WorldWideScience

Sample records for arid terrains tanami

  1. Mesoscale aspects of storms producing floods over regions of arid mountainous terrain

    Science.gov (United States)

    Houze, R.; Romatschke, U.; Rasmussen, K. L.

    2011-12-01

    We have used the TRMM satellite's Precipitation Radar (PR) to develop a climatology of extreme convection in the regions of the Andes and Himalayas. This work shows that intense convection often occurs in arid regions but does not usually produce large amounts of rain. Large quantities of rain falling in mountainous regions is associated with the convective systems that have the greatest horizontal scales. When such wide systems occur over arid mountains, they can produce lethal floods. The Pakistan flood of 2010 is a case in point. Wide convective systems with large stratiform components became situated over the arid mountains of that region, with the result of the Indus River overflowed with disastrous consequences over a huge area. The potential of heavy rain in the region could have been inferred from the forecast synoptic-scale circulation, which indicated the occurrence of a great buildup of moisture in the region. Although the synoptic conditions were well forecast, that information alone was insufficient for predicting the flood conditions. It would have been necessary to anticipate also the mesoscale structure of the storms. Our TRMM satellite climatology of rainstorm structures in this region indicated that the mesoscale convective rainstorms responsible for the floods were of a type that does not normally occur in this region. Rather, this type of storm usually occurs and produces copious monsoon rain far to the east, over the mountains and wetlands of northeastern India and Bangladesh. In this event, catastrophic runoff and flooding resulted as these rainstorms occurred far to the west of where they usually occur, over an arid and mountainous region unaccustomed to such storms. This study indicates that taking into account the mesoscale structures of the cloud systems as well as the synoptic conditions in which they are embedded is essential for forecasting floods in this region of complex terrain.

  2. Lode-gold mineralization in the Tanami region, northern Australia

    Science.gov (United States)

    Huston, David L.; Vandenberg, Leon; Wygralak, Andrew S.; Mernagh, Terrence P.; Bagas, Leon; Crispe, Andrew; Lambeck, Alexis; Cross, Andrew; Fraser, Geoff; Williams, Nick; Worden, Kurt; Meixner, Tony; Goleby, Bruce; Jones, Leonie; Lyons, Pat; Maidment, David

    2007-01-01

    The Tanami region of northern Australia has emerged over the last two decades as the largest gold-producing region in the Northern Territory. Gold is hosted by epigenetic quartz veins in sedimentary and mafic rocks, and by sulfide-rich replacement zones within iron formation. Although limited, geochronological data suggest that most mineralization occurred at about 1,805-1,790 Ma, during a period of extensive granite intrusion, although structural relationships suggest that some deposits predate this period. There are three main goldfields in the Tanami region: the Dead Bullock Soak goldfield, which hosts the world-class Callie deposit; The Granites goldfield; and the Tanami goldfield. In the Dead Bullock Soak goldfield, deposits are hosted by carbonaceous siltstone and iron formation where a late (D5) structural corridor intersects an early F1 anticlinorium. In The Granites goldfield, deposits are hosted by highly sheared iron formation and are interpreted to predate D5. The Tanami goldfield consists of a large number of small, mostly basalt-hosted deposits that probably formed at a high structural level during D5. The D5 structures that host most deposits formed in a convergent structural regime with σ 1 oriented between E-W and ENE-WSW. Structures active during D5 include NE-trending oblique thrust (dextral) faults and ESE-trending (sinistral) faults that curve into N- to NNW-trending reverse faults localized in supracrustal belts between and around granite complexes. Granite intrusions also locally perturbed the stress field, possibly localizing structures and deposits. Forward modeling and preliminary interpretations of reflection seismic data indicate that all faults extend into the mid-crust. In areas characterized by the N- to NW-trending faults, orebodies also tend to be N- to NW-trending, localized in dilational jogs or in fractured, competent rock units. In areas characterized by ESE-trending faults, the orebodies and veins tend to strike broadly east

  3. Radio and Gamma-ray Properties of Extragalactic Jets from the TANAMI Sample

    CERN Document Server

    Böck, M; Müller, C; Tosti, G; Ojha, R; Wilms, J; Bastieri, D; Burnett, T; Carpenter, B; Cavazzuti, E; Dutka, M; Blanchard, J; Edwards, P G; Hase, H; Horiuchi, S; Jauncey, D L; Krauss, F; Lister, M L; Lovell, J E J; Lott, B; Murphy, D W; Phillips, C; Plötz, C; Pursimo, T; Quick, J; Ros, E; Taylor, G; Thompson, D J; Tingay, S J; Tzioumis, A; Zensus, J A

    2016-01-01

    Using high-resolution radio imaging with VLBI techniques, the TANAMI program has been observing the parsec-scale radio jets of southern (declination south of -30{\\deg}) gamma-ray bright AGN simultaneously with Fermi/LAT monitoring of their gamma-ray emission. We present the radio and gamma-ray properties of the TANAMI sources based on one year of contemporaneous TANAMI and Fermi/LAT data. A large fraction (72%) of the TANAMI sample can be associated with bright gamma-ray sources for this time range. Association rates differ for different optical classes with all BL Lacs, 76% of quasars and just 17% of galaxies detected by the LAT. Upper limits were established on the gamma-ray flux from TANAMI sources not detected by LAT. This analysis led to the identification of three new Fermi sources whose detection was later confirmed. The gamma-ray and radio luminosities are related by $L_\\gamma \\propto L_r^{0.89+-0.04}$. The brightness temperatures of the radio cores increase with the average gamma-ray luminosity, and ...

  4. Southern-Hemisphere AGN Monitoring on (Sub-)Parsec Scales: The TANAMI Program

    CERN Document Server

    Müller, Cornelia; Wilms, J; Kadler, M; Ojha, R; Blanchard, J; Dutka, M; Ros, E

    2012-01-01

    The Very Long Baseline Interferometry (VLBI) monitoring program TANAMI provides bi-monthly, dualfrequency (8GHz and 22GHz) observations of extragalactic jets with milliarcsecond resolution south of -30 deg declination using the Australian Long Baseline Array (LBA) and additional radio telescopes in Antarctica, Chile, New Zealand and South Africa. Supporting programs provide multiwavelength coverage of the Fermi/LAT sources of the TANAMI sample, in order to construct simultaneous broadband spectral energy distributions (SEDs), as well as rapid follow-ups of high energy flares. The main purpose of this project is to study the radio-gamma-ray connection seen in the jets of active galactic nuclei (AGN) via simultaneous monitoring of their VLBI structure and broadband emission in order to distinguish between different proposed emission models. Here we give a brief description of the TANAMI program and will then focus on its current status: (1) We present some results on the first simultaneous dual-frequency images...

  5. Groundwater potentiality mapping of hard-rock terrain in arid regions using geospatial modelling: example from Wadi Feiran basin, South Sinai, Egypt

    Science.gov (United States)

    Arnous, Mohamed O.

    2016-09-01

    Identifying a good site for groundwater exploitation in hard-rock terrains is a challenging task. In Sinai, Egypt, groundwater is the only source of water for local inhabitants. Interpretation of satellite data for delineation of lithological units and weathered zones, and for mapping of lineament density and their trends, provides a valuable aid for the location of groundwater promising areas. Complex deformational histories of the wide range of lithological formations add to the difficulty. Groundwater prospect mapping is a systematic approach that considers the major controlling factors which influence the aquifer and quality of groundwater. The presented study aims to delineate, identify, model and map groundwater potential zones in arid South Sinai using remote sensing data and a geographic information system (GIS) to prepare various hydromorphogeological thematic maps such as maps of slope, drainage density, lithology, landforms, structural lineaments, rainfall intensity and plan curvature. The controlling-factor thematic maps are each allocated a fixed score and weight, computed by using a linear equation approach. Furthermore, each weighted thematic map is statistically computed to yield a groundwater potential zone map of the study area. The groundwater potential zones thus obtained were divided into five categories (very poor, poor, moderate, good and very good) and were validated using the relation between the zone and the spatial distribution of productive wells and of previous geophysical investigations from a literature review. The results show the groundwater potential zones in the study area, and create awareness for better planning and management of groundwater resources.

  6. TANAMI Blazars in the IceCube PeV Neutrino Fields

    CERN Document Server

    Krauß, F; Mannheim, K; Schulz, R; Trüstedt, J; Wilms, J; Ojha, R; Ros, E; Anton, G; Baumgartner, W; Beuchert, T; Blanchard, J; Bürkel, C; Carpenter, B; Eberl, T; Edwards, P G; Eisenacher, D; Elsässer, D; Fehn, K; Fritsch, U; Gehrels, N; Gräfe, C; Großberger, C; Hase, H; Horiuchi, S; James, C; Kappes, A; Katz, U; Kreikenbohm, A; Kreykenbohm, I; Langejahn, M; Leiter, K; Litzinger, E; Lovell, J E J; Müller, C; Phillips, C; Plötz, C; Quick, J; Steinbring, T; Stevens, J; Thompson, D J; Tzioumis, A K

    2014-01-01

    The IceCube Collaboration has announced the discovery of a neutrino flux in excess of the atmospheric background. Due to the steeply falling atmospheric background spectrum, events at PeV energies are most likely of extraterrestrial origin. We present the multiwavelength properties of the six radio brightest blazars positionally coincident with these events using contemporaneous data of the TANAMI blazar sample, including high-resolution images and spectral energy distributions. Assuming the X-ray to {\\gamma}-ray emission originates in the photoproduction of pions by accelerated protons, the integrated predicted neutrino luminosity of these sources is large enough to explain the two detected PeV events.

  7. Recognition of shallow karst water resources and cave potentials using thermal infrared image and terrain characteristics in semi-arid regions of Iran

    Science.gov (United States)

    Jalali, Nader; Saghafian, Bahram; Imanov, Farda; Museyyibov, Museyyib

    2009-12-01

    Shallow karst water resources and caves may influence land surface temperatures due to cold transfer property of rocks and evaporation from buried karst. The objective of this research was to develop a method for recognition of karst areas based on evaluating the surface characteristics that manifest itself by low land surface temperature in the satellite images. Investigation of thermal ETM + image of the study region in Iran showed that parts of carbonate rocks that bear karst water are relatively cooler compared to areas with similar terrain conditions. Relational modeling provided useful information on spatial distribution of areas that have the potential to hold karst water resources and/or caves. Further inspection of ASTER images, along with geotechnical, geophysical and geological field surveys verified the approach. Significant correlation was found between electrical resistivity and thermal band values. The method may be used as a primary exploratory tool for shallow karst water explorations in similar areas.

  8. TANAMI monitoring of Centaurus A: The complex dynamics within the inner parsec of an extragalactic jet

    CERN Document Server

    Müller, C; Ojha, R; Perucho, M; Großberger, C; Ros, E; Wilms, J; Blanchard, J; Böck, M; Carpenter, B; Dutka, M; Edwards, P G; Hase, H; Horiuchi, S; Kreikenbohm, A; Lovell, J E J; Markowitz, A; Phillips, C; Plötz, C; Pursimo, T; Quick, J; Rothschild, R; Schulz, R; Steinbring, T; Stevens, J; Trüstedt, J; Tzioumis, A K

    2014-01-01

    Centaurus A is the closest radio-loud active galaxy. Very Long Baseline Interferometry (VLBI) enables us to study the jet-counterjet system on milliarcsecond (mas) scales, providing essential information for jet emission and propagation models. We study the evolution of the central parsec jet structure of Cen A over 3.5 years. The proper motion analysis of individual jet components allows us to constrain jet formation and propagation and to test the proposed correlation of increased high energy flux with jet ejection events. Cen A is an exceptional laboratory for such detailed study as its proximity translates to unrivaled linear resolution, where 1 mas corresponds to 0.018 pc. The first 7 epochs of high-resolution TANAMI VLBI observations at 8 GHz of Cen A are presented, resolving the jet on (sub-)mas scales. They show a differential motion of the sub-pc scale jet with significantly higher component speeds further downstream where the jet becomes optically thin. We determined apparent component speeds within...

  9. Chaotic Terrain

    Science.gov (United States)

    2003-01-01

    [figure removed for brevity, see original site] Released 4 June 2003Chaotic terrain on Mars is thought to form when there is a sudden removal of subsurface water or ice, causing the surface material to slump and break into blocks. The chaotic terrain in this THEMIS visible image is confined to a crater just south of Elysium Planitia. It is common to see chaotic terrain in the vicinity of the catastrophic outflow channels on Mars, but the terrain in this image is on the opposite side of the planet from these channels, making it somewhat of an oddity.Image information: VIS instrument. Latitude -5.9, Longitude 108.1 East (251.9 West). 19 meter/pixel resolution.Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

  10. Terrain-Toolkit

    DEFF Research Database (Denmark)

    Wang, Qi; Kaul, Manohar; Long, Cheng

    2014-01-01

    , as will be shown, is used heavily for query processing in spatial databases; and (3) they do not provide the surface distance operator which is fundamental for many applications based on terrain data. Motivated by this, we developed a tool called Terrain-Toolkit for terrain data which accepts a comprehensive set...

  11. Arid Zone Hydrology

    Science.gov (United States)

    Arid zone hydrology encompasses a wide range of topics and hydro-meteorological and ecological characteristics. Although arid and semi-arid watersheds perform the same functions as those in humid environments, their hydrology and sediment transport characteristics cannot be readily predicted by inf...

  12. DIORAMA Earth Terrain Model

    Energy Technology Data Exchange (ETDEWEB)

    Werley, Kenneth Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-03-10

    When simulating near-surface nuclear detonations, the terrain of the Earth can have an effect on the observed outputs. The critical parameter is called the “height of burst”. In order to model the effect of terrain on the simulations we have incorporated data from multiple sources to give 9 km resolution data with global coverage.

  13. Terrain correlation suitability

    Science.gov (United States)

    Tang, Wang; McClintock, Robert L.

    1994-07-01

    Terrain-aided navigation (TAN), also referred to as terrain correlation, is a technique that has proven to be highly successful as a navigational aid for autonomous, unmanned guided missiles. Qualitatively speaking, the effectiveness of terrain correlation is a function of signal- to-noise (S/N) ratio. The signal is equivalent to terrain roughness, while the noise is the combination of reference map errors, radar altimeter errors, and INS altitude errors. However, it is not practical to use only a single parameter, such as S/N, to define the suitability of terrain correlation. This paper discusses the shortcomings of the conventional single-parameter approach to the terrain contour matching algorithm (TERCOM) used in cruise missile guidance systems scene selection. A more comprehensive technique is then presented that analyzes the terrain correlation suitability based on a Monte Carlo simulation technique. A figure-of-merit (FOM) for terrain correlation suitability, computed from sample statistics, is introduced and simulation results are provided to illustrate the feasibility of using a multi-parameter FOM technique. The preliminary results indicate that the proposed approach could provide a cost effective enhancement to the TAN-based mission planning process.

  14. Terrain Software Conversion.

    Science.gov (United States)

    1987-06-29

    iv~ 1. Background. In 1979, CASAA (now TRAC-FLVN) contracted BDM Corporation to produce a terrain data base for the Corps Battle Game (predecessor to...vie% and mod-fv terrain Gata used by several of TRAO-FLVN’s war - si-,ulatiors was comnatible only with Tektronix 4027 hardware. TAB-GT was -,e- tc

  15. TERRAIN, TRAVIS COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  16. TERRAIN, Pierce County, WA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. TERRAIN, Franklin COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. TERRAIN, KENDALL COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. TERRAIN, WORTH COUNTY, IOWA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. TERRAIN, BARNSTABLE COUNTY, MASSACHUSETTS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. TERRAIN, HOWARD COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  2. TERRAIN, BERKS COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN, MITCHELL COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, MITCHELL COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. TERRAIN, Mecklenburg County, NC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  6. TERRAIN, KITSAP COUNTY, WASHINGTON

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. TERRAIN, FRANKLIN COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, HANCOCK COUNTY, OH

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. TERRAIN, MIAMI COUNTY, OH

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, DELAWARE COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. TERRAIN, NOBLES COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. TERRAIN, PIERCE, COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. TERRAIN, SHERIDAN COUNTY, WY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, DAWSON COUNTY, NE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. TERRAIN, Northampton COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that were used to create...

  16. TERRAIN, TULSA COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  17. TERRAIN, POTTER COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that were used to create...

  18. TERRAIN, CALVERT COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. TERRAIN, Bennington County, Vermont

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. TERRAIN, LAWRENCE COUNTY, ARKANSAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. TERRAIN, WEBER COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. TERRAIN, LEON COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN, Norfolk County, Massachusetts

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, Hampden County, Massachusetts

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. TERRAIN, Walthall COUNTY, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. TERRAIN, CLALLAM COUNTY, WASHINGTON

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. TERRAIN, CEDAR COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, HARDIN COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  9. TERRAIN, DARKE COUNTY, OH

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, WRIGHT COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  11. TERRAIN, TROUSDALE COUNTY, TENNESSEE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. TERRAIN, WAYNE COUNTY, TENNESSEE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. TERRAIN, CECIL COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DspaceOgreTerrain 3D Terrain Visualization Tool

    Science.gov (United States)

    Myint, Steven; Jain, Abhinandan; Pomerantz, Marc I.

    2012-01-01

    DspaceOgreTerrain is an extension to the DspaceOgre 3D visualization tool that supports real-time visualization of various terrain types, including digital elevation maps, planets, and meshes. DspaceOgreTerrain supports creating 3D representations of terrains and placing them in a scene graph. The 3D representations allow for a continuous level of detail, GPU-based rendering, and overlaying graphics like wheel tracks and shadows. It supports reading data from the SimScape terrain- modeling library. DspaceOgreTerrain solves the problem of displaying the results of simulations that involve very large terrains. In the past, it has been used to visualize simulations of vehicle traverses on Lunar and Martian terrains. These terrains were made up of billions of vertices and would not have been renderable in real-time without using a continuous level of detail rendering technique.

  15. Submarine Salt Karst Terrains

    Directory of Open Access Journals (Sweden)

    Nico Augustin

    2016-06-01

    Full Text Available Karst terrains that develop in bodies of rock salt (taken as mainly of halite, NaCl are special not only for developing in one of the most soluble of all rocks, but also for developing in one of the weakest rocks. Salt is so weak that many surface-piercing salt diapirs extrude slow fountains of salt that that gravity spread downslope over deserts on land and over sea floors. Salt fountains in the deserts of Iran are usually so dry that they flow at only a few cm/yr but the few rain storms a decade so soak and weaken them that they surge at dm/day for a few days. We illustrate the only case where the rates at which different parts of one of the many tens of subaerial salt karst terrains in Iran flows downslope constrains the rates at which its subaerial salt karst terrains form. Normal seawater is only 10% saturated in NaCl. It should therefore be sufficiently aggressive to erode karst terrains into exposures of salt on the thousands of known submarine salt extrusions that have flowed or are still flowing over the floors of hundreds of submarine basins worldwide. However, we know of no attempt to constrain the processes that form submarine salt karst terrains on any of these of submarine salt extrusions. As on land, many potential submarine karst terrains are cloaked by clastic and pelagic sediments that are often hundreds of m thick. Nevertheless, detailed geophysical and bathymetric surveys have already mapped likely submarine salt karst terrains in at least the Gulf of Mexico, and the Red Sea. New images of these two areas are offered as clear evidence of submarine salt dissolution due to sinking or rising aggressive fluids. We suggest that repeated 3D surveys of distinctive features (± fixed seismic reflectors of such terrains could measure any downslope salt flow and thus offer an exceptional opportunity to constrain the rates at which submarine salt karst terrains develop. Such rates are of interest to all salt tectonicians and the many

  16. Sakhalin Island terrain intelligence

    Science.gov (United States)

    ,

    1943-01-01

    This folio of maps and explanatory tables outlines the principal terrain features of Sakhalin Island. Each map and table is devoted to a specialized set of problems; together they cover the subjects of terrain appreciation, climate, rivers, water supply, construction materials, suitability for roads, suitability for airfields, fuels and other mineral resources, and geology. In most cases, the map of the island is divided into two parts: N. of latitude 50° N., Russian Sakhalin, and south of latitude 50° N., Japanese Sakhalin or Karafuto. These maps and data were compiled by the United States Geological Survey during the period from March to September, 1943.

  17. Aridity and decomposition processes in complex landscapes

    Science.gov (United States)

    Ossola, Alessandro; Nyman, Petter

    2015-04-01

    Decomposition of organic matter is a key biogeochemical process contributing to nutrient cycles, carbon fluxes and soil development. The activity of decomposers depends on microclimate, with temperature and rainfall being major drivers. In complex terrain the fine-scale variation in microclimate (and hence water availability) as a result of slope orientation is caused by differences in incoming radiation and surface temperature. Aridity, measured as the long-term balance between net radiation and rainfall, is a metric that can be used to represent variations in water availability within the landscape. Since aridity metrics can be obtained at fine spatial scales, they could theoretically be used to investigate how decomposition processes vary across complex landscapes. In this study, four research sites were selected in tall open sclerophyll forest along a aridity gradient (Budyko dryness index ranging from 1.56 -2.22) where microclimate, litter moisture and soil moisture were monitored continuously for one year. Litter bags were packed to estimate decomposition rates (k) using leaves of a tree species not present in the study area (Eucalyptus globulus) in order to avoid home-field advantage effects. Litter mass loss was measured to assess the activity of macro-decomposers (6mm litter bag mesh size), meso-decomposers (1 mm mesh), microbes above-ground (0.2 mm mesh) and microbes below-ground (2 cm depth, 0.2 mm mesh). Four replicates for each set of bags were installed at each site and bags were collected at 1, 2, 4, 7 and 12 months since installation. We first tested whether differences in microclimate due to slope orientation have significant effects on decomposition processes. Then the dryness index was related to decomposition rates to evaluate if small-scale variation in decomposition can be predicted using readily available information on rainfall and radiation. Decomposition rates (k), calculated fitting single pool negative exponential models, generally

  18. Flow on noisy terrains

    DEFF Research Database (Denmark)

    Tsirogiannis, Konstantinos; Haverkort, Herman

    2011-01-01

    Computing watersheds on triangulated terrain models in a robust manner is a difficult task as it is sensitive to noise that appears in the elevation values of the input. This is amplified by the existence of many very small watersheds (corresponding to spurious minima) that obscure the overall hy...... to use a robust flow model together with exact arithmetic....

  19. Navigating Hypermasculine Terrains

    DEFF Research Database (Denmark)

    Henriksen, Ann-Karina Eske

    2015-01-01

    The study addresses how young women navigate urban terrains that are characterized by high levels of interpersonal aggression and crime. It is argued that young women apply a range of gendered tactics to establish safety and social mastery, and that these are framed by the limits and possibilitie...

  20. Good terrain geometry, cheap!

    Energy Technology Data Exchange (ETDEWEB)

    Duchaineau, M. [Los Alamos National Lab., NM (United States)]|[Lawrence Livermore National Lab., CA (United States); Wolinsky, M.; Sigeti, D.E. [Los Alamos National Lab., NM (United States)] [and others

    1997-04-01

    Real-time terrain rendering for interactive visualization remains a demanding task. We present a novel algorithm with several advantages over previous methods: our method is unusually stingy with polygons yet achieves real-time performance and is scalable to arbitrary regions and resolutions. The method provides a continuous terrain mesh of specified triangle count having provably minimum error in restricted but reasonably general classes of permissible meshes and error metrics. Our method provides an elegant solution to guaranteeing certain elusive types of consistency in scenes produced by multiple scene generators which share a common finest-resolution database but which otherwise operate entirely independently. This consistency is achieved by exploiting the freedom of choice of error metric allowed by the algorithm to provide, for example, multiple exact lines-of-sight in real-time. Our methods rely on an off-line pre-processing phase to construct a multi-scale data structure consisting of triangular terrain approximations enhanced ({open_quotes}thickened{close_quotes}) with world-space error information. In real time, this error data is efficiently transformed into screen-space where it is used to guide a greedy top-down triangle subdivision algorithm which produces the desired minimal error continuous terrain mesh. Our algorithm has been implemented and it operates at real-time rates.

  1. Terrain perception for robot navigation

    Science.gov (United States)

    Karlsen, Robert E.; Witus, Gary

    2007-04-01

    This paper presents a method to forecast terrain trafficability from visual appearance. During training, the system identifies a set of image chips (or exemplars) that span the range of terrain appearance. Each chip is assigned a vector tag of vehicle-terrain interaction characteristics that are obtained from simple performance models and on-board sensors, as the vehicle traverses the terrain. The system uses the exemplars to segment images into regions, based on visual similarity to the terrain patches observed during training, and assigns the appropriate vehicle-terrain interaction tag to them. This methodology will therefore allow the online forecasting of vehicle performance on upcoming terrain. Currently, the system uses a fuzzy c-means clustering algorithm for training. In this paper, we explore a number of different features for characterizing the visual appearance of the terrain and measure their effect on the prediction of vehicle performance.

  2. Urban Terrain Zone Characteristics

    Science.gov (United States)

    1987-09-01

    GROUP SUB-GROUP MOUT Urban Geography 13 13 MOBA Structures 15 06 06.07 Combat in Cities 19. ABSTRACT (Continue on reverie if necessary ind identify by...was introduced by the autbor in conjunction with the development end use of a computer-assisted game (ACABUG) for combat development studies...Activity (TRASANA) under the title of American Canadian Australian British Urban Game . (ACABUG) Urban Terrain Classification System. The claseification

  3. Waste biorefinery in arid/semi-arid regions.

    Science.gov (United States)

    Bastidas-Oyanedel, Juan-Rodrigo; Fang, Chuanji; Almardeai, Saleha; Javid, Usama; Yousuf, Ahasa; Schmidt, Jens Ejbye

    2016-09-01

    The utilization of waste biorefineries in arid/semi-arid regions is advisable due to the reduced sustainable resources in arid/semi-arid regions, e.g. fresh water and biomass. This review focuses on biomass residues available in arid/semi-arid regions, palm trees residues, seawater biomass based residues (coastal arid/semi-arid regions), and the organic fraction of municipal solid waste. The present review aims to describe and discuss the availability of these waste biomasses, their conversion to value chemicals by waste biorefinery processes. For the case of seawater biomass based residues it was reviewed and advise the use of seawater in the biorefinery processes, in order to decrease the use of fresh water. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Information measures for terrain visualization

    Science.gov (United States)

    Bonaventura, Xavier; Sima, Aleksandra A.; Feixas, Miquel; Buckley, Simon J.; Sbert, Mateu; Howell, John A.

    2017-02-01

    Many quantitative and qualitative studies in geoscience research are based on digital elevation models (DEMs) and 3D surfaces to aid understanding of natural and anthropogenically-influenced topography. As well as their quantitative uses, the visual representation of DEMs can add valuable information for identifying and interpreting topographic features. However, choice of viewpoints and rendering styles may not always be intuitive, especially when terrain data are augmented with digital image texture. In this paper, an information-theoretic framework for object understanding is applied to terrain visualization and terrain view selection. From a visibility channel between a set of viewpoints and the component polygons of a 3D terrain model, we obtain three polygonal information measures. These measures are used to visualize the information associated with each polygon of the terrain model. In order to enhance the perception of the terrain's shape, we explore the effect of combining the calculated information measures with the supplementary digital image texture. From polygonal information, we also introduce a method to select a set of representative views of the terrain model. Finally, we evaluate the behaviour of the proposed techniques using example datasets. A publicly available framework for both the visualization and the view selection of a terrain has been created in order to provide the possibility to analyse any terrain model.

  5. Eastern Siberia terrain intelligence

    Science.gov (United States)

    ,

    1942-01-01

    The following folio of terrain intelligence maps, charts and explanatory tables represent an attempt to bring together available data on natural physical conditions such as will affect military operations in Eastern Siberia. The area covered is the easternmost section of the U.S.S.R.; that is the area east of the Yenisei River. Each map and accompanying table is devoted· to a specialized set of problems; together they cover such subjects as geology, construction materials, mineral fuels, terrain, water supply, rivers and climate. The data is somewhat generalized due to the scale of treatment as well as to the scarcity of basic data. Each of the maps are rated as to reliability according to the reliability scale on the following page. Considerable of the data shown is of an interpretative nature, although precise data from literature was used wherever possible. The maps and tables were compiled  by a special group from the United States Geological Survey in cooperation with the Intelligence Branch of the Office, Chief of Engineers, War Department.

  6. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...

  7. Turbulence measurements over complex terrain

    Science.gov (United States)

    Skupniewicz, Charles E.; Kamada, Ray F.; Schacher, Gordon E.

    1989-07-01

    Horizontal turbulence measurements obtained from 22 wind sensors located on 9 towers in a mountainous coastal area are described and categorized by stability and terrain. Vector wind time series are high-pass filtered, and lateral and longitudinal wind speed variance is calculated for averaging times ranging from 15 s to 2 h. Parameterizations of the functional dependence of variance on averaging time are discussed, and a modification of Panofsky's (1988) uniform terrain technique applicable to complex terrain is presented. The parameterization is applied to the data and shown to be more realistic than a less complicated power law technique. The parameter values are shown to be different than the flat terrain cases of Kaimal et al. (1972), and are primarily a function of sensor location within the complex terrain. The parameters are also examined in terms of their dependence upon season, stability, marine boundary-layer height, and measurement height.

  8. Polygonal terrains on Mars

    Directory of Open Access Journals (Sweden)

    Pedro Pina

    2009-06-01

    Full Text Available The presence of water ice on Mars is well established. Some featureson the planet point to the occurrence of processes similar to those that take place in periglacial areas of Earth. One of the clues for this is the existence of small-scale polygonal terrains. In this paper, we present a methodology that aims at the automated identification of polygonal patterns on high-spatial resolution images of the surface of Mars. In the context of the research project TERPOLI, this step will be complemented with a full characterization, in both geometric and topological terms, of thenetworks detected. In this manner, we hope to collect data that will lead to a better understanding of the conditions of formation of the polygons, and of their temporal evolution; namely, we intend to identify different groups of polygons and to compare them with terrestrial examples.

  9. Turbulence in complex terrain

    Energy Technology Data Exchange (ETDEWEB)

    Mann, Jakob [Risoe National Lab., Wind Energy and Atmosheric Physics Dept., Roskilde (Denmark)

    1999-03-01

    The purpose of this work is to develop a model of the spectral velocity-tensor in neutral flow over complex terrain. The resulting equations are implemented in a computer code using the mean flow generated by a linear mean flow model as input. It estimates turbulence structure over hills (except on the lee side if recirculation is present) in the so-called outer layer and also models the changes in turbulence statistics in the vicinity roughness changes. The generated turbulence fields are suitable as input for dynamic load calculations on wind turbines and other tall structures and is under implementation in the collection of programs called WA{sup s}P Engineering. (au) EFP-97; EU-JOULE-3. 15 refs.

  10. On characterizing terrain visibility graphs

    Directory of Open Access Journals (Sweden)

    William Evans

    2015-06-01

    Full Text Available A terrain is an $x$-monotone polygonal line in the $xy$-plane. Two vertices of a terrain are mutually visible if and only if there is no terrain vertex on or above the open line segment connecting them. A graph whose vertices represent terrain vertices and whose edges represent mutually visible pairs of terrain vertices is called a terrain visibility graph. We would like to find properties that are both necessary and sufficient for a graph to be a terrain visibility graph; that is, we would like to characterize terrain visibility graphs.Abello et al. [Discrete and Computational Geometry, 14(3:331--358, 1995] showed that all terrain visibility graphs are “persistent”. They showed that the visibility information of a terrain point set implies some ordering requirements on the slopes of the lines connecting pairs of points in any realization, and as a step towards showing sufficiency, they proved that for any persistent graph $M$ there is a total order on the slopes of the (pseudo lines in a generalized configuration of points whose visibility graph is $M$.We give a much simpler proof of this result by establishing an orientation to every triple of vertices, reflecting some slope ordering requirements that are consistent with $M$ being the visibility graph, and prove that these requirements form a partial order. We give a faster algorithm to construct a total order on the slopes. Our approach attempts to clarify the implications of the graph theoretic properties on the ordering of the slopes, and may be interpreted as defining properties on an underlying oriented matroid that we show is a restricted type of $3$-signotope.

  11. Robot Would Climb Steep Terrain

    Science.gov (United States)

    Kennedy, Brett; Ganino, Anthony; Aghazarian, Hrand; Hogg, Robert; McHerny, Michael; Garrett, Michael

    2007-01-01

    This brief describes the steep terrain access robot (STAR) -- a walking robot that has been proposed for exploring steep terrain on remote planets. The STAR would be able to climb up or down on slopes as steep as vertical, and even beyond vertical to overhangs. Its system of walking mechanisms and controls would be to react forces and maintain stability. To enable the STAR to anchor itself in the terrain on steep slopes to maintain stability and react forces, it would be necessary to equip the tips of the walking legs with new ultrasonic/ sonic drill corers (USDCs) and to develop sensors and control algorithms to enable robust utilization of the USDCs.

  12. Martian terrain - 3D

    Science.gov (United States)

    1997-01-01

    This area of terrain near the Sagan Memorial Station was taken on Sol 3 by the Imager for Mars Pathfinder (IMP). 3D glasses are necessary to identify surface detail.The IMP is a stereo imaging system with color capability provided by 24 selectable filters -- twelve filters per 'eye.' It stands 1.8 meters above the Martian surface, and has a resolution of two millimeters at a range of two meters.Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.Click below to see the left and right views individually. [figure removed for brevity, see original site] Left [figure removed for brevity, see original site] Right

  13. TERRAIN, GADSDEN COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, STEWART COUNTY, TN, USA

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  15. TERRAIN, HOUSTON COUNTY, TN, USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. TERRAIN, MONROE COUNTY, TN, USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. TERRAIN, MADISON PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. TERRAIN, WILCOX COUNTY, ALABAMA USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. TERRAIN, LARUE COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. TERRAIN, CULLMAN COUNTY, ALABAMA USA

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  1. TERRAIN, LOGAN COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. Terrain Data, KENT COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN, OWEN COUNTY, KENTUCKY USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, NEW KENT COUNTY, USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  5. TERRAIN, TAYLOR COUNTY, KENTUCKY USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. TERRAIN, NATCHITOCHES PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  7. TERRAIN Submission for CHICKASAW, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, WAKULLA COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. TERRAIN, SUWANNEE COUNTY, FLORIDA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, LYON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. TERRAIN, MACOMB COUNTY, MI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. TERRAIN, CHILTON COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. TERRAIN, COLBERT COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, BOYLE COUNTY, KENTUCKY USA

    Data.gov (United States)

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  15. TERRAIN, Catahoula PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. TERRAIN, DEKALB COUNTY, TN, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. TERRAIN, VERNON PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. TERRAIN, EVANGELINE PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. TERRAIN, DALLAS COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. TERRAIN, SEBASTIAN COUNTY, AR, USA

    Data.gov (United States)

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  1. TERRAIN, ESCAMBIA COUNTY, ALABAMA USA

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  2. TERRAIN, FRANKLIN COUNTY, KENTUCKY USA

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  3. TERRAIN, CLARK COUNTY, Missouri USA

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  4. TERRAIN, RUSSELL COUNTY, KENTUCKY USA

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  5. TERRAIN, Sedgwick COUNTY, Kansas USA

    Data.gov (United States)

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  6. TERRAIN, GRAYSON COUNTY, KENTUCKY USA

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  7. TERRAIN, EVANGELINE PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, SANTA CRUZ COUNTY, AZ

    Data.gov (United States)

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  9. TERRAIN, CLARKE COUNTY, ALABAMA USA

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  10. TERRAIN, KENTON COUNTY, KENTUCKY USA

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  11. TERRAIN, CAMPBELL COUNTY, KENTUCKY USA

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  12. TERRAIN, MARENGO COUNTY, ALABAMA USA

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  13. TERRAIN, MARION COUNTY, KENTUCKY USA

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  14. TERRAIN, CLARK COUNTY, KENTUCKY USA

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  15. TERRAIN, PIKE COUNTY, ALABAMA USA

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  16. TERRAIN, Concordia PARISH, LA, USA

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  17. TERRAIN, Webster COUNTY, Missouri USA

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  18. TERRAIN, JESSAMINE COUNTY, KENTUCKY USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. Terrain Data, Westmoreland COUNTY, USA

    Data.gov (United States)

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  20. TERRAIN, LEVY COUNTY, FL, USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. TERRAIN, FRANKLIN COUNTY, ALABAMA USA

    Data.gov (United States)

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  2. TERRAIN, LIMESTONE COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN, NELSON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, LAWRENCE COUNTY, Ohio USA

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    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. TERRAIN, SUMTER COUNTY, ALABAMA USA

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  6. TERRAIN, MADISON COUNTY, KENTUCKY USA

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  7. TERRAIN, TALLAPOOSA COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, WALKER COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. TERRAIN, SCOTT COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, SHELBY COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. TERRAIN, PENDLETON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  12. TERRAIN, CLINTON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. TERRAIN, MERCER COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, CALDWELL COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. TERRAIN, POWELL COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. TERRAIN, HARRISON COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. TERRAIN, Robertson COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. TERRAIN, RUSSELL COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. Handling Massive and Dynamic Terrain Data

    DEFF Research Database (Denmark)

    Revsbæk, Morten

    analyzing flood risk and visibility, to producing nautical charts. Many algorithms and much commercial software have been developed to help analyze terrain models. However, significant algorithmic challenges arise from the increasing detail (and therefore size) of modern terrain models. Furthermore, terrain...... we develop so-called I/O-efficient algorithms for a set of well-known terrain analysis problems. First, we present an I/O-efficient algorithm for terrain model simplification. This algorithm can be used in connection with terrain analysis to reduce the topological complexity of a detailed terrain...

  20. Aridity and hominin environments

    Science.gov (United States)

    Blumenthal, Scott A.; Levin, Naomi E.; Brown, Francis H.; Brugal, Jean-Philip; Chritz, Kendra L.; Harris, John M.; Jehle, Glynis E.; Cerling, Thure E.

    2017-07-01

    Aridification is often considered a major driver of long-term ecological change and hominin evolution in eastern Africa during the Plio-Pleistocene; however, this hypothesis remains inadequately tested owing to difficulties in reconstructing terrestrial paleoclimate. We present a revised aridity index for quantifying water deficit (WD) in terrestrial environments using tooth enamel δ18O values, and use this approach to address paleoaridity over the past 4.4 million years in eastern Africa. We find no long-term trend in WD, consistent with other terrestrial climate indicators in the Omo-Turkana Basin, and no relationship between paleoaridity and herbivore paleodiet structure among fossil collections meeting the criteria for WD estimation. Thus, we suggest that changes in the abundance of C4 grass and grazing herbivores in eastern Africa during the Pliocene and Pleistocene may have been decoupled from aridity. As in modern African ecosystems, other factors, such as rainfall seasonality or ecological interactions among plants and mammals, may be important for understanding the evolution of C4 grass- and grazer-dominated biomes.

  1. Complete Scene Recovery and Terrain Classification in Textured Terrain Meshes

    Directory of Open Access Journals (Sweden)

    Kyhyun Um

    2012-08-01

    Full Text Available Terrain classification allows a mobile robot to create an annotated map of its local environment from the three-dimensional (3D and two-dimensional (2D datasets collected by its array of sensors, including a GPS receiver, gyroscope, video camera, and range sensor. However, parts of objects that are outside the measurement range of the range sensor will not be detected. To overcome this problem, this paper describes an edge estimation method for complete scene recovery and complete terrain reconstruction. Here, the Gibbs-Markov random field is used to segment the ground from 2D videos and 3D point clouds. Further, a masking method is proposed to classify buildings and trees in a terrain mesh.

  2. Processing Terrain Point Cloud Data

    KAUST Repository

    DeVore, Ronald

    2013-01-10

    Terrain point cloud data are typically acquired through some form of Light Detection And Ranging sensing. They form a rich resource that is important in a variety of applications including navigation, line of sight, and terrain visualization. Processing terrain data has not received the attention of other forms of surface reconstruction or of image processing. The goal of terrain data processing is to convert the point cloud into a succinct representation system that is amenable to the various application demands. The present paper presents a platform for terrain processing built on the following principles: (i) measuring distortion in the Hausdorff metric, which we argue is a good match for the application demands, (ii) a multiscale representation based on tree approximation using local polynomial fitting. The basic elements held in the nodes of the tree can be efficiently encoded, transmitted, visualized, and utilized for the various target applications. Several challenges emerge because of the variable resolution of the data, missing data, occlusions, and noise. Techniques for identifying and handling these challenges are developed. © 2013 Society for Industrial and Applied Mathematics.

  3. Flow Computations on Imprecise Terrains

    CERN Document Server

    Driemel, Anne; Löffler, Maarten

    2011-01-01

    We study the computation of the flow of water on imprecise terrains. We consider two approaches to modeling flow on a terrain: one where water flows across the surface of a polyhedral terrain in the direction of steepest descent, and one where water only flows along the edges of a predefined graph, for example a grid or a triangulation. In both cases each vertex has an imprecise elevation, given by an interval of possible values, while its (x,y)-coordinates are fixed. For the first model, we show that the problem of deciding whether one vertex may be contained in the watershed of another is NP-hard. In contrast, for the second model we give a simple O(n log n) time algorithm to compute the minimal and the maximal watershed of a vertex, where n is the number of edges of the graph. On a grid model, we can compute the same in O(n) time.

  4. Complex Terrain and Wind Lidars

    DEFF Research Database (Denmark)

    Bingöl, Ferhat

    This thesis includes the results of a PhD study about complex terrain and wind lidars. The study mostly focuses on hilly and forested areas. Lidars have been used in combination with cups, sonics and vanes, to reach the desired vertical measurement heights. Several experiments are performed...... in complex terrain sites and the measurements are compared with two different flow models; a linearised flow model LINCOM and specialised forest model SCADIS. In respect to the lidar performance in complex terrain, the results showed that horizontal wind speed errors measured by a conically scanning lidar....... The SCADIS model worked better than the LINCOM model at the forest edge but the model reported closer results to the measurements at upwind than the downwind and this should be noted as a limitation of the model. As the general conclusion of the study, it was stated that the lidars can be used in complex...

  5. Dispersion scenarios over complex terrain

    DEFF Research Database (Denmark)

    Thykier-Nielsen, S.; Mikkelsen, T.; Moreno, J.

    1993-01-01

    A presentation of preliminary results from a real-time simulation of full-scale dispersion experiments carried out over complex terrain in Northern Spain is given. Actual wind and turbulence measurements as observed during the experiments were analysed and used as input data for a series of simul......A presentation of preliminary results from a real-time simulation of full-scale dispersion experiments carried out over complex terrain in Northern Spain is given. Actual wind and turbulence measurements as observed during the experiments were analysed and used as input data for a series...... are suitable for subsequent comparison with observed mean dispersion data when they become available....

  6. Dispersion scenarios over complex terrain

    DEFF Research Database (Denmark)

    Thykier-Nielsen, S.; Mikkelsen, T.; Moreno, J.

    1993-01-01

    A presentation of preliminary results from a real-time simulation of full-scale dispersion experiments carried out over complex terrain in Northern Spain is given. Actual wind and turbulence measurements as observed during the experiments were analysed and used as input data for a series of simul......A presentation of preliminary results from a real-time simulation of full-scale dispersion experiments carried out over complex terrain in Northern Spain is given. Actual wind and turbulence measurements as observed during the experiments were analysed and used as input data for a series...

  7. Complex terrain and wind lidars

    Energy Technology Data Exchange (ETDEWEB)

    Bingoel, F.

    2009-08-15

    This thesis includes the results of a PhD study about complex terrain and wind lidars. The study mostly focuses on hilly and forested areas. Lidars have been used in combination with cups, sonics and vanes, to reach the desired vertical measurement heights. Several experiments are performed in complex terrain sites and the measurements are compared with two different flow models; a linearised flow model LINCOM and specialised forest model SCADIS. In respect to the lidar performance in complex terrain, the results showed that horizontal wind speed errors measured by a conically scanning lidar can be of the order of 3-4% in moderately-complex terrain and up to 10% in complex terrain. The findings were based on experiments involving collocated lidars and meteorological masts, together with flow calculations over the same terrains. The lidar performance was also simulated with the commercial software WAsP Engineering 2.0 and was well predicted except for some sectors where the terrain is particularly steep. Subsequently, two experiments were performed in forested areas; where the measurements are recorded at a location deep-in forest and at the forest edge. Both sites were modelled with flow models and the comparison of the measurement data with the flow model outputs showed that the mean wind speed calculated by LINCOM model was only reliable between 1 and 2 tree height (h) above canopy. The SCADIS model reported better correlation with the measurements in forest up to approx6h. At the forest edge, LINCOM model was used by allocating a slope half-in half out of the forest based on the suggestions of previous studies. The optimum slope angle was reported as 17 deg.. Thus, a suggestion was made to use WAsP Engineering 2.0 for forest edge modelling with known limitations and the applied method. The SCADIS model worked better than the LINCOM model at the forest edge but the model reported closer results to the measurements at upwind than the downwind and this should be

  8. An automated system for terrain database construction

    Science.gov (United States)

    Johnson, L. F.; Fretz, R. K.; Logan, T. L.; Bryant, N. A.

    1987-01-01

    An automated Terrain Database Preparation System (TDPS) for the construction and editing of terrain databases used in computerized wargaming simulation exercises has been developed. The TDPS system operates under the TAE executive, and it integrates VICAR/IBIS image processing and Geographic Information System software with CAD/CAM data capture and editing capabilities. The terrain database includes such features as roads, rivers, vegetation, and terrain roughness.

  9. Aridity modulates N availability in arid and semiarid Mediterranean grasslands.

    Directory of Open Access Journals (Sweden)

    Manuel Delgado-Baquerizo

    Full Text Available While much is known about the factors that control each component of the terrestrial nitrogen (N cycle, it is less clear how these factors affect total N availability, the sum of organic and inorganic forms potentially available to microorganisms and plants. This is particularly true for N-poor ecosystems such as drylands, which are highly sensitive to climate change and desertification processes that can lead to the loss of soil nutrients such as N. We evaluated how different climatic, abiotic, plant and nutrient related factors correlate with N availability in semiarid Stipa tenacissima grasslands along a broad aridity gradient from Spain to Tunisia. Aridity had the strongest relationship with N availability, suggesting the importance of abiotic controls on the N cycle in drylands. Aridity appeared to modulate the effects of pH, plant cover and organic C (OC on N availability. Our results suggest that N transformation rates, which are largely driven by variations in soil moisture, are not the direct drivers of N availability in the studied grasslands. Rather, the strong relationship between aridity and N availability could be driven by indirect effects that operate over long time scales (decades to millennia, including both biotic (e.g. plant cover and abiotic (e.g. soil OC and pH. If these factors are in fact more important than short-term effects of precipitation on N transformation rates, then we might expect to observe a lagged decrease in N availability in response to increasing aridity. Nevertheless, our results suggest that the increase in aridity predicted with ongoing climate change will reduce N availability in the Mediterranean basin, impacting plant nutrient uptake and net primary production in semiarid grasslands throughout this region.

  10. Spectra of Velocity components over Complex Terrain

    DEFF Research Database (Denmark)

    Panofsky, H. A.; Larko, D.; Lipschut, R.

    1982-01-01

    Spectra have been measured over a variety of types of complex terrain: on tops of hills and escarpments, over land downstream of a water surface, and over rolling terrain. Differences between spectra over many types of complex terrain, and over uniform terrain, can be explained by these hypotheses...... is horizontal, and decrease when the flow is uphill, for the longitudinal velocity component only. Since vertical-velocity spectra contain relatively less low wavenumber energy than horizontal-velocity spectra, energetic vertical-velocity fluctuations tend to be in equilibrium with local terrain....

  11. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production......The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations...

  12. New crops for arid lands.

    Science.gov (United States)

    Hinman, C W

    1984-09-28

    Five plants are described that could be grown commercially under arid conditions. Once the most valuable component has been obtained from each plant (rubber from guayule; seed oil from jojoba, buffalo gourd, and bladderpod; and resin from gumweed), the remaining material holds potential for useful products as well as fuel. It is difficult to realize the full potential of arid land plants, however, because of the complexities of developing the necessary agricultural and industrial infrastructure simultaneously. To do so, multicompany efforts or cooperative efforts between government and the private sector will be required.

  13. Stability measures in arid ecosystems

    Science.gov (United States)

    Nosshi, M. I.; Brunsell, N. A.; Koerner, S.

    2015-12-01

    Stability, the capacity of ecosystems to persist in the face of change, has proven its relevance as a fundamental component of ecological theory. Here, we would like to explore meaningful and quantifiable metrics to define stability, with a focus on highly variable arid and semi-arid savanna ecosystems. Recognizing the importance of a characteristic timescale to any definition of stability, our metrics will be focused scales from annual to multi-annual, capturing different aspects of stability. Our three measures of stability, in increasing order of temporal scale, are: (1) Ecosystem resistance, quantified as the degree to which the system maintains its mean state in response to a perturbation (drought), based on inter-annual variability in Normalized Difference Vegetation Index (NDVI). (2) An optimization approach, relevant to arid systems with pulse dynamics, that models vegetation structure and function based on a trade off between the ability to respond to resource availability and avoid stress. (3) Community resilience, measured as species turnover rate (β diversity). Understanding the nature of stability in structurally-diverse arid ecosystems, which are highly variable, yields theoretical insight which has practical implications.

  14. Annual plants in arid and semi-arid desert regions

    Institute of Scientific and Technical Information of China (English)

    Xuehua LI; Xiaolan LI; Deming JIANG; Zhimin LIU; Qinghe YU

    2008-01-01

    Annual plants are the main vegetation in arid and semi-arid desert regions.Because of their unique traits,they are the optimal experimental subjects for eco-logical studies.In this article,we summarize annual plants' seed germination strategies,seedling adaptability mechanism to environments,seed dispersal,and soil seed banks.We also discuss the biotic and abiotic factors affecting the composition and dynamics of annual plant populations and communities.Because annual plants have important ecological functions in desert vegetation systems,this study on annual plants will be of great bene-fit to the conservation and restoration of desert ecosys-tems,the rational utilization of resources,and the sustainable development of desert regions.

  15. A GPS inspired Terrain Referenced Navigation algorithm

    NARCIS (Netherlands)

    Vaman, D.

    2014-01-01

    Terrain Referenced Navigation (TRN) refers to a form of localization in which measurements of distances to the terrain surface are matched with a digital elevation map allowing a vehicle to estimate its own position within the map. The main goal of this dissertation is to improve TRN performance thr

  16. A GPS inspired Terrain Referenced Navigation algorithm

    NARCIS (Netherlands)

    Vaman, D.

    2014-01-01

    Terrain Referenced Navigation (TRN) refers to a form of localization in which measurements of distances to the terrain surface are matched with a digital elevation map allowing a vehicle to estimate its own position within the map. The main goal of this dissertation is to improve TRN performance thr

  17. The surface energy balance over drying semi-arid terrain in West Africa

    NARCIS (Netherlands)

    Schüttemeyer, D.

    2005-01-01

    One of the fundamental aspects of current research in earth system science is the proper understanding of land-atmosphere interactions. The role of the land surface is crucial in the climate system, since a large fraction of incoming solar radiation passes through the atmosphere and is converted at

  18. Photometric Characteristics of Lunar Terrains

    Science.gov (United States)

    Sato, Hiroyuki; Hapke, Bruce W.; Denevi, Brett W.; Robinson, Mark

    2016-10-01

    The photometric properties of the lunar depend on albedo, surface roughness, porosity, and the internal/external structure of particles. Hapke parameter maps derived using a bidirectional reflectance model [Hapke, 2012] from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) images demonstrated the spatial and spectral variation of the photometric properties of the Moon [Sato et al., 2014]. Using the same methodology, here we present the photometric characteristics of typical lunar terrains, which were not systematically analyzed in the previous study.We selected five representative terrain types: mare, highland, swirls, and two Copernican (fresh) crater ejecta (one mare and one highlands example). As for the datasets, we used ~39 months of WAC repeated observations, and for each image pixel, we computed latitude, longitude, incidence, emission, and phase angles using the WAC GLD100 stereo DTM [Scholten et al., 2012]. To obtain similar phase and incidence angle ranges, all sampling sites are near the equator and in the vicinity of Reiner Gamma. Three free Hapke parameters (single scattering albedo: w, HG2 phase function parameter: c, and angular width of SHOE: hs) were then calculated for the seven bands (321-689 nm). The remaining parameters were fixed by simplifying the model [Sato et al., 2014].The highlands, highland ejecta, and swirl (Reiner Gamma) showed clearly higher w than the mare and mare ejecta. The derived c values were lower (less backscattering) for the swirl and higher (more backscattering) for the highlands (and ejecta) relative to the other sites. Forward scattering materials such as unconsolidated transparent crystalline materials might be relatively enriched in the swirl. In the highlands, anorthositic agglutinates with dense internal scattering could be responsible for the strong backscattering. The mare and mare ejecta showed continuously decreasing c from UV to visible wavelengths. This might be caused by the FeO-rich pyroxene

  19. Walking Algorithm of Humanoid Robot on Uneven Terrain with Terrain Estimation

    Directory of Open Access Journals (Sweden)

    Jiang Yi

    2016-02-01

    Full Text Available Humanoid robots are expected to achieve stable walking on uneven terrains. In this paper, a control algorithm for humanoid robots walking on previously unknown terrains with terrain estimation is proposed, which requires only minimum modification to the original walking gait. The swing foot trajectory is redesigned to ensure that the foot lands at the desired horizontal positions under various terrain height. A compliant terrain adaptation method is applied to the landing foot to achieve a firm contact with the ground. Then a terrain estimation method that takes into account the deformations of the linkages is applied, providing the target for the following correction and adjustment. The algorithm was validated through walking experiments on uneven terrains with the full-size humanoid robot Kong.

  20. Human Robotic Systems (HRS): Extreme Terrain Mobility Element

    Data.gov (United States)

    National Aeronautics and Space Administration — During 2014, the Extreme Terrain Mobility project element is developing five technologies:Exoskeleton Development for ISS EvaluationExtreme Terrain Mobility...

  1. Wind turbine wake measurement in complex terrain

    Science.gov (United States)

    Hansen, KS; Larsen, GC; Menke, R.; Vasiljevic, N.; Angelou, N.; Feng, J.; Zhu, WJ; Vignaroli, A.; W, W. Liu; Xu, C.; Shen, WZ

    2016-09-01

    SCADA data from a wind farm and high frequency time series measurements obtained with remote scanning systems have been analysed with focus on identification of wind turbine wake properties in complex terrain. The analysis indicates that within the flow regime characterized by medium to large downstream distances (more than 5 diameters) from the wake generating turbine, the wake changes according to local atmospheric conditions e.g. vertical wind speed. In very complex terrain the wake effects are often “overruled” by distortion effects due to the terrain complexity or topology.

  2. Biologic Analog Science Associated with Lava Terrains

    Science.gov (United States)

    Thomas, N. K.; Hamilton, J. C.; Veillet, A.; Muir, C.

    2016-05-01

    The goal of BASALT is to use Hawaiian volcanic terrain to constrain the upper limits of biomass that could have been supported on Mars and how those upper bounds inform future detection requirements for manned missions.

  3. TERRAIN, McCRACKEN COUNTY, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. DCS Terrain Submission for Lewis County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  5. TERRAIN, ST. CLAIR COUNTY, ALABAMA USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain Submission for Adair, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Logan, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN, CITY OF DALLAS, DALLAS COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  9. DCS TERRAIN Submission for STEARNS COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. DCS Terrain Submission for Rockland County NY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  11. DCS Terrain for Jasper County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS TERRAIN SUBMISSION FOR SHELBY COUNTY, TN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  13. DCS Terrain Submission for Brazos TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DCS Terrain Submission for Cass County, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain Submission for Irwin, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submission for Seminole, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. Terrain Sumbission for Howard County NE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain Submission for Ector, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS Terrain for HOUSTON COUNTY, ALABAMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain Submission for Cass County, MO

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS TERRAIN SUBMISSION FOR PUTNAM COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  2. DCS Terrain Submission for Benton County, AR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  3. DCS Terrain Submission for Solano, CA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, ESSEX COUNTY, MASSACHUSETTS - Coastal PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. DCS TERRAIN SUBMISSION FOR KNOX COUNTY, TN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  6. TERRAIN, Pointe Coupee PARISH, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Mason County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  8. TERRAIN, UPPER CUMBERLAND WATERSHED, KENTUCKY USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  9. DCS Terrain Submission for Mississippi County AR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, CERRO GORDO COUNTY, IOWA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain Submission for Sanders County, Montana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for Houston TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain Submission for Jackson, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. Terrain, CEDAR RAPIDS, LINN COUNTY, IA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain Submission for Lagrange County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. TERRAIN Submission for Dodge Countywide DFIRM

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain Submission for Chippewa County, Wisconsin

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain Submission for George, MS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS Terrain Submission for Harrison, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain Submission for Fox Lake PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain for Quitman County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain Submission for Charlton Co GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN Submission for CHISAGO COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  4. DCS Terrain for Harris County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. DCS Terrain Submission for Carter, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain for Murray County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Pike County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  8. DCS Terrain Submission for Hancock County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  9. DCS Terrain Submission for Magoffin County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  10. DCS Terrain Submission for Greenup County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  11. DCS Terrain Submission for Boyd County, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  12. DCS Terrain Submission for Lagrange County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain Submission for Delaware, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DCS Terrain Submission for Cherokee, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain Submission for Texas, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submission for Fulton County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain Submission for Seminole, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. Dummy metadata TERRAIN, Montgomery County, Pennsylvania

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data includes digital elevation models, LIDAR derived contours, LIDAR three-dimensional spot elevations and breaklines, field surveyed ground elevations and...

  19. DCS Terrain Submission for Wabash County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain Submission for Sequoyah, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain Submission for Miami County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain Submission for Pontodoc, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. TERRAIN DATA CAPTURE STANDARDS, Bedford PA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data includes digital elevation models, LIDAR derived contours, LIDAR three-dimensional spot elevations and breaklines, field surveyed ground elevations and...

  4. DCS Terrain Submission for Lincoln, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  5. DCS Terrain Submission for Noble County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain Submission for Woodward, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Gunnison County, CO

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  8. DCS Terrain Submission for Mayes, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. DCS Terrain Submission for Caddo, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. DCS Terrain Submission for Custer, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain Submission for Tipton County, IN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for Stephens, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain Submission for Bark River PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, BRISTOL COUNTY, RHODE ISLAND - Coastal PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  15. TERRAIN, UPPER CUMBERLAND WATERSHED, PMR, TENNESSEE, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain for Pickens County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain Submission for Ulster County NY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  18. DCS Terrain for Cobb County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS TERRAIN SUBMISSION FOR VOLUSIA COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  20. DCS Terrain Submission for Sanders County, Montana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain for Hancock County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain Submission for Howard, AR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. DCS Terrain Submission for Winston County, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. TERRAIN, ST. LOUIS COUNTY, Missouri USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  5. DCS Terrain Submission for Tyler TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain Submission for Citrus County FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  7. DCS Terrain Submission for Kingfisher, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  8. TERRAIN DATA, CITY OF CARSON CITY, NV

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  9. TERRAIN, CANNON COUNTY, TENNESSEE and INCORPORATED AREAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. DCS TERRAIN Submission for STEARNS COUNTY, MN

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain for Stewart County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for Chippewa County, Wisconsin

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain for Warren County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DCS Terrain for Middlesex County, NJ

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that were used to create...

  15. DCS Terrain for Williamson County, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submission for Albany County NY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  17. DCS Terrain Submission for Rusk County, Wisconsin

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain for Greene County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS Terrain for Heard County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. TERRAIN-FREMONT COUNTY, WY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain Submission for Chemung County, NY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain Submission for Hempstead, AR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  3. DCS Terrain for Clay County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  4. NONLINEAR PREDICTIVE CONTROL FOR TERRAIN FOLLOWING

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    A nonlinear continuous predictive control method was used for design of cruise missile terrain-following controller. A performance index which combined the tracking error and rate of tracking error is presented. Then an optimal nonlinear feedback control law is generated to minimize the performance index. The tracking performance and robustness of controller are discussed. The advantage of the control law is demonstrated by successfully designing cruise missile terrain following controllers. The results show that the controller exhibits robustness and excellent tracking performance.

  5. Automatic terrain modeling using transfinite element analysis

    KAUST Repository

    Collier, Nathaniel O.

    2010-05-31

    An automatic procedure for modeling terrain is developed based on L2 projection-based interpolation of discrete terrain data onto transfinite function spaces. The function space is refined automatically by the use of image processing techniques to detect regions of high error and the flexibility of the transfinite interpolation to add degrees of freedom to these areas. Examples are shown of a section of the Palo Duro Canyon in northern Texas.

  6. Numerical investigation into effects of complex terrain on spatial and temporal variability of precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Stalker, J.R.; Bossert, J.E.; Reisner, J.M.

    1998-12-31

    This study is part of an ongoing research effort at Los Alamos to understand the hydrologic cycle at regional scales by coupling atmospheric, land surface, river channel, and groundwater models. In this study the authors examine how local variation of heights of the two mountain ranges representative of those that surround the Rio Grande Valley affects precipitation. The lack of observational data to adequately assess precipitation variability in complex terrain, and the lack of previous work has prompted this modeling study. Thus, it becomes imperative to understand how the local terrain affects snow accumulations and rainfall during winter and summer seasons respectively so as to manage this valuable resource in this semi-arid region. While terrain is three dimensional, simplifying the problem to two dimensions can provide some valuable insight into topographic effects that may exist at various transects across the Rio Grande Valley. The authors induce these topographic effects by introducing variations in heights of the mountains and the width of the valley using an analytical function for the topography. The Regional Atmospheric Modeling System (RAMS) is used to examine these effects.

  7. The MAP program: building the digital terrain model.

    Science.gov (United States)

    R.H. Twito; R.W. Mifflin; R.J. McGaughey

    1987-01-01

    PLANS, a software package for integrated timber-harvest planning, uses digital terrain models to provide the topographic data needed to fit harvest and transportation designs to specific terrain. MAP, an integral program in the PLANS package, is used to construct the digital terrain models required by PLANS. MAP establishes digital terrain models using digitizer-traced...

  8. Terrain correction for gravity measurements, using a digital terrain model (DTM)

    NARCIS (Netherlands)

    Ketelaar, A.C.R.

    1987-01-01

    A single-term expression is given to calculate the gravitational effect for any square vertical prism with a sloping surface. A moderate measure of approximation is involved. The expression is well suited to automatic calculation of the terrain correction when a digital terrain model is available. T

  9. An algorithm of multi-model spatial overlay based on three-dimensional terrain model TIN and its application

    Institute of Scientific and Technical Information of China (English)

    王少安; 张子平; 龚健雅

    2001-01-01

    3D-GIS spatial overlay analysis is being broadly concerned about in international academe and is a research focus. It is one of the important functions of spatial analysis using GIS technology. An algorithm of multi-model spatial overlay based on three-dimensional terrain model TIN is introduced in this paper which can be used to solve the TIN-based thrcc-dimensional overlay operation in spatial analysis. The feasibility arid validity of this algorithm is identified. This algorithm is used successfully in three-dimensional overlay and region variation overlay analysis.

  10. High performance robotic traverse of desert terrain.

    Energy Technology Data Exchange (ETDEWEB)

    Whittaker, William (Carnegie Mellon University, Pittsburgh, PA)

    2004-09-01

    This report presents tentative innovations to enable unmanned vehicle guidance for a class of off-road traverse at sustained speeds greater than 30 miles per hour. Analyses and field trials suggest that even greater navigation speeds might be achieved. The performance calls for innovation in mapping, perception, planning and inertial-referenced stabilization of components, hosted aboard capable locomotion. The innovations are motivated by the challenge of autonomous ground vehicle traverse of 250 miles of desert terrain in less than 10 hours, averaging 30 miles per hour. GPS coverage is assumed to be available with localized blackouts. Terrain and vegetation are assumed to be akin to that of the Mojave Desert. This terrain is interlaced with networks of unimproved roads and trails, which are a key to achieving the high performance mapping, planning and navigation that is presented here.

  11. SCIENCES IN COLD AND ARID REGIONS

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Aims and Scope Sciences in Cold and Arid Regions, an international Engiish-language journal, is devoted to publishing the latest research achievements on the process and the pattern of Earth surface system in cold and arid regions. Researches in cold regions 1) emphasize particularly on the cold-region-characterized physical, chemical and biological processes and their interactions, and on the response of Cryosphere to Global change and Human activities as well as its effect to environment and the acclimatizable

  12. Terrain Simplification Research in Augmented Scene Modeling

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the "short-sight" problem associated with the traditional methods.

  13. Improved Inlet Conditions for Terrain CFD

    DEFF Research Database (Denmark)

    Pedersen, Jesper Grønnegaard

    The atmospheric boundary layer flow over different types of terrain is studied through simulations made with the finite volume CFD code of Ellipsys 2D and 3D. The simulations are compared to measurements made at the Høvsøre test site and over the hill of Askervein.The primary objective of these i......The atmospheric boundary layer flow over different types of terrain is studied through simulations made with the finite volume CFD code of Ellipsys 2D and 3D. The simulations are compared to measurements made at the Høvsøre test site and over the hill of Askervein.The primary objective...

  14. Investigation of Terrain Bounce Electronic Countermeasure

    Science.gov (United States)

    1980-12-01

    no point for which both the slope of the curve and the value of Vpd are equal to zero. (See Figure 5 for C -. 5.) Thus, there is no physical ...for rough terrain. A methodology was presented for solving the Terrain Bounce problem. In Section II1, the metho - dology was applied to a specific...Waves from Slightly Rough Surfaces", Communications on Pure Applied Mathematics , 4: 351-378 (1951). 22. Sherwood, E.M. and E.L. Ginzton. "Reflection

  15. Chronology of heavily cratered terrains on Mercury

    Science.gov (United States)

    Marchi, S.; Chapman, C. R.

    2012-12-01

    Imaging of Mercury by Mariner 10 revealed a planet with more extensive plains units than on the Moon. Even in heavily cratered terrain, there is a lack of craters Morbidelli et al., [1] in order to interpret new crater counts on these terrains. We find that these craters are probably not saturated but may have been in equilibrium with a rapid resurfacing process, presumably volcanism that formed the earliest recognized intercrater plains. The crater retention age for this terrain, which contains the oldest large craters on Mercury, is surprisingly young, perhaps hundreds of millions of years younger than the heavily cratered pre-Nectarian terrains on the Moon [2]. These results are important for understanding the early geological and geophysical evolution of Mercury. References: [1] Morbidelli A., Marchi S., Bottke W.F., and Kring D.A. 2012. A sawtooth timeline for the first billion years of the lunar bombardment. Earth and Planetary Science Letters, in press. [2] Marchi S., Bottke W.F., Kring D.A., and Morbidelli A. 2012. The onset of the lunar cataclysm as recorded in its ancient crater populations. Earth and Planetary Science Letters 325, 27-38.

  16. Processes Modifying Cratered Terrains on Pluto

    Science.gov (United States)

    Moore, J. M.

    2015-01-01

    The July encounter with Pluto by the New Horizons spacecraft permitted imaging of its cratered terrains with scales as high as approximately 100 m/pixel, and in stereo. In the initial download of images, acquired at 2.2 km/pixel, widely distributed impact craters up to 260 km diameter are seen in the near-encounter hemisphere. Many of the craters appear to be significantly degraded or infilled. Some craters appear partially destroyed, perhaps by erosion such as associated with the retreat of scarps. Bright ice-rich deposits highlight some crater rims and/or floors. While the cratered terrains identified in the initial downloaded images are generally seen on high-to-intermediate albedo surfaces, the dark equatorial terrain informally known as Cthulhu Regio is also densely cratered. We will explore the range of possible processes that might have operated (or still be operating) to modify the landscape from that of an ancient pristinely cratered state to the present terrains revealed in New Horizons images. The sequence, intensity, and type of processes that have modified ancient landscapes are, among other things, the record of climate and volatile evolution throughout much of the Pluto's existence. The deciphering of this record will be discussed. This work was supported by NASA's New Horizons project.

  17. Wind turbine wake measurement in complex terrain

    DEFF Research Database (Denmark)

    Hansen, Kurt Schaldemose; Larsen, Gunner Chr.; Menke, Robert;

    2016-01-01

    SCADA data from a wind farm and high frequency time series measurements obtained with remote scanning systems have been analysed with focus on identification of wind turbine wake properties in complex terrain. The analysis indicates that within the flow regime characterized by medium to large...

  18. Modelling Canopy Flows over Complex Terrain

    Science.gov (United States)

    Grant, Eleanor R.; Ross, Andrew N.; Gardiner, Barry A.

    2016-06-01

    Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO_2 and other gaseous fluxes over forests in complex terrain, predicting wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required.

  19. Conically scanning lidar error in complex terrain

    DEFF Research Database (Denmark)

    Bingöl, Ferhat; Mann, Jakob; Foussekis, Dimitri

    2009-01-01

    Conically scanning lidars assume the flow to be homogeneous in order to deduce the horizontal wind speed. However, in mountainous or complex terrain this assumption is not valid implying a risk that the lidar will derive an erroneous wind speed. The magnitude of this error ismeasured by collocating...

  20. Scaling Terrain Attributes By Fractal Methods

    Science.gov (United States)

    Terrain attributes derived from grid digital elevation models (DEMs) are commonly used in distributed hydrologic models. However, many attribute estimations are biased by DEM grid cell size. For example, land surface slopes estimated from 30-m DEMs are, on average, less than slopes estimated from ...

  1. Terrain Measurement with SAR/InSAR

    Science.gov (United States)

    Li, Deren; Liao, Mingsheng; Balz, Timo; Zhang, Lu; Yang, Tianliang

    2016-08-01

    Terrain measurement and surface motion estimation are the most important applications for commercial and scientific SAR missions. In Dragon-3, we worked on these applications, especially regarding DEM generation, surface motion estimation with SAR time- series for urban subsidence monitoring and landslide motion estimation, as well as developing tomographic SAR processing methods in urban areas.

  2. Maintaining Contour Trees of Dynamic Terrains

    DEFF Research Database (Denmark)

    Agarwal, Pankaj K.; Mølhave, Thomas; Revsbæk, Morten;

    2015-01-01

    We study the problem of maintaining the contour tree T of a terrain Sigma, represented as a triangulated xy-monotone surface, as the heights of its vertices vary continuously with time. We characterize the combinatorial changes in T and how they relate to topological changes in Sigma. We present ...

  3. Tessera terrain: Characteristics and models of origin

    Science.gov (United States)

    Bindschadler, D. L.; Head, James W.

    1989-01-01

    Tessera terrain consists of complexly deformed regions characterized by sets of ridges and valleys that intersect at angles ranging from orthogonal to oblique, and were first viewed in Venera 15/16 SAR data. Tesserae cover more area (approx. 15 percent of the area north of 30 deg N) than any of the other tectonic units mapped from the Venera data and are strongly concentrated in the region between longitudes 0 deg E and 150 deg E. Tessera terrain is concentrated between a proposed center of crustal extension and divergence in Aphrodite and a region of intense deformation, crustal convergence, and orogenesis in western Ishtar Terra. Thus, the tectonic processes responsible for tesserae are an important part of Venus tectonics. As part of an effort to understand the formation and evolution of this unusual terrain type, the basic characteristics of the tesserae were compared to the predictions made by a number of tectonic models. The basic characteristics of tessera terrain are described and the models and some of their basic predictions are briefly discussed.

  4. Modelling Canopy Flows over Complex Terrain

    Science.gov (United States)

    Grant, Eleanor R.; Ross, Andrew N.; Gardiner, Barry A.

    2016-12-01

    Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO_2 and other gaseous fluxes over forests in complex terrain, predicting wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required.

  5. Declarative terrain modeling for military training games

    NARCIS (Netherlands)

    Smelik, R.M.; Tutenel, T.; Kraker, J.K.. de; Bidarra, R.

    2010-01-01

    Military training instructors increasingly often employ computer games to train soldiers in all sorts of skills and tactics. One of the difficulties instructors face when using games as a training tool is the creation of suitable content, including scenarios, entities, and corresponding terrain mode

  6. Evaluating rainwater harvesting systems in arid and semi-arid regions

    NARCIS (Netherlands)

    Ammar, Adham Ali

    2017-01-01

    Rainwater harvesting (RWH) is an ancient traditional technology practised in many parts of the world, especially in arid and semi-arid regions (ASARs). ASARs represent 40% of the earth’s land surface and are characterised by low average annual rainfall and uneven temporal and spatial distribut

  7. Rainwater harvesting in arid and semi-arid zones (repr. 1997)

    NARCIS (Netherlands)

    Boers, Th.M.

    1994-01-01

    In arid and semi-arid regions, the scarcity of water can be alleviated by rainwater harvesting, which is defined as a method of inducing, collecting, storing, and conserving local surface runoff for agriculture. Rainwater harvesting can be applied with different systems, and this dissertation deals

  8. Beekeeping technology adoption in arid and semi-arid lands of ...

    African Journals Online (AJOL)

    Beekeeping technology adoption in arid and semi-arid lands of southern Kenya. ... on the effect of these technologies on the production levels of hive products and on the farmers' social and ... Of the adopters, 75.6% were found to be using traditional technology while the rest were using modern technology. ... Article Metrics.

  9. Evaluating rainwater harvesting systems in arid and semi-arid regions

    NARCIS (Netherlands)

    Ammar, Adham Ali

    2017-01-01

    Rainwater harvesting (RWH) is an ancient traditional technology practised in many parts of the world, especially in arid and semi-arid regions (ASARs). ASARs represent 40% of the earth’s land surface and are characterised by low average annual rainfall and uneven temporal and spatial

  10. Spatial and temporal variations of aridity indices in Iraq

    Science.gov (United States)

    Şarlak, Nermin; Mahmood Agha, Omar M. A.

    2017-06-01

    This study investigates the spatial and temporal variations of the aridity indices to reveal the desertification vulnerability of Iraq region. Relying on temperature and precipitation data taken from 28 meteorological stations for 31 years, the study aims to determine (1) dry land types and their delineating boundaries and (2) temporal change in aridity conditions in Iraq. Lang's aridity (Im), De Martonne's aridity (Am), United Nations Environmental Program (UNEP) aridity (AIu), and Erinç aridity (IE) indices were selected in this study because of the scarcity of the observed data. The analysis of the spatial variation of aridity indices exhibited that the arid and semi-arid regions cover about 97% of the country's areas. As for temporal variations, it was observed that the aridity indices tend to decrease (statistically significant or not) for all stations. The cumulative sum charts (CUSUMs) were applied to detect the year on which the climate pattern of aridity indices had changed from one pattern to another. The abrupt change point was detected around year 1997 for the majority of the stations. Thus, the spatial and temporal aridity characteristics in Iraq were examined for the two periods 1980-1997 and 1998-2011 (before and after the change-point year) to observe the influence of abrupt change point on aridity phenomena. The spatial variation after 1997 was observed from semi-arid (dry sub humid) to arid (semi-arid) especially at the stations located in northern Iraq, while hyper-arid and arid climatic conditions were still dominant over southern and central Iraq. Besides, the negative temporal variations of the two periods 1980-1997 and 1998-2011 were obtained for almost every station. As a result, it was emphasized that Iraq region, like other Middle East regions, has become drier after 1997. The observed reduction in precipitation and increase in temperature for this region seem to make the situation worse in future.

  11. Traversable Terrain Modeling and Performance Measurement of Mobile Robots

    Science.gov (United States)

    2004-08-01

    In this paper, we have described a technique for terrain traversability assessment modeling of mobile robots operating in natural terrain and...presented a fast near-optimum algorithm for autonomous navigational path planning of mobile robots in rough terrain environments. The proposed method is

  12. Sink plot for runoff measurements on semi-flat terrains: preliminary data and their potential hydrological and ecological implications

    Directory of Open Access Journals (Sweden)

    Kidron Giora J.

    2014-12-01

    Full Text Available In arid and semiarid regions where water is the main limiting factor, water redistribution is regarded as an important hydrological process of great ecological value. By providing additional water to certain loci, moist pockets of great productivity are formed, characterized by high plant biomass and biological activity. These moist pockets are often a result of runon. Yet, although runoff may take place on semi-flat undulating surfaces, runoff measurements are thus far confined to slopes, where a sufficient gradient facilitates downslope water harvesting. On undulating surfaces of mounds and depressions, such as in interdunes, no quantification of the amount of water reaching depressions is feasible due to the fact that no reliable method for measuring the runoff amounts in semi-flat terrains is available. The current paper describes specific runoff plots, designed to measure runoff in depressions (sinks. These plots, termed sink plots (SPs, were operative in the Hallamish dunefield (Negev Desert, Israel. The paper presents measurements of runoff yield that were carried out between January 2013 and January 2014 on SPs and compared them to runoff obtained from crusted slope plots and fine-grained (playa surfaces. The potential hydrological and ecological implications of water redistribution within semi-flat terrains for this and other arid ecosystems are discussed.

  13. The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

    Directory of Open Access Journals (Sweden)

    J. L. Peña-Arancibia

    2010-07-01

    Full Text Available The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients (kbf. Mean annual rainfall (MAR and aridity index (AI were found to explain 49% of the spatial variation of kbf. The rest of climatic indices plus average catchment slope (SLO and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE, a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a~potential alternative for kbf parameterisation in ungauged areas.

  14. Large Terrain Continuous Level of Detail 3D Visualization Tool

    Science.gov (United States)

    Myint, Steven; Jain, Abhinandan

    2012-01-01

    This software solved the problem of displaying terrains that are usually too large to be displayed on standard workstations in real time. The software can visualize terrain data sets composed of billions of vertices, and can display these data sets at greater than 30 frames per second. The Large Terrain Continuous Level of Detail 3D Visualization Tool allows large terrains, which can be composed of billions of vertices, to be visualized in real time. It utilizes a continuous level of detail technique called clipmapping to support this. It offloads much of the work involved in breaking up the terrain into levels of details onto the GPU (graphics processing unit) for faster processing.

  15. Study on robust terrain following control

    Institute of Scientific and Technical Information of China (English)

    Zha Xu; Cui Pingyuan

    2005-01-01

    Based on classical terrain following (TF) algorithm (adaptive angle method), a new method for TF controller is proposed by using angle of attack. A method of obtaining terrain outline data from Digital Elevation Map (DEM) for TF control is discussed in order to save store space. The block control model, which is suitable for backstepping design,is given for nonlinear model of aircraft. Making full use of the characteristics of the system and combining block control principle, backstepping technique, a robust controller design method is proposed. Uncertainties in every sub-block are allowed, and can be canceled by using the idea of nonlinear damping. It is proved that the state tracking errors converge to the neighborhood of the origin exponentially. Finally, nonlinear six-degree-of-freedom simulation results for the aircraft model are presented to demonstrate the effectiveness of the proposed control law.

  16. Application of Digital Terrain Model to volcanology

    Directory of Open Access Journals (Sweden)

    V. Achilli

    2006-06-01

    Full Text Available Three-dimensional reconstruction of the ground surface (Digital Terrain Model, DTM, derived by airborne GPS photogrammetric surveys, is a powerful tool for implementing morphological analysis in remote areas. High accurate 3D models, with submeter elevation accuracy, can be obtained by images acquired at photo scales between 1:5000-1:20000. Multitemporal DTMs acquired periodically over volcanic area allow the monitoring of areas interested by crustal deformations and the evaluation of mass balance when large instability phenomena or lava flows have occurred. The work described the results obtained from the analysis of photogrammetric data collected over the Vulcano Island from 1971 to 2001. The data, processed by means of the Digital Photogrammetry Workstation DPW 770, provided DTM with accuracy ranging between few centimeters to few decimeters depending on the geometric image resolution, terrain configuration and quality of photographs.

  17. The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

    Directory of Open Access Journals (Sweden)

    J. L. Peña-Arancibia

    2010-11-01

    Full Text Available The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1 from the Global River Discharge Center (GRDC and a linear reservoir model were used to obtain baseflow recession coefficients (kbf for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR and aridity index (AI were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE, a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.

  18. development of hardy sorghum cultivars for the arid and

    African Journals Online (AJOL)

    DEVELOPMENT OF HARDY SORGHUM CULTIVARS FOR THE ARID AND. SEMI ARID REGIONS .... media and presence or absence ofin vitro selective agents (Amzallag et ...... diversity in India Mustard (Brassica Juncea) and its relationship ...

  19. Visual Media Reasoning - Terrain-based Geolocation

    Science.gov (United States)

    2015-06-01

    silhouette has been computed for a pixel, the signatures is computed. The details of the GPU kernel and the mathematics pertinent to the extraction of the...system software for large-scale pattern matching. The technologies offer many promising benefits in a variety of fields that rely on pattern...representation of terrain silhouettes. In Proceedings of the 13th annual ACM international workshop on Geographic information systems, GIS ’05, pages

  20. Mobility versus terrain: a game theoretic approach

    Science.gov (United States)

    Bednarz, David; Muench, Paul

    2016-05-01

    Mobility and terrain are two sides of the same coin. You cannot describe mobility unless you describe the terrain. For example, if my world is trench warfare, the tank may be the ideal vehicle. If my world is urban warfare, clearing buildings and such, the tank may not be an ideal vehicle, perhaps an anthropomorphic robot would be better. We seek a general framework for mobility that captures the relative value of different mobility strategies. Game theory is positively the right way to analyze the interactions of rational players who behave strategically. In this paper, we will describe the interactions between a mobility player, who is trying to make it from point A to point B with one chance to refuel, and a terrain player who is trying to minimize that probability by placing an obstacle somewhere along the path from A to B. In previous work [1], we used Monte Carlo methods to analyze this mobility game, and found optimal strategies for a discretized version of the game. Here we show the relationship of this game to a classic game of timing [2], and use solution methods from that literature to solve for optimal strategies in a continuous version of this mobility game.

  1. Cooperative terrain model acquisition by two point-robots in planar polygonal terrains

    Energy Technology Data Exchange (ETDEWEB)

    Rao, N.S.V.; Protopopescu, V.

    1994-11-29

    We address the model acquisition problem for an unknown terrain by a team of two robots. The terrain may be cluttered by a finite number of polygonal obstacles with unknown shapes and positions. The robots are point-sized and equipped with visual sensors which acquire all visible parts of the terrain by scanning from their locations. The robots communicate with each other via wireless connection. The performance is measured by the number of the sensor (scan) operations which are assumed to be the most time-consuming/expensive of all the robot operations. We employ the restricted visibility graph methods in a hierarchiacal setup. For terrains with convex obstacles, the sensing time can be halved compared to a single robot implementation. For terrains with concave corners, the performance of the algorithm depends on the number of concave regions and their depths. A hierarchical decomposition of the restricted visibility graph into 2-connected components and trees is considered. Performance for the 2-robot team is expressed in terms of sizes of 2-connected components, and the sizes and diameters of the trees. The proposed algorithm and analysis can be applied to the methods based on Voronoi diagram and trapezoidal decomposition.

  2. Performance evaluation of constructed wetlands: A review of arid ...

    African Journals Online (AJOL)

    Administrator

    and on the effect of biological processes on the elements of the water cycle. It is actually the ... for wastewater treatment in arid and semi-arid areas. Key words: Arid ... industries, organic and inorganic contaminants from municipalities and brown ... more, in the last three decades, scientists in Europe and. America mimicked ...

  3. Permafrost distribution modelling in the semi-arid Chilean Andes

    Science.gov (United States)

    Azócar, Guillermo F.; Brenning, Alexander; Bodin, Xavier

    2017-04-01

    Mountain permafrost and rock glaciers in the dry Andes are of growing interest due to the increase in mining industry and infrastructure development in this remote area. Empirical models of mountain permafrost distribution based on rock glacier activity status and temperature data have been established as a tool for regional-scale assessments of its distribution; this kind of model approach has never been applied for a large portion of the Andes. In the present study, this methodology is applied to map permafrost favourability throughout the semi-arid Andes of central Chile (29-32° S), excluding areas of exposed bedrock. After spatially modelling of the mean annual air temperature distribution from scarce temperature records (116 station years) using a linear mixed-effects model, a generalized additive model was built to model the activity status of 3524 rock glaciers. A permafrost favourability index (PFI) was obtained by adjusting model predictions for conceptual differences between permafrost and rock glacier distribution. The results indicate that the model has an acceptable performance (median AUROC: 0.76). Conditions highly favourable to permafrost presence (PFI ≥ 0.75) are predicted for 1051 km2 of mountain terrain, or 2.7 % of the total area of the watersheds studied. Favourable conditions are expected to occur in 2636 km2, or 6.8 % of the area. Substantial portions of the Elqui and Huasco watersheds are considered to be favourable for permafrost presence (11.8 % each), while in the Limarí and Choapa watersheds permafrost is expected to be mostly limited to specific sub-watersheds. In the future, local ground-truth observations will be required to confirm permafrost presence in favourable areas and to monitor permafrost evolution under the influence of climate change.

  4. Conservation and restoration of degraded ecosystems in arid and semi-arid areas of northwest China

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    In "West Development" of China, one of the most important activities is the Natural Forest Protection Program, designed to swiftly convert the focus of management and utilization of the natural forests from a timber orientation towards forest conservation, sustainable management and environmental protection. The project covered almost all the arid and semi-arid regions in Northwest region. Accompanying this great campaign this paper studied the conservation and restoration model of degraded ecosystems in arid and semi-arid lands in Northwest China. The past practices have resulted in considerably natural forest degradation and loss through land conversion (primarily for agriculture), over-harvesting, inadequate reforestation and lack of protection. The consequences have been the loss of soil and water resources, diminished timber production capacity on a sustainable basis, and environmental losses. This paper applied Aronson's restoration model and proposed the conservation, restoration, re-allocation and preservation program for the implementation of environmental improvement and natural forest conservation.

  5. Applying animal behavior to arid rangeland mangement

    Science.gov (United States)

    Livestock production is one of many demands placed on today’s arid rangelands. Therefore, understanding plant and animal biology and their effects on biotic and abiotic landscape components is fundamental if rangelands are to remain ecologically sustainable. One limiting factor to accomplishing posi...

  6. The International Workshop on Environmental Changes and Sustainable Development in Arid and Semi-arid Regions

    Institute of Scientific and Technical Information of China (English)

    Xiaoping Yang; Arthur Conacher

    2007-01-01

    @@ Arid regions,dominated by deserts,are characterized by a severe shortage of moisture,and a lack of perennial and integrated systems of drainage.Distributed over a very large range of temperatures,from the very hot to the very cold zones,arid regions cover about one third of the world's land surface and occur in every continent,including Antarctica.

  7. Adaptation to drought in arid and semi-arid environments: Case of the Zambezi Valley, Zimbabwe

    OpenAIRE

    Emmanuel Mavhura; Desmond Manatsa; Terence Mushore

    2015-01-01

    Small-scale rain-fed agriculture is the main livelihood in arid to semi-arid regions of subSaharan Africa. The area is characterised by erratic rainfall and frequent droughts, making the capacity for coping with temporal water shortages essential for smallholder farmers. Focusing on the Zambezi Valley, Zimbabwe, this study investigates the impact of drought on food security and the strategies used by smallholder farmers to cope with drought. We used meteorological data and interviews to exami...

  8. Biomechanics and energetics of running on uneven terrain.

    Science.gov (United States)

    Voloshina, Alexandra S; Ferris, Daniel P

    2015-03-01

    In the natural world, legged animals regularly run across uneven terrain with remarkable ease. To gain understanding of how running on uneven terrain affects the biomechanics and energetics of locomotion, we studied human subjects (N=12) running at 2.3 m s(-1) on an uneven terrain treadmill, with up to a 2.5 cm height variation. We hypothesized that running on uneven terrain would show increased energy expenditure, step parameter variability and leg stiffness compared with running on smooth terrain. Subject energy expenditure increased by 5% (0.68 W kg(-1); Prunning on uneven terrain compared with smooth terrain. Step width and length variability also increased by 27% and 26%, respectively (Prunning on uneven terrain compared with smooth terrain. Calculations of gravitational potential energy fluctuations suggest that about half of the energetic increases can be explained by additional positive and negative mechanical work for up and down steps on the uneven surface. This is consistent between walking and running, as the absolute increases in energetic cost for walking and running on uneven terrain were similar: 0.68 and 0.48 W kg(-1), respectively. These results provide insight into how surface smoothness can affect locomotion biomechanics and energetics in the real world.

  9. Digital terrain data base - new possibilities of 3D terrain modeling

    Directory of Open Access Journals (Sweden)

    Mateja Rihtaršič

    1992-12-01

    Full Text Available GISs has brought new dimensions in the field of digital terrain modelling, too. Modem DTMs must be real (relational databases with high degree of "intelligence". This paper presents some of the demands, ivhich have to be solved in modern digital terrain databases, together with main steps of their's generation. Problems, connected to regional level, multi-pur pose use, new possibilities and direct integration into GIS are presented. The practical model was created across smaller test area, so few lines with practical experiences can be droped, too.

  10. Aridity under conditions of increased CO2

    Science.gov (United States)

    Greve, Peter; Roderick, Micheal L.; Seneviratne, Sonia I.

    2016-04-01

    A string of recent of studies led to the wide-held assumption that aridity will increase under conditions of increasing atmospheric CO2 concentrations and associated global warming. Such results generally build upon analyses of changes in the 'aridity index' (the ratio of potential evaporation to precipitation) and can be described as a direct thermodynamic effect on atmospheric water demand due to increasing temperatures. However, there is widespread evidence that contradicts the 'warmer is more arid' interpretation, leading to the 'global aridity paradox' (Roderick et al. 2015, WRR). Here we provide a comprehensive assessment of modeled changes in a broad set of dryness metrics (primarily based on a range of measures of water availability) over a large range of realistic atmospheric CO2 concentrations. We use an ensemble of simulations from of state-of-the-art climate models to analyse both equilibrium climate experiments and transient historical simulations and future projections. Our results show that dryness is, under conditions of increasing atmospheric CO2 concentrations and related global warming, generally decreasing at global scales. At regional scales we do, however, identify areas that undergo changes towards drier conditions, located primarily in subtropical climate regions and the Amazon Basin. Nonetheless, the majority of regions, especially in tropical and mid- to northern high latitudes areas, display wetting conditions in a warming world. Our results contradict previous findings and highlight the need to comprehensively assess all aspects of changes in hydroclimatological conditions at the land surface. Roderick, M. L., P. Greve, and G. D. Farquhar (2015), On the assessment of aridity with changes in atmospheric CO2, Water Resour. Res., 51, 5450-5463

  11. CHARACTERISTICS OF ARIDITY CONDITIONS IN SOUTH DOBRUDJA

    Directory of Open Access Journals (Sweden)

    A. TISCOVSCHI

    2013-04-01

    Full Text Available Characteristics of Aridity Conditions in South Dobrudja. For most people, the arid and semi-arid lands are those where precipitation is low (less than 200 mm per year, and yet enough for supplying streams capable of temporarily carrying the debris resulted from weathering, but insufficient for encouraging the development of a vegetal cover meant to protect the soil blanket against eroding agents. The drought is a major and permanent climatic risk for the Dobrudja territory as a whole and for South Dobrudja in particular, a territory where hydrographic network is underdeveloped, streams are ephemeral, and semi-endorheic areas are well developed. When the period of moisture deficiency lasts longer, it can bring about a significant water imbalance, which results in crop losses or restrictions in water consumption, thus leading to a number of economic problems. Under the circumstances, the risk of aridity expansion is significant, this being the reason why a better water management system in Romania is urgently needed. In the last decades, the numerous specialty studies undertaken in the area have emphasized an intensification of the process of dryness, because atmospheric and pedological droughts have become more and more serious. Romania is a member of the United Nations Convention to Combat Desertification (UNCCD and the World Meteorological Organization (WMO. It actively participates within the drought management network and the Drought Management Center for Southeastern Europe, which comprises 11 countries. The scope is to work together and exchange experience with the neighboring countries that have recorded positive results and acquired a rich experience in terms of drought management. The employment of appropriate pluvial indices in identifying the areas prone to aridity may prove to be convenient tool for finding practical solutions meant to mitigate the impact of this phenomenon on the local communities living in South Dobrudja.

  12. Analysis list: Arid1a [Chip-atlas[Archive

    Lifescience Database Archive (English)

    Full Text Available Arid1a Adipocyte + mm9 http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/target/Arid1a....1.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/target/Arid1a.5.tsv http://dbarchive.biosciencedbc.jp/...kyushu-u/mm9/target/Arid1a.10.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/colo/Arid1a.Adipocyte.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/colo/Adipocyte.gml ...

  13. Morphological modeling of terrains and volume data

    CERN Document Server

    Comic, Lidija; Magillo, Paola; Iuricich, Federico

    2014-01-01

    This book describes the mathematical background behind discrete approaches to morphological analysis of scalar fields, with a focus on Morse theory and on the discrete theories due to Banchoff and Forman. The algorithms and data structures presented are used for terrain modeling and analysis, molecular shape analysis, and for analysis or visualization of sensor and simulation 3D data sets. It covers a variety of application domains including geography, geology, environmental sciences, medicine and biology. The authors classify the different approaches to morphological analysis which are all ba

  14. Revolutionary High Mobility Rovers for Rugged Terrain

    Science.gov (United States)

    Clark, P. E.; Curtis, S. A.; Rilee, M. L.; Cheung, C. Y.; Wesenberg, R. P.; Dorband, J. E.; Lunsford, A. W.

    2006-05-01

    Reconfigurable architecture is essential in exploration because reaching features of the great potential interest, whether searching for life in volcanic terrain or water in at the bottom of craters, will require crossing a wide range of terrains. Such areas of interest are largely inaccessible to permanently appendaged vehicles. For example, morphology and geochemistry of interior basins, walls, and ejecta blankets of volcanic or impact structures must all be studied to understand the nature of a geological event. One surface might be relatively flat and navigable, while another could be rough, variably sloping, broken, or dominated by unconsolidated debris. To be totally functional, structures must form pseudo-appendages varying in size, rate, and manner of deployment (gait). We have already prototyped a simple robotic walker from a single reconfigurable tetrahedron (with struts as sides and nodes as apices) capable of tumbling and are simulating and building a prototype of the more evolved 12Tetrahedral Walker (Autonomous Moon or Mars Investigator) which has interior nodes for payload, more continuous motion, and is commandable through a user friendly interface. We are currently developing a more differentiated architecture to form detachable, reconfigurable, reshapable linearly extendable bodies to act as manual assistant subsystems on rovers, with extensions terminating in a wider range of sensors. We are now simulating gaits for and will be building a prototype rover arm. Ultimately, complex continuous n-tetrahedral structures will have deployable outer skin, and even higher degrees of freedom. Tetrahedral rover advantages over traditional wheeled or tread robots are being demonstrated and include abilities to: 1) traverse terrain more rugged in terms of slope, roughness, and obstacle size; 2) precisely place and lower instruments into hard-to-reach crevices; 3) sample more locations per unit time; 4) conform to virtually any terrain; 5) avoid falling down or

  15. Quantification of rock slope terrain properties

    Science.gov (United States)

    Volkwein, Axel; Gerber, Werner

    2017-04-01

    Rockfall trajectory simulation codes need information on the terrain properties to formulate appropriate rebound models. Usually, the manuals of rockfall simulation codes give sketches or photographs of terrain samples [1,2]. Based on these the user can select suitable terrains for the simulation area. We now would like to start a discussion whether it is possible to numerically quantify the terrain properties which would make the ground assignment more objective. Different ground properties play a role for the interaction between a falling rock and the ground: • Elastic deformation • plastic deformation • Energy absorption • friction • hardness • roughness • surface vs. underground • etc. The question is now whether it is possible to quantify above parameters and to finally provide tables that contain appropriate simulation parameters. In a first attempt we suggest different methods or parameters that might be evaluated in situ: • Small scale drop tests • Light weight deflectometer (LWD) • Particle sizes • Sliding angle • Particle distribution • Soil cover • Water content Of course, above measurements will never perfectly fit to different mountain slopes. However, if a number of measurements has been made their spreading will give an idea on the natural variability of the ground properties. As an example, the following table gives an idea on how the ME and Evd values vary for different soils. Table 1: LWD measurements on different soil types [3] Ground type Soil layer Soil humidityEvd (median)σ (median)Evd (average) Humus-carb. < 10cm dry 17.4 6.8 15.6 Regosol 10 - 30cm dry 8.6 3.9 9.4 Brownish 30 - 50cm dry 12.1 3.2 11.7 Calcaric 30 - 50cm dry 7.5 3.3 7.0 Acid brownish70 - 100cmdry 7.8 2.1 7.7 Fahlgley 10 - 30cm dry 9.2 4.0 7.7 References [1] Bartelt P et al (2016) RAMMS::rockfall user manual v1.6. SLF, Davos. [2] Dorren L.K.A., 2015. Rockyfor3D (v5.2) revealed - Transparent description of the complete 3D rockfall model. ecoris

  16. Modeling Terrain Impact on Mobile Ad Hoc Networks (MANET) Connectivity

    Science.gov (United States)

    2014-05-01

    Modeling Terrain Impact on Mobile Ad Hoc Networks ( MANET ) Connectivity Lance Joneckis Corinne Kramer David Sparrow David Tate I N S T I T U T E F...SUBTITLE Modeling Terrain Impact on Mobile Ad Hoc Networks ( MANET ) Connectivity 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...1882 ljonecki@ida.org Abstract—Terrain affects connectivity in mobile ad hoc net- works ( MANET ). Both average pairwise link closure and the rate

  17. Numerical modeling of 3-D terrain effect on MT field

    Institute of Scientific and Technical Information of China (English)

    徐世浙; 阮百尧; 周辉; 陈乐寿; 徐师文

    1997-01-01

    Using the boundary element method, the numerical modeling problem of three-dimensional terrain effect on magnetotelluric (MT) field is solved. This modeling technique can be run on PC in the case of adopting special net division. The result of modeling test for 2-D terrain by this modeling technique is basically coincident with that by 2-D modeling technique, but there is a great difference between the results of 3-D and 2-D modeling for 3-D terrain.

  18. Mathematical Modeling Of The Terrain Around A Robot

    Science.gov (United States)

    Slack, Marc G.

    1992-01-01

    In conceptual system for modeling of terrain around autonomous mobile robot, representation of terrain used for control separated from representation provided by sensors. Concept takes motion-planning system out from under constraints imposed by discrete spatial intervals of square terrain grid(s). Separation allows sensing and motion-controlling systems to operate asynchronously; facilitating integration of new map and sensor data into planning of motions.

  19. Gravity Terrain Effect of the Seafloor Topography in Taiwan

    Directory of Open Access Journals (Sweden)

    Lun-Tao Tong Tai-Rong Guo

    2007-01-01

    Full Text Available Gravity terrain correction is used to compensate for the gravitational effects of the topography residual to the Bouguer plate. The seafloor topography off the eastern offshore of Taiwan is extremely rugged, and the depth of the sea bottom could be greater than 5000 m. In order to evaluate the terrain effect caused by the seafloor topography, a modern computer algorithm is used to calculate the terrain correction based on the digital elevation model (DEM.

  20. Climate change scenarios of herbaceous production along an aridity gradient: vulnerability increases with aridity.

    Science.gov (United States)

    Golodets, Carly; Sternberg, Marcelo; Kigel, Jaime; Boeken, Bertrand; Henkin, Zalmen; Seligman, No'am G; Ungar, Eugene D

    2015-04-01

    Climate change is expected to reduce annual precipitation by 20% and increase its standard deviation by 20% in the eastern Mediterranean. We have examined how these changes may affect herbaceous aboveground net primary production (ANPP) and its inter-annual coefficient of variation (CV) in natural rangelands along a desert-Mediterranean precipitation gradient, at five sites representing arid, semi-arid, and Mediterranean-type ecosystems, respectively, all showing positive linear relationships between herbaceous ANPP and annual precipitation. Scenarios of reduced annual precipitation and increased inter-annual precipitation variability were defined by manipulating mean annual precipitation (MAP) and its standard deviation. We simulated precipitation and calculated ANPP using current ANPP-precipitation relationships. Our model predicts that reduced precipitation will strongly reduce ANPP in arid and semi-arid sites. Moreover, the effect of reduced precipitation on the CV of ANPP along the entire gradient may be modified by changes in inter-annual variability in MAP. Reduced precipitation combined with increased precipitation variability was the scenario most relevant to the wet end of the gradient, due to the increased likelihood for both dry and rainy years. In contrast, the scenario most relevant to the arid end of the gradient combined reduced precipitation with decreased precipitation variability, due to the strong effect on mean ANPP. All scenarios increased variability of ANPP along the entire gradient. However, the higher sensitivity of vegetation at arid and semi-arid sites (i.e., lower forage production) to future changes in the precipitation regime emphasizes the need to adapt grazing management in these ecosystems to secure their long-term viability as sustainable rangelands.

  1. UNIFIED REPRESENTATION FOR COLLABORATIVE VISUALIZATION OF PLANETARY TERRAIN DATA Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to apply to planetary terrain mapping an alternative, multiresolution method, subdivision surfaces (subdivs), in place of conventional digital elevation...

  2. T-transformation: traversability analysis for navigation on rugged terrain

    Science.gov (United States)

    Ye, Cang; Borenstein, Johann

    2004-09-01

    In order to maneuver autonomously on rough terrain, a mobile robot must constantly decide whether to traverse or circumnavigate terrain features ahead. This ability is called Obstacle Negotiation (ON). A critical aspect of ON is the so-called traversability analysis, which evaluates the level of difficulty associated with the traversal of the terrain. This paper presents a new method for traversability analysis, called T-transformation. It is implemented in a local terrain map as follows: (1) For each cell in the local terrain map, a square terrain patch is defined that symmetrically overlays the cell; (2) a plane is fitted to the data points in the terrain patch using a least-square approach and the slope of the least-squares plane and the residual of the fit are computed and used to calculate the Traversability Index (TI) for that cell; (3) after each cell is assigned a TI value, the local terrain map is transformed into a traversability map. The traversability map is further transformed into a traversability field histogram where each element represents the overall level of difficulty to move along the corresponding direction. Based on the traversability field histogram our reactive ON system then computes the steering and velocity commands to move the robot toward the intended goal while avoiding areas of poor traversability. The traversability analysis algorithm and the overall ON system were verified by extensive simulation. We verified our method partially through experiments on a Segway Robotics Mobility Platform (RMP), albeit only on flat terrain.

  3. LUNAR TERRAIN AND ALBEDO RECONSTRUCTION FROM APOLLO IMAGERY

    Data.gov (United States)

    National Aeronautics and Space Administration — LUNAR TERRAIN AND ALBEDO RECONSTRUCTION FROM APOLLO IMAGERY ARA V NEFIAN*, TAEMIN KIM, MICHAEL BROXTON, AND ZACH MORATTO Abstract. Generating accurate three...

  4. Tool for Viewing Faults Under Terrain

    Science.gov (United States)

    Siegel, Herbert, L.; Li, P. Peggy

    2005-01-01

    Multi Surface Light Table (MSLT) is an interactive software tool that was developed in support of the QuakeSim project, which has created an earthquake- fault database and a set of earthquake- simulation software tools. MSLT visualizes the three-dimensional geometries of faults embedded below the terrain and animates time-varying simulations of stress and slip. The fault segments, represented as rectangular surfaces at dip angles, are organized into collections, that is, faults. An interface built into MSLT queries and retrieves fault definitions from the QuakeSim fault database. MSLT also reads time-varying output from one of the QuakeSim simulation tools, called "Virtual California." Stress intensity is represented by variations in color. Slips are represented by directional indicators on the fault segments. The magnitudes of the slips are represented by the duration of the directional indicators in time. The interactive controls in MSLT provide a virtual track-ball, pan and zoom, translucency adjustment, simulation playback, and simulation movie capture. In addition, geographical information on the fault segments and faults is displayed on text windows. Because of the extensive viewing controls, faults can be seen in relation to one another, and to the terrain. These relations can be realized in simulations. Correlated slips in parallel faults are visible in the playback of Virtual California simulations.

  5. Parallel path planning in unknown terrains

    Science.gov (United States)

    Prassler, Erwin A.; Milios, Evangelos E.

    1991-03-01

    We present a parallel processing approach to path planning in unknown terrains which combines map-based and sensor-based techniques into a real-time capable navigation system. The method is based on massively parallel computations in a grid of simple processing elements denoted as cells. In the course of a relaxation process a potential distribution is created in the grid which exhibits a monotonous slope from a start cell to the cell corresponding to the robot''s goal position. A shortest path is determined by means of a gradient descent criterion which settles on the steepest descent in the potential distribution. Like high-level path planning algorithms our approach is capable of planning shortest paths through an arbitrarily cluttered large-scale terrain on the basis of its current internal map. Sequentially implemented its complexity is in the order of efficient classical path planning algorithms. Unlike these algorithms however the method is also highly responsive to new obstacles encountered in the terrain. By continuing the planning process during the robot''s locomotion information about previously unknown obstacles immediately affects further path planning without a need to interrupt the ongoing planning process. New obstacles cause distortions of the potential distribution which let the robot find proper detours. By ensuring a monotonous slope in the overall distribution we avoid local minimum effects which may trap a robot in the proximity of an obstacle configuration before it has reached its goal. 1 Until the recent past research on path planning in the presence of obstacles can be assigned to two major categories: map-based high-level planning approaches and sensor-based low-level conLrol approaches. In work such as 12 path planning is treated as a high-level planning task. Assuming that an (accnrae) precompiled map of the terrain is available high-level path planners provide paths which guarantee a collision-free locomotion through an arbitrary

  6. Aridity increases below-ground niche breadth in grass communities

    Science.gov (United States)

    Butterfield, Bradley J.; Bradford, John B.; Munson, Seth M.; Gremer, Jennifer R.

    2017-01-01

    Aridity is an important environmental filter in the assembly of plant communities worldwide. The extent to which root traits mediate responses to aridity, and how they are coordinated with leaf traits, remains unclear. Here, we measured variation in root tissue density (RTD), specific root length (SRL), specific leaf area (SLA), and seed size within and among thirty perennial grass communities distributed along an aridity gradient spanning 190–540 mm of climatic water deficit (potential minus actual evapotranspiration). We tested the hypotheses that traits exhibited coordinated variation (1) among species, as well as (2) among communities varying in aridity, and (3) functional diversity within communities declines with increasing aridity, consistent with the “stress-dominance” hypothesis. Across communities, SLA and RTD exhibited a coordinated response to aridity, shifting toward more conservative (lower SLA, higher RTD) functional strategies with increasing aridity. The response of SRL to aridity was more idiosyncratic and was independent of variation in SLA and RTD. Contrary to the stress-dominance hypothesis, the diversity of SRL values within communities increased with aridity, while none of the other traits exhibited significant diversity responses. These results are consistent with other studies that have found SRL to be independent of an SLA–RTD axis of functional variation and suggest that the dynamic nature of soil moisture in arid environments may facilitate a wider array of resource capture strategies associated with variation in SRL.

  7. Rainfall Characterization In An Arid Area

    OpenAIRE

    Bazaraa, A. S.; Ahmed, Shamim

    1991-01-01

    The objective of this work is to characterize the rainfall in Doha which lies in an arid region. The rainfall data included daily rainfall depth since 1962 and the hyetographs of the individual storms since 1976. The rainfall is characterized by high variability and severe thunderstorms which are of limited geographical extent. Four probability distributions were used to fit the maximum rainfall in 24 hours and the annual rainfall depth. The extreme value distribution was found to have the be...

  8. VOCs in Arid soils: Technology summary

    Energy Technology Data Exchange (ETDEWEB)

    1994-02-01

    The Volatile Organic Compounds In Arid Soils Integrated Demonstration (VOC-Arid ID) focuses on technologies to clean up volatile organic compounds and associated contaminants in soil and groundwater at arid sites. The initial host site is the 200 West Area at DOE`s Hanford site in southeastern Washington state. The primary VOC contaminant is carbon tetrachloride, in association with heavy metals and radionuclides. An estimated 580--920 metric tons of carbon tetrachloride were disposed of between 1955 and 1973, resulting in extensive soil and groundwater contamination. The VOC-Arid ID schedule has been divided into three phases of implementation. The phased approach provides for: rapid transfer of technologies to the Environmental Restoration (EM-40) programs once demonstrated; logical progression in the complexity of demonstrations based on improved understanding of the VOC problem; and leveraging of the host site EM-40 activities to reduce the overall cost of the demonstrations. During FY92 and FY93, the primary technology demonstrations within the ID were leveraged with an ongoing expedited response action at the Hanford 200 West Area, which is directed at vapor extraction of VOCs from the vadose (unsaturated) zone. Demonstration efforts are underway in the areas of subsurface characterization including: drilling and access improvements, off-gas and borehole monitoring of vadose zone VOC concentrations to aid in soil vapor extraction performance evaluation, and treatment of VOC-contaminated off-gas. These current demonstration efforts constitute Phase 1 of the ID and, because of the ongoing vadose zone ERA, can result in immediate transfer of successful technologies to EM-40.

  9. Single-Frame Terrain Mapping Software for Robotic Vehicles

    Science.gov (United States)

    Rankin, Arturo L.

    2011-01-01

    This software is a component in an unmanned ground vehicle (UGV) perception system that builds compact, single-frame terrain maps for distribution to other systems, such as a world model or an operator control unit, over a local area network (LAN). Each cell in the map encodes an elevation value, terrain classification, object classification, terrain traversability, terrain roughness, and a confidence value into four bytes of memory. The input to this software component is a range image (from a lidar or stereo vision system), and optionally a terrain classification image and an object classification image, both registered to the range image. The single-frame terrain map generates estimates of the support surface elevation, ground cover elevation, and minimum canopy elevation; generates terrain traversability cost; detects low overhangs and high-density obstacles; and can perform geometry-based terrain classification (ground, ground cover, unknown). A new origin is automatically selected for each single-frame terrain map in global coordinates such that it coincides with the corner of a world map cell. That way, single-frame terrain maps correctly line up with the world map, facilitating the merging of map data into the world map. Instead of using 32 bits to store the floating-point elevation for a map cell, the vehicle elevation is assigned to the map origin elevation and reports the change in elevation (from the origin elevation) in terms of the number of discrete steps. The single-frame terrain map elevation resolution is 2 cm. At that resolution, terrain elevation from 20.5 to 20.5 m (with respect to the vehicle's elevation) is encoded into 11 bits. For each four-byte map cell, bits are assigned to encode elevation, terrain roughness, terrain classification, object classification, terrain traversability cost, and a confidence value. The vehicle s current position and orientation, the map origin, and the map cell resolution are all included in a header for each

  10. 14 CFR 93.311 - Minimum terrain clearance.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Minimum terrain clearance. 93.311 Section 93.311 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED... of Grand Canyon National Park, AZ § 93.311 Minimum terrain clearance. Except in an emergency,...

  11. Colour based off-road environment and terrain type classification

    NARCIS (Netherlands)

    Jansen, P.; Mark, W. van der; Heuvel, J.C. van den; Groen, F.C.A.

    2005-01-01

    Terrain classification is an important problem that still remains to be solved for off-road autonomous robot vehicle guidance. Often, obstacle detection systems are used which cannot distinguish between solid obstacles such as rocks or soft obstacles such as tall patches of grass. Terrain classifica

  12. Design Of An Omnidirectional Mobile Robot For Rough Terrain

    Science.gov (United States)

    2007-09-01

    rough terrain, isotropy, mobile robots , design I. INTRODUCTION Mobile robots are finding increasing use in military [1], disaster recovery [2], and...exploration applications [3]. These applications frequently require operation in rough, unstructured terrain. Currently, most mobile robots designed...perform some maneuvers, such as lateral displacement. Omnidirectional mobile robots could potentially navigate faster and more robustly through

  13. Terrain Perception in a Shape Shifting Rolling-Crawling Robot

    Directory of Open Access Journals (Sweden)

    Fuchida Masataka

    2016-09-01

    Full Text Available Terrain perception greatly enhances the performance of robots, providing them with essential information on the nature of terrain being traversed. Several living beings in nature offer interesting inspirations which adopt different gait patterns according to nature of terrain. In this paper, we present a novel terrain perception system for our bioinspired robot, Scorpio, to classify the terrain based on visual features and autonomously choose appropriate locomotion mode. Our Scorpio robot is capable of crawling and rolling locomotion modes, mimicking Cebrenus Rechenburgi, a member of the huntsman spider family. Our terrain perception system uses Speeded Up Robust Feature (SURF description method along with color information. Feature extraction is followed by Bag of Word method (BoW and Support Vector Machine (SVM for terrain classification. Experiments were conducted with our Scorpio robot to establish the efficacy and validity of the proposed approach. In our experiments, we achieved a recognition accuracy of over 90% across four terrain types namely grass, gravel, wooden deck, and concrete.

  14. 75 FR 5767 - All Terrain Vehicle Chinese Language Webinar; Meeting

    Science.gov (United States)

    2010-02-04

    ... COMMISSION All Terrain Vehicle Chinese Language Webinar; Meeting AGENCY: Consumer Product Safety Commission... Terrain Vehicle Chinese Language Webinar. The webinar will focus on CPSC's requirements for ATV's... February 4, 2010 at 6:00 am Eastern Standard Time. Location: The meeting will be held live via...

  15. Stereo based Obstacle Detection with Uncertainty in Rough Terrain

    NARCIS (Netherlands)

    Mark, W. van der; Heuvel, J.C. van den; Groen, F.C.A.

    2007-01-01

    Autonomous robot vehicles that operate in offroad terrain should avoid obstacle hazards. In this paper we present a stereo vision based method that is able to cluster reconstructed terrain points into obstacles by evaluating their relative angles and distances. In our approach, constraints are enfor

  16. 47 CFR 80.759 - Average terrain elevation.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Average terrain elevation. 80.759 Section 80... Average terrain elevation. (a)(1) Draw radials from the antenna site for each 45 degrees of azimuth.... (d) Average the values by adding them and dividing by the number of readings along each radial....

  17. Arid sites stakeholder participation in evaluating innovative technologies: VOC-Arid Site Integrated Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, T.S.; McCabe, G.H.; Brockbank, B.R. [and others

    1995-05-01

    Developing and deploying innovative environmental cleanup technologies is an important goal for the U.S. Department of Energy (DOE), which faces challenging remediation problems at contaminated sites throughout the United States. Achieving meaningful, constructive stakeholder involvement in cleanup programs, with the aim of ultimate acceptance of remediation decisions, is critical to meeting those challenges. DOE`s Office of Technology Development sponsors research and demonstration of new technologies, including, in the past, the Volatile Organic Compounds Arid Site Integrated Demonstration (VOC-Arid ID), hosted at the Hanford Site in Washington State. The purpose of the VOC-Arid ID has been to develop and demonstrate new technologies for remediating carbon tetrachloride and other VOC contamination in soils and ground water. In October 1994 the VOC-Arid ID became a part of the Contaminant Plume Containment and Remediation Focus Area (Plume Focus Area). The VOC Arid ID`s purpose of involving stakeholders in evaluating innovative technologies will now be carried on in the Plume Focus Area in cooperation with Site Technology Coordination Groups and Site Specific Advisory Boards. DOE`s goal is to demonstrate promising technologies once and deploy those that are successful across the DOE complex. Achieving that goal requires that the technologies be acceptable to the groups and individuals with a stake in DOE facility cleanup. Such stakeholders include groups and individuals with an interest in cleanup, including regulatory agencies, Native American tribes, environmental and civic interest groups, public officials, environmental technology users, and private citizens. This report documents the results of the stakeholder involvement program, which is an integral part of the VOC-Arid ID.

  18. Satellite-Based Monitoring of Decadal Soil Salinization and Climate Effects in a Semi-arid Region of China

    Institute of Scientific and Technical Information of China (English)

    WANG Hesong; JIA Gensuo

    2012-01-01

    Soil salinization is a common phenomenon that affects both the environment and the socio-economy in arid and semi-arid regions; it is also an important aspect of land cover change.In this study,we integrated multi-sensor remote sensing data with a field survey to analyze processes of soil salinization in a semi-arid area in China from 1979 to 2009. Generally,the area of salt-affected soils increased by 0.28% per year with remarkable acceleration from 1999 to 2009 (0.42% increase per year).In contrast,the area of surface water bodies showed a decreasing trend (-0.08% per year) in the same period.Decreases in precipitation and increases in aridity due to annual (especially summer) warming provided a favorable condition for soil salinization. The relatively flat terrain favored waterlogging at the surface,and continuous drought facilitated upward movement of soil water and accumulation of surface saline and calcium. Meanwhile,land-use practices also played a crucial role in accelerating soil salinization.The conversion to cropland from natural vegetation greatly increased the demand for groundwater irrigation and aggravated the process of soil salinization.Furthermore,there are potential feedbacks of soil salinization to regional climate.The salinization of soils can limit the efficiency of plant water use as well as photosynthesis; therefore,it reduces the amount of carbon sequestrated by terrestrial ecosystem.Soil salinization also reduces the absorbed solar radiation by increasing land surface albedo.Such conversions of land cover significantly change the energy and water balance between land and atmosphere.

  19. Analysis list: ARID3A [Chip-atlas[Archive

    Lifescience Database Archive (English)

    Full Text Available ARID3A Blood,Liver + hg19 http://dbarchive.biosciencedbc.jp/kyushu-u/hg19/target/ARID3A.1.tsv http:...//dbarchive.biosciencedbc.jp/kyushu-u/hg19/target/ARID3A.5.tsv http://dbarchive.biosciencedb...c.jp/kyushu-u/hg19/target/ARID3A.10.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/hg19/colo/ARID3A.Blood.tsv,http:...//dbarchive.biosciencedbc.jp/kyushu-u/hg19/colo/ARID3A.Liver.tsv http://db...archive.biosciencedbc.jp/kyushu-u/hg19/colo/Blood.gml,http://dbarchive.biosciencedbc.jp/kyushu-u/hg19/colo/Liver.gml ...

  20. Statistical Modeling of Robotic Random Walks on Different Terrain

    Science.gov (United States)

    Naylor, Austin; Kinnaman, Laura

    Issues of public safety, especially with crowd dynamics and pedestrian movement, have been modeled by physicists using methods from statistical mechanics over the last few years. Complex decision making of humans moving on different terrains can be modeled using random walks (RW) and correlated random walks (CRW). The effect of different terrains, such as a constant increasing slope, on RW and CRW was explored. LEGO robots were programmed to make RW and CRW with uniform step sizes. Level ground tests demonstrated that the robots had the expected step size distribution and correlation angles (for CRW). The mean square displacement was calculated for each RW and CRW on different terrains and matched expected trends. The step size distribution was determined to change based on the terrain; theoretical predictions for the step size distribution were made for various simple terrains. It's Dr. Laura Kinnaman, not sure where to put the Prefix.

  1. Terrain Identification for Prosthetic Knees Based on Electromyographic Signal Features

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The features of electromyographic (EMG) signals were investigated while people walking on different terrains, including up and down slopes, up and down stairs, and during level walking at different speeds. The features were used to develop a terrain identification method. The technology can be used to develop an intelligent transfemoral prosthetic limb with terrain identification capability. The EMG signals from 8 hip muscles of 13 healthy persons were recorded as they walked on the different terrains. The signals from the sound side of a transfemoral amputee were also recorded. The features of these signals were obtained using data processing techniques with an identification process developed for the identification of the terrain type. The procedure was simplified by using only the signals from three muscles. The identification process worked well in an intelligent prosthetic knee in a laboratory setting.

  2. Learning Long-range Terrain Perception for Autonomous Mobile Robots

    Directory of Open Access Journals (Sweden)

    Mingjun Wang

    2010-02-01

    Full Text Available Long-range terrain perception has a high value in performing efficient autonomous navigation and risky intervention tasks for field robots, such as earlier recognition of hazards, better path planning, and higher speeds. However, Stereo-based navigation systems can only perceive near-field terrain due to the nearsightedness of stereo vision. Many near-to-far learning methods, based on regions' appearance features, are proposed to predict the far-field terrain. We proposed a statistical prediction framework to enhance long-range terrain perception for autonomous mobile robots. The main difference between our solution and other existing methods is that our framework not only includes appearance features as its prediction basis, but also incorporates spatial relationships between terrain regions in a principled way. The experiment results show that our framework outperforms other existing approaches in terms of accuracy, robustness and adaptability to dynamic unstructured outdoor environments.

  3. Conically scanning lidar error in complex terrain

    Directory of Open Access Journals (Sweden)

    Ferhat Bingöl

    2009-05-01

    Full Text Available Conically scanning lidars assume the flow to be homogeneous in order to deduce the horizontal wind speed. However, in mountainous or complex terrain this assumption is not valid implying a risk that the lidar will derive an erroneous wind speed. The magnitude of this error is measured by collocating a meteorological mast and a lidar at two Greek sites, one hilly and one mountainous. The maximum error for the sites investigated is of the order of 10 %. In order to predict the error for various wind directions the flows at both sites are simulated with the linearized flow model, WAsP Engineering 2.0. The measurement data are compared with the model predictions with good results for the hilly site, but with less success at the mountainous site. This is a deficiency of the flow model, but the methods presented in this paper can be used with any flow model.

  4. Enveloping Relief Surfaces of Landslide Terrain

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Two relief surfaces that envelop the rock fall region in a part of Garhwal Himalayas around Chamoli have been identified. Relative relief and absolute relief have been analyzed and the enveloping surfaces recorded at two levels of relief in the landscape. All landslide activity lies within these surfaces. The lower enveloping surface (800 m) dips due south by 7-8 degrees, due to an elevation rise of 100 meters within 12 km from south to north, i.e., a gradient of 8 percent. The nature of the surface is smooth. The upper enveloping surface (> 2500 m) is almost parallel to the lower one but its surface is undulatory due to landslides and denudation. The area has been a seismically active region and has undergone seismic activity up until recently, as evidenced by the Chamoli earthquake of 29th March 1999. The effects of earthquakes are seen at higher levels in the form of landslide imprints on the terrain.

  5. Maintaining Contour Trees of Dynamic Terrains

    DEFF Research Database (Denmark)

    Agarwal, Pankaj K.; Mølhave, Thomas; Revsbæk, Morten

    2015-01-01

    We study the problem of maintaining the contour tree T of a terrain Sigma, represented as a triangulated xy-monotone surface, as the heights of its vertices vary continuously with time. We characterize the combinatorial changes in T and how they relate to topological changes in Sigma. We present...... a kinetic data structure (KDS) for maintaining T efficiently. It maintains certificates that fail, i.e., an event occurs, only when the heights of two adjacent vertices become equal or two saddle vertices appear on the same contour. Assuming that the heights of two vertices of Sigma become equal only O(1......) times and these instances can be computed in O(1) time, the KDS processes O(kappa + n) events, where n is the number of vertices in Sigma and kappa is the number of events at which the combinatorial structure of T changes, and processes each event in O(log n) time. The KDS can be extended to maintain...

  6. Digital terrain modeling with the Chebyshev polynomials

    CERN Document Server

    Florinsky, I V

    2015-01-01

    Mathematical problems of digital terrain analysis include interpolation of digital elevation models (DEMs), DEM generalization and denoising, and computation of morphometric variables by calculation of partial derivatives of elevation. Traditionally, these procedures are based on numerical treatments of two-variable discrete functions of elevation. We developed a spectral analytical method and algorithm based on high-order orthogonal expansions using the Chebyshev polynomials of the first kind with the subsequent Fejer summation. The method and algorithm are intended for DEM analytical treatment, such as, DEM global approximation, denoising, and generalization as well as computation of morphometric variables by analytical calculation of partial derivatives. To test the method and algorithm, we used a DEM of the Northern Andes including 230,880 points (the elevation matrix 480 $\\times$ 481). DEMs were reconstructed with 480, 240, 120, 60, and 30 expansion coefficients. The first and second partial derivatives ...

  7. Groundwater flood hazards in lowland karst terrains

    Science.gov (United States)

    Naughton, Owen; McCormack, Ted

    2016-04-01

    The spatial and temporal complexity of flooding in karst terrains pose unique flood risk management challenges. Lowland karst landscapes can be particularly susceptible to groundwater flooding due to a combination of limited drainage capacity, shallow depth to groundwater and a high level of groundwater-surface water interactions. Historically the worst groundwater flooding to have occurred in the Rep. of Ireland has been centred on the Gort Lowlands, a karst catchment on the western coast of Ireland. Numerous notable flood events have been recorded throughout the 20th century, but flooding during the winters of 2009 and 2015 were the most severe on record, inundating an area in excess of 20km2 and causing widespread and prolonged disruption and damage to property and infrastructure. Effective flood risk management requires an understanding of the recharge, storage and transport mechanisms during flood conditions, but is often hampered by a lack of adequate data. Using information gathered from the 2009 and 2015 events, the main hydrological and geomorphological factors which influence flooding in this complex lowland karst groundwater system under are elucidated. Observed flood mechanisms included backwater flooding of sinks, overland flow caused by the overtopping of sink depressions, high water levels in turlough basins, and surface ponding in local epikarst watersheds. While targeted small-scale flood measures can locally reduce the flood risk associated with some mechanisms, they also have the potential to exacerbate flooding down-catchment and must be assessed in the context of overall catchment hydrology. This study addresses the need to improve our understanding of groundwater flooding in karst terrains, in order to ensure efficient flood prevention and mitigation in future and thus help achieve the aims of the EU Floods Directive.

  8. Predicting Potential Evaporation in Topographically Complex Terrain

    Science.gov (United States)

    Koohafkan, M.; Thompson, S. E.; Hamilton, M. P.

    2012-12-01

    Predicting and understanding the water cycle in topographically complex terrain poses challenges for upscaling point-scale measurements of water and energy balance and for downscaling observations made from remote sensing or predictions made via global circulation models. This study evaluates hydrologic and climate data drawn from a spatially-distributed wireless sensor network at the Blue Oak Ranch Reserve near San Jose, California to investigate the influence of topographic variation, landscape position, and local ecology (vegetation) on one core component of the water balance: potential evaporation. High-resolution observations of solar radiation, ambient temperature, wind speed, and relative humidity are combined with canopy maps generated from LiDAR flyovers to develop spatially-distributed predictions of potential evaporation. These data are compared to estimates of EP based on inverse modeling of surface soil moisture data. Preliminary results suggest that the spatial structure of microclimate at Blue Oak Ranch Reserve is dominated by variations around the elevation gradient, with strong nocturnal inversions hypothesized to reflect the influence of the coastal marine layer. Estimates of EP based on the Penman-Monteith equation suggest that EP could vary by up to a factor of 5 across the site, with differences in vapor pressure deficit and canopy height largely responsible for this variability. The results suggest that a) large differences in the timing and magnitude of water stress could arise in topographically complex terrain due to localized differences in energy balance, and b) both localized and regional effects need to be accounted for when downscaling climate data over topographically complex sites. 2) Color map showing preliminary estimates of annual EP incorporating canopy information (spatially-distributed values of aerodynamic resistance and LAI) drawn from LiDAR imagery. The effect of the resistance on the dynamics is striking in its ability to

  9. Self-Supervised Learning to Visually Detect Terrain Surfaces for Autonomous Robots Operating in Forested Terrain

    Science.gov (United States)

    2012-01-01

    classified. Stereo algorithms can generate 3D point clouds at relatively high frequency (sev- eral hertz). However, the resulting depth map is typically...10.1002/rob 280 • Journal of Field Robotics—2012 (a) (b) (c) (d) Figure 1. Experimental robot platform, (a) lateral view and (b) top view. (c) Perception ... monocular road detection in desert terrain. In Proceedings of robotics: Science and systems, Philadelphia, USA. Elmqvist, M. (2002). Ground surface

  10. Analysis list: Arid3a [Chip-atlas[Archive

    Lifescience Database Archive (English)

    Full Text Available Arid3a Pluripotent stem cell + mm9 http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/target/Ari...d3a.1.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/target/Arid3a.5.tsv http://dbarchive.biosc...iencedbc.jp/kyushu-u/mm9/target/Arid3a.10.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/colo/Arid3a.Pluri...potent_stem_cell.tsv http://dbarchive.biosciencedbc.jp/kyushu-u/mm9/colo/Pluripotent_stem_cell.gml ...

  11. On predicting debris flows in arid mountain belts

    Science.gov (United States)

    Stolle, Amelie; Langer, Maria; Blöthe, Jan Henrik; Korup, Oliver

    2015-03-01

    The use of topographic metrics for estimating the susceptibility to, and reconstructing the characteristics of, debris flows has a long research tradition, although largely devoted to humid mountainous terrain. The exceptional 2010 monsoonal rainstorms in the high-altitude mountain desert of Ladakh and Zanskar, NW India, were a painful reminder of how susceptible arid regions are to rainfall-triggered flash floods, landslides, and debris flows. The rainstorms of August 4-6 triggered numerous debris flows, killing 182 people, devastating 607 houses, and more than 10 bridges around Ladakh's capital of Leh. The lessons from this disaster motivated us to revisit methods of predicting (a) flow parameters such as peak discharge and maximum velocity from field and remote sensing data, and (b) the susceptibility to debris flows from catchment morphometry. We focus on quantifying uncertainties tied to these approaches. Comparison of high-resolution satellite images pre- and post-dating the 2010 rainstorm reveals the extent of damage and catastrophic channel widening. Computations based on these geomorphic markers indicate maximum flow velocities of 1.6-6.7 m s- 1 with runout of up to ~ 10 km on several alluvial fans that sustain most of the region's settlements. We estimate median peak discharges of 310-610 m3 s- 1, which are largely consistent with previous estimates. Monte Carlo-based error propagation for a single given flow-reconstruction method returns a variance in discharge similar to one derived from juxtaposing several different flow reconstruction methods. We further compare discriminant analysis, classification tree modelling, and Bayesian logistic regression to predict debris-flow susceptibility from morphometric variables of 171 catchments in the Ladakh Range. These methods distinguish between fluvial and debris flow-prone catchments at similar success rates, but Bayesian logistic regression allows quantifying uncertainties and relationships between potential

  12. Remote Sensing Parameterization of Land Surface Heat Fluxes over Arid and Semi-arid Areas

    Institute of Scientific and Technical Information of China (English)

    马耀明; 王介民; 黄荣辉; 卫国安; MassimoMENENTI; 苏中波; 胡泽勇; 高峰; 文军

    2003-01-01

    Dealing with the regional land surfaces heat fluxes over inhomogeneous land surfaces in arid and semi-arid areas is an important but not an easy issue. In this study, one parameterization method based on satellite remote sensing and field observations is proposed and tested for deriving the regional land surface heat fluxes over inhomogeneous landscapes. As a case study, the method is applied to the Dunhuang experimental area and the HEIFE (Heihe River Field Experiment, 1988-1994) area. The Dunhuang area is selected as a basic experimental area for the Chinese National Key Programme for Developing Basic Sciences: Research on the Formation Mecbanism and Prediction Theory of Severe Climate Disaster in China (G1998040900, 1999-2003). The four scenes of Landsat TM data used in this study are 3 June 2000,22 August 2000, and 29 January 2001 for the Dunhuang area and 9 July 1991 for the HEIFE area. The regional distributions of land surface variables, vegetation variables, and heat fluxes over inhomogeneous landscapes in arid and semi-arid areas are obtained in this study.

  13. Mobile robots traversability awareness based on terrain visual sensory data fusion

    Science.gov (United States)

    Shirkhodaie, Amir

    2007-04-01

    In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on

  14. Terrain aided navigation for autonomous underwater vehicles with coarse maps

    Science.gov (United States)

    Zhou, Ling; Cheng, Xianghong; Zhu, Yixian

    2016-09-01

    Terrain aided navigation (TAN) is a form of geophysical localization technique for autonomous underwater vehicles (AUVs) operating in GPS-denied environments. TAN performance on sensor-rich AUVs has been evaluated in sea trials. However, many challenges remain before TAN can be successfully implemented on sensor-limited AUVs, especially with coarse maps. To improve TAN performance over coarse maps, a Gaussian process (GP) is proposed for the modeling of bathymetric terrain and integrated into the particle filter (GP-PF). GP is applied to provide not only the bathymetric value prediction through learning a set of bathymetric data from coarse maps but also the variance of the prediction. As a measurement update, calculated on bathymetric deviation is performed through the PF to obtain absolute and bounded positioning accuracy. Through the analysis of TAN performance on experimental data for two different terrains with map resolutions of 10-50 m, both the ability of the proposed model to represent the actual bathymetric terrain with accuracy and the effect of the GP-PF for TAN on sensor-limited systems in suited terrain are demonstrated. The experiment results further verify that there is an inverse relationship between the coarseness of the map and the overall TAN accuracy in rough terrains, but there is hardly any relationship between them in relatively flat terrains.

  15. From digital elevation model data to terrain depiction data

    Science.gov (United States)

    Helmetag, Arnd; Smietanski, Guillaume; Baumgart, Michael; Kubbat, Wolfgang

    1999-07-01

    The analysis of accidents focused our work on the avoidance of 'Controlled Flight Into Terrain' caused by insufficient situation awareness. Analysis of safety concepts led us to the design of the proposed synthetic vision system that will be described. Since most information on these 3D-Displays is shown in a graphical way, it can intuitively be seized by the pilot. One key element of SVS is terrain depiction, that is the topic of this paper. Real time terrain depiction has to face two requirements. On the one hand spatial awareness requires recognition of synthetic environment demanding characteristics. On the other hand the number of rendered polygons has to be minimized due to limitations of real time image generation performance. Visual quality can significantly be enhanced if equidistant data like Digital Elevation Model data (DEM) are vectorized. One method of data vectorization will be explained in detail and advantages will be mentioned. In Virtual Reality (VR) applications, conventional decimation software degrades the visual quality of geometry that is compensated by complex textures and lighting. Since terrain decimated with those tools looses its characteristics, and textures are not acceptable for several reasons, a terrain specific decimation has to be performed. How can a Digital Elevation Model (DEM) be decimated without decreasing the visualization value? In this paper, extraction of terrain characteristics and adapted decimation will be proposed. Steps from DEM to Terrain Depiction Data (TDD) are discussed in detail.

  16. Visible and infrared properties of unaltered to weathered rocks from Precambrian granite-greenstone terrains of the West African Craton

    Science.gov (United States)

    Metelka, Václav; Baratoux, Lenka; Jessell, Mark W.; Naba, Séta

    2015-12-01

    In situ and laboratory 0.35 μm-2.5 μm spectra of rocks from a Paleoproterozoic granite-greenstone terrain along with its Neoproterozoic sedimentary cover and derived regolith materials were examined in western Burkina Faso. The reflectance spectra show the influence of typical arid to semi-arid weathering with the formation of desert varnish, iron films, and dust coatings. Fe and Mg-OH absorption features related to chlorite, amphibole, pyroxene, epidote, and biotite are observable in the mafic and intermediate meta-volcanic rocks as well as in the granodiorites and tonalites. Al-OH absorption caused by kaolinite, smectite, illite/muscovite are typical for meta-volcano-sedimentary schists, Tarkwaian-type detrital meta-sediments, sandstones of the Taoudeni basin, all of the weathered surfaces and regolith materials. Ferric and ferrous iron absorptions related to both primary rock-forming minerals and secondary weathering minerals (goethite, hematite) were observed in most of the sampled materials. The results show that although weathering alters the spectral signature of the fresh rock, indicative absorption features located in the short wave infrared region remain detectable. In addition, spectra of soils partially reflect the mineral composition of the weathered rock surfaces. The analysis of the hyperspectral data shows the potential of differentiating between the sampled surfaces. The library presents a primary database for the geological and regolith analysis of remote sensing data in West Africa.

  17. Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

    Science.gov (United States)

    Bajracharya, Max; Howard, Andrew B.; Matthies, Larry H.

    2009-01-01

    Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

  18. MRO CTX-based Digital Terrain Models

    Science.gov (United States)

    Dumke, Alexander

    2016-04-01

    In planetary surface sciences, digital terrain models (DTM) are paramount when it comes to understanding and quantifying processes. In this contribution an approach for the derivation of digital terrain models from stereo images of the NASA Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) are described. CTX consists of a 350 mm focal length telescope and 5000 CCD sensor elements and is operated as pushbroom camera. It acquires images with ~6 m/px over a swath width of ~30 km of the Mars surface [1]. Today, several approaches for the derivation of CTX DTMs exist [e. g. 2, 3, 4]. The discussed approach here is based on established software and combines them with proprietary software as described below. The main processing task for the derivation of CTX stereo DTMs is based on six steps: (1) First, CTX images are radiometrically corrected using the ISIS software package [5]. (2) For selected CTX stereo images, exterior orientation data from reconstructed NAIF SPICE data are extracted [6]. (3) In the next step High Resolution Stereo Camera (HRSC) DTMs [7, 8, 9] are used for the rectification of CTX stereo images to reduce the search area during the image matching. Here, HRSC DTMs are used due to their higher spatial resolution when compared to MOLA DTMs. (4) The determination of coordinates of homologous points between stereo images, i.e. the stereo image matching process, consists of two steps: first, a cross-correlation to obtain approximate values and secondly, their use in a least-square matching (LSM) process in order to obtain subpixel positions. (5) The stereo matching results are then used to generate object points from forward ray intersections. (6) As a last step, the DTM-raster generation is performed using software developed at the German Aerospace Center, Berlin. Whereby only object points are used that have a smaller error than a threshold value. References: [1] Malin, M. C. et al., 2007, JGR 112, doi:10.1029/2006JE002808 [2] Broxton, M. J. et al

  19. New Vocabulary: Araneiform and Lace Terrains

    Science.gov (United States)

    2007-01-01

    [figure removed for brevity, see original site] [figure removed for brevity, see original site] Figure 1Figure 2 The south polar terrain on Mars contains landforms unlike any that we see on Earth, so much that a new vocabulary is required to describe them. The word 'araneiform' means 'spider-like.' There are radially organized channels on Mars that look spider-like, but we don't want to confuse anyone by talking about 'spiders' when we really mean 'channels,' not 'bugs.' The first subimage (figure 1) shows an example of 'connected araneiform topography,' terrain that is filled with spider-like channels whose arms branch and connect to each other. Gas flows through these channels until it encounters a vent, where is escapes out to the atmosphere, carrying dust along with it. The dark dust is blown around by the prevailing wind. The second subimage (figure 2) shows a different region of the same image where the channels are not radially organized. In this region they form a dense tangled network of tortuous strands. We refer to this as 'lace.' Observation Geometry Image PSP_002651_0930 was taken by the High Resolution Imaging Science Experiment (HiRISE) camera onboard the Mars Reconnaissance Orbiter spacecraft on 18-Feb-2007. The complete image is centered at -86.9 degrees latitude, 97.2 degrees East longitude. The range to the target site was 268.7 km (167.9 miles). At this distance the image scale is 53.8 cm/pixel (with 2 x 2 binning) so objects 161 cm across are resolved. The image shown here has been map-projected to 50 cm/pixel . The image was taken at a local Mars time of 04:56 PM and the scene is illuminated from the west with a solar incidence angle of 86 degrees, thus the sun was about 4 degrees above the horizon. At a solar longitude of 186.4 degrees, the season on Mars is Northern Autumn.

  20. AFTI/F16 terrain-aided navigation system

    Energy Technology Data Exchange (ETDEWEB)

    Boozer, D.D.; Lau, M.K.; Fellerhoff, J.R.

    1985-01-01

    A recursive, real-time, terrain-aided navigation algorithm, AFTI/SITAN, was designed for use on the Advanced Fighter Technology Integration (AFTI) F16 aircraft. The algorithm implemented in a Zilog Z8001 microprocessor, can reliably locate the aircraft's position within a 926-m (0.5 nm) CEP circle and accurately estimate its position continuously (3 Hz). The design and execution of the algorithm are described, and simulation results using actual flight test data are presented. A median accuracy of less than 100 m was achieved over gently rolling, forested terrain using cartographic-based digital terrain elevation data.

  1. Path planning for complex terrain navigation via dynamic programming

    Energy Technology Data Exchange (ETDEWEB)

    Kwok, K.S.; Driessen, B.J.

    1998-12-31

    This work considers the problem of planning optimal paths for a mobile robot traversing complex terrain. In addition to the existing obstacles, locations in the terrain where the slope is too steep for the mobile robot to navigate safely without tipping over become mathematically equivalent to extra obstacles. To solve the optimal path problem, the authors use a dynamic programming approach. The dynamic programming approach utilized herein does not suffer the difficulties associated with spurious local minima that the artificial potential field approaches do. In fact, a globally optimal solution is guaranteed to be found if a feasible solution exists. The method is demonstrated on several complex examples including very complex terrains.

  2. Formation of gravel pavements during fluvial erosion as an explanation for persistence of ancient cratered terrain on Titan and Mars

    Science.gov (United States)

    Howard, Alan D.; Breton, Sylvain; Moore, Jeffrey M.

    2016-05-01

    In many terrestrial channels the gravel bed is only transported during rare floods (threshold channels), and rates of erosion are very slow. In this paper we explore how coarse debris delivered to channels on Mars and Titan from erosion may inhibit further erosion once a coarse gravel channel bed develops. Portions of the equatorial region of Titan are fluvially eroded into banded (crenulated) terrain, some of which contains numerous circular structures that are likely highly degraded large impact craters surviving from the late heavy bombardment. No mechanism that can chemically or physically break down ice (likely the most important component of Titans crust) has been unambiguously identified. This paper examines a scenario in which fluvial erosion on Titan has largely involved erosion into an impact-generated megaregolith that contains a modest component of gravel-sized debris. As the megaregolith is eroded, coarse gravel gradually accumulates as a lag pavement on channel beds, limiting further erosion and creating a dissected, but largely inactive, or senescent, landscape. Similar development of gravel pavements occur in ancient mountain belts on Earth, and partially explain the persistence of appreciable relief after hundreds of millions of years. Likewise, coarse gravel beds may have limited the degree to which erosion could modify the heavily cratered terrains on Mars, particularly if weathering were largely due to physical, rather than chemical weathering processes in a relatively cold and/or arid environment.

  3. Integrating geospatial and ground geophysical information as guidelines for groundwater potential zones in hard rock terrains of south India.

    Science.gov (United States)

    Rashid, Mehnaz; Lone, Mahjoor Ahmad; Ahmed, Shakeel

    2012-08-01

    The increasing demand of water has brought tremendous pressure on groundwater resources in the regions were groundwater is prime source of water. The objective of this study was to explore groundwater potential zones in Maheshwaram watershed of Andhra Pradesh, India with semi-arid climatic condition and hard rock granitic terrain. GIS-based modelling was used to integrate remote sensing and geophysical data to delineate groundwater potential zones. In the present study, Indian Remote Sensing RESOURCESAT-1, Linear Imaging Self-Scanner (LISS-4) digital data, ASTER digital elevation model and vertical electrical sounding data along with other data sets were analysed to generate various thematic maps, viz., geomorphology, land use/land cover, geology, lineament density, soil, drainage density, slope, aquifer resistivity and aquifer thickness. Based on this integrated approach, the groundwater availability in the watershed was classified into four categories, viz. very good, good, moderate and poor. The results reveal that the modelling assessment method proposed in this study is an effective tool for deciphering groundwater potential zones for proper planning and management of groundwater resources in diverse hydrogeological terrains.

  4. Uses of tree legumes in semi-arid regions

    Energy Technology Data Exchange (ETDEWEB)

    Felker, P.

    1980-01-01

    Uses of tree legumes in semi-arid and arid regions are reviewed. This review is divided into sections according to the following general use categories: fuels; human food; livestock food; to increase yields of crops grown beneath their canopies;and control of desertification. (MHR)

  5. International Arid Lands Consortium: A synopsis of accomplishments

    Science.gov (United States)

    Peter F. Ffolliott; Jeffrey O. Dawson; James T. Fisher; Itshack Moshe; Timothy E. Fulbright; W. Carter Johnson; Paul Verburg; Muhammad Shatanawi; Jim P. M. Chamie

    2003-01-01

    The International Arid Lands Consortium (IALC) was established in 1990 to promote research, education, and training activities related to the development, management, and reclamation of arid and semiarid lands in the Southwestern United States, the Middle East, and elsewhere in the world. The Consortium supports the ecological sustainability and environmentally sound...

  6. Terrain mapping camera for Chandrayaan-1

    Indian Academy of Sciences (India)

    A S Kiran Kumar; A Roy Chowdhury

    2005-12-01

    The Terrain Mapping Camera (TMC)on India ’s first satellite for lunar exploration,Chandrayaan-1, is for generating high-resolution 3-dimensional maps of the Moon.With this instrument,a complete topographic map of the Moon with 5 m spatial resolution and 10-bit quantization will be available for scienti fic studies.The TMC will image within the panchromatic spectral band of 0.4 to 0.9 m with a stereo view in the fore,nadir and aft directions of the spacecraft movement and have a B/H ratio of 1.The swath coverage will be 20 km.The camera is configured for imaging in the push broom-mode with three linear detectors in the image plane.The camera will have four gain settings to cover the varying illumination conditions of the Moon.Additionally,a provision of imaging with reduced resolution,for improving Signal-to-Noise Ratio (SNR)in polar regions,which have poor illumination conditions throughout,has been made.SNR of better than 100 is expected in the ± 60° latitude region for mature mare soil,which is one of the darkest regions on the lunar surface. This paper presents a brief description of the TMC instrument.

  7. All-terrain self-leveling wheelchair.

    Science.gov (United States)

    Schofield, Andrew; Barrett, Steven

    2014-01-01

    Limited mobility is something that affects approximately 6.8 million Americans. Approximately 1.7 million are using wheelchairs or scooters of some kind to enhance mobility. Everyday obstacles present a challenge to those in a wheelchair. Also, outdoor environments such as campsites, lakes, or even grass fields provide additional challenges for those with limited mobility. This project provides a solution to some of the limitations faced by those in wheelchairs. The wheels and tires of the wheelchair allow navigation through most terrains such as grass, gravel, and sand. Furthermore, as a wheelchair climbs or descends a hill it becomes unstable and the user risks tipping the wheelchair causing injury or even death. The self-leveling wheelchair uses an accelerometer to determine its angle of inclination and depending on user interface choices will display the angle or raise the seat with linear actuators to keep the seat level. This will keep the center of gravity towards the front of the chair when going up a hill and towards the back of the chair when going down a hill. This enhanced stability will give the user the confidence and ability to go places where most traditional wheelchairs can not. The chair has the ability to self-level at up to 45 degree and can provide a manual lift of 6 inches. The design presented in this report is patent pending.

  8. Wind and diffusion modeling for complex terrain

    Energy Technology Data Exchange (ETDEWEB)

    Cox, R.M.; Sontowski, J.; Fry, R.N. Jr. [and others

    1996-12-31

    Atmospheric transport and dispersion over complex terrain were investigated. Meteorological and sulfur hexafluoride (SF{sub 6}) concentration data were collected and used to evaluate the performance of a transport and diffusion model coupled with a mass consistency wind field model. Meteorological data were collected throughout April 1995. Both meteorological and concentration data were measured in December 1995. The data included 11 to 15 surface stations, 1 to 3 upper air stations, and 1 mobile profiler. A range of conditions was encountered, including inversion and post-inversion breakup, light to strong winds, and a broad distribution of wind directions. The models used included the SCIPUFF (Second-order Closure Integrated Puff) transport and diffusion model and the MINERVE mass consistency wind model. Evaluation of the models was focused primarily on their effectiveness as a short term (one to four hours) predictive tool. These studies showed how they can be used to help direct emergency response following a hazardous material release. For purposes of the experiments, the models were used to direct the deployment of mobile sensors intended to intercept and measure tracer clouds.

  9. Reorienting with terrain slope and landmarks.

    Science.gov (United States)

    Nardi, Daniele; Newcombe, Nora S; Shipley, Thomas F

    2013-02-01

    Orientation (or reorientation) is the first step in navigation, because establishing a spatial frame of reference is essential for a sense of location and heading direction. Recent research on nonhuman animals has revealed that the vertical component of an environment provides an important source of spatial information, in both terrestrial and aquatic settings. Nonetheless, humans show large individual and sex differences in the ability to use terrain slope for reorientation. To understand why some participants--mainly women--exhibit a difficulty with slope, we tested reorientation in a richer environment than had been used previously, including both a tilted floor and a set of distinct objects that could be used as landmarks. This environment allowed for the use of two different strategies for solving the task, one based on directional cues (slope gradient) and one based on positional cues (landmarks). Overall, rather than using both cues, participants tended to focus on just one. Although men and women did not differ significantly in their encoding of or reliance on the two strategies, men showed greater confidence in solving the reorientation task. These facts suggest that one possible cause of the female difficulty with slope might be a generally lower spatial confidence during reorientation.

  10. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.

  11. CHARACTERISTICS AND CONSTRUCTION OF LANDSCAPE???ECOLOGY IN ARID REGIONS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper analyzes the characteristics of the landscape structures and landacape ecological processes in arid regions of China. Landscape structure is simplicity and homogeneity with the pattern of desert-oasis-river and canal corridor. The spatial distribution of landscape heterogeneity mosaics is relatively dependent on water resources. In arid regions,the landscape changes rapidly and extensively because of the sensitive landscape ecosystems and fragile regional ecosystems.For the sustainable development of arid regions, the theories and methods for the eco-environmental construction and the strategies of ecological construction in the arid regions were proposed in the view of landscape ecology. Keynote subjects of landscape ecology were also discussed. The paper points out that protecting and increasing landscape diversity and heterogeneity are critical to control ecological safety in arid regions.

  12. The current bioenergy production potential of semi-arid and arid regions in sub-Saharan Africa

    NARCIS (Netherlands)

    Wicke, B.; Smeets, E.M.W.; Watson, H.; Faaij, A.P.C.

    2011-01-01

    This article assesses the current technical and economic potential of three bioenergy production systems (cassava ethanol, jatropha oil and fuelwood) in semi-arid and arid regions of eight sub-Saharan African countries. The results indicate that the availability of land for energy production ranges

  13. DCS Terrain Submission for New Castle County, DE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DCS Terrain Submittal for Spalding County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain Submission for Clay County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submittal for Washita County, Oklahoma, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  17. Lunar All-Terrain Utility Vehicle for EVA Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ProtoInnovations, LLC proposes to develop a new type of planetary rover called a Lunar All-terrain Utility Vehicle ("Lunar ATV") to assist extra-vehicular activities...

  18. Classification of Mars Terrain Using Multiple Data Sources

    Data.gov (United States)

    National Aeronautics and Space Administration — Classification of Mars Terrain Using Multiple Data Sources Alan Kraut1, David Wettergreen1 ABSTRACT. Images of Mars are being collected faster than they can be...

  19. DCS Terrain for Wilcox County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain Submission for Logan County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain Submission for Baxter County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. Lunar All-Terrain Utility Vehicle for EVA Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ProtoInnovations, LLC proposes to develop a new type of planetary rover called a Lunar All-terrain Utility Vehicle ("LATUV") to assist extra-vehicular activities in...

  3. TERRAIN, Town of Pocatello Levee PMR, Bannock COUNTY, IDAHO

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Town of Pocatello, Bannock County, ID created 2ft contours by photogrametric methods to serve as terrain. The areas for contour creation have been designed as...

  4. Error detection and rectification in digital terrain models

    Science.gov (United States)

    Hannah, M. J.

    1979-01-01

    Digital terrain models produced by computer correlation of stereo images are likely to contain occasional gross errors in terrain elevation. These errors typically result from having mismatched sub-areas of the two images, a problem which can occur for a variety of image- and terrain-related reasons. Such elevation errors produce undesirable effects when the models are further processed, and should be detected and corrected as early in the processing as possible. Algorithms have been developed to detect and correct errors in digital terrain models. These algorithms focus on the use of constraints on both the allowable slope and the allowable change in slope in local areas around each point. Relaxation-like techniques are employed in the iteration of the detection and correction phases to obtain best results.

  5. DCS Terrain Submittal for Macon County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain Submission for Floyd County, IN (PMR)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Chippewa County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  8. TERRAIN submission for Rock River RiskMap DFIRM

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. DCS Terrain for Dodge County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN, CITY OF SEWARD, KENAI PENINSULA BOROUGH, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain Submission for Jackson County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for Randolph County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain Submission for La Crosse County, Wisconsin

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. TERRAIN, City of El Dorado, Butler County, KS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  15. DCS Terrain Submission for Eau Claire County, Wisconsin

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. Weather in Mountainous Terrain (Overcoming Scientific Barriers to Weather Support)

    Science.gov (United States)

    2011-02-15

    Weather in Mountainous Terrain (Overcoming Scientific Barriers to Weather Support) Fiesta Resort & Conference Center Tempe, AZ February 1...Meteorology Overcoming Scientific Barriers to Weather Support Fiesta Resort & Conference Center Tempe, AZ February 1 & 2, 2010 Hosted by University

  17. Terrain Submission for Pottawattamie County, IA (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  18. DCS Terrain Submittal for Bernalillo County, New Mexico, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DIGITAL DCS Terrain Submission for WHATCOM COUNTY, WASHINGTON

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  20. DCS Terrain Submission for Pope County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain Submittal for Mitchell County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain for Toombs County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. DCS Terrain Submittal for Dougherty County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. DCS Terrain Submission for Pine County, MN (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  5. DCS Terrain for Bullcoh County GA MAPMOD04-08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  6. TERRAIN, CITY OF GRAND PRAIRIE, DALLAS COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain for Bacon County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  8. Terrain Submission for Dickinson County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  9. DCS Terrain Submission for Jefferson Davis Parish, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. DCS Terrain Submittal for Dooly County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain Submission for Acadia Parish, LA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for La Paz County, AZ

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that were used to create...

  13. Terrain Submission for Menominee County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  14. DCS Terrain for Wheeler County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain for Chatham Co GA (FY2010)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain for Effingham Co GA (FY2010)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain for Montgomery County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain for Wayne County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS Terrain for Burke County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain for Glascock County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain for Telfair County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain for Jefferson County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. DCS Terrain for Tattnall County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  4. DCS Terrain for Lanier County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  5. DCS Terrain for Jenkins County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  6. DCS Terrain for Johnson County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain for Roscommon County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  8. DCS Terrain Submission for Monmouth County, New Jersey

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  9. Terrain, BIG BLUE RIVER TRIBUTARY NO 44, GAGE COUNTY, NE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  10. TERRAIN DATA CAPTURE STANDARDS, LUZERNE COUNTY, PA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data includes digital elevation models, LIDAR derived contours, LIDAR three-dimensional spot elevations and breaklines, field surveyed ground elevations and...

  11. DCS Terrain Submission for LeFlore, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  12. DCS Terrain Submission for Bear Creek in Clear Creek County

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  13. DCS Terrain Submission for McCurtain, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. DCS Terrain Submission for Forked Gulch in Canon City CO

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  15. DCS Terrain Submittal for Worth County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submittal for Thomas County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain for Appling County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain Submission for Lake Kaweah PMR - Tulare County, California

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  19. TERRAIN, CITY OF NORWALK, FAIRFIELD COUNTY, CONNECTICUT - Levee PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain submission for Washoe County NV PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  1. TERRAIN, CITY OF ANSONIA, NEW HAVEN COUNTY, CONNECTICUT - Levee PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  2. TERRAIN, CITY OF Derby, NEW HAVEN COUNTY, CONNECTICUT - Levee PMR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. DCS Terrain Submission for Miller County, AR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  4. DCS Terrain Submission for Gratiot County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  5. DCS TERRAIN SUBMISSION for MORRIS COUNTY, NEW JERSEY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that were used to create...

  6. DCS Terrain Submission for Ramsey County, North Dakota

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  7. DCS Terrain Submission for Cheboygan County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  8. DCS Terrain for Laurens County GA MAPMOD04-08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  9. TERRAIN DATA, DELANEY CREEK WATERSHED, HILLSBOROUGH COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describe the digital topographic data that were used to create...

  10. DCS Terrain Submission for Gold Star Canyon Study

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  11. DCS Terrain for Evans County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  12. Terrain Submission for Crawford County, MI (Countywide DFIRM)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describe the digital topographic data that were used to create...

  13. DCS Terrain Submission for Santa Cruz,CA - CW (NAVD)

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  14. Gravity gradient-terrain aided navigation based on particle filter

    Science.gov (United States)

    Xiong, Ling; Ma, Jie; Tian, Jin-Wen

    2009-10-01

    Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain elevation data. The position can be actualized through matching the real-time measured gravity gradient data to the prepared gravity gradient reference map. The most widely used approximate filtering method is the extended Kaman filter (EKF). EKF is computationally simple but, the convergence of the state estimation for the position is not guaranteed. Particle filter (PF) makes use of the non-linear state and measurement functions, no linearization technology is needed. PF can assure the convergence of the state estimation which follows from the classical results on convergence of Bayesian estimators. Simulations have been done and Particle filter has been shown to be a superior alternative to the EKF in the gravity gradient-terrain matching navigation systems.

  15. DCS Terrain for Emanuel County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  16. DCS Terrain Submission for Los Angeles County, CA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  17. DCS Terrain Submission for Hunterdon County New Jersey

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  18. DCS Terrain Submittal for Harmon County, Oklahoma, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  19. DCS Terrain Submittal for Butts County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  20. DCS Terrain for Wheeler County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  1. DCS Terrain Submittal for Terrell County, Georgia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix N: Data Capture Standards, describes the digital topographic data that was used to create...

  2. DCS Terrain for Tift County GA MapMod08

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Terrain data, as defined in FEMA Guidelines and Specifications, Appendix M: Data Capture Standards, describes the digital topographic data that was used to create...

  3. Cross-Coupled Control for All-Terrain Rovers

    Directory of Open Access Journals (Sweden)

    Giulio Reina

    2013-01-01

    Full Text Available Mobile robots are increasingly being used in challenging outdoor environments for applications that include construction, mining, agriculture, military and planetary exploration. In order to accomplish the planned task, it is critical that the motion control system ensure accuracy and robustness. The achievement of high performance on rough terrain is tightly connected with the minimization of vehicle-terrain dynamics effects such as slipping and skidding. This paper presents a cross-coupled controller for a 4-wheel-drive/4-wheel-steer robot, which optimizes the wheel motors’ control algorithm to reduce synchronization errors that would otherwise result in wheel slip with conventional controllers. Experimental results, obtained with an all-terrain rover operating on agricultural terrain, are presented to validate the system. It is shown that the proposed approach is effective in reducing slippage and vehicle posture errors.

  4. Improving terrain height estimates from RADARSAT interferometric measurements

    Energy Technology Data Exchange (ETDEWEB)

    Thompson, P.A.; Eichel, P.H.; Calloway, T.M.

    1998-03-01

    The authors describe two methods of combining two-pass RADAR-SAT interferometric phase maps with existing DTED (digital terrain elevation data) to produce improved terrain height estimates. The first is a least-squares estimation procedure that fits the unwrapped phase data to a phase map computed from the DTED. The second is a filtering technique that combines the interferometric height map with the DTED map based on spatial frequency content. Both methods preserve the high fidelity of the interferometric data.

  5. Subgrid snow depth coefficient of variation within complex mountainous terrain

    OpenAIRE

    Sexstone, Graham A.; Fassnacht, Steven R.; López-Moreno, Juan Ignacio; Christopher A. Hiemstra

    2016-01-01

    Given the substantial variability of snow in complex mountainous terrain, a considerable challenge of coarse scale modeling applications is accurately representing the subgrid variability of snowpack properties. The snow depth coefficient of variation (CVds) is a useful metric for characterizing subgrid snow distributions but has not been well defined by a parameterization for mountainous environments. This study utilizes lidar-derived snow depth datasets from mountainous terrain in Colorado,...

  6. World Representation Using Terrain Maps: Enabling High-Speed Navigation

    Science.gov (United States)

    2005-12-01

    under the Miro framework [15, 9, 16, 17, 18]. This map, representing the terrain in front of the Raptor UGV, feeds the traversibility analysis and...thus is instrumental in enabling obstacle and hazard avoidance behaviours . The Raptor UGV is shown in Figure 12. Figure 12: The Raptor UGV 6.1...Configuration The Raptor UGV carries four perception sensors that feed data to the terrain map: • Nodding SICK Laser. • Digiclops Stereo vision cameras

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

    Directory of Open Access Journals (Sweden)

    Lujin Hu

    2015-10-01

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

  8. 47 CFR 24.53 - Calculation of height above average terrain (HAAT).

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Calculation of height above average terrain... average terrain (HAAT). (a) HAAT is determined by subtracting average terrain elevation from antenna height above mean sea level. (b) Average terrain elevation shall be calculated using elevation data...

  9. Terrain mechanical parameters online estimation for lunar rovers

    Science.gov (United States)

    Liu, Bing; Cui, Pingyuan; Ju, Hehua

    2007-11-01

    This paper presents a new method for terrain mechanical parameters estimation for a wheeled lunar rover. First, after deducing the detailed distribution expressions of normal stress and sheer stress at the wheel-terrain interface, the force/torque balance equations of the drive wheel for computing terrain mechanical parameters is derived through analyzing the rigid drive wheel of a lunar rover which moves with uniform speed in deformable terrain. Then a two-points Guass-Lengendre numerical integral method is used to simplify the balance equations, after simplifying and rearranging the resolve model are derived which are composed of three non-linear equations. Finally the iterative method of Newton and the steepest descent method are combined to solve the non-linear equations, and the outputs of on-board virtual sensors are used for computing terrain key mechanical parameters i.e. internal friction angle and press-sinkage parameters. Simulation results show correctness under high noises disturbance and effectiveness with low computational complexity, which allows a lunar rover for online terrain mechanical parameters estimation.

  10. Submarine navigation based on gravity gradient-terrain matching

    Science.gov (United States)

    Xiong, Ling; Ma, Jie; Zhang, Li; Tian, Jin-Wen; Liu, Jian

    2007-11-01

    Based on the geophysics technology, a gravity gradient-terrain matching submarine navigation approach is proposed in this paper. The submarine's current position obtained by matching the measured gravity gradient data to the prepared gravity gradient reference map is used to correct the inertial navigation system's accumulated error. Although the precision gradiometer is in use, there is no world-wide gravity gradient map. The ocean's gravity gradient data is even scarce. Therefore, a gravity gradient matching navigation system directly utilizing the gravity gradient reference map can't be realized. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain elevation data and the preparing approach of the gravity gradient map is proposed in detail in the paper. Since the seabed terrain elevation map, especially highly accurate offing terrain elevation map has been pre-surveyed, the location can be actualized through matching the real-time measured gravity gradient data to the prepared gravity gradient reference map. Simulations show that the submarine navigation approach on gravity gradient-terrain matching is feasible and can be put into practice.

  11. Organic textile waste as a resource for sustainable agriculture in arid and semi-arid areas.

    Science.gov (United States)

    Eriksson, Bo G

    2017-03-01

    New vegetation in barren areas offers possibilities for sequestering carbon in the soil. Arid and semi-arid areas (ASAs) are candidates for new vegetation. The possibility of agriculture in ASAs is reviewed, revealing the potential for cultivation by covering the surface with a layer of organic fibres. This layer collects more water from humidity in the air than does the uncovered mineral surface, and creates a humid environment that promotes microbial life. One possibility is to use large amounts of organic fibres for soil enhancement in ASAs. In the context of the European Commission Waste Framework Directive, the possibility of using textile waste from Sweden is explored. The costs for using Swedish textile waste are high, but possible gains are the sale of agricultural products and increased land prices as well as environmental mitigation. The findings suggest that field research on such agriculture in ASAs should start as soon as possible.

  12. Determine the optimum spectral reflectance of juniper and pistachio in arid and semi-arid region

    Science.gov (United States)

    Fadaei, Hadi; Suzuki, Rikie

    2012-11-01

    Arid and semi-arid areas of northeast Iran cover about 3.4 million ha are populated by two main tree species, the broadleaf Pistacia vera. L (pistachio) and the conifer Juniperus excelsa ssp. polycarpos (Persian juniper). Natural stands of pistachio in Iran are not only environmentally important but genetically essential as seed sources for pistachio production in orchards. In this study, we estimated the optimum spectral reflectance of juniper forests and natural pistachio stands using remote sensing to help in the sustainable management and production of pistachio in Iran. In this research spectral reflectance are able to specify of multispectral from Advanced Land Observing Satellite (ALOS) that provided by JAXA. These data included PRISM is a panchromatic radiometer with a 2.5 m spatial resolution at nadir, has one band with a wavelength of 0.52-0.77 μm and AVNIR-2 is a visible and near infrared radiometer for observing land and coastal zones with a 10 m spatial resolution at nadir, has four multispectral bands: blue (0.42-0.50 μm), green (0.52-0.60 μm), red (0.61-0.69 μm), and near infrared (0.76-0.89 μm). Total ratio vegetation index (TRVI) of optimum spectral reflectance of juniper and pistachio have been evaluated. The result of TRVI for Pistachio and juniper were (R2= 0.71 and 0.55). I hope this research can provide decision of managers to helping sustainable management for arid and semi-arid regions in Iran.

  13. Population Aggregation in Ancient Arid Environments

    Directory of Open Access Journals (Sweden)

    Marco A. Janssen

    2010-06-01

    Full Text Available Human societies have adapted to spatial and temporal variability, such as that found in the prehistoric American Southwest. A question remains as to what the implications are of different social adaptations to long-term vulnerability of small-scale human societies. A stylized agent-based model is presented that captures small-group decision making on movements and resource use in ancient arid environments. The impact of various assumptions concerning storage, exchange, sharing, and migration on indicators of aggregation and sustainability are explored. Climate variability is found to increase the resilience of population levels at the system level. Variability reduces the time a population stays in one location and can degrade the soils. In addition to climate variability, the long-term population dynamics is mainly driven by the level of storage and the decision rules governing when to migrate and with whom to exchange.

  14. Long-term aridity changes in the western United States.

    Science.gov (United States)

    Cook, Edward R; Woodhouse, Connie A; Eakin, C Mark; Meko, David M; Stahle, David W

    2004-11-01

    The western United States is experiencing a severe multiyear drought that is unprecedented in some hydroclimatic records. Using gridded drought reconstructions that cover most of the western United States over the past 1200 years, we show that this drought pales in comparison to an earlier period of elevated aridity and epic drought in AD 900 to 1300, an interval broadly consistent with the Medieval Warm Period. If elevated aridity in the western United States is a natural response to climate warming, then any trend toward warmer temperatures in the future could lead to a serious long-term increase in aridity over western North America.

  15. Wind and Diffusion Modeling for Complex Terrain.

    Science.gov (United States)

    Cox, Robert M.; Sontowski, John; Fry, Richard N., Jr.; Dougherty, Catherine M.; Smith, Thomas J.

    1998-10-01

    Atmospheric transport and dispersion over complex terrain were investigated. Meteorological and sulfur hexafluoride (SF6) concentration data were collected and used to evaluate the performance of a transport and diffusion model coupled with a mass consistency wind field model. Meteorological data were collected throughout April 1995. Both meteorological and plume location and concentration data were measured in December 1995. The meteorological data included measurements taken at 11-15 surface stations, one to three upper-air stations, and one mobile profiler. A range of conditions was encountered, including inversion and postinversion breakup, light to strong winds, and a broad distribution of wind directions.The models used were the MINERVE mass consistency wind model and the SCIPUFF (Second-Order Closure Integrated Puff) transport and diffusion model. These models were expected to provide and use high-resolution three-dimensional wind fields. An objective of the experiment was to determine if these models could provide emergency personnel with high-resolution hazardous plume information for quick response operations.Evaluation of the models focused primarily on their effectiveness as a short-term (1-4 h) predictive tool. These studies showed how they could be used to help direct emergency response following a hazardous material release. For purposes of the experiments, the models were used to direct the deployment of mobile sensors intended to intercept and measure tracer clouds.The April test was conducted to evaluate the performance of the MINERVE wind field generation model. It was evaluated during the early morning radiation inversion, inversion dissipation, and afternoon mixed atmosphere. The average deviations in wind speed and wind direction as compared to observations were within 0.4 m s1 and less than 10° for up to 2 h after data time. These deviations increased as time from data time increased. It was also found that deviations were greatest during

  16. An Optimized Method for Terrain Reconstruction Based on Descent Images

    Directory of Open Access Journals (Sweden)

    Xu Xinchao

    2016-02-01

    Full Text Available An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang’e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang’e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions.

  17. Impacts of Post-Dam Land-use/Land-cover Changes on Modification of Extreme precipitation in Contrasting Hydro-climate and Terrain Features

    Science.gov (United States)

    Woldemichael, A. T.; Hossain, F.

    2013-12-01

    Understanding the impact of post-dam climate feedbacks, due to land-use/land-cover (LULC) variability, on modification of extreme precipitation (EP) remains a challenge for a 21st century approach to dam design and operation. In this study, we used the Regional Atmospheric Modeling System (RAMS, version 6.0), involving a number of pre-defined LULC scenarios to address the important question regarding dams and their impoundments: How sensitive are the hydroclimatology and terrain features of a region in modulating the post-dam response of climate feedbacks to EP? The study region covered the Owyhee dam/reservoir on Owyhee River Watershed (ORW) -located in eastern Oregon. A systematic perturbation of the relative humidity in the initial and boundary condition of the model was carried out to simulate EP. Among the different LULC scenarios used in the simulation over the ORW, irrigation expansion in the post-dam era resulted in an increase in EP up to 6% in the 72-hr precipitation total. The contribution of the reservoir on EP added 8% to the 72-hr total when compared to the pre-dam LULC conditions. In order to address the science question, a previously completed investigation on the Folsom dam (American River Watershed, ARW) in California, was compared with the ORW findings on the basis of contrasting differences in hydroclimatology and terrain features. Our results indicate that the post-dam LULC change scenarios impact EP of ORW (Owyhee Dam) is much greater than the EP of the ARW (Folsom Dam) due to its semi-arid climate (leeward side) and flat terrain. LULC changes are found to be less sensitive to EP modification in the windward side of the mountainous terrain of ARW.

  18. DRIFT-ARID: Application of a method for environmental water ...

    African Journals Online (AJOL)

    DRIFT-ARID: Application of a method for environmental water requirements ... of water required (EWR) to sustain ecosystem services in non-perennial rivers need ... river types, especially episodic rivers where data are scarce or non-existent.

  19. Assessment of microbial diversity under arid plants by culture ...

    African Journals Online (AJOL)

    Dr. R. K. Jain

    2013-10-02

    Oct 2, 2013 ... Both culture- dependent and culture-independent methods indicated that in arid crops, ... on analysis of DNA allow investigation of this potential. .... Addition of anionic detergent, SDS along with CTAB yielded maximum DNA.

  20. The Improved Kriging Interpolation Algorithm for Local Underwater Terrain Based on Fractal Compensation

    Directory of Open Access Journals (Sweden)

    Pengyun Chen

    2014-01-01

    Full Text Available The interpolation-reconstruction of local underwater terrain using the underwater digital terrain map (UDTM is an important step for building an underwater terrain matching unit and directly affects the accuracy of underwater terrain matching navigation. The Kriging method is often used in terrain interpolation, but, with this method, the local terrain features are often lost. Therefore, the accuracy cannot meet the requirements of practical application. Analysis of the geographical features is performed on the basis of the randomness and self-similarity of underwater terrain. We extract the fractal features of local underwater terrain with the fractal Brownian motion model, compensating for the possible errors of the Kriging method with fractal theory. We then put forward an improved Kriging interpolation method based on this fractal compensation. Interpolation-reconstruction tests show that the method can simulate the real underwater terrain features well and that it has good usability.

  1. Hybrid RANS/LES applied to complex terrain

    DEFF Research Database (Denmark)

    Bechmann, Andreas; Sørensen, Niels N.

    2011-01-01

    aspect ratio in the RANS layer and thereby resolve the mean near-wall velocity profile. The method is applicable to complex terrain and the benefits of traditional LES are kept intact. Using the hybrid method, simulations of the wind over a natural complex terrain near Wellington in New Zealand......Large Eddy Simulation (LES) of the wind in complex terrain is limited by computational cost. The number of computational grid points required to resolve the near-ground turbulent structures (eddies) are very high. The traditional solution to the problem has been to apply a wall function...... that accounts for the whole near-wall region. Recently, a hybrid method was proposed in which the eddies close to the ground were modelled in a Reynolds-averaged sense (RANS) and the eddies above this region were simulated using LES. The advantage of the approach is the ability to use shallow cells of high...

  2. Automatic target tracking on multi-resolution terrain

    Institute of Scientific and Technical Information of China (English)

    WAN Ming; ZHANG Wei; MURRAY Marie O.; KAUFMAN Arie

    2006-01-01

    We propose a high-performance path planning algorithm for automatic target tracking in the applications of real-time simulation and visualization of large-scale terrain datasets, with a large number of moving objects (such as vehicles) tracking multiple moving targets. By using a modified Dijkstra's algorithm, an optimal path between each vehicle-target pair over a weighted grid-presented terrain is computed and updated to eliminate the problem of local minima and losing of tracking. Then, a dynamic path re-planning strategy using multi-resolution representation of a dynamic updating region is proposed to achieve high-performance by trading-off precision for efficiency, while guaranteeing accuracy. Primary experimental results showed that our algorithm successfully achieved 10 to 96 frames per second interactive path-replanning rates during a terrain simulation scenario with 10 to 100 vehicles and multiple moving targets.

  3. Dynamic Terrain Visualization Based on ROAM and OGRE

    Institute of Scientific and Technical Information of China (English)

    FU Hui; WANG Quanmin

    2009-01-01

    Terrain Visualization is an important part of visualization systems of battlefield,and the visualization of dynamic terrain is also important for dynamic battle environment.In this paper,special attention has been paid on real-time optimally adapting meshes (ROAM) algorithm,which is a candidate for dynamic terrain,and its mesh representation,mesh continuity algorithm and error metrics are discussed.The DEXTER-ROAM algorithm is discussed and analyzed.By revising the mesh representation of ROAM,a dynamic ROAM algorithm based on partial-regular grid is established.By introducing transition region,mesh discontinuity of dynamic partial-regular grid is resolved.Error metric blocks are removed for computation complexity and culling blocks are introduced to accelerate view frustum culling.The algorithm is implemented in a 3D rendering engine called OGRE.In the end,an example of dynamic crater is given to examine the dynamic ROAM algorithm.

  4. ISOSTATICALLY DISTURBED TERRAIN OF NORTHWESTERN ANDES MOUNTAINS FROM SPECTRALLY CORRELATED FREE-AIR AND GRAVITY TERRAIN DATA

    Directory of Open Access Journals (Sweden)

    Hernández P Orlando

    2006-12-01

    Full Text Available Recently revised models on global tectonics describe the convergence of the North Andes, Nazca, Caribbean and South American Plates and their seismicity, volcanism, active faulting and extreme
    topography. The current plate boundaries of the area are mainly interpreted from volcanic and seismic datasets with variable confidence levels. New insights on the isostatic state and plate boundaries of
    the northwestern Andes Mountains can be obtained from the spectral analysis of recently available gravity and topography data.
    Isostatically disturbed terrain produces free-air anomalies that are highly correlated with the gravity effects of the terrain. The terrain gravity effects (TGE and free air gravity anomalies (FAGA of the
    Andes mountains spectral correlation data confirms that these mountains are isostatically disturbed. Strong negative terrain-correlated FAGA along western South America and the Greater and Lesser Antilles are consistent with anomalously deepened mantle displaced by subducting oceanic plates.

    Inversion of the compensated terrain gravity effects (CTGE reveals plate subduction systems with alternating shallower and steeper subduction angles. The gravity modeling highlights crustal
    deformation from plate collision and subduction and other constraints on the tectonism of the plate boundary zones for the region.

  5. Impacts of Climate Anomalies on the Vegetation Patterns in the Arid and Semi-Arid Zones of Uzbekistan

    Science.gov (United States)

    Dildora, Aralova; Toderich, Kristina; Dilshod, Gafurov

    2016-08-01

    Steadily rising temperature anomalies in last decades are causing changes in vegetation patterns for sensitive to climate change in arid and semi-arid dryland ecosystems. After desiccation of the Aral Sea, Uzbekistan has been left with the challenge to develop drought and heat stress monitoring system and tools (e.g., to monitor vegetation status and/crop pattern dynamics) with using remote sensing technologies in broad scale. This study examines several climate parameters, NDVI and drought indexes within geostatistical method to predict further vegetation status in arid and semi-arid zones of landscapes. This approaches aimed to extract and utilize certain variable environmental data (temperature and precipitation) for assessment and inter-linkages of vegetation cover dynamics, specifically related to predict degraded and recovered zones or desertification process in the drylands due to scarcity of water resources and high risks of climate anomalies in fragile ecosystem of Uzbekistan.

  6. Late glacial aridity in southern Rocky Mountains

    Energy Technology Data Exchange (ETDEWEB)

    Davis, O.K.; Pitblado, B.L. [Univ. of Arizona, Tucson, AZ (United States)

    1995-09-01

    While the slopes of the present-day Colorado Rocky Mountains are characterized by large stands of subalpine and montane conifers, the Rockies of the late glacial looked dramatically different. Specifically, pollen records suggest that during the late glacial, Artemisia and Gramineae predominated throughout the mountains of Colorado. At some point between 11,000 and 10,000 B.P., however, both Artemisia and grasses underwent a dramatic decline, which can be identified in virtually every pollen diagram produced for Colorado mountain sites, including Como Lake (Sangre de Cristo Mountains), Copley Lake and Splains; Gulch (near Crested Butte), Molas Lake (San Juan Mountains), and Redrock Lake (Boulder County). Moreover, the same pattern seems to hold for pollen spectra derived for areas adjacent to Colorado, including at sites in the Chuska Mountains of New Mexico and in eastern Wyoming. The implications of this consistent finding are compelling. The closest modem analogues to the Artemisia- and Gramineae-dominated late-glacial Colorado Rockies are found in the relatively arid northern Great Basin, which suggests that annual precipitation was much lower in the late-glacial southern Rocky Mountains than it was throughout the Holocene.

  7. Entomological studies for surveillance and prevention of dengue in arid and semi-arid districts of Rajasthan, India

    Directory of Open Access Journals (Sweden)

    Anil Purohit

    2008-05-01

    Full Text Available Background & objectives: Rajasthan is one of the dengue endemic states of India. Very few studies have been published on entomological aspects of dengue in this state. Owing to water scarcity, inhabitants in desert areas overstore domestic water which leads to the persistence of dengue vectors within the domestic premises. Area specific knowledge on breeding, key containers and seasonal rhythms of vector population is essential for preparing an effective prevention plan against dengue. Present paper reports results of entomological investigations on dengue vectors in arid and semi-arid districts of Rajasthan. Methods: Longitudinal studies were undertaken during 2004–06 in one arid and two semi-arid dengue endemic districts of Rajasthan. Adult and larval Aedes were collected from the randomly selected houses in representative towns and villages with associated details of container types and water storage practices of inhabitants. Results: In urban areas during all the seasons adult house index (AHI of Aedes aegypti was maximum in desert zone (25 and least in semi-arid area with saline river III (1. The difference of AHI during three seasons was statistically significant (c2 = 16.1, p <0.01 for urban; and c2 = 50.71, p < 0.001 for rural. Breeding of Ae. aegypti among urban settings was maximum in desert zone. During all the seasons cement tanks were the key breeding habitats for Ae. aegypti in desert as well as semi-arid areas. Interpretation & conclusion: Water storage habits during summer season emerged to be the risk factor of vector abundance in urban areas of arid and semi-arid settings. A carefully designed study of key containers targeting cement tanks as the primary habitats of mosquito control may lead to commendable results for dengue prevention.

  8. Keeping Sediment and Nutrients out of Streams in Arid/Semi-Arid Regions: Application of Low Impact Development/Green Infrastructure Practices

    Science.gov (United States)

    Yongping, Yuan

    2015-04-01

    Climatic and hydrological characteristics in the arid/semi-arid areas create unique challenges to soil, water and biodiversity conservation. These areas are environmentally sensitive, but very valuable for the ecosystems services they provide to society. Some of these areas are experiencing the fastest urbanization and now face multiple water resource challenges. Low Impact Development (LID)/Green Infrastructure (GI) practices are increasingly popular for reducing stormwater and nonpoint source pollution in many regions around the world. However, streamflow in the arid/semi-arid regions is largely dependent on seasonal, short term, and high intensity rainfall events. LID has not been very common in the arid/semi-arid regions due to a lack of performance evaluation, as well as the perception that LID may not be very useful for regions with little annual precipitation. This study focused on investigating the hydrologic and pollutant removal performance of LID/GI systems in arid/semi-arid climates. Ten types of practices were found in use in the Western/Southwestern U.S.: rainwater harvest systems, detention ponds, retention ponds, bioretention, media filters, porous pavements, vegetated swales/buffer/strips, green roofs, infiltration trenches, and integrated LIDs. This study compared the performance of these practices in terms of their effectiveness at pollutant removal and cost-effectiveness. This analysis provides insight into the future implementation of LID/GI in the arid/semi-arid areas. Key words: LID/GI, arid/semi-arid, effectiveness of pollutant removal, cost-effectiveness analysis

  9. Simulation of Wind Farms in Flat & Complex terrain using CFD

    DEFF Research Database (Denmark)

    Prospathopoulos, John; Cabezon, D.; Politis, E.S.

    2010-01-01

    tested. This method features the advantage of not utilizing the wind speed at a specific distance from the rotor disk, which is a doubtful approximation when a W/T is located in the wake of another and/or the terrain is complex. To account for the underestimation of the near wake deficit, a correction......, the combination of the induction factor method along with the turbulence correction provides satisfactory results. In the complex terrain case, there are some significant discrepancies with the measurements, which are discussed. In this case, the induction factor method does not provide satisfactory results....

  10. Terrain Contour Matching (TERCOM): A Cruise Missile Guidance Aid

    Science.gov (United States)

    Golden, Joe P.

    1980-12-01

    The Cruise Missile is guided by an inertial guidance system aided by an updating technique called Terrain Contour Matching (TERCOM). Chance-Vought first proposed the terrain correlation technique in the late 1950's. Since that time TERCOM has evolved into a reliable, accurate, all weather, day and night method of position fixing and updating for cruise missiles. A brief history of TERCOM development will be presented giving results where possible. A description of TERCOM and how is works will be discussed. A snapshot of the present TERCOM status and future planned developments will be addressed.

  11. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross sections...... of the object using a CAD-model. The raw measurements are input to a SAR system and terrain model, which models thermal noise, terrain clutter, and SAR focusing to produce synthetic SAR images. Examples of SAR images at 0.3m and 0.1m resolution, and a comparison with real SAR imagery from the MSTAR dataset...

  12. The Derivation of Skeleton Lines for Terrain Features

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The geometric and physical analysis methods are conventional methods for the derivation of skeleton lines in the fields of cartography,digital photogrammetry,and related areas.This paper proposes a stepwise approach that uses the physical analysis method in the first stage and the geometric analysis method in the subsequent stage.The physical analysis method analyses the terrain globally to obtain a rough set of skeleton lines for a terrain surface.The rough skeleton lines help to structure the ordering of feature points by the geometric analysis method.

  13. Optimization of Wind Farm Layout in Complex Terrain

    DEFF Research Database (Denmark)

    Xu, Chang; Yang, Jianchuan; Li, Chenqi

    2013-01-01

    Microscopic site selection for wind farms in complex terrain is a technological difficulty in the development of onshore wind farms. This paper presented a method for optimizing wind farm layout in complex terrain. This method employed Lissaman and Jensen wake models, took wind velocity...... are subject to boundary conditions and minimum distance conditions. The improved genetic algorithm (GA) for real number coding was used to search the optimal result. Then the optimized result was compared to the result from the experienced layout method. Results show the advantages of the present method...

  14. Flow over complex terrain. The secrets of Bolund

    DEFF Research Database (Denmark)

    Lange, Julia

    and the understanding of flow over complex terrain. The work presented in this thesis contains two diverse approaches to help under- stand the flow behavior over a complex terrain site, in this case the Bolund peninsula. The first approach investigates the wake and recirculation zone downstream of the Bolund escarpment....... A modification of the escarpment of the Bolund model to give a sharper edge has dramatic consequences for a wind turbine positioned close to the edge. Additionally the windtunnel investigations show only a modest Reynolds number dependence of the flow, while it is more sensitive to the details of the inflow wind...

  15. Optimization of Wind Farm Layout in Complex Terrain

    DEFF Research Database (Denmark)

    Xu, Chang; Yang, Jianchuan; Li, Chenqi

    2013-01-01

    are subject to boundary conditions and minimum distance conditions. The improved genetic algorithm (GA) for real number coding was used to search the optimal result. Then the optimized result was compared to the result from the experienced layout method. Results show the advantages of the present method......Microscopic site selection for wind farms in complex terrain is a technological difficulty in the development of onshore wind farms. This paper presented a method for optimizing wind farm layout in complex terrain. This method employed Lissaman and Jensen wake models, took wind velocity...

  16. Terrain Mapping and Classification in Outdoor Environments Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Alberto Yukinobu Hata

    2009-12-01

    Full Text Available This paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. We propose the use of a multi-layer perceptron neural network to classify the terrain into navigable, partially navigable, and non-navigable. The maps generated by our approach can be used for path planning, navigation, and local obstacle avoidance. Experimental tests using an outdoor robot and a laser sensor demonstrate the accuracy of the presented methods.

  17. Prediction of wind energy distribution in complex terrain using CFD

    DEFF Research Database (Denmark)

    Xu, Chang; Li, Chenqi; Yang, Jianchuan

    2013-01-01

    Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software...... to predict wind speed distribution in complex terrain. TECPLOT software post-processing is used to get the whole wind flow field, the wind speed distribution characteristics and distribution of wind energy. The obtained results are compared with the results of WAsP software and are also more accordance...

  18. A Novel Kinematic Model for Rough Terrain Robots

    Science.gov (United States)

    Auchter, Joseph; Moore, Carl A.; Ghosal, Ashitava

    We describe in detail a novel kinematic simulation of a three—wheeled mo bile robot moving on extremely uneven terrain. The purpose of this simulation is to test a new concept, called Passive Variable Camber (PVC), for reducing undesir able wheel slip. PVC adds an extra degree of freedom at each wheel/platform joint, thereby allowing the wheel to tilt laterally. This extra motion allows the vehicle to better adapt to uneven terrain and reduces wheel slip, which is harmful to vehicle efficiency and performance.

  19. Terrain dependant hop count selection for transparent relay transmissions

    Directory of Open Access Journals (Sweden)

    Cibile K. Kanjirathumkal

    2013-12-01

    Full Text Available In this Letter, the selection of the best hop count for a particular topography, in the context of enhanced connectivity using multi-hop transparent relay communication is addressed. Based on the coefficient of variation and the terrain specific fading severity factor of the distribution, it is possible to estimate the optimal hop count that can provide the required performance at detector. Two distribution models, which can adequately characterise the terrain fading effects on empirical data are considered for performance comparison. The results are useful in selecting branches, with low variability and optimal hop count for connectivity, in multi-stream switched diversity combining systems.

  20. Diagnosis of GLDAS LSM based aridity index and dryland identification.

    Science.gov (United States)

    Ghazanfari, Sadegh; Pande, Saket; Hashemy, Mehdy; Sonneveld, Ben

    2013-04-15

    The identification of dryland areas is crucial for guiding policy aimed at intervening in water-stressed areas and addressing the perennial livelihood or food insecurity of these areas. However, the prevailing aridity indices (such as UNEP aridity index) have methodological limitations that restrict their use in delineating drylands and may be insufficient for decision-making frameworks. In this study, we propose a new aridity index based on based on 3 decades of soil moisture time series by accounting for site-specific soil and vegetation that partitions precipitation into the competing demands of evaporation and runoff. Our proposed aridity index is the frequency at which the dominant soil moisture value at a location is not exceeded by the dominant soil moisture values in all of the other locations. To represent the dominant spatial template of the soil moisture conditions, we extract the first eigenfunction from the empirical orthogonal function (EOF) analysis from 3 GLDAS land surface models (LSMs): VIC, MOSAIC and NOAH at 1 × 1 degree spatial resolution. The EOF analysis reveals that the first eigenfunction explains 33%, 43% and 47% of the VIC, NOAH and MOSAIC models, respectively. We compare each LSM aridity indices with the UNEP aridity index, which is created based on LSM data forcings. The VIC aridity index displays a pattern most closely resembling that of UNEP, although all of the LSM-based indices accurately isolate the dominant dryland areas. The UNEP classification identifies portions of south-central Africa, southeastern United States and eastern India as drier than predicted by all of the LSMs. The NOAH and MOSAIC LSMs categorize portions of southwestern Africa as drier than the other two classifications, while all of the LSMs classify portions of central India as wetter than the UNEP classification. We compare all aridity maps with the long-term average NDVI values. Results show that vegetation cover in areas that the UNEP index classifies as