WorldWideScience

Sample records for ocean radar lidar

  1. Radar and Lidar Radar DEM

    Science.gov (United States)

    Liskovich, Diana; Simard, Marc

    2011-01-01

    Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

  2. A Concept for Differential Absorption Lidar and Radar Remote Sensing of the Earth's Atmosphere and Ocean from NRHO Orbit

    Science.gov (United States)

    Hu, Y.; Marshak, A.; Omar, A.; Lin, B.; Baize, R.

    2018-02-01

    We propose a concept that will put microwave and laser transmitters on the Deep Space Gateway platform for measurements of the Earth's atmosphere and ocean. Receivers will be placed on the ground, buoys, Argo floats, and cube satellites.

  3. Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

    Science.gov (United States)

    Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

    2015-01-01

    To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

  4. Forest Biomass Mapping From Lidar and Radar Synergies

    Science.gov (United States)

    Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

    2011-01-01

    The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the

  5. Combining Lidar and Synthetic Aperture Radar Data to Estimate Forest Biomass: Status and Prospects

    Directory of Open Access Journals (Sweden)

    Sanna Kaasalainen

    2015-01-01

    Full Text Available Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the aboveground biomass (AGB, which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.

  6. Multi-wavelength Ocean Profiling and Atmospheric Lidar

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to build and demonstrate the world's first multi-wavelength ocean-profiling high spectral resolution lidar (HSRL). The lidar will provide profiles of...

  7. Amplification of radar and lidar signatures using quantum sensors

    Science.gov (United States)

    Lanzagorta, Marco

    2013-05-01

    One of the major scientific thrusts from recent years has been to try to harness quantum phenomena to dramat­ ically increase the performance of a wide variety of classical devices. These advances in quantum information science have had a considerable impact on the development of photonic-based quantum sensors. Even though quantum radar and quantum lidar remain theoretical proposals, preliminary results suggest that these sensors have the potential of becoming disruptive technologies able to revolutionize reconnaissance systems. In this paper we will discuss how quantum entanglement can be exploited to increase the radar and lidar signature of rectangular targets. In particular, we will show how the effective visibility of the target is increased if observed with an entangled multi-photon quantum sensor.

  8. MST radar and polarization lidar observations of tropical cirrus

    Directory of Open Access Journals (Sweden)

    Y. Bhavani Kumar

    2001-08-01

    Full Text Available Significant gaps in our understanding of global cirrus effects on the climate system involve the role of frequently occurring tropical cirrus. Much of the cirrus in the atmosphere is largely due to frequent cumulus and convective activity in the tropics. In the Indian sub-tropical region, the deep convective activity is very prominent from April to December, which is a favorable period for the formation of deep cumulus clouds. The fibrous anvils of these clouds, laden with ice crystals, are one of the source mechanisms for much of the cirrus in the atmosphere. In the present study, several passages of tropical cirrus were investigated by simultaneously operating MST radar and a co-located polarization lidar at the National MST Radar Facility (NMRF, Gadanki (13.45° N, 79.18° E, India to understand its structure, the background wind field and the microphysics at the cloud boundaries. The lidar system used is capable of measuring the degree of depolarization in the laser backscatter. It has identified several different cirrus structures with a peak linear depolarization ratio (LDR in the range of 0.1 to 0.32. Simultaneous observations of tropical cirrus by the VHF Doppler radar indicated a clear enhancement of reflectivity detected in the vicinity of the cloud boundaries, as revealed by the lidar and are strongly dependent on observed cloud LDR. An inter-comparison of radar reflectivity observed for vertical and oblique beams reveals that the radar-enhanced reflectivity at the cloud boundaries is also accompanied by significant aspect sensitivity. These observations indicate the presence of anisotropic turbulence at the cloud boundaries. Radar velocity measurements show that boundaries of cirrus are associated with enhanced horizontal winds, significant vertical shear in the horizontal winds and reduced vertical velocity. Therefore, these measurements indicate that a circulation at the cloud boundaries suggest an entrainment taking place close to

  9. MST radar and polarization lidar observations of tropical cirrus

    Directory of Open Access Journals (Sweden)

    Y. Bhavani Kumar

    Full Text Available Significant gaps in our understanding of global cirrus effects on the climate system involve the role of frequently occurring tropical cirrus. Much of the cirrus in the atmosphere is largely due to frequent cumulus and convective activity in the tropics. In the Indian sub-tropical region, the deep convective activity is very prominent from April to December, which is a favorable period for the formation of deep cumulus clouds. The fibrous anvils of these clouds, laden with ice crystals, are one of the source mechanisms for much of the cirrus in the atmosphere. In the present study, several passages of tropical cirrus were investigated by simultaneously operating MST radar and a co-located polarization lidar at the National MST Radar Facility (NMRF, Gadanki (13.45° N, 79.18° E, India to understand its structure, the background wind field and the microphysics at the cloud boundaries. The lidar system used is capable of measuring the degree of depolarization in the laser backscatter. It has identified several different cirrus structures with a peak linear depolarization ratio (LDR in the range of 0.1 to 0.32. Simultaneous observations of tropical cirrus by the VHF Doppler radar indicated a clear enhancement of reflectivity detected in the vicinity of the cloud boundaries, as revealed by the lidar and are strongly dependent on observed cloud LDR. An inter-comparison of radar reflectivity observed for vertical and oblique beams reveals that the radar-enhanced reflectivity at the cloud boundaries is also accompanied by significant aspect sensitivity. These observations indicate the presence of anisotropic turbulence at the cloud boundaries. Radar velocity measurements show that boundaries of cirrus are associated with enhanced horizontal winds, significant vertical shear in the horizontal winds and reduced vertical velocity. Therefore, these measurements indicate that a circulation at the cloud boundaries suggest an entrainment taking place close to

  10. Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

    Science.gov (United States)

    Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

    2017-08-01

    Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

  11. 2013 Suwannee River Water Management District Lidar: Ocean Pond (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 3, Classified Point Cloud, in north-central...

  12. The lidar dark band: An oddity of the radar bright band analogy

    Energy Technology Data Exchange (ETDEWEB)

    Sassen, K. [Univ. of Utah, Salt Lake City, UT (United States)

    1996-04-01

    Although much has sbeen learned from independent radar and lidar studies of atmospheric precipitations, occasionally supported by aircraft profiling, what has been lacking is combined optical, microwave, and insitu observations of the melting layer. Fortunately, the rainshowers on April 21, 1994, during the Remote Cloud Sensing intensive obervations Period (RCSIOP) at the Southern Great Plains Cloud and radiation Testbed (CART) site provided an opportunity for coordinated dual-wavelength University of Utah Polarization Diversity Lidar, University of Massachusetts Cloud Profiling Radar System Doppler Radar, and the University of North Dakota Citation aircraft measurements.

  13. Ocean subsurface particulate backscatter estimation from CALIPSO spaceborne lidar measurements

    Science.gov (United States)

    Chen, Peng; Pan, Delu; Wang, Tianyu; Mao, Zhihua

    2017-10-01

    A method for ocean subsurface particulate backscatter estimation from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite was demonstrated. The effects of the CALIOP receiver's transient response on the attenuated backscatter profile were first removed. The two-way transmittance of the overlying atmosphere was then estimated as the ratio of the measured ocean surface attenuated backscatter to the theoretical value computed from wind driven wave slope variance. Finally, particulate backscatter was estimated from the depolarization ratio as the ratio of the column-integrated cross-polarized and co-polarized channels. Statistical results show that the derived particulate backscatter by the method based on CALIOP data agree reasonably well with chlorophyll-a concentration using MODIS data. It indicates a potential use of space-borne lidar to estimate global primary productivity and particulate carbon stock.

  14. Airborne ocean water lidar (OWL) real time processor (RTP)

    Science.gov (United States)

    Hryszko, M.

    1995-03-01

    The Hyperflo Real Time Processor (RTP) was developed by Pacific-Sierra Research Corporation as a part of the Naval Air Warfare Center's Ocean Water Lidar (OWL) system. The RTP was used for real time support of open ocean field tests at Barbers Point, Hawaii, in March 1993 (EMERALD I field test), and Jacksonville, Florida, in July 1994 (EMERALD I field test). This report describes the system configuration, and accomplishments associated with the preparation and execution of these exercises. This document is intended to supplement the overall test reports and provide insight into the development and use of the PTP. A secondary objective is to provide basic information on the capabilities, versatility and expandability of the Hyperflo RTP for possible future projects. It is assumed herein that the reader has knowledge of the OWL system, field test operations, general lidar processing methods, and basic computer architecture.

  15. Combined Lidar-Radar Remote Sensing: Initial Results from CRYSTAL-FACE and Implications for Future Spaceflight Missions

    Science.gov (United States)

    McGill, Matthew J.; Li, Li-Hua; Hart, William D.; Heymsfield, Gerald M.; Hlavka, Dennis L.; Vaughan, Mark A.; Winker, David M.

    2003-01-01

    In the near future NASA plans to fly satellites carrying a multi-wavelength backscatter lidar and a 94-GHz cloud profiling radar in formation to provide complete global profiling of cloud and aerosol properties. The CRYSTAL-FACE field campaign, conducted during July 2002, provided the first high-altitude colocated measurements from lidar and cloud profiling radar to simulate these spaceborne sensors. The lidar and radar provide complementary measurements with varying degrees of measurement overlap. This paper presents initial results of the combined airborne lidar-radar measurements during CRYSTAL-FACE. The overlap of instrument sensitivity is presented, within the context of particular CRYSTAL-FACE conditions. Results are presented to quantify the portion of atmospheric profiles sensed independently by each instrument and the portion sensed simultaneously by the two instruments.

  16. Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

    Science.gov (United States)

    Hlavka, Dennis; Tian, Lin; Hart, William; Li, Lihua; McGill, Matthew; Heymsfield, Gerald

    2009-01-01

    Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy

  17. Basic study for tsunami detection with DBF ocean radar

    International Nuclear Information System (INIS)

    Sakai, Shin'ichi; Matsuyama, Masafumi; Okuda, Kouzou; Uehara, Fumihiro

    2015-01-01

    To develop early tsunami warning system utilizing ocean radars, the evaluation of the variety of measuring coverage and data accuracy is indispensable in real oceans. The field observation was carried out at 5 minutes interval with two digital beam forming ocean radars with VHF band from 2012 to 2014 in the sea of Enshu. The high data acquisition areas are found in the extent of 17 km off the coast on a hill site and of 13 km on a low ground site. The measured current by the ocean radar were well correlated with that by the current-meter in the depth of 2 m near the coast with the correlation coefficient of ∼0.6. It is inferred that the main factor of difference in both data sets was due to the presence of wind-driven current through the multi-regression analysis with both current data and wind data. In addition, the order of the temporal current deviations as to the representative time-scale of one hour is about 5 cm/s under the ordinary sea conditions, which suggest that ocean radars could sufficiently detect the current deviation due to grant tsunami. (author)

  18. A study on the use of radar and lidar for characterizing ultragiant aerosol

    Science.gov (United States)

    Madonna, F.; Amodeo, A.; D'Amico, G.; Pappalardo, G.

    2013-09-01

    19 April to 19 May 2010, volcanic aerosol layers originating from the Eyjafjallajökull volcano were observed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy Atmospheric Observatory, named CIAO (40.60°N, 15.72°E, 760 m above sea level), in Southern Italy with a multiwavelength Raman lidar. During this period, ultragiant aerosols were also observed at CIAO using a colocated 8.45 mm wavelength Doppler radar. The Ka-band radar signatures observed in four separate days (19 April and 7, 10, and 13 May) are consistent with the observation of nonspherical ultragiant aerosols characterized by values of linear depolarization ratio (LDR) higher than -4 dB. Air mass back trajectory analysis suggests a volcanic origin of the ultragiant aerosols observed by the radar. The observed values of the radar reflectivity (Ze) are consistent with a particle effective radius (r) larger than 50-75 µm. Scattering simulations based on the T-matrix approach show that the high LDR values can be explained if the observed particles have an absolute aspect ratio larger than 3.0 and consist of an internal aerosol core and external ice shell, with a variable radius ratio ranging between 0.2 and 0.7 depending on the shape and aspect ratio. Comparisons between daytime vertical profiles of aerosol backscatter coefficient (β) as measured by lidar and radar LDR reveal a decrease of β where ultragiant particles are observed. Scattering simulations based on Mie theory show how the lidar capability in typing ultragiant aerosols could be limited by low number concentrations or by the presence of an external ice shell covering the aerosol particles. Preferential vertical alignment of the particles is discussed as another possible reason for the decrease of β.

  19. Oceanic eddies in synthetic aperture radar images

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    2000) can be carried out in two different ways. The first one is ..... mushroom-like currents forming composite multi- .... eddies. Combination of SAR, IR and color data will ... Fu L-L and Holt B 1982 Seasat views oceans and sea ice with.

  20. Helicopter-based lidar system for monitoring the upper ocean and terrain surface

    International Nuclear Information System (INIS)

    Lee, Kwi Joo; Park, Youngsik; Bunkin, Alexey; Pershin, Serguei; Voliak, Konstantin; Nunes, Raul

    2002-01-01

    A compact helicopter-based lidar system is developed and tested under laboratory and field conditions. It is shown that the lidar can measure concentrations of chlorophyll a and dissolved organic matter at the surface of water bodies, detect fluorescence spectra of ground vegetation at a distance of up to 530 m, and determine the vertical profile of light-scattering particle concentration in the upper ocean. The possibilities of the lidar system are demonstrated by detection of polluted areas at the ocean surface, by online monitoring of three-dimensional distribution of light-scattering layers, and by recognition of plant types and physiological states

  1. Advancing Atmosphere-Ocean Remote Sensing with Spaceborne High Spectral Resolution Lidar

    Science.gov (United States)

    Hostetler, C. A.; Behrenfeld, M. J.; Chepfer, H.; Hu, Y.; Hair, J. W.; Trepte, C. R.; Winker, D. M.; Ferrare, R. A.; Burton, S. P.; Scarino, A. J.; Powell, K. A.; Michaud, J.

    2016-12-01

    More than 1600 publications employing observations from the CALIOP lidar on CALIPSO testify to the value of spaceborne lidar for aerosol and cloud remote sensing. Recent publications have shown the value of CALIOP data for retrievals of key ocean carbon cycle stocks. In this presentation we focus on the advantages of a more advanced technique, High Spectral Resolution Lidar (HSRL), for aerosol, cloud, and ocean remote sensing. An atmosphere-ocean optimized HSRL achieves greater accuracy over the standard backscatter lidar technique for retrievals of aerosol and cloud extinction and backscatter profiles, provides additional capability to retrieve aerosol and cloud microphysical parameters, and enables vertically-resolved characterization of scattering and absorption properties of suspended and dissolved materials in the ocean. Numerous publications highlight the synergy of coincident CALIOP and passive A-train observations for studies of aerosol-cloud radiative effects and cloud-climate feedback. Less appreciated is the complementarity that would exist between an optimized spaceborne lidar and passive ocean color. An optimized HSRL flown in formation with the Plankton, Aerosol, and ocean Ecosystem (PACE) mission would provide phytoplankton vertical distribution, which is needed for accurately estimating net primary productivity but absent in the PACE ocean color data. The HSRL would also provide data needed to improve atmospheric correction schemes in ocean color retrievals. Because lidar provides measurements both night and day, through tenuous clouds and aerosol layers, and in holes between clouds, the sampling achieved is highly complementary to passive radiometry, providing data in important high latitude regions where ocean color data are sparse or nonexistent. In this presentation we will discuss 1) relevant aerosol, cloud, and ocean retrievals from airborne HSRL field missions; 2) the advantages of an optimized spaceborne HSRL for aerosol, cloud, and ocean

  2. Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions

    Directory of Open Access Journals (Sweden)

    R. H. Rasshofer

    2005-01-01

    Full Text Available Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001. Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt. Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001. Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.

  3. Characteristics of Volcanic Stratospheric Aerosol Layer Observed by CALIOP and Ground Based Lidar at Equatorial Atmosphere Radar Site

    Science.gov (United States)

    Abo, Makoto; Shibata, Yasukuni; Nagasawa, Chikao

    2018-04-01

    We investigated the relation between major tropical volcanic eruptions in the equatorial region and the stratospheric aerosol data, which have been collected by the ground based lidar observations at at Equatorial Atmosphere Radar site between 2004 and 2015 and the CALIOP observations in low latitude between 2006 and 2015. We found characteristic dynamic behavior of volcanic stratospheric aerosol layers over equatorial region.

  4. Quality assessment of water cycle parameters in REMO by radar-lidar synergy

    Directory of Open Access Journals (Sweden)

    B. Hennemuth

    2008-01-01

    Full Text Available A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study

  5. The physical basis for estimating wave-energy spectra with the radar ocean-wave spectrometer

    Science.gov (United States)

    Jackson, Frederick C.

    1987-01-01

    The derivation of the reflectivity modulation spectrum of the sea surface for near-nadir-viewing microwave radars using geometrical optics is described. The equations required for the derivation are presented. The derived reflectivity modulation spectrum provides data on the physical basis of the radar ocean-wave spectrometer measurements of ocean-wave directional spectra.

  6. ATLID: atmospheric lidar for clouds and aerosol observation combined with radar sounding

    Science.gov (United States)

    Pain, Th.; Martimort, Ph.; Tanguy, Ph.; Leibrandt, W.; Heliere, A.

    2017-11-01

    The atmospheric lidar ATLID is part of the payload of the joint collaborative satellite mission Earth Cloud and Aerosol Explorer (EarthCARE) conducted by the European Space Agency (ESA) and the National Space Development Agency of Japan (JAXA). In December 2002, ESA granted Alcatel Space with a phase A study of the EarthCARE mission in which Alcatel Space is also in charge to define ATLID. The primary objective of ATLID at the horizon 2011 is to provide global observation of clouds in synergy with a cloud profiling radar (CPR) mounted on the same platform. The planned spaceborne mission also embarks an imager and a radiometer and shall fly for 3 years. The lidar design is based on a novel concept that maximises the scientific return and fosters a cost-effective approach. This improved capability results from a better understanding of the way optical characteristics of aerosol and clouds affect the performance budget. For that purpose, an end to end performance model has been developed utilising a versatile data retrieval method suitable for new and more conventional approaches. A synthesis of the achievable performance will be presented to illustrate the potential of the system together with a description of the design.

  7. Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion

    Science.gov (United States)

    Kwon, Seong Kyung; Hyun, Eugin; Lee, Jin-Hee; Lee, Jonghun; Son, Sang Hyuk

    2017-11-01

    Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

  8. An Innovative Concept for Spacebased Lidar Measurement of Ocean Carbon Biomass

    Science.gov (United States)

    Hu, Yongxiang; Behrenfeld, Michael; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei; hide

    2015-01-01

    Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor). On July 17, 2014, the CALIPSO satellite was tilted 30Âdeg off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraft-based high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

  9. Combined High Spectral Resolution Lidar and Millimeter Wavelength Radar Measurement of Ice Crystal Precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Eloranta, Edwin [Univ. of Wisconsin, Madison, WI (United States)

    2016-10-28

    The goal of this research has been to improve measurements of snowfall using a combination of millimeter-wavelength radar and High Spectral Resolution Lidar (HSRL) Observations. Snowflakes are large compared to the 532nm HSRL wavelength and small compared to the 3.2 and 8.6 mm wavelength radars used in this study. This places the particles in the optical scattering regime of the HSRL, where extinction cross-section is proportional to the projected area of the particles, and in the Rayleigh regime for the radar, where the backscatter cross-section is proportional to the mass-squared of the particles. Forming a ratio of the radar measured cross-section to the HSRL measured cross section eliminates any dependence on the number of scattering particles, yielding a quantity proportional to the average mass-squared of the snowflakes over the average area of the flakes. Using simultaneous radar measurements of particle fall velocities, which are dependent particle mass and cross-sectional area it is possible to derive the average mass of the snow flakes, and with the radar measured fall velocities compute the snowfall rate. Since this retrieval requires the optical extinction cross-section we began by considering errors this quantity. The HSRL is particularly good at measuring the backscatter cross-section. In previous studies of snowfall in the high Arctic were able to estimate the extinction cross-section directly as a fixed ratio to the backscatter cross-section. Measurements acquired in the STORMVEX experiment in Colorado showed that this approach was not valid in mid-latitude snowfalls and that direct measurement of the extinction cross-section is required. Attempts to measure the extinction directly uncovered shortcomings in thermal regulation and mechanical stability of the newly deployed DOE HSRL systems. These problems were largely mitigated by modifications installed in both of the DOE systems. We also investigated other sources of error in the HSRL direct

  10. Simulation of simultaneously obtaining ocean temperature and salinity using dual-wavelength Brillouin lidar

    International Nuclear Information System (INIS)

    Yu, Yin; Ma, Yong; Li, Hao; Huang, Jun; Fang, Yu; Liang, Kun; Zhou, Bo

    2014-01-01

    A method for simultaneously obtaining the ocean temperature and salinity based on dual-wavelength Brillouin lidar is proposed in this letter. On the basis of the relationships between the temperature and salinity and the Brillouin shifts, a retrieval model for retrieving the temperature and salinity is established. By using the retrieval model, the ocean temperature and salinity can be simultaneously obtained through the Brillouin shifts. Simulation based on dual-wavelength Brillouin lidar is also carried out for verification of the accuracy of the retrieval model. Results show that the errors of the retrieval model for temperature and salinity are ±0.27 °C and ±0.33‰. (letter)

  11. A joint study of the lower ionosphere by radar, lidar, and spectrometer

    International Nuclear Information System (INIS)

    Zhou, Qihou.

    1991-01-01

    The dynamics and associated phenomena occurring in the lower ionospheric-E region, especially the mesopause region between 80 km to 110 km at low latitude, are studied. In particular, incoherent scatter radar (ISR), sodium lidar and airglow spectrometry are used to study the ionospheric structure and neutral sodium structure. The simultaneous study of the ionospheric plasma and neutral atomic sodium is unprecedented in scope and detail. The joint study of the mesopause region reveals that plasma, neutral densities and temperature are interconnected through the same atmospheric dynamics. The theme of the thesis is to explain the formation of the controversial sporadic sodium layer (SSL) events. Strong correlation is established between the average total ion and sodium concentrations, and between sporadic-E and SSL events. The mechanism proposed in the thesis, which invokes temperature fluctuations induced by tides and gravity waves, finds good agreement with observations. Tides and gravity waves can converge ions into thin layers through the windshear mechanisms and can influence the concentration of atomic sodium through temperature fluctuations. Sodium abundance is shown to augment rapidly when the temperature is increased. Gravity wave theory states that the ion convergence node coincides with a temperature maximum for a westward propagating gravity wave, and coincides with a temperature minimum for an eastward propagating wave. Because tidal winds propagate westward, the ion layer coincides with the temperature maximum which consequently induces higher sodium concentration. This can account for the general correlation between sodium and total ion concentration and is supported by the O2(0-1) rotational temperature. Gravity waves and their interaction with tidal winds are believed to be responsible for the close association between sudden sodium layers and sporadic-E layers

  12. Combined Atmospheric and Ocean Profiling from an Airborne High Spectral Resolution Lidar

    Directory of Open Access Journals (Sweden)

    Hair Johnathan

    2016-01-01

    Full Text Available First of its kind combined atmospheric and ocean profile data were collected by the recently upgraded NASA Langley Research Center’s (LaRC High Spectral Resolution Lidar (HSRL-1 during the 17 July – 7 August 2014 Ship-Aircraft Bio-Optical Research Experiment (SABOR. This mission sampled over a region that covered the Gulf of Maine, open-ocean near Bermuda, and coastal waters from Virginia to Rhode Island. The HSRL-1 and the Research Scanning Polarimeter from NASA Goddard Institute for Space Studies collected data onboard the NASA LaRC King Air aircraft and flight operations were closely coordinated with the Research Vessel Endeavor that made in situ ocean optical measurements. The lidar measurements provided profiles of atmospheric backscatter and particulate depolarization at 532nm, 1064nm, and extinction (532nm from approximately 9km altitude. In addition, for the first time HSRL seawater backscatter, depolarization, and diffuse attenuation data at 532nm were collected and compared to both the ship measurements and the Moderate Resolution Imaging Spectrometer (NASA MODIS-Aqua satellite ocean retrievals.

  13. A preliminary comparison of Na lidar and meteor radar zonal winds during geomagnetic quiet and disturbed conditions

    Science.gov (United States)

    Kishore Kumar, G.; Nesse Tyssøy, H.; Williams, Bifford P.

    2018-03-01

    We investigate the possibility that sufficiently large electric fields and/or ionization during geomagnetic disturbed conditions may invalidate the assumptions applied in the retrieval of neutral horizontal winds from meteor and/or lidar measurements. As per our knowledge, the possible errors in the wind estimation have never been reported. In the present case study, we have been using co-located meteor radar and sodium resonance lidar zonal wind measurements over Andenes (69.27°N, 16.04°E) during intense substorms in the declining phase of the January 2005 solar proton event (21-22 January 2005). In total, 14 h of measurements are available for the comparison, which covers both quiet and disturbed conditions. For comparison, the lidar zonal wind measurements are averaged over the same time and altitude as the meteor radar wind measurements. High cross correlations (∼0.8) are found in all height regions. The discrepancies can be explained in light of differences in the observational volumes of the two instruments. Further, we extended the comparison to address the electric field and/or ionization impact on the neutral wind estimation. For the periods of low ionization, the neutral winds estimated with both instruments are quite consistent with each other. During periods of elevated ionization, comparatively large differences are noticed at the highermost altitude, which might be due to the electric field and/or ionization impact on the wind estimation. At present, one event is not sufficient to make any firm conclusion. Further study with more co-located measurements are needed to test the statistical significance of the result.

  14. The Comparison of Canopy Height Profiles Extracted from Ku-band Profile Radar Waveforms and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Hui Zhou

    2018-05-01

    Full Text Available An airborne Ku-band frequency-modulated continuous waveform (FM-CW profiling radar, Tomoradar, records the backscatter signal from the canopy surface and the underlying ground in the southern boreal forest zone of Finland. The recorded waveforms are transformed into canopy height profiles (CHP with a similar methodology utilized in large-footprint light detection and ranging (LiDAR. The point cloud data simultaneously collected by a Velodyne® VLP-16 LiDAR on-board the same platform represent the frequency of discrete returns, which are also applied to the extraction of the CHP by calculating the gap probability and incremental distribution. To thoroughly explore the relationships of the CHP derived from Tomoradar waveforms and LiDAR data we utilized the effective waveforms of one-stripe field measurements and comparison them with four indicators, including the correlation coefficient, the root-mean-square error (RMSE of the difference, and the coefficient of determination and the RMSE of residuals of linear regression. By setting the Tomoradar footprint as 20 degrees to contain over 95% of the transmitting energy of the main lobe, the results show that 88.17% of the CHPs derived from Tomoradar waveforms correlated well with those from the LiDAR data; 98% of the RMSEs of the difference ranged between 0.002 and 0.01; 79.89% of the coefficients of determination were larger than 0.5; and 98.89% of the RMSEs of the residuals ranged from 0.001 to 0.01. Based on the investigations, we discovered that the locations of the greatest CHP derived from the Tomoradar were obviously deeper than those from the LiDAR, which indicated that the Tomoradar microwave signal had a stronger penetration capability than the LiDAR signal. Meanwhile, there are smaller differences (the average RMSEs of differences is only 0.0042 when the total canopy closure is less than 0.5 and better linear regression results in an area with a relatively open canopy than with a denser

  15. New Techniques for Radar Altimetry of Sea Ice and the Polar Oceans

    Science.gov (United States)

    Armitage, T. W. K.; Kwok, R.; Egido, A.; Smith, W. H. F.; Cullen, R.

    2017-12-01

    Satellite radar altimetry has proven to be a valuable tool for remote sensing of the polar oceans, with techniques for estimating sea ice thickness and sea surface height in the ice-covered ocean advancing to the point of becoming routine, if not operational, products. Here, we explore new techniques in radar altimetry of the polar oceans and the sea ice cover. First, we present results from fully-focused SAR (FFSAR) altimetry; by accounting for the phase evolution of scatterers in the scene, the FFSAR technique applies an inter-burst coherent integration, potentially over the entire duration that a scatterer remains in the altimeter footprint, which can narrow the effective along track resolution to just 0.5m. We discuss the improvement of using interleaved operation over burst-more operation for applying FFSAR processing to data acquired by future missions, such as a potential CryoSat follow-on. Second, we present simulated sea ice retrievals from the Ka-band Radar Interferometer (KaRIn), the instrument that will be launched on the Surface Water and Ocean Topography (SWOT) mission in 2021, that is capable of producing swath images of surface elevation. These techniques offer the opportunity to advance our understanding of the physics of the ice-covered oceans, plus new insight into how we interpret more conventional radar altimetry data in these regions.

  16. Ocean current surface measurement using dynamic elevations obtained by the GEOS-3 radar altimeter

    Science.gov (United States)

    Leitao, C. D.; Huang, N. E.; Parra, C. G.

    1977-01-01

    Remote Sensing of the ocean surface from the GEOS-3 satellite using radar altimeter data has confirmed that the altimeter can detect the dynamic ocean topographic elevations relative to an equipotential surface, thus resulting in a reliable direct measurement of the ocean surface. Maps of the ocean dynamic topography calculated over a one month period and with 20 cm contour interval are prepared for the last half of 1975. The Gulf Stream is observed by the rapid slope change shown by the crowding of contours. Cold eddies associated with the current are seen as roughly circular depressions.

  17. Two-component wind fields over ocean waves using atmospheric lidar and motion estimation algorithms

    Science.gov (United States)

    Mayor, S. D.

    2016-02-01

    Numerical models, such as large eddy simulations, are capable of providing stunning visualizations of the air-sea interface. One reason for this is the inherent spatial nature of such models. As compute power grows, models are able to provide higher resolution visualizations over larger domains revealing intricate details of the interactions of ocean waves and the airflow over them. Spatial observations on the other hand, which are necessary to validate the simulations, appear to lag behind models. The rough ocean environment of the real world is an additional challenge. One method of providing spatial observations of fluid flow is that of particle image velocimetry (PIV). PIV has been successfully applied to many problems in engineering and the geosciences. This presentation will show recent research results that demonstate that a PIV-style approach using pulsed-fiber atmospheric elastic backscatter lidar hardware and wavelet-based optical flow motion estimation software can reveal two-component wind fields over rough ocean surfaces. Namely, a recently-developed compact lidar was deployed for 10 days in March of 2015 in the Eureka, California area. It scanned over the ocean. Imagery reveal that breaking ocean waves provide copius amounts of particulate matter for the lidar to detect and for the motion estimation algorithms to retrieve wind vectors from. The image below shows two examples of results from the experiment. The left panel shows the elastic backscatter intensity (copper shades) under a field of vectors that was retrieved by the wavelet-based optical flow algorithm from two scans that took about 15 s each to acquire. The vectors, that reveal offshore flow toward the NW, were decimated for clarity. The bright aerosol features along the right edge of the sector scan were caused by ocean waves breaking on the beach. The right panel is the result of scanning over the ocean on a day when wave amplitudes ranged from 8-12 feet and whitecaps offshore beyond the

  18. Holes in the ocean: Filling voids in bathymetric lidar data

    Science.gov (United States)

    Coleman, John B.; Yao, Xiaobai; Jordan, Thomas R.; Madden, Marguertie

    2011-04-01

    The mapping of coral reefs may be efficiently accomplished by the use of airborne laser bathymetry. However, there are often data holes within the bathymetry data which must be filled in order to produce a complete representation of the coral habitat. This study presents a method to fill these data holes through data merging and interpolation. The method first merges ancillary digital sounding data with airborne laser bathymetry data in order to populate data points in all areas but particularly those of data holes. What follows is to generate an elevation surface by spatial interpolation based on the merged data points obtained in the first step. We conduct a case study of the Dry Tortugas National Park in Florida and produced an enhanced digital elevation model in the ocean with this method. Four interpolation techniques, including Kriging, natural neighbor, spline, and inverse distance weighted, are implemented and evaluated on their ability to accurately and realistically represent the shallow-water bathymetry of the study area. The natural neighbor technique is found to be the most effective. Finally, this enhanced digital elevation model is used in conjunction with Ikonos imagery to produce a complete, three-dimensional visualization of the study area.

  19. Efficient Estimation of Spectral Moments and the Polarimetric Variables on Weather Radars, Sonars, Sodars, Acoustic Flow Meters, Lidars, and Similar Active Remote Sensing Instruments

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A method for estimation of Doppler spectrum, its moments, and polarimetric variables on pulsed weather radars which uses over sampled echo components at a rate...

  20. Ocean wave-radar modulation transfer functions from the West Coast experiment

    Science.gov (United States)

    Wright, J. W.; Plant, W. J.; Keller, W. C.; Jones, W. L.

    1980-01-01

    Short gravity-capillary waves, the equilibrium, or the steady state excitations of the ocean surface are modulated by longer ocean waves. These short waves are the predominant microwave scatterers on the ocean surface under many viewing conditions so that the modulation is readily measured with CW Doppler radar used as a two-scale wave probe. Modulation transfer functions (the ratio of the cross spectrum of the line-of-sight orbital speed and backscattered microwave power to the autospectrum of the line-of-sight orbital speed) were measured at 9.375 and 1.5 GHz (Bragg wavelengths of 2.3 and 13 cm) for winds up to 10 m/s and ocean wave periods from 2-18 s. The measurements were compared with the relaxation-time model; the principal result is that a source of modulation other than straining by the horizontal component of orbital speed, possibly the wave-induced airflow, is responsible for most of the modulation by waves of typical ocean wave period (10 s). The modulations are large; for unit coherence, spectra of radar images of deep-water waves should be proportional to the quotient of the slope spectra of the ocean waves by the ocean wave frequency.

  1. Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

    Science.gov (United States)

    Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

    2018-04-01

    We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

  2. Airborne Lidar and Radar Measurments In and Around Greenland CryoVEx 2006

    DEFF Research Database (Denmark)

    Stenseng, Lars; Hvidegaard, Sine Munk; Skourup, Henriette

    Air Greenland. The main purpose was to collect coincident ASIRAS and laser data at validation sites placed on land ice and sea ice in the Arctic area and offer logistic support to ground teams. The data collected will be important for the understanding of CryoSat-2 radar signals. A number...

  3. Hyper-resolution urban flood modeling using high-resolution radar precipitation and LiDAR data

    Science.gov (United States)

    Noh, S. J.; Lee, S.; Lee, J.; Seo, D. J.

    2016-12-01

    Floods occur most frequently among all natural hazards, often causing widespread economic damage and loss of human lives. In particular, urban flooding is becoming increasingly costly and difficult to manage with a greater concentration of population and assets in urban centers. Despite of known benefits for accurate representation of small scale features and flow interaction among different flow domains, which have significant impact on flood propagation, high-resolution modeling has not been fully utilized due to expensive computation and various uncertainties from model structure, input and parameters. In this study, we assess the potential of hyper-resolution hydrologic-hydraulic modeling using high-resolution radar precipitation and LiDAR data for improved urban flood prediction and hazard mapping. We describe a hyper-resolution 1D-2D coupled urban flood model for pipe and surface flows and evaluate the accuracy of the street-level inundation information produced. For detailed geometric representation of urban areas and for computational efficiency, we use 1 m-resolution topographical data, processed from LiDAR measurements, in conjunction with adaptive mesh refinement. For street-level simulation in large urban areas at grid sizes of 1 to 10 m, a hybrid parallel computing scheme using MPI and openMP is also implemented in a high-performance computing system. The modeling approach developed is applied for the Johnson Creek Catchment ( 40 km2), which makes up the Arlington Urban Hydroinformatics Testbed. In addition, discussion will be given on availability of hyper-resolution simulation archive for improved real-time flood mapping.

  4. Active laser radar (lidar) for measurement of corresponding height and reflectance images

    Science.gov (United States)

    Froehlich, Christoph; Mettenleiter, M.; Haertl, F.

    1997-08-01

    For the survey and inspection of environmental objects, a non-tactile, robust and precise imaging of height and depth is the basis sensor technology. For visual inspection,surface classification, and documentation purposes, however, additional information concerning reflectance of measured objects is necessary. High-speed acquisition of both geometric and visual information is achieved by means of an active laser radar, supporting consistent 3D height and 2D reflectance images. The laser radar is an optical-wavelength system, and is comparable to devices built by ERIM, Odetics, and Perceptron, measuring the range between sensor and target surfaces as well as the reflectance of the target surface, which corresponds to the magnitude of the back scattered laser energy. In contrast to these range sensing devices, the laser radar under consideration is designed for high speed and precise operation in both indoor and outdoor environments, emitting a minimum of near-IR laser energy. It integrates a laser range measurement system and a mechanical deflection system for 3D environmental measurements. This paper reports on design details of the laser radar for surface inspection tasks. It outlines the performance requirements and introduces the measurement principle. The hardware design, including the main modules, such as the laser head, the high frequency unit, the laser beam deflection system, and the digital signal processing unit are discussed.the signal processing unit consists of dedicated signal processors for real-time sensor data preprocessing as well as a sensor computer for high-level image analysis and feature extraction. The paper focuses on performance data of the system, including noise, drift over time, precision, and accuracy with measurements. It discuses the influences of ambient light, surface material of the target, and ambient temperature for range accuracy and range precision. Furthermore, experimental results from inspection of buildings, monuments

  5. Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zhien

    2010-06-29

    The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processes is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The

  6. 2015 Lowndes County (GA) Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: NOAA OCM Lidar for Lowndes County, GA with the option to Collect Lidar in Cook and Tift Counties, GA Lidar Data Acquisition and Processing Production Task...

  7. 2015 OLC Lidar: Wasco, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Wasco County, WA, study area. The Oregon LiDAR Consortium's Wasco County...

  8. Bistatic High Frequency Radar Ocean Surface Cross Section for an FMCW Source with an Antenna on a Floating Platform

    Directory of Open Access Journals (Sweden)

    Yue Ma

    2016-01-01

    Full Text Available The first- and second-order bistatic high frequency radar cross sections of the ocean surface with an antenna on a floating platform are derived for a frequency-modulated continuous wave (FMCW source. Based on previous work, the derivation begins with the general bistatic electric field in the frequency domain for the case of a floating antenna. Demodulation and range transformation are used to obtain the range information, distinguishing the process from that used for a pulsed radar. After Fourier-transforming the autocorrelation and comparing the result with the radar range equation, the radar cross sections are derived. The new first- and second-order antenna-motion-incorporated bistatic radar cross section models for an FMCW source are simulated and compared with those for a pulsed source. Results show that, for the same radar operating parameters, the first-order radar cross section for the FMCW waveform is a little lower than that for a pulsed source. The second-order radar cross section for the FMCW waveform reduces to that for the pulsed waveform when the scattering patch limit approaches infinity. The effect of platform motion on the radar cross sections for an FMCW waveform is investigated for a variety of sea states and operating frequencies and, in general, is found to be similar to that for a pulsed waveform.

  9. Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR: Chapter 1

    Science.gov (United States)

    Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.

    2015-01-01

    The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.

  10. Radar Chart

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Radar Chart collection is an archived product of summarized radar data. The geographic coverage is the 48 contiguous states of the United States. These hourly...

  11. 2015 OLC Lidar: Chelan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Chelan FEMA study area. This study area is located in...

  12. KARIN: The Ka-Band Radar Interferometer for the Proposed Surface Water and Ocean Topography (SWOT) Mission

    Science.gov (United States)

    Esteban-Fernandez, Daniel; Peral, Eva; McWatters, Dalia; Pollard, Brian; Rodriguez, Ernesto; Hughes, Richard

    2013-01-01

    Over the last two decades, several nadir profiling radar altimeters have provided our first global look at the ocean basin-scale circulation and the ocean mesoscale at wavelengths longer than 100 km. Due to sampling limitations, nadir altimetry is unable to resolve the small wavelength ocean mesoscale and sub-mesoscale that are responsible for the vertical mixing of ocean heat and gases and the dissipation of kinetic energy from large to small scales. The proposed Surface Water and Ocean Topography (SWOT) mission would be a partnership between NASA, CNES (Centre National d'Etudes Spaciales) and the Canadian Space Agency, and would have as one of its main goals the measurement of ocean topography with kilometer-scale spatial resolution and centimeter scale accuracy. In this paper, we provide an overview of all ocean error sources that would contribute to the SWOT mission.

  13. The Ability of MM5 to Simulate Ice Clouds: Systematic Comparison between Simulated and Measured Fluxes and Lidar/Radar Profiles at SIRTA Atmospheric Observatory

    Energy Technology Data Exchange (ETDEWEB)

    Chiriaco, M.; Vautard, R.; Chepfer, H.; Haeffelin, M.; Wanherdrick, Y.; Morille, Y.; Protat, A.; Dudhia, J.

    2005-03-18

    Ice clouds play a major role in the radiative energy budget of the Earth-atmosphere system (Liou 1986). Their radiative effect is governed primarily by the equilibrium between their albedo and greenhouse effects. Both macrophysical and microphysical properties of ice clouds regulate this equilibrium. For quantifying the effect of these clouds onto climate and weather systems, they must be properly characterized in atmospheric models. In this paper we use remote-sensing measurements from the SIRTA ground based atmospheric observatory (Site Instrumental de Recherche par Teledetection Atmospherique, http://sirta.lmd.polytechnique.fr). Lidar and radar observations taken over 18 months are used, in order to gain statistical confidence in the model evaluation. Along this period of time, 62 days are selected for study because they contain parts of ice clouds. We use the ''model to observations'' approach by simulating lidar and radar signals from MM5 outputs. Other more classical variables such as shortwave and longwave radiative fluxes are also used. Four microphysical schemes, among which that proposed by Reisner et al. (1998) with original or modified parameterizations of particle terminal fall velocities (Zurovac-Jevtic and Zhang 2003, Heymsfield and Donner 1990), and the simplified Dudhia (1989) scheme are evaluated in this study.

  14. Study of ocean red tide multi-parameter monitoring technology based on double-wavelength airborne lidar system

    Science.gov (United States)

    Lin, Hong; Wang, Xinming; Liang, Kun

    2010-10-01

    For monitoring and forecasting of the ocean red tide in real time, a marine environment monitoring technology based on the double-wavelength airborne lidar system is proposed. An airborne lidar is father more efficient than the traditional measure technology by the boat. At the same time, this technology can detect multi-parameter about the ocean red tide by using the double-wavelength lidar.It not only can use the infrared laser to detect the scattering signal under the water and gain the information about the red tise's density and size, but also can use the blue-green laser to detect the Brillouin scattering signal and deduce the temperature and salinity of the seawater.The red tide's density detecting model is firstly established by introducing the concept about the red tide scattering coefficient based on the Mie scattering theory. From the Brillouin scattering theory, the relationship about the blue-green laser's Brillouin scattering frequency shift value and power value with the seawater temperature and salinity is found. Then, the detecting mode1 of the saewater temperature and salinity can be established. The value of the red tide infrared scattering signal is evaluated by the simulation, and therefore the red tide particles' density can be known. At the same time, the blue-green laser's Brillouin scattering frequency shift value and power value are evaluated by simulating, and the temperature and salinity of the seawater can be known. Baed on the multi-parameters, the ocean red tide's growth can be monitored and forecasted.

  15. Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

    Science.gov (United States)

    García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

    2018-04-01

    Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

  16. 2002 Maryland Department of Natural Resources LiDAR: Worcester County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  17. 2005 Maryland Department of Natural Resources LiDAR: Cecil County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LIDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  18. Spatial variations in drainage efficiency in a boreal wetland environment as a function of lidar and radar-derived deviations from the regional hydraulic gradient

    Science.gov (United States)

    Hopkinson, C.; Brisco, B.; Chasmer, L.; Devito, K.; Montgomery, J. S.; Patterson, S.; Petrone, R. M.

    2017-12-01

    The dense forest cover of the Western Boreal Plains of northern Alberta is underlain by a mix of glacial moraines, sandy outwash sediments and clay plains possessing spatially variable hydraulic conductivities. The region is also characterised by a large number of post-glacial surface depression wetlands that have seasonally and topographically limited surface connectivity. Consequently, drainage along shallow regional hydraulic gradients may be dominated either by variations in surface geology or local variations in Et. Long-term government lake level monitoring is sparse in this region, but over a decade of hydrometeorological monitoring has taken place around the Utikuma Regional Study Area (URSA), a research site led by the University of Alberta. In situ lake and ground water level data are here combined with time series of airborne lidar and RadarSat II synthetic aperture radar (SAR) data to assess the spatial variability of water levels during late summer period characterised by flow recession. Long term Lidar data were collected or obtained by the authors in August of 2002, 2008, 2011 and 2016, while seasonal SAR data were captured approximately every 24 days during the summers of 2015, 2016 and 2017. Water levels for wetlands exceeding 100m2 in area across a north-trending 20km x 5km topographic gradient north of Utikuma Lake were extracted directly from the lidar and indirectly from the SAR. The recent seasonal variability in spatial water levels was extracted from SAR, while the lidar data illustrated more long term trends associated with land use and riparian vegetation succession. All water level data collected in August were combined and averaged at multiple scales using a raster focal statistics function to generate a long term spatial map of the regional hydraulic gradient and scale-dependent variations. Areas of indicated high and low drainage efficiency were overlain onto layers of landcover and surface geology to ascertain causal relationships

  19. Lagrangian modelling of ocean surface waves and synthetic aperture radar wave measurements

    Energy Technology Data Exchange (ETDEWEB)

    Fouques, Sebastien

    2005-07-01

    The present thesis is concerned with the estimation of the ocean wave spectrum from synthetic aperture radar imaging and the modelling of ocean surface waves using the Lagrangian formalism. The first part gives a short overview of the theories of ocean surface waves and synthetic aperture radar (SAR) whereas the second part consists of five independent publications. The first two articles investigate the influence of the radar backscatter model on the SAR imaging of ocean waves. In Article I, Monte Carlo simulations of SAR images of the ocean surface are carried out using a nonlinear backscatter model that include both specular reflection and Bragg scattering and the results are compared to simulations from the classical Hasselmann integral transform (Hasselmann and Hasselmann, 1991). It is shown that nonlinearities in the backscatter model strongly influence the imaging of range-travelling waves and that the former can suppress the range-splitting effect (Bruning et al., 1988). Furthermore, in Article II a database of Envisat-ASAR Wave Mode products co-located with directional wave spectra from the numerical model WAM and which contains range-travelling wave cases only, is set up. The WAM spectra are used as input to several ocean-to-SAR integral transforms, with various real aperture radar (RAR) models and the obtained SAR image cross-spectra are compared to the Envisat-ASAR observations. A first result is that the use of a linear backscatter model leads to a high proportion of non-physical negative backscatter values in the RAR image, as suggested by Schulz-Stellenfleth (2001). Then, a comparison between the observed SAR cross-spectra and the ones simulated through Hasselmann's integral transform reveals that only twenty percents of the observations show a range-splitting effect as strong as in the simulations. A much better agreement is obtained when using the integral transform by Schulz-Stellenfleth (2003), which is based on a nonlinear hackscatter model

  20. 2015 OLC Lidar DEM: Wasco, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Wasco County, WA, study area. The Oregon LiDAR Consortium's Wasco County...

  1. 2006 MDEQ Camp Shelby, MS Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the acquisition and processing of bare earth lidar data, raw point cloud lidar data, lidar intensity data, and floodmap breaklines...

  2. RADAR PPI Scope Overlay

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — RADAR PPI Scope Overlays are used to position a RADAR image over a station at the correct resolution. The archive maintains several different RADAR resolution types,...

  3. Observations on Stratospheric-Mesospheric-Thermospheric temperatures using Indian MST radar and co-located LIDAR during Leonid Meteor Shower (LMS

    Directory of Open Access Journals (Sweden)

    R. Selvamurugan

    2002-11-01

    Full Text Available The temporal and height statistics of the occurrence of meteor trails during the Leonid meteor shower revealed the capability of the Indian MST radar to record large numbers of meteor trails. The distribution of radio meteor trails due to a Leonid meteor shower in space and time provided a unique opportunity to construct the height profiles of lower thermospheric temperatures and winds, with good time and height resolution. There was a four-fold increase in the meteor trails observed during the LMS compared to a typical non-shower day. The temperatures were found to be in excellent continuity with the temperature profiles below the radio meteor region derived from the co-located Nd-Yag LIDAR and the maximum height of the temperature profile was extended from the LIDAR to ~110 km. There are, how-ever, some significant differences between the observed profiles and the CIRA-86 model profiles. The first results on the meteor statistics and neutral temperature are presented and discussed below.  Key words. Atmospheric composition and structure (pres-sure, density, and temperature History of geophysics (at-mospheric sciences Meteorology and atmospheric dynamics (middle atmosphere dynamics

  4. 2008 NOAA Integrated Ocean and Coastal Mapping (IOCM) LIDAR: New Hampshire

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using an OPTECH ALTM system on June 8,...

  5. 2008 NOAA/NGS Integrated Ocean and Coastal Mapping (IOCM) LIDAR: Kenai Peninsula Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using an OPTECH ALTM system. The data...

  6. A probabilistic method for the estimation of ocean surface currents from short time series of HF radar data

    Science.gov (United States)

    Guérin, Charles-Antoine; Grilli, Stéphan T.

    2018-01-01

    We present a new method for inverting ocean surface currents from beam-forming HF radar data. In contrast with the classical method, which inverts radial currents based on shifts of the main Bragg line in the radar Doppler spectrum, the method works in the temporal domain and inverts currents from the amplitude modulation of the I and Q radar time series. Based on this principle, we propose a Maximum Likelihood approach, which can be combined with a Bayesian inference method assuming a prior current distribution, to infer values of the radial surface currents. We assess the method performance by using synthetic radar signal as well as field data, and systematically comparing results with those of the Doppler method. The new method is found advantageous for its robustness to noise at long range, its ability to accommodate shorter time series, and the possibility to use a priori information to improve the estimates. Limitations are related to current sign errors at far-ranges and biased estimates for small current values and very short samples. We apply the new technique to a data set from a typical 13.5 MHz WERA radar, acquired off of Vancouver Island, BC, and show that it can potentially improve standard synoptic current mapping.

  7. 2004 Maryland Department of Natural Resources LiDAR: Anne Arundel, Charles, Howard and St. Mary's Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LIDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  8. 2014 OLC Lidar: Colville, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI, a Quantum Spatial company, has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Colville study area. This study area is...

  9. 2015 OLC Lidar DEM: Chelan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Chelan FEMA study area. This study area is located in...

  10. 2015 OLC Lidar: Okanogan WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Okanogan FEMA study area. This study area is located in...

  11. 2012 USGS Lidar: Juneau (AK)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This task order is for planning, acquisition, processing, and derivative products of LiDAR data to be collected for Juneau, Alaska. LiDAR data, and derivative...

  12. A Radar/Radiometer Instrument for Mapping Soil Moisture and Ocean Salinity

    Science.gov (United States)

    Hildebrand, Peter H.; Hilliard, Laurence; Rincon, Rafael; LeVine, David; Mead, James

    2003-01-01

    The RadSTAR instrument combines an L-band, digital beam-forming radar with an L-band synthetic aperture, thinned array (STAR) radiometer. The RadSTAR development will support NASA Earth science goals by developing a novel, L-band scatterometer/ radiometer that measures Earth surface bulk material properties (surface emissions and backscatter) as well as surface characteristics (backscatter). Present, real aperture airborne L-Band active/passive measurement systems such as the JPUPALS (Wilson, et al, 2000) provide excellent sampling characteristics, but have no scanning capabilities, and are extremely large; the huge JPUPALS horn requires a the C-130 airborne platform, operated with the aft loading door open during flight operation. The approach used for the upcoming Aquarius ocean salinity mission or the proposed Hydros soil mission use real apertures with multiple fixed beams or scanning beams. For real aperture instruments, there is no upgrade path to scanning over a broad swath, except rotation of the whole aperture, which is an approach with obvious difficulties as aperture size increases. RadSTAR will provide polarimetric scatterometer and radiometer measurements over a wide swath, in a highly space-efficient configuration. The electronic scanning approaches provided through STAR technology and digital beam forming will enable the large L-band aperture to scan efficiently over a very wide swath. RadSTAR technology development, which merges an interferometric radiometer with a digital beam forming scatterometer, is an important step in the path to space for an L-band scatterometer/radiometer. RadSTAR couples a patch array antenna with a 1.26 GHz digital beam forming radar scatterometer and a 1.4 GHz STAR radiometer to provide Earth surface backscatter and emission measurements in a compact, cross-track scanning instrument with no moving parts. This technology will provide the first L-band, emission and backscatter measurements in a compact aircraft instrument

  13. Ocean, Land and Meteorology Studies Using Space-Based Lidar Measurements

    Science.gov (United States)

    Hu,Yongxiang

    2009-01-01

    CALIPSO's main mission objective is studying the climate impact of clouds and aerosols in the atmosphere. CALIPSO also collects information about other components of the Earth's ecosystem, such as oceans and land. This paper introduces the physics concepts and presents preliminary results for the valueadded CALIPSO Earth system science products. These include ocean surface wind speeds, column atmospheric optical depths, ocean subsurface backscatter, land surface elevations, atmospheric temperature profiles, and A-train data fusion products.

  14. Lidar to lidar calibration

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Villanueva, Héctor

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  15. Inter-seasonal surface deformations of an active rock glacier imaged with radar and lidar remote sensing; Turtmann valley, Switzerland

    Science.gov (United States)

    Kos, Andrew; Buchli, Thomas; Strozzi, Tazio; Springman, Sarah

    2013-04-01

    Inter-seasonal changes in surface deformation were imaged using a portable radar interferometer and terrestrial laser scanner during a series of three campaigns that took place in autumn 2011, summer 2012 and autumn 2012 on a rock glacier located in the Turtmann valley, Switzerland. Satellite radar interferometry (ERS 1 & 2, CosmoSkymed) indicate that accelerated downslope movement of the rock glacier commenced during the 1990s. Due to signal decorrelation associated with the satellite repeat pass time interval, continuous ground-based radar interferometry measurements were undertaken. Results show that the rock glacier accelerated significantly in Summer (Vmax = 6.0cm/25hrs), probably in response to the condition of the subsurface hydrology (e.g. post-peak spring snow melt and/or infiltration of rainfall). In autumn, the displacement velocity was reduced (Vmax = 2.0cm/25hrs). A one year surface difference of the glacier topography, derived from terrestrial laser scanning, provided insight into the rock glacier kinematics. Ongoing research is aimed at integrating surface displacement results with an extensive borehole monitoring system consisting of inclinometers and temperature sensors.

  16. Light Detection and Ranging (LIDAR) From Space - Laser Altimeters

    Science.gov (United States)

    Sun, Xiaoli

    2016-01-01

    Light detection and ranging, or lidar, is like radar but atoptical wavelengths. The principle of operation and theirapplications in remote sensing are similar. Lidars havemany advantages over radars in instrument designs andapplications because of the much shorter laser wavelengthsand narrower beams. The lidar transmitters and receiveroptics are much smaller than radar antenna dishes. Thespatial resolution of lidar measurement is much finer thanthat of radar because of the much smaller footprint size onground. Lidar measurements usually give a better temporalresolution because the laser pulses can be much narrowerthan radio frequency (RF) signals. The major limitation oflidar is the ability to penetrate clouds and ground surfaces.

  17. 2003 Maryland Department of Natural Resources LiDAR: Dorchester, Somerset, Talbot,and Wicomico Counties, with portions of Caroline, Kent and Queen Anne's Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  18. Use of Ground Penetrating Radar for Locating Contraband Aboard Ocean Going Vessels: Feasibility Study

    National Research Council Canada - National Science Library

    Llopis, Jose

    2001-01-01

    Ground Penetrating Radar (GPR) surveys were conducted over various stockpiled materials at the Alabama state Docks located in Mobile, AL, to determine whether GPR is a viable method for rapidly detecting contraband materials...

  19. Radar Plan Position Indicator Scope

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Radar Plan Position Indicator Scope is the collection of weather radar imagery for the period prior to the beginning of the Next Generation Radar (NEXRAD) system...

  20. 2003 Oahu Coastline Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

  1. Fault zone structure and kinematics from lidar, radar, and imagery: revealing new details along the creeping San Andreas Fault

    Science.gov (United States)

    DeLong, S.; Donnellan, A.; Pickering, A.

    2017-12-01

    Aseismic fault creep, coseismic fault displacement, distributed deformation, and the relative contribution of each have important bearing on infrastructure resilience, risk reduction, and the study of earthquake physics. Furthermore, the impact of interseismic fault creep in rupture propagation scenarios, and its impact and consequently on fault segmentation and maximum earthquake magnitudes, is poorly resolved in current rupture forecast models. The creeping section of the San Andreas Fault (SAF) in Central California is an outstanding area for establishing methodology for future scientific response to damaging earthquakes and for characterizing the fine details of crustal deformation. Here, we describe how data from airborne and terrestrial laser scanning, airborne interferometric radar (UAVSAR), and optical data from satellites and UAVs can be used to characterize rates and map patterns of deformation within fault zones of varying complexity and geomorphic expression. We are evaluating laser point cloud processing, photogrammetric structure from motion, radar interferometry, sub-pixel correlation, and other techniques to characterize the relative ability of each to measure crustal deformation in two and three dimensions through time. We are collecting new and synthesizing existing data from the zone of highest interseismic creep rates along the SAF where a transition from a single main fault trace to a 1-km wide extensional stepover occurs. In the stepover region, creep measurements from alignment arrays 100 meters long across the main fault trace reveal lower rates than those in adjacent, geomorphically simpler parts of the fault. This indicates that deformation is distributed across the en echelon subsidiary faults, by creep and/or stick-slip behavior. Our objectives are to better understand how deformation is partitioned across a fault damage zone, how it is accommodated in the shallow subsurface, and to better characterize the relative amounts of fault creep

  2. Radar Weather Observation

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Radar Weather Observation is a set of archived historical manuscripts stored on microfiche. The primary source of these radar weather observations manuscript records...

  3. Weather Radar Impact Zones

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data represent an inventory of the national impacts of wind turbine interference with NEXRAD radar stations. This inventory was developed by the NOAA Radar...

  4. Retrieval of the ocean wave spectrum in open and thin ice covered ocean waters from ERS Synthetic Aperture Radar images

    International Nuclear Information System (INIS)

    De Carolis, G.

    2001-01-01

    This paper concerns with the task of retrieving ocean wave spectra form imagery provided by space-borne SAR systems such as that on board ERS satellite. SAR imagery of surface wave fields travelling into open ocean and into thin sea ice covers composed of frazil and pancake icefields is considered. The major purpose is to gain insight on how the spectral changes can be related to sea ice properties of geophysical interest such as the thickness. Starting from SAR image cross spectra computed from Single Look Complex (SLC) SAR images, the ocean wave spectrum is retrieved using an inversion procedure based on the gradient descent algorithm. The capability of this method when applied to satellite SAR sensors is investigated. Interest in the SAR image cross spectrum exploitation is twofold: first, the directional properties of the ocean wave spectra are retained; second, external wave information needed to initialize the inversion procedure may be greatly reduced using only information included in the SAR image cross spectrum itself. The main drawback is that the wind waves spectrum could be partly lost and its spectral peak wave number underestimated. An ERS-SAR SLC image acquired on April 10, 1993 over the Greenland Sea was selected as test image. A pair of windows that include open-sea only and sea ice cover, respectively, were selected. The inversions were carried out using different guess wave spectra taken from SAR image cross spectra. Moreover, care was taken to properly handle negative values eventually occurring during the inversion runs. This results in a modification of the gradient descending the technique that is required if a non-negative solution of the wave spectrum is searched for. Results are discussed in view of the possibility of SAR data to detect ocean wave dispersion as a means for the retrieval of ice thickness

  5. 2015 OLC Lidar DEM: Big Wood, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Big Wood 2015 study area. This study area is located in...

  6. 2007 South Carolina DNR Lidar: Dorchester County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Woolpert Inc. conducted a LiDAR survey to acquire LiDAR capable of producing a DEM for orthophoto rectification and able to support 2-foot contour specifications....

  7. 2015 OLC FEMA Lidar: Snake River, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Snake River FEMA study area. This study area is located...

  8. 2007 South Carolina DNR Lidar: Anderson County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LiDAR data acquisition was executed in 5 sessions, from March 7 to March 9, 2007. The airborne GPS (ABGPS) base stations supporting the LiDAR acquisition...

  9. 2011 South Carolina DNR Lidar: York County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,500 square miles in York, Pickens, Anderson, and Oconee Counties in South Carolina. This metadata covers the LiDAR produced...

  10. 2014 PSLC Lidar: City of Redmond

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In February 2014, Quantum Spatial (QSI) was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data for the City of...

  11. 2008 St. Johns County, FL Countywide Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne terrestrial LiDAR was collected for St. Johns County, FL. System Parameters/Flight Plan. The LiDAR system acquisition parameters were developed based on a...

  12. 2006 Volusia County Florida LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is the lidar data for Volusia County, Florida, approximately 1,432 square miles, acquired in early March of 2006. A total of 143 flight lines of Lidar...

  13. 2009 Bayfield County Lake Superior Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LIDAR survey presents digital elevation data sets of a bald earth surface model and 2ft interval contours covering Bayfield County, Wisconsin. The LIDAR data was...

  14. 2014 OLC Lidar DEM: Colville, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI, a Quantum Spatial company, has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Colville study area. This study area is...

  15. 2014 Horry County, South Carolina Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry...

  16. 2010 ARRA Lidar: 4 Southeast Counties (MI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Southeast Michigan LiDAR LiDAR Data Acquisition and Processing Production Task- Monroe, St. Clair, Macomb, and Livingston Counties SEMCOG CONTRACT:...

  17. 2015 Oregon Department Forestry Lidar: Northwest OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GeoTerra, Inc. was selected by Oregon Department of Forestry to provide Lidar remote sensing data including LAZ files of the classified Lidar points and surface...

  18. 2007 USGS Lidar: Canyon Fire (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Southern California Light Detection and Ranging (LiDAR) data is to provide high accuracy LIDAR data. These datasets will be the initial acquisition to support...

  19. A Smart Climatology of Evaporation Duct Height and Surface Radar Propagation in the Indian Ocean

    National Research Council Canada - National Science Library

    Twigg, Katherine L

    2007-01-01

    .... We have used existing, civilian, dynamically balanced reanalysis data, for 1970 to 2006, and a state-of-the-art ED model, to produce a spatially and temporally refined EDH climatology for the Indian Ocean (10) and nearby seas...

  20. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Tulalip Partnership

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2012, WSI (Watershed Sciences, Inc.) was contracted by the Puget Sound LiDAR Consortium (PSLC)to collect Light Detection and Ranging (LiDAR) data on a...

  1. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Willapa Valley (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In January, 2014 WSI, a Quantum Spatial (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  2. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Saddle Mountain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2013, WSI, a Quantum Spatial Company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  3. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  4. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  5. 2012 MEGIS Topographic Lidar: Statewide Lidar Project Area 1 (Aroostook), Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  6. 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Lewis County survey area for the Puget Sound LiDAR Consortium. This data...

  7. 2012 MEGIS Topographic Lidar: Statewide Lidar Project Areas 2 and 3 (Mid-Coastal Cleanup), Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  8. SAR and LIDAR fusion: experiments and applications

    Science.gov (United States)

    Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

    2013-05-01

    In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

  9. What distinguishes the small fraction of tropical ocean storms with lightning? An examination of the environment, organization, and evolution of radar features over Kwajalein

    Science.gov (United States)

    Bang, S. D.; Zipser, E. J.

    2017-12-01

    Lightning over the tropical ocean, though much rarer than over land, is predominantly observed in large, mostly mature convective systems. The implication is that these may require external forcing or organization in order to develop updrafts sufficiently strong to loft and sustain graupel and supercooled water above the freezing level and thereby produce lightning. We examine three years of radar data from the Kwajalein Atoll in the Marshall Islands in the tropical Pacific Ocean, which we subject to the Warning Decisions Support System - Integrated Information (WDSS-II) tracking algorithm in order to create an evolutionary radar feature dataset. In conjunction with ERA-interim reanalysis environmental data and World Wide Lightning Location Network (WWLLN) lightning data, we are able to observe the lifecycles of electrified convection over Kwajalein and examine the characteristics leading up to a lightning flash for radar features throughout the intensity spectrum. We find that lightning over Kwajalein exhibits the same tendency to occur in large, mature radar features, and the probability of lightning increases with increasing size and, to a certain extent, age. However, there is little evidence to support the role of singular environmental parameters in the development into large features. We continue to struggle to find the reasons that may influence or control the evolution of small features into large, organized convective systems, a major issue that has importance well beyond whether the feature is electrified.

  10. A Ground-Based Doppler Radar and Micropulse Lidar Forward Simulator for GCM Evaluation of Arctic Mixed-Phase Clouds: Moving Forward Towards an Apples-to-apples Comparison of Hydrometeor Phase

    Science.gov (United States)

    Lamer, K.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

    2017-12-01

    An important aspect of evaluating Artic cloud representation in a general circulation model (GCM) consists of using observational benchmarks which are as equivalent as possible to model output in order to avoid methodological bias and focus on correctly diagnosing model dynamical and microphysical misrepresentations. However, current cloud observing systems are known to suffer from biases such as limited sensitivity, and stronger response to large or small hydrometeors. Fortunately, while these observational biases cannot be corrected, they are often well understood and can be reproduced in forward simulations. Here a ground-based millimeter wavelength Doppler radar and micropulse lidar forward simulator able to interface with output from the Goddard Institute for Space Studies (GISS) ModelE GCM is presented. ModelE stratiform hydrometeor fraction, mixing ratio, mass-weighted fall speed and effective radius are forward simulated to vertically-resolved profiles of radar reflectivity, Doppler velocity and spectrum width as well as lidar backscatter and depolarization ratio. These forward simulated fields are then compared to Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) ground-based observations to assess cloud vertical structure (CVS). Model evalution of Arctic mixed-phase cloud would also benefit from hydrometeor phase evaluation. While phase retrieval from synergetic observations often generates large uncertainties, the same retrieval algorithm can be applied to observed and forward-simulated radar-lidar fields, thereby producing retrieved hydrometeor properties with potentially the same uncertainties. Comparing hydrometeor properties retrieved in exactly the same way aims to produce the best apples-to-apples comparisons between GCM ouputs and observations. The use of a comprenhensive ground-based forward simulator coupled with a hydrometeor classification retrieval algorithm provides a new perspective for GCM evaluation of Arctic mixed

  11. 2006 Fulton County Georgia Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of Fulton County. The Fulton County LiDAR Survey project area consists of approximately 690.5 square...

  12. The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

    Science.gov (United States)

    Protat, A.; Delanoë, J.; May, P. T.; Haynes, J.; Jakob, C.; O'Connor, E.; Pope, M.; Wheeler, M. C.

    2011-08-01

    The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by

  13. 2012 Oregon Lidar Consortium (OLC) Lidar DEM: Keno (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Oregon Keno Study Area for the Oregon Department of Geology and Mineral...

  14. 2012 Oregon Lidar Consortium (OLC) Lidar: Keno (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Oregon Keno Study Area for the Oregon Department of Geology and Mineral...

  15. Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

    Science.gov (United States)

    Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

    2017-12-01

    A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

  16. 2009 SCDRN Lidar: Florence County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The South Carolina Department of Natural Resources (SCDNR) contracted with Sanborn to provide LiDAR mapping services for Florence County, SC. Utilizing multi-return...

  17. 2006 FEMA Lidar: Hawaiian Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The FEMA Task Order 26 LiDAR data set was collected by Airborne 1 Corporation of El Segundo, California in September - December of 2006 for URS Corp.

  18. 2009 SCDNR Charleston County Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Photoscience completed the original collection and classification of the multiple return LiDAR of Charleston County, South Carolina in the winter of 2006-2007. In...

  19. 2009 Chatham County Georgia Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR generated point cloud acquired in spring 2009 for Chatham County, Georgia for the Metropolitan Planning Commission. The data are classified as follows: Class 1...

  20. 2014 NJMC Lidar: Hackensack Meadowlands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In February 2014, Quantum Spatial, Inc. (QSI) was contracted by the New Jersey Meadowlands Commission (NJMC) to collect Light Detection and Ranging (LiDAR) data in...

  1. 2014 Mobile County, AL Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Atlantic was contracted to acquire high resolution topographic LiDAR (Light Detection and Ranging) data located in Mobile County, Alabama. The intent was to collect...

  2. 2008 City of Baltimore Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In the spring of 2008, the City of Baltimore expressed an interest to upgrade the City GIS Database with mapping quality airborne LiDAR data. The City of Baltimore...

  3. 2013 USGS Lidar: Norfolk (VA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Laser Mapping Specialist, Inc (LMSI) and The Atlantic Group (Atlantic) provided high accuracy, calibrated multiple return LiDAR for roughly 1,130 square miles around...

  4. 2009 SCDNR Horry County Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sanborn Map Company completed the original classification of the multiple return LiDAR of Horry County, South Carolina in 2009. In 2013, Dewberry was tasked with...

  5. Constraining mass-diameter relations from hydrometeor images and cloud radar reflectivities in tropical continental and oceanic convective anvils

    Science.gov (United States)

    Fontaine, E.; Schwarzenboeck, A.; Delanoë, J.; Wobrock, W.; Leroy, D.; Dupuy, R.; Gourbeyre, C.; Protat, A.

    2014-10-01

    In this study the density of ice hydrometeors in tropical clouds is derived from a combined analysis of particle images from 2-D-array probes and associated reflectivities measured with a Doppler cloud radar on the same research aircraft. Usually, the mass-diameter m(D) relationship is formulated as a power law with two unknown coefficients (pre-factor, exponent) that need to be constrained from complementary information on hydrometeors, where absolute ice density measurement methods do not apply. Here, at first an extended theoretical study of numerous hydrometeor shapes simulated in 3-D and arbitrarily projected on a 2-D plan allowed to constrain the exponent βof the m(D) relationship from the exponent σ of the surface-diameterS(D)relationship, which is likewise written as a power law. Since S(D) always can be determined for real data from 2-D optical array probes or other particle imagers, the evolution of the m(D) exponent can be calculated. After that, the pre-factor α of m(D) is constrained from theoretical simulations of the radar reflectivities matching the measured reflectivities along the aircraft trajectory. The study was performed as part of the Megha-Tropiques satellite project, where two types of mesoscale convective systems (MCS) were investigated: (i) above the African continent and (ii) above the Indian Ocean. For the two data sets, two parameterizations are derived to calculate the vertical variability of m(D) coefficients α and β as a function of the temperature. Originally calculated (with T-matrix) and also subsequently parameterized m(D) relationships from this study are compared to other methods (from literature) of calculating m(D) in tropical convection. The significant benefit of using variable m(D) relations instead of a single m(D) relationship is demonstrated from the impact of all these m(D) relations on Z-CWC (Condensed Water Content) and Z-CWC-T-fitted parameterizations.

  6. 2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (New Jersey)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS New Jersey CMGP Sandy Lidar 0.7 Meter NPS LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No....

  7. Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

    Science.gov (United States)

    Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

    2009-01-01

    Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm

  8. Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

    Directory of Open Access Journals (Sweden)

    Cristina M. Bentz

    2009-01-01

    Full Text Available Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD, Ocean Chlorophyll 4 bands (OC4v4RAD, and Ocean Chlorophyll 2 bands (OC2v4RAD. The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT, and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg·m-3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD. The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3 than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively. We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed

  9. 2004 Alaska Lidar Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data sets are generated using the OPTECH ALTM 70 kHz LIDAR system mounted onboard AeroMap's twin-engine Cessna 320 aircraft. Classified data sets such as this...

  10. 2013-2014 USGS Lidar: Olympic Peninsula (WA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS Olympic Peninsula Washington LIDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00849...

  11. 2015 OLC FEMA Lidar DEM: Snake River, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Snake River FEMA study area. This study area is located...

  12. 2009 - 2011 CA Coastal Conservancy Coastal Lidar Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  13. 2014 USGS CMGP Lidar: Post Sandy (Long Island, NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Long Island New York Sandy LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00296 Woolpert...

  14. 2006 FEMA New Jersey Flood Mitigation Lidar: Highlands Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. LiDAR was flown for...

  15. 2012 NOAA Fisheries Topographic Lidar: Bridge Creek, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data. This data set is an LAZ (compressed LAS) format file containing LIDAR point...

  16. 2010 USGS Lidar: Southeastern Michigan (Hillsdale, Jackson, Lenawee Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Lake Erie LiDAR Priority Area 1 LiDAR Data Acquisition and Processing Production Task- Jackson, Hillsdale, and Lenawee Counties USGS Contract No....

  17. 2012 NRCS-USGS Tupelo, MS Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  18. 2008 Florida Division of Emergency Management Lidar: Middle Suwannee River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR Survey for the Suwannee River Water Management District (SRWMD), Florida. The LiDAR aerial acquisition was conducted in January of 2008, and the breaklines and...

  19. 2015 Oregon Department Forestry Lidar DEM: Northwest OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GeoTerra, Inc. was selected by Oregon Department of Forestry to provide Lidar remote sensing data including LAZ files of the classified Lidar points and surface...

  20. Theory of CW lidar aerosol backscatter measurements and development of a 2.1 microns solid-state pulsed laser radar for aerosol backscatter profiling

    Science.gov (United States)

    Kavaya, Michael J.; Henderson, Sammy W.; Frehlich, R. G.

    1991-01-01

    The performance and calibration of a focused, continuous wave, coherent detection CO2 lidar operated for the measurement of atmospheric backscatter coefficient, B(m), was examined. This instrument functions by transmitting infrared (10 micron) light into the atmosphere and collecting the light which is scattered in the rearward direction. Two distinct modes of operation were considered. In volume mode, the scattered light energy from many aerosols is detected simultaneously, whereas in the single particle mode (SPM), the scattered light energy from a single aerosol is detected. The analysis considered possible sources of error for each of these two cases, and also considered the conditions where each technique would have superior performance. The analysis showed that, within reasonable assumptions, the value of B(m) could be accurately measured by either the VM or the SPM method. The understanding of the theory developed during the analysis was also applied to a pulsed CO2 lidar. Preliminary results of field testing of a solid state 2 micron lidar using a CW oscillator is included.

  1. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Quinault River Watershed, Washington (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on the Quinault watershed survey area for the Puget Sound LiDAR Consortium. This...

  2. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Cedar River Watershed (Delivery 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In September 2013, WSI, a Quantum Spatial company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  3. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Cedar River Watershed (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In September 2013, WSI, a Quantum Spatial company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  4. Wind Profiling Radar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Clutter present in radar return signals as used for wind profiling is substantially removed by carrying out a Daubechies wavelet transformation on a time series of...

  5. 2013-2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (New York City)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS New York CMGP Sandy Lidar 0.7 Meter NPS LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No....

  6. Integrated Monitoring of the Soya Warm Current Using HF Ocean Radars, Satellite Altimeters, Coastal Tide Gauges, and a Bottom-Mounted ADCP

    Science.gov (United States)

    Ebuchi, N.; Fukamachi, Y.; Ohshima, K. I.; Wakatsuchi, M.

    2007-12-01

    The Soya Warm Current (SWC) is a coastal boundary current, which flows along the coast of Hokkaido in the Sea of Okhotsk. The SWC flows into the Sea of Okhotsk from the Sea of Japan through the Soya/La Perouse Strait, which is located between Hokkaido, Japan, and Sakhalin, Russia. It supplies warm, saline water in the Sea of Japan to the Sea of Okhotsk and largely affects the ocean circulation and water mass formation in the Sea of Okhotsk, and local climate, environment and fishery in the region. However, the SWC has never been continuously monitored due to the difficulties involved in field observations related to, for example, severe weather conditions in the winter, political issues at the border strait, and conflicts with fishing activities in the strait. Detailed features of the SWC and its variations have not yet been clarified. In order to monitor variations in the SWC, three HF ocean radar stations were installed around the strait. The radar covers a range of approximately 70 km from the coast. It is shown that the HF radars clearly capture seasonal and subinertial variations of the SWC. The velocity of the SWC reaches its maximum, approximately 1 m/s, in summer, and weakens in winter. The velocity core is located 20 to 30 km from the coast, and its width is approximately 50 km. The surface transport by the Soya Warm Current shows a significant correlation with the sea level difference along the strait, as derived from coastal tide gauge records. The cross-current sea level difference, which is estimated from the sea level anomalies observed by the Jason-1 altimeter and a coastal tide gauge, also exhibits variation in concert with the surface transport and along-current sea level difference.

  7. Spaceborne Lidar in the Study of Marine Systems.

    Science.gov (United States)

    Hostetler, Chris A; Behrenfeld, Michael J; Hu, Yongxiang; Hair, Johnathan W; Schulien, Jennifer A

    2018-01-03

    Satellite passive ocean color instruments have provided an unbroken ∼20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

  8. Spaceborne Lidar in the Study of Marine Systems

    Science.gov (United States)

    Hostetler, Chris A.; Behrenfeld, Michael J.; Hu, Yongxiang; Hair, Johnathan W.; Schulien, Jennifer A.

    2018-01-01

    Satellite passive ocean color instruments have provided an unbroken ˜20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

  9. Airborne lidar measurements of aerosol spatial distribution and optical properties over the Atlantic Ocean during a European pollution outbreak of ACE-2[Special issue with manuscripts related to the second Aerosol Characterization Experiment (ACE-2), 16 June-25 July 1997

    Energy Technology Data Exchange (ETDEWEB)

    Flamant, Cyrille; Pelon, Jaques; Trouillet, Vincent; Bruneau, Didier [CNRS-UPMC-UVSQ, Paris (France). Service d' Aeronomie; Chazette, Patrick; Leon, J.F. [CEA-CNRS, Gif-sur-Yvette (France). Lab. des Sciences du Climat et de l' Environment; Quinn, P.K.; Bates, T.S.; Johnson, James [National Oceanic and Atmospheric Administration, Seattle, WA (United States). Pacific Marine Environmental Lab.; Frouin, Robert [Scripps Inst. of Oceanography, La Jolla, CA (United States); Livingston, John [SRI International, Menlo Park, CA (United States)

    2000-04-01

    Airborne lidar measurements of the aerosol spatial distribution and optical properties associated with an European pollution outbreak which occurred during the Second Aerosol Characterization Experiment (ACE-2) are presented. Size distribution spectra measured over the ocean near Sagres (Portugal), on-board the Research Vessel Vodyanitsky and on-board the Avion de Recherche Atmospherique et Teledetection (ARAT) have been used to parameterize the aerosol vertical distribution. This parameterization, which is essential to the analysis of airborne lidar measurements, has been validated via closure experiments on extinction coefficient profiles and aerosol optical depth (AOD). During the studied event, AOD's retrieved from lidar measurements at 0.73 {mu}m range between 0.055 and 0.10. The parameterized aerosol vertical distribution has been used to shift AOD retrievals from 0.73 to 0.55 {mu}m to enable comparison with other remote sensing instruments. At the latter wavelength, AOD's retrieved from lidar measurements range between 0.08 and 0.14. An agreement better than 20% is obtained between AOD's derived from lidar and sunphotometer measurements made at the same time and place over the ocean near the coast. However, large differences are observed with the AOD estimated from Meteosat imagery in the same area. These differences are thought to be caused by large uncertainties associated with the Meteosat sensitivity for small AOD's or by the presence of thin scattered clouds. Lidar-derived particulate extinction profiles and scattering coefficient profiles measured by a nephelometer mounted on the ARAT, in a different part of the plume, were found in good agreement, which could be an indication that absorption by pollution aerosols is small and/or that soot is present in small amounts in the European pollution plume. Lidar measurements have also been used to differentiate the contribution of different aerosol layers to the total AOD. It is shown that

  10. LIDAR and atmosphere remote sensing

    CSIR Research Space (South Africa)

    Venkataraman, S

    2008-05-01

    Full Text Available using state of the art Light Detection And Ranging (LiDAR) instrumentation and other active and passive remote sensing tools. First “Lidar Field Campaign” • 2-day measurement campaign at University of Pretoria • First 23-hour continuous measurement... head2rightCirrus cloud morphology and dynamics. Atmospheric Research in Southern Africa and Indian Ocean (ARSAIO) Slide 24 © CSIR 2008 www.csir.co.za Middle atmosphere dynamics and thermal structure: comparative studies from...

  11. Hub Height Ocean Winds over the North Sea Observed by the NORSEWInD Lidar Array: Measuring Techniques, Quality Control and Data Management

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Stein, Detlef; Courtney, Michael

    2013-01-01

    performed excellently, two slightly failed the first criterion and one failed both. The lidars were operated offshore from six months to more than two years and observed in total 107 months of 10-min mean wind profile observations. Four lidars were re-evaluated post deployment with excellent results...

  12. Lidar: range-resolved optical remote sensing of the atmosphere

    National Research Council Canada - National Science Library

    Weitkamp, Claus; Walther, Herbert

    2005-01-01

    "Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection...

  13. 18th International Laser Radar Conference

    CERN Document Server

    Neuber, Roland; Rairoux, Patrick; Wandinger, Ulla

    1997-01-01

    Lidar or laser radar, the depth-resolved remote measurement of atmospheric parameters with optical means, has become an important tool in the field of atmospheric and environmental remote sensing. In this volume the latest progress in the development of lidar methods, experiments, and applications is described. The content is based on selected and thoroughly refereed papers presented at the 18th International Laser Radar Conference, Berlin, 22-26 July 1996. The book is divided into six parts which cover the topics of tropospheric aerosols and clouds, lidar in space, wind, water vapor, troposheric trace gases and plumes, and stratospheric and mesospheric profiling. As a supplement to fundamental lidar textbooks this volume may serve as a guide for scientists, engineers, and graduate students through the blossoming field of modern lidar techniques and their contribution to atmospheric and environmental research.

  14. 2013 NRCS-USGS Lidar: Lauderdale (MS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:NRCS LAUDERDALE MS 0.7M NPS LIDAR. LiDAR Data Acquisition and Processing Production Task. USGS Contract No. G10PC00057. Task Order No. G12PD000125 Woolpert...

  15. Saginaw Bay, MI LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:(NRCS) Saginaw Bay, MI LiDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G11PD01254 Woolpert Order...

  16. 2012 USGS Lidar: Elwha River (WA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Elwha River, WA LiDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G11PD01088 Woolpert Order No....

  17. 2006 South Carolina DNR Lidar: Aiken County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LiDAR data acquisition was executed in five sessions, on March 15, 16 & 17, 2006, using a Leica ALS50 LiDAR System. Specific details about the ALS50 system...

  18. 2014 USGS/NRCS Lidar: Central MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS-NRCS Laurel MS 0.7m NPS LIDAR Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD01086 Woolpert...

  19. NOAA NEXt-Generation RADar (NEXRAD) Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of Level III weather radar products collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska,...

  20. 2010 Northwestern Hawaiian Islands Lidar - Midway Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  1. 2010 Northwestern Hawaiian Islands Lidar - Laysan Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  2. 2012 OLC Lidar: West Metro, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon West Metro Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI)....

  3. 2012 OLC Lidar DEM: West Metro, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon West Metro Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI)....

  4. 2013 South Carolina DNR Lidar: Greenville County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Atlantic Group provided high accuracy, calibrated multiple return LiDAR for roughly 1,510 square miles covering both Greenville and Spartanburg counties, South...

  5. 2006 NOAA Bathymetric Lidar: Puerto Rico (Southwest)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set (Project Number OPR-I305-KRL-06) depicts depth values (mean 5 meter gridded) collected using LiDAR (Light Detection & Ranging) from the shoreline...

  6. USGS Atchafalaya 2 LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin project area. The entire survey area for Atchafalaya encompasses approximately...

  7. 2004 Harrison County, Mississippi Lidar Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the topographic mapping of Harrison County, Mississippi in March of 2004. Products generated include lidar point clouds in .LAS format...

  8. 2015 Cook & Tift County (GA) Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: NOAA OCM Tift and Cook Counties GA Lidar Data Acquisition and Processing Production Task NOAA Contract No. EA133C-11-CQ-0010 Woolpert Order No. 75271...

  9. 2010 ARRA Lidar: Golden Gate (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Golden Gate LiDAR Project is a cooperative project sponsored by the US Geological Survey (USGS) and San Francisco State University (SFSU) that has resulted in...

  10. 2012 USGS Lidar: Brooks Camp (AK)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) had a requirement for high resolution Lidar needed for mapping the Brooks Camp region of Katmai National Park in Alaska....

  11. 2005 Oahu/Maui Lidar Mapping Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

  12. 2004 USGS Lidar: San Francisco Bay (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

  13. 2010 ARRA Lidar: Eleven County Virginia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint and LMSI collected LiDAR for over 2,572 square miles in Northumberland, Lancaster, Middlesex, King and Queen, Matthews, Gloucester, James City,...

  14. 2012 South Carolina DNR Lidar: Edgefield County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,300 square miles in Calhoun, Aiken, Barnwell, Edgefield, McCormick, and Abbeville counties in South Carolina. This metadata...

  15. 2007 Sumpter Powder River Mine Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data for the USDA Forest Service on September 17, 2007. The project covers an 8-mile...

  16. 2009 - 2011 OLC Lidar DEM: Deschutes (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data of the Deschutes Study Area for the Oregon Department of Geology and Mineral Industries...

  17. 2008 USGS New Jersey Lidar: Somerset County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data support the general geospatial needs of the USGS and other federal agencies. LiDAR data is remotely sensed high-resolution elevation data collected by an...

  18. 2016 USGS Lidar: Maine QL2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Product: This lidar data set includes classified LAS files, breaklines, digital elevation models (DEMs), intensity imagery, and contours. Geographic Extent: Four...

  19. 2013 South Carolina DNR Lidar: Beaufort County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LMSI provided high accuracy, calibrated multiple return LiDAR for roughly 785 square miles covering Beaufort County, South Carolina. The nominal point spacing for...

  20. 2004 FEMA Lidar: Blackstone (MA & RI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LIDAR-derived data was collected in the Blackstone River area. This data supports the Federal Emergency Management Agency's specifications for mapping...

  1. 2011 USGS Lidar: Orange County (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR (Light Detection and Ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

  2. 2012 South Carolina DNR Lidar: Calhoun County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,300 square miles in Calhoun, Aiken, Barnwell, Edgefield, McCormick, and Abbeville counties in South Carolina. This metadata...

  3. 2011 FEMA Lidar: Southern Virginia Cities

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Dewberry collected LiDAR for ~3,341 square miles in various Virginia Counties, a part of Worcester County, and Hooper's Island. The acquisition was performed by...

  4. 2013 South Carolina DNR Lidar: Spartanburg County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Atlantic Group provided high accuracy, calibrated multiple return LiDAR for roughly 1,510 square miles covering both Greenville and Spartanburg counties, South...

  5. 2010 USGS Lidar: Salton Sea (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The USGS Salton Sea project encompasses a 5-kilometer buffer around the Salton Sea, California. Dewberry classified LiDAR for a project boundary that touches 623...

  6. 2014 USACE NCMP Topobathy Lidar DEM: Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping...

  7. 2010 South Carolina DNR Lidar: Sumter County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Sumter County, SC. Provide Bare Earth DEM (vegetation removal) of Sumter County, SC.

  8. 2010 South Carolina DNR Lidar: Richland County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Richland County, SC. Provide Bare Earth DEM (vegetation removal) of Richland County, SC.

  9. 2015 City of Portland, Maine, Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 2015 City of Portland Maine Lidar Data Acquisition and Processing Woolpert Order No. 75564 Contractor: Woolpert, Inc. This task is for a high resolution data set of...

  10. 2016 Martin County QL2 Lidar (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Martin County FL QL2 Lidar Acquisition and Processing Production Task Task Order No. G14PS00574 Woolpert Order No. 76001 Contractor: Woolpert, Inc. This task is for...

  11. 2009 - 2011 OLC Lidar: Deschutes (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data of the Deschutes Study Area for the Oregon Department of Geology and Mineral Industries...

  12. 2005 NCFMP Lidar: NC Statewide Phase 3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired March through April 2005. These data sets may represent a single geographic tile of a larger, county/sub-county data...

  13. 2015 NOAA Lidar: Pelekane Watershed (HI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata describes the Digital Elevation Model (DEM) 1 meter products derived from the airborne LiDAR data collected in August of 2015 for the Pelekane...

  14. 2006 FEMA Lidar: Rhode Island Coastline

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

  15. 2010 South Carolina DNR Lidar: Kershaw County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Kershaw County, SC. Provide Bare Earth DEM (vegetation removal) of Kershaw County, SC.

  16. 2010 Northwestern Hawaiian Islands Lidar - Kure Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  17. 2010 Northwestern Hawaiian Islands Lidar - Lisianki Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  18. 2003 NCFMP Lidar: NC Statewide Phase 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired January through March 2003. Point data (XYZ) in ASCII format. Horizontal datum NAD83(1995) North Carolina State Plane...

  19. A comparison of mixing depths observed by ground-based wind profilers and an airborne lidar

    Energy Technology Data Exchange (ETDEWEB)

    White, A.B.; Senff, C. [Univ. of Colorado/NOAA Environmental Technology Lab., Cooperative Inst. for Research in Environmental Sciences, Boulder, CO (United States); Banta, R.M. [NOAA Environmental Technology Lab., Boulder, CO (United States)

    1997-10-01

    The mixing depth is one of the most important parameters in air pollution studies because it determines the vertical extent of the `box` in which pollutants are mixed and dispersed. During the 1995 Southern Oxidants Study (SOS95), scientists from the National Oceanic and Atmospheric Administration Environmental Technology Laboratory (NOAA/ETL) deployed four 915-MHz boundary-layer radar/wind profilers (hereafter radars) in and around the Nashville, Tennessee metropolitan area. Scientists from NOAA/ETL also operated an ultraviolet differential absorption lidar (DIAL) onboard a CASA-212 aircraft. Profiles from radar and DIAL can be used to derive estimates of the mixing depth. The methods used for both instruments are similar in that they depend on information derived from the backscattered power. However, different scattering mechanisms for the radar and DIAL mean that different tracers of mixing depth are measured. In this paper we compare the mixing depth estimates obtained from the radar and DIAL and discuss the similarities and differences that occur. (au)

  20. 2012-2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Hoh River Watershed, Washington (Deliveries 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on the Hoh River watershed survey area for the Puget Sound LiDAR Consortium and the...

  1. Lidar to lidar calibration of Ground-based Lidar

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Courtney, Michael

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  2. High Resolution Ecosystem Structure, Biomass and Blue Carbon stocks in Mangrove Ecosystems- Methods and Applications of Lidar, radar Interferometry and High Resolution imagery

    Science.gov (United States)

    Lagomasino, D.; Fatoyinbo, T. E.; Lee, S. K.; Feliciano, E. A.; Simard, M.; Trettin, C.

    2016-12-01

    Earth's climate is determined by the exchange of radiant energy between the Sun, Earth and space. The absorbed solar radiation (ASR) fuels the climate system, providing the energy required for atmospheric and oceanic motions, while the system cools by emitting outgoing longwave (LW) radiation to space. A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget along with the associated atmospheric and surface properties that influence it. CERES data products utilize a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, polar orbiting and geostationary spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. Here we use simple diagnostic model of Earth's albedo and CERES Energy Balanced and Filled (EBAF) Ed4.0 data for March 2000-February 2016 to quantify interannual variations in SW TOA flux associated with surface albedo and atmospheric reflectance and transmittance variations. Surface albedo variations account for albedo and atmospheric reflectance/transmittance. Equatorward of 60-degree latitude, the atmospheric contribution exceeds that of the surface by at least an order-of-magnitude. In contrast, the surface and atmospheric variations contribute equally poleward of 60S and surface variations account for twice as much as the atmosphere poleward of 60N. However, as much as 40% of the total SW TOA flux variance poleward of 60N is explained by the covariance of surface albedo and atmospheric reflectance/transmittance, highlighting the tight coupling between sea-ice concentration and cloud properties over the Arctic Ocean.

  3. Combined analysis of the radar cross-section modulation due to the long ocean waves around 14° and 34° incidence: Implication for the hydrodynamic modulation

    Science.gov (United States)

    Hauser, DanièLe; Caudal, GéRard

    1996-11-01

    The analysis of synthetic aperture radar observations over the ocean to derive the directional spectra of the waves is based upon a complex transfer function which is the sum of three terms: tilt modulation, hydrodynamic modulation, and velocity bunching effect. Both the hydrodynamic and the velocity bunching terms are still poorly known. Here we focus on the hydrodynamic part of the transfer function, from an experimental point of view. In this paper a new method is proposed to estimate the hydrodynamic modulation. The approach consists in analyzing observations obtained with an airborne real-aperture radar (called RESSAC). This radar (C band, HH polarized, broad beam of 14° × 3°) was used during the SEMAPHORE experiment, in two different modes. From the first mode (incidence angles from 7° to 21°) the directional spectra of the long waves are deduced under the assumption that the hydrodynamic modulation can be neglected (small incidence angles) and validated against in situ measurements. From the second mode (incidence angle from 27° to 41°) the amplitude and phase of the hydrodynamic modulation are deduced by combining the measured signal modulation spectrum at a mean incidence angle of 34° and the directional wave spectrum obtained from the first mode. The results, obtained in four different wind-wave cases of the SEMAPHORE experiment, show that the modulus of the hydrodynamic modulation is larger than that of the tilt modulation. Furthermore, we find that the modulus of the hydrodynamic transfer function is several times larger (by a factor 2-12) than the theoretical value proposed in previous works and 1.5-2.5 larger than experimental values reported in recent papers. The phase of the hydrodynamic modulation is found to be close to zero for waves propagating at an angle from the wind direction and between -20° and -40° for waves propagating along the wind direction. This indicates a significant influence of the wind-wave angle on the phase of the

  4. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Big Wood, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Big Wood 2015 study area. This study area is located in...

  5. 2012 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Green Peter

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data of the Green Peter study area for the Oregon LiDAR Consortium (OLC) in Linn County, Oregon. The collection of...

  6. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Big Windy

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Big Windy 2015 study area. This study area is located near...

  7. 2016 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: McKenzie River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) McKenzie River study area. This study area is located near...

  8. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Upper Rogue 3DEP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Upper Rogue 2015 study area. The collection of high...

  9. 2014 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Crooked Ochoco

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI, a Quantum Spatial company, has collected lidar data for the Oregon LiDAR Consortium (OLC) Crooked Ochoco study area. This study area is adjacent to the Ochoco...

  10. 2013 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Scappoose

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Scappoose study area. The Scappoose project area encompasses...

  11. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Upper Umpqua

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — QSI has completed the acquisition and processing of Light Detection and Ranging (LiDAR) data describing the Oregon LiDAR Consortium's (OLC) Umpqua Study Area. The...

  12. 2013 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Clackamol

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Clackamol 2013 study area in Clackamas and Marion County, Oregon. The...

  13. 2013 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar DEM: Scappoose

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Scappoose study area. The Scappoose project area encompasses...

  14. 2013 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar DEM: Clackamol

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Clackamol 2013 study area in Clackamas and Marion County, Oregon. The...

  15. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Green Peter

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data of the Green Peter study area for the Oregon LiDAR Consortium (OLC) in Linn County, Oregon. The collection of...

  16. 2015 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar DEM: Upper Rogue 3DEP

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Upper Rogue 2015 study area. The collection of high...

  17. 2016 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar DEM: McKenzie River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) McKenzie River study area. This study area is located near...

  18. 2004 Federal Emergency Management Agency (FEMA) Bare Earth Topographic LiDAR: Connecticut River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. The LiDAR files were converted from .PTS format to LAS...

  19. Bayfield Co. QL2 LiDAR (2015-16) - DEM

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Bayfield County lidar project area covers approximately 1681 square miles plus a 100 meter buffer around the county boundary. The lidar data was acquired at a...

  20. Bayfield Co. QL2 LiDAR (2015-16) - Classified Point Cloud

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Bayfield County lidar project area covers approximately 1681 square miles plus a 100 meter buffer around the county boundary. The lidar data was acquired at a...

  1. Manitowoc Co. QL2 LiDAR (2015-16) - Classified Point Cloud

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Manitowoc County lidar project area covers approximately 602 square miles plus a 100 meter buffer around the county boundary. The lidar data was acquired at a...

  2. 2007 US Army Corps of Engineers (USACE), Jacksonville District US Virgin Islands LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) bare-earth classified LAS dataset is a topographic survey conducted for the USACE USVI LiDAR Project. These data were...

  3. 2009 - 2011 CA Coastal Conservancy Coastal Lidar Project: Hydro-flattened Bare Earth DEM

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  4. Manitowoc Co. QL2 LiDAR (2015-16) - DEM

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Manitowoc County lidar project area covers approximately 602 square miles plus a 100 meter buffer around the county boundary. The lidar data was acquired at a...

  5. 2011 U.S. Geological Survey (USGS) Topographic LiDAR: Louisiana Region 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Louisiana Region 1 LiDAR ARRA Task Order LiDAR Data Acquisition and Processing Production Task- Vermillion, Iberia, St. Mary, Terrebonne, and Lafourche...

  6. 2010 US Army Corps of Engineers (USACE) Portland District Columbia River Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Columbia River Light Detection and Ranging (LiDAR) survey project was a collaborative effort to develop detailed high density LiDAR terrain data for the US Army...

  7. 2016 USACE NCMP Topobathy Lidar DEM: Stamp Sands, Lake Superior (MI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain rasterized, bare earth topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping and Imaging Lidar...

  8. 2011 U.S. Geological Survey (USGS) Topographic LiDAR: Louisiana Region 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Louisiana Region 2 LiDAR ARRA Task Order LiDAR Data Acquisition and Processing Production Task- Orleans, Plaquemines, St. Bernard, St. Tammany Parishes,...

  9. LIDAR and atmosphere remote sensing [DST Space Science Initiatives

    CSIR Research Space (South Africa)

    Venkataraman, S

    2009-04-01

    Full Text Available Energy Source included in the measurement. Slide 2 © CSIR 2008 www.csir.co.za The observer can control the source Eg. Radar, Lidar, Sodar, Sonar etc. (b) Passive remote sensors. Energy source is not included in the measurement... Instrument Passive Slide 3 © CSIR 2008 www.csir.co.za Active LiDAR Principle • LIDAR (Light Detection and Ranging) • LiDAR employs a laser as a source of pulsed energy • Lasers are advantageous because – checkbld Monochromatic...

  10. 2000 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Kitsap Peninsula, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 1,146 square miles and covers part...

  11. 2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Snohomish County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 167 square miles and covers a...

  12. 2011 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Rattlesnake

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data on six days between September 15th and November 5th, and from November 6th - 13th,...

  13. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: North Puget Sound Lowlands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data contributing to the Puget Sound Lowlands project of 2005. Arlington, City of Snohomish, Snohomish...

  14. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lower Columbia River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint, on behalf of multiple agencies, collected topographic lidar of the Lower Columbia River area. Field data collection took place between the dates of...

  15. 2003 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 100 square miles and covers part of...

  16. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Nooksack

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In July 2012, WSI (Watershed Sciences, Inc.) was contracted by the Puget Sound LiDARConsortium (PSLC) to collect Light Detection and Ranging (LiDAR) data on a...

  17. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data for the Lewis County project of 2005. The project site covered approximately 223 square miles, divided...

  18. 2005 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Olympic Peninsula

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected Light Detection and Ranging (LiDAR) data for the Olympic Peninsula project of 2005, totaling approximately 114.59 sq mi: 24.5 for Clallam...

  19. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Upper Naches River, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Upper Naches River Valley and Nile Slide area of interest on September 30th,...

  20. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Entiat

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2012, WSI (Watershed Sciences, Inc.) was contracted by the Puget Sound LiDARConsortium (PSLC) to collect Light Detection and Ranging (LiDAR) data for the...

  1. Lidar to lidar calibration phase 2

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents the results from phase 2 of a lidar to lidar (L2L) calibration procedure. Phase two of the project included two measurement campaigns conducted at given sites. The purpose was to find out if the lidar-to-lidar calibration procedure can be conducted with similar results...

  2. Nonlinear filtering for LIDAR signal processing

    Directory of Open Access Journals (Sweden)

    D. G. Lainiotis

    1996-01-01

    Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.

  3. Synthetic aperture radar capabilities in development

    Energy Technology Data Exchange (ETDEWEB)

    Miller, M. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    The Imaging and Detection Program (IDP) within the Laser Program is currently developing an X-band Synthetic Aperture Radar (SAR) to support the Joint US/UK Radar Ocean Imaging Program. The radar system will be mounted in the program`s Airborne Experimental Test-Bed (AETB), where the initial mission is to image ocean surfaces and better understand the physics of low grazing angle backscatter. The Synthetic Aperture Radar presentation will discuss its overall functionality and a brief discussion on the AETB`s capabilities. Vital subsystems including radar, computer, navigation, antenna stabilization, and SAR focusing algorithms will be examined in more detail.

  4. Lidar to lidar calibration phase 1

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents a feasibility study of a lidar to lidar (L2L) calibration procedure. Phase one of the project was conducted at Høvsøre, Denmark. Two windcubes were placed next to the 116m met mast and different methods were applied to obtain the sensing height error of the lidars. The purpose...... is to find the most consistent method and use it in a potential lidar to lidar calibration procedure....

  5. Synoptic measurements of subsurface phytoplankton layers collected from Fish Lidar, Oceanic, Experimenta (FLOE) Light Detection and Ranging (LIDAR) from aircraft in Chukchi Sea and Beaufort Sea from 2014-07-17 to 2014-07-29 (NCEI Accession 0128217)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In July 2014, FLOE was installed in a NOAA Twin Otter to make the first synoptic measurements of subsurface phytoplankton layers associated with the retreating ice...

  6. Quantum radar

    CERN Document Server

    Lanzagorta, Marco

    2011-01-01

    This book offers a concise review of quantum radar theory. Our approach is pedagogical, making emphasis on the physics behind the operation of a hypothetical quantum radar. We concentrate our discussion on the two major models proposed to date: interferometric quantum radar and quantum illumination. In addition, this book offers some new results, including an analytical study of quantum interferometry in the X-band radar region with a variety of atmospheric conditions, a derivation of a quantum radar equation, and a discussion of quantum radar jamming.This book assumes the reader is familiar w

  7. Tenth Biennial Coherent Laser Radar Technology and Applications Conference

    Science.gov (United States)

    Kavaya, Michael J. (Compiler)

    1999-01-01

    The tenth conference on coherent laser radar technology and applications is the latest in a series beginning in 1980 which provides a forum for exchange of information on recent events current status, and future directions of coherent laser radar (or lidar or lader) technology and applications. This conference emphasizes the latest advancement in the coherent laser radar field, including theory, modeling, components, systems, instrumentation, measurements, calibration, data processing techniques, operational uses, and comparisons with other remote sensing technologies.

  8. 2012 NOAA American Samoa Lidar: Islands of Tutuila, Aunu'u, Ofu, Olosega, Ta'u and Rose Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  9. Operational Bright-Band Snow Level Detection Using Doppler Radar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A method to detect the bright-band snow level from radar reflectivity and Doppler vertical velocity data collection with an atmospheric profiling Doppler radar. The...

  10. NOAA Next Generation Radar (NEXRAD) Level 2 Base Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of Level II weather radar data collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii,...

  11. Stellwagen Bank National Marine Sanctuary - Synthetic Aperture Radar (SAR) Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geodatabase contains Synthetic Aperture Radar images (SAR), which consist of a fine resolution (12.5-50m), two-dimensional radar backscatter map of the...

  12. NOAA Next Generation Radar (NEXRAD) Level 3 Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of Level 3 weather radar products collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska,...

  13. 2015 USGS Lidar DEM: 3DEP Co-Op South Central MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Mississippi Coastal QL2 Lidar with 3DEP Extension Lidar 0.7m NPS Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No....

  14. 2015 USGS Lidar: 3DEP Co-Op South Central MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Mississippi Coastal QL2 Lidar with 3DEP Extension Lidar 0.7m NPS Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No....

  15. High Frequency Radar Locations in the United States as of February 2016.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset show the point locations of High Frequency (HF) radar systems across the US. HF radars measure the speed and direction of ocean surface currents in near...

  16. 2013 Suwannee River Water Management District Lidar: Greenville (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G12PD00242 1.0 Meter LiDAR Survey Area 3, Classified Point Cloud, in north-central...

  17. 2014 Suwannee River Water Management District Lidar: Cooks Hammock (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G14PD00206 0.7 Meter LiDAR Survey in central Florida and encompasses 571 square...

  18. 2013 Suwannee River Water Management District Lidar: Bell (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 4, Classified Point Cloud, in north-central...

  19. 2013 Suwannee River Water Management District Lidar: Mayo (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G12PD00242 1.0 Meter LiDAR Survey Area 4, Classified Point Cloud, in north-central...

  20. 2006 OSIP OGRIP: Upland Counties LiDAR Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The 2006 OSIP digital LiDAR data was collected during the months of March and May (leaf-off conditions). The LiDAR covers the entire land area of the northern tier...

  1. 2013 USGS-NRCS Lidar: Maine (Cumberland, Kennebec and York)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: NRCS Maine 0.7M NPS LIDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00954 Woolpert Order No....

  2. Dickinson County, MI LIDAR_LAS_1.2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:(NRCS) Dickinson County, MI LIDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G12PD00721 Woolpert...

  3. 2013 Suwannee River Water Management District Lidar: Obrien (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 1, Classified Point Cloud, in north-central...

  4. 2013 Suwannee River Water Management District (SRWMD) Lidar: Ichetucknee (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G12PD00242 1.0 Meter LiDAR Survey area 2 in north-central Florida and encompasses...

  5. Suwannee River Water Management District Lidar: Falmouth (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G12PD00242 1.0 Meter LiDAR Survey area 5 in north-central Florida and encompasses...

  6. Radar Fundamentals, Presentation

    OpenAIRE

    Jenn, David

    2008-01-01

    Topics include: introduction, radar functions, antennas basics, radar range equation, system parameters, electromagnetic waves, scattering mechanisms, radar cross section and stealth, and sample radar systems.

  7. Sea clutter scattering, the K distribution and radar performance

    CERN Document Server

    Ward, Keith; Watts, Simon

    2013-01-01

    Sea Clutter: Scattering, the K Distribution and Radar Performance, 2nd Edition gives an authoritative account of our current understanding of radar sea clutter. Topics covered include the characteristics of radar sea clutter, modelling radar scattering by the ocean surface, statistical models of sea clutter, the simulation of clutter and other random processes, detection of small targets in sea clutter, imaging ocean surface features, radar detection performance calculations, CFAR detection, and the specification and measurement of radar performance. The calculation of the performance of pract

  8. Lidar data for the community of Golovin, Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This publication presents lidar data collected over the community of Golovin, on the southern coast of the Seward Peninsula in western Alaska (fig. 1). The original...

  9. 2006 Texas Water Development Board (TWDB) Lidar: Brazoria County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

  10. 2009 PSLC-USGS Topographic LiDAR: Wenatchee

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data of the Wenatchee USGS area of interest (AOI) east of Wenatchee, WA on May 1nd - May...

  11. North Carolina Statewide Lidar DEM 2014 Phase 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest for Sandy, covering approximately 9,396 square miles. Dataset Description: The North Carolina - Sandy LiDAR...

  12. 2011 FEMA Lidar: Chemung Watershed (NY) (AOI 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data was acquired by Tuck Mapping Solutions, Inc. (TMSI) for the Chemung Watershed and broken down into two AOIs based on the level of processing performed on...

  13. 2007 FEMA New Jersey Flood Mitigation Lidar: Gloucester County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

  14. 2004 ENSR Bare Earth Topographic Lidar: Hampden County, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Spectrum Mapping was tasked by ENSR International (now a subsidiary of AECOM Technology Corporation) to collect LIDAR data and digital ortho imagery to generate...

  15. 2010 ARRA Lidar: California Coastal Project (Zone 4)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  16. 2013 USACE Topographic Lidar: Rio Puerto Nuevo (PR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data. The NAD83/2011 geodetic products were delivered as individual LAS files...

  17. High Power, Thermally Optimized Blue Laser for Lidar, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — To enable widespread and rapid airborne bathymetric lidar to adequate depths in many ocean regions a low-cost, rugged, and high energy pulsed laser source must be...

  18. High Power, Thermally Optimized Blue Laser for Lidar, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — To enable widespread and rapid airborne bathymetric lidar to adequate depths in many ocean regions a low-cost, rugged, and high energy pulsed laser source must be...

  19. 2005 Southwest Florida Water Management District (SWFWMD) Lidar: Manatee District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  20. 2014 NCFMP Lidar: Statewide North Carolina (Phase 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest for Sandy, covering approximately 9,396 square miles. Dataset Description: The North Carolina - Sandy LiDAR...

  1. 2012 USGS-FEMA Lidar: Virginia Northern Counties (North)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Dewberry collected LiDAR for ~3,341 square miles in various Virginia Counties, a part of Worcester County, and Hoopers Island. The acquisition was performed by...

  2. 2015 USACE NCMP Topobathy Lidar DEM: Avalon (NJ)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping...

  3. 2010 ARRA Lidar: California Coastal Project (Zone 3)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  4. 2006 Federal Emergency Management Agency (FEMA) Lidar: Nueces County, Texas

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Spectrum Mapping, LLC was tasked by MAPVI - URS Corporation, Albuquergue, to provide airborne Light Detection and Ranging (Lidar) of approximately 620 square miles...

  5. 2006 FEMA New Jersey Flood Mitigation Lidar: Middlesex County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

  6. 2011 MDEQ Tennessee-Tombigbee Waterway Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collect and deliver high-density elevation point data derived from multiple-return light detection and ranging (LiDAR) measurements for use in supporting topographic...

  7. 2013 USACE NCMP Topobathy Lidar DEM: Niihau (HI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping...

  8. 2012 USACE Topobathy Lidar: Post Sandy (NJ & NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1) and valid topographic data classified as ground (2),...

  9. 2004 FEMA Lidar: Portions of Burlington and Camden Counties (NJ)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In early October 2004, LIDAR was flown for Burlington and Camden Counties. The acquisition is being sponsored FEMA because of the July flood. It will be delivered to...

  10. North Carolina Statewide Lidar DEM 2015 Phase 3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest, covering approximately 7,197 square miles. Dataset Description: The North Carolina LiDAR project called for the...

  11. 2016 Martin County QL2 Lidar DEM (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Martin County FL QL2 Lidar Acquisition and Processing Production Task Task Order No. G14PS00574 Woolpert Order No. 76001 Contractor: Woolpert, Inc. This task is for...

  12. 2015 USACE NCMP Topobathy Lidar DEM: Sand Island (WA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping...

  13. 2016 USACE NCMP Topobathy Lidar DEM: Gulf Coast (TX)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These bare earth Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 meter grid size, generated from data collected by the...

  14. 2006 Texas Water Development Board (TWDB) Lidar: Orange County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, 43 flight lines of standard density (1.4 meter ground sample distance) data were collected over...

  15. 2015 USACE NCMP Topobathy Lidar DEM: Egmont Key (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These 1 m gridded bare earth Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations generated from data collected by the Coastal Zone...

  16. 2007 Northwest Florida Water Management District (NWFWMD) Lidar: Holmes County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR-derived binary (.las) files containing points classified as bare-earth and canopy (first return) were produced for the 2007/2008 Northwest Florida Water...

  17. 2015 NCFMP Lidar: Statewide North Carolina (Phase 3)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest, covering approximately 7,197 square miles. Dataset Description: The North Carolina LiDAR project called for the...

  18. 2006 Texas Water Development Board (TWDB) Lidar: Galveston County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

  19. 2015 NRCS-MDEQ Lidar: Southeast Mississippi QL2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This report contains a comprehensive outline of the Mississippi QL2 and Tupelo QL3 Lidar Processing task order for the United States Geological Survey (USGS). This...

  20. 2005 Alaska Division of Geological & Geophysical Surveys Lidar: Unalakleet, Alaska

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This report is a summary of a LiDAR data collection over the community of Unalakleet, in the Norton Sound region of Alaska. The original data were collected on...

  1. 2006 Southwest Florida Water Management District (SWFWMD) Lidar: North District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is one component of a digital terrain model (DTM) for the Southwest Florida Water Management District's FY2006 Digital Orthophoto (B089) and LiDAR...

  2. 2006 Texas Water Development Board (TWDB) Lidar: Jackson County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

  3. Radar equations for modern radar

    CERN Document Server

    Barton, David K

    2012-01-01

    Based on the classic Radar Range-Performance Analysis from 1980, this practical volume extends that work to ensure applicability of radar equations to the design and analysis of modern radars. This unique book helps you identify what information on the radar and its environment is needed to predict detection range. Moreover, it provides equations and data to improve the accuracy of range calculations. You find detailed information on propagation effects, methods of range calculation in environments that include clutter, jamming and thermal noise, as well as loss factors that reduce radar perfo

  4. 2006 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Eastern Washington and River Corridors

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data in eastern Washington, eastern Oregon, and southern Canada in October and November,...

  5. 2008 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: North Carolina

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain topographic lidar data collected by the Compact Hydrographic Airborne Rapid Total Survey (CHARTS) system along the coast of North Carolina near...

  6. 2012 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Chehalis River Watershed Area, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Chehalis River Watershed study area on January 28th, February 2nd-7th,...

  7. 2002 Puget Sound LiDAR Consortium (PSLC) Unclassified Topographic LiDAR: Puget Sound Lowlands Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TerraPoint surveyed and created this data for the Puget Sound LiDAR Consortium under contract. The area surveyed is approximately 730 square miles and covers the...

  8. OW ASCAT Ocean Surface Winds

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Advanced Scatterometer (ASCAT) sensor onboard the EUMETSAT MetOp polar-orbiting satellite provides ocean surface wind observations by means of radar...

  9. 2014 NOAA Post-Sandy Topobathymetric Lidar: Void DEMs Rhode Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These lidar data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The...

  10. Social Radar

    Science.gov (United States)

    2012-01-01

    RTA HFM-201/RSM PAPER 3 - 1 © 2012 The MITRE Corporation. All Rights Reserved. Social Radar Barry Costa and John Boiney MITRE Corporation...defenders require an integrated set of capabilities that we refer to as a “ social radar.” Such a system would support strategic- to operational-level...situation awareness, alerting, course of action analysis, and measures of effectiveness for each action undertaken. Success of a social radar

  11. Planetary Radar

    Science.gov (United States)

    Neish, Catherine D.; Carter, Lynn M.

    2015-01-01

    This chapter describes the principles of planetary radar, and the primary scientific discoveries that have been made using this technique. The chapter starts by describing the different types of radar systems and how they are used to acquire images and accurate topography of planetary surfaces and probe their subsurface structure. It then explains how these products can be used to understand the properties of the target being investigated. Several examples of discoveries made with planetary radar are then summarized, covering solar system objects from Mercury to Saturn. Finally, opportunities for future discoveries in planetary radar are outlined and discussed.

  12. Underwater lidar system: design challenges and application in pollution detection

    Science.gov (United States)

    Gupta, Pradip; Sankolli, Swati; Chakraborty, A.

    2016-05-01

    The present remote sensing techniques have imposed limitations in the applications of LIDAR Technology. The fundamental sampling inadequacy of the remote sensing data obtained from satellites is that they cannot resolve in the third spatial dimension, the vertical. This limits our possibilities of measuring any vertical variability in the water column. Also the interaction between the physical and biological process in the oceans and their effects at subsequent depths cannot be modeled with present techniques. The idea behind this paper is to introduce underwater LIDAR measurement system by using a LIDAR mounted on an Autonomous Underwater Vehicle (AUV). The paper introduces working principles and design parameters for the LIDAR mounted AUV (AUV-LIDAR). Among several applications the papers discusses the possible use and advantages of AUV-LIDAR in water pollution detection through profiling of Dissolved Organic Matter (DOM) in water bodies.

  13. Combining millimeter-wave radar and communication paradigms for automotive applications : a signal processing approach.

    Science.gov (United States)

    2016-05-01

    As driving becomes more automated, vehicles are being equipped with more sensors generating even higher data rates. Radars (RAdio Detection and Ranging) are used for object detection, visual cameras as virtual mirrors, and LIDARs (LIght Detection and...

  14. Results from the search-lidar demonstrator project for detection of small Sea-Surface targets

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Putten, F.J.M. van; Cohen, L.H.; Kemp, R.A.W.; Franssen, G.C.

    2009-01-01

    Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC's, and speedboats. Previous lidar

  15. Search-Lidar Demonstrator for Detection of Small Sea-Surface Targets

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M. van; Cohen, L.H.; Schleijpen, H.M.A.

    2008-01-01

    Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC’s, and speedboats. Lidar

  16. 2008 FEMA Lidar: South Oneida County (NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — For Oneida County, NY, there were two types of elevation datasets. The first type is LiDAR and the second one is Auto-correlation DEM. Auto-correlation DEM data was...

  17. 2009 USGS Potato Creek Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR collected for the upper portion of the Flint River in central georgia. 237.6 sqmiles collected between May 1st and May 4th, 2009. The data contains 1 meter...

  18. Assessing LiDAR elevation data for KDOT applications.

    Science.gov (United States)

    2013-02-01

    LiDAR-based elevation surveys are a cost-effective means for mapping topography over large areas. LiDAR : surveys use an airplane-mounted or ground-based laser radar unit to scan terrain. Post-processing techniques are : applied to remove vegetation ...

  19. Wind energy applications of synthetic aperture radar

    DEFF Research Database (Denmark)

    Badger, Merete

    Synthetic aperture radars (SAR), mounted on satellites or aircraft, have proven useful for ocean wind mapping. Wind speeds at the height 10 m may be retrieved from measurements of radar backscatter using empirical model functions. The resulting windfields are valuable in offshore wind energy plan...

  20. Study on the influence of attitude angle on lidar wind measurement results

    Science.gov (United States)

    Han, Xiaochen; Dou, Peilin; Xue, Yangyang

    2017-11-01

    When carrying on wind profile measurement of offshore wind farm by shipborne Doppler lidar technique, the ship platform often produces motion response under the action of ocean environment load. In order to measure the performance of shipborne lidar, this paper takes two lidar wind measurement results as the research object, simulating the attitude of the ship in the ocean through the three degree of freedom platform, carrying on the synchronous observation test of the wind profile, giving an example of comparing the wind measurement data of two lidars, and carrying out the linear regression statistical analysis for all the experimental correlation data. The results show that the attitude angle will affect the precision of the lidar, The influence of attitude angle on the accuracy of lidar is uncertain. It is of great significance to the application of shipborne Doppler lidar wind measurement technology in the application of wind resources assessment in offshore wind power projects.

  1. 2011 - 2012 New York State Department of Environmental Conservation (NYSDEC) Lidar: Coastal New York (Long Island and along the Hudson River)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  2. LIDAR Research & Development Lab

    Data.gov (United States)

    Federal Laboratory Consortium — The LIDAR Research and Development labs are used to investigate and improve LIDAR components such as laser sources, optical signal detectors and optical filters. The...

  3. Significant wave height retrieval from synthetic radar images

    NARCIS (Netherlands)

    Wijaya, Andreas Parama; van Groesen, Embrecht W.C.

    2014-01-01

    In many offshore activities radar imagery is used to observe and predict ocean waves. An important issue in analyzing the radar images is to resolve the significant wave height. Different from 3DFFT methods that use an estimate related to the square root of the signal-to-noise ratio of radar images,

  4. The RITMARE Ocean Observing System for the Italian Seas

    Science.gov (United States)

    Crise, A.

    2016-02-01

    Among its objectives, the Italian RITMARE Flagship Programme has the aim to produce a prototype of the RITMARE Ocean observing system explicitelly designed to provide a powerful infrastructure to the Italian marine science community, to help implement national and Europen environmental regulations and to contribute to the future European Ocean Observing System. The projects takes advantage of the existing platforms (fixed-point moorings, HF and X-band radars, gliders, satellite products), that constitute the basic components of the system. The structure of the RITMARE Ocean observing system is composed by a permanent component (mooring network, satellite images, HF radars) and relocatable component (gliders, drifters, relocatable infrastructures). The increasing number of available relocatable/expandable platforms allow a much larger flexibility in term of allocation of observations but requires an sampling strategy the can be modified according the scientific and socio-economic priorities. As an example, RITMARE focus is set on an experiment on the South Adriatic Pit convective area and its dynamic interactions with the adjacent Bari Canyon cascading site. (Central Mediterranean Sea). Additional effort is paid to support innovation for sensors (e.g. ship-borne LIDAR, stereo-optic directional wave detection, X-band radar innovative products), operational employment of gliders (e.g. Wave Glider) and new class of operational models. The integration can be obtained at different level: the is expected to be achieved at ICT level by defining standard interfaces (NedCDF, SOS) and catalogs in order to facilitate the discovery, viewing and downloading services of data and products. The implementation of a distributed platform-oriented RT repositories adopt a number of THREDDS web servers that act as endpoints for the RITMARE portal. The final aim is to decouple the platforms from the observations, moving from a set of observation to a suite of Essential Ocean Variables by

  5. Linking sardine recruitment in coastal areas to ocean currents using surface drifters and HF radar. A case study in the Gulf of Manfredonia, Adriatic Sea

    DEFF Research Database (Denmark)

    Sciascia, Roberta; Berta, Maristella; Carlson, Daniel Frazier

    2017-01-01

    Understanding the role of ocean currents in the recruitment of commercially and ecologically important fish is an important step towards developing sustainable resource management guidelines. To this end, we attempt to elucidate the role of surface ocean transport in supplying recruits of sardine...

  6. Study on analysis from sources of error for Airborne LIDAR

    Science.gov (United States)

    Ren, H. C.; Yan, Q.; Liu, Z. J.; Zuo, Z. Q.; Xu, Q. Q.; Li, F. F.; Song, C.

    2016-11-01

    With the advancement of Aerial Photogrammetry, it appears that to obtain geo-spatial information of high spatial and temporal resolution provides a new technical means for Airborne LIDAR measurement techniques, with unique advantages and broad application prospects. Airborne LIDAR is increasingly becoming a new kind of space for earth observation technology, which is mounted by launching platform for aviation, accepting laser pulses to get high-precision, high-density three-dimensional coordinate point cloud data and intensity information. In this paper, we briefly demonstrates Airborne laser radar systems, and that some errors about Airborne LIDAR data sources are analyzed in detail, so the corresponding methods is put forwarded to avoid or eliminate it. Taking into account the practical application of engineering, some recommendations were developed for these designs, which has crucial theoretical and practical significance in Airborne LIDAR data processing fields.

  7. Lidar calibration experiments

    DEFF Research Database (Denmark)

    Ejsing Jørgensen, Hans; Mikkelsen, T.; Streicher, J.

    1997-01-01

    detection to test the reproducibility and uncertainty of lidars. Lidar data were obtained from both single-ended and double-ended Lidar configurations. A backstop was introduced in one of the experiments and a new method was developed where information obtained from the backstop can be used in the inversion...... algorithm. Independent in-situ aerosol plume concentrations were obtained from a simultaneous tracer gas experiment with SF6, and comparisons with the two lidars were made. The study shows that the reproducibility of the lidars is within 15%, including measurements from both sides of a plume...

  8. 2005 Mississippi Merged LiDAR Data (2005 LiDAR data merged with 2005 Post-Katrina LiDAR data to create a bare-earth product for flood plain mapping in coastal Mississippi).

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Pre- and post-hurricane Katrina LiDAR datasets of Hancock, Harrison, and Jackson Counties, MS, were merged into a seamless coverage by URS. The pre-Katrina LiDAR...

  9. Sixteenth International Laser Radar Conference, Part 1

    International Nuclear Information System (INIS)

    Mccormick, M.P.

    1992-07-01

    This publication contains extended abstracts of papers presented at the 16th International Laser Radar Conference. One-hundred ninety-five papers were presented in both oral and poster sessions. The topics of the conference sessions were: (1) Mt. Pinatubo Volcanic Dust Layer Observations; (2) Global Change/Ozone Measurements; (3) GLOBE/LAWS/LITE; (4) Mesospheric Measurements and Measurement Systems; (5) Middle Atmosphere; (6) Wind Measurements and Measurement Systems; (7) Imaging and Ranging; (8) Water Vapor Measurements; (9) Systems and Facilities; and (10) Laser Devices and Technology. This conference reflects the breadth of research activities being conducted in the lidar field. These abstracts address subjects from lidar-based atmospheric investigations relating to global change to the development of new lidar systems and technology

  10. 2004 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Portland, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The all returns ASCII files contain the X,Y,Z values of all the LiDAR returns collected during the survey mission. In addition each return also has a time stamp,...

  11. Optical Backscattering Measured by Airborne Lidar and Underwater Glider

    Directory of Open Access Journals (Sweden)

    James H. Churnside

    2017-04-01

    Full Text Available The optical backscattering from particles in the ocean is an important quantity that has been measured by remote sensing techniques and in situ instruments. In this paper, we compare estimates of this quantity from airborne lidar with those from an in situ instrument on an underwater glider. Both of these technologies allow much denser sampling of backscatter profiles than traditional ship surveys. We found a moderate correlation (R = 0.28, p < 10−5, with differences that are partially explained by spatial and temporal sampling mismatches, variability in particle composition, and lidar retrieval errors. The data suggest that there are two different regimes with different scattering properties. For backscattering coefficients below about 0.001 m−1, the lidar values were generally greater than the glider values. For larger values, the lidar was generally lower than the glider. Overall, the results are promising and suggest that airborne lidar and gliders provide comparable and complementary information on optical particulate backscattering.

  12. Weather Radar Stations

    Data.gov (United States)

    Department of Homeland Security — These data represent Next-Generation Radar (NEXRAD) and Terminal Doppler Weather Radar (TDWR) weather radar stations within the US. The NEXRAD radar stations are...

  13. A Wing Pod-based Millimeter Wave Cloud Radar on HIAPER

    Science.gov (United States)

    Vivekanandan, Jothiram; Tsai, Peisang; Ellis, Scott; Loew, Eric; Lee, Wen-Chau; Emmett, Joanthan

    2014-05-01

    One of the attractive features of a millimeter wave radar system is its ability to detect micron-sized particles that constitute clouds with lower than 0.1 g m-3 liquid or ice water content. Scanning or vertically-pointing ground-based millimeter wavelength radars are used to study stratocumulus (Vali et al. 1998; Kollias and Albrecht 2000) and fair-weather cumulus (Kollias et al. 2001). Airborne millimeter wavelength radars have been used for atmospheric remote sensing since the early 1990s (Pazmany et al. 1995). Airborne millimeter wavelength radar systems, such as the University of Wyoming King Air Cloud Radar (WCR) and the NASA ER-2 Cloud Radar System (CRS), have added mobility to observe clouds in remote regions and over oceans. Scientific requirements of millimeter wavelength radar are mainly driven by climate and cloud initiation studies. Survey results from the cloud radar user community indicated a common preference for a narrow beam W-band radar with polarimetric and Doppler capabilities for airborne remote sensing of clouds. For detecting small amounts of liquid and ice, it is desired to have -30 dBZ sensitivity at a 10 km range. Additional desired capabilities included a second wavelength and/or dual-Doppler winds. Modern radar technology offers various options (e.g., dual-polarization and dual-wavelength). Even though a basic fixed beam Doppler radar system with a sensitivity of -30 dBZ at 10 km is capable of satisfying cloud detection requirements, the above-mentioned additional options, namely dual-wavelength, and dual-polarization, significantly extend the measurement capabilities to further reduce any uncertainty in radar-based retrievals of cloud properties. This paper describes a novel, airborne pod-based millimeter wave radar, preliminary radar measurements and corresponding derived scientific products. Since some of the primary engineering requirements of this millimeter wave radar are that it should be deployable on an airborne platform

  14. Progress in coherent laser radar

    Science.gov (United States)

    Vaughan, J. M.

    1986-01-01

    Considerable progress with coherent laser radar has been made over the last few years, most notably perhaps in the available range of high performance devices and components and the confidence with which systems may now be taken into the field for prolonged periods of operation. Some of this increasing maturity was evident at the 3rd Topical Meeting on Coherent Laser Radar: Technology and Applications. Topics included in discussions were: mesoscale wind fields, nocturnal valley drainage and clear air down bursts; airborne Doppler lidar studies and comparison of ground and airborne wind measurement; wind measurement over the sea for comparison with satellite borne microwave sensors; transport of wake vortices at airfield; coherent DIAL methods; a newly assembled Nd-YAG coherent lidar system; backscatter profiles in the atmosphere and wavelength dependence over the 9 to 11 micrometer region; beam propagation; rock and soil classification with an airborne 4-laser system; technology of a global wind profiling system; target calibration; ranging and imaging with coherent pulsed and CW system; signal fluctuations and speckle. Some of these activities are briefly reviewed.

  15. Bistatic radar

    CERN Document Server

    Willis, Nick

    2004-01-01

    Annotation his book is a major extension of a chapter on bistatic radar written by the author for the Radar Handbook, 2nd edition, edited by Merrill Skolnik. It provides a history of bistatic systems that points out to potential designers the applications that have worked and the dead-ends not worth pursuing. The text reviews the basic concepts and definitions, and explains the mathematical development of relationships, such as geometry, Ovals of Cassini, dynamic range, isorange and isodoppler contours, target doppler, and clutter doppler spread.Key Features * All development and analysis are

  16. Linking sardine recruitment in coastal areas to ocean currents using surface drifters and HF radar. A case study in the Gulf of Manfredonia, Adriatic Sea

    DEFF Research Database (Denmark)

    Sciascia, Roberta; Berta, Maristella; Carlson, Daniel Frazier

    2017-01-01

    Understanding the role of ocean currents in the recruitment of commercially and ecologically important fish is an important step towards developing sustainable resource management guidelines. To this end, we attempt to elucidate the role of surface ocean transport in supplying recruits of sardine...... (Sardinus pilchardus) to the Gulf of Manfredonia, a known recruitment area in the Adriatic Sea. Sardine early life history stages (ELHS) were collected during two cruises to provide observational estimates of age-size relationship and of their passive pelagic larval duration (PPLD). We combine these PPLDs...... in the Gulf is characterized by repeated pulses from remote SAs. This is the first attempt to describe the processes related to Lagrangian connection to, and retention in, the Gulf of Manfredonia that will be complemented in the future using validated numerical ocean models and biophysical models....

  17. 2010-2011 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: Oregon and Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain topographic and bathymetric lidar data collected with the Leica ALS60 (topo) and SHOALS-1000T (bathy) systems along the coasts of Oregon and...

  18. HF Radar Sea-echo from Shallow Water

    Directory of Open Access Journals (Sweden)

    Josh Kohut

    2008-08-01

    Full Text Available HF radar systems are widely and routinely used for the measurement of ocean surface currents and waves. Analysis methods presently in use are based on the assumption of infinite water depth, and may therefore be inadequate close to shore where the radar echo is strongest. In this paper, we treat the situation when the radar echo is returned from ocean waves that interact with the ocean floor. Simulations are described which demonstrate the effect of shallow water on radar sea-echo. These are used to investigate limits on the existing theory and to define water depths at which shallow-water effects become significant. The second-order spectral energy increases relative to the first-order as the water depth decreases, resulting in spectral saturation when the waveheight exceeds a limit defined by the radar transmit frequency. This effect is particularly marked for lower radar transmit frequencies. The saturation limit on waveheight is less for shallow water. Shallow water affects second-order spectra (which gives wave information far more than first-order (which gives information on current velocities, the latter being significantly affected only for the lowest radar transmit frequencies for extremely shallow water. We describe analysis of radar echo from shallow water measured by a Rutgers University HF radar system to give ocean wave spectral estimates. Radar-derived wave height, period and direction are compared with simultaneous shallow-water in-situ measurements.

  19. Wind field measurement in the nonprecipitous regions surrounding storms by an airborne pulsed Doppler lidar system, appendix A

    Science.gov (United States)

    Bilbro, J. W.; Vaughan, W. W.

    1980-01-01

    Coherent Doppler lidar appears to hold great promise in contributing to the basic store of knowledge concerning flow field characteristics in the nonprecipitous regions surrounding severe storms. The Doppler lidar, through its ability to measure clear air returns, augments the conventional Doppler radar system, which is most useful in the precipitous regions of the storm. A brief description of the Doppler lidar severe storm measurement system is provided along with the technique to be used in performing the flow field measurements. The application of the lidar is addressed, and the planned measurement program is outlined.

  20. 2011-2013 Indiana Statewide Imagery and LiDAR Program: Lake Michigan Watershed Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Indiana's Statewide LiDAR data is produced at 1.5-meter average post spacing for all 92 Indiana Counties covering more than 36,420 square miles. New LiDAR data was...

  1. Wayne and Washtenaw Counties 1.0 PPSM LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Wayne and Washtenaw Counties 1.0 PPSM LiDAR LiDAR Data Acquisition and Processing Production Task USGS CONTRACT: 07CRCN0006 TASK ORDER NUMBER: G09PD00300...

  2. Development of a pulsed 9.5 micron lidar for regional scale O3 measurement

    Science.gov (United States)

    Stewart, R. W.

    1980-01-01

    A pulsed infrared lidar system designed for application to the remote sensing of atmospheric trace gases from an airborne platform is described. The system is also capable of measuring the infrared backscatter characteristics of the ocean surface, terrain, cloud, and aerosol targets. The lidar employed is based on dual wavelength pulse energy measurements in the 9-11 micrometer wavelength region.

  3. Jean Lafitte 2013, 1.0 Meter LiDAR, Classified point cloud

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Jean Lafitte,G13PD00214, 1.0 Meter LiDAR Survey Area in south of New Orleans and encompasses 77...

  4. FY12 St Johns River Water Management LiDAR Survey: Putnam (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the FY12 St Johns River Water Management LiDAR Survey, project area in north-central Florida and...

  5. SMAP RADAR Calibration and Validation

    Science.gov (United States)

    West, R. D.; Jaruwatanadilok, S.; Chaubel, M. J.; Spencer, M.; Chan, S. F.; Chen, C. W.; Fore, A.

    2015-12-01

    The Soil Moisture Active Passive (SMAP) mission launched on Jan 31, 2015. The mission employs L-band radar and radiometer measurements to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Immediately following launch, there was a three month instrument checkout period, followed by six months of level 1 (L1) calibration and validation. In this presentation, we will discuss the calibration and validation activities and results for the L1 radar data. Early SMAP radar data were used to check commanded timing parameters, and to work out issues in the low- and high-resolution radar processors. From April 3-13 the radar collected receive only mode data to conduct a survey of RFI sources. Analysis of the RFI environment led to a preferred operating frequency. The RFI survey data were also used to validate noise subtraction and scaling operations in the radar processors. Normal radar operations resumed on April 13. All radar data were examined closely for image quality and calibration issues which led to improvements in the radar data products for the beta release at the end of July. Radar data were used to determine and correct for small biases in the reported spacecraft attitude. Geo-location was validated against coastline positions and the known positions of corner reflectors. Residual errors at the time of the beta release are about 350 m. Intra-swath biases in the high-resolution backscatter images are reduced to less than 0.3 dB for all polarizations. Radiometric cross-calibration with Aquarius was performed using areas of the Amazon rain forest. Cross-calibration was also examined using ocean data from the low-resolution processor and comparing with the Aquarius wind model function. Using all a-priori calibration constants provided good results with co-polarized measurements matching to better than 1 dB, and cross-polarized measurements matching to about 1 dB in the beta release. During the

  6. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Northern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. PAMAP data are organized into blocks, which...

  7. 2009 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Fort Kent, Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Camp Dresser McKee Inc. contracted with Sanborn Map Company to provide LiDAR mapping services for Fort Kent, Maine. Utilizing multi-return systems, Light Detection...

  8. 2007 Bureau of Land Management (BLM) Lidar: Panther Creek Watershed, Yamhill County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset represents LiDAR elevations acquired during a leaf-off and a leaf-on vegetative condition for the Upper Panther Creek Watershed in the Yamhill County...

  9. March 2003 Lidar Point Data of Southern California Coastline: Dana Point to Point La Jolla

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (Geodetic Coordinates) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  10. April 2004 Lidar Point Data of Southern California Coastline: Dana Point to Point La Jolla

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (Geodetic Coordinates) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  11. October 2005 Lidar Point Data of Southern California Coastline: Long Beach to US/Mexican Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (UTM, Zone 11) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from Long...

  12. 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...

  13. 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...

  14. 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Klamath Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  15. December 2002 Lidar Point Data of Southern California Coastline: Dana Point to Point La Jolla

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (latitude and longitude) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs)...

  16. 2010 Federal Emergency Management Agency (FEMA) Topographic Lidar: Concord River Watershed, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Concord AOI consists of one area. Ground Control is collected throughout the AOI for use in the processing of LiDAR data to ensure data accurately represents the...

  17. 2007 Northwest Florida Water Management District (NWFWMD) Lidar: North Jefferson County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range finding, GPS...

  18. 2017 USACE FEMA Topobathy Lidar DEM: Florida East Coast, Florida Keys, and Collier County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain rasterized topobathy lidar elevations collected after Hurricane Irma. In an effort to provide data as soon as possible, JALBTCX will be sending...

  19. 2006 Florida LiDAR: Escambia, Santa Rosa, and Walton Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — ESCAMBIA: The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Escambia County, Florida. These data were produced for Dewberry and...

  20. 2017 NOAA/OCM Unmanned Aerial System Lidar: Grand Bay NERR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial (QSI) and PrecisionHawk (PH) collected lidar for test sites within the Grand Bay National Estuarine Research Reserve (NERR) using an unmanned aerial...

  1. 2012 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Central Coast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon Central Coast Study Area for the Oregon Department of Geology and Mineral Industries...

  2. 2011 FEMA Risk Mapping, Assessment, and Planning (Risk MAP) Lidar: Nashua River Watershed (Massachusetts, New Hampshire)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Nashua River Watershed. This area falls in portions of...

  3. 2012 FEMA Risk Map Lidar: Merrimack River Watershed (Massachusetts, New Hampshire)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Merrimack River Watershed. This area falls in portions...

  4. 2014 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Four Rivers

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has completed the acquisition and processing of Light Detection and Ranging (LiDAR) data and Four-Band Radiometric Image Enhanced Survey (FRIES) of the Oregon...

  5. 2012 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Tillamook Yamhill

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon Tillamook-Yamhill Study Area for the Oregon Department of Geology and Mineral Industries...

  6. April 2005 Lidar Point Data of Southern California Coastline: Long Beach to US/Mexican Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (latitude/longitude) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  7. October 2003 Lidar Point Data of Southern California Coastline: Newport Beach to US/Mexican Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (Geodetic Coordinates) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  8. 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Crater Lake Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  9. 2006 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Connecticut Coastline Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

  10. 2012 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Rogue River Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Rogue River Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI),...

  11. 2010 U.S. Geological Survey (USGS) Topographic LiDAR: San Francisco Bay, California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  12. 2009 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar: Willamette Valley

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  13. 2014 Oregon Department of Geology and Mineral Industries (DOGAMI) Oregon Lidar DEM: Four Rivers

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has completed the acquisition and processing of Light Detection and Ranging (LiDAR) data and Four-Band Radiometric Image Enhanced Survey (FRIES) of the Oregon...

  14. 2008 Northwest Florida Water Management District (NWFWMD) Lidar: Eglin Air Force Base, Walton County, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In the summer of 2008, the Northwest Florida Water Management District collected lidar data over a portion of Walton County, FL (Eglin Air force Base) to support...

  15. 2005/2006 Southwest Florida Water Management District (SWFWMD) Lidar: Peace River South (including Carter Creek)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  16. 2007 Florida Division of Emergency Management (FDEM) Lidar Project: Southwest Florida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a topographic survey conducted for a coalition of GIS practitioners, including the Florida Division of...

  17. March 2006 Lidar Point Data of Southern California Coastline: Long Beach to US/Mexican Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (Geodetic Coordinates) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  18. 2011 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Quinnipiac River Watershed, Connecticut

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Quinnipiac AOI consists of one 443 square mile area. Ground Control is collected throughout the AOI for use in the processing of LiDAR data to ensure data...

  19. 2007 Lake County Board of County Commissioners Topographic LiDAR: Lake County, Florida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the LiDAR point data in LAS format produced by Kucera covering the project area of Lake County, FL. The data produced is...

  20. 2010 U.S. Geological Survey (USGS) Topographic Lidar: Channel Islands, California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint collected LiDAR for 197 square miles covering five islands off the coast of Los Angeles, California. These islands are part of the Channel Islands...

  1. 2007 Florida Division of Emergency Management (FDEM) Lidar Project: Bay County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a topographic survey conducted for a coalition of GIS practitioners, including the Florida Division of...

  2. 2006 Maryland Department of Natural Resources Lidar: Caroline, Kent and Queen Anne Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Maryland Department of Natural Resources requested the collection of LIDAR data over Kent, Queen Anne and Caroline Counties, MD. In response, EarthData acquired the...

  3. 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Mt. Shasta Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  4. 2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (National Capital Region)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract No. G10PC00025 CONTRACTOR: Quantum Spatial, Inc Ground Control Points were acquired and calibrated by Compass Data, Inc. All Lidar data acquisition,...

  5. 2017 NOAA/OCM Unmanned Aerial System Lidar DEM: Grand Bay NERR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial (QSI) and PrecisionHawk (PH) collected lidar for test sites within the Grand Bay National Estuarine Research Reserve (NERR) using an unmanned aerial...

  6. 2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hillsborough/Little Manatee Districts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — EarthData International collected ADS-50 derived LiDAR over a portion of Hillsborough and Manatee Counties with a one meter post spacing. The period of collection...

  7. 2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hernando County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is one component of a digital terrain model (DTM) for the Southwest Florida Water Management Districts FY2006 Digital Orthophoto (B089) and LiDAR...

  8. 2006 Southwest Florida Water Management District (SWFWMD) Lidar: Rutland Ranch District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Rutland Ranch. This data falls in Manatee County. These data were produced for...

  9. 2005 Southwest Florida Water Management District (SWFWMD) Lidar: Little Manatee District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  10. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Southern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. Additional information is available at the...

  11. 2001 NCFMP Lidar: Phase 1B (Cape Fear and Lumber River Basins)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This airborne LiDAR terrain mapping data was acquired in the spring of 2001. The data were collected for the floodplain mapping program for the state of North...

  12. 2004 Southwest Florida Water Management District (SWFWMD) Lidar Project: Pasco County (Classified)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Earthdata International was contracted to provide mapping services in Pasco County, Florida. Conventional aerial photography along with LIDAR observations were made....

  13. Coastal Elevation Data (from Lidar) for US and Territories from 1996 to Present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Many different partners and groups, and several Center-led data projects, have contributed to the lidar data collection housed and distributed by the NOAA Office for...

  14. 2009 National Renewable Energy Laboratory/Boston Redevelopment Authority Topographic LiDAR: Boston, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Alliance for Sustainable Energy, LLC contracted with Sanborn to provide LiDAR mapping services for the Boston area. Utilizing multi-return systems, Light...

  15. September 2004 Lidar Point Data of Southern California Coastline: Long Beach to US/Mexican Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data (Geodetic Coordinates) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from...

  16. 2007 Northwest Florida Water Manangement District (NWFWMD) Lidar: Jackson County ("Jackson Blue")

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR-derived binary (.las) files containing points classified as bare-earth and canopy (first return) were produced for the 2007 Northwest Florida Water Management...

  17. 2007 Northwest Florida Water Manangement District(NWFWMD) Lidar: Gadsden County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR-derived binary (.las) files containing points classified as bare-earth and canopy (first return) were produced for the 2007 Northwest Florida Water Management...

  18. 2012 Oregon Department of Interior, Bureau of Land Management (BLM) Lidar: Panther Creek Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Interior, Bureau of Land Management (BLM) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  19. 2008 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Lake Billy Chinook, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  20. 2013 NOAA Topographic Lidar: U.S. Virgin Islands (St. Croix, St. John, St. Thomas)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The United States Virgin Islands Topographic LiDAR project collected topographic elevation point data derived from multiple return light detection and ranging...

  1. 2010 U.S. Geological Survey Topographic LiDAR: Atchafalaya Basin, Louisiana

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin in south-central Louisiana. The entire survey area encompasses 981 square miles....

  2. 2012 USACE Post Sandy Topographic LiDAR: Rhode Island and Massachusetts Coast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This topographic elevation point data derived from multiple return light detection and ranging (LiDAR) represents 354.272 square miles of coastline for Rhode Island...

  3. Hydrographic & Topographic LIDAR Acquisition, Northwest Coast, Washington State - Bathymetric Survey Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data were collected by the SHOALS-1000T(Scanning Hydrographic Operational Airborne Lidar Survey)system which consists of an airborne laser transmitter/receiver...

  4. May 2002 Lidar Point Data of Southern California Coastline: Dana Point to Point La Jolla

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from Dana Point to Point La...

  5. September 2002 Lidar Point Data of Southern California Coastline: Dana Point to Point La Jolla

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains lidar point data from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from Dana Point to Point La...

  6. 2013 NOAA Topographic Lidar: US Virgin Islands Digital Elevation Models (DEMs)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The United States Virgin Islands Topographic LiDAR Task Order involved collecting and delivering topographic elevation point data derived from multiple return light...

  7. 2008 USGS Lidar: Twelve County, Illinois (Grundy, Kane, McHenry only)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This LiDAR data is within Illinois Department of Transportation districts 1 and 3 covering Grundy, Kane and McHenry counties. The data is updated from its original...

  8. 2006 Texas Water Development Board (TWDB) Lidar: Northern Cameron and Willacy Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, standard density (1.4 meter ground sample distance) data were collected over areas in Northern...

  9. 2008 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Ontario

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic lidar data for...

  10. 2011 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Burns Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  11. 2010 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Newberry Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  12. 2008 Northwest Florida Water Management District (NWFWMD) LiDAR: Inland Okaloosa County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a survey of inland Okaloosa County, Florida not covered in the 2008 Florida Department of Emergency...

  13. 2007 Northwest Florida Water Manangement District (NWFWMD) Lidar: 5 Counties (Jackson, Calhoun, Washington, Liberty, Holmes)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR-derived binary (.las) files containing points classified as bare-earth and canopy (first return) were produced for the 2007/2008 Northwest Florida Water...

  14. 2007 Federal Emergency Management Agency (FEMA) New York Lidar: Niagara County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The spring 2007 LiDAR Flight Acquisition required the collection of approximately 526 square miles of Niagara County and approximately 30 square miles of the...

  15. LiDAR Relative Reflectivity Surface (2011) for the St. Thomas East End Reserve, St. Thomas

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for the St. Thomas East End Reserve...

  16. 2001 NCFMP Lidar: Phase 1A (Neuse, Pasquotank, Tar-Pamlico, White Oak River Basins)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This airborne LiDAR terrain mapping data was acquired January through March 2001. The data were collected for the floodplain mapping program for the state of North...

  17. 2007 California Department of Water Resources Topographic LiDAR: San Joaquin Delta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data are from LIDAR flights of the Sacramento-San Joaquin Delta conducted during late January and February of 2007. The work was conducted under contract...

  18. U.S. Coastal Lidar Elevation Data - Including the Great Lakes and Territories, 1996 - present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Coastal Services Center manages and distributes lidar data for the coastal United States, including territorial possessions via the Digital Coast Data...

  19. 2012 FEMA Topographic Lidar: Hudson-Hoosic and Deerfield Watersheds, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Hudson-Hoosic and Deerfield project area. The entire survey area for Massachusetts is...

  20. Atmospheric aerosol and gas sensing using Scheimpflug lidar

    Science.gov (United States)

    Mei, Liang; Brydegaard, Mikkel

    2015-04-01

    This work presents a new lidar technique for atmospheric remote sensing based on Scheimpflug principle, which describes the relationship between nonparallel image- and object-planes[1]. When a laser beam is transmitted into the atmosphere, the implication is that the backscattering echo of the entire illuminated probe volume can be in focus simultaneously without diminishing the aperture. The range-resolved backscattering echo can be retrieved by using a tilted line scan or two-dimensional CCD/CMOS camera. Rather than employing nanosecond-pulsed lasers, cascade detectors, and MHz signal sampling, all of high cost and complexity, we have developed a robust and inexpensive atmospheric lidar system based on compact laser diodes and array detectors. We present initial applications of the Scheimpflug lidar for atmospheric aerosol monitoring in bright sunlight, with a 3 W, 808 nm CW laser diode. Kilohertz sampling rates are also achieved with applications for wind speed and entomology [2]. Further, a proof-of-principle demonstration of differential absorption lidar (DIAL) based on the Scheimpflug lidar technique is presented [3]. By utilizing a 30 mW narrow band CW laser diode emitting at around 760 nm, the detailed shape of an oxygen absorption line can be resolved remotely with an integration time of 6 s and measurement cycle of 1 minute during night time. The promising results demonstrated in this work show potential for the Scheimpflug lidar technique for remote atmospheric aerosol and gas sensing, and renews hope for robust and realistic instrumentation for atmospheric lidar sensing. [1] F. Blais, "Review of 20 years of range sensor development," Journal of Electronic Imaging, vol. 13, pp. 231-243, Jan 2004. [2] M. Brydegaard, A. Gebru, and S. Svanberg, "Super resolution laser radar with blinking atmospheric particles - application to interacting flying insects " Progress In Electromagnetics Research, vol. 147, pp. 141-151, 2014. [3] L. Mei and M. Brydegaard

  1. Lidar Range-Resolved Optical Remote Sensing of the Atmosphere

    CERN Document Server

    Weitkamp, Claus

    2005-01-01

    Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection. Its broad cross-disciplinary scope should appeal to both the experienced scientist and the novice in the field. The Foreword is by one of the early pioneers in the area, Herbert Walther.

  2. CloudSat 2C-ICE product update with a new Ze parameterization in lidar-only region.

    Science.gov (United States)

    Deng, Min; Mace, Gerald G; Wang, Zhien; Berry, Elizabeth

    2015-12-16

    The CloudSat 2C-ICE data product is derived from a synergetic ice cloud retrieval algorithm that takes as input a combination of CloudSat radar reflectivity ( Z e ) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation lidar attenuated backscatter profiles. The algorithm uses a variational method for retrieving profiles of visible extinction coefficient, ice water content, and ice particle effective radius in ice or mixed-phase clouds. Because of the nature of the measurements and to maintain consistency in the algorithm numerics, we choose to parameterize (with appropriately large specification of uncertainty) Z e and lidar attenuated backscatter in the regions of a cirrus layer where only the lidar provides data and where only the radar provides data, respectively. To improve the Z e parameterization in the lidar-only region, the relations among Z e , extinction, and temperature have been more thoroughly investigated using Atmospheric Radiation Measurement long-term millimeter cloud radar and Raman lidar measurements. This Z e parameterization provides a first-order estimation of Z e as a function extinction and temperature in the lidar-only regions of cirrus layers. The effects of this new parameterization have been evaluated for consistency using radiation closure methods where the radiative fluxes derived from retrieved cirrus profiles compare favorably with Clouds and the Earth's Radiant Energy System measurements. Results will be made publicly available for the entire CloudSat record (since 2006) in the most recent product release known as R05.

  3. Advances in bistatic radar

    CERN Document Server

    Willis, Nick

    2007-01-01

    Advances in Bistatic Radar updates and extends bistatic and multistatic radar developments since publication of Willis' Bistatic Radar in 1991. New and recently declassified military applications are documented. Civil applications are detailed including commercial and scientific systems. Leading radar engineers provide expertise to each of these applications. Advances in Bistatic Radar consists of two major sections: Bistatic/Multistatic Radar Systems and Bistatic Clutter and Signal Processing. Starting with a history update, the first section documents the early and now declassified military

  4. Shipborne LiDAR system for coastal change monitoring

    Science.gov (United States)

    Kim, chang hwan; Park, chang hong; Kim, hyun wook; hyuck Kim, won; Lee, myoung hoon; Park, hyeon yeong

    2016-04-01

    Coastal areas, used as human utilization areas like leisure space, medical care, ports and power plants, etc., are regions that are continuously changing and interconnected with oceans and land and the sea level has risen by about 8cm (1.9mm / yr) due to global warming from 1964 year to 2006 year in Korea. Coastal erosion due to sea-level rise has caused the problem of marine ecosystems and loss of tourism resources, etc. Regular monitoring of coastal erosion is essential at key locations with such volatility. But the survey method of land mobile LiDAR (light detection and ranging) system has much time consuming and many restrictions. For effective monitoring beach erosion, KIOST (Korea Institute of Ocean Science & Technology) has constructed a shipborne mobile LiDAR system. The shipborne mobile LiDAR system comprised a land mobile LiDAR (RIEGL LMS-420i), an INS (inertial navigation system, MAGUS Inertial+), a RTKGPS (LEICA GS15 GS25), and a fixed platform. The shipborne mobile LiDAR system is much more effective than a land mobile LiDAR system in the measuring of fore shore areas without shadow zone. Because the vessel with the shipborne mobile LiDAR system is continuously moved along the shoreline, it is possible to efficiently survey a large area in a relatively short time. Effective monitoring of the changes using the constructed shipborne mobile LiDAR system for seriously eroded coastal areas will be able to contribute to coastal erosion management and response.

  5. Application of in situ observations, high frequency radars, and ocean color, to study suspended matter, particulate carbon, and dissolved organic carbon fluxes in coastal waters of the Barents Sea - the NORDFLUX project

    Science.gov (United States)

    Stramska, Malgorzata; Yngve Børsheim, Knut; Białogrodzka, Jagoda; Cieszyńska, Agata; Ficek, Dariusz; Wereszka, Marzena

    2016-04-01

    There is still a limited knowledge about suspended and dissolved matter fluxes transported from coastal regions into the open sea regions in the Arctic. The land/sea interface is environmentally important and sensitive to climate change. Important biogeochemical material entering the oceans (including carbon) passes through this interface, but too little is known about the efficiency of this transport. Our goal in the NORDFLUX program is to improve quantitative understanding of the environmental feedbacks involved in these processes through an interdisciplinary study with innovative in situ observations. Completed work includes two in situ experiments in the Norwegian fiord (Porsangerfjorden) in the summers of 2014 and 2015. Experiments used research boat for collection of water samples and in situ bio-optical data, an autonomous glider, mooring with T S sensors, and a high frequency radar system. We have used these data to derive spatial maps of water temperature, salinity, surface currents, chlorophyll fluorescence, dissolved organic matter (DOM) fluorescence, and inherent optical properties (IOPs) of the water. The interpretation of these data in terms of suspended matter concentration and composition is possible by in situ 'calibrations' using water samples from discrete hydrographic stations. Total suspended matter (TSM), particulate carbon (POC and PIC), and dissolved organic carbon (DOC) concentrations together with measured water currents will allow us to estimate reservoirs and fluxes. Concentrations and fluxes will be related to physical conditions and meteorological data. An important aspect of this project is the work on regional ocean color algorithms. Global ocean color (OC) algorithms currently used by NASA do not perform sufficiently well in coastal Case 2 waters. Our data sets will allow us to derive such local algorithms. We will then use these algorithms for interpretation of OC data in terms of TSM concentrations and composition and DOC. After

  6. Alexandrite Lidar Receiver

    National Research Council Canada - National Science Library

    Wilkerson, Thomas

    2000-01-01

    ...". The chosen vendor, Orca Photonics, In. (Redmond, WA), in close collaboration with USU personnel, built a portable, computerized lidar system that not only is suitable as a receiver for a near IR alexandrite laser, but also contains an independent Nd...

  7. LIDAR Thomson scattering

    International Nuclear Information System (INIS)

    1991-07-01

    This collection contains 21 papers on the application and development of LIDAR (Light Detection and Ranging) Thomson scattering techniques for the determination of spatially resolved electron temperature and density in magnetic confinement experiments, particularly tokamaks. Refs, figs and tabs

  8. Lidar 2009 - All Returns

    Data.gov (United States)

    Kansas Data Access and Support Center — LIDAR-derived binary (.las) files containing classified points of all returns. We have 3 classifications Unclassified, Ground, Low points. The average Ground Sample...

  9. Holographic Raman lidar

    International Nuclear Information System (INIS)

    Andersen, G.

    2000-01-01

    Full text: We have constructed a Raman lidar system that incorporates a holographic optical element. By resolving just 3 nitrogen lines in the Resonance Raman spectroscopy (RRS) spectrum, temperature fits as good as 1% at altitudes of 20km can be made in 30 minutes. Due to the narrowband selectivity of the HOE, the lidar provides measurements over a continuous 24hr period. By adding a 4th channel to capture the Rayleigh backscattered light, temperature profiles can be extended to 80km

  10. Installation report - Lidar

    DEFF Research Database (Denmark)

    Georgieva Yankova, Ginka; Villanueva, Héctor

    The report describes the installation, configuration and data transfer for the ground-based lidar. The unit is provided by a customer but is installed and operated by DTU while in this project.......The report describes the installation, configuration and data transfer for the ground-based lidar. The unit is provided by a customer but is installed and operated by DTU while in this project....

  11. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  12. Radar Images of the Earth and the World Wide Web

    Science.gov (United States)

    Chapman, B.; Freeman, A.

    1995-01-01

    A perspective of NASA's Jet Propulsion Laboratory as a center of planetary exploration, and its involvement in studying the earth from space is given. Remote sensing, radar maps, land topography, snow cover properties, vegetation type, biomass content, moisture levels, and ocean data are items discussed related to earth orbiting satellite imaging radar. World Wide Web viewing of this content is discussed.

  13. 2015 USGS-MDEQ Lidar: Coastal Mississippi QL2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This task is issued under USGS Contract No. G10PC00057, Task Order No. G15PD00091. This task order requires lidar data to be acquired over approximately 5981 square...

  14. 2009-2010 USACE Vicksburg District Lidar: Mississippi River Delta

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR collected at 1.0 points per square meter (1.0m GSD) for the entire portion of the Mississippi River Delta in the Vicksburg District. This area was flown during...

  15. Twomey effect in subtropical stratocumulus clouds from UV depolarization lidar

    NARCIS (Netherlands)

    de Graaf, M.; Brown, Jessica; Donovan, D.P.; Nicolae, D.; Makoto, A.; Vassilis, A.; Balis, D.; Behrendt, A.; Comeron, A.; Gibert, F.; Landulfo, E.; McCormick, M.P.; Senff, C.; Veselovskii, I.; Wandinger, U.

    2018-01-01

    Marine stratocumulus clouds are important climate regulators, reflecting sunlight over a dark ocean background. A UV-depolarization lidar on Ascension, a small remote island in the south Atlantic, measured cloud droplet sizes and number concentration using an inversion method based on Monte Carlo

  16. 2012 USGS Lidar: Central Virginia Seismic (Louisa County)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract: G10PC00013 Task Order Number: G12PD00264 Prepared for USGS, Prepared by: Dewberry, 1000 Ashley Blvd., Suite 801, Tampa, Florida 33602-3718 The LiDAR...

  17. 2011 USGS Topographic LiDAR: Suwannee River Expansion

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Task Order No. G10PD00236 USGS Contract No. G10PC00093 The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River Expansion in...

  18. Evaluation of LIDAR for Automating Recognition of Roads and Trails Beneath Forest Canopy

    Science.gov (United States)

    2011-09-01

    Measurement Unit InSAR Interferometric Synthetic Aperture Radar ISS International Space Station JALBTCX Joint Airborne LiDAR Bathymetry Technical Center of...California police arrest 100 over marijuana growing. Retrieved July 29, 2011, from http://www.bbc.co.uk/news/world–us–canada–14351501 Contreras, M

  19. 2004 Anne Arundel, Charles, Howard & St. Mary's Counties LiDAR Mapping

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Light Detection and Ranging (LIDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

  20. Lidar remote sensing of above-ground biomass in three biomes.

    Science.gov (United States)

    Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas. Gower

    2002-01-01

    Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

  1. Minimum redundancy MIMO radars

    OpenAIRE

    Chen, Chun-Yang; Vaidyanathan, P. P.

    2008-01-01

    The multiple-input multiple-output (MIMO) radar concept has drawn considerable attention recently. In the traditional single-input multiple-output (SIMO) radar system, the transmitter emits scaled versions of a single waveform. However, in the MIMO radar system, the transmitter transmits independent waveforms. It has been shown that the MIMO radar can be used to improve system performance. Most of the MIMO radar research so far has focused on the uniform array. However, i...

  2. Enhanced Ocean Scatterometry

    NARCIS (Netherlands)

    Fois, F.

    2015-01-01

    An ocean scatterometer is an active microwave instrument which is designed to determine the normalized radar cross section (NRCS) of the sea surface. Scatterometers transmit pulses towards the sea surface and measure the reflected energy. The primary objective of spaceborne scatterometers is to

  3. 2013-2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (MA, NH, RI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: New England CMGP Sandy Lidar LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00796 Woolpert Order...

  4. Calibration of scanning Lidar

    DEFF Research Database (Denmark)

    Gómez Arranz, Paula; Courtney, Michael

    This report describes the tests carried out on a scanning lidar at the DTU Test Station for large wind turbines, Høvsøre. The tests were divided in two parts. In the first part, the purpose was to obtain wind speed calibrations at two heights against two cup anemometers mounted on a mast. Additio......This report describes the tests carried out on a scanning lidar at the DTU Test Station for large wind turbines, Høvsøre. The tests were divided in two parts. In the first part, the purpose was to obtain wind speed calibrations at two heights against two cup anemometers mounted on a mast...

  5. 2007 Oregon Department of Geology and Mineral Industries (DoGAMI) LiDAR: Northwest Oregon and Portland Metro Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data for the Oregon Department of Geology and Mineral Industries (DoGAMI) and the Oregon...

  6. 2010 VA Information Technologies Agency (VITA)/VA Geographic Information Network (VGIN) Lidar: Eastern Shore, VA (Accomack and Northampton Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Virginia Geographic Information Network (VGIN) contracted with Sanborn to provide LiDAR mapping services for Accomack and Northampton counties on the eastern...

  7. 2011 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: US Forest Service (FS) Newberry Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  8. 2011 NOAA Bathymetric Lidar: U.S. Virgin Islands - St. Thomas, St. John, St. Croix (Salt River Bay, Buck Island)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data represents a LiDAR (Light Detection & Ranging) gridded bathymetric surface and a gridded relative seafloor reflectivity surface (incorporated into the...

  9. 2007 Florida Division of Emergency Management (FDEM) Lidar: Herbert Hoover Dike Project Area (Southeastern Florida, Lake Okeechobee Surrounding Area)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data was collected by Merrick & Company from September through December of 2007 for the Florida Division of Emergency Management (FDEM). The project area...

  10. 2011 U.S. Department of Agriculture- Natural Resources Conservation Service (USDA-NRCS) Topographic Lidar: North West Connecticut

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Earth Eye collected LiDAR data for approximately 1,703 square kilometers that partially cover the Connecticut counties of Litchfield and Fairfield. The nominal pulse...

  11. April 2008 Scripps Institute of Oceanography (SIO) Lidar of the Southern California Coastline: Long Beach to US/Mexico Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This lidar point data set collected during low tide conditions along an approximately 500-700 meter wide strip of the Southern California coastline within an area...

  12. November 2007 Scripps Institute of Oceanography (SIO) Lidar of the Southern California Coastline: Long Beach to US/Mexico Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This lidar point data set was collected during low tide conditions along an approximately 500-700 meter wide strip of the Southern California coastline within an...

  13. September 2008 Scripps Institute of Oceanography (SIO) Lidar of the Southern California Coastline: Long Beach to US/Mexico Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This lidar point data set was collected during low tide conditions along an approximately 500-700 meter wide strip of the Southern California coastline within an...

  14. 2010 U.S. Department of Agriculture- Natural Resources Conservation Service (USDA-NRCS) Topographic Lidar: Eastern Connecticut

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Earth Eye collected LiDAR data for approximately 4,589 square kilometers that partially cover the Connecticut counties of Hartford, Tolland, Windham, Middlesex and...

  15. 2011 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Cascade Volcano Observatory (CVO) Newberry Study Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high resolution topographic LiDAR data for...

  16. 2003 U.S. Geological Survey (USGS) Experimental Advanced Airborne Research Lidar (EAARL): US Virgin Islands (St. John, St. Croix)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains topographic and bathymetric lidar data that were collected on April 21, 23, 30, May 2, and June 14, 17 of 2003, cooperatively by the U.S....

  17. March 2009 Scripps Institute of Oceanography (SIO) Lidar of the Southern California Coastline: Long Beach to US/Mexico Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This lidar point data set was collected during low tide conditions along an approximately 500-700 meter wide strip of the Southern California coastline within an...

  18. 2009 USGS/NPS Experimental Advanced Airborne Research Lidar (EAARL): Cape Hatteras National Seashore - Post-Nor'easter Ida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is a bare-earth data lidar data set that was collected on November 27, 29 and December 1, 2009 along the shoreline of the Cape Hatteras National Seashore in...

  19. 2011 U.S. Army Corps of Engineers (USACE) Topographic LiDAR: Massachusetts and New Hampshire

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1), valid topographic data classified as ground (2),...

  20. 2011 Georgia Department of Natural Resources (GADNR) Environmental Protection Division (EPD) Lidar: Four Counties (Burke, Columbia, Lincoln, and Richmond)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is the topographic elevation point data derived from multiple return light detection and ranging (LiDAR) measurements for four counties in Georgia....

  1. 2010 Northern San Francisco Bay Area Lidar: Portions of Alameda, Contra Costa, Marin, Napa, San Francisco, Solano, and Sonoma Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) dataset is a survey of northern San Francisco Bay, California. The project area consists of approximately 437 square miles...

  2. Adaptive radar resource management

    CERN Document Server

    Moo, Peter

    2015-01-01

    Radar Resource Management (RRM) is vital for optimizing the performance of modern phased array radars, which are the primary sensor for aircraft, ships, and land platforms. Adaptive Radar Resource Management gives an introduction to radar resource management (RRM), presenting a clear overview of different approaches and techniques, making it very suitable for radar practitioners and researchers in industry and universities. Coverage includes: RRM's role in optimizing the performance of modern phased array radars The advantages of adaptivity in implementing RRMThe role that modelling and

  3. Radar and ARPA manual

    CERN Document Server

    Bole, A G

    2013-01-01

    Radar and ARPA Manual focuses on the theoretical and practical aspects of electronic navigation. The manual first discusses basic radar principles, including principles of range and bearing measurements and picture orientation and presentation. The text then looks at the operational principles of radar systems. Function of units; aerial, receiver, and display principles; transmitter principles; and sitting of units on board ships are discussed. The book also describes target detection, Automatic Radar Plotting Aids (ARPA), and operational controls of radar systems, and then discusses radar plo

  4. A Variational Method to Retrieve the Extinction Profile in Liquid Clouds Using Multiple Field-of-View Lidar

    Science.gov (United States)

    Pounder, Nicola L.; Hogan, Robin J.; Varnai, Tamas; Battaglia, Alessandro; Cahalan, Robert F.

    2011-01-01

    While liquid clouds playa very important role in the global radiation budget, it's been very difficult to remotely determine their internal cloud structure. Ordinary lidar instruments (similar to radars but using visible light pulses) receive strong signals from such clouds, but the information is limited to a thin layer near the cloud boundary. Multiple field-of-view (FOV) lidars offer some new hope as they are able to isolate photons that were scattered many times by cloud droplets and penetrated deep into a cloud before returning to the instrument. Their data contains new information on cloud structure, although the lack of fast simulation methods made it challenging to interpret the observations. This paper describes a fast new technique that can simulate multiple-FOV lidar signals and can even estimate the way the signals would change in response to changes in cloud properties-an ability that allows quick refinements in our initial guesses of cloud structure. Results for a hypothetical airborne three-FOV lidar suggest that this approach can help determine cloud structure for a deeper layer in clouds, and can reliably determine the optical thickness of even fairly thick liquid clouds. The algorithm is also applied to stratocumulus observations by the 8-FOV airborne "THOR" lidar. These tests demonstrate that the new method can determine the depth to which a lidar provides useful information on vertical cloud structure. This work opens the way to exploit data from spaceborne lidar and radar more rigorously than has been possible up to now.

  5. Multistatic Aerosol Cloud Lidar in Space: A Theoretical Perspective

    Science.gov (United States)

    Mishchenko, Michael I.; Alexandrov, Mikhail D.; Cairns, Brian; Travis, Larry D.

    2016-01-01

    measurements. Although the specific subject of this Perspective is the multistatic lidar concept, all our conclusions equally apply to a multistatic radar system intended to study from space the global distribution of cloud and precipitation characteristics.

  6. Calibrating nacelle lidars

    Energy Technology Data Exchange (ETDEWEB)

    Courtney, M.

    2013-01-15

    Nacelle mounted, forward looking wind lidars are beginning to be used to provide reference wind speed measurements for the power performance testing of wind turbines. In such applications, a formal calibration procedure with a corresponding uncertainty assessment will be necessary. This report presents four concepts for performing such a nacelle lidar calibration. Of the four methods, two are found to be immediately relevant and are pursued in some detail. The first of these is a line of sight calibration method in which both lines of sight (for a two beam lidar) are individually calibrated by accurately aligning the beam to pass close to a reference wind speed sensor. A testing procedure is presented, reporting requirements outlined and the uncertainty of the method analysed. It is seen that the main limitation of the line of sight calibration method is the time required to obtain a representative distribution of radial wind speeds. An alternative method is to place the nacelle lidar on the ground and incline the beams upwards to bisect a mast equipped with reference instrumentation at a known height and range. This method will be easier and faster to implement and execute but the beam inclination introduces extra uncertainties. A procedure for conducting such a calibration is presented and initial indications of the uncertainties given. A discussion of the merits and weaknesses of the two methods is given together with some proposals for the next important steps to be taken in this work. (Author)

  7. Nacelle lidar power curve

    DEFF Research Database (Denmark)

    Gómez Arranz, Paula; Wagner, Rozenn

    This report describes the power curve measurements performed with a nacelle LIDAR on a given wind turbine in a wind farm and during a chosen measurement period. The measurements and analysis are carried out in accordance to the guidelines in the procedure “DTU Wind Energy-E-0019” [1]. The reporting...

  8. Lidar 2009 - IMG

    Data.gov (United States)

    Kansas Data Access and Support Center — ESRI Grids 1 meter resolution are created from the ground classified lidar points. The tiles are delivered in 5,000m by 5,000m tiles. The ESRI grids are exported to...

  9. Coherent Doppler Laser Radar: Technology Development and Applications

    Science.gov (United States)

    Kavaya, Michael J.; Arnold, James E. (Technical Monitor)

    2000-01-01

    NASA's Marshall Space Flight Center has been investigating, developing, and applying coherent Doppler laser radar technology for over 30 years. These efforts have included the first wind measurement in 1967, the first airborne flights in 1972, the first airborne wind field mapping in 1981, and the first measurement of hurricane eyewall winds in 1998. A parallel effort at MSFC since 1982 has been the study, modeling and technology development for a space-based global wind measurement system. These endeavors to date have resulted in compact, robust, eyesafe lidars at 2 micron wavelength based on solid-state laser technology; in a factor of 6 volume reduction in near diffraction limited, space-qualifiable telescopes; in sophisticated airborne scanners with full platform motion subtraction; in local oscillator lasers capable of rapid tuning of 25 GHz for removal of relative laser radar to target velocities over a 25 km/s range; in performance prediction theory and simulations that have been validated experimentally; and in extensive field campaign experience. We have also begun efforts to dramatically improve the fundamental photon efficiency of the laser radar, to demonstrate advanced lower mass laser radar telescopes and scanners; to develop laser and laser radar system alignment maintenance technologies; and to greatly improve the electrical efficiency, cooling technique, and robustness of the pulsed laser. This coherent Doppler laser radar technology is suitable for high resolution, high accuracy wind mapping; for aerosol and cloud measurement; for Differential Absorption Lidar (DIAL) measurements of atmospheric and trace gases; for hard target range and velocity measurement; and for hard target vibration spectra measurement. It is also suitable for a number of aircraft operations applications such as clear air turbulence (CAT) detection; dangerous wind shear (microburst) detection; airspeed, angle of attack, and sideslip measurement; and fuel savings through

  10. ISTEF Laser Radar Program

    National Research Council Canada - National Science Library

    Stryjewski, John

    1998-01-01

    The BMDO Innovative Science and Technology Experimentation Facility (BMDO/ISTEF) laser radar program is engaged in an ongoing program to develop and demonstrate advanced laser radar concepts for Ballistic Missile Defense (BMD...

  11. Novel radar techniques and applications

    CERN Document Server

    Klemm, Richard; Lombardo, Pierfrancesco; Nickel, Ulrich

    2017-01-01

    Novel Radar Techniques and Applications presents the state-of-the-art in advanced radar, with emphasis on ongoing novel research and development and contributions from an international team of leading radar experts. This volume covers: Real aperture array radar; Imaging radar and Passive and multistatic radar.

  12. Principles of modern radar systems

    CERN Document Server

    Carpentier, Michel H

    1988-01-01

    Introduction to random functions ; signal and noise : the ideal receiver ; performance of radar systems equipped with ideal receivers ; analysis of the operating principles of some types of radar ; behavior of real targets, fluctuation of targets ; angle measurement using radar ; data processing of radar information, radar coverage ; applications to electronic scanning antennas to radar ; introduction to Hilbert spaces.

  13. Lidars for oceanological research: criteria for comparison, main limitations, perspectives

    Science.gov (United States)

    Feigels, Victor I.

    1992-12-01

    The paper contains a comparative analysis and discussion of resultant recommendations for the optimization of an airborne lidar's parameters, with application to modern lidar systems as employed in various countries for the ocean and continental shelf research. As criteria for the systems comparison in different remote sensing conditions (aircraft altitude, depth, day/night, zenithal sun angle, sea-water attenuation coefficient, receiver optical system's field of view (FOV), laser wavelength, etc.,) Sakitt's D-index of discriminability is used. We demonstrate the optical signal, as determined by the following process: reflecting from boundary -- backscattering in the atmosphere -- secondary reflecting from boundary, to be the cause for limiting the distance of underwater measurements. Some estimates for the bottom depth values to be achieved by a `super-lidar' are presented.

  14. Software Radar Technology

    Directory of Open Access Journals (Sweden)

    Tang Jun

    2015-08-01

    Full Text Available In this paper, the definition and the key features of Software Radar, which is a new concept, are proposed and discussed. We consider the development of modern radar system technology to be divided into three stages: Digital Radar, Software radar and Intelligent Radar, and the second stage is just commencing now. A Software Radar system should be a combination of various modern digital modular components conformed to certain software and hardware standards. Moreover, a software radar system with an open system architecture supporting to decouple application software and low level hardware would be easy to adopt "user requirements-oriented" developing methodology instead of traditional "specific function-oriented" developing methodology. Compared with traditional Digital Radar, Software Radar system can be easily reconfigured and scaled up or down to adapt to the changes of requirements and technologies. A demonstration Software Radar signal processing system, RadarLab 2.0, which has been developed by Tsinghua University, is introduced in this paper and the suggestions for the future development of Software Radar in China are also given in the conclusion.

  15. Oceanic eddies in synthetic aperture radar images

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    determining mechanism of eddy formation in this case is the vorticity (shear) of the currents or devi- ation of one current by another. Figure 10 shows the ERS-1 SAR image with a couple of cyclonic eddies that is supposedly located in the area of confluence of oppositely directed currents in the central part of the Japan Sea.

  16. HI-CLASS on AEOS: A Large Aperture Laser Radar for Space Surveillance/ Situational Awareness Investigations

    National Research Council Canada - National Science Library

    Uroden, M

    2001-01-01

    ...) laser radar systems at MSSS. The paper reviews the first generation kilowatt class ladar/lidar HI-CLASS/LBD systems as the foundation for a second-generation ladar system that was developed under the AFRL/DE ALVA program...

  17. Coherent laser radar with dual-frequency Doppler estimation and interferometric range detection

    NARCIS (Netherlands)

    Onori, D.; Scotti, F.; Laghezza, F.; Scaffardi, M.; Bogoni, A.

    2016-01-01

    The concept of a coherent interferometric dual frequency laser radar, that measures both the target range and velocity, is presented and experimentally demonstrated. The innovative architecture combines the dual frequency lidar concept, allowing a precise and robust Doppler estimation, with the

  18. Tentative detection of clear-air turbulence using a ground-based Rayleigh lidar.

    Science.gov (United States)

    Hauchecorne, Alain; Cot, Charles; Dalaudier, Francis; Porteneuve, Jacques; Gaudo, Thierry; Wilson, Richard; Cénac, Claire; Laqui, Christian; Keckhut, Philippe; Perrin, Jean-Marie; Dolfi, Agnès; Cézard, Nicolas; Lombard, Laurent; Besson, Claudine

    2016-05-01

    Atmospheric gravity waves and turbulence generate small-scale fluctuations of wind, pressure, density, and temperature in the atmosphere. These fluctuations represent a real hazard for commercial aircraft and are known by the generic name of clear-air turbulence (CAT). Numerical weather prediction models do not resolve CAT and therefore provide only a probability of occurrence. A ground-based Rayleigh lidar was designed and implemented to remotely detect and characterize the atmospheric variability induced by turbulence in vertical scales between 40 m and a few hundred meters. Field measurements were performed at Observatoire de Haute-Provence (OHP, France) on 8 December 2008 and 23 June 2009. The estimate of the mean squared amplitude of bidimensional fluctuations of lidar signal showed excess compared to the estimated contribution of the instrumental noise. This excess can be attributed to atmospheric turbulence with a 95% confidence level. During the first night, data from collocated stratosphere-troposphere (ST) radar were available. Altitudes of the turbulent layers detected by the lidar were roughly consistent with those of layers with enhanced radar echo. The derived values of turbulence parameters Cn2 or CT2 were in the range of those published in the literature using ST radar data. However, the detection was at the limit of the instrumental noise and additional measurement campaigns are highly desirable to confirm these initial results. This is to our knowledge the first successful attempt to detect CAT in the free troposphere using an incoherent Rayleigh lidar system. The built lidar device may serve as a test bed for the definition of embarked CAT detection lidar systems aboard airliners.

  19. Understanding radar systems

    CERN Document Server

    Kingsley, Simon

    1999-01-01

    What is radar? What systems are currently in use? How do they work? This book provides engineers and scientists with answers to these critical questions, focusing on actual radar systems in use today. It is a perfect resource for those just entering the field, or as a quick refresher for experienced practitioners. The book leads readers through the specialized language and calculations that comprise the complex world of radar engineering as seen in dozens of state-of-the-art radar systems. An easy to read, wide ranging guide to the world of modern radar systems.

  20. Pulse Doppler radar

    CERN Document Server

    Alabaster, Clive

    2012-01-01

    This book is a practitioner's guide to all aspects of pulse Doppler radar. It concentrates on airborne military radar systems since they are the most used, most complex, and most interesting of the pulse Doppler radars; however, ground-based and non-military systems are also included. It covers the fundamental science, signal processing, hardware issues, systems design and case studies of typical systems. It will be a useful resource for engineers of all types (hardware, software and systems), academics, post-graduate students, scientists in radar and radar electronic warfare sectors and milit

  1. Observations of movement dynamics of flying insects using high resolution lidar

    DEFF Research Database (Denmark)

    Kirkeby, Carsten Thure; Wellenreuther, Maren; Brydegaard, Mikkel

    2016-01-01

    insects (wing size cross-section) moved across the field and clustered near the light trap around 22:00 local time, while larger insects (wing size >2.5 mm2 in cross-section) were most abundant near the lidar beam before 22:00 and then moved towards the light trap between 22:00 and 23:30. We......Insects are fundamental to ecosystem functioning and biodiversity, yet the study of insect movement, dispersal and activity patterns remains a challenge. Here we present results from a novel high resolution laser-radar (lidar) system for quantifying flying insect abundance recorded during one...

  2. Lidar: air pollution applications

    International Nuclear Information System (INIS)

    Collis, R.T.H.

    1977-01-01

    This introduction to the use of lidar in air pollution applications is mainly concerned with its capability to detect and monitor atmospheric particulates by elastic backscattering. Even when quite imperceptible to the eye, such particulates may be detected at ranges of several kilometers even by lidars of modest performance. This capability is valuable in connection with air pollution in the following ways: by mapping and tracking inhomogeneities in particulate concentration, atmospheric structure and motion may be monitored; measurements of the optical properties of the atmosphere provide an indication of turbidity or of particulate number or mass concentrations; and the capability of obtaining at a single point return signals from remote atmospheric volumes makes it possible to make range-resolved measurements of gaseous concentration along the path by using the resonant absorption of energy of appropriate wavelengths

  3. Quantitative determination of optical aerosol properties with lidar at 0.53 and 1.06 mum wavelength

    NARCIS (Netherlands)

    Salemink H; Schotanus P; Bergwerff J; van der Meulen A

    1984-01-01

    Beschreven wordt de kwantitatieve detectie van aerosol in de atmosferische grenslaag tot een hoogte van 1,5 km (remote sensing m.b.v. laser-radar). Voor optische aerosol-eigenschappen wordt goede overeenkomst gevonden tussen lidar (remote) en lokale waarnemingen in vliegtuig en op grondniveau.

  4. VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Octariady

    2017-05-01

    Full Text Available Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

  5. Let’s agree on the casing of Lidar

    Science.gov (United States)

    Deering, Carol; Stoker, Jason M.

    2014-01-01

    Is it lidar, Lidar, LiDAR, LIDAR, LiDar, LiDaR, or liDAR? A comprehensive review of the scientific/technical literature reveals seven different casings of this short form for light detection and ranging. And there could be more.

  6. Can Wind Lidars Measure Turbulence?

    DEFF Research Database (Denmark)

    Sathe, Ameya; Mann, Jakob; Gottschall, Julia

    2011-01-01

    Modeling of the systematic errors in the second-order moments of wind speeds measured by continuous-wave (ZephIR) and pulsed (WindCube) lidars is presented. These lidars use the conical scanning technique to measure the velocity field. The model captures the effect of volume illumination and coni...

  7. Surface detection performance evaluation of pseudo-random noise continuous wave laser radar

    Science.gov (United States)

    Mitev, Valentin; Matthey, Renaud; Pereira do Carmo, Joao

    2017-11-01

    A number of space missions (including in the ESA Exploration Programme) foreseen a use of laser radar sensor (or lidar) for determination of range between spacecrafts or between spacecraft and ground surface (altimetry). Such sensors need to be compact, robust and power efficient, at the same time with high detection performance. These requirements can be achieved with a Pseudo-Random Noise continuous wave lidar (PRN cw lidar). Previous studies have pointed to the advantages of this lidar with respect to space missions, but they also identified its limitations in high optical background. The progress of the lasers and the detectors in the near IR spectral range requires a re-evaluation of the PRN cw lidar potential. Here we address the performances of this lidar for surface detection (altimetry) in planetary missions. The evaluation is based on the following system configuration: (i) A cw fiber amplifier as lidar transmitter. The seeding laser exhibits a single-frequency spectral line, with subsequent amplitude modulation. The fiber amplifier allows high output power level, keeping the spectral characteristics and the modulation of the seeding light input. (ii) An avalanche photodiode in photon counting detection; (iii) Measurement scenarios representative for Earth, Mercury and Mars.

  8. Phased-array radar design application of radar fundamentals

    CERN Document Server

    Jeffrey, Thomas

    2009-01-01

    Phased-Array Radar Design is a text-reference designed for electrical engineering graduate students in colleges and universities as well as for corporate in-house training programs for radar design engineers, especially systems engineers and analysts who would like to gain hands-on, practical knowledge and skills in radar design fundamentals, advanced radar concepts, trade-offs for radar design and radar performance analysis.

  9. Doppler radar physiological sensing

    CERN Document Server

    Lubecke, Victor M; Droitcour, Amy D; Park, Byung-Kwon; Singh, Aditya

    2016-01-01

    Presents a comprehensive description of the theory and practical implementation of Doppler radar-based physiological monitoring. This book includes an overview of current physiological monitoring techniques and explains the fundamental technology used in remote non-contact monitoring methods. Basic radio wave propagation and radar principles are introduced along with the fundamentals of physiological motion and measurement. Specific design and implementation considerations for physiological monitoring radar systems are then discussed in detail. The authors address current research and commercial development of Doppler radar based physiological monitoring for healthcare and other applications.

  10. Radar Signature Calculation Facility

    Data.gov (United States)

    Federal Laboratory Consortium — FUNCTION: The calculation, analysis, and visualization of the spatially extended radar signatures of complex objects such as ships in a sea multipath environment and...

  11. LIDAR COMBINED SCANNING UNIT

    Directory of Open Access Journals (Sweden)

    V. V. Elizarov

    2016-11-01

    Full Text Available Subject of Research. The results of lidar combined scanning unit development for locating leaks of hydrocarbons are presented The unit enables to perform high-speed scanning of the investigated space in wide and narrow angle fields. Method. Scanning in a wide angular field is produced by one-line scanning path by means of the movable aluminum mirror with a frequency of 20Hz and amplitude of 20 degrees of swing. Narrowband scanning is performed along a spiral path by the deflector. The deflection of the beam is done by rotation of the optical wedges forming part of the deflector at an angle of ±50. The control function of the scanning node is performed by a specialized software product written in C# programming language. Main Results. This scanning unit allows scanning the investigated area at a distance of 50-100 m with spatial resolution at the level of 3 cm. The positioning accuracy of the laser beam in space is 15'. The developed scanning unit gives the possibility to browse the entire investigated area for the time not more than 1 ms at a rotation frequency of each wedge from 50 to 200 Hz. The problem of unambiguous definition of the beam geographical coordinates in space is solved at the software level according to the rotation angles of the mirrors and optical wedges. Lidar system coordinates are determined by means of GPS. Practical Relevance. Development results open the possibility for increasing the spatial resolution of scanning systems of a wide range of lidars and can provide high positioning accuracy of the laser beam in space.

  12. Making lidar more photogenic: creating band combinations from lidar information

    Science.gov (United States)

    Stoker, Jason M.

    2010-01-01

    Over the past five to ten years the use and applicability of light detection and ranging (lidar) technology has increased dramatically. As a result, an almost exponential amount of lidar data is being collected across the country for a wide range of applications, and it is currently the technology of choice for high resolution terrain model creation, 3-dimensional city and infrastructure modeling, forestry and a wide range of scientific applications (Lin and Mills, 2010). The amount of data that is being delivered across the country is impressive. For example, the U.S. Geological Survey’s (USGS) Center for Lidar Information Coordination and Knowledge (CLICK), which is a National repository of USGS and partner lidar point cloud datasets (Stoker et al., 2006), currently has 3.5 percent of the United States covered by lidar, and has approximately another 5 percent in the processing queue. The majority of data being collected by the commercial sector are from discrete-return systems, which collect billions of lidar points in an average project. There are also a lot of discussions involving a potential National-scale Lidar effort (Stoker et al., 2008).

  13. Balloonborne lidar experiment

    Science.gov (United States)

    Shepherd, O.; Aurilio, G.; Bucknam, R. D.; Brooke, R. W.; Hurd, A. G.

    1980-12-01

    The object of this contract was to design a balloonborne lidar experiment capable of performing nightime atmospheric density measurements in the 10 to 40 km altitude domain with a resolution of 100 meters. The payload includes a frequency-tripled Nd:YAG laser with outputs at 353 and 1064 nm, a telescoped receiver with PMT detectors, a command-controlled optical pointing system, and support systems, including thermal control, telemetry, command, and power. Density measurements would be made using the back-scattered 353 nm radiation data with aerosol corrections obtained from 1064 nm radiation scatterings.

  14. Compressive full waveform lidar

    Science.gov (United States)

    Yang, Weiyi; Ke, Jun

    2017-05-01

    To avoid high bandwidth detector, fast speed A/D converter, and large size memory disk, a compressive full waveform LIDAR system, which uses a temporally modulated laser instead of a pulsed laser, is studied in this paper. Full waveform data from NEON (National Ecological Observatory Network) are used. Random binary patterns are used to modulate the source. To achieve 0.15 m ranging resolution, a 100 MSPS A/D converter is assumed to make measurements. SPIRAL algorithm with canonical basis is employed when Poisson noise is considered in the low illuminated condition.

  15. NOAA Geotiff - 5 meter LiDAR Reflectivity, U.S. Caribbean - Puerto Rico (southwest) - Projects OPR-I305-KRL-06, (2006), UTM 19N NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) intensity mosaic (mean 5 meter gridded) from the shoreline of southwestern Puerto Rico to about 50...

  16. NOAA Geotiff - 5 meter LiDAR Reflectivity, U.S. Caribbean - Puerto Rico (southwest) - Projects OPR-I305-KRL-06, (2006), UTM 19N NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection and Ranging) intensity mosaic (mean 5 meter gridded) from the shoreline of southwestern Puerto Rico to about 50 meters...

  17. NOAA Geotiff - 4 meter LiDAR bathymetry, U.S. Caribbean - Puerto Rico (southwest) - Projects OPR-I305-KRL-06, (2006), UTM 19N NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection and Ranging) bathymetric mosaic (mean 4 meter gridded) collected along the coastline of southwestern Puerto Rico. The...

  18. NOAA Geotiff - 4 meter LiDAR bathymetry, U.S. Caribbean - Puerto Rico (southwest) - Projects OPR-I305-KRL-06, (2006), UTM 19N NAD83

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) bathymetric mosaic (mean 4 meter gridded) collected along the coastline of southwestern Puerto Rico....

  19. March 2007 Scripps Institute of Oceanography (SIO) Lidar of the Southern California Coastline: Long Beach to the US/Mexico Border

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This lidar point data set was collected during low tide conditions along an approximately 500-700 meter wide strip of the Southern California coastline within an...

  20. 2005-2006 Southwest Florida Water Management District (SWFWMD) Lidar: Polk County (Including Hampton, Judy, Lake Wales, Peace River (North), and Polk District Remainder Tracts)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is one component of a digital terrain model (DTM) for the SWFWMD Polk District. This record includes information about the LiDAR data for the following...