networks. This research paper proposes a method for generating high accuracy DEMs based on SPOT satellite 1A stereo pair images, ground control points (GCP) and Erdas OrthoBASE Pro image processing software. DEMs with 0.2911 m mean error were achieved for the hilly and heavily populated city of Amman. The generated DEM was used to design a mobile communication network resulted in a minimum number of radio base transceiver stations, maximum number of covered regions and less than 2% of dead zones.

  14. Falling paper: Navier-Stokes solutions, model of fluid forces, and center of mass elevation.

    Science.gov (United States)

    Pesavento, Umberto; Wang, Z Jane

    2004-10-01

    We investigate the problem of falling paper by solving the two dimensional Navier-Stokes equations subject to the motion of a free-falling body at Reynolds numbers around 10(3). The aerodynamic lift on a tumbling plate is found to be dominated by the product of linear and angular velocities rather than velocity squared, as appropriate for an airfoil. This coupling between translation and rotation provides a mechanism for a brief elevation of center of mass near the cusplike turning points. The Navier-Stokes solutions further provide the missing quantity in the classical theory of lift, the instantaneous circulation, and suggest a revised model for the fluid forces.

  15. 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

  16. Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

    Science.gov (United States)

    Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, P.; Williams, C.; Ardö, J.; Boucher, M.; Cappelaere, B.; de Grandcourt, A.; Nickless, A.; Nouvellon, Y.; Scholes, R.; Kutsch, W.

    2013-03-01

    Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

  17. 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.

  18. 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.

  19. 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.

  20. 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)

  1. 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.

  2. 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

  3. 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

  4. 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/.

  5. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Jacksonville (FL) WFO - St. Johns, Flagler and Putnam Counties

    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. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Portland (OR) WFO - Tillamook, Lincoln, and Lane Counties

    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...

  7. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Eureka (CA) WFO - Humboldt and Del Norte Counties

    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...

  8. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Melbourne (FL) WFO - Indian River, St. Lucie, and Martin Counties

    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...

  9. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Melbourne (FL) WFO - Brevard and Volusia Counties

    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...

  10. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Tampa (FL) WFO - Manatee, Sarasota, Charlotte, and Lee Counties

    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...

  11. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Tampa (FL) WFO - Citrus, Hernando, Pasco, Pinellas, and Hillsborough Counties

    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...

  12. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Jacksonville (FL) WFO - Duval, Clay, and Nassau Counties

    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...

  13. Original Product Resolution (OPR) Source Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data collection is the Original Product Resolution (OPR) Digital Elevation Model (DEM) as provided to the USGS. This DEM is delivered in the original...

  14. STUDY OF INFLUENCE OF EFFLUENT ON GROUND WATER USING REMOTE SENSING, GIS AND MODELING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    S. Pathak

    2012-07-01

    Full Text Available The area lies in arid zone of western Rajasthan having very scanty rains and very low ground water reserves. Some of the other problems that are faced by the area are disposal of industrial effluent posing threat to its sustainability of water resource. Textiles, dyeing and printing industries, various mechanical process and chemical/synthetic dyes are used and considerable wastewater discharged from these textile units contains about high amount of the dyes into the adjoining drainages. This has caused degradation of water quality in this water scarce semi-arid region of the country. Pali city is located South-West, 70 Kms from Jodhpur in western Rajasthan (India. There are four Common Effluent Treatment Plant (CETP treating wastewater to meet the pollutant level permissible to river discharge, a huge amount of effluent water of these factories directly meets the into the river Bandi – a tributary of river Luni. In order to monitor the impact of industrial effluents on the environment, identifying the extent of the degradation and evolving possible means of minimizing the impacts studies on quality of effluents, polluted river water and water of adjoining wells, the contamination migration of the pollutants from the river to ground water were studied. Remote sensing analysis has been carried out using Resourcesat −1 multispectral satellite data along with DEM derived from IRS P5 stereo pair. GIS database generated of various thematic layers viz. base layer – inventorying all waterbodies in the vicinity, transport network and village layer, drainage, geomorphology, structure, land use. Analysis of spatial distribution of the features and change detection in land use/cover carried out. GIS maps have been used to help factor in spatial location of source and hydro-geomorphological settings. DEM & elevation contour helped in delineation of watershed and identifying flow modelling boundaries. Litholog data analysis carried out for aquifer

  15. Study of Influence of Effluent on Ground Water Using Remote Sensing, GIS and Modeling Techniques

    Science.gov (United States)

    Pathak, S.; Bhadra, B. K.; Sharma, J. R.

    2012-07-01

    The area lies in arid zone of western Rajasthan having very scanty rains and very low ground water reserves. Some of the other problems that are faced by the area are disposal of industrial effluent posing threat to its sustainability of water resource. Textiles, dyeing and printing industries, various mechanical process and chemical/synthetic dyes are used and considerable wastewater discharged from these textile units contains about high amount of the dyes into the adjoining drainages. This has caused degradation of water quality in this water scarce semi-arid region of the country. Pali city is located South-West, 70 Kms from Jodhpur in western Rajasthan (India). There are four Common Effluent Treatment Plant (CETP) treating wastewater to meet the pollutant level permissible to river discharge, a huge amount of effluent water of these factories directly meets the into the river Bandi - a tributary of river Luni. In order to monitor the impact of industrial effluents on the environment, identifying the extent of the degradation and evolving possible means of minimizing the impacts studies on quality of effluents, polluted river water and water of adjoining wells, the contamination migration of the pollutants from the river to ground water were studied. Remote sensing analysis has been carried out using Resourcesat -1 multispectral satellite data along with DEM derived from IRS P5 stereo pair. GIS database generated of various thematic layers viz. base layer - inventorying all waterbodies in the vicinity, transport network and village layer, drainage, geomorphology, structure, land use. Analysis of spatial distribution of the features and change detection in land use/cover carried out. GIS maps have been used to help factor in spatial location of source and hydro-geomorphological settings. DEM & elevation contour helped in delineation of watershed and identifying flow modelling boundaries. Litholog data analysis carried out for aquifer boundaries using specialized

  16. Modeling carbon dioxide sequestration in saline aquifers: Significance of elevated pressures and salinities

    International Nuclear Information System (INIS)

    Allen, D.E.; Strazisar, B.R.; Soong, Y.; Hedges, S.W.

    2005-01-01

    The ultimate capacity of saline formations to sequester carbon dioxide by solubility and mineral trapping must be determined by simulating sequestration with geochemical models. These models, however, are only as reliable as the data and reaction scheme on which they are based. Several models have been used to make estimates of carbon dioxide solubility and mineral formation as a function of pressure and fluid composition. Intercomparison of modeling results indicates that failure to adjust all equilibrium constants to account for elevated carbon dioxide pressures results in significant errors in both solubility and mineral formation estimates. Absence of experimental data at high carbon dioxide pressures and high salinities make verification of model results difficult. Results indicate standalone solubility models that do not take mineral reactions into account will underestimate the total capacity of aquifers to sequester carbon dioxide in the long term through enhanced solubility and mineral trapping mechanisms. Overall, it is difficult to confidently predict the ultimate sequestration capacity of deep saline aquifers using geochemical models. (author)

  17. Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

    Science.gov (United States)

    Musick, H. Brad

    1993-01-01

    The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

  18. Hydraulic sediment remotion in physical models; Aplicacion en modelos fisicos de la remocion hidraulica de sedimentos

    Energy Technology Data Exchange (ETDEWEB)

    Marengo Mogollon, Humberto [Comision Federal de Electricidad (Mexico)

    2001-03-01

    Sediment remotion in reservoirs has received an increased attention worldwide because of the difficulty to build new dams. This paper shows the application of some flushing techniques in two hydraulic experimental models that were used in order to estimate the efficiency in sediment remotion, as well as feasible solutions to be applied in our country. [Spanish] La remocion de sedimentos que se acumulan en los embalses ha recibido recientemente una gran atencion en diversas partes del mundo debido fundamentalmente a la dificultad de construir nuevas presas. Este articulo muestra el uso de la remocion hidraulica de sedimentos en embalses aplicados a dos modelos hidraulicos experimentales que se emplearon para estimar la eficiencia de dicha remocion, ademas de posibles soluciones que se consideran factibles de utilizarse en nuestro pais.

  19. 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

  20. 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

  1. "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

  2. Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    2018-01-01

    in terrestrial water storage depletion within the Arabian Peninsula and explore its relation to increased agricultural activity in the region using satellite data. Next, we evaluate a number of large-scale remote sensing-based evaporation models, giving insight

  3. 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.

  4. VALIDATION OF THE ASTER GLOBAL DIGITAL ELEVATION MODEL VERSION 2 OVER THE CONTERMINOUS UNITED STATES

    Directory of Open Access Journals (Sweden)

    D. Gesch

    2012-07-01

    Full Text Available The ASTER Global Digital Elevation Model Version 2 (GDEM v2 was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1 in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of –0.20 meters is a significant improvement over the GDEM v1 mean error of –3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height, GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.

  5. Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States

    Science.gov (United States)

    Gesch, Dean B.; Oimoen, Michael J.; Zhang, Zheng; Meyer, David J.; Danielson, Jeffrey J.

    2012-01-01

    The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of -0.20 meters is a significant improvement over the GDEM v1 mean error of -3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.

  6. Bathymetric survey and digital elevation model of Little Holland Tract, Sacramento-San Joaquin Delta, California

    Science.gov (United States)

    Snyder, Alexander G.; Lacy, Jessica R.; Stevens, Andrew W.; Carlson, Emily M.

    2016-06-10

    The U.S. Geological Survey conducted a bathymetric survey in Little Holland Tract, a flooded agricultural tract, in the northern Sacramento-San Joaquin Delta (the “Delta”) during the summer of 2015. The new bathymetric data were combined with existing data to generate a digital elevation model (DEM) at 1-meter resolution. Little Holland Tract (LHT) was historically diked off for agricultural uses and has been tidally inundated since an accidental levee breach in 1983. Shallow tidal regions such as LHT have the potential to improve habitat quality in the Delta. The DEM of LHT was developed to support ongoing studies of habitat quality in the area and to provide a baseline for evaluating future geomorphic change. The new data comprise 138,407 linear meters of real-time-kinematic (RTK) Global Positioning System (GPS) elevation data, including both bathymetric data collected from personal watercraft and topographic elevations collected on foot at low tide. A benchmark (LHT15_b1) was established for geodetic control of the survey. Data quality was evaluated both by comparing results among surveying platforms, which showed systematic offsets of 1.6 centimeters (cm) or less, and by error propagation, which yielded a mean vertical uncertainty of 6.7 cm. Based on the DEM and time-series measurements of water depth, the mean tidal prism of LHT was determined to be 2,826,000 cubic meters. The bathymetric data and DEM are available at http://dx.doi.org/10.5066/F7RX9954. 

  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. 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.

  9. Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

    DEFF Research Database (Denmark)

    Tagesson, Håkan Torbern; Smith, Benjamin; Løfgren, Anders

    2009-01-01

    and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average......The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs...... in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model...

  10. Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas

    Science.gov (United States)

    Leitão, João P.; Moy de Vitry, Matthew; Scheidegger, Andreas; Rieckermann, Jörg

    2016-04-01

    Precise and detailed digital elevation models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM, such as airplane light detection and ranging (lidar) DEMs and point and contour maps, remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of unmanned aerial vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions. In addition, we compared the best-quality UAV DEM to a conventional lidar-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to lidar-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g. buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional lidar-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is

  11. ASTER-Derived 30-Meter-Resolution Digital Elevation Models of Afghanistan

    Science.gov (United States)

    Chirico, Peter G.; Warner, Michael B.

    2007-01-01

    INTRODUCTION The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is an imaging instrument aboard the Terra satellite, launched on December 19, 1999, as part of the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). The ASTER sensor consists of three subsystems: the visible and near infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR), each with a different spatial resolution (VNIR, 15 meters; SWIR, 30 meters, TIR 90 meters). The VNIR system has the capability to generate along-track stereo images that can be used to create digital elevation models (DEMs) at 30-meter resolution. Currently, the only available DEM dataset for Afghanistan is the 90-meter-resolution Shuttle Radar Topography Mission (SRTM) data. This dataset is appropriate for macroscale DEM analysis and mapping. However, ASTER provides a low cost opportunity to generate higher resolution data. For this publication, study areas were identified around populated areas and areas where higher resolution elevation data were desired to assist in natural resource assessments. The higher resolution fidelity of these DEMs can also be used for other terrain analysis including landform classification and geologic structure analysis. For this publication, ASTER scenes were processed and mosaicked to generate 36 DEMs which were created and extracted using PCI Geomatics' OrthoEngine 3D Stereo software. The ASTER images were geographically registered to Landsat data with at least 15 accurate and well distributed ground control points with a root mean square error (RMSE) of less that one pixel (15 meters). An elevation value was then assigned to each ground control point by extracting the elevation from the 90-meter SRTM data. The 36 derived DEMs demonstrate that the software correlated on nearly flat surfaces and smooth slopes accurately. Larger errors occur in cloudy and snow-covered areas, lakes, areas with steep slopes, and

  12. COMPARISON OF MULTI-SCALE DIGITAL ELEVATION MODELS FOR DEFINING WATERWAYS AND CATCHMENTS OVER LARGE AREAS

    Directory of Open Access Journals (Sweden)

    B. Harris

    2012-07-01

    Full Text Available Digital Elevation Models (DEMs allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas are adequate for the creation of waterways and catchments at a regional scale.

  13. Comparison of Multi-Scale Digital Elevation Models for Defining Waterways and Catchments Over Large Areas

    Science.gov (United States)

    Harris, B.; McDougall, K.; Barry, M.

    2012-07-01

    Digital Elevation Models (DEMs) allow for the efficient and consistent creation of waterways and catchment boundaries over large areas. Studies of waterway delineation from DEMs are usually undertaken over small or single catchment areas due to the nature of the problems being investigated. Improvements in Geographic Information Systems (GIS) techniques, software, hardware and data allow for analysis of larger data sets and also facilitate a consistent tool for the creation and analysis of waterways over extensive areas. However, rarely are they developed over large regional areas because of the lack of available raw data sets and the amount of work required to create the underlying DEMs. This paper examines definition of waterways and catchments over an area of approximately 25,000 km2 to establish the optimal DEM scale required for waterway delineation over large regional projects. The comparative study analysed multi-scale DEMs over two test areas (Wivenhoe catchment, 543 km2 and a detailed 13 km2 within the Wivenhoe catchment) including various data types, scales, quality, and variable catchment input parameters. Historic and available DEM data was compared to high resolution Lidar based DEMs to assess variations in the formation of stream networks. The results identified that, particularly in areas of high elevation change, DEMs at 20 m cell size created from broad scale 1:25,000 data (combined with more detailed data or manual delineation in flat areas) are adequate for the creation of waterways and catchments at a regional scale.

  14. TecDEM: A MATLAB Based Toolbox for understanding Tectonics from Digital Elevation Models

    Science.gov (United States)

    Shahzad, F.; Mahmood, S. A.; Gloaguen, R.

    2009-04-01

    TecDEM is a MATLAB based tool box for understanding the tectonics from digital elevation models (DEMs) of any area. These DEMs can be derived from data of any spatial resolution (Low, medium and High). In the first step we extract drainage network from the DEMs using flow grid approach. Drainage network is a group of streams having elevation and catchment area information as a function of spatial locations. We implement an array of stream structure to study this drainage network. Knickpoints can be identified on each stream of the drainage network by a graphical user interface and are helpful for understanding stream morphology. Stream profile analysis in steady state condition is applied on all streams to calculate geomorphic parameters and regional uplift rates. Hack index is calculated for all the profiles at a certain interval and over the change of knickpoints. Reports menu of this tool box generates detailed statistics report, complete tabulated report, graphical output of each analyzed stream profile and Hack index profile. All the calculated values are part of stream structure and is saved as .mat file for later use with this tool box. The spatial distribution of geomorphic parameters, uplift rates and knickpoints are exported as a shape files for visualization in professional GIS software. We test this tool box on DEMs from different tectonic settings worldwide and received verifiable results with other studies.

  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. A Framework for Sharing and Integrating Remote Sensing and GIS Models Based on Web Service

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016

  18. A framework for sharing and integrating remote sensing and GIS models based on Web service.

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.

  19. 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

  20. VEGETATION COVERAGE AND IMPERVIOUS SURFACE AREA ESTIMATED BASED ON THE ESTARFM MODEL AND REMOTE SENSING MONITORING

    Directory of Open Access Journals (Sweden)

    R. Hu

    2018-04-01

    Full Text Available Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM, the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC and impervious layer with high spatiotemporal resolution (30 m, 8 day were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1 ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2 The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

  1. Vegetation Coverage and Impervious Surface Area Estimated Based on the Estarfm Model and Remote Sensing Monitoring

    Science.gov (United States)

    Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun

    2018-04-01

    Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

  2. 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.

  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. Evaluation of remotely sensed actual evapotranspiration data for modeling small scale irrigation in Ethiopia.

    Science.gov (United States)

    Taddele, Y. D.; Ayana, E.; Worqlul, A. W.; Srinivasan, R.; Gerik, T.; Clarke, N.

    2017-12-01

    The research presented in this paper is conducted in Ethiopia, which is located in the horn of Africa. Ethiopian economy largely depends on rainfed agriculture, which employs 80% of the labor force. The rainfed agriculture is frequently affected by droughts and dry spells. Small scale irrigation is considered as the lifeline for the livelihoods of smallholder farmers in Ethiopia. Biophysical models are highly used to determine the agricultural production, environmental sustainability, and socio-economic outcomes of small scale irrigation in Ethiopia. However, detailed spatially explicit data is not adequately available to calibrate and validate simulations from biophysical models. The Soil and Water Assessment Tool (SWAT) model was setup using finer resolution spatial and temporal data. The actual evapotranspiration (AET) estimation from the SWAT model was compared with two remotely sensed data, namely the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectrometer (MODIS). The performance of the monthly satellite data was evaluated with correlation coefficient (R2) over the different land use groups. The result indicated that over the long term and monthly the AVHRR AET captures the pattern of SWAT simulated AET reasonably well, especially on agricultural dominated landscapes. A comparison between SWAT simulated AET and AVHRR AET provided mixed results on grassland dominated landscapes and poor agreement on forest dominated landscapes. Results showed that the AVHRR AET products showed superior agreement with the SWAT simulated AET than MODIS AET. This suggests that remotely sensed products can be used as valuable tool in properly modeling small scale irrigation.

  5. Flood Inundation Modelling Under Uncertainty Using Globally and Freely Available Remote Sensing Data

    Science.gov (United States)

    Yan, K.; Di Baldassarre, G.; Giustarini, L.; Solomatine, D. P.

    2012-04-01

    The extreme consequences of recent catastrophic events have highlighted that flood risk prevention still needs to be improved to reduce human losses and economic damages, which have considerably increased worldwide in recent years. Flood risk management and long term floodplain planning are vital for living with floods, which is the currently proposed approach to cope with floods. To support the decision making processes, a significant issue is the availability of data to build appropriate and reliable models, from which the needed information could be obtained. The desirable data for model building, calibration and validation are often not sufficient or available. A unique opportunity is offered nowadays by globally available data which can be freely downloaded from internet. This might open new opportunities for filling the gap between available and needed data, in order to build reliable models and potentially lead to the development of global inundation models to produce floodplain maps for the entire globe. However, there remains the question of what is the real potential of those global remote sensing data, characterized by different accuracy, for global inundation monitoring and how to integrate them with inundation models. This research aims at contributing to understand whether the current globally and freely available remote sensing data (e.g. SRTM, SAR) can be actually used to appropriately support inundation modelling. In this study, the SRTM DEM is used for hydraulic model building, while ENVISAT-ASAR satellite imagery is used for model validation. To test the usefulness of these globally and freely available data, a model based on the high resolution LiDAR DEM and ground data (high water marks) is used as benchmark. The work is carried out on a data-rich test site: the River Alzette in the north of Luxembourg City. Uncertainties are estimated for both SRTM and LiDAR based models. Probabilistic flood inundation maps are produced under the framework of

  6. 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.

  7. 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

  8. 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

  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. 3D Fractal reconstruction of terrain profile data based on digital elevation model

    International Nuclear Information System (INIS)

    Huang, Y.M.; Chen, C.-J.

    2009-01-01

    Digital Elevation Model (DEM) often makes it difficult for terrain reconstruction and data storage due to the failure in acquisition of details with higher resolution. If original terrain of DEM can be simulated, resulting in geographical details can be represented precisely while reducing the data size, then an effective reconstruction scheme is essential. This paper adopts two sets of real-world 3D terrain profile data to proceed data reducing, i.e. data sampling randomly, then reconstruct them through 3D fractal reconstruction. Meanwhile, the quantitative and qualitative difference generated from different reduction rates were evaluated statistically. The research results show that, if 3D fractal interpolation method is applied to DEM reconstruction, the higher reduction rate can be obtained for DEM of larger data size with respect to that of smaller data size under the assumption that the entire terrain structure is still maintained.

  11. Modeling the response of plants and ecosystems to elevated CO sub 2 and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, J.F.; Hilbert, D.W.; Chen, Jia-lin; Harley, P.C.; Kemp, P.R.; Leadley, P.W.

    1992-03-01

    While the exact effects of elevated CO{sub 2} on global climate are unknown, there is a growing consensus among climate modelers that global temperature and precipitation will increase, but that these changes will be non-uniform over the Earth's surface. In addition to these potential climatic changes, CO{sub 2} also directly affects plants via photosynthesis, respiration, and stomatal closure. Global climate change, in concert with these direct effects of CO{sub 2} on plants, could have a significant impact on both natural and agricultural ecosystems. Society's ability to prepare for, and respond to, such changes depends largely on the ability of climate and ecosystem researchers to provide predictions of regional level ecosystem responses with sufficient confidence and adequate lead time.

  12. Modeling the response of plants and ecosystems to elevated CO{sub 2} and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, J.F.; Hilbert, D.W.; Chen, Jia-lin; Harley, P.C.; Kemp, P.R.; Leadley, P.W.

    1992-03-01

    While the exact effects of elevated CO{sub 2} on global climate are unknown, there is a growing consensus among climate modelers that global temperature and precipitation will increase, but that these changes will be non-uniform over the Earth`s surface. In addition to these potential climatic changes, CO{sub 2} also directly affects plants via photosynthesis, respiration, and stomatal closure. Global climate change, in concert with these direct effects of CO{sub 2} on plants, could have a significant impact on both natural and agricultural ecosystems. Society`s ability to prepare for, and respond to, such changes depends largely on the ability of climate and ecosystem researchers to provide predictions of regional level ecosystem responses with sufficient confidence and adequate lead time.

  13. Textured digital elevation model formation from low-cost UAV LADAR/digital image data

    Science.gov (United States)

    Bybee, Taylor C.; Budge, Scott E.

    2015-05-01

    Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

  14. Elevated incidence of dental caries in a mouse model of cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Marcelo A Catalán

    2011-01-01

    Full Text Available Dental caries is the single most prevalent and costly infectious disease worldwide, affecting more than 90% of the population in the U.S. The development of dental cavities requires the colonization of the tooth surface by acid-producing bacteria, such as Streptococcus mutans. Saliva bicarbonate constitutes the main buffering system which neutralizes the pH fall generated by the plaque bacteria during sugar metabolism. We found that the saliva pH is severely decreased in a mouse model of cystic fibrosis disease (CF. Given the close relationship between pH and caries development, we hypothesized that caries incidence might be elevated in the mouse CF model.We induced carious lesions in CF and wildtype mice by infecting their oral cavity with S. mutans, a well-studied cariogenic bacterium. After infection, the mice were fed a high-sucrose diet for 5 weeks (diet 2000. The mice were then euthanized and their jaws removed for caries scoring and bacterial counting. A dramatic increase in caries and severity of lesions scores were apparent in CF mice compared to their wildtype littermates. The elevated incidence of carious lesions correlated with a striking increase in the S. mutans viable population in dental plaque (20-fold increase in CF vs. wildtype mice; p value < 0.003; t test. We also found that the pilocarpine-stimulated saliva bicarbonate concentration was significantly reduced in CF mice (16 ± 2 mM vs. 31 ± 2 mM, CF and wildtype mice, respectively; p value < 0.01; t test.Considering that bicarbonate is the most important pH buffering system in saliva, and the adherence and survival of aciduric bacteria such as S. mutans are enhanced at low pH values, we speculate that the decrease in the bicarbonate content and pH buffering of the saliva is at least partially responsible for the increased severity of lesions observed in the CF mouse.

  15. 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.

  16. Ground-based grasslands data to support remote sensing and ecosystem modeling of terrestrial primary production

    Science.gov (United States)

    Olson, R. J.; Scurlock, J. M. O.; Turner, R. S.; Jennings, S. V.

    1995-01-01

    Estimating terrestrial net primary production (NPP) using remote-sensing tools and ecosystem models requires adequate ground-based measurements for calibration, parameterization, and validation. These data needs were strongly endorsed at a recent meeting of ecosystem modelers organized by the International Geosphere-Biosphere Program's (IGBP's) Data and Information System (DIS) and its Global Analysis, Interpretation, and Modelling (GAIM) Task Force. To meet these needs, a multinational, multiagency project is being coordinated by the IGBP DIS to compile existing NPP data from field sites and to regionalize NPP point estimates to various-sized grid cells. Progress at Oak Ridge National Laboratory (ORNL) on compiling NPP data for grasslands as part of the IGBP DIS data initiative is described. Site data and associated documentation from diverse field studies are being acquired for selected grasslands and are being reviewed for completeness, consistency, and adequacy of documentation, including a description of sampling methods. Data are being compiled in a database with spatial, temporal, and thematic characteristics relevant to remote sensing and global modeling. NPP data are available from the ORNL Distributed Active Archive Center (DAAC) for biogeochemical dynamics. The ORNL DAAC is part of the Earth Observing System Data and Information System, of the US National Aeronautics and Space Administration.

  17. Ground-based grasslands data to support remote sensing and ecosystem modeling of terrestrial primary production

    Energy Technology Data Exchange (ETDEWEB)

    Olson, R.J.; Turner, R.S. [Oak Ridge National Lab., TN (United States); Scurlock, J.M.O. [King`s College London, (England); Jennings, S.V. [Tennessee Univ., Knoxville, TN (United States)

    1995-12-31

    Estimating terrestrial net primary production (NPP) using remote- sensing tools and ecosystem models requires adequate ground-based measurements for calibration, parameterization, and validation. These data needs were strongly endorsed at a recent meeting of ecosystem modelers organized by the International Geosphere-Biosphere Programme`s (IGBP`s) Data and Information System (DIS) and its Global Analysis, Interpretation, and Modelling (GAIM) Task Force. To meet these needs, a multinational, multiagency project is being coordinated by the IGBP DIS to compile existing NPP data from field sites and to regionalize NPP point estimates to various-sized grid cells. Progress at Oak Ridge National Laboratory (ORNL) on compiling NPP data for grasslands as part of the IGBP DIS data initiative is described. Site data and associated documentation from diverse field studies are being acquired for selected grasslands and are being reviewed for completeness, consistency, and adequacy of documentation, including a description of sampling methods. Data are being compiled in a database with spatial, temporal, and thematic characteristics relevant to remote sensing and global modeling. NPP data are available from the ORNL Distributed Active Archive Center (DAAC) for biogeochemical dynamics. The ORNL DAAC is part of the Earth Observing System Data and Information System, of the US National Aeronautics and Space Administration.

  18. 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.

  19. Assessment of the most recent satellite based digital elevation models of Egypt

    Science.gov (United States)

    Rabah, Mostafa; El-Hattab, Ahmed; Abdallah, Mohamed

    2017-12-01

    Digital Elevation Model (DEM) is crucial to a wide range of surveying and civil engineering applications worldwide. Some of the DEMs such as ASTER, SRTM1 and SRTM3 are freely available open source products. In order to evaluate the three DEMs, the contribution of EGM96 are removed and all DEMs heights are becoming ellipsoidal height. This step was done to avoid the errors occurred due to EGM96. 601 points of observed ellipsoidal heights compared with the three DEMs, the results show that the SRTM1 is the most accurate one, that produces mean height difference and standard deviations equal 2.89 and ±8.65 m respectively. In order to increase the accuracy of SRTM1 in EGYPT, a precise Global Geopotential Model (GGM) is needed to convert the SRTM1 ellipsoidal height to orthometric height, so that, we quantify the precision of most-recent released GGM (five models). The results show that, the GECO model is the best fit global models over Egypt, which produces a standard deviation of geoid undulation differences equals ±0.42 m over observed 17 HARN GPS/leveling stations. To confirm an enhanced DEM in EGYPT, the two orthometric height models (SRTM1 ellipsoidal height + EGM96) and (SRTM1 ellipsoidal height + GECO) are assessment with 17 GPS/leveling stations and 112 orthometric height stations, the results show that the estimated height differences between the SRTM1 before improvements and the enhanced model are at rate of 0.44 m and 0.06 m respectively.

  20. 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.