WorldWideScience

Sample records for satellite multibeam phased

  1. Advanced Communication Technology Satellite (ACTS) multibeam antenna technology verification experiments

    Science.gov (United States)

    Acosta, Roberto J.; Larko, Jeffrey M.; Lagin, Alan R.

    1992-01-01

    The Advanced Communication Technology Satellite (ACTS) is a key to reaching NASA's goal of developing high-risk, advanced communications technology using multiple frequency bands to support the nation's future communication needs. Using the multiple, dynamic hopping spot beams, and advanced on board switching and processing systems, ACTS will open a new era in communications satellite technology. One of the key technologies to be validated as part of the ACTS program is the multibeam antenna with rapidly reconfigurable hopping and fixed spot beam to serve users equipped with small-aperature terminals within the coverage areas. The proposed antenna technology experiments are designed to evaluate in-orbit ACTS multibeam antenna performance (radiation pattern, gain, cross pol levels, etc.).

  2. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  3. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  4. Spectrum and power allocation in cognitive multi-beam satellite communications with flexible satellite payloads

    Science.gov (United States)

    Liu, Zhihui; Wang, Haitao; Dong, Tao; Yin, Jie; Zhang, Tingting; Guo, Hui; Li, Dequan

    2018-02-01

    In this paper, the cognitive multi-beam satellite system, i.e., two satellite networks coexist through underlay spectrum sharing, is studied, and the power and spectrum allocation method is employed for interference control and throughput maximization. Specifically, the multi-beam satellite with flexible payload reuses the authorized spectrum of the primary satellite, adjusting its transmission band as well as power for each beam to limit its interference on the primary satellite below the prescribed threshold and maximize its own achievable rate. This power and spectrum allocation problem is formulated as a mixed nonconvex programming. For effective solving, we first introduce the concept of signal to leakage plus noise ratio (SLNR) to decouple multiple transmit power variables in the both objective and constraint, and then propose a heuristic algorithm to assign spectrum sub-bands. After that, a stepwise plus slice-wise algorithm is proposed to implement the discrete power allocation. Finally, simulation results show that adopting cognitive technology can improve spectrum efficiency of the satellite communication.

  5. Advanced Communication Technology Satellite (ACTS) multibeam antenna analysis and experiment

    Science.gov (United States)

    Acosta, Roberto J.; Lagin, Alan R.; Larko, Jeffrey M.; Narvaez, Adabelle

    1992-01-01

    One of the most important aspects of a satellite communication system design is the accurate estimation of antenna performance degradation. Pointing error, end coverage gain, peak gain degradation, etc. are the main concerns. The thermal or dynamic distortions of a reflector antenna structural system can affect the far-field antenna power distribution in a least four ways. (1) The antenna gain is reduced; (2) the main lobe of the antenna can be mispointed thus shifting the destination of the delivered power away from the desired locations; (3) the main lobe of the antenna pattern can be broadened, thus spreading the RF power over a larger area than desired; and (4) the antenna pattern sidelobes can increase, thus increasing the chances of interference among adjacent beams of multiple beam antenna system or with antenna beams of other satellites. The in-house developed NASA Lewis Research Center thermal/structural/RF analysis program was designed to accurately simulate the ACTS in-orbit thermal environment and predict the RF antenna performance. The program combines well establish computer programs (TRASYS, SINDA and NASTAN) with a dual reflector-physical optics RF analysis program. The ACTS multibeam antenna configuration is analyzed and several thermal cases are presented and compared with measurements (pre-flight).

  6. Coverage Extension via Side-Lobe Transmission in Multibeam Satellite System

    OpenAIRE

    Gharanjik, Ahmad; Kmieciak, Jarek; Shankar, Bhavani; Ottersten, Björn

    2017-01-01

    In this paper, we study feasibility of coverage extension of a multibeam satellite network by providing low-rate communications to terminals located outside the coverage of main beams. Focusing on the MEO satellite network, and using realistic link budgets from O3b networks, we investigate the performance of both forward and return-links for terminals stationed in the side lobes of the main beams. Particularly, multi-carrier transmission for forward-link and single carrier transmission for re...

  7. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  8. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  9. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  10. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  11. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  12. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  13. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  14. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  15. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  16. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  17. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  18. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  19. A Multibeam Dual-Band Orthogonal Linearly Polarized Antenna Array for Satellite Communication on the Move

    Directory of Open Access Journals (Sweden)

    Yi Liu

    2015-01-01

    Full Text Available The design and simulation of a 10 × 8 multibeam dual-band orthogonal linearly polarized antenna array operating at Ku-band are presented for transmit-receive applications. By using patches with different coupling methods as elements, both perpendicular polarization in 12.25–12.75 GHz band and horizontal polarization in 14.0–14.5 GHz band are realized in a shared antenna aperture. A microstrip Rotman lens is employed as the beamforming network with 7 input ports, which can generate a corresponding number of beams to cover −30°–30° with 5 dB beamwidth along one dimension. This type of multibeam orthogonal linearly polarized planar antenna is a good candidate for satellite communication (SatCom.

  20. Sunflower array antenna for multi-beam satellite applications

    NARCIS (Netherlands)

    Vigano, M.C.

    2011-01-01

    Saving space on board, reducing costs and improving the antenna performances are tasks of outmost importance in the field of satellite communication. In this work it is shown how a non-uniformly spaced, direct radiating array designed according to the so called ‘sunflower’ law is able to satisfy

  1. Development of Ray Tracing Algorithms for Scanning Plane and Transverse Plane Analysis for Satellite Multibeam Application

    Directory of Open Access Journals (Sweden)

    N. H. Abd Rahman

    2014-01-01

    Full Text Available Reflector antennas have been widely used in many areas. In the implementation of parabolic reflector antenna for broadcasting satellite applications, it is essential for the spacecraft antenna to provide precise contoured beam to effectively serve the required region. For this purpose, combinations of more than one beam are required. Therefore, a tool utilizing ray tracing method is developed to calculate precise off-axis beams for multibeam antenna system. In the multibeam system, each beam will be fed from different feed positions to allow the main beam to be radiated at the exact direction on the coverage area. Thus, detailed study on caustics of a parabolic reflector antenna is performed and presented in this paper, which is to investigate the behaviour of the rays and its relation to various antenna parameters. In order to produce accurate data for the analysis, the caustic behaviours are investigated in two distinctive modes: scanning plane and transverse plane. This paper presents the detailed discussions on the derivation of the ray tracing algorithms, the establishment of the equations of caustic loci, and the verification of the method through calculation of radiation pattern.

  2. Multi-beam synchronous measurement based on PSD phase detection using frequency-domain multiplexing

    Science.gov (United States)

    Duan, Ying; Qin, Lan; Xue, Lian; Xi, Feng; Mao, Jiubing

    2013-10-01

    According to the principle of centroid measurement, position-sensitive detectors (PSD) are commonly used for micro displacement detection. However, single-beam detection method cannot satisfy such tasks as multi-dimension position measurement, three dimension vision reconstruction, and robot precision positioning, which require synchronous measurement of multiple light beams. Consequently, we designed PSD phase detection method using frequency-domain multiplexing for synchronous detection of multiple modulated light beams. Compared to previous PSD amplitude detection method, the phase detection method using FDM has advantages of simplified measuring system, low cost, high capability of resistance to light interference as well as improved resolution. The feasibility of multi-beam synchronous measurement based on PSD phase detection using FDM was validated by multi-beam measuring experiments. The maximum non-linearity error of the multi-beam synchronous measurement is 6.62%.

  3. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  4. Advanced Communication Technology Satellite (ACTS) Multibeam Antenna On-Orbit Performance

    Science.gov (United States)

    1995-01-01

    The NASA Lewis Research Center's Advanced Communication Technology Satellite (ACTS) was launched in September 1993. ACTS introduced several new technologies, including a multibeam antenna (MBA) operating at extremely short wavelengths never before used in communications. This antenna, which has both fixed and rapidly reconfigurable high-energy spot beams (150 miles in diameter), serves users equipped with small antenna terminals. Extensive structural and thermal analyses have been performed for simulating the ACTS MBA on-orbit performance. The results show that the reflector surfaces (mainly the front subreflector), antenna support assembly, and metallic surfaces on the spacecraft body will be distorted because of the thermal effects of varying solar heating, which degrade the ACTS MBA performance. Since ACTS was launched, a number of evaluations have been performed to assess MBA performance in the space environment. For example, the on-orbit performance measurements found systematic environmental disturbances to the MBA beam pointing. These disturbances were found to be imposed by the attitude control system, antenna and spacecraft mechanical alignments, and on-orbit thermal effects. As a result, the MBA may not always exactly cover the intended service area. In addition, the on-orbit measurements showed that antenna pointing accuracy is the performance parameter most sensitive to thermal distortions on the front subreflector surface and antenna support assemblies. Several compensation approaches were tested and evaluated to restore on-orbit pointing stability. A combination of autotrack (75 percent of the time) and Earth sensor control (25 percent of the time) was found to be the best way to compensate for antenna pointing error during orbit. This approach greatly minimizes the effects of thermal distortions on antenna beam pointing.

  5. Application Research of Horn Array Multi-Beam Antenna in Reference Source System for Satellite Interference Location

    Science.gov (United States)

    Zhou, Ping; Lin, Hui; Zhang, Qi

    2018-01-01

    The reference source system is a key factor to ensure the successful location of the satellite interference source. Currently, the traditional system used a mechanical rotating antenna which leaded to the disadvantages of slow rotation and high failure-rate, which seriously restricted the system’s positioning-timeliness and became its obvious weaknesses. In this paper, a multi-beam antenna scheme based on the horn array was proposed as a reference source for the satellite interference location, which was used as an alternative to the traditional reference source antenna. The new scheme has designed a small circularly polarized horn antenna as an element and proposed a multi-beamforming algorithm based on planar array. Moreover, the simulation analysis of horn antenna pattern, multi-beam forming algorithm and simulated satellite link cross-ambiguity calculation have been carried out respectively. Finally, cross-ambiguity calculation of the traditional reference source system has also been tested. The comparison between the results of computer simulation and the actual test results shows that the scheme is scientific and feasible, obviously superior to the traditional reference source system.

  6. An Optimal Beamforming Algorithm for Phased-Array Antennas Used in Multi-Beam Spaceborne Radiometers

    DEFF Research Database (Denmark)

    Iupikov, O. A.; Ivashina, M. V.; Pontoppidan, K.

    2015-01-01

    Strict requirements for future spaceborne ocean missions using multi-beam radiometers call for new antenna technologies, such as digital beamforming phased arrays. In this paper, we present an optimal beamforming algorithm for phased-array antenna systems designed to operate as focal plane arrays...... to a FPA feeding a torus reflector antenna (designed under the contract with the European Space Agency) and tested for multiple beams. The results demonstrate an improved performance in terms of the optimized beam characteristics, yielding much higher spatial and radiometric resolution as well as much...

  7. Leaky wave enhanced feeds for multibeam reflectors to be used for telecom satellite based links

    NARCIS (Netherlands)

    Neto, A.; Ettorre, M.; Gerini, G.; Maagt, P. de

    2012-01-01

    The use of dielectric super-layers for shaping the radiation pattern of focal plane feeds of a multibeam reflector system is discussed. Using the super-layers, it is possible to reduce the spillover from the reflectors without increasing the dimension of each aperture. The effect has been

  8. Experimental Satellite Phase 3D before Launch

    Directory of Open Access Journals (Sweden)

    J. Sebesta

    1999-04-01

    Full Text Available To build a satellite can be a dream for many engineers. We are happy that we can participate in the AMSAT PHASE 3D project. Our responsibility is very high because one of our on-board receivers is the main one of the command link and will never be switched off. The project is also a very good opportunity for our students to meet satellite technology.

  9. Merged/integrated Bathymetric Data Derived from Multibeam Sonar, LiDAR, and Satellite-derived Bathymetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with derived bathymetry from alternate sources to provide a GIS layer with expanded spatial coverage. Integrated products...

  10. Empirical water depth predictions in Dublin Bay based on satellite EO multispectral imagery and multibeam data using spatially weighted geographical analysis

    Science.gov (United States)

    Monteys, Xavier; Harris, Paul; Caloca, Silvia

    2014-05-01

    The coastal shallow water zone can be a challenging and expensive environment within which to acquire bathymetry and other oceanographic data using traditional survey methods. Dangers and limited swath coverage make some of these areas unfeasible to survey using ship borne systems, and turbidity can preclude marine LIDAR. As a result, an extensive part of the coastline worldwide remains completely unmapped. Satellite EO multispectral data, after processing, allows timely, cost efficient and quality controlled information to be used for planning, monitoring, and regulating coastal environments. It has the potential to deliver repetitive derivation of medium resolution bathymetry, coastal water properties and seafloor characteristics in shallow waters. Over the last 30 years satellite passive imaging methods for bathymetry extraction, implementing analytical or empirical methods, have had a limited success predicting water depths. Different wavelengths of the solar light penetrate the water column to varying depths. They can provide acceptable results up to 20 m but become less accurate in deeper waters. The study area is located in the inner part of Dublin Bay, on the East coast of Ireland. The region investigated is a C-shaped inlet covering an area of 10 km long and 5 km wide with water depths ranging from 0 to 10 m. The methodology employed on this research uses a ratio of reflectance from SPOT 5 satellite bands, differing to standard linear transform algorithms. High accuracy water depths were derived using multibeam data. The final empirical model uses spatially weighted geographical tools to retrieve predicted depths. The results of this paper confirm that SPOT satellite scenes are suitable to predict depths using empirical models in very shallow embayments. Spatial regression models show better adjustments in the predictions over non-spatial models. The spatial regression equation used provides realistic results down to 6 m below the water surface, with

  11. Micro Resistojet for Small Satellites, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Micro-resistojets offer an excellent combination of simplicity, performance and wet system mass for small satellites (<100 kg, <50 watts) requiring mN level...

  12. Virtual Satellite Integration Environment, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Advatech Pacific proposes to develop a Virtual Satellite Integration Environment (VSIE) for the NASA Ames Mission Design Center. The VSIE introduces into NASA...

  13. Micro Resistojet for Small Satellites, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Micro-resistojets offer the best combination of simplicity, performance, wet system mass and power consumption for small satellites (<100kg, <50Watts)...

  14. Virtual Satellite Integration Environment, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — An integrated environment for rapid design studies of small satellite missions will be developed. This environment will be designed to streamline processes at the...

  15. Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR, optical satellite imagery, and Lidar data

    Science.gov (United States)

    Jahncke, Raymond; Leblon, Brigitte; Bush, Peter; LaRocque, Armand

    2018-06-01

    Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multi-date and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands

  16. Estimation of satellite position, clock and phase bias corrections

    Science.gov (United States)

    Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs

    2018-05-01

    Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.

  17. Precise Orbit Determination of GPS Satellites Using Phase Observables

    Directory of Open Access Journals (Sweden)

    Myung-Kook Jee

    1997-12-01

    Full Text Available The accuracy of user position by GPS is heavily dependent upon the accuracy of satellite position which is usually transmitted to GPS users in radio signals. The real-time satellite position information directly obtained from broadcast ephimerides has the accuracy of 3 x 10 meters which is very unsatisfactory to measure 100km baseline to the accuracy of less than a few mili-meters. There are globally at present seven orbit analysis centers capable of generating precise GPS ephimerides and their orbit quality is of the order of about 10cm. Therefore, precise orbit model and phase processing technique were reviewed and consequently precise GPS ephimerides were produced after processing the phase observables of 28 global GPS stations for 1 day. Initial 6 orbit parameters and 2 solar radiation coefficients were estimated using batch least square algorithm and the final results were compared with the orbit of IGS, the International GPS Service for Geodynamics.

  18. Considerations of digital phase modulation for narrowband satellite mobile communication

    Science.gov (United States)

    Grythe, Knut

    1990-01-01

    The Inmarsat-M system for mobile satellite communication is specified as a frequency division multiple access (FDMA) system, applying Offset Quadrature Phase Shift Keying (QPSK) for transmitting 8 kbit/sec in 10 kHz user channel bandwidth. We consider Digital Phase Modulation (DPM) as an alternative modulation format for INMARSAT-M. DPM is similar to Continuous Phase Modulation (CPM) except that DPM has a finite memory in the premodular filter with a continuous varying modulation index. It is shown that DPM with 64 states in the VA obtains a lower bit error rate (BER). Results for a 5 kHz system, with the same 8 kbit/sec transmitted bitstream, is also presented.

  19. Multibeam sonar backscatter data processing

    Science.gov (United States)

    Schimel, Alexandre C. G.; Beaudoin, Jonathan; Parnum, Iain M.; Le Bas, Tim; Schmidt, Val; Keith, Gordon; Ierodiaconou, Daniel

    2018-06-01

    Multibeam sonar systems now routinely record seafloor backscatter data, which are processed into backscatter mosaics and angular responses, both of which can assist in identifying seafloor types and morphology. Those data products are obtained from the multibeam sonar raw data files through a sequence of data processing stages that follows a basic plan, but the implementation of which varies greatly between sonar systems and software. In this article, we provide a comprehensive review of this backscatter data processing chain, with a focus on the variability in the possible implementation of each processing stage. Our objective for undertaking this task is twofold: (1) to provide an overview of backscatter data processing for the consideration of the general user and (2) to provide suggestions to multibeam sonar manufacturers, software providers and the operators of these systems and software for eventually reducing the lack of control, uncertainty and variability associated with current data processing implementations and the resulting backscatter data products. One such suggestion is the adoption of a nomenclature for increasingly refined levels of processing, akin to the nomenclature adopted for satellite remote-sensing data deliverables.

  20. Satellites

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  1. Multibeam Bathymetry Database (MBBDB)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Originally designed for military use, the multibeam echosounder has proved very useful for nautical charting, oceanographic research and modeling, habitat...

  2. Communications Satellite Systems Conference, 9th, San Diego, CA, March 7-11, 1982, Collection of Technical Papers

    Science.gov (United States)

    The Shuttle-to-Geostationary Orbital Transfer by mid-level thrust is considered along with multibeam antenna concepts for global communications, the antenna pointing systems for large communication satellites, the connection phase of multidestination protocols for broadcast satellites, and an experiment in high-speed international packet switching. Attention is given to a dynamic switch matrix for the TDMA satellite switching system, the characterization of 16 bit microprocessors for space use, in-orbit operation and test of Intelsat V satellites, the first operational communications system via satellite in Europe, the Arab satellite communications systems, second generation business satellite systems for Europe, and a high performance Ku-band satellite for the 1980's. Other topics investigated are related to Ku-band terminal design tradeoffs, progress in the definition of the Italian satellite for domestic telecommunications, future global satellite systems for Intelsat, and satellite refuelling in orbit.

  3. Small Satellite Transceiver for Launch Vehicles, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — NAL Research Corporation proposes to develop a small, light-weight, low-cost transceivers capable of establishing satellite communications links for telemetry and...

  4. Miniature Reaction Wheel for Small Satellite Control, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall goal of this project is to design, develop, demonstrate, and deliver a miniature, high torque, low-vibration reaction wheel for use on small satellites....

  5. SPS-ALPHA: The First Practical Solar Power Satellite via Arbitrarily Large PHased Array

    Data.gov (United States)

    National Aeronautics and Space Administration — SPS-ALPHA (Solar Power Satellite via Arbitrarily Large Phased Array) is a novel, bio-mimetic approach to the challenge of space solar power. If successful, this...

  6. Automatic phase control in solar power satellite systems

    Science.gov (United States)

    Lindsey, W. C.; Kantak, A. V.

    1978-01-01

    Various approaches to the problem of generating, maintaining and distributing a coherent, reference phase signal over a large area are suggested, mathematically modeled and analyzed with respect to their ability to minimize: phase build-up, beam diffusion and beam steering phase jitter, cable length, and maximize power transfer efficiency. In addition, phase control configurations are suggested which alleviate the need for layout symmetry.

  7. The phase curve survey of the irregular saturnian satellites: A possible method of physical classification

    Science.gov (United States)

    Bauer, James M.; Grav, Tommy; Buratti, Bonnie J.; Hicks, Michael D.

    2006-09-01

    During its 2005 January opposition, the saturnian system could be viewed at an unusually low phase angle. We surveyed a subset of Saturn's irregular satellites to obtain their true opposition magnitudes, or nearly so, down to phase angle values of 0.01°. Combining our data taken at the Palomar 200-inch and Cerro Tololo Inter-American Observatory's 4-m Blanco telescope with those in the literature, we present the first phase curves for nearly half the irregular satellites originally reported by Gladman et al. [2001. Nature 412, 163-166], including Paaliaq (SXX), Siarnaq (SXXIX), Tarvos (SXXI), Ijiraq (SXXII), Albiorix (SXVI), and additionally Phoebe's narrowest angle brightness measured to date. We find centaur-like steepness in the phase curves or opposition surges in most cases with the notable exception of three, Albiorix and Tarvos, which are suspected to be of similar origin based on dynamical arguments, and Siarnaq.

  8. New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

    Science.gov (United States)

    Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

    2016-12-01

    Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

  9. AFSC/ABL: Multibeam Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Seafloor habitat maps have been created using high resolution multibeam sonar with co-registered backscatter at various locations throughout the Alaska Region. Most...

  10. Multibeam fiber laser cutting

    DEFF Research Database (Denmark)

    Olsen, Flemming Ove; Hansen, Klaus Schütt; Nielsen, Jakob Skov

    2009-01-01

    The appearance of the high power high brilliance fiber laser has opened for new possibilities in laser materials processing. In laser cutting this laser has demonstrated high cutting performance compared to the dominating Cutting laser, the CO2 laser. However, quality problems in fiber......-laser cutting have until now limited its application to metal cutting. In this paper the first results of proof-of-principle Studies applying a new approach (patent pending) for laser cutting with high brightness and short wavelength lasers will be presented. In the approach, multibeam patterns are applied...... to control the melt flow out of the cut kerf resulting in improved cut quality in metal cutting. The beam patterns in this study are created by splitting up beams from two single mode fiber lasers and combining these beams into a pattern in the cut kerf. The results are obtained with a total of 550 W...

  11. Phase Error Modeling and Its Impact on Precise Orbit Determination of GRACE Satellites

    Directory of Open Access Journals (Sweden)

    Jia Tu

    2012-01-01

    Full Text Available Limiting factors for the precise orbit determination (POD of low-earth orbit (LEO satellite using dual-frequency GPS are nowadays mainly encountered with the in-flight phase error modeling. The phase error is modeled as a systematic and a random component each depending on the direction of GPS signal reception. The systematic part and standard deviation of random part in phase error model are, respectively, estimated by bin-wise mean and standard deviation values of phase postfit residuals computed by orbit determination. By removing the systematic component and adjusting the weight of phase observation data according to standard deviation of random component, the orbit can be further improved by POD approach. The GRACE data of 1–31 January 2006 are processed, and three types of orbit solutions, POD without phase error model correction, POD with mean value correction of phase error model, and POD with phase error model correction, are obtained. The three-dimensional (3D orbit improvements derived from phase error model correction are 0.0153 m for GRACE A and 0.0131 m for GRACE B, and the 3D influences arisen from random part of phase error model are 0.0068 m and 0.0075 m for GRACE A and GRACE B, respectively. Thus the random part of phase error model cannot be neglected for POD. It is also demonstrated by phase postfit residual analysis, orbit comparison with JPL precise science orbit, and orbit validation with KBR data that the results derived from POD with phase error model correction are better than another two types of orbit solutions generated in this paper.

  12. Phase calibration of the EISCAT Svalbard Radar interferometer using optical satellite signatures

    Directory of Open Access Journals (Sweden)

    J. M. Sullivan

    2006-09-01

    Full Text Available The link between natural ion-line enhancements in radar spectra and auroral activity has been the subject of recent studies but conclusions have been limited by the spatial and temporal resolution previously available. The next challenge is to use shorter sub-second integration times in combination with interferometric programmes to resolve spatial structure within the main radar beam, and so relate enhanced filaments to individual auroral rays. This paper presents initial studies of a technique, using optical and spectral satellite signatures, to calibrate the received phase of a signal with the position of the scattering source along the interferometric baseline of the EISCAT Svalbard Radar. It is shown that a consistent relationship can be found only if the satellite passage through the phase fringes is adjusted from the passage predicted by optical tracking. This required adjustment is interpreted as being due to the vector between the theoretical focusing points of the two antennae, i.e. the true radar baseline, differing from the baseline obtained by survey between the antenna foot points. A method to obtain a measurement of the true interferometric baseline using multiple satellite passes is outlined.

  13. Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

    Science.gov (United States)

    Choi, Michael K.

    2014-01-01

    This paper uses phase change material (PCM) in the scan cavity of an imager or sounder on satellites in geostationary orbit (GEO) to maintain the telescope temperature stable. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the telescope warm. It has no moving parts or bimetallic springs. It reduces heater power required to make up the heat lost by radiation to space through the aperture. It is an attractive thermal control option to a radiator with a louver and a sunshade.

  14. NASA satellite communications application research. Phase 2: Efficient high power, solid state amplifier for EFH communications

    Science.gov (United States)

    Benet, James

    1993-01-01

    The final report describes the work performed from 9 Jun. 1992 to 31 Jul. 1993 on the NASA Satellite Communications Application Research (SCAR) Phase 2 program, Efficient High Power, Solid State Amplifier for EHF Communications. The purpose of the program was to demonstrate the feasibility of high-efficiency, high-power, EHF solid state amplifiers that are smaller, lighter, more efficient, and less costly than existing traveling wave tube (TWT) amplifiers by combining the output power from up to several hundred solid state amplifiers using a unique orthomode spatial power combiner (OSPC).

  15. Wideband satellite phase coherent beacon observations at auroral and equatorial latitudes - A review

    International Nuclear Information System (INIS)

    Rino, C.L.; Livingston, R.C.; Cousins, M.D.; Fair, B.C.

    1978-01-01

    This paper presents a brief review of some of the principal results from the first two years of operation of the Wideband satellite which transmits phase-coherent signals from S-band to VHF. The auroral zone data show narrow regions of enhanced scintillation well equatorward of the discrete aurora. Such enhancements can be explained as a purely geometrical effect if the irregularities within the major precipitation regions have a sheet-like structure. Evidence of a localized irregularity source at the poleward boundary of the plasma trough is also found. Model computations are discussed and applied to the interpretation of equatorial data

  16. Design of a Push-Broom Multi-Beam Radiometer for Future Ocean Observations

    DEFF Research Database (Denmark)

    Cappellin, C.; Pontoppidan, K.; Nielsen, P. H.

    2015-01-01

    The design of a push-broom multi-beam radiometer for future ocean observations is described. The radiometer provides a sensitivity one order of magnitude higher than a traditional conical scanning radiometer, and has the big advantage of being fully stationary relative to the satellite platform...

  17. Study of multibeam techniques for bathymetry and seabottom backscatter applications

    Digital Repository Service at National Institute of Oceanography (India)

    Nair, R.R.; Chakraborty, B.

    Indian ocean is presented using Hydrosweep-multibeam installed onboard ORV Sagarkanya. A seabottom classification model is proposed which can be applied for multibeam backscatter data. Certain aspects of the multibeam backscatter signal data processing...

  18. Multimodel evaluation of cloud phase transition using satellite and reanalysis data

    Science.gov (United States)

    Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J.-L. F.

    2015-08-01

    We take advantage of climate simulations from two multimodel experiments to characterize and evaluate the cloud phase partitioning in 16 general circulation models (GCMs), specifically the vertical structure of the transition between liquid and ice in clouds. We base our analysis on the ratio of ice condensates to the total condensates (phase ratio, PR). Its transition at 90% (PR90) and its links with other relevant variables are evaluated using the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation Cloud Product climatology, reanalysis data, and other satellite observations. In 13 of 16 models, the PR90 transition height occurs too low (6 km to 8.4 km) and at temperatures too warm (-13.9°C to -32.5°C) compared to observations (8.6 km, -33.7°C); features consistent with a lack of supercooled liquid with respect to ice above 6.5 km. However, this bias would be slightly reduced by using the lidar simulator. In convective regimes (more humid air and precipitation), the observed cloud phase transition occurs at a warmer temperature than for subsidence regimes (less humid air and precipitation). Only few models manage to roughly replicate the observed correlations with humidity (5/16), vertical velocity (5/16), and precipitation (4/16); 3/16 perform well for all these parameters (MPI-ESM, NCAR-CAM5, and NCHU). Using an observation-based Clausius-Clapeyron phase diagram, we illustrate that the Bergeron-Findeisen process is a necessary condition for models to represent the observed features. Finally, the best models are those that include more complex microphysics.

  19. Multi-beam linear accelerator EVT

    Energy Technology Data Exchange (ETDEWEB)

    Teryaev, Vladimir E., E-mail: vladimir_teryaev@mail.ru [Omega-P, Inc., New Haven, CT 06510 (United States); Kazakov, Sergey Yu. [Fermilab, Batavia, IL 60510 (United States); Hirshfield, Jay L. [Omega-P, Inc., New Haven, CT 06510 (United States); Yale University, New Haven, CT 06511 (United States)

    2016-09-01

    A novel electron multi-beam accelerator is presented. The accelerator, short-named EVT (Electron Voltage Transformer) belongs to the class of two-beam accelerators. It combines an RF generator and essentially an accelerator within the same vacuum envelope. Drive beam-lets and an accelerated beam are modulated in RF modulators and then bunches pass into an accelerating structure, comprising uncoupled with each other and inductive tuned cavities, where the energy transfer from the drive beams to the accelerated beam occurs. A phasing of bunches is solved by choice correspond distances between gaps of the adjacent cavities. Preliminary results of numerical simulations and the initial specification of EVT operating in S-band, with a 60 kV gun and generating a 2.7 A, 1.1 MV beam at its output is presented. A relatively high efficiency of 67% and high design average power suggest that EVT can find its use in industrial applications.

  20. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  1. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    International Nuclear Information System (INIS)

    Andersson, Christer

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  2. K-Band Phased Array Developed for Low- Earth-Orbit Satellite Communications

    Science.gov (United States)

    Anzic, Godfrey

    1999-01-01

    Future rapid deployment of low- and medium-Earth-orbit satellite constellations that will offer various narrow- to wide-band wireless communications services will require phased-array antennas that feature wide-angle and superagile electronic steering of one or more antenna beams. Antennas, which employ monolithic microwave integrated circuits (MMIC), are perfectly suited for this application. Under a cooperative agreement, an MMIC-based, K-band phased-array antenna is being developed with 50/50 cost sharing by the NASA Lewis Research Center and Raytheon Systems Company. The transmitting array, which will operate at 19 gigahertz (GHz), is a state-of-the-art design that features dual, independent, electronically steerable beam operation ( 42 ), a stand-alone thermal management, and a high-density tile architecture. This array can transmit 622 megabits per second (Mbps) in each beam from Earth orbit to small Earth terminals. The weight of the total array package is expected to be less than 8 lb. The tile integration technology (flip chip MMIC tile) chosen for this project represents a major advancement in phased-array engineering and holds much promise for reducing manufacturing costs.

  3. Guidance, Navigation, and Control System for Maneuverable Pico-Satellites, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A compact, low-power GN&C system is essential to the success of pico-satellite Automated Rendezvous and Docking (AR&D). Austin Satellite Design (ASD)...

  4. A Small Ku-Band Polarization Tracking Active Phased Array for Mobile Satellite Communications

    Directory of Open Access Journals (Sweden)

    Wei Shi

    2013-01-01

    Full Text Available A compact polarization tracking active phased array for Ku-band mobile satellite signal reception is presented. In contrast with conventional mechanically tracking antennas, the approach presented here meets the requirements of beam tracking and polarization tracking simultaneously without any servo components. The two-layer stacked square patch fed by two probes is used as antenna element. The impedance bandwidth of 16% for the element covers the operating frequency range from 12.25 GHz to 12.75 GHz. In the presence of mutual coupling, the dimensional parameters for each element of the small 7 × 7 array are optimized during beam scanning and polarization tracking. The compact polarization tracking modules based on the low-temperature cofired ceramic (LTCC system-in-package (SiP technology are proposed. A small active phased array prototype with the size of 120 mm (length × 120 mm (width × 55 mm (height is developed. The measured polarization tracking patterns of the prototype are given. The polarization tracking beam can be steered in the elevation up to 50°. The gain of no less than 16.0 dBi and the aperture efficiency of more than 50% are obtained. The measured and simulated polarization tracking patterns agreed well.

  5. Low-Cost Planar MM-Wave Phased Array Antenna for Use in Mobile Satellite (MSAT) Platforms

    DEFF Research Database (Denmark)

    Ojaroudiparchin, Naser; Shen, Ming; Pedersen, Gert F.

    2015-01-01

    In this paper, a compact 8×8 phased array antenna for mobile satellite (MSAT) devices is designed and investigated. 64-elements of 22 GHz patch antennas with coaxial-probe feeds have been used for the proposed planar design. The antenna is designed on a low-cost FR4 substrate with thickness, diel...

  6. Autonomous Satellite Command and Control Through the World Wide Web. Phase 3

    Science.gov (United States)

    Cantwell, Brian; Twiggs, Robert

    1998-01-01

    The Automated Space System Experimental Testbed (ASSET) system is a simple yet comprehensive real-world operations network being developed. Phase 3 of the ASSET Project was January-December 1997 and is the subject of this report. This phase permitted SSDL and its project partners to expand the ASSET system in a variety of ways. These added capabilities included the advancement of ground station capabilities, the adaptation of spacecraft on-board software, and the expansion of capabilities of the ASSET management algorithms. Specific goals of Phase 3 were: (1) Extend Web-based goal-level commanding for both the payload PI and the spacecraft engineer. (2) Support prioritized handling of multiple (PIs) Principle Investigators as well as associated payload experimenters. (3) Expand the number and types of experiments supported by the ASSET system and its associated spacecraft. (4) Implement more advanced resource management, modeling and fault management capabilities that integrate the space and ground segments of the space system hardware. (5) Implement a beacon monitoring test. (6) Implement an experimental blackboard controller for space system management. (7) Further define typical ground station developments required for Internet-based remote control and for full system automation of the PI-to-spacecraft link. Each of those goals are examined. Significant sections of this report were also published as a conference paper. Several publications produced in support of this grant are included as attachments. Titles include: 1) Experimental Initiatives in Space System Operations; 2) The ASSET Client Interface: Balancing High Level Specification with Low Level Control; 3) Specifying Spacecraft Operations At The Product/Service Level; 4) The Design of a Highly Configurable, Reusable Operating System for Testbed Satellites; 5) Automated Health Operations For The Sapphire Spacecraft; 6) Engineering Data Summaries for Space Missions; and 7) Experiments In Automated Health

  7. PHASES: a concept for a satellite-borne ultra-precise spectrophotometer

    International Nuclear Information System (INIS)

    Burgo, C del; Prieto, C Allende; Peacocke, T

    2010-01-01

    The Planet Hunting and Asteroseismology Explorer Spectrophotometer, PHASES, is a concept for a space-borne instrument to obtain flux calibrated spectra and measure micro-magnitude photometric variations of nearby stars. The science drivers are the determination of the physical properties of stars and the characterisation of planets orbiting them, to very high precision. PHASES, intended to be housed in a micro-satellite, consists of a 20 cm aperture modified Baker telescope feeding two detectors: the tracking detector, with a field of 1 degree square, and the science detector for performing spectrophotometry. The optical design has been developed with the primary goal of avoiding stray light on the science detector, while providing spectra in the wavelength range 370-960 nm with a resolving power that ranges from ∼ 900 at 370 nm to ∼ 200 at 960 nm. The signal to noise per resolution element obtained for a V = 10 magnitude star in a 1 minute integration varies between ∼ 35 and 140. An analysis of the light curve constrains the radii of the planets relative to their parent stars' radii, which are, in turn, tightly constrained by the combination of absolute spectrophotometry and trigonometric parallaxes. The provisional optical design satisfies all the scientific requirements, including a ∼ 1% rms flux calibration strategy based on observations of bright A-type stars and model atmospheres, allowing the determination of stellar angular diameters for nearby solar-like stars to 0.5%. This level of accuracy will be propagated to the stellar radii for the nearest stars, with highly reliable Hipparcos parallaxes, and more significantly, to the planetary radii.

  8. Data Filtering and Assimilation of Satellite Derived Aerosol Optical Depth, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Satellite observations of the Earth often contain excessive noise and extensive data voids. Aerosol measurements, for instance, are obscured and contaminated by...

  9. Miniaurizable, High Performance, Fiber-Optic Gyroscopes for Small Satellites, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Small satellites require much lighter weight, smaller, and long life Attitude control components that can withstand stressing launch conditions and space vibration...

  10. Multibeam radiation therapy treatment application

    International Nuclear Information System (INIS)

    Manens, J.P.; Le Gall, G.; Chenal, C.; Ben Hassel, M.; Fresne, F.; Barillot, C.; Gibaud, B.; Lemoine, D.; Bouliou, A.; Scarabin, J.M.

    1991-01-01

    A software package has been developed for multibeam radiation therapy treatment application. We present in this study a computer-assisted dosimetric planning procedure which includes: i), an analytical stage for setting up the large volume via 2D and 3D displays; ii), a planning stage for issue of a treatment strategy including dosimetric simulations; and iii), a treatment stage to drive the target volume to the radiation unit isocenter. The combined use of stereotactic methods and multimodality imagery ensures spatial coherence and makes target definition and cognition of structure environment more accurate. The dosimetric planning suited to the spatial reference (the stereotactic frame) guarantees optimal distribution of the dose, computed by the original 3D volumetric algorithm. A computer-driven chair-framework cluster was designed to position the target volume at the radiation unit isocenter [fr

  11. Regeneratively-Cooled, Pump-Fed Propulsion Technology for Nano / Micro Satellite Launch Vehicles, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Ventions proposes the development of a pump-fed, 2-stage nano launch vehicle for low-cost on demand placement of cube and nano-satellites into LEO. The proposed...

  12. Synchronized Position and Hold Reorient Experimental Satellites - International Space Station (SPHERES-ISS), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. (PSI) and the MIT Space Systems Laboratory (MIT-SSL) propose an innovative research program entitled SPHERES-ISS that uses their satellite...

  13. Servo-Drive Amplifier for Micro-Satellite Superconductor-Levitated Flywheels, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — A new servo-drive technology is available to support energy storage and navigation for micro-satellites. Exploiting the ?pinning? effect of high-temperature...

  14. Miniaturized Lightweight Monopropellant Feed System for Nano- and Micro-satellites, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — There is a need for viable and practical solutions for utilizing chemical thrusters operating with green monopropellants on small- and micro-satellites and cubesats...

  15. Odyssey, an optimized personal communications satellite system

    Science.gov (United States)

    Rusch, Roger J.

    Personal communications places severe demands on service providers and transmission facilities. Customers are not satisfied with the current levels of service and want improvements. Among the characteristics that users seek are: lower service rates, hand held convenience, acceptable time delays, ubiquitous service, high availability, reliability, and high quality. The space industry is developing commercial space systems for providing mobile communications to personal telephones. Provision of land mobile satellite service is fundamentally different from the fixed satellite service provided by geostationary satellites. In fixed service, the earth based antennas can depend on a clear path from user to satellite. Mobile users in a terrestrial environment commonly encounter blockage due to vegetation, terrain or buildings. Consequently, high elevation angles are of premium value. TRW studied the issues and concluded that a Medium Earth Orbit constellation is the best solution for Personal Communications Satellite Service. TRW has developed Odyssey, which uses twelve satellites in medium altitude orbit to provide personal communications satellite service. The Odyssey communications system projects a multibeam antenna pattern to the Earth. The attitude control system orients the satellites to ensure constant coverage of land mass and coastal areas. Pointing can be reprogrammed by ground control to ensure optimized coverage of the desired service areas. The payload architecture features non-processing, "bent pipe" transponders and matrix amplifiers to ensure dynamic power delivery to high demand areas. Circuit capacity is 3000 circuits per satellite. Each satellite weighs 1917 kg (4226 pounds) at launch and the solar arrays provide 3126 Watts of power. Satellites are launched in pairs on Ariane, Atlas, or other vehicles. Each satellite is placed in a circular orbit at an altitude of 10,354 km. There are three orbit planes inclined at 55° to the equatorial plane

  16. Solar power satellite system definition study. Volume 7, phase 1: SPS and rectenna systems analyses

    Science.gov (United States)

    1979-01-01

    A systems definition study of the solar power satellite systems is presented. The design and power distribution of the rectenna system is discussed. The communication subsystem and thermal control characteristics are described and a failure analysis performed on the systems is reported.

  17. Radiated EMC& EMI Management During Design Qualification and Test Phases on LEO Satellites Constellation

    Science.gov (United States)

    Blondeaux, H.; Terral, M.; Gutierrez-Galvan, R.; Baud, C.

    2016-05-01

    The aim of the proposed paper is to present the global radiated EMC/EMI approach applied by Thales Alenia Space in the frame of a telecommunication Low Earth Orbit (LEO) satellites constellation program. The paper will present this approach in term of analyses, of specific characterisation and of sub-system and satellite tests since first design reviews up-to satellite qualification tests on Prototype Flight Model (PFM) and to production tests on reduced FMs. The global aim is : 1 - to reduce risk and cost (units EMC delta qualification, EMC tests at satellite level for the 81 Space Vehicles (SV) through appropriated EMC analyses (in term of methodologies and contours) provided in the frame of design reviews.2 - to early anticipate potential critical case to reduce the impact in term of engineering/qualification/test extra cost and of schedule.3 - to secure/assure the payload and SV design/layout.4 - to define and optimize the EMC/EMI test campaigns to be performed on Prototype Flight Model (PFM) for complete qualification and on some FMs for industrial qualification/validation.The last part of the paper is dedicated to system Bite Error Rate (BER) functional test performed on PFM SV to demonstrate the final compatibility between the three on-board payloads and to the Internal EMC tests performed on PFM and some FMs to demonstrate the SV panel RF shielding efficiency before and after environmental tests and the Thales Alenia Space (TAS) and Orbital AKT (OATK) workmanships reproducibility.

  18. NASA satellite communications application research, phase 2 addendum. Efficient high power, solid state amplifier for EHF communications

    Science.gov (United States)

    Benet, James

    1994-01-01

    This document is an addendum to the NASA Satellite Communications Application Research (SCAR) Phase 2 Final Report, 'Efficient High Power, Solid State Amplifier for EHF Communications.' This report describes the work performed from 1 August 1993 to 11 March 1994, under contract number NASW-4513. During this reporting period an array of transistor amplifiers was repaired by replacing all MMIC amplifier chips. The amplifier array was then tested using three different feedhorn configurations. Descriptions, procedures, and results of this testing are presented in this report, and conclusions are drawn based on the test results obtained.

  19. Comparison of the peak resolution and the stationary phase retention between the satellite and the planetary motions using the coil satellite centrifuge with counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives.

    Science.gov (United States)

    Shinomiya, Kazufusa; Zaima, Kazumasa; Harada, Yukina; Yasue, Miho; Harikai, Naoki; Tokura, Koji; Ito, Yoichiro

    2017-01-20

    Coil satellite centrifuge (CSC) produces the complex satellite motion consisting of the triplicate rotation of the coiled column around three axes including the sun axis (the angular velocity, ω 1 ), the planet axis (ω 2 ) and the satellite axis (the central axis of the column) (ω 3 ) according to the following formula: ω 1 =ω 2 +ω 3 . Improved peak resolution in the separation of 4-methylumbelliferyl sugar derivatives was achieved using the conventional multilayer coiled columns with ethyl acetate/1-butanol/water (3: 2: 5, v/v) for the lower mobile phase at the combination of the rotation speeds (ω 1 , ω 2 , ω 3 )=(300, 150, 150rpm), and (1:4:5, v/v) for the upper mobile phase at (300:100:200rpm). The effect of the satellite motion on the peak resolution and the stationary phase retention was evaluated by each CSC separation with the different rotation speeds of ω 2 and ω 3 under the constant revolution speed at ω 1 =300rpm. With the lower mobile phase, almost constant peak resolution and stationary phase retention were yielded regardless of the change of ω 2 and ω 3 , while with the upper mobile phase these two values were sensitively varied according to the different combination of ω 2 and ω 3 . For example, when ω 2 =147 or 200rpm is used, no stationary phase was retained in the coiled column while ω 2 =150rpm could retain enough volume of stationary phase for separation. On the other hand, the combined rotation speeds at (ω 1 , ω 2 , ω 3 )=(300, 300, 0rpm) or (300, 0, 300rpm) produced insufficient peak resolution regardless of the choice of the mobile phase apparently due to the lack of rotation speed except at (300, 0, 300rpm) with the upper mobile phase. At lower rotation speed of ω 1 =300rpm, better peak resolution and stationary phase retention were obtained by the satellite motion (ω 3 ) than by the planetary motion (ω 2 ), or ω 3 >ω 2 . The effect of the hydrophobicity of the two-phase solvent systems on the stationary phase

  20. Miniaurizable, High Performance, Fiber-Optic Gyroscopes for Small Satellites, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — This Phase 2 program builds on a successful Phase 1 effort that demonstrated practical engineering methods as well as continuing development paths to build smaller...

  1. Precise orbit determination of the Sentinel-3A altimetry satellite using ambiguity-fixed GPS carrier phase observations

    Science.gov (United States)

    Montenbruck, Oliver; Hackel, Stefan; Jäggi, Adrian

    2017-11-01

    The Sentinel-3 mission takes routine measurements of sea surface heights and depends crucially on accurate and precise knowledge of the spacecraft. Orbit determination with a targeted uncertainty of less than 2 cm in radial direction is supported through an onboard Global Positioning System (GPS) receiver, a Doppler Orbitography and Radiopositioning Integrated by Satellite instrument, and a complementary laser retroreflector for satellite laser ranging. Within this study, the potential of ambiguity fixing for GPS-only precise orbit determination (POD) of the Sentinel-3 spacecraft is assessed. A refined strategy for carrier phase generation out of low-level measurements is employed to cope with half-cycle ambiguities in the tracking of the Sentinel-3 GPS receiver that have so far inhibited ambiguity-fixed POD solutions. Rather than explicitly fixing double-difference phase ambiguities with respect to a network of terrestrial reference stations, a single-receiver ambiguity resolution concept is employed that builds on dedicated GPS orbit, clock, and wide-lane bias products provided by the CNES/CLS (Centre National d'Études Spatiales/Collecte Localisation Satellites) analysis center of the International GNSS Service. Compared to float ambiguity solutions, a notably improved precision can be inferred from laser ranging residuals. These decrease from roughly 9 mm down to 5 mm standard deviation for high-grade stations on average over low and high elevations. Furthermore, the ambiguity-fixed orbits offer a substantially improved cross-track accuracy and help to identify lateral offsets in the GPS antenna or center-of-mass (CoM) location. With respect to altimetry, the improved orbit precision also benefits the global consistency of sea surface measurements. However, modeling of the absolute height continues to rely on proper dynamical models for the spacecraft motion as well as ground calibrations for the relative position of the altimeter reference point and the CoM.

  2. Link Analysis of Shipboard SATCOM Phased-Array Antennas

    National Research Council Canada - National Science Library

    Major, R

    1998-01-01

    ...) project funded by Space and Naval Warfare Systems Command, PMW 133. The objective of the MMBA project is to demonstrate the capability of a multibeam, multiband satellite communications (SATCOM...

  3. Experimental evidence of phase coherence of magnetohydrodynamic turbulence in the solar wind: GEOTAIL satellite data.

    Science.gov (United States)

    Koga, D; Chian, A C-L; Hada, T; Rempel, E L

    2008-02-13

    Magnetohydrodynamic (MHD) turbulence is commonly observed in the solar wind. Nonlinear interactions among MHD waves are likely to produce finite correlation of the wave phases. For discussions of various transport processes of energetic particles, it is fundamentally important to determine whether the wave phases are randomly distributed (as assumed in the quasi-linear theory) or have a finite coherence. Using a method based on the surrogate data technique, we analysed the GEOTAIL magnetic field data to evaluate the phase coherence in MHD turbulence in the Earth's foreshock region. The results demonstrate the existence of finite phase correlation, indicating that nonlinear wave-wave interactions are in progress.

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

    Science.gov (United States)

    Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

    2016-04-01

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

  5. Design of a K-Band Transmit Phased Array For Low Earth Orbit Satellite Communications

    Science.gov (United States)

    Watson, Thomas; Miller, Stephen; Kershner, Dennis; Anzic, Godfrey

    2000-01-01

    The design of a light weight, low cost phased array antenna is presented. Multilayer printed wiring board (PWB) technology is utilized for Radio Frequencies (RF) and DC/Logic manifold distribution. Transmit modules are soldered on one side and patch antenna elements are on the other, allowing the use of automated assembly processes. The 19 GHz antenna has two independently steerable beams, each capable of transferring data at 622 Mbps. A passive, self-contained phase change thermal management system is also presented.

  6. Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

    Science.gov (United States)

    1989-01-01

    This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

  7. Ammonia-water phase diagram and its implications for icy satellites

    International Nuclear Information System (INIS)

    Johnson, M.L.; Nicol, M.

    1986-01-01

    A Holzapfel-type diamond anvil cell is used to determine the NH 3 - H 2 O phase diagram in the region from 0 to 33 mole percent NH 3 , 240 to 370 K, and 0 to 5 GPa. The following phases were identified: liquid; water ices Ih, III, V, VI, VII, and VIII; ammonia monohydrate, NH 3 .H 2 O; and ammonia dihydrate NH 3 . 2 H 2 O. Ammonia dihydrate becomes prominent at moderate pressures (less than 1 GPa), with planetologically significant implications, including the possibility of layering in Titan's magma ocean

  8. Autonomous Satellite Command and Control through the World Wide Web: Phase 3

    Science.gov (United States)

    Cantwell, Brian; Twiggs, Robert

    1998-01-01

    NASA's New Millenium Program (NMP) has identified a variety of revolutionary technologies that will support orders of magnitude improvements in the capabilities of spacecraft missions. This program's Autonomy team has focused on science and engineering automation technologies. In doing so, it has established a clear development roadmap specifying the experiments and demonstrations required to mature these technologies. The primary developmental thrusts of this roadmap are in the areas of remote agents, PI/operator interface, planning/scheduling fault management, and smart execution architectures. Phases 1 and 2 of the ASSET Project (previously known as the WebSat project) have focused on establishing World Wide Web-based commanding and telemetry services as an advanced means of interfacing a spacecraft system with the PI and operators. Current automated capabilities include Web-based command submission, limited contact scheduling, command list generation and transfer to the ground station, spacecraft support for demonstrations experiments, data transfer from the ground station back to the ASSET system, data archiving, and Web-based telemetry distribution. Phase 2 was finished in December 1996. During January-December 1997 work was commenced on Phase 3 of the ASSET Project. Phase 3 is the subject of this report. This phase permitted SSDL and its project partners to expand the ASSET system in a variety of ways. These added capabilities included the advancement of ground station capabilities, the adaptation of spacecraft on-board software, and the expansion of capabilities of the ASSET management algorithms. Specific goals of Phase 3 were: (1) Extend Web-based goal-level commanding for both the payload PI and the spacecraft engineer; (2) Support prioritized handling of multiple PIs as well as associated payload experimenters; (3) Expand the number and types of experiments supported by the ASSET system and its associated spacecraft; (4) Implement more advanced resource

  9. The Differential Vector Phase-Locked Loop for Global Navigation Satellite System Signal Tracking

    Science.gov (United States)

    2014-06-01

    Precise Positioning”. Reports on Geodesy , 87(2):77–85, 2009. [6] Cellmer, S. “The Real-Time Precise Positioning Using MAFA Method”. Proceedings of...Wielgosz, and Z. Rzepecka. “Modified Ambiguity Function Approach for GPS Carrier Phase Positioning”. Journal of Geodesy , 84(4):267–275, 2010. [10] Chan, B...Journal of Geodesy , 70:330–341, 1996. [30] Hatch, R. “Instantaneous Ambiguity Resolution”. Proceedings of the International Symposium 107 on Kinematic

  10. Ka Band Phase Locked Loop Oscillator Dielectric Resonator Oscillator for Satellite EHF Band Receiver

    Directory of Open Access Journals (Sweden)

    S. Coco

    2008-01-01

    Full Text Available This paper describes the design and fabrication of a Ka Band PLL DRO having a fundamental oscillation frequency of 19.250 GHz, used as local oscillator in the low-noise block of a down converter (LNB for an EHF band receiver. Apposite circuital models have been created to describe the behaviour of the dielectric resonator and of the active component used in the oscillator core. The DRO characterization and measurements have shown very good agreement with simulation results. A good phase noise performance is obtained by using a very high Q dielectric resonator.

  11. Exploitation of Amplitude and Phase of Satellite SAR Images for Landslide Mapping: The Case of Montescaglioso (South Italy

    Directory of Open Access Journals (Sweden)

    Federico Raspini

    2015-11-01

    Full Text Available Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy. In this paper, ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry and amplitude information (through speckle tracking techniques of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide.

  12. Mobility management in satellite networks

    Science.gov (United States)

    Johanson, Gary A.

    1995-01-01

    This paper addresses the methods used or proposed for use in multi-beam and/or multi-satellite networks designed to provide Mobile Satellite Services (MSS). Specific topics include beam crossover in the North American Mobile Satellite (MSAT) system as well as registration and live call hand-off for a multi-regional geosynchronous (GEO) satellite based system and a global coverage Low Earth Orbiting (LEO) system. In the MSAT system, the individual satellite beams cover very large geographic areas so the need for live call hand-off was not anticipated. This paper discusses the methods used to keep track of the beam location of the users so that incoming call announcements or other messages may be directed to them. Proposed new GEO systems with large numbers of beams will provide much smaller geographic coverage in individual beams and thus the need arises to keep track of the user's location as well as to provide live call hand-off as the user traverses from beam to beam. This situation also occurs in proposed LEO systems where the problems are worsened by the need for satellite to satellite hand-off as well as beam to beam hand-off within a single satellite. The paper discusses methods to accomplish these handoffs and proposes system architectures to address the various hand-off scenarios.

  13. Early- and later-phases satellite cell responses and myonuclear content with resistance training in young men.

    Science.gov (United States)

    Damas, Felipe; Libardi, Cleiton A; Ugrinowitsch, Carlos; Vechin, Felipe C; Lixandrão, Manoel E; Snijders, Tim; Nederveen, Joshua P; Bacurau, Aline V; Brum, Patricia; Tricoli, Valmor; Roschel, Hamilton; Parise, Gianni; Phillips, Stuart M

    2018-01-01

    Satellite cells (SC) are associated with skeletal muscle remodelling after muscle damage and/or extensive hypertrophy resulting from resistance training (RT). We recently reported that early increases in muscle protein synthesis (MPS) during RT appear to be directed toward muscle damage repair, but MPS contributes to hypertrophy with progressive muscle damage attenuation. However, modulations in acute-chronic SC content with RT during the initial (1st-wk: high damage), early (3rd-wk: attenuated damage), and later (10th-wk: no damage) stages is not well characterized. Ten young men (27 ± 1 y, 23.6 ± 1.0 kg·m-2) underwent 10-wks of RT and muscle biopsies (vastus-lateralis) were taken before (Pre) and post (48h) the 1st (T1), 5th (T2) and final (T3) RT sessions to evaluate fibre type specific SC content, cross-sectional area (fCSA) and myonuclear number by immunohistochemistry. We observed RT-induced hypertrophy after 10-wks of RT (fCSA increased ~16% in type II, P phase of RT than muscle hypertrophy resulted from 10-wks RT in young men. Chronic elevated SC pool size with RT is important providing proper environment for future stresses or larger fCSA increases.

  14. A compact low energy multibeam gamma-ray densitometer for pipe-flow measurements

    International Nuclear Information System (INIS)

    Tjugum, Stein-Arild; Frieling, Joop; Johansen, Geir Anton

    2002-01-01

    A compact low-energy multibeam gamma-ray densitometer for oil/water/gas pipe-flow measurement has been built at the University of Bergen. The instrument consists of one Am-241 source and three detectors, all collimated and embedded in the pipe wall. Only the 59.5 keV radiation energy of the source is utilized. Two of the detectors measure transmitted radiation across the pipe flow, and one measure scattered radiation at a 90 degree sign angle. The purpose of the multibeam measurement geometry is to acquire flow regime information and to reduce the flow regime dependency of the gas volume fraction (GVF) measurements. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be exploited. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to obtain salinity independent GVF measurements. The salinity dependency is otherwise strongly significant when using low-energy radiation. It is also possible to measure the salinity by using this principle. The instrument is a laboratory prototype, and it has been used for characterising the measurement principle and to test different detector alternatives. The testing of the instrument includes static tests on plastic phantoms, tests on simulated water/gas flow and three phase flow loop tests. Both the multibeam measurement principle and the DMD principle have been verified to provide valuable information. This paper presents the physics behind, experimental results and an evaluation of the system

  15. The Multibeam Advisory Committee (MAC): a search for solutions for collecting consistent high quality multibeam data across multiple ships, systems, and operators in the U.S. Academic Fleet.

    Science.gov (United States)

    Johnson, P. D.; Ferrini, V. L.; Jerram, K.

    2016-12-01

    In 2015 the National Science Foundation funded the University of New Hampshire's Center for Coastal and Ocean Mapping and Lamont-Doherty Earth Observatory, for the second time, to coordinate the effort of standardizing the quality of multibeam echosounder (MBES) data across the U.S. academic fleet. This effort supports 9 different ship operating institutions who manage a total of 12 multibeam-equipped ships carrying 6 different MBES systems, manufactured by two different companies. These MBES are designed to operate over a very wide range of depths and operational modes. The complexity of this endeavor led to the creation of the Multibeam Advisory Committee (MAC), a team of academic and industry experts whose mission is to support the needs of the U.S academic fleet's multibeam echo sounders through all of the phases of the "life" of a MBES system and its data, from initial acceptance of the system, to recommendations on at-sea acquisition of data, to validation of already installed systems, and finally to the post-survey data evaluation. The main activities of the MAC include 1.) standardizing both the Shipboard Acceptance Testing of all new systems and Quality Assurance Testing of already installed systems, 2.) working with the both the ship operators/technicians and the manufacturers of the multibeam systems to guarantee that each MBES is working at its peak performance level, 3.) developing tools that aid in the collection of data, assessment of the MBES hardware, and evaluation of the quality of the MBES data, 4.) creating "best practices" documentation concerning data acquisition and workflow, and 5.) providing a website, http://mac.unols.org, to host technical information, tools, reports, and a "help desk" for operators of the systems to ask questions concerning issues that they see with their systems.

  16. OpenSAT, An Open Source Based Satellite Design Data Architecture with API Design and Management Plugins, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Satellite design encompasses a multitude of steps from concept to flight. Mission specification to flight can take several years, depending on the scope,...

  17. Statistical study of phase relationships between magnetic and plasma thermal pressures in the near-earth magnetosphere using the THEMIS satellites

    Science.gov (United States)

    Nishi, K.; Kazuo, S.

    2017-12-01

    The auroral finger-like structures appear in the equatorward part of the auroral oval in the diffuse auroral region, and contribute to the auroral fragmentation into patches during substorm recovery phase. In our previous presentations, we reported the first conjugate observation of auroral finger-like structures using the THEMIS GBO cameras and the THEMIS satellites, which was located at a radial distance of 9 Re in the dawnside plasma sheet. In this conjugate event, we found anti-phase fluctuation of plasma pressure and magnetic pressure with a time scale of 5-20 min in the plasma sheet. This observational fact is consistent with the idea that the finger-like structures are caused by a pressure-driven instability in the balance of plasma and magnetic pressures in the magnetosphere. Then we also searched simultaneous observation events of auroral finger-like structures with the RBSP satellites which have an apogee of 5.8 Re in the inner magnetosphere. Contrary to the first result, the observed variation of plasma and magnetic pressures do not show systematic phase relationship. In order to investigate these phase relationships between plasma and magnetic pressures in the magnetosphere, we statistically analyzed these pressure data using the THEMIS-E satellite for one year in 2011. In the preliminary analysis of pressure variation spectra, we found that out of phase relationship between magnetic and plasma pressures occupied 40 % of the entire period of study. In the presentation, we will discuss these results in the context of relationships between the pressure fluctuations and the magnetospheric instabilities that can cause auroral finger-like structures.

  18. San Francisco Bay Multi-beam Bathymetry: Area A

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These multi-beam bathymetric data were collected over shallow subtidal areas in the San Francisco Bay estuary system. Bathymetric and acoustic backscatter data were...

  19. February 2007 Multibeam Mapping of Pulley Ridge, southwest Florida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This disk or set of disks contain high-resolution multibeam and backscatter maps of the Pulley Ridge Area, near the Tortugas, in the Gulf of Mexico. It includes the...

  20. Performance appraisal of multibeam system - Hydrosweep at different seabed provinces

    Digital Repository Service at National Institute of Oceanography (India)

    Kodagali, V.N.; Chakraborty, B.

    The performance of the multibeam sounding system (hydrosweep system) has been assessed at three varying zones of the seabed-continental shelf, continental slope, and deepsea seamount areas. Statistical studies were performed on the beamwise time...

  1. NOAA Ship Pisces Cruise PC1106 (14) Multibeam Sonar Workshop

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The overall objective is to familiarize participating scientists with PISCES multibeam echosounder (Simrad ME70) configuration, operation, calibration and data...

  2. Acoustic Multi-Beam Echosounder Data (ME70)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Southeast Fisheries Science Center Mississippi Laboratories collects data using a Simrad ME70 scientific multibeam acoustic echosounder during resource...

  3. Topology Control in Aerial Multi-Beam Directional Networks

    Science.gov (United States)

    2017-04-24

    Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology ...underlying challenges to topology control in multi-beam direction networks. Two topology control algorithms are developed: a centralized algorithm

  4. On board processing for future satellite communications systems: Comparison of FDM, TDM and hybrid accessing schemes

    Science.gov (United States)

    Berk, G.; Jean, P. N.; Rotholz, E.

    1982-01-01

    Several satellite uplink and downlink accessing schemes for customer premises service are compared. Four conceptual system designs are presented: satellite-routed frequency division multiple access (FDMA), satellite-switched time division multiple access (TDMA), processor-routed TDMA, and frequency-routed TDMA, operating in the 30/20 GHz band. The designs are compared on the basis of estimated satellite weight, system capacity, power consumption, and cost. The systems are analyzed for fixed multibeam coverage of the continental United States. Analysis shows that the system capacity is limited by the available satellite resources and by the terminal size and cost.

  5. Mosaic of gridded multibeam and lidar bathymetry of the US Territory of Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

  6. Coverage map of gridded multibeam and lidar bathymetry of the US Territory of Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded lidar bathymetry. Gridded (5 m cell size) multibeam bathymetry were collected aboard NOAA Ship Hiialaka'i and...

  7. Gridded multibeam bathymetry of Apra Harbor, Guam U.S. Territory

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded bathymetry from Apra Harbor, Guam U.S. Territory. The netCDF and Arc ASCII grids include multibeam bathymetry from the Reson SeaBat 8125 multibeam sonar...

  8. Advanced mobile satellite communications system using Ka and MM-wave bands in Japan's R and D satellite project

    Science.gov (United States)

    Isobe, Shunkichi; Ohmori, Shingo; Hamamoto, Naokazu; Yamamoto, Minoru

    1991-01-01

    Communications Research Laboratory (CRL) studied an advanced mobile satellite communications system using Ka and millimeter-wave bands in the R&D Satellite project. The project started in 1990 and the satellite will be launched in 1997. On-board multi-beam interconnecting is one of basic functions to realize one-hop connection among Very Small Aperture Terminals (VSATs), mobile, and hand-held terminals in future mobile satellite communications system. An Intermediate Frequency (IF) filter bank and regenerative transponder are suitable for this function. The transponder configuration of an advanced mobile communications mission of the R&D Satellite for experiment is shown. High power transmitters of Ka and millimeter-wave bands, a 3x3 IF filter band and Single Channel Per Carrier/Time Division Multiplexing (SCPC/TDM) regenerative MODEMS, which will be boarded on the R&D Satellite, are being developed for the purpose of studying the feasibility of advanced mobile communications system.

  9. An FDMA system concept for 30/20 GHz high capacity domestic satellite service

    Science.gov (United States)

    Berk, G.; Jean, P. N.; Rotholz, E.; White, B. E.

    1982-01-01

    The paper summarizes a feasibility study of a multibeam FDMA satellite system operating in the 30/20 GHz band. The system must accommodate a very high volume of traffic within the restrictions of a 5 kW solar cell array and a 2.5 GHz bandwidth. Multibeam satellite operation reduces the DC power demand and allows reuse of the available bandwidth. Interferences among the beams are brought to acceptable levels by appropriate frequency assignments. A transponder design is presented; it is greatly simplified by the application of a regional concept. System analysis shows that MSK modulation is appropriate for a high-capacity system because it conserves the frequency spectrum. Rain attenuation, a serious problem in this frequency band, is combatted with sufficient power margins and with coding. Link budgets, cost analysis, and weight and power calculations are also discussed. A satellite-routed FDMA system compares favorably in performance and cost with a satellite-switched TDMA system.

  10. Multi-beam injector development at LBL

    International Nuclear Information System (INIS)

    Rutkowski, H.L.; Faltens, A.; Brodzik, D.A.; Johnson, R.M.; Pike, C.D.; Vanecek, D.L.; Humphries, S. Jr.; Meyer, E.A.; Hewett, D.W.

    1990-06-01

    LBL is developing a multi-beam injector that will be used for scaled accelerator experiments related to Heavy Ion Fusion. The device will produce sixteen 0.5 Amp beams of C+ at 2 MeV energy. The carbon arc source has been developed to the point where the emittance is within a factor of four of the design target. Modelling of the source behavior to find ways to reduce the emittance is discussed. Source lifetime and reliability is also of paramount importance to us and data regarding the lifetime and failure modes of different source configurations is discussed. One half of the accelerating column has been constructed and tested at high voltage. One beam experiments in this half column are underway. The second half of the column is being built and the transition 2 MV experiments should begin soon. In addition to beam and source performance we also discuss the controls for the injector and the electronics associated with the source and current injection. 3 refs., 2 figs

  11. Multibeam smart antenna field trial experiments in mobile radio environments

    Science.gov (United States)

    Perini, Patrick

    1996-01-01

    Several types of high gain multibeam antennas were tested and compared to traditional sector and omni antennas in various mobile radio environments. A vehicle equipped with a mobile transmitter drove in several mobile radio environments while the received signal strength (RSS) was recorded on multiple antenna channels attached to multibeam, sector and omni directional antennas. The RSS data recorded included the fast (rayleigh) fading and was averaged into local means based on the mobile's position/speed. Description of the experiment and analysis of the gain improvement, average RSS, diversity gain are presented.

  12. 'Taking X-ray phase contrast imaging into mainstream applications' and its satellite workshop 'Real and reciprocal space X-ray imaging'.

    Science.gov (United States)

    Olivo, Alessandro; Robinson, Ian

    2014-03-06

    A double event, supported as part of the Royal Society scientific meetings, was organized in February 2013 in London and at Chicheley Hall in Buckinghamshire by Dr A. Olivo and Prof. I. Robinson. The theme that joined the two events was the use of X-ray phase in novel imaging approaches, as opposed to conventional methods based on X-ray attenuation. The event in London, led by Olivo, addressed the main roadblocks that X-ray phase contrast imaging (XPCI) is encountering in terms of commercial translation, for clinical and industrial applications. The main driver behind this is the development of new approaches that enable XPCI, traditionally a synchrotron method, to be performed with conventional laboratory sources, thus opening the way to its deployment in clinics and industrial settings. The satellite meeting at Chicheley Hall, led by Robinson, focused on the new scientific developments that have recently emerged at specialized facilities such as third-generation synchrotrons and free-electron lasers, which enable the direct measurement of the phase shift induced by a sample from intensity measurements, typically in the far field. The two events were therefore highly complementary, in terms of covering both the more applied/translational and the blue-sky aspects of the use of phase in X-ray research. 

  13. Dualband MW/LW Strained Layer Superlattice Focal Plane Arrays for Satellite-Based Wildfire Detection, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Infrared focal plane arrays (FPAs) based on Type-II strained layer superlattice (SLS) photodiodes have recently experienced significant advances. In Phase I we...

  14. Comparative study of FDMA, TDMA and hybrid 30/20 GHz satellite communications systems for small users

    Science.gov (United States)

    Berk, G.; Jean, P. N.; Rotholz, E.

    1982-01-01

    This study compares several satellite uplink and downlink accessing schemes for a Customer Premises Service. Four conceptual system designs are presented: Satellite-Routed FDMA, Frequency-Routed TDMA, Satellite-Switched TDMA, and Processor-Routed TDMA, operating in the 30/20 GHz band. The designs are compared on the basis of estimated satellite weight, power consumption, and cost. The system capacities are analyzed for a fixed multibeam coverage of CONUS. Analysis shows that the system capacity is limited by the available satellite resources and by the terminal size and cost.

  15. The phase space and stellar populations of cluster galaxies at z ∼ 1: simultaneous constraints on the location and timescale of satellite quenching

    Energy Technology Data Exchange (ETDEWEB)

    Muzzin, Adam; Van der Burg, R. F. J.; McGee, Sean L.; Balogh, Michael; Franx, Marijn; Hoekstra, Henk [Leiden Observatory, Leiden University, P.O. Box 9513, 2300 RA Leiden (Netherlands); Hudson, Michael J. [Department of Physics and Astronomy, University of Waterloo, Waterloo, ON N2L 3G1 (Canada); Noble, Allison; Taranu, Dan S.; Yee, H. K. C. [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON M5S 3H4 (Canada); Webb, Tracy [Department of Physics, McGill University, Montréal, QC (Canada); Wilson, Gillian [Department of Physics and Astronomy, University of California, Riverside, CA 92521 (United States)

    2014-11-20

    We investigate the velocity versus position phase space of z ∼ 1 cluster galaxies using a set of 424 spectroscopic redshifts in nine clusters drawn from the GCLASS survey. Dividing the galaxy population into three categories, that is, quiescent, star-forming, and poststarburst, we find that these populations have distinct distributions in phase space. Most striking are the poststarburst galaxies, which are commonly found at small clustercentric radii with high clustercentric velocities, and appear to trace a coherent 'ring' in phase space. Using several zoom simulations of clusters, we show that the coherent distribution of the poststarbursts can be reasonably well reproduced using a simple quenching scenario. Specifically, the phase space is best reproduced if these galaxies are quenched with a rapid timescale (0.1 <τ {sub Q} < 0.5 Gyr) after they make their first passage of R ∼ 0.5 R {sub 200}, a process that takes a total time of ∼1 Gyr after first infall. The poststarburst phase space is not well reproduced using long quenching timescales (τ {sub Q} > 0.5 Gyr) or by quenching galaxies at larger radii (R ∼ R {sub 200}). We compare this quenching timescale to the timescale implied by the stellar populations of the poststarburst galaxies and find that the poststarburst spectra are well-fit by a rapid quenching (τ {sub Q} = 0.4{sub −0.4}{sup +0.3} Gyr) of a typical star-forming galaxy. The similarity between the quenching timescales derived from these independent indicators is a strong consistency check of the quenching model. Given that the model implies satellite quenching is rapid and occurs well within R {sub 200}, this would suggest that ram-pressure stripping of either the hot or cold gas component of galaxies are the most plausible candidates for the physical mechanism. The high cold gas consumption rates at z ∼ 1 make it difficult to determine whether hot or cold gas stripping is dominant; however, measurements of the redshift

  16. Application of photonics in next generation telecommunication satellites payloads

    Science.gov (United States)

    Anzalchi, J.; Inigo, P.; Roy, B.

    2017-11-01

    Next generation broadband telecommunication satellites are required to provide very high data throughput using complex multibeam architectures. These high throughput `Terabit/s' Satellites will incorporate payloads with very large quantity of conventional RF equipment, co-axial cables, waveguides, harnesses and ancillary equipment, making the Assembly, Integration and Test (AIT) very complex. Use of `RF over Fiber' and associated photonics equipment can make the process of AIT much simpler with the added benefit of significant reduction in number of payload equipment and inherent payload mass.

  17. Novel multi-beam radiometers for accurate ocean surveillance

    DEFF Research Database (Denmark)

    Cappellin, C.; Pontoppidan, K.; Nielsen, P. H.

    2014-01-01

    Novel antenna architectures for real aperture multi-beam radiometers providing high resolution and high sensitivity for accurate sea surface temperature (SST) and ocean vector wind (OVW) measurements are investigated. On the basis of the radiometer requirements set for future SST/OVW missions...

  18. Discrimination of Closely-Spaced Geosynchronous Satellites - Phase Curve Analysis & New Small Business Innovative Research (SBIR) Efforts

    Science.gov (United States)

    Levan, P.

    2010-09-01

    Geosynchronous objects appear as unresolved blurs even when observed with the largest ground-based telescopes. Due to the lack of any spatial detail, two or more objects appearing at similar brightness levels within the spectral bandpass they are observed are difficult to distinguish. Observing a changing pattern of such objects from one time epoch to another showcases the deficiencies in associating individual objects before and after the configuration change. This paper explores solutions to this deficiency in the form of spectral (under small business innovative research) and phase curve analyses. The extension of the technique to phase curves proves to be a powerful new capability.

  19. Comparison of Shallow Survey 2012 Multibeam Datasets

    Science.gov (United States)

    Ramirez, T. M.

    2012-12-01

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

  20. Seabottom characterization using multibeam echosounder angular backscatter: An application of the composite roughness theory

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Schenke, H.W.; Kodagali, V.N.; Hagen, R.

    multibeam echosounding systems reveal significant results related to seabottom geological processes ([3] and references therein). Jackson et al., [1] had proposed simultaneous application of the two backscatter theories related to the large and small-scale... to acquire multibeam deep ocean seabottom backscatter data of higher angular range (62 20 14 incidence angle). However, with the commercial availability of the multibeam-Hydrosweep system [4], which operates at a 45 14 half fan width, it has become possible...

  1. Optical recording in functional polymer nanocomposites by multi-beam interference holography

    Science.gov (United States)

    Zhuk, Dmitrij; Burunkova, Julia; Kalabin, Viacheslav; Csarnovics, Istvan; Kokenyesi, Sandor

    2017-05-01

    Our investigations relate to the development of new polymer nanocomposite materials and technologies for fabrication of photonic elements like gratings, integrated elements, photonic crystals. The goal of the present work was the development and application of the multi-beam interference method for one step, direct formation of 1-, 2- or even 3D photonic structures in functional acrylate nanocomposites, which contain SiO2 and Au nanoparticles and which are sensitized to blue and green laser illumination. The presence of gold nanoparticles and possibility to excite plasmonic effects can essentially influence the polymerization processes and the spatial redistribution of nanoparticles in the nanocomposite during the recording. This way surface and volume phase reliefs can be recorded. It is essential, that no additional treatments of the material after the recording are necessary and the elements possess high transparency, are stable after some relaxation time. New functionalities can be provided to the recorded structures if luminescent materials are added to such materials.

  2. GOLD MINERAL PROSPECTING USING PHASED ARRAY TYPE L-BAND SYNTHETIC APERTURE RADAR (PALSAR SATELLITE REMOTE SENSING DATA, CENTRAL GOLD BELT, MALAYSIA

    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour

    2016-06-01

    Full Text Available The Bentong-Raub Suture Zone (BRSZ of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.

  3. Impulsive and gradual phases of a solar limb flare as observed from the solar maximum mission satellite

    Energy Technology Data Exchange (ETDEWEB)

    Poland, A.I.; Frost, K.J.; Woodgate, B.E.; Shine, R.A.; Kenny, P.J. (National Aeronautics and Space Administration, Greenbelt, MD (USA). Lab. for Astronomy and Solar Physics); Machado, M.E. (Observatorio Nacional de Fisica Cosmica, San Miguel (Argentina)); Wolfson, C.J.; Bruner, E.C. (Lockheed Palo Alto Research Labs., CA (USA)); Cheng, C.C. (Naval Research Lab., Washington, DC (USA)); Tandberg-Hanssen, E.A. (National Aeronautics and Space Administration, Huntsville, AL (USA). George C. Marshall Space Flight Center)

    1982-06-01

    Simultaneous observations of a solar limb flare in the X-ray and ultraviolet regions of the spectrum are presented. Temporal and spectral X-ray observations were obtained for the 25-300 keV range while temporal, spectral, and spatial X-ray observations were obtained for the 30-0.3 keV range. The ultraviolet observations were images with a 10'' spatial resolution in the lines of O v (Tsub(e) approx. equal to 2.5 x 10/sup 5/ K) and Fe XXI (Tsub(e) approx. equal to 1.1 x 10/sup 7/ K). The hard X-ray and O v data indicate that the impulsive phase began in the photosphere or chromosphere and continued for several minutes as material was ejected into the corona. Impulsive excitation was observed up to 30,000 km above the solar surface at specific points in the flare loop. The Fe XXI observations indicate a preheating before the impulsive phase and showed the formation of hot post-flare loops. This later formation was confirmed by soft X-ray observations. These observations provide limitations for current flare models and will provide the data needed for initial conditions in modeling the concurrent coronal transient.

  4. The impulsive and gradual phases of a solar limb flare as observed from the solar maximum mission satellite

    International Nuclear Information System (INIS)

    Poland, A.I.; Frost, K.J.; Woodgate, B.E.; Shine, R.A.; Kenny, P.J.; Wolfson, C.J.; Bruner, E.C.; Cheng, C.C.; Tandberg-Hanssen, E.A.

    1982-01-01

    Simultaneous observations of a solar limb flare in the X-ray and ultraviolet regions of the spectrum are presented. Temporal and spectral X-ray observations were obtained for the 25-300 keV range while temporal, spectral, and spatial X-ray observations were obtained for the 30-0.3 keV range. The ultraviolet observations were images with a 10'' spatial resolution in the lines of O v (Tsub(e) approx. equal to 2.5 x 10 5 K) and Fe XXI (Tsub(e) approx. equal to 1.1 x 10 7 K). The hard X-ray and O v data indicate that the impulsive phase began in the photosphere or chromosphere and continued for several minutes as material was ejected into the corona. Impulsive excitation was observed up to 30,000 km above the solar surface at specific points in the flare loop. The Fe XXI observations indicate a preheating before the impulsive phase and showed the formation of hot post-flare loops. This later formation was confirmed by soft X-ray observations. These observations provide limitations for current flare models and will provide the data needed for initial conditions in modeling the concurrent coronal transient. (orig.)

  5. Saturn satellites

    International Nuclear Information System (INIS)

    Ruskol, E.L.

    1981-01-01

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

  6. Advanced Communications Technology Satellite (ACTS): Four-Year System Performance

    Science.gov (United States)

    Acosta, Roberto J.; Bauer, Robert; Krawczyk, Richard J.; Reinhart, Richard C.; Zernic, Michael J.; Gargione, Frank

    1999-01-01

    The Advanced Communications Technology Satellite (ACTS) was conceived at the National Aeronautics and Space Administration (NASA) in the late 1970's as a follow-on program to ATS and CTS to continue NASA's long history of satellite communications projects. The ACTS project set the stage for the C-band satellites that started the industry, and later the ACTS project established the use of Ku-band for video distribution and direct-to-home broadcasting. ACTS, launched in September 1993 from the space shuttle, created a revolution in satellite system architecture by using digital communications techniques employing key technologies such as a fast hopping multibeam antenna, an on-board baseband processor, a wide-band microwave switch matrix, adaptive rain fade compensation, and the use of 900 MHz transponders operating at Ka-band frequencies. This paper describes the lessons learned in each of the key ACTS technology areas, as well as in the propagation investigations.

  7. In vivo endoscopic multi-beam optical coherence tomography

    Energy Technology Data Exchange (ETDEWEB)

    Standish, Beau A; Mariampillai, Adrian; Munce, Nigel R; Leung, Michael K K; Vitkin, I Alex [Deptartment of Medical Biophysics, University of Toronto, Toronto (Canada); Lee, Kenneth K C; Yang, Victor X D [Ontario Cancer Institute/University Health Network, Toronto (Canada)], E-mail: standish@ee.ryerson.ca

    2010-02-07

    A multichannel optical coherence tomography (multi-beam OCT) system and an in vivo endoscopic imaging probe were developed using a swept-source OCT system. The distal optics were micro-machined to produce a high numerical aperture, multi-focus fibre optic array. This combination resulted in a transverse design resolution of <10 {mu}m full width half maximum (FWHM) throughout the entire imaging range, while also increasing the signal intensity within the focus of the individual channels. The system was used in a pre-clinical rabbit study to acquire in vivo structural images of the colon and ex vivo images of the oesophagus and trachea. A good correlation between the structural multi-beam OCT images and H and E histology was achieved, demonstrating the feasibility of this high-resolution system and its potential for in vivo human endoscopic imaging.

  8. In vivo endoscopic multi-beam optical coherence tomography

    International Nuclear Information System (INIS)

    Standish, Beau A; Mariampillai, Adrian; Munce, Nigel R; Leung, Michael K K; Vitkin, I Alex; Lee, Kenneth K C; Yang, Victor X D

    2010-01-01

    A multichannel optical coherence tomography (multi-beam OCT) system and an in vivo endoscopic imaging probe were developed using a swept-source OCT system. The distal optics were micro-machined to produce a high numerical aperture, multi-focus fibre optic array. This combination resulted in a transverse design resolution of <10 μm full width half maximum (FWHM) throughout the entire imaging range, while also increasing the signal intensity within the focus of the individual channels. The system was used in a pre-clinical rabbit study to acquire in vivo structural images of the colon and ex vivo images of the oesophagus and trachea. A good correlation between the structural multi-beam OCT images and H and E histology was achieved, demonstrating the feasibility of this high-resolution system and its potential for in vivo human endoscopic imaging.

  9. Reanalyses of the radiation belt electron phase space density using nearly equatorial CRRES and polar-orbiting Akebono satellite observations

    Science.gov (United States)

    Ni, Binbin; Shprits, Yuri; Nagai, Tsugunobu; Thorne, Richard; Chen, Yue; Kondrashov, Dmitri; Kim, Hee-jeong

    2009-05-01

    Data assimilation techniques provide algorithms that allow for blending of incomplete and inaccurate data with physics-based dynamic models to reconstruct the electron phase space density (PSD) in the radiation belts. In this study, we perform reanalyses of the radial PSD profile using two independent data sources from the nearly equatorial CRRES Medium Electron A (MEA) observations and the polar-orbiting Akebono Radiation Monitor (RDM) measurements for a 50-day period from 18 August to 6 October 1990. We utilize the University of California, Los Angeles, One-Dimensional Versatile Electron Radiation Belt (UCLA 1-D VERB) code and a Kalman filtering approach. Comparison of the reanalyses obtained independently using the CRRES MEA and Akebono RDM measurements shows that the dynamics of the PSD can be accurately reconstructed using Kalman filtering even when available data are sparse, inaccurate, and contaminated by random errors. The reanalyses exhibit similarities in the locations and magnitudes of peaks in radial profiles of PSD and the rate and radial extent of the dropouts during storms. This study shows that when unidirectional data are not available, pitch angle averaged flux measurements can be used to infer the long-term behavior (climatology) of the radiation belts. The methodology of obtaining PSD from pitch angle averaged and unidirectional fluxes using the Tsyganenko and Stern (1996) magnetic field model is described in detail.

  10. Vibration piezoelectric energy harvester with multi-beam

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Yan, E-mail: yanc@dlut.edu.cn; Zhang, Qunying, E-mail: zhangqunying89@126.com; Yao, Minglei, E-mail: yaomingleiok@126.com [Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education, Dalian University of Technology, 116024, Dalian, Liaoning Province (China); Dong, Weijie, E-mail: dongwj@dlut.edu.cn [School of Electronic and Information Engineering, Dalian University of Technology, 116024, Dalian, Liaoning Province (China); Gao, Shiqiao, E-mail: gaoshq@bit.edu.cn [State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, 100081, Beijing Province (China)

    2015-04-15

    This work presents a novel vibration piezoelectric energy harvester, which is a micro piezoelectric cantilever with multi-beam. The characteristics of the PZT (Pb(Zr{sub 0.53}Ti{sub 0.47})O{sub 3}) thin film were measured; XRD (X-ray diffraction) pattern and AFM (Atomic Force Microscope) image of the PZT thin film were measured, and show that the PZT (Pb(Zr{sub 0.53}Ti{sub 0.47})O{sub 3}) thin film is highly (110) crystal oriented; the leakage current is maintained in nA magnitude, the residual polarisation Pr is 37.037 μC/cm{sup 2}, the coercive field voltage Ec is 27.083 kV/cm, and the piezoelectric constant d{sub 33} is 28 pC/N. In order to test the dynamic performance of the energy harvester, a new measuring system was set up. The maximum output voltage of the single beam of the multi-beam can achieve 80.78 mV under an acceleration of 1 g at 260 Hz of frequency; the maximum output voltage of the single beam of the multi-beam is almost 20 mV at 1400 Hz frequency. .

  11. Multibeam 3D Underwater SLAM with Probabilistic Registration

    Directory of Open Access Journals (Sweden)

    Albert Palomer

    2016-04-01

    Full Text Available This paper describes a pose-based underwater 3D Simultaneous Localization and Mapping (SLAM using a multibeam echosounder to produce high consistency underwater maps. The proposed algorithm compounds swath profiles of the seafloor with dead reckoning localization to build surface patches (i.e., point clouds. An Iterative Closest Point (ICP with a probabilistic implementation is then used to register the point clouds, taking into account their uncertainties. The registration process is divided in two steps: (1 point-to-point association for coarse registration and (2 point-to-plane association for fine registration. The point clouds of the surfaces to be registered are sub-sampled in order to decrease both the computation time and also the potential of falling into local minima during the registration. In addition, a heuristic is used to decrease the complexity of the association step of the ICP from O ( n 2 to O ( n . The performance of the SLAM framework is tested using two real world datasets: First, a 2.5D bathymetric dataset obtained with the usual down-looking multibeam sonar configuration, and second, a full 3D underwater dataset acquired with a multibeam sonar mounted on a pan and tilt unit.

  12. Systems analysis for modular versus multi-beam HIF drivers

    International Nuclear Information System (INIS)

    Meier, W.R.; Logan, B.G.

    2004-01-01

    Previous modeling for HIF drivers concentrated on designs in which 100 or more beams are grouped in an array and accelerated through a common set of induction cores. The total beam energy required by the target is achieved by the combination of final ion energy, current per beam and number of beams. Economic scaling favors a large number of small (∼1 cm dia.) beams. An alternative architecture has now been investigated, which we refer to as a modular driver. In this case, the driver is subdivided into many (>10) independent accelerators with one or many beams each. A key objective of the modular driver approach is to be able to demonstrate all aspects of the driver (source-to-target) by building a single, lower cost module compared to a full-scale, multi-beam driver. We consider and compare several design options for the modular driver including single-beam designs with solenoid instead of quadrupole magnets in order to transport the required current per module in a single beam, solenoid/quad combinations, and multi-beam, all-quad designs. The drivers are designed to meet the requirements of the hybrid target, which can accommodate a larger spot size than the distributed radiator target that was used for the Robust Point Design. We compare the multi-beam and modular driver configuration for a variety and assumptions and identify key technology advances needed for the modular design

  13. The start-up phase of the national satellite forest monitoring systems for DRC and PNG: a joint venture between FAO and INPE

    Science.gov (United States)

    Jonckheere, I. G.; FAO UN-REDD Team Forestry Department

    2011-12-01

    Reducing Emissions from Deforestation and Forest Degradation (REDD) is an effort to create a financial value for the carbon stored in forests, offering incentives for developing countries to reduce emissions from forested lands and invest in low-carbon paths to sustainable development. "REDD+" goes beyond deforestation and forest degradation, and includes the role of conservation, sustainable management of forests and enhancement of forest carbon stocks. In the framework of getting countries ready for REDD+, the UN-REDD Programme, a partnership between UNEP, FAO and UNDP, assists developing countries to prepare and implement national REDD+ strategies. Designed collaboratively by a broad range of stakeholders, national UN-REDD Programmes are informed by the technical expertise of FAO, UNDP and UNEP. For the monitoring, reporting and verification, FAO supports the countries to develop satellite forest monitoring systems that allow for credible measurement, reporting and verification (MRV)of REDD+ activities. These are among the most critical elements for the successful implementation of any REDD+ mechanism, also following the COP 16 decisions in Cancun last year. The UN-REDD Programme through a joint effort of FAO and Brazil's National Space Agency, INPE, is supporting countries to develop cost-effective, robust and compatible national monitoring and MRV systems, providing tools, methodologies, training and knowledge sharing that help countries to strengthen their technical and institutional capacity for effective MRV systems. To develop strong nationally-owned forest monitoring systems, technical and institutional capacity building is key. The UN-REDD Programme, through FAO, has taken on intensive training together with INPE, and has provided technical help and assistance for in-country training and implementation for national satellite forest monitoring. The goal of the start-up phase for DRC and Papua New Guinea (PNG) in this capacity building effort is the

  14. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  15. A DC excited waveguide multibeam CO2 laser using high frequency ...

    Indian Academy of Sciences (India)

    High power industrial multibeam CO2 lasers consist of a large number of closely packed ... by producing pre-ionization using an auxiliary high frequency pulsed ... of few kilowatts output power, multibeam technique is used [2]. .... gas mixture of CO2, N2 and He enters in each discharge tube individually from .... Commercial.

  16. Satellite Communications

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'

  17. Multibeam bathymetry and CTD measurements in two fjord systems in southeastern Greenland

    Science.gov (United States)

    Kjellerup Kjeldsen, Kristian; Weinrebe, Reimer Wilhelm; Bendtsen, Jørgen; Anker Bjørk, Anders; Kjær, Kurt Henrik

    2017-08-01

    We present bathymetry and hydrological observations collected in the summer of 2014 from two fjord systems in southeastern Greenland with a multibeam sonar system. Our results provide a detailed bathymetric map of the fjord complex around the island of Skjoldungen in Skjoldungen Fjord and the outer part of Timmiarmiut Fjord and show far greater depths compared to the International Bathymetric Chart of the Arctic Ocean. The hydrography collected shows different properties in the fjords with the bottom water masses below 240 m in Timmiarmiut Fjord being 1-2 °C warmer than in the two fjords around Skjoldungen, but data also illustrate the influence of sills on the exchange of deeper water masses within fjords. Moreover, evidence of subglacial discharge in Timmiarmiut Fjord, which is consistent with satellite observations of ice mélange set into motion, adds to our increasing understanding of the distribution of subglacial meltwater. Data are available through the PANGAEA website at pangaea.de/10.1594/PANGAEA.860627" target="_blank">https://doi.pangaea.de/10.1594/PANGAEA.860627.

  18. Multibeam bathymetry and CTD measurements in two fjord systems in southeastern Greenland

    Directory of Open Access Journals (Sweden)

    K. K. Kjeldsen

    2017-08-01

    Full Text Available We present bathymetry and hydrological observations collected in the summer of 2014 from two fjord systems in southeastern Greenland with a multibeam sonar system. Our results provide a detailed bathymetric map of the fjord complex around the island of Skjoldungen in Skjoldungen Fjord and the outer part of Timmiarmiut Fjord and show far greater depths compared to the International Bathymetric Chart of the Arctic Ocean. The hydrography collected shows different properties in the fjords with the bottom water masses below 240 m in Timmiarmiut Fjord being 1–2 °C warmer than in the two fjords around Skjoldungen, but data also illustrate the influence of sills on the exchange of deeper water masses within fjords. Moreover, evidence of subglacial discharge in Timmiarmiut Fjord, which is consistent with satellite observations of ice mélange set into motion, adds to our increasing understanding of the distribution of subglacial meltwater. Data are available through the PANGAEA website at https://doi.pangaea.de/10.1594/PANGAEA.860627.

  19. Satellite communication transponders and their reliability; Eisei tosai tsushin kiki oyobi shinraisei ni tsuite

    Energy Technology Data Exchange (ETDEWEB)

    Ogawa, H [NTT Wireless System Laboratories, Kanagawa (Japan)

    1994-11-01

    The Engineering Test Satellite-VI is a large composite test satellite weighing two tons to perform different communication experiments. Adoption of the multi-beam satellite communication system has made possible to increase the transmission capacity, reduce the sizes of earth stations, and utilize frequencies more effectively. This paper describes the configuration of the relaying devices mounted thereon, the newly developed circuit technologies, and their reliability. The multi-beam satellite communication system mounts a number of transponders, with the frequency bands used divided into the 2.6/2.5 GHz band between the moving body and the satellite, the 6/4 GHz band for the channels between the earth stations and the satellite, and the 30/20 GHz band for the fixed communications. These arrangements were intended to achieve large size reduction as a result of applying the integrated circuit technology. The transmitters and the receivers corresponding to each beam are connected by using the satellite switches (16 inputs {times} 12 outputs). The parts used were general purpose ones rather than those specified in the MIL standards because of their number having reached so huge. Their reliability was ensured by long-term burn-in operations. 5 refs., 6 figs., 1 tab.

  20. Multibeam collection for EW9104: Multibeam data collected aboard Maurice Ewing from 1991-06-16 to 1991-07-27, Papeete, French Polynesia to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW0212: Multibeam data collected aboard Maurice Ewing from 2002-11-17 to 2002-11-20, Puntarenas, Costa Rica to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EW0007: Multibeam data collected aboard Maurice Ewing from 2000-07-15 to 2000-08-16, St. John's, Newfoundland to Newark, NJ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for EW0209: Multibeam data collected aboard Maurice Ewing from 2002-09-07 to 2002-09-11, Newport, OR to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for EW0201: Multibeam data collected aboard Maurice Ewing from 2002-01-31 to 2002-02-14, Hobart, Tasmania to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EW9414: Multibeam data collected aboard Maurice Ewing from 1994-10-03 to 1994-10-10, Coos Bay, OR to Long Beach, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EW9415: Multibeam data collected aboard Maurice Ewing from 1994-10-13 to 1994-10-21, Long Beach, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EW9506: Multibeam data collected aboard Maurice Ewing from 1995-07-19 to 1995-07-26, San Francisco, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for EW9504: Multibeam data collected aboard Maurice Ewing from 1995-05-17 to 1995-06-07, San Diego, CA to Eureka, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for EW9601: Multibeam data collected aboard Maurice Ewing from 1996-02-07 to 1996-03-13, Lyttelton, New Zealand to Lyttelton, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for EW9416: Multibeam data collected aboard Maurice Ewing from 1994-11-03 to 1994-11-08, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9603: Multibeam data collected aboard Maurice Ewing from 1996-05-14 to 1996-05-31, Papeete, French Polynesia to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW9309: Multibeam data collected aboard Maurice Ewing from 1993-11-20 to 1993-12-26, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EW9401: Multibeam data collected aboard Maurice Ewing from 1994-01-04 to 1994-02-13, Montevideo, Uruguay to Salvador de Bahia, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for EW9303: Multibeam data collected aboard Maurice Ewing from 1993-06-26 to 1993-07-20, Reykjavik, Iceland to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW0102: Multibeam data collected aboard Maurice Ewing from 2001-03-10 to 2001-04-05, Charleston, SC to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9708: Multibeam data collected aboard Maurice Ewing from 1997-11-06 to 1997-12-06, Manzanillo, Mexico to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW9706: Multibeam data collected aboard Maurice Ewing from 1997-08-20 to 1997-09-05, Lisbon, Portugal to Cristobal, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for EW0211: Multibeam data collected aboard Maurice Ewing from 2002-11-08 to 2002-11-12, Manzanillo, Mexico to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for EW9803: Multibeam data collected aboard Maurice Ewing from 1998-03-15 to 1998-04-06, Bridgetown, Barbados to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9501: Multibeam data collected aboard Maurice Ewing from 1995-02-16 to 1995-03-21, Tampa, FL to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9903: Multibeam data collected aboard Maurice Ewing from 1999-03-10 to 1999-04-12, Cristobal, Panama to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EW0103: Multibeam data collected aboard Maurice Ewing from 2001-04-08 to 2001-04-12, San Juan, Puerto Rico to Colon, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for EW9910: Multibeam data collected aboard Maurice Ewing from 1999-08-30 to 1999-09-15, Agana, Guam to Lae, Papua New Guinea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for EW0206: Multibeam data collected aboard Maurice Ewing from 2002-06-14 to 2002-07-02, Kodiak, AK to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EW0409: Multibeam data collected aboard Maurice Ewing from 2004-09-28 to 2004-10-14, Kodiak, AK to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EW9806: Multibeam data collected aboard Maurice Ewing from 1998-07-02 to 1998-08-13, Halifax, Canada to Halifax, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EW0008: Multibeam data collected aboard Maurice Ewing from 2000-09-02 to 2000-10-17, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for EW9301: Multibeam data collected aboard Maurice Ewing from 1993-05-16 to 1993-05-23, Jacksonville, FL to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for EW0402: Multibeam data collected aboard Maurice Ewing from 2004-02-27 to 2004-03-01, Progresso, Mexico to Gulfport, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for EW9608: Multibeam data collected aboard Maurice Ewing from 1996-10-18 to 1996-11-16, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9002: Multibeam data collected aboard Maurice Ewing from 1990-06-20 to 1990-06-24, Miami, FL to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW9707: Multibeam data collected aboard Maurice Ewing from 1997-09-09 to 1997-10-24, Balboa, Panama to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EW0301: Multibeam data collected aboard Maurice Ewing from 2003-04-13 to 2003-05-10, Norfolk, VA to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for EW9404: Multibeam data collected aboard Maurice Ewing from 1994-04-09 to 1994-04-14, Bridgetown, Barbados to Cristobal, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW9304: Multibeam data collected aboard Maurice Ewing from 1993-08-01 to 1993-08-09, Woods Hole, MA to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9907: Multibeam data collected aboard Maurice Ewing from 1999-06-18 to 1999-07-19, Yokohama, Japan to Kochi, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW9102: Multibeam data collected aboard Maurice Ewing from 1991-03-21 to 1991-05-07, Punta Arenas, Chile to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for EW0203: Multibeam data collected aboard Maurice Ewing from 2002-03-28 to 2002-04-25, Guam to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for EW9802: Multibeam data collected aboard Maurice Ewing from 1998-02-15 to 1998-03-12, Honolulu, HI to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9502: Multibeam data collected aboard Maurice Ewing from 1995-03-27 to 1995-04-27, Balboa, Panama to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9405: Multibeam data collected aboard Maurice Ewing from 1994-04-20 to 1994-05-14, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EW0005: Multibeam data collected aboard Maurice Ewing from 2000-05-27 to 2000-06-27, Puntarenas, Costa Rica to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for EW9206: Multibeam data collected aboard Maurice Ewing from 1992-05-27 to 1992-05-31, Cristobal, Panama to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for EW0406: Multibeam data collected aboard Maurice Ewing from 2004-06-23 to 2004-07-09, Tampa, FL to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EW0104: Multibeam data collected aboard Maurice Ewing from 2001-04-14 to 2001-05-19, Cristobal, Panama to Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EW0403: Multibeam data collected aboard Maurice Ewing from 2004-04-07 to 2004-04-13, Mobile, AL to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for 650610_p_100: Multibeam data collected aboard Mary Sears from 2010-08-08 to 2010-09-03, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for SEA1201P: Multibeam data collected aboard Mary Sears from 2012-03-20 to 2012-05-11, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for RR1208: Multibeam data collected aboard Roger Revelle from 2012-06-28 to 2012-07-17, Danang, Vietnam to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AT21-02: Multibeam data collected aboard Atlantis from 2012-06-01 to 2012-06-17, Bridgetown, Barbados to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for MV1012: Multibeam data collected aboard Melville from 2010-09-25 to 2010-10-03, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AT26-15: Multibeam data collected aboard Atlantis from 2014-05-21 to 2014-06-14, Gulfport, MS to St. Petersburg, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for FK140625: Multibeam data collected aboard Falkor from 2014-06-25 to 2014-07-07, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for SEAW02RR: Multibeam data collected aboard Roger Revelle from 2001-02-17 to 2001-02-25, San Diego, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for MV1302: Multibeam data collected aboard Melville from 2013-02-01 to 2013-02-15, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for MGL1205: Multibeam data collected aboard Marcus G. Langseth from 2012-03-04 to 2012-03-21, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for MGL1204: Multibeam data collected aboard Marcus G. Langseth from 2012-02-02 to 2012-02-29, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for B00027: Multibeam data collected aboard Surveyor from 1985-09-03 to 1985-09-15, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for A131L11: Multibeam data collected aboard Atlantis II from 1994-03-10 to 1994-03-22, Acapulco, Mexico to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KN203-02: Multibeam data collected aboard Knorr from 2011-08-22 to 2011-09-22, Reykjavik, Iceland to Isafjorour, Iceland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW0303: Multibeam data collected aboard Maurice Ewing from 2003-05-28 to 2003-06-24, Gulfport, MS to Galveston, TX

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EX1004: Multibeam data collected aboard Okeanos Explorer from 2010-06-08 to 2010-08-19, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for FK150523: Multibeam data collected aboard Falkor from 2015-05-23 to 2015-06-22, Singapore, Singapore to Padang, Indonesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for BD0601: Multibeam data collected aboard Bowditch from 2006-10-16 to 2006-11-11, Okinawa, Japan to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for TN273: Multibeam data collected aboard Thomas G. Thompson from 2011-12-22 to 2012-01-22, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for TUNE06WT: Multibeam data collected aboard Thomas Washington from 1991-10-31 to 1991-12-02, Kwajalein, Marshall Islands to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EX1005: Multibeam data collected aboard Okeanos Explorer from 2010-08-23 to 2010-09-05, Apra, Guam to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGLN36MV: Multibeam data collected aboard Melville from 2008-04-05 to 2008-04-26, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM1004: Multibeam data collected aboard Kilo Moana from 2010-02-26 to 2010-03-11, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for EX1604: Multibeam data collected aboard Okeanos Explorer from 2016-03-23 to 2016-04-13, Kwajalein, Marshall Islands to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for MGL1206: Multibeam data collected aboard Marcus G. Langseth from 2012-03-24 to 2012-04-16, Apra, Guam to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MGLN01MV: Multibeam data collected aboard Melville from 2006-03-22 to 2006-04-11, San Diego, CA to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for FK151221: Multibeam data collected aboard Falkor from 2015-12-21 to 2016-01-05, Apra, Guam to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for FK141109: Multibeam data collected aboard Falkor from 2014-11-09 to 2014-12-09, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for FK151121: Multibeam data collected aboard Falkor from 2015-11-21 to 2015-12-17, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM0913: Multibeam data collected aboard Kilo Moana from 2009-06-07 to 2009-06-18, Apra, Guam to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EX1003: Multibeam data collected aboard Okeanos Explorer from 2010-05-19 to 2010-06-03, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for TN272: Multibeam data collected aboard Thomas G. Thompson from 2011-11-05 to 2011-12-17, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for FK141215: Multibeam data collected aboard Falkor from 2014-12-15 to 2014-12-21, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for TN233: Multibeam data collected aboard Thomas G. Thompson from 2009-04-20 to 2009-05-01, Apra, Guam to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for MGL1202: Multibeam data collected aboard Marcus G. Langseth from 2012-01-09 to 2012-01-24, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for TUNE08WT: Multibeam data collected aboard Thomas Washington from 1992-01-01 to 1992-01-31, Apra, Guam to Majuro, Marshall Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KM1021: Multibeam data collected aboard Kilo Moana from 2010-10-17 to 2010-11-09, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for MV1301: Multibeam data collected aboard Melville from 2013-01-16 to 2013-01-29, Honolulu, HI to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for TN275: Multibeam data collected aboard Thomas G. Thompson from 2012-02-11 to 2012-02-21, Apra, Guam to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for Heceta: Multibeam data collected aboard Ocean Alert from 1998-05-18 to 1998-05-23, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for RR0914: Multibeam data collected aboard Roger Revelle from 2009-11-06 to 2009-11-19, Apra, Guam to Nuku'alofa, Tonga

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for EW0410: Multibeam data collected aboard Maurice Ewing from 2004-10-21 to 2004-11-03, Astoria, OR to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for TN290B: Multibeam data collected aboard Thomas G. Thompson from 2013-01-16 to 2013-01-20, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KM1201: Multibeam data collected aboard Kilo Moana from 2012-01-04 to 2012-01-07, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for TN267: Multibeam data collected aboard Thomas G. Thompson from 2011-07-29 to 2011-08-09, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AMAT04RR: Multibeam data collected aboard Roger Revelle from 2006-04-18 to 2006-05-23, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KN205: Multibeam data collected aboard Knorr from 2012-02-22 to 2012-03-17, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KN184: Multibeam data collected aboard Knorr from 2006-08-07 to 2006-08-21, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KNOX11RR: Multibeam data collected aboard Roger Revelle from 2007-11-07 to 2007-11-24, Victoria, Seychelles to Port Louis, Mauritius

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW0112: Multibeam data collected aboard Maurice Ewing from 2001-10-06 to 2001-10-23, Seychelles to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for KN162L15: Multibeam data collected aboard Knorr from 2001-05-07 to 2001-05-20, Seychelles to Istanbul, Turkey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KNOX06RR: Multibeam data collected aboard Roger Revelle from 2007-06-18 to 2007-08-06, Phuket, Thailand to Singapore

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for cv11_seai: Multibeam data collected aboard Celtic Voyager from 2011-04-21 to 2011-04-29, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KM1006: Multibeam data collected aboard Kilo Moana from 2010-04-04 to 2010-04-14, Apra, Guam to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KIWI10RR: Multibeam data collected aboard Roger Revelle from 1998-03-24 to 1998-04-29, Lyttelton, New Zealand to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM0416: Multibeam data collected aboard Kilo Moana from 2004-08-28 to 2004-09-07, Honolulu, HI to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for MGLN06MV: Multibeam data collected aboard Melville from 2006-07-21 to 2006-08-31, Rabaul, Papua New Guinea to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for RR0916: Multibeam data collected aboard Roger Revelle from 2009-12-09 to 2009-12-15, Suva, Fiji to Nuku'alofa, Tonga

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KM0704: Multibeam data collected aboard Kilo Moana from 2007-04-19 to 2007-04-30, Suva, Fiji to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for RR0915: Multibeam data collected aboard Roger Revelle from 2009-11-21 to 2009-12-05, Nuku'alofa, Tonga to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for SO99: Multibeam data collected aboard Sonne from 1995-01-07 to 1995-01-14, Manila, Philippines to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for TUIM08MV: Multibeam data collected aboard Melville from 2005-07-01 to 2005-07-11, Suva, Fiji to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for BMRG08MV: Multibeam data collected aboard Melville from 1996-05-07 to 1996-06-08, Suva, Fiji to Pago Pago, American Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for TUIM06MV: Multibeam data collected aboard Melville from 2005-05-15 to 2005-06-02, Suva, Fiji to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW0002: Multibeam data collected aboard Maurice Ewing from 2000-02-05 to 2000-02-28, Lyttelton, New Zealand to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KM0409: Multibeam data collected aboard Kilo Moana from 2004-03-24 to 2004-04-03, Honolulu, HI to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for TUIM05MV: Multibeam data collected aboard Melville from 2005-04-05 to 2005-05-11, Nuku'alofa, Tonga to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KM1007: Multibeam data collected aboard Kilo Moana from 2010-04-16 to 2010-04-25, Suva, Fiji to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW0003: Multibeam data collected aboard Maurice Ewing from 2000-03-02 to 2000-03-26, Suva, Fiji to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM1023: Multibeam data collected aboard Kilo Moana from 2010-11-24 to 2010-12-08, Suva, Fiji to Nuku'alofa, Tonga

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW9512: Multibeam data collected aboard Maurice Ewing from 1995-11-23 to 1995-12-23, Suva, Fiji to Auckland, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for RR1310: Multibeam data collected aboard Roger Revelle from 2013-07-22 to 2013-08-25, Apra, Guam to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for RR1211: Multibeam data collected aboard Roger Revelle from 2012-09-09 to 2012-09-26, Suva, Fiji to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KM0411: Multibeam data collected aboard Kilo Moana from 2004-05-12 to 2004-05-19, Suva, Fiji to Wellington, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9511: Multibeam data collected aboard Maurice Ewing from 1995-10-16 to 1995-11-18, Honiara, Solomon Island to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for MGLN08MV: Multibeam data collected aboard Melville from 2006-10-04 to 2006-10-10, Suva, Fiji to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for BMRG07MV: Multibeam data collected aboard Melville from 1996-04-19 to 1996-05-03, Port Hedland, Australia to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KM0703: Multibeam data collected aboard Kilo Moana from 2007-03-14 to 2007-04-18, Townsville, Australia to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KM1022: Multibeam data collected aboard Kilo Moana from 2010-11-11 to 2010-11-21, Apra, Guam to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for MV1104: Multibeam data collected aboard Melville from 2011-03-23 to 2011-04-23, Valparaiso, Chile to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for AT15-61: Multibeam data collected aboard Atlantis from 2010-01-29 to 2010-03-03, Iquique, Chile to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for BAS_GAP: Multibeam data collected aboard James Clark Ross from 2003-06-13 to 2003-06-14, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for EW9805: Multibeam data collected aboard Maurice Ewing from 1998-05-16 to 1998-07-01, Halifax, Canada to Halifax, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for EW0310: Multibeam data collected aboard Maurice Ewing from 2003-11-14 to 2003-11-20, St. George's, Bermuda to Newark, NJ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW0107: Multibeam data collected aboard Maurice Ewing from 2001-07-02 to 2001-07-10, St. George's, Bermuda to Ponta Delgada, Azores

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW0309: Multibeam data collected aboard Maurice Ewing from 2003-10-22 to 2003-11-09, Bridgetown, Barbados to St. George's, Bermuda

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EW0108: Multibeam data collected aboard Maurice Ewing from 2001-07-23 to 2001-08-01, Patras, Greece to Piraeus, Greece

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for EW0208: Multibeam data collected aboard Maurice Ewing from 2002-08-12 to 2002-09-06, Newport, OR to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW9704: Multibeam data collected aboard Maurice Ewing from 1997-06-01 to 1997-07-04, Jacksonville, FL to Lisbon, Portugal

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9902: Multibeam data collected aboard Maurice Ewing from 1999-02-28 to 1999-03-05, Bridgetown, Barbados to Cristobal, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW0202: Multibeam data collected aboard Maurice Ewing from 2002-02-24 to 2002-03-26, Guam to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for EW9205: Multibeam data collected aboard Maurice Ewing from 1992-05-12 to 1992-05-26, Budhypramono, Marquesas Islands to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for EW0401: Multibeam data collected aboard Maurice Ewing from 2004-02-20 to 2004-02-26, Norfolk, VA to Progresso, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KNOX19RR: Multibeam data collected aboard Roger Revelle from 2008-08-21 to 2008-10-03, Miami, FL to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for HLY09TD: Multibeam data collected aboard Healy from 2009-07-06 to 2009-07-25, Seattle, WA to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EX0907: Multibeam data collected aboard Okeanos Explorer from 2009-07-14 to 2009-07-23, Astoria, OR to San Francisco, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for RB0703: Multibeam data collected aboard Ronald H. Brown from 2007-05-02 to 2007-05-29, Bridgetown, Barbados to Fort Lauderdale, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for SOJN02MV: Multibeam data collected aboard Melville from 1996-10-28 to 1996-11-21, Papeete, French Polynesia to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KM0505: Multibeam data collected aboard Kilo Moana from 2005-03-24 to 2005-04-01, Brisbane, Australia to Pago Pago, American Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for B00025: Multibeam data collected aboard Surveyor from 1985-08-29 to 1985-09-18, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for AT11L32: Multibeam data collected aboard Atlantis from 2005-09-08 to 2005-09-19, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for HLY0805: Multibeam data collected aboard Healy from 2008-08-14 to 2008-09-05, Barrow, AK to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for B00144: Multibeam data collected aboard Surveyor from 1988-06-08 to 1988-06-15, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for RB09TR: Multibeam data collected aboard Ronald H. Brown from 2009-01-15 to 2009-04-15, Rodman, Panama to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for TN274: Multibeam data collected aboard Thomas G. Thompson from 2012-01-25 to 2012-02-09, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for Puna-rid: Multibeam data collected aboard Ocean Alert from 1998-03-01 to 1998-03-03, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for HLY1302: Multibeam data collected aboard Healy from 2013-08-16 to 2013-09-07, Barrow, AK to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KM1116: Multibeam data collected aboard Kilo Moana from 2011-05-20 to 2011-06-07, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for B00118: Multibeam data collected aboard Davidson from 1987-11-09 to 1987-11-23, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for USF1999: Multibeam data collected aboard Bellows from 1999-02-17 to 1999-10-08, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for NEMO03MV: Multibeam data collected aboard Melville from 2000-05-15 to 2000-06-08, Manzanillo, Mexico to Puerto Caldera, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for AT18-12: Multibeam data collected aboard Atlantis from 2011-10-04 to 2011-10-28, San Diego, CA to Balboa, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for AT15-16: Multibeam data collected aboard Atlantis from 2007-02-13 to 2007-03-19, Manzanillo, Mexico to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for RR1412: Multibeam data collected aboard Roger Revelle from 2014-10-29 to 2014-11-23, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for RNDB02WT: Multibeam data collected aboard Thomas Washington from 1988-05-18 to 1988-06-10, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM0205: Multibeam data collected aboard Kilo Moana from 2002-09-22 to 2002-10-18, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for HLY07TC: Multibeam data collected aboard Healy from 2007-04-04 to 2007-04-09, Seattle, WA to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for HLY13TC: Multibeam data collected aboard Healy from 2013-09-08 to 2013-09-21, Barrow, AK to Seward, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EW9602: Multibeam data collected aboard Maurice Ewing from 1996-03-23 to 1996-03-25, Lyttelton, New Zealand to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for TN159: Multibeam data collected aboard Thomas G. Thompson from 2003-07-28 to 2003-08-20, Victoria, Canada to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for FK141015: Multibeam data collected aboard Falkor from 2014-10-15 to 2014-11-03, Pohnpei, Micronesia to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM0918: Multibeam data collected aboard Kilo Moana from 2009-07-23 to 2009-07-27, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for AMAT05RR: Multibeam data collected aboard Roger Revelle from 2006-05-26 to 2006-05-31, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KM0606: Multibeam data collected aboard Kilo Moana from 2006-02-18 to 2006-02-20, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KM0616: Multibeam data collected aboard Kilo Moana from 2006-06-07 to 2006-06-09, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KRY11_01: Multibeam data collected aboard Keary from 2011-04-13 to 2011-06-14, Waterford, Ireland to Waterford, Ireland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KRUS05RR: Multibeam data collected aboard Roger Revelle from 2004-09-14 to 2004-10-09, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for COOK22MV: Multibeam data collected aboard Melville from 2002-04-14 to 2002-04-27, Majuro, Marshall Islands to Osaka, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for MV1102: Multibeam data collected aboard Melville from 2011-02-20 to 2011-03-14, Cape Town, South Africa to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for RR1201: Multibeam data collected aboard Roger Revelle from 2012-01-10 to 2012-02-12, Phuket, Thailand to Durban, South Africa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for RR0903: Multibeam data collected aboard Roger Revelle from 2009-03-20 to 2009-05-13, Cape Town, South Africa to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KM0311: Multibeam data collected aboard Kilo Moana from 2003-06-22 to 2003-08-04, Seattle, WA to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for FK006B: Multibeam data collected aboard Falkor from 2012-11-06 to 2012-11-28, Pascagoula, MS to Pascagoula, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KN195-12: Multibeam data collected aboard Knorr from 2009-07-27 to 2009-08-09, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KM0631: Multibeam data collected aboard Kilo Moana from 2006-11-16 to 2006-11-20, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for BMRG01MV: Multibeam data collected aboard Melville from 1995-10-15 to 1995-11-23, San Diego, CA to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for BMRG04MV: Multibeam data collected aboard Melville from 1996-01-07 to 1996-01-11, Dunedin, New Zealand to Hobart, Tasmania

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for BMRG05MV: Multibeam data collected aboard Melville from 1996-01-16 to 1996-02-16, Hobart, Tasmania to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for FK005C: Multibeam data collected aboard Falkor from 2012-10-08 to 2012-10-20, Corpus Christi, TX to Corpus Christi, TX

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for TN080: Multibeam data collected aboard Thomas G. Thompson from 1998-07-14 to 1998-07-15, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM0415: Multibeam data collected aboard Kilo Moana from 2004-07-16 to 2004-08-24, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for HLY03DF: Multibeam data collected aboard Healy from 2003-01-31 to 2003-04-01, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for FK150324: Multibeam data collected aboard Falkor from 2015-03-24 to 2015-04-06, Broome, Australia to Broome, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for MGLN11MV: Multibeam data collected aboard Melville from 2006-11-15 to 2006-12-17, Honolulu, HI to Brisbane, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9911: Multibeam data collected aboard Maurice Ewing from 1999-10-10 to 1999-10-10, Lae, Papua New Guinea to Townsville, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KM0701: Multibeam data collected aboard Kilo Moana from 2007-01-03 to 2007-02-12, Honolulu, HI to Brisbane, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for WEST10MV: Multibeam data collected aboard Melville from 1995-01-29 to 1995-03-12, Fremantle, Australia to Hobart, Tasmania

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KRY14_04: Multibeam data collected aboard Keary from 2014-08-22 to 2014-09-07, Blacksod, Ireland to Blacksod, Ireland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for AT05L07: Multibeam data collected aboard Atlantis from 2001-09-03 to 2001-09-05, Bermuda to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for TN244: Multibeam data collected aboard Thomas G. Thompson from 2009-12-05 to 2009-12-08, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for lostcity2005: Multibeam data collected aboard Ronald H. Brown from 2005-07-17 to 2005-08-04, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for MV1209: Multibeam data collected aboard Melville from 2012-06-30 to 2012-07-10, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KM0518: Multibeam data collected aboard Kilo Moana from 2005-10-15 to 2005-11-05, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9003: Multibeam data collected aboard Maurice Ewing from 1990-06-25 to 1990-07-02, Port Everglades, FL to Newark, NJ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KM1520: Multibeam data collected aboard Kilo Moana from 2015-11-20 to 2015-12-20, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for M26-2: Multibeam data collected aboard Meteor from 1993-10-03 to 1993-10-21, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for AT07L32: Multibeam data collected aboard Atlantis from 2003-03-25 to 2003-04-14, Freeport, Bahamas to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for TN331: Multibeam data collected aboard Thomas G. Thompson from 2015-10-01 to 2015-10-15, Newport, OR to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KN165: Multibeam data collected aboard Knorr from 2001-11-06 to 2001-11-10, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for KM0620: Multibeam data collected aboard Kilo Moana from 2006-07-05 to 2006-07-10, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for B00255: Multibeam data collected aboard Mt. Mitchell from 1990-11-17 to 1990-11-20, Norfolk, VA to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM0716: Multibeam data collected aboard Kilo Moana from 2007-08-23 to 2007-08-30, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for VANC04MV: Multibeam data collected aboard Melville from 2002-11-02 to 2002-12-05, Arica, Chile to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for MV1218: Multibeam data collected aboard Melville from 2012-12-18 to 2013-01-14, San Diego, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for COOK23MV: Multibeam data collected aboard Melville from 2002-05-01 to 2002-06-06, Osaka, Japan to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW9908: Multibeam data collected aboard Maurice Ewing from 1999-07-21 to 1999-08-18, Kochi, Japan to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for RR1507: Multibeam data collected aboard Roger Revelle from 2015-04-21 to 2015-05-14, Auckland, New Zealand to Auckland, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KM0625: Multibeam data collected aboard Kilo Moana from 2006-08-15 to 2006-10-04, Honolulu, HI to Rabaul, Papua New Guinea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KM0626: Multibeam data collected aboard Kilo Moana from 2006-10-05 to 2006-10-15, Rabaul, Papua New Guinea to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for titanic2004: Multibeam data collected aboard Ronald H. Brown from 2004-05-27 to 2004-06-12, Boston, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EX1603: Multibeam data collected aboard Okeanos Explorer from 2016-02-23 to 2016-03-18, Pearl Harbor, HI to Kwajalein, Marshall Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KM0410: Multibeam data collected aboard Kilo Moana from 2004-04-06 to 2004-05-09, Suva, Fiji to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KM0305: Multibeam data collected aboard Kilo Moana from 2003-03-22 to 2003-03-24, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9417: Multibeam data collected aboard Maurice Ewing from 1994-11-27 to 1994-12-08, Balboa, Panama to Tampa, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NT05-10: Multibeam data collected aboard Natsushima from 2005-07-06 to 2005-07-13, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for NT05-12: Multibeam data collected aboard Natsushima from 2005-07-27 to 2005-07-31, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KN201: Multibeam data collected aboard Knorr from 2011-06-24 to 2011-07-17, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for RC2912: Multibeam data collected aboard Robert D. Conrad from 1988-12-02 to 1989-01-07, Cadiz, Spain to Azores

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for NT06-12: Multibeam data collected aboard Natsushima from 2006-06-24 to 2006-06-26, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for MGL1110: Multibeam data collected aboard Marcus G. Langseth from 2011-06-29 to 2011-08-05, Kodiak, AK to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for AT18-14: Multibeam data collected aboard Atlantis from 2011-11-25 to 2011-12-08, Piraievs, Greece to Piraievs, Greece

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for AT18-08: Multibeam data collected aboard Atlantis from 2011-07-19 to 2011-08-01, Astoria, OR to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for EW9901: Multibeam data collected aboard Maurice Ewing from 1999-01-30 to 1999-02-24, Norfolk, VA to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KN162L11: Multibeam data collected aboard Knorr from 2001-02-11 to 2001-03-15, Mombassa, Kenya to Seychelles

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for TN183: Multibeam data collected aboard Thomas G. Thompson from 2005-09-02 to 2005-10-04, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KN192-05: Multibeam data collected aboard Knorr from 2007-11-16 to 2007-12-13, Natal, Brazil to Walvis Bay, Namibia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for RC3003: Multibeam data collected aboard Robert D. Conrad from 1989-02-10 to 1989-03-12, Fortaleza, Brazil to Recife, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for PLUM04WT: Multibeam data collected aboard Thomas Washington from 1990-03-08 to 1990-04-11, Recife, Brazil to Montevideo, Uruguay

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for PLUM05WT: Multibeam data collected aboard Thomas Washington from 1990-04-18 to 1990-05-22, Montevideo, Uruguay to Recife, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KN161L06: Multibeam data collected aboard Knorr from 2000-04-07 to 2000-05-16, Recife, Brazil to Recife, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for RC2515: Multibeam data collected aboard Robert D. Conrad from 1984-12-26 to 1985-01-09, Belem, Brazil to Ascension Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KN161L07: Multibeam data collected aboard Knorr from 2000-05-21 to 2000-06-04, Recife, Brazil to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KN192-04: Multibeam data collected aboard Knorr from 2007-10-29 to 2007-11-11, St. John's, Canada to Natal, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9011: Multibeam data collected aboard Maurice Ewing from 1990-12-16 to 1991-01-25, Recife, Brazil to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for TN153: Multibeam data collected aboard Thomas G. Thompson from 2003-02-09 to 2003-03-05, Guam to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for MGL1212: Multibeam data collected aboard Marcus G. Langseth from 2012-07-12 to 2012-07-23, Astoria, OR to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for RR1212: Multibeam data collected aboard Roger Revelle from 2012-09-27 to 2012-10-01, Apia, Samoa to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for RR1505: Multibeam data collected aboard Roger Revelle from 2015-03-20 to 2015-03-22, Auckland, New Zealand to Auckland, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for MGL1214: Multibeam data collected aboard Marcus G. Langseth from 2012-07-31 to 2012-08-01, Astoria, OR to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for SKQ201603T: Multibeam data collected aboard Sikuliaq from 2016-03-22 to 2016-03-29, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for AT28: Multibeam data collected aboard Atlantis from 2015-06-04 to 2015-06-04, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for TN242: Multibeam data collected aboard Thomas G. Thompson from 2009-11-02 to 2009-11-06, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for RR1511: Multibeam data collected aboard Roger Revelle from 2015-08-04 to 2015-08-15, Colombo, Sri Lanka to Colombo, Sri Lanka

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for RR1407: Multibeam data collected aboard Roger Revelle from 2014-07-02 to 2014-07-13, Trincomalee, Sri Lanka to Trincomalee, Sri Lanka

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for RR1014: Multibeam data collected aboard Roger Revelle from 2010-10-12 to 2010-10-24, Naha, Japan to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for RR0904: Multibeam data collected aboard Roger Revelle from 2009-05-20 to 2009-06-23, Fremantle, Australia to Port Darwin, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KM1301: Multibeam data collected aboard Kilo Moana from 2013-01-10 to 2013-02-07, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for MV1405: Multibeam data collected aboard Melville from 2014-07-03 to 2014-07-26, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KN192-07: Multibeam data collected aboard Knorr from 2007-12-31 to 2008-01-17, Natal, Brazil to Ascension Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM1226: Multibeam data collected aboard Kilo Moana from 2012-11-19 to 2012-11-30, Pohnpei, Micronesia to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for KM0310: Multibeam data collected aboard Kilo Moana from 2003-05-22 to 2003-06-10, Kodiak, AK to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for RB0607: Multibeam data collected aboard Ronald H. Brown from 2006-10-02 to 2006-10-27, Charleston, SC to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for RB0709: Multibeam data collected aboard Ronald H. Brown from 2007-10-09 to 2007-11-07, Charleston, SC to Galapagos Islands, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for RB0505: Multibeam data collected aboard Ronald H. Brown from 2005-09-26 to 2005-10-21, Miami, FL to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9210: Multibeam data collected aboard Maurice Ewing from 1992-09-29 to 1992-11-09, Bridgetown, Barbados to St. George's, Bermuda

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for SKQ201502T: Multibeam data collected aboard Sikuliaq from 2015-02-12 to 2015-02-18, Ketchikan, AK to Juneau, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for RC2614: Multibeam data collected aboard Robert D. Conrad from 1985-12-01 to 1985-12-30, Hong Kong, China to Singapore

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for SO92: Multibeam data collected aboard Sonne from 1993-12-15 to 1993-12-27, Singapore, Singapore to Colombo, Sri Lanka

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KN145L12: Multibeam data collected aboard Knorr from 1995-11-01 to 1995-11-09, Singapore, Singapore to Dampier, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for MV0909: Multibeam data collected aboard Melville from 2009-05-20 to 2009-05-25, Brisbane, Australia to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM1128: Multibeam data collected aboard Kilo Moana from 2011-10-01 to 2011-10-25, Honolulu, HI to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for RC2506: Multibeam data collected aboard Robert D. Conrad from 1984-04-18 to 1984-05-19, Nice, France to Piraievs, Greece

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for ZHNG09RR: Multibeam data collected aboard Roger Revelle from 2005-07-21 to 2005-08-27, Yokohama, Japan to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KM0414: Multibeam data collected aboard Kilo Moana from 2004-06-20 to 2004-07-10, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KM0401: Multibeam data collected aboard Kilo Moana from 2004-01-07 to 2004-01-14, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for COOK02MV: Multibeam data collected aboard Melville from 2000-10-02 to 2000-10-14, Arica, Chile to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for COOK14MV: Multibeam data collected aboard Melville from 2001-10-06 to 2001-10-29, Suva, Fiji to Apia, Western Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for COOK19MV: Multibeam data collected aboard Melville from 2002-01-25 to 2002-02-26, Lyttelton, New Zealand to Lyttelton, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for COOK24MV: Multibeam data collected aboard Melville from 2002-06-09 to 2002-06-16, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for COOK01MV: Multibeam data collected aboard Melville from 2000-08-21 to 2000-09-27, San Diego, CA to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for COOK07MV: Multibeam data collected aboard Melville from 2001-03-04 to 2001-04-12, Apra, Guam to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for COOK11MV: Multibeam data collected aboard Melville from 2001-08-08 to 2001-08-17, Naha, Japan to Lae, Papua New Guinea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for COOK09MV: Multibeam data collected aboard Melville from 2001-06-21 to 2001-07-05, Pusan, South Korea to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for PLUM08WT: Multibeam data collected aboard Thomas Washington from 1990-06-29 to 1990-07-09, La Guaira, Venezuela to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for CRUISE10: Multibeam data collected aboard Nikolaj Strakhov from 1990-03-29 to 1990-06-01, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for CRUISE5: Multibeam data collected aboard Nikolaj Strakhov from 1987-05-18 to 1987-07-05, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for RC2909: Multibeam data collected aboard Robert D. Conrad from 1988-09-15 to 1988-10-14, Cape Verde to Ponta Delgada, Azores

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KN159L7: Multibeam data collected aboard Knorr from 1998-11-17 to 1998-12-16, Recife, Brazil to Cape Verde

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for AT26-12: Multibeam data collected aboard Atlantis from 2014-03-14 to 2014-03-26, New Orleans, LA to Gulfport, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for AT26-19: Multibeam data collected aboard Atlantis from 2014-08-28 to 2014-09-11, Astoria, OR to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM0417: Multibeam data collected aboard Kilo Moana from 2004-09-09 to 2004-10-17, Suva, Fiji to Suva, Fiji

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM0718: Multibeam data collected aboard Kilo Moana from 2007-09-10 to 2007-10-08, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for MV0904: Multibeam data collected aboard Melville from 2009-03-23 to 2009-03-28, Manila, Philippines to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for EW9302: Multibeam data collected aboard Maurice Ewing from 1993-05-27 to 1993-06-21, Woods Hole, MA to Reykjavik, Iceland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9403: Multibeam data collected aboard Maurice Ewing from 1994-03-21 to 1994-03-27, Cayenne, French Guiana to Martinique

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AT07L01: Multibeam data collected aboard Atlantis from 2001-09-22 to 2001-09-30, New York, NY to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KN162L13: Multibeam data collected aboard Knorr from 2001-03-30 to 2001-05-01, Mauritius to Mauritius

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for MV1011: Multibeam data collected aboard Melville from 2010-09-08 to 2010-09-19, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for HLY06TI: Multibeam data collected aboard Healy from 2006-08-30 to 2006-09-03, Kodiak, AK to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for HLY07TI: Multibeam data collected aboard Healy from 2007-09-26 to 2007-09-30, Juneau, AK to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for B00086: Multibeam data collected aboard Surveyor from 1986-10-25 to 1986-11-03, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for AT25: Multibeam data collected aboard Atlantis from 2013-05-03 to 2013-05-06, Woods Hole, MA to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for DANA07RR: Multibeam data collected aboard Roger Revelle from 2004-03-11 to 2004-04-01, Mazatlan, Mexico to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for HLY12TC: Multibeam data collected aboard Healy from 2012-09-24 to 2012-09-27, Barrow, AK to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KM1405: Multibeam data collected aboard Kilo Moana from 2014-01-30 to 2014-01-31, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for MV1304: Multibeam data collected aboard Melville from 2013-02-25 to 2013-03-17, Yokohama, Japan to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for EX0901: Multibeam data collected aboard Okeanos Explorer from 2009-03-29 to 2009-04-03, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for EX0801: Multibeam data collected aboard Okeanos Explorer from 2008-09-08 to 2008-09-22, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for MV1005: Multibeam data collected aboard Melville from 2010-03-25 to 2010-04-03, Valparaiso, Chile to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for B00076: Multibeam data collected aboard Discoverer from 1986-10-03 to 1986-10-13, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM1109: Multibeam data collected aboard Kilo Moana from 2011-03-04 to 2011-03-10, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for Tecfluc: Multibeam data collected aboard Ocean Alert from 1998-05-23 to 1998-05-26, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM1316: Multibeam data collected aboard Kilo Moana from 2013-09-16 to 2013-09-28, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KNOX05RR: Multibeam data collected aboard Roger Revelle from 2007-05-07 to 2007-06-14, Phuket, Thailand to Phuket, Thailand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for MGL1208: Multibeam data collected aboard Marcus G. Langseth from 2012-04-30 to 2012-05-26, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AT1L2: Multibeam data collected aboard Atlantis from 1997-03-29 to 1997-04-06, Fort Lauderdale, FL to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KM0317: Multibeam data collected aboard Kilo Moana from 2003-10-19 to 2003-10-23, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for GEOMETEP: Multibeam data collected aboard Sonne from 1985-12-17 to 1986-01-07, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for RR1116: Multibeam data collected aboard Roger Revelle from 2011-11-06 to 2011-12-11, Phuket, Thailand to Phuket, Thailand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KRUS03RR: Multibeam data collected aboard Roger Revelle from 2004-07-10 to 2004-08-16, Dutch Harbor, AK to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for KM0818: Multibeam data collected aboard Kilo Moana from 2008-09-08 to 2008-09-22, Port Hueneme, CA to Port Hueneme, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for SUM0108A: Multibeam data collected aboard Sumner from 2001-06-17 to 2001-06-22, Unknown Port to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for MGL1218: Multibeam data collected aboard Marcus G. Langseth from 2012-11-25 to 2012-11-25, Astoria, OR to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for B00289: Multibeam data collected aboard Surveyor from 1991-07-24 to 1991-08-03, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9701B: Multibeam data collected aboard Maurice Ewing from 1997-04-18 to 1997-04-29, Newark, NJ to Savannah, GA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EW9703: Multibeam data collected aboard Maurice Ewing from 1997-05-19 to 1997-05-25, Port Canaveral, FL to Jacksonville, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for EW9702: Multibeam data collected aboard Maurice Ewing from 1997-05-03 to 1997-05-16, Savannah, GA to Port Canaveral, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KN195-13: Multibeam data collected aboard Knorr from 2009-08-14 to 2009-09-10, Honolulu, HI to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KN195L03: Multibeam data collected aboard Knorr from 2009-01-12 to 2009-02-23, Puntarenas, Costa Rica to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EX1505: Multibeam data collected aboard Okeanos Explorer from 2015-10-05 to 2015-10-16, Honolulu, HI to Alameda, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for TUNE04WT: Multibeam data collected aboard Thomas Washington from 1991-10-05 to 1991-10-16, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM1106: Multibeam data collected aboard Kilo Moana from 2011-02-19 to 2011-02-23, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM1113: Multibeam data collected aboard Kilo Moana from 2011-04-10 to 2011-04-14, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KM0824: Multibeam data collected aboard Kilo Moana from 2008-12-15 to 2008-12-16, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9507: Multibeam data collected aboard Maurice Ewing from 1995-07-28 to 1995-08-02, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for TN264: Multibeam data collected aboard Thomas G. Thompson from 2011-05-21 to 2011-05-24, Honolulu, HI to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EX1504L1: Multibeam data collected aboard Okeanos Explorer from 2015-07-10 to 2015-07-24, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for MGL1002: Multibeam data collected aboard Marcus G. Langseth from 2010-05-07 to 2010-05-19, Astoria, OR to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KIWI02RR: Multibeam data collected aboard Roger Revelle from 1997-08-11 to 1997-08-21, San Francisco, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM0319: Multibeam data collected aboard Kilo Moana from 2003-10-26 to 2003-10-31, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for MV1002: Multibeam data collected aboard Melville from 2010-02-18 to 2010-02-22, Valparaiso, Chile to Puerto Montt, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for LWAD99MV: Multibeam data collected aboard Melville from 1999-09-05 to 1999-09-20, San Diego, CA to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for Marianas: Multibeam data collected aboard Onnuri from 2003-09-18 to 2003-09-23, Guam to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for CNTL10RR: Multibeam data collected aboard Roger Revelle from 2003-06-10 to 2003-06-15, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for CNTL08RR: Multibeam data collected aboard Roger Revelle from 2003-05-19 to 2003-05-22, San Diego, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for CNTL12RR: Multibeam data collected aboard Roger Revelle from 2003-06-24 to 2003-07-09, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for CNTL09RR: Multibeam data collected aboard Roger Revelle from 2003-05-29 to 2003-06-08, San Diego, CA to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for CNTL15RR: Multibeam data collected aboard Roger Revelle from 2003-09-04 to 2003-09-22, Newport, OR to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for CNTL14RR: Multibeam data collected aboard Roger Revelle from 2003-08-25 to 2003-09-02, Honolulu, HI to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for CNTL13RR: Multibeam data collected aboard Roger Revelle from 2003-07-14 to 2003-08-22, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM1312: Multibeam data collected aboard Kilo Moana from 2013-07-02 to 2013-07-28, Honolulu, HI to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for TUIM13MV: Multibeam data collected aboard Melville from 2005-08-19 to 2005-08-30, San Diego, CA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for TN296: Multibeam data collected aboard Thomas G. Thompson from 2013-04-22 to 2013-04-26, Seattle, WA to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for TN281: Multibeam data collected aboard Thomas G. Thompson from 2012-05-24 to 2012-05-26, Seattle, WA to Esquimalt Harbor, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KM1304: Multibeam data collected aboard Kilo Moana from 2013-03-01 to 2013-03-03, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MV1112: Multibeam data collected aboard Melville from 2011-11-03 to 2011-11-26, Port Elizabeth, South Africa to Durban, South Africa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MV1004: Multibeam data collected aboard Melville from 2010-03-17 to 2010-03-25, Valparaiso, Chile to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for MV1103: Multibeam data collected aboard Melville from 2011-03-15 to 2011-03-20, Valparaiso, Chile to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for AT26-17: Multibeam data collected aboard Atlantis from 2014-07-14 to 2014-08-06, Astoria, OR to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM0816: Multibeam data collected aboard Kilo Moana from 2008-08-21 to 2008-08-23, Honolulu, HI to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for RR1002: Multibeam data collected aboard Roger Revelle from 2010-01-26 to 2010-02-18, Wellington, New Zealand to Wellington, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for CE16007: Multibeam data collected aboard Celtic Explorer from 2016-04-08 to 2016-04-22, Galway, Ireland to St. John's, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Coverage includes a swath of multibeam data with focus on a previously unidentified seabed feature in the Mid-Atlantic Ridge. The survey was conducted between 08/04...

  19. Multibeam collection for KNOX09RR: Multibeam data collected aboard Roger Revelle from 2007-09-20 to 2007-10-18, Mormugao, India to Mormugao, India

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for RR1514: Multibeam data collected aboard Roger Revelle from 2015-09-22 to 2015-10-07, Chennai, India to Palau, Palau

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...