WorldWideScience

Sample records for elevation models remote

  1. Mapping three-dimensional geological features from remotely-sensed images and digital elevation models

    Science.gov (United States)

    Morris, Kevin Peter

    Accurate mapping of geological structures is important in numerous applications, ranging from mineral exploration through to hydrogeological modelling. Remotely sensed data can provide synoptic views of study areas enabling mapping of geological units within the area. Structural information may be derived from such data using standard manual photo-geologic interpretation techniques, although these are often inaccurate and incomplete. The aim of this thesis is, therefore, to compile a suite of automated and interactive computer-based analysis routines, designed to help a the user map geological structure. These are examined and integrated in the context of an expert system. The data used in this study include Digital Elevation Model (DEM) and Airborne Thematic Mapper images, both with a spatial resolution of 5m, for a 5 x 5 km area surrounding Llyn Cow lyd, Snowdonia, North Wales. The geology of this area comprises folded and faulted Ordo vician sediments intruded throughout by dolerite sills, providing a stringent test for the automated and semi-automated procedures. The DEM is used to highlight geomorphological features which may represent surface expressions of the sub-surface geology. The DEM is created from digitized contours, for which kriging is found to provide the best interpolation routine, based on a number of quantitative measures. Lambertian shading and the creation of slope and change of slope datasets are shown to provide the most successful enhancement of DEMs, in terms of highlighting a range of key geomorphological features. The digital image data are used to identify rock outcrops as well as lithologically controlled features in the land cover. To this end, a series of standard spectral enhancements of the images is examined. In this respect, the least correlated 3 band composite and a principal component composite are shown to give the best visual discrimination of geological and vegetation cover types. Automatic edge detection (followed by line

  2. Capturing Micro-topography of an Arctic Tundra Landscape through Digital Elevation Models (DEMs) Acquired from Various Remote Sensing Platforms

    Science.gov (United States)

    Vargas, S. A., Jr.; Tweedie, C. E.; Oberbauer, S. F.

    2013-12-01

    The need to improve the spatial and temporal scaling and extrapolation of plot level measurements of ecosystem structure and function to the landscape level has been identified as a persistent research challenge in the arctic terrestrial sciences. Although there has been a range of advances in remote sensing capabilities on satellite, fixed wing, helicopter and unmanned aerial vehicle platforms over the past decade, these present costly, logistically challenging (especially in the Arctic), technically demanding solutions for applications in an arctic environment. Here, we present a relatively low cost alternative to these platforms that uses kite aerial photography (KAP). Specifically, we demonstrate how digital elevation models (DEMs) were derived from this system for a coastal arctic landscape near Barrow, Alaska. DEMs of this area acquired from other remote sensing platforms such as Terrestrial Laser Scanning (TLS), Airborne Laser Scanning, and satellite imagery were also used in this study to determine accuracy and validity of results. DEMs interpolated using the KAP system were comparable to DEMs derived from the other platforms. For remotely sensing acre to kilometer square areas of interest, KAP has proven to be a low cost solution from which derived products that interface ground and satellite platforms can be developed by users with access to low-tech solutions and a limited knowledge of remote sensing.

  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. 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

  5. Digtial Elevation Model (DEM) 250K

    Data.gov (United States)

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

  6. 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. 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...

  8. 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...

  9. 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...

  10. Arecibo, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

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

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  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. 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...

  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. 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...

  14. 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...

  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. Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

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

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. Fajardo, Puerto Rico Coastal Digital Elevation Model

    Data.gov (United States)

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

  14. 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...

  15. Dutch Harbor, Alaska Coastal Digital Elevation Model

    Data.gov (United States)

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

  16. 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...

  17. 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...

  18. 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...

  19. 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....

  20. 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.

  1. 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

  2. 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...... of firn compaction to correct ICESat measurements and assessing the present mass loss of the Greenland ice sheet. Validation of the model against the radar data gives good results and confidence in using the model to answer important questions. Questions such as; how large is the firn compaction...... 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...

  3. 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.

  4. Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques

    OpenAIRE

    Miliaresis, George

    2014-01-01

    Recognition of landforms from digital elevation models and satellite imagery with expert systems, pattern recognition and image processing techniques. PhD Thesis, Remote Sensing & Terrain Pattern Recognition),National Technical University of Athens, Dpt. of Topography (2000).

  5. 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...... 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......-density coverage. During campaigns in 2000, 2003 and 2005, we have collected and processed ice-sheet surface elevation and ice-thickness data, acquired with a laser altimeter and a 60~MHz ice-penetrating radar. Both instruments were mounted on a small Twin-Otter aircraft which were positioned using three onboard...

  6. 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

  7. 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.

  8. 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...

  9. 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.

  10. 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

  11. Model-based acoustic remote sensing of seafloor characteristics

    Digital Repository Service at National Institute of Oceanography (India)

    De, Ch.; Chakraborty, B.

    =UTF-8 3868 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 49, NO. 10, OCTOBER 2011 Model-Based Acoustic Remote Sensing of Seafloor Characteristics Chanchal De and Bishwajit Chakraborty, Member, IEEE Abstract—The characterization... of the estimated values of seafloor roughness spectrum parameters with the values of sediment mean grain size are compared with published information available in the literature. Index Terms—Acoustic remote sensing, backscatter model, echo envelope, inversion, mean...

  12. 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.

  13. 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

  14. 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...

  15. Creating Digital Elevation Model Using a Mobile Device

    Science.gov (United States)

    Durmaz, A. İ.

    2017-11-01

    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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Influence of Elevation Data Source on 2D Hydraulic Modelling

    Science.gov (United States)

    Bakuła, Krzysztof; StĘpnik, Mateusz; Kurczyński, Zdzisław

    2016-08-01

    The aim of this paper is to analyse the influence of the source of various elevation data on hydraulic modelling in open channels. In the research, digital terrain models from different datasets were evaluated and used in two-dimensional hydraulic models. The following aerial and satellite elevation data were used to create the representation of terrain-digital terrain model: airborne laser scanning, image matching, elevation data collected in the LPIS, EuroDEM, and ASTER GDEM. From the results of five 2D hydrodynamic models with different input elevation data, the maximum depth and flow velocity of water were derived and compared with the results of the most accurate ALS data. For such an analysis a statistical evaluation and differences between hydraulic modelling results were prepared. The presented research proved the importance of the quality of elevation data in hydraulic modelling and showed that only ALS and photogrammetric data can be the most reliable elevation data source in accurate 2D hydraulic modelling.

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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....

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. Niue 3 arc-second Digital Elevation Model

    Data.gov (United States)

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

  17. Antarctic 5-km Digital Elevation Model from ERS-1 Altimetry

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a digital elevation model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data...

  18. 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....

  19. 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...

  20. 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...

  1. Port San Luis, California Coastal Digital Elevation Model

    Data.gov (United States)

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

  2. 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...

  3. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    1997-01-01

    This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, s

  4. Remote sensing and photogrammetric studies: Part D: repeatability of elevation measurements--Apollo photography

    Science.gov (United States)

    Wu, Sherman S.C.; Schafer, Francis J.; Nakata, Gary M.; Jordan, Raymond

    1973-01-01

    Stereoscopic photographs of the Moon taken by the metric and panoramic cameras on board the service module of Apollo spacecraft provide a source for quantitative data on lunar topography. The accuracy of the topographic data depends, in part, on the repeatability of elevation measurements. The repeatability depends on contrast in the stereoscopic image and is affected by many factors, such as photographic quality, the photogrammetric instrument used, and illumination conditions. For the Moon, illumination conditions are important so that repeatability of elevation measurements may be statistically related to Sun elevation angles, local slopes, and albedos of surfaces. We have examined the effect of Sun elevation angle on repeatability, using Apollo 15 photographs (Wu, unpublished data), and extended the results to slope-related effects.

  5. 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 on ...

  6. 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)

  7. Remote Raman Spectroscopy of Minerals at Elevated Temperature Relevant to Venus Exploration

    Science.gov (United States)

    Sharma, Shiv K.; Misra, Anupam K.; Singh, Upendra N.

    2008-01-01

    We have used a remote time-resolved telescopic Raman system equipped with 532 nm pulsed laser excitation and a gated intensified CCD (ICCD) detector for measuring Raman spectra of a number of minerals at high temperature to 970 K. Remote Raman measurements were made with samples at 9-meter in side a high-temperature furnace by gating the ICCD detector with 2 micro-sec gate to minimize interference from blackbody emission from mineral surfaces at high temperature as well as interference from ambient light. A comparison of Raman spectra of gypsum (CaSO4.2H2O), dolomite (CaMg(CO3)2), and olivine (Mg2Fe2-xSiO4), as a function of temperature shows that the Raman lines remains sharp and well defined even in the high-temperature spectra. In the case of gypsum, Raman spectral fingerprints of CaSO4.H2O at 518 K were observed due to dehydration of gypsum. In the case of dolomite, partial mineral dissociation was observed at 973 K at ambient pressure indicating that some of the dolomite might survive on Venus surface that is at approximately 750 K and 92 atmospheric pressure. Time-resolved Raman spectra of low clino-enstatite (MgSiO3) measured at 75 mm from the sample in side the high-temperature furnace also show that the Raman lines remains sharp and well defined in the high temperature spectra. These high-temperature remote Raman spectra of minerals show that time-resolved Raman spectroscopy can be used as a potential tool for exploring Venus surface mineralogy at shorter (75 mm) and long (9 m) distances from the samples both during daytime and nighttime. The remote Raman system could also be used for measuring profiles of molecular species in the dense Venus atmosphere during descent as well as on the surface.

  8. 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

  9. The National Map seamless digital elevation model specifications

    Science.gov (United States)

    Archuleta, Christy-Ann M.; Constance, Eric W.; Arundel, Samantha T.; Lowe, Amanda J.; Mantey, Kimberly S.; Phillips, Lori A.

    2017-08-02

    This specification documents the requirements and standards used to produce the seamless elevation layers for The National Map of the United States. Seamless elevation data are available for the conterminous United States, Hawaii, Alaska, and the U.S. territories, in three different resolutions—1/3-arc-second, 1-arc-second, and 2-arc-second. These specifications include requirements and standards information about source data requirements, spatial reference system, distribution tiling schemes, horizontal resolution, vertical accuracy, digital elevation model surface treatment, georeferencing, data source and tile dates, distribution and supporting file formats, void areas, metadata, spatial metadata, and quality assurance and control.

  10. Group Elevator Peak Scheduling Based on Robust Optimization Model

    OpenAIRE

    ZHANG, J.; ZONG, Q.

    2013-01-01

    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 re...

  11. 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...... 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...

  12. 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...

  13. 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.

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

    DEFF Research Database (Denmark)

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

    Currently available Digital Elevation Models(DEMs) of the Greenland Ice Sheet (GrIS) were originally derived from radar altimetry data, e.g. Bamber (Bamber et al., 2001) and later improved by photoclinometry to fill the regions between orbits (Scambos and Haran, 2002). The elevation error...... of these DEMs is a few meters in the higher part (above 2000 m) of the ice sheet, but it can be as much as 50-100 meters in marginal regions. The relatively low resolution and accuracy poses a problem, especially for ice sheet modeling. Although accurate elevation data have been collected by airborne...... m)), a high resolution, consistent DEM of GrIS is not yet available. This is due to various problems, such as different error sources in the data and different dates of data acquisition. In order to overcome these difficulties, we generated a multi-resolution DEM of GrIS, reflecting June 2008...

  15. Accuracy Assessment of Open Source Digital Elevation Models

    Directory of Open Access Journals (Sweden)

    Aqeel Abboud Abdul Hassan

    2018-02-01

    Full Text Available Digital Elevation Model is a three-dimensional representation of the earth's surface, which is essential for Geoscience and hydrological implementations. DEM can be created utilizing Photogrammetry techniques, radar interferometry, laser scanning and land surveying. There are some world agencies provide open source digital elevation models which are freely available for all users, such as the National Aeronautics and Space Administration (NASA, Japan Aerospace Exploration Agency’s (JAXA and others. ALOS, SRTM and ASTER are satellite based DEMs which are open source products. The technologies that are used for obtaining raw data and the methods used for its processing and on the other hand the characteristics of natural land and land cover type, these and other factors are the cause of implied errors produced in the digital elevation model which can't be avoided. In this paper, ground control points observed by the differential global positioning system DGPS were used to compare the validation and performance of different satellite based digital elevation models. For validation, standard statistical tests were applied such as Mean Error (ME and Root Mean Square Error (RMSE which showed ALOS DEM had ME and RMSE are -1.262m and 1.988m, while SRTM DEM had ME of -0.782m with RMSE of 2.276m and ASTER DEM had 4.437m and 6.241m, respectively. These outcomes can be very helpful for analysts utilizing such models in different areas of work.

  16. Comparison of digital elevation models and relevant derived attributes

    Science.gov (United States)

    Li, Xinchuan; Zhang, Youjing; Jin, Xiuliang; He, Qiaoning; Zhang, Xiuping

    2017-10-01

    The digital elevation model (DEM) and its derivative attributes are important parameters for evaluating any process using digital terrain analysis. Five freely available global DEM products including Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model version 2 (ASTER GDEM2), Shuttle Radar Topographic Mission version 4.1 (SRTM V4.1), Global Multiresolution Terrain Elevation Data 2010 (GMTED2010), EarthEnv-DEM90, and Global 30 Arc-Second Elevation (GTOPO30) were assessed in this study. The objective of this study was to compare the differences of elevations, slopes, and topographic wetness indices (TWIs) derived from these five DEM products. SRTM V4.1 showed a better accuracy [root mean square error (RMSE)=4.87 m] than ASTER GDEM2 (RMSE=7.08 m) based on ICESat/GLAS (the Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) laser altimetry points. ICESat/GLAS data were then selected as the benchmark to rectify the SRTM V4.1 data using the simple kriging (SK) interpolation method. The corrected high-accuracy SRTM V4.1 data (RMSE=1.14 m) were then regarded as the reference data. EarthEnv-DEM90 displayed the best accuracy in the DEM and slope, whereas the TWI accuracy of GMTED2010 was best. The accuracy of topographic attributes was sensitive to the roughness of the terrain. DEM and slope displayed a larger error variance as the elevation increased. DEM was sensitive to the data source and slope was sensitive to the data source and spatial resolution. TWI was influenced by data source and spatial resolution. As the spatial resolution decreased, the differences of topographic attributes tended to decrease.

  17. 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

  18. Determining the optimum cell size of digital elevation model for ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 120; Issue 4. Determining the optimum cell size of digital elevation model for hydrologic ... Technology, Bahal 127 028, Bhiwani, Haryana, India. Agricultural & Food Engineering Department, Indian Institute of Technology, Kharagpur-721302, West Bengal, India.

  19. 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.

  20. 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

  1. Extraction of terrain features from digital elevation models

    Science.gov (United States)

    Price, Curtis V.; Wolock, David M.; Ayers, Mark A.

    1989-01-01

    Digital elevation models (DEMs) are being used to determine variable inputs for hydrologic models in the Delaware River basin. Recently developed software for analysis of DEMs has been applied to watershed and streamline delineation. The results compare favorably with similar delineations taken from topographic maps. Additionally, output from this software has been used to extract other hydrologic information from the DEM, including flow direction, channel location, and an index describing the slope and shape of a watershed.

  2. 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.

  3. Hydrologic model calibration using remotely-sensed data in Alaska

    Science.gov (United States)

    Driscoll, J. M.; Hay, L.; Van Beusekom, A. E.

    2016-12-01

    Watershed models in Alaska are critical for understanding snow- and glacier-dominated hydrologic processes in a changing climate. The highly diverse, frozen, and remote landscapes in Alaska present a host of new challenges for broad-scale hydrologic model development, including a notable absence of field-measured streamflow data. Without this commonly-used data for model calibration, alternative methods need to be developed in order to model hydrologic processes Alaska. Calibration methods that use remotely-sensed data in multi-objective, step-wise procedures were developed in this study. A calibration method using snow covered area (SCA) measured by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) was developed for a daily, deterministic, physically-based watershed model. The model selected for this study was the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS), and focused on a 62,500-sqkm test basin in southeastern Alaska from 2000 to 2014. Watershed model calibration to SCA ensures model processes adequately estimate transitional model states during snowmelt, a dominant hydrologic process in the basin. Gridded SCA data measuring fractional coverage were spatially aggregated to hydrologic response units within the basin. Model results were aggregated to eleven subbasins for calibration, comparison, and evaluation. Calibration of the subbasin watersheds to intermediate snowmelt process states, such as daily SCA, will likely also improve model estimates of solar radiation, potential evapotranspiration, annual water balance, and components of daily runoff. In Alaska where snow and glacier-fed systems are abundant, observed data are often scarce; therefore the development of calibration methods with remotely-sensed data are critical for improvement of watershed models which can then be used to estimate response to climate change. This study provides a method using remotely-sensed snow cover data to overcome field-measured data

  4. Modeling, simulation, and analysis of optical remote sensing systems

    Science.gov (United States)

    Kerekes, John Paul; Landgrebe, David A.

    1989-01-01

    Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

  5. Sensitivity of Coastal Flood Risk Assessments to Digital Elevation Models

    Directory of Open Access Journals (Sweden)

    Bas van de Sande

    2012-07-01

    Full Text Available Most coastal flood risk studies make use of a Digital Elevation Model (DEM in addition to a projected flood water level in order to estimate the flood inundation and associated damages to property and livelihoods. The resolution and accuracy of a DEM are critical in a flood risk assessment, as land elevation largely determines whether a location will be flooded or will remain dry during a flood event. Especially in low lying deltaic areas, the land elevation variation is usually in the order of only a few decimeters, and an offset of various decimeters in the elevation data has a significant impact on the accuracy of the risk assessment. Publicly available DEMs are often used in studies for coastal flood risk assessments. The accuracy of these datasets is relatively low, in the order of meters, and is especially low in comparison to the level of accuracy required for a flood risk assessment in a deltaic area. For a coastal zone area in Nigeria (Lagos State an accurate LiDAR DEM dataset was adopted as ground truth concerning terrain elevation. In the case study, the LiDAR DEM was compared to various publicly available DEMs. The coastal flood risk assessment using various publicly available DEMs was compared to a flood risk assessment using LiDAR DEMs. It can be concluded that the publicly available DEMs do not meet the accuracy requirement of coastal flood risk assessments, especially in coastal and deltaic areas. For this particular case study, the publically available DEMs highly overestimated the land elevation Z-values and thereby underestimated the coastal flood risk for the Lagos State area. The findings are of interest when selecting data sets for coastal flood risk assessments in low-lying deltaic areas.

  6. 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

  7. 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

    levels are therefore recommended to take into account both local sources and local atmospheric transport, and not to rely only on describing regional to long-range transport of pollen. The derived pollen source inventory can be entered into local-scale atmospheric transport models in combination...

  8. 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

  9. 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...

  10. Distributed calibrating snow models using remotely sensed snow cover information

    Science.gov (United States)

    Li, H.

    2015-12-01

    Distributed calibrating snow models using remotely sensed snow cover information Hongyi Li1, Tao Che1, Xin Li1, Jian Wang11. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China For improving the simulation accuracy of snow model, remotely sensed snow cover data are used to calibrate spatial parameters of snow model. A physically based snow model is developed and snow parameters including snow surface roughness, new snow density and critical threshold temperature distinguishing snowfall from precipitation, are spatially calibrated in this study. The study region, Babaohe basin, located in northwestern China, have seasonal snow cover and with complex terrain. The results indicates that the spatially calibration of snow model parameters make the simulation results more reasonable, and the simulated snow accumulation days, plot-scale snow depth are more better than lumped calibration.

  11. The Utilisation of Digital Elevation Models in the Monitoring of Global Wetlands

    Science.gov (United States)

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

    2009-11-01

    Wetlands are one of the planets most vital hydrological systems, but also one of its most fragile, with slight changes in elevation dramatically affecting surface water flow. These sites require constant monitoring in order for fully informed water management decisions; however they are often located in the most remote areas making in-situ measurements hard to obtain. Satellite based observation systems are therefore vital in monitoring the changes taking place within these sites.ACE2 is the new Global Digital Elevation model derived from merging over 100 million altimeter data points with the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). This new dataset has improved the orthometric heights currently available over numerous wetlands globally. This paper presents results over a selection of the largest wetlands including the Okavango Delta and the Sudd marshes.This paper also examines the impact of DEMs on the monitoring capability of wetlands by Satellite Radar Altimetry. Accurate masks derived from the DEMs enable results to be obtained from within the wetlands and also facilitate the generation of inflow/outflow water heights. Furthermore the ability of the Radar Altimeter to obtain a signal representing the "brightness" of the ground (Sigma0), coupled with an accurate DEM, can allow an estimate of those areas seasonally inundated.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. Use of remotely sensed precipitation and leaf area index in a distributed hydrological model

    DEFF Research Database (Denmark)

    Andersen, Jens; Dybkjær, Gorm Ibsen; Jensen, Karsten Høgh

    2002-01-01

    distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration......distributed hydrological modelling, remote sensing, precipitation, leaf area index, NOAA AVHRR, cold cloud duration...

  17. Perspectives in using a remotely sensed dryness index in distributed hydrological models at river basin scale

    DEFF Research Database (Denmark)

    Andersen, J.; Sandholt, Inge; Jensen, Karsten Høgh

    2002-01-01

    Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture......Remote Sensing, hydrological modelling, dryness index, surface temperature, vegetation index, Africa, Senegal, soil moisture...

  18. 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

  19. 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.

  20. 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.

  1. Remote Ischemic Perconditioning to Reduce Reperfusion Injury During Acute ST-Segment-Elevation Myocardial Infarction: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    McLeod, Shelley L; Iansavichene, Alla; Cheskes, Sheldon

    2017-05-17

    Remote ischemic conditioning (RIC) is a noninvasive therapeutic strategy that uses brief cycles of blood pressure cuff inflation and deflation to protect the myocardium against ischemia-reperfusion injury. The objective of this systematic review was to determine the impact of RIC on myocardial salvage index, infarct size, and major adverse cardiovascular events when initiated before catheterization. Electronic searches of Medline, Embase, and Cochrane Central Register of Controlled Trials were conducted and reference lists were hand searched. Randomized controlled trials comparing percutaneous coronary intervention (PCI) with and without RIC for patients with ST-segment-elevation myocardial infarction were included. Two reviewers independently screened abstracts, assessed quality of the studies, and extracted data. Data were pooled using random-effects models and reported as mean differences and relative risk with 95% confidence intervals. Eleven articles (9 randomized controlled trials) were included with a total of 1220 patients (RIC+PCI=643, PCI=577). Studies with no events were excluded from meta-analysis. The myocardial salvage index was higher in the RIC+PCI group compared with the PCI group (mean difference: 0.08; 95% confidence interval, 0.02-0.14). Infarct size was reduced in the RIC+PCI group compared with the PCI group (mean difference: -2.46; 95% confidence interval, -4.66 to -0.26). Major adverse cardiovascular events were lower in the RIC+PCI group (9.5%) compared with the PCI group (17.0%; relative risk: 0.57; 95% confidence interval, 0.40-0.82). RIC appears to be a promising adjunctive treatment to PCI for the prevention of reperfusion injury in patients with ST-segment-elevation myocardial infarction; however, additional high-quality research is required before a change in practice can be considered. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

  2. Use of remotely sensed land surface temperature as a proxy for air temperatures at high elevations: Findings from a 5000 m elevational transect across Kilimanjaro

    Science.gov (United States)

    Pepin, N. C.; Maeda, E. E.; Williams, R.

    2016-09-01

    High elevations are thought to be warming more rapidly than lower elevations, but there is a lack of air temperature observations in high mountains. This study compares instantaneous values of land surface temperature (10:30/22:30 and 01:30/13:30 local solar time) as measured by Moderate Resolution Imaging Spectroradiometer MOD11A2/MYD11A2 at 1 km resolution from the Terra and Aqua platforms, respectively, with equivalent screen-level air temperatures (in the same pixel). We use a transect of 22 in situ weather stations across Kilimanjaro ranging in elevation from 990 to 5803 m, one of the biggest elevational ranges in the world. There are substantial differences between LST and Tair, sometimes up to 20°C. During the day/night land surface temperature tends to be higher/lower than Tair. LST-Tair differences (ΔT) show large variance, particularly during the daytime, and tend to increase with elevation, particularly on the NE slope which faces the morning Sun. Differences are larger in the dry seasons (JF and JJAS) and reduce in cloudy seasons. Healthier vegetation (as measured by normalized difference vegetation index) and increased humidity lead to reduced daytime surface heating above air temperature and lower ΔT, but these relationships weaken with elevation. At high elevations transient snow cover cools LST more than Tair. The predictability of ΔT therefore reduces. It will therefore be challenging to use satellite data at high elevations as a proxy for in situ air temperatures in climate change assessments, especially for daytime Tmax. ΔT is smaller and more consistent at night, so it will be easier to use LST to monitor changes in Tmin.

  3. 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...

  4. 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.

  5. 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

  6. 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.

  7. Cooling tower and plume modeling for satellite remote sensing applications

    Energy Technology Data Exchange (ETDEWEB)

    Powers, B.J.

    1995-05-01

    It is often useful in nonproliferation studies to be able to remotely estimate the power generated by a power plant. Such information is indirectly available through an examination of the power dissipated by the plant. Power dissipation is generally accomplished either by transferring the excess heat generated into the atmosphere or into bodies of water. It is the former method with which we are exclusively concerned in this report. We discuss in this report the difficulties associated with such a task. In particular, we primarily address the remote detection of the temperature associated with the condensed water plume emitted from the cooling tower. We find that the effective emissivity of the plume is of fundamental importance for this task. Having examined the dependence of the plume emissivity in several IR bands and with varying liquid water content and droplet size distributions, we conclude that the plume emissivity, and consequently the plume brightness temperature, is dependent upon not only the liquid water content and band, but also upon the droplet size distribution. Finally, we discuss models dependent upon a detailed point-by-point description of the hydrodynamics and thermodynamics of the plume dynamics and those based upon spatially integrated models. We describe in detail a new integral model, the LANL Plume Model, which accounts for the evolution of the droplet size distribution. Some typical results obtained from this model are discussed.

  8. 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.

  9. 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.

  10. 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.

  11. Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

    Science.gov (United States)

    Steyaert, Louis T.; Loveland, Thomas R.; Brown, Jesslyn F.; Reed, Bradley C.

    1993-01-01

    Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues

  12. 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).

  13. `Dem DEMs: Comparing Methods of Digital Elevation Model Creation

    Science.gov (United States)

    Rezza, C.; Phillips, C. B.; Cable, M. L.

    2017-12-01

    Topographic details of Europa's surface yield implications for large-scale processes that occur on the moon, including surface strength, modification, composition, and formation mechanisms for geologic features. In addition, small scale details presented from this data are imperative for future exploration of Europa's surface, such as by a potential Europa Lander mission. A comparison of different methods of Digital Elevation Model (DEM) creation and variations between them can help us quantify the relative accuracy of each model and improve our understanding of Europa's surface. In this work, we used data provided by Phillips et al. (2013, AGU Fall meeting, abs. P34A-1846) and Schenk and Nimmo (2017, in prep.) to compare DEMs that were created using Ames Stereo Pipeline (ASP), SOCET SET, and Paul Schenk's own method. We began by locating areas of the surface with multiple overlapping DEMs, and our initial comparisons were performed near the craters Manannan, Pwyll, and Cilix. For each region, we used ArcGIS to draw profile lines across matching features to determine elevation. Some of the DEMs had vertical or skewed offsets, and thus had to be corrected. The vertical corrections were applied by adding or subtracting the global minimum of the data set to create a common zero-point. The skewed data sets were corrected by rotating the plot so that it had a global slope of zero and then subtracting for a zero-point vertical offset. Once corrections were made, we plotted the three methods on one graph for each profile of each region. Upon analysis, we found relatively good feature correlation between the three methods. The smoothness of a DEM depends on both the input set of images and the stereo processing methods used. In our comparison, the DEMs produced by SOCET SET were less smoothed than those from ASP or Schenk. Height comparisons show that ASP and Schenk's model appear similar, alternating in maximum height. SOCET SET has more topographic variability due to its

  14. 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

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

    Science.gov (United States)

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

    1975-01-01

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

  16. Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau

    Science.gov (United States)

    Purinton, Benjamin; Bookhagen, Bodo

    2017-04-01

    In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30 m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12 m TanDEM-X, 10 m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5 m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000 m of elevation. For the 30 m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.

  17. Evaluation of Evapotranspiration Partitioning in Remote Sensing Models

    Science.gov (United States)

    Talsma, C.; Good, S. P.; Jimenez, C.; Martens, B.; Fisher, J.

    2017-12-01

    Satellite driven evapotranspiration(ET) products have become a preferred method in estimating global and regional evaporative fluxes. However, the estimated ET partitions of soil evaporation, transpiration, and canopy interception show strong divergence between models and have largely not been validated. This paper considers three such algorithms: The Penman-Montieth model from the Moderate Resolution Imaging Spectroradiometer (PM-MODIS), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), and the Global Land Evaporation Amsterdam Model (GLEAM). Modeled partition outputs from 2005-2007 are validated against a compiled list of field studies spanning several decades. Field studies using stable isotope tracers, sap-flow measurements, radial flowmeters, and other techniques to measure ET components were included. The correlation between annual estimates of field and remote sensing modeled soil evaporation (r2= 0.12-0.22, N=38), interception (r2 = 0.32-0.85, N=24), and transpiration (r2 = 0.37-0.56, N=38) are relatively poor compared to the quality of total ET estimates (r2= 0.61-0.74, N=38). The modeled estimates of soil evaporation are generally poor across all models and are likely culpable for much of the partitioning error. Possible reasons for divergences between and amongst modeled estimates of ET partitions are also presented.

  18. The utility of remotely-sensed vegetative and terrain covariates at different spatial resolutions in modelling soil and watertable depth (for digital soil mapping)

    OpenAIRE

    Taylor, J. A.; Jacob, Frédéric; Galleguillos, M.; Prevot, L.; Guix, N.; Lagacherie, P.

    2013-01-01

    Digital soil modelling and mapping is reliant on the availability and utility of easily derived and accessible covariates. In this paper, the value of covariates derived from a time-series of remotely-sensed ASTER satellite imagery and digital elevation models were evaluated for modelling two soil attributes - soil depth and watertable depth. Modelling was performed at two resolutions: a fine resolution (15 m pixels) that relates to the resolution of the ASTER Visible-NIR bands, and a larger ...

  19. 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

  20. 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

  1. Frequency Modulation Spectroscopy Modeling for Remote Chemical Detection

    Energy Technology Data Exchange (ETDEWEB)

    Sheen, David M.

    2000-09-30

    Frequency modulation (FM) spectroscopy techniques show promise for active infrared remote chemical sensing. FM spectroscopy techniques have reduced sensitivity to optical and electronic noise, and are relatively immune to the effects of various electronic and mechanical drifts. FM systems are responsive to sharp spectral features and can therefore reduce the effects of spectral clutter due to interfering chemicals in the plume or in the atmosphere. The relatively high modulation frequencies used for FM also reduces the effects of albedo (reflectance) and plume variations. Conventional differential absorption lidar (DIAL) systems are performance limited by the noise induced by speckle. Analysis presented in this report shows that FM based sensors may reduce the effects of speckle by one to two orders of magnitude. This can result in reduced dwell times and faster area searches, as well as reducing various forms of spatial clutter. FM systems will require a laser system that is continuously tunable at relatively high frequencies (0.1 to 20 MHz). One promising candidate is the quantum-cascade (QC) laser [1, 2]. The QC laser is potentially capable of power levels on the order of 1 Watt and frequency tuning on the order of 3 - 6 GHz, which is the performance level required for FM spectroscopy based remote sensing. In this report we describe a high-level numerical model for an FM spectroscopy based remote sensing system, and application to two unmanned airborne vehicle (UAV) scenarios. A Predator scenario operating at a slant range of 6.5 km with a 10 cm diameter telescope, and a Global Hawk scenario operating at a range of 30 km with a 20 cm diameter telescope, has been assumed to allow estimation of the performance of potential FM systems.

  2. Modeling Relationships among 217 Fires Using Remote Sensing of Burn Severity in Southern Pine Forests

    Directory of Open Access Journals (Sweden)

    Amr Abd-Elrahman

    2011-09-01

    Full Text Available Pine flatwoods forests in the southeastern US have experienced severe wildfires over the past few decades, often attributed to fuel load build-up. These forest communities are fire dependent and require regular burning for ecosystem maintenance and health. Although prescribed fire has been used to reduce wildfire risk and maintain ecosystem integrity, managers are still working to reintroduce fire to long unburned areas. Common perception holds that reintroduction of fire in long unburned forests will produce severe fire effects, resulting in a reluctance to prescribe fire without first using expensive mechanical fuels reduction techniques. To inform prioritization and timing of future fire use, we apply remote sensing analysis to examine the set of conditions most likely to result in high burn severity effects, in relation to vegetation, years since the previous fire, and historical fire frequency. We analyze Landsat imagery-based differenced Normalized Burn Ratios (dNBR to model the relationships between previous and future burn severity to better predict areas of potential high severity. Our results show that remote sensing techniques are useful for modeling the relationship between elevated risk of high burn severity and the amount of time between fires, the type of fire (wildfire or prescribed burn, and the historical frequency of fires in pine flatwoods forests.

  3. 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.

  4. 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

  5. Use of remote sensing to model ungauged Chilean basins

    Science.gov (United States)

    Vasquez, Nicolas; Vargas, Ximena

    2016-04-01

    Calibration of hydrological models is usually performed in gauged basins with streamflow data, which is the result of the hydrological cycle processes, due to a poor monitoring system of other processes like melting, infiltration, evapotranspiration or sublimation. This approach can generate several parameters combinations with similar streamflow results and choosing a reliable set of parameters can be challenging, especially in ungauged basins. Remote sensing can be useful because is an additional source of ungauged variables, and is distributed in space and time. This is valuable information related to the processes of hydrological cycle, and it helps to represent the basin with physically based models where the focus is on the processes, such as the Cold Regional Hydrological Model (CRHM). There are several satellites products related to the hydrological cycle such as snow covered area, albedo, evapotranspiration or surface temperature, in the case of MODIS, rain rate from TRMM, Soil moisture from SMOS or snow water equivalent (SWE) from AMSR, and these can be used to improve the representation of the processes in a basin or, in the case of this work, to estimate stream flow using remote sensing only. The study area is Elqui River, in northern Chile, with a semi-arid mediterranean climate and a snow driven regime due to the Andes, where snow accumulation and snowmelt control water availability and the maximum snow covered area reach 50% of the total basin. Several satellite products related principally to snow are considered to represent the variation of the snowpack in space and time as inputs to the model or as state variables.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. A new, high-resolution digital elevation model of Greenland fully validated with airborne laser altimeter data

    DEFF Research Database (Denmark)

    Bamber, J.L.; Ekholm, Simon; Krabill, W.B.

    2001-01-01

    coverage existed. The data were interpolated onto a regular grid with a spacing of similar to1 km. The accuracy of the resultant digital elevation model over the ice sheet was assessed using independent and spatially extensive measurements from an airborne laser altimeter that had an accuracy of between 10......A new digital elevation model of the Greenland ice sheet and surrounding rock outcrops has been produced at 1-km postings from a comprehensive suite of satellite remote sensing and cartographic data sets. Height data over the ice sheet were mainly from ERS-1 and Geosat radar altimetry. These data...... and 12 cm. In a comparison with the laser altimetry the digital elevation model was found to have a slope-dependent accuracy ranging from -1.04 +/-1.98 m to -0.06 +/- 14.33 m over the ice sheet for a slope range of 0.0-1.0 degrees. The mean accuracy over the whole ice sheet was -0.33 +/-6.97 m. Over...

  14. 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

  15. 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...

  16. Enhanced Modeling of Remotely Sensed Annual Land Surface Temperature Cycle

    Science.gov (United States)

    Zou, Z.; Zhan, W.; Jiang, L.

    2017-09-01

    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.

  17. Remote Sensing and Modeling of Cyclone Monica near Peak Intensity

    Directory of Open Access Journals (Sweden)

    Stephen L. Durden

    2010-07-01

    Full Text Available Cyclone Monica was an intense Southern Hemisphere tropical cyclone of 2006. Although no in situ measurements of Monica’s inner core were made, microwave, infrared, and visible satellite instruments observed Monica before and during peak intensity through landfall on Australia’s northern coast. The author analyzes remote sensing measurements in detail to investigate Monica’s intensity. While Dvorak analysis of its imagery argues that it was of extreme intensity, infrared and microwave soundings indicate a somewhat lower intensity, especially as it neared landfall. The author also describes several numerical model runs that were made to investigate the maximum possible intensity for the observed environmental conditions; these simulations also suggest a lower intensity than estimates from Dvorak analysis alone. Based on the evidence from the various measurements and modeling, the estimated range for the minimum sea level pressure at peak intensity is 900 to 920 hPa. The estimated range for the one-minute averaged maximum wind speed at peak intensity is 72 to 82 m/s. These maxima were likely reached about 24 hours prior to landfall, with some weakening occurring afterward.

  18. 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

  19. 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

  20. Flashback behavior in a model swirl combustor at elevated pressure

    Science.gov (United States)

    Ranjan, Rakesh; Ebi, Dominik; Clemens, Noel

    2014-11-01

    Understanding of combustion physics at high pressure is essential for safe and efficient operation of gas turbine combustors. A new optically-accessible elevated pressure combustion facility has been developed for this purpose. The modular design of the chamber allows applying various optical diagnostic techniques and the installation of different types of combustors. In the current study, the effect of pressure on boundary layer flashback in lean-premixed swirl flames is investigated. Mixtures of hydrogen and methane at different equivalence ratios are tested. High-speed chemiluminescence imaging is employed to study the upstream flame propagation inside the mixing tube, which allows comparison to previous results of flashback at atmospheric pressure.

  1. Hyperspectral Remote Sensing and Ecological Modeling Research and Education at Mid America Remote Sensing Center (MARC): Field and Laboratory Enhancement

    Science.gov (United States)

    Cetin, Haluk

    1999-01-01

    The purpose of this project was to establish a new hyperspectral remote sensing laboratory at the Mid-America Remote sensing Center (MARC), dedicated to in situ and laboratory measurements of environmental samples and to the manipulation, analysis, and storage of remotely sensed data for environmental monitoring and research in ecological modeling using hyperspectral remote sensing at MARC, one of three research facilities of the Center of Reservoir Research at Murray State University (MSU), a Kentucky Commonwealth Center of Excellence. The equipment purchased, a FieldSpec FR portable spectroradiometer and peripherals, and ENVI hyperspectral data processing software, allowed MARC to provide hands-on experience, education, and training for the students of the Department of Geosciences in quantitative remote sensing using hyperspectral data, Geographic Information System (GIS), digital image processing (DIP), computer, geological and geophysical mapping; to provide field support to the researchers and students collecting in situ and laboratory measurements of environmental data; to create a spectral library of the cover types and to establish a World Wide Web server to provide the spectral library to other academic, state and Federal institutions. Much of the research will soon be published in scientific journals. A World Wide Web page has been created at the web site of MARC. Results of this project are grouped in two categories, education and research accomplishments. The Principal Investigator (PI) modified remote sensing and DIP courses to introduce students to ii situ field spectra and laboratory remote sensing studies for environmental monitoring in the region by using the new equipment in the courses. The PI collected in situ measurements using the spectroradiometer for the ER-2 mission to Puerto Rico project for the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS). Currently MARC is mapping water quality in Kentucky Lake and

  2. Intercomparisons between passive and active microwave remote sensing, and hydrological modeling for soil moisture

    Science.gov (United States)

    Wood, E. F.; Lin, D.-S.; Mancini, M.; Thongs, D.; Troch, P. A.; Jackson, T. J.; Famiglietti, J. S.; Engman, E. T.

    1993-01-01

    Soil moisture estimations from a distributed hydrological model and two microwave sensors were compared with ground measurements collected during the MAC-HYDRO'90 experiment. The comparison was done with the purpose of evaluating the performance of the hydrological model and examining the limitations of remote sensing techniques used in soil moisture estimation. An image integration technique was used to integrate and analyze rainfall, soil properties, land cover, topography, and remote sensing imagery. Results indicate that the hydrological model and microwave sensors successfully picked up temporal variations of soil moisture and that the spatial soil moisture pattern may be remotely sensed with reasonable accuracy using existing algorithms.

  3. 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.

  4. 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.

  5. Modeling and Risk Mapping of Forest Fires using Remote Sensing and GIS (Case Study: Baghe-Shadi Protected Area, Yazd Province)

    OpenAIRE

    A. Najafi; M. H. Irannezhad; A. Sotoudeh; M. H. Mokhtari; B. Kiani

    2016-01-01

    Baghe-shadi in Yazd province is one the forests which is reported to be an area with high rate fire occurrence. The aim of this study was to model and map the fire risk area using geographic information system and remote sensing. In this study Analytical Hierarchy Process (AHP) with human related factors (distance from road, distance from settlements, and distance from vegetation), climatic related factors (air temperature and rainfall), and physiographic related factors (elevation, slope, as...

  6. 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.

  7. 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

  8. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    2007-01-01

    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  9. Model-based remote handling with the MAESTRO hydraulic manipulator

    International Nuclear Information System (INIS)

    Gravez, Philippe; Leroux, C.; Irving, M.; Galbiati, L.; Raneda, A.; Siuko, M.; Maisonnier, D.; Palmer, J.D.

    2003-01-01

    A powerful hydraulic manipulator may be a useful tool to deal efficiently with the remote handling, dexterous operations required during the Divertor maintenance. Its main advantages are a good weight capacity, the large range of tasks that can be addressed and its capability to recover from unforeseen situations. On the other hand, it implies intensive video monitoring and the use of hydraulics technology that is not currently suited to nuclear environments. This paper describes the developments and experiments performed in conjunction with CEA/LIST, IHA and ENEA in the frame of task T329-5 to enhance the benefits of computer-assisted hydraulic remote operation, while minimising its shortcomings

  10. Nonlinear plasticity model for structural alloys at elevated temperature. [LMFBR

    Energy Technology Data Exchange (ETDEWEB)

    Robinson, D N

    1978-11-01

    A nonlinear, time-independent plasticity model is presented which incorporates some aspects of both isotropic and kinematic hardening. The model characterizes a material with limited memory, i.e., in the sense that part of the deformation history as recorded in the internal dislocation structure is erased at stress reversals. This feature ensures that the predicted response eventually reaches a limit cycle under cyclic stressing, even in the presence of creep and relaxation. The model is intended as a candidate for replacing the nonlinear model now residing in Sect. 4.3.6 of RDT Standard F9-5T.

  11. 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...

  12. 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...

  13. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Portland WFO (WA)

    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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

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

    Data.gov (United States)

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

  2. 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...

  3. 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...

  4. 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...

  5. 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...

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

    Data.gov (United States)

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

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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....

  15. 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...

  16. 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...

  17. 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...

  18. 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....

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

    Data.gov (United States)

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

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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....

  5. 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....

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Medford 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. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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....

  1. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Seattle (WA) WFO - Grays Harbor County

    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...

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

    Data.gov (United States)

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

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. Antarctic 5-km Digital Elevation Model from ERS-1 Altimetry, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a Digital Elevation Model (DEM) for Antarctica to 81.5 degrees south latitude, at a resolution of 5 km. Approximately twenty million data...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  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. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

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

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador...

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

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects....

  13. 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. 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...

  15. 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....

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

    Data.gov (United States)

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

  17. 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...

  18. 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...

  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. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. Perryville and Ivanof Bay, Alaska 1/3 arc-second Coastal Digital Elevation Model

    Data.gov (United States)

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

  7. 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...

  8. 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...

  9. Adak, 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...

  10. 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....

  11. 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...

  12. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Corpus Christi Weather Forecast Office (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...

  13. 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...

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

    African Journals Online (AJOL)

    Abstract. 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.

  15. 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 ...

  16. An object-based storage model for distributed remote sensing images

    Science.gov (United States)

    Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

    2006-10-01

    It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

  17. 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...

  18. 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...

  19. 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..

  20. 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...

  1. 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.)

  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. 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

  4. 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.

  5. 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.

  6. Remote ischemic conditioning in ST-elevation myocardial infarction as adjuvant to primary angioplasty (RIC-STEMI): study protocol for a randomized controlled trial.

    Science.gov (United States)

    Gaspar, António; Pereira, Miguel Álvares; Azevedo, Pedro; Lourenço, André; Marques, Jorge; Leite-Moreira, Adelino

    2015-09-08

    ST-elevation myocardial infarction (STEMI) accounts for nearly one third of acute coronary syndromes. Despite improved STEMI patient care, mortality remains high, contributing significantly to the ischemic heart disease burden. This may partly be related to ischemia-reperfusion injury (IRI). Remote ischemic conditioning (RIC), through short cycles of ischemia-reperfusion applied to a limb, has been shown to reduce IRI in various clinical settings. Our primary hypothesis is that RIC will reduce adverse events related to STEMI when applied as adjunctive therapy to primary percutaneous coronary intervention (PCI). "Remote ischemic conditioning in ST-elevation myocardial infarction as adjuvant to primary angioplasty" (RIC-STEMI) is an ongoing prospective, single-center, open-label, randomized controlled trial to assess whether RIC as an adjunctive therapy during primary PCI in patients presenting with STEMI can improve clinical outcomes. After enrollment, participants are randomized according to a computer-generated randomization schedule, in a ratio of 1:1 to RIC or no intervention, in blocks of four individuals. RIC is begun at least 10 min before the estimated time of the first balloon inflation and its duration is 30 min. Ischemia is induced by three cycles of inflation of a blood pressure cuff placed on the left lower limb to 200 mmHg and then deflation to 0 mmHg for another 5 min. Primary endpoint is a combined endpoint of death from cardiac cause or hospitalization for heart failure (HF) on follow-up (including device implantation: implantable cardioverter defibrillator, cardiac resynchronization and left ventricular assist device). Secondary endpoints are myocardial infarction (MI) size (estimated by the 48 h area under the curve of serum troponin I levels), development of Q-wave MI, left ventricular function (assessed by echocardiography within the first 3 days after admission), contrast-induced nephropathy, in-hospital mortality, all-cause mortality and

  7. Determining the optimum cell size of digital elevation model for ...

    Indian Academy of Sciences (India)

    obtained DEMs were explored for their intrinsic quality using four different methods, i.e., sink analy- sis, fractal dimension of derived stream network, entropy measurement and ... ters decrease, and many delicate landscape fea- tures are lost. However, as one can understand, it is not enough to model the cell size effects.

  8. Determining the optimum cell size of digital elevation model for ...

    Indian Academy of Sciences (India)

    obtained DEMs were explored for their intrinsic quality using four different methods, i.e., sink analy- sis, fractal dimension of derived stream network, entropy measurement and semivariogram modelling. These methods were applied to determine the level artifacts (interpolation error) in DEM surface as well as derived stream ...

  9. The Application of Spaceborne Remote Sensing Datasets for Species Distribution Modeling in South America

    Science.gov (United States)

    McDonald, K. C.; Carnaval, A.; Waltari, E.; Schroeder, R.

    2012-12-01

    For the last 40 years, the fields of evolutionary biogeography and conservation biology witnessed substantial improvement and usage of correlative species distribution in studies of biodiversity patterns and their underlying processes Thanks to a suite of new algorithms and the integration of maximum entropy concepts into the biological sciences, field scientists are now able to better predict species ranges from environmental surrogates. To date, biologists have been relying on a single major set of global environmental grids for the purpose of both delimiting species environmental envelopes and projecting envelopes through space and time. The data set, also known as the WorldClim database, relies on measurements of elevation, precipitation, mean, maximum and minimum temperature collected from weather-stations across the world. These data were used to derive worldwide grids, at 1 km resolution, through interpolation of average monthly climate data from stations. Nineteen bioclimatic grids have been derived from the air temperature and precipitation values and have been used extensively in predictive studies. Although these WorldClim grids have been successfully applied to a suite of ecological and evolutionary research questions, their performance can be suboptimal especially in topographically complex areas where interpolation methods fail to capture true variation in local climate, in biological systems impacted by environmental phenomena occurring at finer temporal or spatial scales, and in regions with few weather stations. The objective of this work is to assess the utility of remote sensing data sets for providing environmental fields to derive novel bioclimatic grids relative to the WorldClim dataset, and test the associated improvement to species distribution models in a topographically complex tropical area. We generate a novel set of bioclimatic grids for biodiversity analysis from such sources as MODIS, AMSR-E, TRMM and MERRA. Using these grids, we

  10. Dynamic modeling and experiments on the coupled vibrations of building and elevator ropes

    Science.gov (United States)

    Yang, Dong-Ho; Kim, Ki-Young; Kwak, Moon K.; Lee, Seungjun

    2017-03-01

    This study is concerned with the theoretical modelling and experimental verification of the coupled vibrations of building and elevator ropes. The elevator ropes consist of a main rope which supports the cage and the compensation rope which is connected to the compensation sheave. The elevator rope is a flexible wire with a low damping, so it is prone to vibrations. In the case of a high-rise building, the rope length also increases significantly, so that the fundamental frequency of the elevator rope approaches the fundamental frequency of the building thus increasing the possibility of resonance. In this study, the dynamic model for the analysis of coupled vibrations of building and elevator ropes was derived by using Hamilton's principle, where the cage motion was also considered. An experimental testbed was built to validate the proposed dynamic model. It was found that the experimental results are in good agreement with the theoretical predictions thus validating the proposed dynamic model. The proposed model was then used to predict the vibrations of real building and elevator ropes.

  11. Measurements and modeling of VLLE at elevated pressures

    DEFF Research Database (Denmark)

    Laursen, Torben

    and pure component calibration. Samples from the different liquid phases in the high-pressure cell is taken using a moveable needle. The systems investigated have been a combination of the components: CO2, N2, di-methyl ether (DME), water, methanol, ethanol and 1-propanol. 41 isotherms have been measured...... has traditionally been considered very time consuming. This work aims at developing and operating an equipment which allows routine measurements of both VLE and VLLE, in the temperature range of 25-45°C and pressure range of 1-100 bar. This has been done by taking advantage of on-line sampling...... and of these 18 were VLLE systems and 32 have not previously been published. Some of the experimental results have been modelled using an equation of state, SRK combined with the MHV1 mixing rule for the a-parameter and the NRTL model for the Gibbs excess energy. The Mathias-Copeman model was used...

  12. Regions-of-interest extraction from remote sensing imageries using visual attention modelling

    Science.gov (United States)

    Tan, Hui Li; Fan, Jiayuan; Toomik, Maria; Lu, Shijian

    2016-10-01

    Processing and analysing large volume of remote sensing data is both labour intensive and time consuming. Therefore, there is a need to effectively and efficiently identify meaningful regions in these remote sensing data for timely resource management. In this paper, we propose a visual attention model for identifying regions-of-interest in remote sensing data. The proposed model incorporates both bottom-up spatial saliency and top-down objectness, by fusing a co-occurrence histogram saliency model with the BING objectness model. The co-occurrence histogram saliency model is constructed by first building a 2D co-occurrence histogram that captures co-occurrence and occurrence of image intensities, and then using the 2D co-occurrence histogram to model local and global saliency. On the other hand, the BING objectness model is constructed by resizing image intensities in variable-sized windows to 8x8 windows, and then using the norms of the gradients in the 8x8 windows as features to train a generic objectness measure. Our experimental results show that the proposed model can effectively and efficiently identify regions-of-interest in remote sensing data. The proposed model may be applied in various remote sensing applications such as anomaly detection, urban area detection, target detection, or land use classification.

  13. 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...

  14. 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 gene...

  15. 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

  16. 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.

  17. 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

    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...

  18. 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......Evaporation of water from soil and its transpiration by vegetation together form a ux between the land and the atmosphere called evapotranspiration (ET). ET is a key factor in many natural and anthropogenic processes. It forms the basis of the hydrological cycle and has a strong inuence on local...

  19. Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

    Science.gov (United States)

    Kenward, T.; Lettenmaier, D. P.

    1997-01-01

    The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

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

    DEFF Research Database (Denmark)

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

    Are low-relief high-elevation surfaces generally a result of uplift of flat surfaces formed close to sea-level or can they be formed "in situ" by climate dependent surface processes such as those associated with glaciation? This question is important to resolve in order to understand the geological...... 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...... periglacial erosion, sediment transport, and the evolving topography. We show that smooth peaks, convex hillslopes, and a few meters thick regolith cover at high elevation are emergent properties of the landscape evolution model. By varying climate and other model parameters, we discuss how the landscape...

  1. Calculation and Error Analysis of a Digital Elevation Model of Hofsjokull, Iceland from SAR Interferometry

    Science.gov (United States)

    Barton, Jonathan S.; Hall, Dorothy K.; Sigurosson, Oddur; Williams, Richard S., Jr.; Smith, Laurence C.; Garvin, James B.

    1999-01-01

    Two ascending European Space Agency (ESA) Earth Resources Satellites (ERS)-1/-2 tandem-mode, synthetic aperture radar (SAR) pairs are used to calculate the surface elevation of Hofsjokull, an ice cap in central Iceland. The motion component of the interferometric phase is calculated using the 30 arc-second resolution USGS GTOPO30 global digital elevation product and one of the ERS tandem pairs. The topography is then derived by subtracting the motion component from the other tandem pair. In order to assess the accuracy of the resultant digital elevation model (DEM), a geodetic airborne laser-altimetry swath is compared with the elevations derived from the interferometry. The DEM is also compared with elevations derived from a digitized topographic map of the ice cap from the University of Iceland Science Institute. Results show that low temporal correlation is a significant problem for the application of interferometry to small, low-elevation ice caps, even over a one-day repeat interval, and especially at the higher elevations. Results also show that an uncompensated error in the phase, ramping from northwest to southeast, present after tying the DEM to ground-control points, has resulted in a systematic error across the DEM.

  2. High Resolution Lidar Digital Elevation Models and Low Resolution Shaded Relief Maps of Antarctica from USGS, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — Lidar high-resolution elevation digital elevation model data and low-resolution shaded relief maps of Antarctica are available for download from the U.S. Antarctic...

  3. AirSWOT observations versus hydrodynamic model outputs of water surface elevation and slope in a multichannel river

    Science.gov (United States)

    Altenau, Elizabeth H.; Pavelsky, Tamlin M.; Moller, Delwyn; Lion, Christine; Pitcher, Lincoln H.; Allen, George H.; Bates, Paul D.; Calmant, Stéphane; Durand, Michael; Neal, Jeffrey C.; Smith, Laurence C.

    2017-04-01

    Anabranching rivers make up a large proportion of the world's major rivers, but quantifying their flow dynamics is challenging due to their complex morphologies. Traditional in situ measurements of water levels collected at gauge stations cannot capture out of bank flows and are limited to defined cross sections, which presents an incomplete picture of water fluctuations in multichannel systems. Similarly, current remotely sensed measurements of water surface elevations (WSEs) and slopes are constrained by resolutions and accuracies that limit the visibility of surface waters at global scales. Here, we present new measurements of river WSE and slope along the Tanana River, AK, acquired from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission. Additionally, we compare the AirSWOT observations to hydrodynamic model outputs of WSE and slope simulated across the same study area. Results indicate AirSWOT errors are significantly lower than model outputs. When compared to field measurements, RMSE for AirSWOT measurements of WSEs is 9.0 cm when averaged over 1 km squared areas and 1.0 cm/km for slopes along 10 km reaches. Also, AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics, while model outputs of spatial variations in slope are very poor. Combining AirSWOT and future SWOT measurements with hydrodynamic models can result in major improvements in model simulations at local to global scales. Scientists can use AirSWOT measurements to constrain model parameters over long reach distances, improve understanding of the physical processes controlling the spatial distribution of model parameters, and validate models' abilities to reproduce spatial variations in slope. Additionally, AirSWOT and SWOT measurements can be assimilated into lower-complexity models to try and approach the accuracies achieved by higher-complexity models.

  4. 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.

  5. A Model for Predicting Persistent Elevation of Factor VIII among Patients with Acute Ischemic Stroke

    Science.gov (United States)

    Samai, Alyana A.; Boehme, Amelia K.; Shaban, Amir; George, Alexander J.; Dowell, Lauren; Monlezun, Dominique J.; Leissinger, Cindy; Schluter, Laurie; El Khoury, Ramy; Martin-Schild, Sheryl

    2016-01-01

    Background and Purpose Elevated levels of coagulation factor VIII (FVIII) may persist independent of the acute-phase response; however, this relationship has not been investigated relative to acute ischemic stroke (AIS). We examined the frequency and predictors of persistently elevated FVIII in AIS patients. Methods AIS patients admitted between July 2008 and May 2014 with elevated baseline FVIII levels and repeat FVIII levels drawn for more than 7 days postdischarge were included. The patients were dichotomized by repeat FVIII level for univariate analysis at 150% and 200% activity thresholds. An adjusted model was developed to predict the likelihood of persistently elevated FVIII levels. Results Among 1616 AIS cases, 98 patients with elevated baseline FVIII had repeat FVIII levels. Persistent FVIII elevation was found in more than 75% of patients. At the 150% threshold, the prediction score ranged from 0 to 7 and included black race, female sex, prior stroke, hyperlipidemia, smoking, baseline FVIII > 200%, and baseline von Willebrand factor (vWF) level greater than 200%. At the 200% threshold, the prediction score ranged from 0–5 and included female sex, prior stroke, diabetes mellitus, baseline FVIII level greater 200%, and baseline vWF level greater than 200%. For each 1-point increase in score, the odds of persistent FVIII at both the 150% threshold (odds ratio [OR] = 10.4, 95% confidence interval [CI] 1.63–66.9, P = .0134) and 200% threshold (OR = 10.2, 95% CI 1.82–57.5, P = .0083) increased 10 times. Conclusion Because an elevated FVIII level confers increased stroke risk, our model for anticipating a persistently elevated FVIII level may identify patients at high risk for recurrent stroke. FVIII may be a target for secondary stroke prevention. PMID:26777556

  6. 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.

  7. 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.

  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. 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

  10. Towards Remotely Sensed Composite Global Drought Risk Modelling

    Science.gov (United States)

    Dercas, Nicholas; Dalezios, Nicolas

    2015-04-01

    Drought is a multi-faceted issue and requires a multi-faceted assessment. Droughts may have the origin on precipitation deficits, which sequentially and by considering different time and space scales may impact soil moisture, plant wilting, stream flow, wildfire, ground water levels, famine and social impacts. There is a need to monitor drought even at a global scale. Key variables for monitoring drought include climate data, soil moisture, stream flow, ground water, reservoir and lake levels, snow pack, short-medium-long range forecasts, vegetation health and fire danger. However, there is no single definition of drought and there are different drought indicators and indices even for each drought type. There are already four operational global drought risk monitoring systems, namely the U.S. Drought Monitor, the European Drought Observatory (EDO), the African and the Australian systems, respectively. These systems require further research to improve the level of accuracy, the time and space scales, to consider all types of drought and to achieve operational efficiency, eventually. This paper attempts to contribute to the above mentioned objectives. Based on a similar general methodology, the multi-indicator approach is considered. This has resulted from previous research in the Mediterranean region, an agriculturally vulnerable region, using several drought indices separately, namely RDI and VHI. The proposed scheme attempts to consider different space scaling based on agroclimatic zoning through remotely sensed techniques and several indices. Needless to say, the agroclimatic potential of agricultural areas has to be assessed in order to achieve sustainable and efficient use of natural resources in combination with production maximization. Similarly, the time scale is also considered by addressing drought-related impacts affected by precipitation deficits on time scales ranging from a few days to a few months, such as non-irrigated agriculture, topsoil moisture

  11. High-resolution digital elevation model and historical topographic maps of the Tisza River floodplain, the Great Hungarian Plain

    Science.gov (United States)

    Timár, G.; Mészáros, J.

    2009-04-01

    The Great Hungarian Plain (GHP), the central part of the Pannonian Basin, is one of the world’s most developed flatlands. The relief differences remain under 20 meters in the central area of the plain, especially in the wide floodplain of the Tisza River. After the flood control measurements of the river (1846-1930), newly built dykes cut the wider floodplain from the actual narrow floodway. Common knowledge of the historical inundation patterns has been almost lost. To obtain pieces of information about the possible flood extents, usage of high-resolution elevation models is a valuable option, as well as application of rectified historical topographic maps. The best available elevation model of the GHP is based on the vectorized 1:10,000 scale topographic maps of the Institute of Geodesy, Cartography and Remote Sensing of Hungary (FÃ-MI). The base contour interval is 1 meter but according to the very flat characteristics of the area, halving contours are commonly used. This contour density is definitely needed to get better elevaition models than the one of the SRTM, which shows only the general features of the flatland with remarkable errors at the forests. Historical topographic datasets, such as the ones compiled directly for the water control measures (triangulation: 1833-34; mapping until 1842 by Sámuel Lányi), as well as the First (1783-86) and Second (1857-61) Military Surveys can be rectified easiliy after understanding their geodetic basis. They show in surprising precisity the fine vertical structure of the river terraces and the historical inundation levels. These cartographic elements are of great value also for the necessary re-assessment of the flood control system.

  12. Unusual surface morphology from digital elevation models of the Greenland ice sheet

    DEFF Research Database (Denmark)

    Ekholm, Simon; Keller, K.; Bamber, J.L.

    1998-01-01

    In this study of the North Greenland ice sheet, we have used digital elevation models to investigate the topographic signatures of a large ice flow feature discovered in 1993 and a unique surface anomaly which we believe has not been observed previously. The small scale topography of the flow...... feature is revealed in striking detail in a high-pass filtered elevation model. Furthermore, ice penetrating radar show that the sub-stream bed is rough with undulation amplitude increasing downstream. The new feature consists of two large depressions in the ice sheet connected by a long curving trench...

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

    Directory of Open Access Journals (Sweden)

    Yvonne Walz

    2015-11-01

    Full Text Available 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

  14. 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

  15. 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...

  16. 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...... and spatial variation of LAI. The modelling results are compared with results based on conventional input of precipitation and vegetation characteristics. The introduction of remotely sensed LAI shows improvements in the simulated hydrographs, a marked change in the relative proportions of actual...... evapotranspiration comprising canopy evaporation, soil evaporation and transpiration. while no clear trend in the spatial pattern could be found, The remotely sensed precipitation resulted in similar model performances with respect to the simulated hydrographs as with the conventional raingauge input. A simple...

  17. Mathematic modeling of the Earth's surface and the process of remote sensing

    Science.gov (United States)

    Balter, B. M.

    1979-01-01

    It is shown that real data from remote sensing of the Earth from outer space are not best suited to the search for optimal procedures with which to process such data. To work out the procedures, it was proposed that data synthesized with the help of mathematical modeling be used. A criterion for simularity to reality was formulated. The basic principles for constructing methods for modeling the data from remote sensing are recommended. A concrete method is formulated for modeling a complete cycle of radiation transformations in remote sensing. A computer program is described which realizes the proposed method. Some results from calculations are presented which show that the method satisfies the requirements imposed on it.

  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. 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.

  20. Test of the depression distress amplification model in young adults with elevated risk of current suicidality.

    Science.gov (United States)

    Capron, Daniel W; Lamis, Dorian A; Schmidt, Norman B

    2014-11-30

    Suicide is a leading cause of death among young adults and the rate of suicide has been increasing for decades. A depression distress amplification model posits that young adults with comorbid depression and anxiety have elevated suicide rates due to the intensification of their depressive symptoms by anxiety sensitivity cognitive concerns. The current study tested the effects of anxiety sensitivity subfactors as well as the depression distress amplification model in a very large sample of college students with elevated suicide risk. Participants were 721 college students who were at elevated risk of suicidality (scored>0 on the Beck Scale for Suicide Ideation). Consistent with prior work, anxiety sensitivity cognitive concerns, but not physical or social concerns, were associated with suicidal ideation. Consistent with the depression distress amplification model, in individuals high in depression, anxiety sensitivity cognitive concerns predicted elevated suicidal ideation but not among those with low depression. The results of this study corroborate the role of anxiety sensitivity cognitive concerns and the depression distress amplification model in suicidal ideation among a large potentially high-risk group of college students. The depression distress amplification model suggests a specific mechanism, anxiety sensitivity cognitive concerns, that may be responsible for increased suicide rates among those with comorbid anxiety and depression. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. A theoretical model of cytosolic calcium elevation following wounding in urothelial cell monolayers

    International Nuclear Information System (INIS)

    Appleby, Peter A; Walker, Dawn; Shabir, Saqib; Southgate, Jennifer

    2013-01-01

    Scratch wounding of a urothelial cell monolayer triggers a number of events including the release of soluble, diffusible signalling factors and mechanical stimulation of cells at the wound edge. These events cause a sustained elevation in cytosolic calcium concentration in the cells surrounding the wound and a transient rise in those further away. The precise form of this calcium transient is believed to play a central role in determining the subsequent response of individual cells and ultimately leads to a co-ordinated, population-level response that rapidly closes the wound. Here we present a framework for modelling the initial phases of this process. We combine a PDE model of diffusion in the extracellular medium and an ODE model of calcium signalling that has been tailored to represent urothelial cells. The ODE model is capable of generating a wide range of calcium transients, including spikes, bursts, oscillations and sustained elevations in the cytosolic calcium concentration. In multi-cell simulations of scratch wounding in a perfusion flow we find that the spatial position of the cells relative to the wound site leads to distinct classes of calcium response, with cells proximal to the wound exhibiting a sustained elevation and cells distal to the wound exhibiting a more transient elevation. We compare these results to existing experimental data and generate a number of novel predictions that could be used to test the model experimentally.

  2. 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.

  3. REMOTE SENSING TECHNOLOGIES AND GEOSPATIAL MODELLING HIERARCHY FOR SMART CITY SUPPORT

    Directory of Open Access Journals (Sweden)

    M. Popov

    2017-12-01

    Full Text Available 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.

  4. 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

  5. Hydrological and sedimentological modeling of the Okavango Delta, Botswana, using remotely sensed input and calibration data

    Science.gov (United States)

    Milzow, C.; Kgotlhang, L.; Kinzelbach, W.; Bauer-Gottwein, P.

    2006-12-01

    The Okavango Delta is a vast wetland situated in the mostly arid southern Africa. It is protected by the Ramsar convention but economic growth of the tributary countries (Angola, Namibia and Botswana) will make the waters of its feeding river, the Okavango, more and more attractive for agricultural water abstraction and production of electrical energy. An integrated hydrological model of the delta is build to study consequences of water abstraction and sediment retention in the river. The model is based on Modflow 2000 but several changes are made to the code. Flows in the delta are of three types: Groundwater flow, slow overland flow and fast flow through channels. These three components are reflected in the model by a standard aquifer layer, a wettable surface layer which also obeys the Darcy law, and stream flow routing using the SFR2 package. The stream-flow routing component of the model simulates realistic flow velocities which allow to incorporate sediment transport in the model. For this purpose a basic sediment transport package for Modflow 2000 has been written. We assume that the position of the channels stays approximately constant over few decades but that channel elevations may change due to aggradation and erosion. Changing slopes induce changes in the distribution of the water to the different arms and flood plains of the deltaic system. Flooding patterns of the delta differ each year. They are a function of inflow, meteorological data and to some extend of the wetting state in previous years in the short term (1-3 years). Vegetation growth, peat fires and sediment deposition lead to variations in the medium term (10 to 50 years). Topography changes with major changes of channel network geometry will only occur in the long term (100 to 1000 years). Tectonic events may, however, lead to sudden discontinuities in the flooding behavior. When analyzing management options and the sustainable use of the Delta's resources the interesting time scale is the

  6. Equivalent sensor radiance generation and remote sensing from model parameters - Part 1: Equivalent sensor radiance formulation

    Science.gov (United States)

    Wind, G.; da Silva, A. M.; Norris, P. M.; Platnick, S.

    2013-07-01

    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 probability density function of total water (vapor and cloud condensate). The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

  7. 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 for ...

  8. 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...

  9. 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...

  10. 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...

  11. A seamless, high-resolution digital elevation model (DEM) of the north-central California coast

    Science.gov (United States)

    Foxgrover, Amy C.; Barnard, Patrick L.

    2012-01-01

    A seamless, 2-meter resolution digital elevation model (DEM) of the north-central California coast has been created from the most recent high-resolution bathymetric and topographic datasets available. The DEM extends approximately 150 kilometers along the California coastline, from Half Moon Bay north to Bodega Head. Coverage extends inland to an elevation of +20 meters and offshore to at least the 3 nautical mile limit of state waters. This report describes the procedures of DEM construction, details the input data sources, and provides the DEM for download in both ESRI Arc ASCII and GeoTIFF file formats with accompanying metadata.

  12. 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...

  13. ICESat Lidar and Global Digital Elevation Models: Application to DESDynI

    Science.gov (United States)

    Carabajal, Claudia C.; Harding, David J.; Suchdeo, Vijay P.

    2010-01-01

    Geodetic control is extremely important in the production and quality control of topographic data sets, enabling elevation results to be referenced to an absolute vertical datum. Global topographic data with improved geodetic accuracy achieved using global Ground Control Point (GCP) databases enable more accurate characterization of land topography and its change related to solid Earth processes, natural hazards and climate change. The multiple-beam lidar instrument that will be part of the NASA Deformation, Ecosystem Structure and Dynamics of Ice (DESDynI) mission will provide a comprehensive, global data set that can be used for geodetic control purposes. Here we illustrate that potential using data acquired by NASA's Ice, Cloud and land Elevation Satellite (ICEsat) that has acquired single-beam, globally distributed laser altimeter profiles (+/-86deg) since February of 2003 [1, 2]. The profiles provide a consistently referenced elevation data set with unprecedented accuracy and quantified measurement errors that can be used to generate GCPs with sub-decimeter vertical accuracy and better than 10 m horizontal accuracy. Like the planned capability for DESDynI, ICESat records a waveform that is the elevation distribution of energy reflected within the laser footprint from vegetation, where present, and the ground where illuminated through gaps in any vegetation cover [3]. The waveform enables assessment of Digital Elevation Models (DEMs) with respect to the highest, centroid, and lowest elevations observed by ICESat and in some cases with respect to the ground identified beneath vegetation cover. Using the ICESat altimetry data we are developing a comprehensive database of consistent, global, geodetic ground control that will enhance the quality of a variety of regional to global DEMs. Here we illustrate the accuracy assessment of the Shuttle Radar Topography Mission (SRTM) DEM produced for Australia, documenting spatially varying elevation biases of several meters

  14. 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...

  15. 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.

  16. Hydrological now- and forecasting : Integration of operationally available remotely sensed and forecasted hydrometeorological variables into distributed hydrological models

    NARCIS (Netherlands)

    Schuurmans, J.M.

    2008-01-01

    Keywords: hydrology, models, soil moisture, rainfall, radar, rain gauge, remote sensing, evapotranspiration, forecasting, numerical weather prediction, Netherlands, Langbroekerwetering, Lopikerwaard. Computer simulation models are an important tool for hydrologists. With these models they can

  17. 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...

  18. 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

  19. 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.

  20. Combining inventories of land cover and forest resources with prediction models and remotely sensed data

    Science.gov (United States)

    Raymond L. Czaplewski

    1989-01-01

    It is difficult to design systems for national and global resource inventory and analysis that efficiently satisfy changing, and increasingly complex objectives. It is proposed that individual inventory, monitoring, modeling, and remote sensing systems be specialized to achieve portions of the objectives. These separate systems can be statistically linked to accomplish...

  1. 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.

  2. Remote sensing data assimilation for a prognostic phenology model

    Science.gov (United States)

    R. Stockli; T. Rutishauser; D. Dragoni; J. O' Keefe; P. E. Thornton; M. Jolly; L. Lu; A. S. Denning

    2008-01-01

    Predicting the global carbon and water cycle requires a realistic representation of vegetation phenology in climate models. However most prognostic phenology models are not yet suited for global applications, and diagnostic satellite data can be uncertain and lack predictive power. We present a framework for data assimilation of Fraction of Photosynthetically Active...

  3. Saddle Position-Based Method for Extraction of Depressions in Fengcong Areas by Using Digital Elevation Models

    Directory of Open Access Journals (Sweden)

    Xianwu Yang

    2018-04-01

    Full Text Available A karst depression is an important sign of the development stage of karst landforms. The morphological characteristics of depressions can help reflect the development and evolution process of such landforms. The accurate identification and extraction of depressions in Fengcong areas are the basis of this research on karst depressions. Previous studies on Fengcong depressions were primarily based on manual surveys, remote sensing image interpretation, and manual map plotting or GIS-based techniques. The extracted landform units of Fengcong depressions in these studies were not accurate and even inauthentic in certain cases. Thus, this work proposes a method for extracting Fengcong depressions in karst areas which is based on terrain saddle points and uses digital elevation models (DEMs. First, the surface morphology of the Fengcong karst area is analyzed. Second, saddles are detected from the intersection points, and spatial trend surfaces are generated by interpolating the elevations of these saddle points. The interface between pinnacles and depressions can be determined by the trend surface. We applied the method in a case Fengcong area of the Lijiang River in Guilin, China. Results showed that the proposed method successfully divided the positive terrain form of pinnacles and the negative terrain form of the depressions in the Fengcong karst area. A total of 188 surface depressions were extracted, whose average area was 0.14 km2 and polygonal depression density was 2.5 km2. Results also showed that most of the depressions were stable in terms of the morphological features of area and depth. A total of 94% of the depth measured less than 60 m, and the area was less than 0.5 km2. This proposed method can accurately determine the boundary of depressions and provide an important reference for quantitative research on the Fengcong depression terrain in karst landforms.

  4. 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

    reservoir level variation. Because of its easy accessibility and immediate availability, radar altimetry lends itself to being used in real-time hydrological applications. As an impartial source of information about the hydrological system that can be updated in real time, the modeling approach described......Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS) data have been recognized as an alternative to in-situ hydrometeorological data in remote...... and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models. In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modeling...

  5. Spatial aggregation of land surface characteristics : impact of resolution of remote sensing data on land surface modelling

    NARCIS (Netherlands)

    Pelgrum, H.

    2000-01-01

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo,

  6. Spatial Irrigation Management Using Remote Sensing Water Balance Modeling and Soil Water Content Monitoring

    Science.gov (United States)

    Barker, J. Burdette

    Spatially informed irrigation management may improve the optimal use of water resources. Sub-field scale water balance modeling and measurement were studied in the context of irrigation management. A spatial remote-sensing-based evapotranspiration and soil water balance model was modified and validated for use in real-time irrigation management. The modeled ET compared well with eddy covariance data from eastern Nebraska. Placement and quantity of sub-field scale soil water content measurement locations was also studied. Variance reduction factor and temporal stability were used to analyze soil water content data from an eastern Nebraska field. No consistent predictor of soil water temporal stability patterns was identified. At least three monitoring locations were needed per irrigation management zone to adequately quantify the mean soil water content. The remote-sensing-based water balance model was used to manage irrigation in a field experiment. The research included an eastern Nebraska field in 2015 and 2016 and a western Nebraska field in 2016 for a total of 210 plot-years. The response of maize and soybean to irrigation using variations of the model were compared with responses from treatments using soil water content measurement and a rainfed treatment. The remote-sensing-based treatment prescribed more irrigation than the other treatments in all cases. Excessive modeled soil evaporation and insufficient drainage times were suspected causes of the model drift. Modifying evaporation and drainage reduced modeled soil water depletion error. None of the included response variables were significantly different between treatments in western Nebraska. In eastern Nebraska, treatment differences for maize and soybean included evapotranspiration and a combined variable including evapotranspiration and deep percolation. Both variables were greatest for the remote-sensing model when differences were found to be statistically significant. Differences in maize yield in

  7. Modeling of an implantable device for remote arterial pressure measurement

    Science.gov (United States)

    Miguel, J. A.; Lechuga, Y.; Mozuelos, R.; Martinez, M.

    2013-05-01

    Cardiovascular diseases are the leading causes of illness and death in Europe, having a major impact on healthcare costs. An intelligent stent (e-stent), capable of obtaining and transmitting measurements of physiological parameters, can be a useful tool for real-time monitorization of arterial blockage without patient hospitalization. In this paper, a behavioral model of a pressure sensing-based e-stent is proposed and simulated under several restenosis conditions. Special attention has been given to the need of an accurate fault model, obtained from realistic finite-element simulations, to ensure long-term reliability; particularly for those faults whose behavior cannot be described by usual analytical models.

  8. 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

  9. 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.

  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. Remotely sensed soil moisture input to a hydrologic model

    Science.gov (United States)

    Engman, E. T.; Kustas, W. P.; Wang, J. R.

    1989-01-01

    The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

  12. Spatiotemporal Variability of Lake Water Quality in the Context of Remote Sensing Models

    Directory of Open Access Journals (Sweden)

    Carly Hyatt Hansen

    2017-04-01

    Full Text Available This study demonstrates a number of methods for using field sampling and observed lake characteristics and patterns to improve techniques for development of algae remote sensing models and applications. As satellite and airborne sensors improve and their data are more readily available, applications of models to estimate water quality via remote sensing are becoming more practical for local water quality monitoring, particularly of surface algal conditions. Despite the increasing number of applications, there are significant concerns associated with remote sensing model development and application, several of which are addressed in this study. These concerns include: (1 selecting sensors which are suitable for the spatial and temporal variability in the water body; (2 determining appropriate uses of near-coincident data in empirical model calibration; and (3 recognizing potential limitations of remote sensing measurements which are biased toward surface and near-surface conditions. We address these issues in three lakes in the Great Salt Lake surface water system (namely the Great Salt Lake, Farmington Bay, and Utah Lake through sampling at scales that are representative of commonly used sensors, repeated sampling, and sampling at both near-surface depths and throughout the water column. The variability across distances representative of the spatial resolutions of Landsat, SENTINEL-2 and MODIS sensors suggests that these sensors are appropriate for this lake system. We also use observed temporal variability in the system to evaluate sensors. These relationships proved to be complex, and observed temporal variability indicates the revisit time of Landsat may be problematic for detecting short events in some lakes, while it may be sufficient for other areas of the system with lower short-term variability. Temporal variability patterns in these lakes are also used to assess near-coincident data in empirical model development. Finally, relationships

  13. 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...

  14. Optimal plant nitrogen use improves model representation of vegetation response to elevated CO2

    Science.gov (United States)

    Caldararu, Silvia; Kern, Melanie; Engel, Jan; Zaehle, Sönke

    2017-04-01

    Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as

  15. Limb remote ischaemic postconditioning-induced elevation of fibulin-5 confers neuroprotection to rats with cerebral ischaemia/reperfusion injury: Activation of the AKT pathway.

    Science.gov (United States)

    Zhang, Wei; Wang, Ye; Bi, Guorong

    2017-06-01

    Limb remote ischaemic postconditioning (RIPostC) is an effective and well-acknowledged treatment for brain ischaemia injury. The present study aimed to evaluate the role of fibulin-5 in the neuroprotection of RIPostC against cerebral ischaemia/reperfusion (I/R) injury in rats. The middle cerebral artery occlusion (MCAO) model was established in rats and then RIPostC was carried out by three cycles of 10 minutes occlusion/10 minutes release of the bilateral femoral artery at the beginning of the reperfusion. To downregulate the fibulin-5 level, fibulin-5 siRNA was injected into the lateral ventricle 24 hours before MCAO. According to our present study, RIPostC attenuated cerebral I/R injury by decreasing infarct volume, improving neurobehavioral score and suppressing blood brain barrier (BBB) leakage. Moreover, the mRNA and protein levels of fibulin-5 were upregulated by RIPostC at 24 hours and 72 hours after reperfusion. Downregulation of fibulin-5 attenuated the neuroprotection of RIPostC. Finally, the result showed that fibulin-5 was upregulated by RIPostC via activation of the PI3K/AKT pathway. Taken together, these results provide evidence that upregulation of fibulin-5 is involved in the beneficial effect of RIPostC against cerebral I/R injury. © 2017 John Wiley & Sons Australia, Ltd.

  16. 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.

  17. A Seamless, High-Resolution, Coastal Digital Elevation Model (DEM) for Southern California

    Science.gov (United States)

    Barnard, Patrick L.; Hoover, Daniel

    2010-01-01

    A seamless, 3-meter digital elevation model (DEM) was constructed for the entire Southern California coastal zone, extending 473 km from Point Conception to the Mexican border. The goal was to integrate the most recent, high-resolution datasets available (for example, Light Detection and Ranging (Lidar) topography, multibeam and single beam sonar bathymetry, and Interferometric Synthetic Aperture Radar (IfSAR) topography) into a continuous surface from at least the 20-m isobath to the 20-m elevation contour. This dataset was produced to provide critical boundary conditions (bathymetry and topography) for a modeling effort designed to predict the impacts of severe winter storms on the Southern California coast (Barnard and others, 2009). The hazards model, run in real-time or with prescribed scenarios, incorporates atmospheric information (wind and pressure fields) with a suite of state-of-the-art physical process models (tide, surge, and wave) to enable detailed prediction of water levels, run-up, wave heights, and currents. Research-grade predictions of coastal flooding, inundation, erosion, and cliff failure are also included. The DEM was constructed to define the general shape of nearshore, beach and cliff surfaces as accurately as possible, with less emphasis on the detailed variations in elevation inland of the coast and on bathymetry inside harbors. As a result this DEM should not be used for navigation purposes.

  18. 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...

  19. 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.

  20. 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.

  1. Stohastic Model for Loads on Offshore Structures from Wave, Wind, Current and Water Elevation

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Sterndorff, M.J.

    2002-01-01

    For code-based LRFD and for reliability-based assessment of offshore structures such as steel platforms it is essential that consistent stochastic models for the main metocean parameters are available. The most important metocean parameters are the significant wave height, maximum individual wave...... height, maximum crest height, wind speed, current speed and water elevation. In this paper a consistent stochastic model for these parameters is formulated, where the relevant directional dependence is included. For code-based LRFD assessment it is shown how the stochastic models can be used to determine...

  2. A comparative study of spherical and flat-Earth geopotential modeling at satellite elevations

    Science.gov (United States)

    Parrott, M. H.; Hinze, W. J.; Braile, L. W.

    1985-01-01

    Flat-Earth and spherical-Earth geopotential modeling of crustal anomaly sources at satellite elevations are compared by computing gravity and scalar magnetic anomalies perpendicular to the strike of variably dimensioned rectangular prisms at altitudes of 150, 300, and 450 km. Results indicate that the error caused by the flat-Earth approximation is less than 10% in most geometric conditions. Generally, error increase with larger and wider anomaly sources at higher altitudes. For most crustal source modeling applications at conventional satellite altitudes, flat-Earth modeling can be justified and is numerically efficient.

  3. 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

  4. Digital elevation modeling via curvature interpolation for LiDAR data

    Directory of Open Access Journals (Sweden)

    Hwamog Kim

    2016-03-01

    Full Text Available 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-posed problem and most computational algorithms become overly expensive as the number of sample points increases. This article studies an effective partial differential equation (PDE-based algorithm, called the curvature interpolation method (CIM. The new method iteratively utilizes curvature information, estimated from an intermediate surface, to construct a reliable image surface that contains all of the data points. The CIM is applied for DEM for point cloud data acquired by light detection and ranging (LiDAR technology. It converges to a piecewise smooth image, requiring O(N operations independently of the number of sample points, where $N$ is the number of grid points.

  5. 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...... of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change-induced habitat losses predicted at the European scale (10 × 10' grid...... in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10 × 10' cells. The greatest prediction discrepancy for alpine species occurs in the area...

  6. Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culcidae), along an elevational gradient in Hawaii

    Science.gov (United States)

    Ahumada, Jorge A.; LaPointe, Dennis; Samuel, Michael D.

    2004-01-01

    We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere.

  7. 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

  8. Canopy development of a model herbaceous community exposed to elevated atmospheric CO2 and soil nutrients.

    Science.gov (United States)

    Hartz-Rubin, Jennifer S.; DeLucia, Evan H.

    2001-10-01

    To test the prediction that elevated CO2 increases the maximum leaf area index (LAI) through a stimulation of photosynthesis, we exposed model herbaceous communities to two levels of CO2 crossed with two levels of soil fertility. Elevated CO2 stimulated the initial rate of canopy development and increased cumulative LAI integrated over the growth period, but it had no effect on the maximum LAI. In contrast to CO2, increased soil nutrient availability caused a substantial increase in maximum LAI. Elevated CO2 caused a slight increase in leaf area and nitrogen allocated to upper canopy layers and may have stimulated leaf turnover deep in the canopy. Gas exchange measurements of intact communities made near the time of maximum LAI indicated that soil nutrient availability, but not CO2 enrichment, caused a substantial stimulation of net ecosystem carbon exchange. These data do not support our prediction of a higher maximum LAI by elevated CO2 because the initial stimulation of LAI diminished by the end of the growth period. However, early in development, leaf area and carbon assimilation of communities may have been greatly enhanced. These results suggest that the rate of canopy development in annual communities may be accelerated with future increases in atmospheric CO2 but that maximum LAI is set by soil fertility.

  9. Development of a statistical model to identify spatial and meteorological drivers of elevated O3 in Nevada and its application to other rural mountainous regions.

    Science.gov (United States)

    Fine, Rebekka; Miller, Matthieu B; Gustin, Mae Sexauer

    2015-10-15

    Measurements of O3 at relatively remote monitoring sites are useful for quantifying baseline O3, and subsequently the magnitude of O3 not controllable by local regulations. As the National Ambient Air Quality Standard (NAAQS) for O3 becomes more stringent, there is an increased need to quantify baseline O3 particularly in the Western US, where regional and global sources can significantly enhance O3 measured at surface sites, yielding baseline mixing ratios approaching or exceeding the NAAQS threshold. Past work has indicated that meteorological conditions as well as site specific spatial characteristics (e.g. elevation, basin size, gradient) are significantly correlated with O3 intercepted at rural monitoring sites. Here, we use 3 years of measurements from sites throughout rural Nevada to develop a categorical tree model to identify spatial and meteorological characteristics that are associated with elevated baseline O3. Data from other sites in the Intermountain Western US are used to test the applicability of the model for sites throughout the region. Our analyses indicate that increased elevation and basin size were associated with increased frequency of elevated O3. On a daily time scale, relative humidity had the strongest association with observed MDA8 O3. Seventy-four percent of MDA8 O3 observations>60 ppbv occurred when daily minimum relative humidity was 60 ppbv whereas including upper air meteorological measurements improved the accuracy of predicting periods when O3 was >60 ppbv. These findings indicate that transport, rather than local production, influences O3 measurements in Nevada, and that high elevation sites in rural Nevada, are representative of baseline conditions in the Intermountain Western US. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. A Volume Model for Urban Heat Island Based on Remote Sensing Imagery and Its Application: A Case Study in Beijing

    Science.gov (United States)

    Zhou, J.; Chen, Y. H.; Li, J.; Weng, Q. H.

    2007-12-01

    Along with urbanization, urban heat island (UHI) has become one of the most serious urban problems, because of its impacts on the urban microclimate, air quality, energy consuming, public health and so on. With the advent of thermal remote sensing technology, remote observations of UHIs become the focus of urban remote sensing. While some progresses have been made by scientists, remote sensing study of UHI has been slow to advance qualitative description of thermal patterns and simple correlations. As a common indicator of UHI, magnitude is often used to describe the degree of UHI occurrence. In order to develop a more quantitative and more effective indicator for UHI dynamic monitoring at regional scale, deriving its spatial feature and facilitating the comparisons between different UHIs occur at different time or different areas based on remote sensing imageries, this paper proposes a new parameter named UHI volume to integrate UHI magnitude and extent effectively. After the subtraction of the rural contribution in the land surface temperature (LST) image, the isolated UHI signature is fitted using a least-squares Gaussian surface and then the UHI volume is calculated as a double integral of the UHI signature function over its footprint. This study investigates the applicability of this volume model based on examination of thirty EOS-Terra MODIS level 1B imageries of Beijing City, China, acquired between 2004~2006. These imageries include fifteen nighttime scenes, with their corresponding daytime scenes. Firstly, the resampled digital elevation model (DEM) data, the normalized difference vegetation index (NDVI) and the modified normalized difference water index (MNDWI) are used to extract the urban areas. Secondly, a simplified method is performed to retrieve the land surface temperature from MODIS channel 31 and channel 32. Thirdly, four transects at different directions including N-S, W-E, NW-SE and NE-SW are selected to detect the UHIs to ensure the

  11. 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...

  12. Lidar Remote Sensing of Forests: New Instruments and Modeling Capabilities

    Science.gov (United States)

    Cook, Bruce D.

    2012-01-01

    Lidar instruments provide scientists with the unique opportunity to characterize the 3D structure of forest ecosystems. This information allows us to estimate properties such as wood volume, biomass density, stocking density, canopy cover, and leaf area. Structural information also can be used as drivers for photosynthesis and ecosystem demography models to predict forest growth and carbon sequestration. All lidars use time-in-flight measurements to compute accurate ranging measurements; however, there is a wide range of instruments and data types that are currently available, and instrument technology continues to advance at a rapid pace. This seminar will present new technologies that are in use and under development at NASA for airborne and space-based missions. Opportunities for instrument and data fusion will also be discussed, as Dr. Cook is the PI for G-LiHT, Goddard's LiDAR, Hyperspectral, and Thermal airborne imager. Lastly, this talk will introduce radiative transfer models that can simulate interactions between laser light and forest canopies. Developing modeling capabilities is important for providing continuity between observations made with different lidars, and to assist the design of new instruments. Dr. Bruce Cook is a research scientist in NASA's Biospheric Sciences Laboratory at Goddard Space Flight Center, and has more than 25 years of experience conducting research on ecosystem processes, soil biogeochemistry, and exchange of carbon, water vapor and energy between the terrestrial biosphere and atmosphere. His research interests include the combined use of lidar, hyperspectral, and thermal data for characterizing ecosystem form and function. He is Deputy Project Scientist for the Landsat Data Continuity Mission (LDCM); Project Manager for NASA s Carbon Monitoring System (CMS) pilot project for local-scale forest biomass; and PI of Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager.

  13. 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

    ) and Kangerdlugssuaq (KL). We find that the main trunks of JI and KL lowered at rates of 30–35 and 7–20ma_1, respectively. The rates decreased inland. The corresponding errors were 0.3–5.2ma_1 for JI and 0.3–5.1ma_1 for KL, with errors increasing proportionally with distance from the altimeter paths....... 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...

  14. 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

  15. 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.

  16. 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...

  17. Development of a drought forecasting model for the Asia-Pacific region using remote sensing and climate data: Focusing on Indonesia

    Science.gov (United States)

    Rhee, Jinyoung; Kim, Gayoung; Im, Jungho

    2017-04-01

    Three regions of Indonesia with different rainfall characteristics were chosen to develop drought forecast models based on machine learning. The 6-month Standardized Precipitation Index (SPI6) was selected as the target variable. The models' forecast skill was compared to the skill of long-range climate forecast models in terms of drought accuracy and regression mean absolute error (MAE). Indonesian droughts are known to be related to El Nino Southern Oscillation (ENSO) variability despite of regional differences as well as monsoon, local sea surface temperature (SST), other large-scale atmosphere-ocean interactions such as Indian Ocean Dipole (IOD) and Southern Pacific Convergence Zone (SPCZ), and local factors including topography and elevation. Machine learning models are thus to enhance drought forecast skill by combining local and remote SST and remote sensing information reflecting initial drought conditions to the long-range climate forecast model results. A total of 126 machine learning models were developed for the three regions of West Java (JB), West Sumatra (SB), and Gorontalo (GO) and six long-range climate forecast models of MSC_CanCM3, MSC_CanCM4, NCEP, NASA, PNU, POAMA as well as one climatology model based on remote sensing precipitation data, and 1 to 6-month lead times. When compared the results between the machine learning models and the long-range climate forecast models, West Java and Gorontalo regions showed similar characteristics in terms of drought accuracy. Drought accuracy of the long-range climate forecast models were generally higher than the machine learning models with short lead times but the opposite appeared for longer lead times. For West Sumatra, however, the machine learning models and the long-range climate forecast models showed similar drought accuracy. The machine learning models showed smaller regression errors for all three regions especially with longer lead times. Among the three regions, the machine learning models

  18. 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.

  19. Constitutive Model of ASTM A992 Steel at Elevated Temperature for Application in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Lee, Jinwoo; Engelhardt, Michael D.

    2014-01-01

    ASTM A992 is the most common grade of high strength steel used for building structures in the U. S. and considered to be applied in Korean nuclear power plant in an immediate future. This paper provides two constitutive models for high strength steel of ASTM A992 steel at elevated temperature to use in steel structures or steel building subjected to fire loads and thermal loads. One is the detailed full constitutive model and it has good agreements for every temperatures from room temperature to 1,000 .deg. C with increments of 100 .deg. C because it was developed using a best-fitting approach method with separated special zones; elastic, plastic plateau, strain-hardening and strain-softening regions. The curve-fitting results were helpful to derive the constitutive models of the stress-strain curves at room and elevated temperatures. The first of these models was developed for academia, and very closely fit the observed test data throughout the strain-hardening and softening zones. The second model was developed as a design model. Despite its simplicity (assumed bilinear stress-strain behavior), it captures the observed stress-strain behavior better than the Eurocode 3-1-2 provisions, most notably in terms of its predicted strain softening behavior and ultimate strains

  20. 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.

  1. Perspectives in using a remotely sensed dryness index in distributed hydrological models at river basin scale

    DEFF Research Database (Denmark)

    Andersen, Jens Asger; Sandholt, Inge; Jensen, Karsten Høgh

    2002-01-01

    evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study...... examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor...

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

    Science.gov (United States)

    Rueda-Velasquez, Carlos Alberto

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

  3. Modelling of trail degradation based on detailed multi-temporal digital elevation models

    Science.gov (United States)

    Tomczyk, Aleksandra; Ewertowski, Marek

    2017-04-01

    Degradation of trails adversely affects the natural environment as well as the safety and comfort of visitors. Managers of protected areas can directly impact some of the factors related to the degradation, for example, they may regulate the type of use or location of the drainage. On the other hand, they may only have an indirect impact on the other factors, e.g. through the appropriate demarcation of trails. The role of national and landscape parks is both protection of the natural environment and providing recreational opportunities. Hence, the need to obtain accurate information about the current state of the trails and the direction of their transformation is apparent. Based on multi-temporal detailed digital elevation models (DEMs) generated using topographic surveys, we proposed a simplified model of geomorphological processes which shape the surface of recreational trails. As the basis of our consideration, we adopt the idea that recreational trails and forest roads can be equated with periodic flows in the context of soil loss, transport and accumulation. Our model of trail development and degradation consists of three phases: 1) Initial phase: In this phase, anthropogenic processes play the most important role. Destroying of vegetation cover by boots and tires leads to developing of a bare trail tread which becomes vulnerable to the natural processes. When the vegetation cover is removed, soil erosion starts, hence anthropogenic processes such as trampling or damaging vegetation by tires can be regarded as preparatory processes for further development. 2) Mature phase: In this phase, natural and anthropogenic processes coexist. All areas of trail tread and its surrounding undergo transformations. Anthropogenic processes impact mainly on trail tread. Trampling leads to soil compaction in case of smooth tread or to soil relocation and loss in case of bumpy tread. Uses of hiking sticks also lead to soil loosening, similar to tires of cycles. Loosening by

  4. Using digital elevation models as an environmental predictor for soil clay contents

    DEFF Research Database (Denmark)

    Greve, Mogens Humlekrog; Bou Kheir, Rania; Greve, Mette Balslev

    2012-01-01

    The objective of this study was to evaluate the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) as an environmental predictor for soil clay content (SCC). It was based on the applicability of different DEMs, i.e., SRTM with 90-m resolution and airborne Light Detection...... and Ranging (LIDAR) (in 24- and 90-m resolution), using regression-tree analysis. Ten terrain parameters were generated from these DEMs. These terrain parameters were used along other environmental variables to statistically explain SCC content in Denmark. Results indicated that the SRTM tree model (T1: 90-m...

  5. Excess Loss Model for Low Elevation Links in Urban Areas for UAVs

    Directory of Open Access Journals (Sweden)

    M. Simunek

    2011-09-01

    Full Text Available In this paper we analyze the link between an UAV and a ground control station in an urban area. This link shows a unique geometry which is somewhere in between the purely terrestrial (e.g., a macro-cell channel and the land mobile satellite case (LMS. We describe a measurement campaign which reproduces the UAV link conditions and shows how the excess loss is mainly dependent on the elevation angle and fairly independent of the distance. Finally, we propose a simple physical model for predicting the excess loss based on a combination of diffracted and reflected components. Results from this model are in good agreement with the measurements.

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

    Science.gov (United States)

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

    2012-04-01

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

  7. 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

  8. Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models

    Directory of Open Access Journals (Sweden)

    José María Bodoque

    2016-07-01

    Full Text Available The use of high resolution ground-based light detection and ranging (LiDAR datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs. As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN. The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i generation an urban TIN from LiDAR data with a density of 0.5 points·m−2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points·m−2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii implementation of a two-dimensional (2D hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings; and (iii determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m show that this parameter has to be neatly characterized in order

  9. 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.

  10. Application of Semi-Automated Filter to Improve Waveform Lidar Sub-Canopy Elevation Model

    Directory of Open Access Journals (Sweden)

    Yongwei Sheng

    2012-05-01

    Full Text Available Modeling sub-canopy elevation is an important step in the processing of waveform lidar data to measure three dimensional forest structure. Here, we present a methodology based on high resolution discrete-return lidar (DRL to correct the ground elevation derived from large-footprint Laser Vegetation Imaging Sensor (LVIS and to improve measurement of forest structure. We use data acquired over Barro Colorado Island, Panama by LVIS large-footprint lidar (LFL in 1998 and DRL in 2009. The study found an average vertical difference of 28.7 cm between 98,040 LVIS last-return points and the discrete-return lidar ground surface across the island. The majority (82.3% of all LVIS points matched discrete return elevations to 2 m or less. Using a multi-step process, the LVIS last-return data is filtered using an iterative approach, expanding window filter to identify outlier points which are not part of the ground surface, as well as applying vertical corrections based on terrain slope within the individual LVIS footprints. The results of the experiment demonstrate that LFL ground surfaces can be effectively filtered using methods adapted from discrete-return lidar point filtering, reducing the average vertical error by 15 cm and reducing the variance in LVIS last-return data by 70 cm. The filters also reduced the largest vertical estimations caused by sensor saturation in the upper reaches of the forest canopy by 14.35 m, which improve forest canopy structure measurement by increasing accuracy in the sub-canopy digital elevation model.

  11. The role of remote sensing in hydrological modelling of the Okavango Delta, Botswana.

    Science.gov (United States)

    Milzow, Christian; Kgotlhang, Lesego; Kinzelbach, Wolfgang; Meier, Philipp; Bauer-Gottwein, Peter

    2009-05-01

    A coupled surface water-groundwater model of the Okavango Delta has been built based on the United States Geological Survey software MODFLOW 2000 including the SFR2 package for stream-flow routing. It will provide a new tool for evaluating water management and climate change scenarios. The delta's size and limited accessibility make direct, on the ground data acquisition difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both model input parameters and calibration. Topography, aquifer thickness, channel positions, evapotranspiration and precipitation data are all based on remote sensing. Simulated flooding patterns are compared to patterns derived from visible to thermal NOAA-AVHRR data and microwave radar ENVISAT-ASAR data.

  12. [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.

  13. On the use of remotely sensed data to constrain process modeling and ecological forecasting

    Science.gov (United States)

    Serbin, S.; Greenberg, J. A.

    2014-12-01

    The ability to seamlessly integrate information on vegetation structure, function, and dynamics across a continuum of scales, from the field to satellite observations, greatly enhances our ability to understand how terrestrial vegetation-atmosphere interactions change over time and in response
to disturbances and global change. For example, ecosystem process models require detailed information on the state (e.g. structure, leaf area index), surface properties (e.g. albedo), and dynamics (e.g. phenology, succession) of ecosystems in order to properly simulate the fluxes of carbon (C), water, and energy from the land to the atmosphere as well as address the vulnerability of ecosystems to environmental, pest and pathogen, and other anthropogenic perturbations. Other activities such as species distribution and environmental niche modeling (SDENM) require not only presence/absence information but also detailed spatial and temporal datasets, including climate and remotely sensed observations, to accurately project species ranges under current and often future climatic scenarios. Despite the many challenges of adequately initializing and parameterizing models, the last several decades have shown a substantial increase in the amount of available data useful for improving ecological predictions. Specifically remote sensing data provides an important data constraint for projecting species and successional changes as well as vegetation dynamics and the fluxes of C, water and energy and the storage of C in ecosystems, principally as a synoptic observational dataset for capturing short- to long-term plant-climate interactions. In this talk we will highlight the current and potential uses of various remotely sensed data sources in constraining process modeling and SDENM activities. We will pay particular attention to the uses of remote sensing as a direct constraint on ecological forecasts or a key observational dataset used to capture plant-climate interactions

  14. GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and...

  15. GLAS/ICESat 500 m Laser Altimetry Digital Elevation Model of Antarctica, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and...

  16. GLAS/ICESat 500 m Laser Altimetry Digital Elevation Model of Antarctica

    Data.gov (United States)

    National Aeronautics and Space Administration — The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and...

  17. GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland

    Data.gov (United States)

    National Aeronautics and Space Administration — The Geoscience Laser Altimeter System (GLAS) instrument on the Ice, Cloud, and land Elevation Satellite (ICESat) provides global measurements of elevation, and...

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    M. Marshall

    2013-03-01

    Full Text Available 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.

  20. 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.

  1. 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)

  2. 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

  3. Filling the voids in the SRTM elevation model — A TIN-based delta surface approach

    Science.gov (United States)

    Luedeling, Eike; Siebert, Stefan; Buerkert, Andreas

    The Digital Elevation Model (DEM) derived from NASA's Shuttle Radar Topography Mission is the most accurate near-global elevation model that is publicly available. However, it contains many data voids, mostly in mountainous terrain. This problem is particularly severe in the rugged Oman Mountains. This study presents a method to fill these voids using a fill surface derived from Russian military maps. For this we developed a new method, which is based on Triangular Irregular Networks (TINs). For each void, we extracted points around the edge of the void from the SRTM DEM and the fill surface. TINs were calculated from these points and converted to a base surface for each dataset. The fill base surface was subtracted from the fill surface, and the result added to the SRTM base surface. The fill surface could then seamlessly be merged with the SRTM DEM. For validation, we compared the resulting DEM to the original SRTM surface, to the fill DEM and to a surface calculated by the International Center for Tropical Agriculture (CIAT) from the SRTM data. We calculated the differences between measured GPS positions and the respective surfaces for 187,500 points throughout the mountain range (ΔGPS). Comparison of the means and standard deviations of these values showed that for the void areas, the fill surface was most accurate, with a standard deviation of the ΔGPS from the mean ΔGPS of 69 m, and only little accuracy was lost by merging it to the SRTM surface (standard deviation of 76 m). The CIAT model was much less accurate in these areas (standard deviation of 128 m). The results show that our method is capable of transferring the relative vertical accuracy of a fill surface to the void areas in the SRTM model, without introducing uncertainties about the absolute elevation of the fill surface. It is well suited for datasets with varying altitude biases, which is a common problem of older topographic information.

  4. A discussion of remote sensing geologic image model of a uranium deposit

    International Nuclear Information System (INIS)

    Qiao Rui

    1998-12-01

    Based on the geologic study on the uranium deposit, the items about remote sensing images of the mineral deposit were discussed, such as the best choice of temporal, the best compose of band, the image characteristics and image model. It is considered that the mineral deposit was controlled by the line, ring and arc through the interpretation of color-composite images. The geologic image model of the mineral deposit is annular fault block controlled by northeast and northwest structures. It is recommended that much attentions should be paid to mineralized regions being similar with this image model in long-range forecast

  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. Remote sensing and modelling analysis of the extreme dust storm hitting the Middle East and eastern Mediterranean in September 2015

    Science.gov (United States)

    Solomos, Stavros; Ansmann, Albert; Mamouri, Rodanthi-Elisavet; Binietoglou, Ioannis; Patlakas, Platon; Marinou, Eleni; Amiridis, Vassilis

    2017-03-01

    The extreme dust storm that affected the Middle East and the eastern Mediterranean in September 2015 resulted in record-breaking dust loads over Cyprus with aerosol optical depth exceeding 5.0 at 550 nm. We analyse this event using profiles from the European Aerosol Research Lidar Network (EARLINET) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), geostationary observations from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI), and high-resolution simulations from the Regional Atmospheric Modeling System (RAMS). The analysis of modelling and remote sensing data reveals the main mechanisms that resulted in the generation and persistence of the dust cloud over the Middle East and Cyprus. A combination of meteorological and surface processes is found, including (a) the development of a thermal low in the area of Syria that results in unstable atmospheric conditions and dust mobilization in this area, (b) the convective activity over northern Iraq that triggers the formation of westward-moving haboobs that merge with the previously elevated dust layer, and (c) the changes in land use due to war in the areas of northern Iraq and Syria that enhance dust erodibility.

  7. 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/.

  8. 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

  9. Ventricular dilation and elevated aqueductal pulsations in a new experimental model of communicating hydrocephalus

    Energy Technology Data Exchange (ETDEWEB)

    Wagshul, M.; Smith, S.; Wagshul, M.; McAllister, J.P.; Rashid, S.; Li, J.; Egnor, M.R.; Walker, M.L.; Yu, M.; Smith, S.D.; Zhang, G.; Chen, J.J.; Beneveniste, H.

    2009-03-01

    In communicating hydrocephalus (CH), explanations for the symptoms and clear-cut effective treatments remain elusive. Pulsatile flow through the cerebral aqueduct is often significantly elevated, but a clear link between abnormal pulsations and ventriculomegaly has yet to be identified. We sought to demonstrate measurement of pulsatile aqueductal flow of CSF in the rat, and to characterize the temporal changes in CSF pulsations in a new model of CH. Hydrocephalus was induced by injection of kaolin into the basal cisterns of adult rats (n = 18). Ventricular volume and aqueductal pulsations were measured on a 9.4 T MRI over a one month period. Half of the animals developed ventricular dilation, with increased ventricular volume and pulsations as early as one day post-induction, and marked chronic elevations compared to intact controls (volume: 130.15 {+-} 83.21 {mu}l vs. 15.52 {+-} 2.00 {mu}l; pulsations: 114.51 nl {+-} 106.29 vs. 0.72 {+-} 0.13 nl). Similar to the clinical presentation, the relationship between ventricular size and pulsations was quite variable. However, the pulsation time-course revealed two distinct sub-types of hydrocephalic animals: those with markedly elevated pulsations which persisted over time, and those with mildly elevated pulsations which returned to near normal levels after one week. These groups were associated with severe and mild ventriculomegaly respectively. Thus, aqueductal flow can be measured in the rat using high-field MRI and basal cistern-induced CH is associated with an immediate change in CSF pulsatility. At the same time, our results highlight the complex nature of aqueductal pulsation and its relationship to ventricular dilation.

  10. Investigation of potential sea level rise impact on the Nile Delta, Egypt using digital elevation models.

    Science.gov (United States)

    Hasan, Emad; Khan, Sadiq Ibrahim; Hong, Yang

    2015-10-01

    In this study, the future impact of Sea Level Rise (SLR) on the Nile Delta region in Egypt is assessed by evaluating the elevations of two freely available Digital Elevation Models (DEMs): the SRTM and the ASTER-GDEM-V2. The SLR is a significant worldwide dilemma that has been triggered by recent climatic changes. In Egypt, the Nile Delta is projected to face SLR of 1 m by the end of the 21th century. In order to provide a more accurate assessment of the future SLR impact on Nile Delta's land and population, this study corrected the DEM's elevations by using linear regression model with ground elevations from GPS survey. The information for the land cover types and future population numbers were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and the Gridded Population of the Worlds (GPWv3) datasets respectively. The DEM's vertical accuracies were assessed using GPS measurements and the uncertainty analysis revealed that the SRTM-DEM has positive bias of 2.5 m, while the ASTER-GDEM-V2 showed a positive bias of 0.8 m. The future inundated land cover areas and the affected population were illustrated based on two SLR scenarios of 0.5 m and 1 m. The SRTM DEM data indicated that 1 m SLR will affect about 3900 km(2) of cropland, 1280 km(2) of vegetation, 205 km(2) of wetland, 146 km(2) of urban areas and cause more than 6 million people to lose their houses. The overall vulnerability assessment using ASTER-GDEM-V2 indicated that the influence of SLR will be intense and confined along the coastal areas. For instance, the data indicated that 1 m SLR will inundate about 580 Km(2) (6%) of the total land cover areas and approximately 887 thousand people will be relocated. Accordingly, the uncertainty analysis of the DEM's elevations revealed that the ASTER-GDEM-V2 dataset product was considered the best to determine the future impact of SLR on the Nile Delta region.

  11. 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)

  12. 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.

  13. 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

  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. Generation of large-scale digital elevation models via synthetic aperture radar interferometry

    Energy Technology Data Exchange (ETDEWEB)

    Fornaro, G.; Lanari, R.; Sansosti, E. [Consiglio Nazionale delle Ricerche, Istituto di Ricerca per l' Elettromagnetismo ed i componenti elettronici, Naples (Italy); Tesauro, M.; Franceschetti, G. [Naples Univ. Federico 2., Naples (Italy). Dipt. di Ingegneria Elettronica e delle Telecomunicazioni

    2001-02-01

    It is investigated the possibility to generate a large-scale Digital Elevation Model by applying the Synthetic Aperture Radar interferometry technique and using tandem data acquired by the ERS-1/ERS-2 sensors. The presented study is mainly focused on the phase unwrapping step that represents the most critical point of the overall processing chain. In particular, it is concentrated on the unwrapping problems related to the use of a large ERS tandem data set that, in order to be unwrapped, must be partitioned. The paper discusses the inclusion of external information (even rough) of the scene topography, the application of a region growing unwrapping technique and the insertion of possible constraints on the phase to be retrieved in order to minimize the global unwrapping errors. The main goal is the generation of a digital elevation model relative to an area of 300 km by 100 km located in the southern part of Italy. Comparisons between the achieved result and a precise digital terrain model, relative to a smaller area, are also included.

  16. 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.

  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. 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

  19. Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa

    Directory of Open Access Journals (Sweden)

    T. Vischel

    2008-05-01

    Full Text Available The paper compares two independent approaches to estimate soil moisture at the regional scale over a 4625 km2 catchment (Liebenbergsvlei, South Africa. The first estimate is derived from a physically-based hydrological model (TOPKAPI. The second estimate is derived from the scatterometer on board the European Remote Sensing satellite (ERS. Results show a good correspondence between the modelled and remotely sensed soil moisture, particularly with respect to the soil moisture dynamic, illustrated over two selected seasons of 8 months, yielding regression R2 coefficients lying between 0.68 and 0.92. Such a close similarity between these two different, independent approaches is very promising for (i remote sensing in general (ii the use of hydrological models to back-calculate and disaggregate the satellite soil moisture estimate and (iii for hydrological models to assimilate the remotely sensed soil moisture.

  20. Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

    Directory of Open Access Journals (Sweden)

    Pengyun Chen

    2017-06-01

    Full Text Available Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information’s relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM, the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM, the pointwise approach and graph theory (PA-GT, and the Principal Component Analysis-Nonlocal Means (PCA-NLM denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

  1. Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application.

    Science.gov (United States)

    Chen, Pengyun; Zhang, Yichen; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola

    2017-06-06

    Traditional image change detection based on a non-subsampled contourlet transform always ignores the neighborhood information's relationship to the non-subsampled contourlet coefficients, and the detection results are susceptible to noise interference. To address these disadvantages, we propose a denoising method based on the non-subsampled contourlet transform domain that uses the Hidden Markov Tree model (NSCT-HMT) for change detection of remote sensing images. First, the ENVI software is used to calibrate the original remote sensing images. After that, the mean-ratio operation is adopted to obtain the difference image that will be denoised by the NSCT-HMT model. Then, using the Fuzzy Local Information C-means (FLICM) algorithm, the difference image is divided into the change area and unchanged area. The proposed algorithm is applied to a real remote sensing data set. The application results show that the proposed algorithm can effectively suppress clutter noise, and retain more detailed information from the original images. The proposed algorithm has higher detection accuracy than the Markov Random Field-Fuzzy C-means (MRF-FCM), the non-subsampled contourlet transform-Fuzzy C-means clustering (NSCT-FCM), the pointwise approach and graph theory (PA-GT), and the Principal Component Analysis-Nonlocal Means (PCA-NLM) denosing algorithm. Finally, the five algorithms are used to detect the southern boundary of the Gurbantunggut Desert in Xinjiang Uygur Autonomous Region of China, and the results show that the proposed algorithm has the best effect on real remote sensing image change detection.

  2. 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

  3. STATISTICAL EVALUATION OF FITTING ACCURACY OF GLOBAL AND LOCAL DIGITAL ELEVATION MODELS IN IRAN

    Directory of Open Access Journals (Sweden)

    F. Alidoost

    2013-09-01

    Full Text Available Digital Elevation Models (DEMs are one of the most important data for various applications such as hydrological studies, topography mapping and ortho image generation. There are well-known DEMs of the whole world that represent the terrain's surface at variable resolution and they are also freely available for 99% of the globe. However, it is necessary to assess the quality of the global DEMs for the regional scale applications.These models are evaluated by differencing with other reference DEMs or ground control points (GCPs in order to estimate the quality and accuracy parameters over different land cover types. In this paper, a comparison of ASTER GDEM ver2, SRTM DEM with more than 800 reference GCPs and also with a local elevation model over the area of Iran is presented. This study investigates DEM’s characteristics such as systematic error (bias, vertical accuracy and outliers for DEMs using both the usual (Mean error, Root Mean Square Error, Standard Deviation and the robust (Median, Normalized Median Absolute Deviation, Sample Quantiles descriptors. Also, the visual assessment tools are used to illustrate the quality of DEMs, such as normalized histograms and Q-Q plots. The results of the study confirmed that there is a negative elevation bias of approximately 5 meters of GDEM ver2. The measured RMSE and NMAD for elevation differences of GDEM-GCPs are 7.1 m and 3.2 m, respectively, while these values for SRTM and GCPs are 9.0 m and 4.4 m. On the other hand, in comparison with the local DEM, GDEM ver2 exhibits the RMSE of about 6.7 m, a little higher than the RMSE of SRTM (5.1 m.The results of height difference classification and other statistical analysis of GDEM ver2-local DEM and SRTM-local DEM reveal that SRTM is slightly more accurate than GDEM ver2. Accordingly, SRTM has no noticeable bias and shift from Local DEM and they have more consistency to each other, while GDEM ver2 has always a negative bias.

  4. 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...

  5. Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa

    OpenAIRE

    T. Vischel; G. Pegram; S. Sinclair; W. Wagner; A. Bartsch

    2007-01-01

    The paper compares two independent approaches to estimate soil moisture at the regional scale over a 4625 km2 catchment (Liebenbergsvlei, South Africa). The first estimate is derived from a physically-based hydrological model (TOPKAPI). The second estimate is derived from the scatterometer on board the European Remote Sensing satellite (ERS). Results show a good correspondence between the modelled and remotely sensed soil moisture, particularly with respect to the soil ...

  6. Application of Low-Cost Digital Elevation Models to Detect Change in Forest Carbon Sequestration Projects

    Energy Technology Data Exchange (ETDEWEB)

    Kenneth Glenn MacDicken

    2007-07-31

    This two-year study evaluated advanced multispectral digital imagery applications for assessment of forest carbon stock change. A series of bench and field studies in North Carolina and Ohio tested aerial assessments of forest change between two time periods using two software packages (ERDAS and TERREST) for Digital Elevation Model (DEM) creation, automated classification software (eCognition) for canopy segmentation and a multiple ranging laser designed to improve quality of elevation data. Results of the DEM software comparison showed that while TERREST has the potential to produce much higher resolution DEM than ERDAS, it is unable to resolve crucial canopy features adequately. Lab tests demonstrated that additional laser data improves image registration and Z-axis DEM quality. Data collected in the field revealed difficult challenges in correctly modeling the location of laser strike and subsequently determining elevations in both software packages. Automated software segmentation of tree canopies provided stem diameter and biomass carbon estimates that were within 3% of comparable ground based estimates in the Ohio site and produced similar biomass estimates for a limited number of plots in the Duke forest. Tree height change between time periods and canopy segmentation from multispectral imagery allowed calculation of forest carbon stock change at costs that are comparable to those for ground-based methods. This work demonstrates the potential of lower cost imagery systems enhanced with laser data to collect high quality imagery and paired laser data for forestry and environmental applications. Additional research on automated canopy segmentation and multi-temporal image registration is needed to refine these methods for commercial use.

  7. The influence of changes in glacier extent and surface elevation on modeled mass balance

    Directory of Open Access Journals (Sweden)

    F. Paul

    2010-12-01

    Full Text Available Glaciers are widely recognized as unique demonstration objects for climate change impacts, mostly due to the strong change of glacier length in response to small climatic changes. However, glacier mass balance as the direct response to the annual atmospheric conditions can be better interpreted in meteorological terms. When the climatic signal is deduced from long-term mass balance data, changes in glacier geometry (i.e. surface extent and elevation must be considered as such adjustments form an essential part of the glacier reaction to new climatic conditions. In this study, a set of modelling experiments is performed to assess the influence of changes in glacier geometry on mass balance for constant climatic conditions. The calculations are based on a simplified distributed energy/mass balance model in combination with information on glacier extent and surface elevation for the years 1850 and 1973/1985 for about 60 glaciers in the Swiss Alps. The results reveal that over this period about 50–70% of the glacier reaction to climate change (here a one degree increase in temperature is "hidden" in the geometric adjustment, while only 30–50% can be measured as the long-term mean mass balance. For larger glaciers, the effect of the areal change is partly reduced by a lowered surface elevation, which results in a slightly more negative balance despite a potential increase of topographic shading. In view of several additional reinforcement feedbacks that are observed in periods of strong glacier decline, it seems that the climatic interpretation of long-term mass balance data is rather complex.

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. Estuarine Bathymetric Digital Elevation Models (30 meter resolution) Derived From Source Hydrographic Survey Soundings Collected by NOAA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Bathymetric Digital Elevation Models (DEM) were generated from original point soundings collected during hydrographic surveys conducted by the National Ocean...

  14. 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.

  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

    2016-01-01

    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.

  16. 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.

  17. Propagation modeling of ocean-scattered low-elevation GPS signals for maritime tropospheric duct inversion

    International Nuclear Information System (INIS)

    Zhang Jin-Peng; Wu Zhen-Sen; Zhao Zhen-Wei; Zhang Yu-Sheng; Wang Bo

    2012-01-01

    The maritime tropospheric duct is a low-altitude anomalous refractivity structure over the ocean surface, and it can significantly affect the performance of many shore-based/shipboard radar and communication systems. We propose the idea that maritime tropospheric ducts can be retrieved from ocean forward-scattered low-elevation global positioning system (GPS) signals. Retrieval is accomplished by matching the measured power patterns of the signals to those predicted by the forward propagation model as a function of the modified refractivity profile. On the basis of a parabolic equation method and bistatic radar equation, we develop such a forward model for computing the trapped propagation characteristics of an ocean forward-scattered GPS signal within a tropospheric duct. A new GPS scattering initial field is defined for this model to start the propagation modeling. A preliminary test on the performance of this model is conducted using measured data obtained from a 2009-experiment in the South China Sea. Results demonstrate that this model can predict GPS propagation characteristics within maritime tropospheric ducts and serve as a forward model for duct inversion

  18. A Modified Johnson Cook Constitutive Model for Aermet 100 at Elevated Temperatures

    Science.gov (United States)

    Zhanwei, Yuan; Fuguo, Li; Guoliang, Ji

    2018-01-01

    The predicted flow behaviors of Aermet 100 steel were analyzed within a wide range of temperatures of 1,073 K-1,473 K and strain rates of 0.01 s-1-50 s-1 based on isothermal compression tests. Using the original Johnson Cook (JC) model and a modified Johnson Cook (MJC) model, the constitutive equations were constructed in the case of elevated temperatures. For both the JC and MJC, and the previously studied (Arrhenius-type model and double-multivariate nonlinear regression (DMNR)) models, their respective predictability levels were evaluated by contrasting both the correlation coefficient R and the average absolute relative error (AARE). The results showed that the prediction from the three models meet the accuracy requirement based on the experimental data, the only exception being the JC model. By comparing the predictability and numbers of material constants involved, the modified Johnson Cook model is regarded as an excellent choice for predicting the flow behaviors of Aermet 100 steel within the range being studied.

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

    Science.gov (United States)

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

    2017-04-01

    Knowledge on hydrological regimes of river basins is crucial for water management. However, data requirements often limit the applicability of hydrological models in basins with scarce in-situ data. Remote sensing provides a unique possibility to acquire information on hydrological variables in these basins. This study explores how multi-mission remote sensing data can inform a hydrological model. The Ogooué basin in Gabon is used as study area. No previous modelling efforts have been conducted for the basin and only historical flow and precipitation observations are available. Publicly available remote sensing observations are used to parametrize, force, calibrate and validate a hydrological model of the Ogooué. The modelling framework used in the study, is a lumped conceptual rainfall-runoff model based on the Budyko framework coupled to a Muskingum routing scheme. Precipitation is a crucial driver of the land-surface water balance, therefore two satellite-based rainfall estimates, Tropical Rainfall Measuring Mission (TRMM) product 3B42 version 7 and Famine Early Warning System - Rainfall Estimate (FEWS-RFE), are compared. The comparison shows good seasonal and spatial agreement between the products; however, TRMM consistently predicts significantly more precipitation: 1726 mm on average per year against 1556 mm for FEWS-RFE. Best modeling results are obtained with the TRMM precipitation forcing. Model calibration combines historical in-situ flow observations and GRACE total water storage observations using the Jet Propulsion Laboratory (JPL) mascon solution in a multi-objective approach. The two models are calibrated using flow duration curves and climatology benchmarks to overcome the lack of simultaneity between simulated and observed discharge. The objectives are aggregated into a global objective function, and the models are calibrated using the Shuffled Complex Evolution Algorithm. Water height observations from drifting orbit altimetry missions are

  20. 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

  1. A Conceptual Model of Surface Reflectance Estimation for Satellite Remote Sensing Images Using in situ Reference Data

    Directory of Open Access Journals (Sweden)

    Ke-Sheng Cheng

    2012-03-01

    Full Text Available For satellite remote sensing, radiances received at the sensor are not only affected by the atmosphere but also by the topographic properties of the terrain surface. As a result, atmospheric correction alone does not yield output images that truly reflect terrain surface properties, namely surface reflectance (bidirectional reflectance factor, BRF of objects on the earth surface. Following the concept of the radiometric control area (RCA-based path radiance estimation method, we herein propose a statistical approach for surface reflectance estimation utilizing DEM data and surface reflectance of selected radiometric control areas. An algorithm for identification of shaded samples and a shape factor model were also developed in this study. The proposed RCA-based surface reflectance estimation method is capable of achieving good reflectance estimates in a region where elevation varies from 0 to approximately 600 m above the mean sea level. However, further study is recommended in order to extend the application of the proposed method to areas with substantial terrain variation.

  2. A stochastic, evolutionary model for range shifts and richness on tropical elevational gradients under Quaternary glacial cycles.

    Science.gov (United States)

    Colwell, Robert K; Rangel, Thiago F

    2010-11-27

    Quaternary glacial-interglacial cycles repeatedly forced thermal zones up and down the slopes of mountains, at all latitudes. Although no one doubts that these temperature cycles have left their signature on contemporary patterns of geography and phylogeny, the relative roles of ecology and evolution are not well understood, especially for the tropics. To explore key mechanisms and their interactions in the context of chance events, we constructed a geographical range-based, stochastic simulation model that incorporates speciation, anagenetic evolution, niche conservatism, range shifts and extinctions under late Quaternary temperature cycles along tropical elevational gradients. In the model, elevational patterns of species richness arise from the differential survival of founder lineages, consolidated by speciation and the inheritance of thermal niche characteristics. The model yields a surprisingly rich variety of realistic patterns of phylogeny and biogeography, including close matches to a variety of contemporary elevational richness profiles from an elevational transect in Costa Rica. Mountaintop extinctions during interglacials and lowland extinctions at glacial maxima favour mid-elevation lineages, especially under the constraints of niche conservatism. Asymmetry in temperature (greater duration of glacial than of interglacial episodes) and in lateral area (greater land area at low than at high elevations) have opposing effects on lowland extinctions and the elevational pattern of species richness in the model--and perhaps in nature, as well.

  3. 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.

  4. 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.

  5. Numerical modeling of a remote Himalayan glacier constrained by satellite data

    Science.gov (United States)

    Scherler, Dirk; Farinotti, Daniel; Anderson, Robert S.; Strecker, Manfred R.

    2010-05-01

    Himalayan glaciers are amongst the least studied and understood glaciers on Earth, yet their future behavior and water budget is crucial for densely-populated areas in south, central, and eastern Asia. Here, we use remotely-sensed glacier-surface velocities from a glacier in the upper Tons valley of western Uttaranchal in the Indian Himalaya, to evaluate the results from a numerical glacier model. We estimate present-day ice thickness distribution from surface topography with an approach based on mass conservation and principles of ice-flow dynamics. The numerical glacier model is based on the shallow ice approximation, and requires a mass-balance profile and glacier-bedrock topography as input. Optical-satellite imagery is used for mapping glacier extents and deriving glacier-surface velocities from cross correlation of multi-temporal ASTER and SPOT images. Modeling results, employing a mass balance profile from nearby monitored glaciers with a better data base, indicate good agreement between observed and modeled glacier extents and surface velocities. Discrepancies between model and observation in the lower part of the glacier are likely related to (1) poorly constrained effects of debris cover, and (2) the present disequilibrium and down-wasting of the glacier. Our technique will be useful for comparative analyses of glacial behavior worldwide as most data for our study has been obtained from analysis of remote-sensing data, virtually available for any region on Earth.

  6. 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

  7. 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.

  8. Use of remote sensing derived parameters in a crop model for biomass prediction of hay crop

    Science.gov (United States)

    El Hajj, Mohammad; Baghdadi, Nicolas; Cheviron, Bruno; Belaud, Gilles; Zribi, Mehrez

    2016-04-01

    Pre-harvest yield forecasting is a critical challenge for producers, especially for large agricultural areas. During previous decades, numerous crop models were developed to predict crop growth and yield at daily time, most often for wheat or maize, and also for grasslands. Crop models require several input parameters that describe soil properties (e.g. field capacity), plant characteristics (e.g. maximal rooting depth) and management options (e.g. sowing dates, irrigation and harvest dates), which are referred to as the soil, plant and management families of parameters. Remote sensing technology has been extensively applied to identify spatially distributed values of some of the accessible parameters in the soil, plant and management families. The aim of this study was to address the feasibility, merits and limitations of forcing remote-sensing-derived parameters (LAI values, harvest and irrigation dates) in the PILOTE crop model, targeting the Total Dry Matter (TDM) of hay crops. Results show that optical images are suitable to feed PILOTE with LAI values without inducing significant errors on the predicted Total Dry Matter (TDM) values (Root Mean Square Error "RMSE" = 0.41 t/ha and Mean Absolute Percentage Error "MAPE" = 22%). Moreover, optical images with revisit times lower than 16 days are adequate to feed PILOTE with remotely sensed harvest dates (RMSE irrigation dates that were estimated from SAR images also enabled reliable model predictions, at least when attaching a random uncertainty of "only" 3 days to the real known irrigation dates. The case of one or several undetected irrigations has also been explored, with the expected conclusion that undetected irrigations significantly affect model predictions only in dry periods. For the tested soil properties and climatic conditions, a maximum underestimation of TDM of approximately 1.55 t/ha (reference TDM of 3.43 t/ha) was observed in the second crop growth cycle when ignoring two irrigations out of four in

  9. Improved hydrological modeling for remote regions using a combination of observed and simulated precipitation data

    DEFF Research Database (Denmark)

    van der Linden, Sandra; Christensen, Jens Hesselbjerg

    2003-01-01

    Precipitation, as simulated by climate models, can be used as input in hydrological models, despite possible biases both in the total annual amount simulated as well as the seasonal variation. Here we elaborated on a new technique, which adjusted precipitation data generated by a high......-resolution regional climate model (HIRHAM4) with a mean-field bias correction using observed precipitation. A hydrological model (USAFLOW) was applied to simulate runoff using observed precipitation and a combination of observed and simulated precipitation as input. The method was illustrated for the remote Usa basin......, situated in the European part of Arctic Russia, close to the Ural Mountains. It was shown that runoff simulations agree better with observations when the combined precipitation data set was used than when only observed precipitation was used. This appeared to be because the HIRHAM4 model data compensated...

  10. 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.

  11. 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

  12. 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.

  13. Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

    Science.gov (United States)

    Kawa, S. R.; Collatz, G. J.; Pawson, S.; Wennberg, P. O.; Wofsy, S. C.; Andrews, A. E.

    2010-01-01

    We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual

  14. 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

  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. 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.

  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. The conservation value of elevation data accuracy and model sophistication in reserve design under sea-level rise.

    Science.gov (United States)

    Zhu, Mingjian; Hoctor, Tom; Volk, Mike; Frank, Kathryn; Linhoss, Anna

    2015-10-01

    Many studies have explored the value of using more sophisticated coastal impact models and higher resolution elevation data in sea-level rise (SLR) adaptation planning. However, we know little about to what extent the improved models and data could actually lead to better conservation outcomes under SLR. This is important to know because high-resolution data are likely to not be available in some data-poor coastal areas in the world and running more complicated coastal impact models is relatively time-consuming, expensive, and requires assistance by qualified experts and technicians. We address this research question in the context of identifying conservation priorities in response to SLR. Specifically, we investigated the conservation value of using more accurate light detection and ranging (Lidar)-based digital elevation data and process-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple "bathtub" models based on the relatively coarse National Elevation Dataset (NED) in a coastal region of northeast Florida. We compared conservation outcomes identified by reserve design software (Zonation) using three different model dataset combinations (Bathtub-NED, Bathtub-Lidar, and SLAMM-Lidar). The comparisons show that the conservation priorities are significantly different with different combinations of coastal impact models and elevation dataset inputs. The research suggests that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because this model-dataset combination could improve conservation outcomes under SLR. Less accurate coastal impact models, including ones created using coarser Digital Elevation Model (DEM) data can still be useful when better data and models are not available or feasible, but results need to be appropriately assessed and communicated. A future research priority is to investigate how

  19. Modelling population distribution using remote sensing imagery and location-based data

    Science.gov (United States)

    Song, J.; Prishchepov, A. V.

    2017-12-01

    Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models

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

    Science.gov (United States)

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

    2013-01-01

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

  1. Cartilage contact pressure elevations in dysplastic hips: a chronic overload model

    Directory of Open Access Journals (Sweden)

    Grosland Nicole M

    2006-10-01

    Full Text Available Abstract Background Developmental dysplasia of the hip (DDH is a condition in which bone growth irregularities subject articular cartilage to higher mechanical stresses, increase susceptibility to subluxation, and elevate the risk of early osteoarthritis. Study objectives were to calculate three-dimensional cartilage contact stresses and to examine increases of accumulated pressure exposure over a gait cycle that may initiate the osteoarthritic process in the human hip, in the absence of trauma or surgical intervention. Methods Patient-specific, non-linear, contact finite element models, constructed from computed tomography arthrograms using a custom-built meshing program, were subjected to normal gait cycle loads. Results Peak contact pressures for dysplastic and asymptomatic hips ranged from 3.56 – 9.88 MPa. Spatially discriminatory cumulative contact pressures ranged from 2.45 – 6.62 MPa per gait cycle. Chronic over-pressure doses, for 2 million cycles per year over 20 years, ranged from 0.463 – 5.85 MPa-years using a 2-MPa damage threshold. Conclusion There were significant differences between the normal control and the asymptomatic hips, and a trend towards significance between the asymptomatic and symptomatic hips of patients afflicted with developmental dysplasia of the hip. The magnitudes of peak cumulative contact pressure differed between apposed articular surfaces. Bone irregularities caused localized pressure elevations and an upward trend between chronic over-pressure exposure and increasing Severin classification.

  2. Potential for monitoring soil erosion features and soil erosion modeling components from remotely sensed data

    Science.gov (United States)

    Langran, K. J.

    1983-01-01

    Accurate estimates of soil erosion and its effects on soil productivity are essential in agricultural decision making and planning from the field scale to the national level. Erosion models have been primarily developed for designing erosion control systems, predicting sediment yield for reservoir design, predicting sediment transport, and simulating water quality. New models proposed are more comprehensive in that the necessary components (hydrology, erosion-sedimentation, nutrient cycling, tillage, etc.) are linked in a model appropriate for studying the erosion-productivity problem. Recent developments in remote sensing systems, such as Landsat Thematic Mapper, Shuttle Imaging Radar (SIR-B), etc., can contribute significantly to the future development and operational use of these models.

  3. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images.

    Science.gov (United States)

    Su, Yuan-Fong; Liou, Jun-Jih; Hou, Ju-Chen; Hung, Wei-Chun; Hsu, Shu-Mei; Lien, Yi-Ting; Su, Ming-Daw; Cheng, Ke-Sheng; Wang, Yeng-Fung

    2008-10-10

    his study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to SPOT multispectral images for estimation of the sea surface reflectance. Two models, univariate and multivariate, for water quality estimation using the sea surface reflectance derived from SPOT images were established. The multivariate model takes into consideration the wavelength-dependent combined effect of individual seawater constituents on the sea surface reflectance and is superior over the univariate model. Finally, quantitative coastal water quality mapping was accomplished by substituting the pixel-specific spectral reflectance into the multivariate water quality estimation model.

  4. Elevated Intracranial Pressure and Cerebral Edema following Permanent MCA Occlusion in an Ovine Model

    Science.gov (United States)

    Wells, Adam J.; Vink, Robert; Helps, Stephen C.; Knox, Steven J.; Blumbergs, Peter C.; Turner, Renée J.

    2015-01-01

    Introduction Malignant middle cerebral artery (MCA) stroke has a disproportionately high mortality due to the rapid development of refractory space-occupying cerebral edema. Animal models are essential in developing successful anti-edema therapies; however to date poor clinical translation has been associated with the predominately used rodent models. As such, large animal gyrencephalic models of stroke are urgently needed. The aim of the study was to characterize the intracranial pressure (ICP) response to MCA occlusion in our recently developed ovine stroke model. Materials and Methods 30 adult female Merino sheep (n = 8–12/gp) were randomized to sham surgery, temporary or permanent proximal MCA occlusion. ICP and brain tissue oxygen were monitored for 24 hours under general anesthesia. MRI, infarct volume with triphenyltetrazolium chloride (TTC) staining and histology were performed. Results No increase in ICP, radiological evidence of ischemia within the MCA territory but without space-occupying edema, and TTC infarct volumes of 7.9+/-5.1% were seen with temporary MCAO. Permanent MCAO resulted in significantly elevated ICP, accompanied by 30% mortality, radiological evidence of space-occupying cerebral edema and TTC infarct volumes of 27.4+/-6.4%. Conclusions Permanent proximal MCAO in the sheep results in space-occupying cerebral edema, raised ICP and mortality similar to human malignant MCA stroke. This animal model may prove useful for pre-clinical testing of anti-edema therapies that have shown promise in rodent studies. PMID:26121036

  5. Elevated Intracranial Pressure and Cerebral Edema following Permanent MCA Occlusion in an Ovine Model.

    Science.gov (United States)

    Wells, Adam J; Vink, Robert; Helps, Stephen C; Knox, Steven J; Blumbergs, Peter C; Turner, Renée J

    2015-01-01

    Malignant middle cerebral artery (MCA) stroke has a disproportionately high mortality due to the rapid development of refractory space-occupying cerebral edema. Animal models are essential in developing successful anti-edema therapies; however to date poor clinical translation has been associated with the predominately used rodent models. As such, large animal gyrencephalic models of stroke are urgently needed. The aim of the study was to characterize the intracranial pressure (ICP) response to MCA occlusion in our recently developed ovine stroke model. 30 adult female Merino sheep (n = 8-12/gp) were randomized to sham surgery, temporary or permanent proximal MCA occlusion. ICP and brain tissue oxygen were monitored for 24 hours under general anesthesia. MRI, infarct volume with triphenyltetrazolium chloride (TTC) staining and histology were performed. No increase in ICP, radiological evidence of ischemia within the MCA territory but without space-occupying edema, and TTC infarct volumes of 7.9+/-5.1% were seen with temporary MCAO. Permanent MCAO resulted in significantly elevated ICP, accompanied by 30% mortality, radiological evidence of space-occupying cerebral edema and TTC infarct volumes of 27.4+/-6.4%. Permanent proximal MCAO in the sheep results in space-occupying cerebral edema, raised ICP and mortality similar to human malignant MCA stroke. This animal model may prove useful for pre-clinical testing of anti-edema therapies that have shown promise in rodent studies.

  6. Using noble gas tracers to constrain a groundwater flow model with recharge elevations: A novel approach for mountainous terrain

    Science.gov (United States)

    Doyle, Jessica M.; Gleeson, Tom; Manning, Andrew H.; Mayer, K. Ulrich

    2015-01-01

    Environmental tracers provide information on groundwater age, recharge conditions, and flow processes which can be helpful for evaluating groundwater sustainability and vulnerability. Dissolved noble gas data have proven particularly useful in mountainous terrain because they can be used to determine recharge elevation. However, tracer-derived recharge elevations have not been utilized as calibration targets for numerical groundwater flow models. Herein, we constrain and calibrate a regional groundwater flow model with noble-gas-derived recharge elevations for the first time. Tritium and noble gas tracer results improved the site conceptual model by identifying a previously uncertain contribution of mountain block recharge from the Coast Mountains to an alluvial coastal aquifer in humid southwestern British Columbia. The revised conceptual model was integrated into a three-dimensional numerical groundwater flow model and calibrated to hydraulic head data in addition to recharge elevations estimated from noble gas recharge temperatures. Recharge elevations proved to be imperative for constraining hydraulic conductivity, recharge location, and bedrock geometry, and thus minimizing model nonuniqueness. Results indicate that 45% of recharge to the aquifer is mountain block recharge. A similar match between measured and modeled heads was achieved in a second numerical model that excludes the mountain block (no mountain block recharge), demonstrating that hydraulic head data alone are incapable of quantifying mountain block recharge. This result has significant implications for understanding and managing source water protection in recharge areas, potential effects of climate change, the overall water budget, and ultimately ensuring groundwater sustainability.

  7. Local and Remote Postconditioning Decrease Intestinal Injury in a Rabbit Ischemia/Reperfusion Model

    Directory of Open Access Journals (Sweden)

    Mu Yang

    2016-01-01

    Full Text Available Intestinal ischemia/reperfusion (I/R injury is a significant problem that is associated with high morbidity and mortality in critical settings. This injury may be ameliorated using postconditioning protocol. In our study, we created a rabbit intestinal I/R injury model to analyze the effects of local ischemia postconditioning (LIPo and remote ischemia postconditioning (RIPo on intestinal I/R injury. We concluded that LIPo affords protection in intestinal I/R injury in a comparable fashion with RIPo by decreasing oxidative stress, neutrophil activation, and apoptosis.

  8. Model studies of laser absorption computed tomography for remote air pollution measurement

    Science.gov (United States)

    Wolfe, D. C., Jr.; Byer, R. L.

    1982-01-01

    Model studies of the potential of laser absorption-computed tomography are presented which demonstrate the possibility of sensitive remote atmospheric pollutant measurements, over kilometer-sized areas, with two-dimensional resolution, at modest laser source powers. An analysis of this tomographic reconstruction process as a function of measurement SNR, laser power, range, and system geometry, shows that the system is able to yield two-dimensional maps of pollutant concentrations at ranges and resolutions superior to those attainable with existing, direct-detection laser radars.

  9. A Nonlinear Multiparameters Temperature Error Modeling and Compensation of POS Applied in Airborne Remote Sensing System

    Directory of Open Access Journals (Sweden)

    Jianli Li

    2014-01-01

    Full Text Available The position and orientation system (POS is a key equipment for airborne remote sensing systems, which provides high-precision position, velocity, and attitude information for various imaging payloads. Temperature error is the main source that affects the precision of POS. Traditional temperature error model is single temperature parameter linear function, which is not sufficient for the higher accuracy requirement of POS. The traditional compensation method based on neural network faces great problem in the repeatability error under different temperature conditions. In order to improve the precision and generalization ability of the temperature error compensation for POS, a nonlinear multiparameters temperature error modeling and compensation method based on Bayesian regularization neural network was proposed. The temperature error of POS was analyzed and a nonlinear multiparameters model was established. Bayesian regularization method was used as the evaluation criterion, which further optimized the coefficients of the temperature error. The experimental results show that the proposed method can improve temperature environmental adaptability and precision. The developed POS had been successfully applied in airborne TSMFTIS remote sensing system for the first time, which improved the accuracy of the reconstructed spectrum by 47.99%.

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

    Science.gov (United States)

    Friedrich, J.; Karslioglu, M. O.

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

  11. Use of remote sensing techniques to determine the effects of grazing on vegetation cover and dune elevation at assateague island national seashore: Impact of horses

    Science.gov (United States)

    De Stoppelaire, G. H.; Gillespie, T.W.; Brock, J.C.; Tobin, G.A.

    2004-01-01

    The effects of grazing by feral horses on vegetation and dune topography at Assateague Island National Seashore were investigated using color-infrared imagery, lidar surveys, and field measurements. Five pairs of fenced and unfenced plots (300 m2) established in 1993 on sand flats and small dunes with similar elevation, topography, and vegetation cover were used for this study. Color-infrared imagery from 1998 and field measurements from 2001 indicated that there was a significant difference in vegetation cover between the fenced and unfenced plot-pairs over the study period. Fenced plots contained a higher percentage of vegetation cover that was dominated by American beachgrass (Ammophila breviligulata). Lidar surveys from 1997, 1999, and 2000 showed that there were significant differences in elevation and topography between fenced and unfenced plot-pairs. Fenced plots were, on average, 0.63 m higher than unfenced plots, whereas unfenced plots had generally decreased in elevation after establishment in 1993. Results demonstrate that feral horse grazing has had a significant impact on dune formation and has contributed to the erosion of dunes at Assateague Island. The findings suggest that unless the size of the feral horse population is reduced, grazing will continue to foster unnaturally high rates of dune erosion into the future. In order to maintain the natural processes that historically occurred on barrier islands, much larger fenced exclosures would be required to prevent horse grazing. ?? 2004 Springer Science+Business Media, Inc.

  12. Detection of mesoscale zones of atmospheric instabilities using remote sensing and weather forecasting model data

    Science.gov (United States)

    Winnicki, I.; Jasinski, J.; Kroszczynski, K.; Pietrek, S.

    2009-04-01

    The paper presents elements of research conducted in the Faculty of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland, concerning application of mesoscale models and remote sensing data to determining meteorological conditions of aircraft flight directly related with atmospheric instabilities. The quality of meteorological support of aviation depends on prompt and effective forecasting of weather conditions changes. The paper presents a computer module for detecting and monitoring zones of cloud cover, precipitation and turbulence along the aircraft flight route. It consists of programs and scripts for managing, processing and visualizing meteorological and remote sensing databases. The application was developed in Matlab® for Windows®. The module uses products of COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere developed by the US Naval Research Laboratory, satellite images acquisition system from the MSG-2 (Meteosat Second Generation) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and meteorological radars data acquired from the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland. The satellite images acquisition system and the COAMPS model are run operationally in the Faculty of Civil Engineering and Geodesy. The mesoscale model is run on an IA64 Feniks multiprocessor 64-bit computer cluster. The basic task of the module is to enable a complex analysis of data sets of miscellaneous information structure and to verify COAMPS results using satellite and radar data. The research is conducted using uniform cartographic projection of all elements of the database. Satellite and radar images are transformed into the Lambert Conformal projection of COAMPS. This facilitates simultaneous interpretation and supports decision making process for safe execution of flights. Forecasts are based on horizontal

  13. LEBANESE SOIL AND TERRAIN UNITES DELINEATION BASED ON DIGITAL ELEVATION MODELS

    Directory of Open Access Journals (Sweden)

    Jean A. Doumit

    2015-01-01

    Full Text Available The Soil and Terrain digital database (SOTER stores attribute data on landform and soils, the United Nations Environmental Program (UNEP create a soil and terrain digital database with a global coverage at a spatial resolution of one kilometer approximately. For a little country as Lebanon such data with a very low resolution cannot be useful, Until recently, only manual methods were used to delineate SOTER (SOil and TERrain Digital Database Units [21]. Theaimofourstudyisto apply aquantitativemethodtoderive terrain classes that match the physiography SOTER of the Lebanese territory at regional scale. According to SRTMdigital elevation model todefinetheSOTERTerrainUnit: hypsometry, slope, reliefintensity and stream density. Several GIS techniques were employed to translate the SOTER mapping concept. The four features are combined and vectorized to achieve the delineation of the SOTER Terrain unit’s map at a spatial precision of 90 meters.

  14. 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.

  15. 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.

  16. Model Simulation of Urban Evapotranspiration Rates Given Spatial Changes in Land Cover and Elevation

    Science.gov (United States)

    Yang, Y.; Endreny, T. A.

    2009-05-01

    Urban heat islands (UHI) emerge due to changes in albedo and imperviousness as compared with surrounding countryside, and UHI mitigation plans have focused on increasing urban tree cover. Trees can cool urban areas by direct shading and indirect evapotranspiration. Our goal is to create spatially distributed estimates of tree evapotranspiration during the growing season, to use in human thermal comfort models and other UHI simulations. We are modifying tree anatomy and growth functions in the USDA Forest Service Urban Forest Effects (UFORE) model. Modification represents the spatial variation of soil moisture and canopy radiation, which regulate evapotranspiration. Surface elevation derived topographic indices and land cover maps, including NLCD and aerial photographs, are used to adjust weather station estimates of radiation and soil moisture. Tree species and initial anatomy were selected from data gathered by the USDA Forest Service from plots in Syracuse, New York. Model estimates of evapotranspiration were generated for 30m by 30m pixels, and represented soil water and radiation constraints by modifying parameters in the Penman Monteith equations. Future work involves incorporating land cover and topographic data uncertainty into soil moisture and radiation constraints, which would be represented through Monte Carlo simulations. Applications of this research will be considered for the UFORE model in managing urban forest tree plantings to mitigate UHI impacts.

  17. Multiscale parameterization of LIDAR elevations for reducing complexity in hydraulic models of coastal urban areas

    Science.gov (United States)

    Cheung, Sweungwon; Slatton, K. Clint; Cho, Hyun-Chong; Dean, Robert G.

    2011-01-01

    Airborne light detection and ranging (LIDAR) technology now makes it possible to sample the Earth's surface with point spacings well below 1 m. It is, however, time consuming, costly, and technically challenging to directly use very high resolution LIDAR data for hydraulic modeling because of the computational requirements associated with solving fluid dynamics equations over complex boundary conditions in large data sets. For high relief terrain and urban areas, using coarse digital elevation models (DEMs) can cause significant degradation in hydraulic modeling, particularly when artificial obstructions, such as buildings, mask spatial correlations between terrain points. In this paper we present a strategy to reduce the computational complexity in the estimation of surface water discharge through a decomposition of the DEM data, wherein features have different characteristic spatial frequencies. Though the optimal DEM scale for a particular application will ultimately be decided by the user's tolerance for error, we present guidelines to choose a proper scale by balancing computer memory usage and accuracy. We also suggest a method to parameterize man-made structures, such as buildings in hydraulic modeling, to efficiently and accurately account for their effects on surface water discharge.

  18. 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.

  19. Characterizing the Surface Connectivity of Depressional Wetlands: Linking Remote Sensing and Hydrologic Modeling Approaches

    Science.gov (United States)

    Christensen, J.; Evenson, G. R.; Vanderhoof, M.; Wu, Q.; Golden, H. E.; Lane, C.

    2017-12-01

    Surface connectivity of wetlands in the 700,000 km2 Prairie Pothole Region of North America (PPR) can occur through fill-spill and fill-merge mechanisms, with some wetlands eventually spilling into stream/river systems. These wetland-to-wetland and wetland-to-stream connections vary both spatially and temporally in PPR watersheds and are important to understanding hydrologic and biogeochemical processes in the landscape. To explore how to best characterize spatial and temporal variability in aquatic connectivity, we compared three approaches, 1) hydrological modeling alone, 2) remotely-sensed data alone, and 3) integrating remotely-sensed data into a hydrological model. These approaches were tested in the Pipestem Creek Watershed, North Dakota across a drought to deluge cycle (1990-2011). A Soil and Water Assessment Tool (SWAT) model was modified to include the water storage capacity of individual non-floodplain wetlands identified in the National Wetland Inventory (NWI) dataset. The SWAT-NWI model simulated the water balance and storage of each wetland and the temporal variability of their hydrologic connections between wetlands during the 21-year study period. However, SWAT-NWI only accounted for fill-spill, and did not allow for the expansion and merging of wetlands situated within larger depressions. Alternatively, we assessed the occurrence of fill-merge mechanisms using inundation maps derived from Landsat images on 19 cloud-free days during the 21 years. We found fill-merge mechanisms to be prevalent across the Pipestem watershed during times of deluge. The SWAT-NWI model was then modified to use LiDAR-derived depressions that account for the potential maximum depression extent, including the merging of smaller wetlands. The inundation maps were used to evaluate the ability of the SWAT-depression model to simulate fill-merge dynamics in addition to fill-spill dynamics throughout the study watershed. Ultimately, using remote sensing to inform and validate

  20. Structural modeling of the Zagros fold-and-thrust belt (Iraq) combining field work and remote sensing techniques

    Science.gov (United States)

    Reif, D.; Grasemann, B.; Faber, R.; Lockhart, D.

    2009-04-01

    contacts) from digital elevation models. The minimum vegetation cover in the investigated area allows an accurate picking of geological planes from the digital elevation model, which has been draped with LANDSAT and ASTER satellite images in order to enhance the contrast of lithological contacts. Geological planes of finite extent are interpolated in the Fault Trace module by virtual planes, which can be translated and rotated in any spatial direction. Comparison of measured data from the field with interpolated spatial orientations from the remote sensing data demonstrate that the calculated dip and strike values can be reproduced within the measurements error of a geological field compass.