Dr. Alan Weidemann Profile

Dr. Alan Weidemann

Oceanographer at US Naval Research Lab

SPIE Involvement:

Conference Program Committee | Author

Publications (40)

SPIE Journal Paper | March 29, 2017

Special Section Guest Editorial: Remote Sensing for Investigating the Coupled Biogeophysical and Biogeochemical Process of Harmful Algal Blooms

Chang, Ni-Bin , Weidemann, Alan

JARS Vol. 11 Issue 01

KEYWORDS: Remote sensing, Synthetic aperture radar, Water, Environmental sensing, LIDAR, Unmanned aerial vehicles, Clouds, Image fusion, Satellites, Analytical research

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PROCEEDINGS ARTICLE | October 16, 2013

Evaluation of ocean color data processing schemes for VIIRS sensor using in-situ data of coastal AERONET-OC sites

Proc. SPIE. 8888, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013

KEYWORDS: Avalanche photodetectors, MODIS, Sensors, Aerosols, Calibration, Satellites, Water, Ocean optics, Data processing, Atmospheric modeling

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In the processing of Ocean Color (OC) data from sensor data recorded by Visible Infrared Imaging Radiometer Suite (VIIRS) aboard JPSS-Suomi satellite, NASA Ocean Biology Processing Group (OBPG) is deriving a continuous temporal calibration based on the on-board calibration measurements for the visible bands, and then reprocessing the full mission to produce a continuously calibrated sensor data record (SDR) product. In addition, a vicarious calibration during SDR to OC Level-2 processing is applied. In the latest processing the vicarious calibration is derived from the Marine Optical Buoy (MOBY) data, whereas in the initial processing it was derived from a sea surface reflectance model and a climatology of chlorophyll-a concentration. Furthermore, NASA has recently reprocessed the OC data for the entire VIIRS mission with lunar-based temporal calibration and updated vicarious gains. On the other hand, in fulfilling the mission of the U.S. National Oceanic and Atmospheric Administration (NOAA), the Interface Data Processing Segment (IDPS) developed by Raytheon Intelligence and Information Systems, for the processing of the environmental data products from sensor data records, has gained beta status for evaluation. As these processing schemes continue to evolve, monitoring the validity and assessments of the related VIIRS ocean color products are necessary, especially for coastal waters, to evaluate the consistency of these processing and calibration schemes. The ocean color component of the Aerosol Robotic Network (AERONET-OC) has been designed to support long-term satellite ocean color investigations through cross-site measurements collected by autonomous multispectral radiometer systems deployed above water. As part of this network, the Long Island Sound Coastal Observatory (LISCO) near New York City and WaveCIS in the Gulf of Mexico expand those observational capabilities with continuous monitoring as well as (for the LISCO site) additional assessment of the hyper-spectral properties of coastal waters. In the investigations carried out over a one and half year period dataset of VIIRS, based on the data from two coastal AERONET-OC sites, it has been observed that the VIIRS sensor captures well the seasonal and temporal variations in the nLw data, exhibiting significant correlation with in-situ data (R = 0.929 and 0.985 for LISCO and WaveCIS respectively). For the WaveCIS site, VIIRS nLw data retrievals are seen to be enhanced with each incremental adjustments of vicarious and calibration procedures. However, that is not the case for the LISCO site which exhibits more frequent occurrences of negative water-leaving radiances, while underestimation in VIIRS nLw data is further exacerbated. Strong consistency between the time-series nLw data retrieved from the VIIRS and MODIS sensors was also observed.

PROCEEDINGS ARTICLE | June 3, 2013

Evaluation of VIIRS ocean color data using measurements from the AERONET-OC sites

Proc. SPIE. 8724, Ocean Sensing and Monitoring V

KEYWORDS: Avalanche photodetectors, Statistical analysis, MODIS, Sensors, Aerosols, Calibration, Satellites, Ocean optics, Atmospheric corrections, Data processing

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PROCEEDINGS ARTICLE | June 3, 2013

Bathymetry estimations using vicariously calibrated HICO data

Proc. SPIE. 8724, Ocean Sensing and Monitoring V

KEYWORDS: Near infrared, Sensors, Calibration, Remote sensing, Reflectivity, Atmospheric corrections, Data processing, Spatial resolution, In situ remote sensing, Absorption

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PROCEEDINGS ARTICLE | June 3, 2013

Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment

Proc. SPIE. 8724, Ocean Sensing and Monitoring V

KEYWORDS: Optical properties, Error analysis, Tongue, Ocean optics, Turbulence, Velocity measurements, Intelligence systems, Optical turbulence, Temperature metrology, Tin

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SPIE Journal Paper | December 5, 2012

Airborne lidar detection and characterization of internal waves in a shallow fjord

Churnside, James , Marchbanks, Richard , Lee, Jennifer , Shaw, Joseph , Weidemann, Alan , Donaghay, Percy

JRS Vol. 6 Issue 01

KEYWORDS: LIDAR, Scattering, Polarization, Wave propagation, Photography, Turbulence, Receivers, Dielectric polarization, Transmitters, Signal attenuation

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PROCEEDINGS ARTICLE | June 12, 2012

Bahamas Optical Turbulence Exercise (BOTEX): preliminary results

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: Imaging systems, Scattering, Sensors, Water, Particles, Ocean optics, High speed cameras, Turbulence, Image transmission, Optical turbulence

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The Bahamas Optical Turbulence Exercise (BOTEX) was conducted in the coastal waters of Florida and the Bahamas from June 30 to July 12 2011, onboard the R/V FG Walton Smith. The primary objective of the BOTEX was to obtain field measurements of optical turbulence structures, in order to investigate the impacts of the naturally occurring turbulence on underwater imaging and optical beam propagation. In order to successfully image through optical turbulence structures in the water and examine their impacts on optical transmission, a high speed camera and targets (both active and passive) were mounted on a rigid frame to form the Image Measurement Assembly for Subsurface Turbulence (IMAST). To investigate the impacts on active imaging systems such as the laser line scan (LLS), the Telescoping Rigid Underwater Sensor Structure (TRUSS) was designed and implemented by Harbor Branch Oceanographic Institute. The experiments were designed to determine the resolution limits of LLS systems as a function of turbulence induced beam wander at the target. The impact of natural turbulence structures on lidar backscatter waveforms was also examined, by means of a telescopic receiver and a short pulse transmitter, co-located, on a vertical profiling frame. To include a wide range of water types in terms of optical and physical conditions, data was collected from four different locations. . Impacts from optical turbulence were observed under both strong and weak physical structures. Turbulence measurements were made by two instruments, the Vertical Microstructure Profiler (VMP) and a 3D acoustical Doppler velocimeter with fast conductivity and temperature probes, in close proximity in the field. Subsequently these were mounted on the IMAST during moored deployments. The turbulence kinetic energy dissipation rate and the temperature dissipation rates were calculated from both setups in order to characterize the physical environments and their impacts. Beam deflection by multiple point patterns are examined, using high speed camera recordings (300 to 1200 fps), in association with measured turbulence structures. Initial results confirmed our hypothesis that turbulence impacted optical transmissions. They also showed that more research will be needed to better quantify and mitigate such effects, especially for the U.S. Navy's next generation EO systems, including active imaging, lidar and optical communications.

PROCEEDINGS ARTICLE | June 12, 2012

Scattered photons as useable signal for underwater imaging

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: Laser sources, Imaging systems, Scattering, Signal attenuation, Photons, Electrons, Laser scattering, Chromium, Receivers, Underwater imaging

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PROCEEDINGS ARTICLE | June 12, 2012

Evaluation of atmospheric correction procedures for ocean color data processing using hyper- and multi-spectral radiometric measurements from the Long Island Sound Coastal Observatory

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: MODIS, Sensors, Aerosols, Satellites, Reflectivity, Atmospheric corrections, Data processing, Atmospheric particles, Atmospheric modeling, Atmospheric optics

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PROCEEDINGS ARTICLE | June 12, 2012

Biological thin layers: history, ecological significance and consequences to oceanographic sensing systems

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: Defense and security, Backscatter, Imaging systems, Scattering, Particles, Organisms, Ocean optics, Sensing systems, Neodymium, Acoustics

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PROCEEDINGS ARTICLE | June 12, 2012

Airborne lidar sensing of internal waves in a shallow fjord

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: Telescopes, Polarization, Scattering, LIDAR, Light scattering, Mouth, Receivers, Wave propagation, Wave sensors, Analytical research

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PROCEEDINGS ARTICLE | October 8, 2011

Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory

Proc. SPIE. 8175, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2011

KEYWORDS: MODIS, Aerosols, Calibration, Satellites, Remote sensing, Ocean optics, Atmospheric corrections, Data processing, Atmospheric particles, Atmospheric optics

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PROCEEDINGS ARTICLE | October 8, 2011

Bidirectional reflectance function in coastal waters: modeling and validation

Proc. SPIE. 8175, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2011

KEYWORDS: Magnesium, Coastal modeling, Data modeling, Backscatter, Sensors, Water, Remote sensing, Reflectivity, Computer simulations, Bidirectional reflectance transmission function

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PROCEEDINGS ARTICLE | May 5, 2011

Quantifying turbulence microstructure for improvement of underwater imaging

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: Target detection, Scattering, Sensors, Water, Light scattering, Turbulence, Underwater imaging, Optical turbulence, Temperature metrology, Visibility

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PROCEEDINGS ARTICLE | May 5, 2011

Impacts of optical turbulence on underwater imaging

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: Optical transfer functions, Data modeling, Optical properties, Scattering, Water, Laser scattering, Turbulence, Modulation transfer functions, Underwater imaging, Optical turbulence

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PROCEEDINGS ARTICLE | May 5, 2011

Hyperspectral and multispectral above-water radiometric measurements to monitor satellite data quality over coastal area

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: MODIS, Sun, Sensors, Calibration, Satellites, Remote sensing, Reflectivity, Atmospheric corrections, Data processing, Radiometry

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SPIE Journal Paper | January 1, 2011

Ocean color patterns help to predict depth of optical layers in stratified coastal waters

Montes-Hugo, Martín , Weidemann, Alan , Gould, Richard , Arnone, Robert , Churnside, James , Jaroz, Ewa

JRS Vol. 5 Issue 1

KEYWORDS: Ocean optics, Water, Reflectivity, Optical properties, Remote sensing, Optical testing, Biomedical optics, Geometrical optics, Scattering, In situ metrology

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PROCEEDINGS ARTICLE | April 20, 2010

Glider optical measurements and BUFR format for data QC and storage

Proc. SPIE. 7678, Ocean Sensing and Monitoring II

KEYWORDS: Optical sensors, Data modeling, Sensors, Data storage, Remote sensing, Optical testing, Ocean optics, Algorithm development, Environmental sensing, Binary data

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PROCEEDINGS ARTICLE | May 7, 2009

Defining the uncertainty of electro-optical identification system performance estimates using a 3D optical environment derived from satellite

Proc. SPIE. 7317, Ocean Sensing and Monitoring

KEYWORDS: 3D acquisition, Optical properties, Sensors, Satellites, 3D modeling, Ocean optics, Image quality, 3D metrology, Electro optical modeling, 3D image processing

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PROCEEDINGS ARTICLE | April 29, 2009

Polarization characteristics of coastal waters and their impact on in-water visibility

Proc. SPIE. 7317, Ocean Sensing and Monitoring

KEYWORDS: Point spread functions, Submerged target modeling, Polarization, Scattering, Cameras, Light scattering, Polarizers, Ocean optics, Monte Carlo methods, Visibility

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PROCEEDINGS ARTICLE | April 29, 2009

Diver visibility: Why one cannot see as far?

Proc. SPIE. 7317, Ocean Sensing and Monitoring

KEYWORDS: Optical transfer functions, Visual process modeling, Data modeling, Modulation, Spatial frequencies, Scattering, Particles, Turbulence, Underwater imaging, Visibility

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SPIE Journal Paper | December 1, 2007

Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform

Lee, Zhongping , Casey, Brandon , Arnone, Robert , Weidemann, Alan , Parsons, Rost , Montes, Marcos , Gao, Bo-Cai , Goode, Wesley , Davis, Curtiss , Dye, Julie

JRS Vol. 1 Issue 01

KEYWORDS: Water, LIDAR, Sensors, Reflectivity, Absorption, Sun, Remote sensing, In situ metrology, Environmental sensing, Atmospheric corrections

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PROCEEDINGS ARTICLE | September 24, 2007

Imagery-derived modulation transfer function and its applications for underwater imaging

Proc. SPIE. 6696, Applications of Digital Image Processing XXX

KEYWORDS: Signal to noise ratio, Point spread functions, Polarization, Optical properties, Imaging systems, Spatial frequencies, Scattering, Cameras, Modulation transfer functions, Absorption

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The main challenge working with underwater imagery results from both rapid decay of signals due to absorption, which leads to poor signal to noise returns, and the blurring caused by strong scattering by the water itself and constituents within, especially particulates. The modulation transfer function (MTF) of an optical system gives the detailed and precise information regarding the system behavior. Underwater imageries can be better restored with the knowledge of the system MTF or the point spread function (PSF), the Fourier transformed equivalent, extending the performance range as well as the information retrieval from underwater electro-optical system. This is critical in many civilian and military applications, including target and especially mine detection, search and rescue, and diver visibility. This effort utilizes test imageries obtained by the Laser Underwater Camera Imaging Enhancer (LUCIE) from Defense Research and Development Canada (DRDC), during an April-May 2006 trial experiment in Panama City, Florida. Imaging of a standard resolution chart with various spatial frequencies were taken underwater in a controlled optical environment, at varying distances. In-water optical properties during the experiment were measured, which included the absorption and attenuation coefficients, particle size distribution, and volume scattering function. Resulting images were preprocessed to enhance signal to noise ratio by averaging multiple frames, and to remove uneven illumination at target plane. The MTF of the medium was then derived from measurement of above imageries, subtracting the effect of the camera system. PSFs converted from the measured MTF were then used to restore the blurred imageries by different deconvolution methods. The effects of polarization from source to receiver on resulting MTFs were examined and we demonstrate that matching polarizations do enhance system transfer functions. This approach also shows promise in deriving medium optical properties including absorption and attenuation.

PROCEEDINGS ARTICLE | April 25, 2007

Objectively assessing underwater image quality for the purpose of automated restoration

Proc. SPIE. 6575, Visual Information Processing XVI

KEYWORDS: Signal to noise ratio, Edge detection, Wavelet transforms, Image compression, Scattering, Wavelets, Image restoration, Image quality, Image enhancement, Modulation transfer functions

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PROCEEDINGS ARTICLE | April 13, 2007

Restoring number of suspended particles in ocean using satellite optical images and forecasting particle fields

Proc. SPIE. 6615, Current Research on Remote Sensing, Laser Probing, and Imagery in Natural Waters

KEYWORDS: Refractive index, Backscatter, Scattering, Satellites, Water, Particles, Remote sensing, Ocean optics, Satellite imaging, Earth observing sensors

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PROCEEDINGS ARTICLE | August 23, 2005

Measurement of ocean water optical properties and seafloor reflectance with scanning hydrographic operational airborne lidar survey (SHOALS): II. Practical results and comparison with independent data

Proc. SPIE. 5885, Remote Sensing of the Coastal Oceanic Environment

KEYWORDS: Avalanche photodetectors, Optical properties, Scattering, LIDAR, Signal attenuation, Calibration, Water, Reflectivity, Receivers, Pulsed laser operation

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PROCEEDINGS ARTICLE | June 1, 2005

Megacollect 2004: hyperspectral collection experiment over the waters of the Rochester Embayment

Proc. SPIE. 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI

KEYWORDS: Data modeling, Optical properties, Sensors, Water, Particles, Remote sensing, Light scattering, Optical testing, Absorption filters, Absorption

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PROCEEDINGS ARTICLE | May 25, 2005

Development, validation, and fusion of high resolution active and passive optical imagery

Proc. SPIE. 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV

KEYWORDS: Signal to noise ratio, LIDAR, Sensors, Calibration, Databases, Water, Error analysis, Reflectivity, Ocean optics, Data fusion

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PROCEEDINGS ARTICLE | May 19, 2005

In harbor underwater threat detection/identification using active imaging

Proc. SPIE. 5780, Photonics for Port and Harbor Security

KEYWORDS: Eye, Polarization, Imaging systems, Scattering, Cameras, Particles, Image enhancement, Zoom lenses, Visibility, Absorption

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PROCEEDINGS ARTICLE | October 28, 1999

Meeting Navy needs with the generic lidar model

Proc. SPIE. 3761, Airborne and In-Water Underwater Imaging

KEYWORDS: Imaging systems, Spatial frequencies, Scattering, LIDAR, Signal attenuation, Receivers, Ocean optics, Laser scanners, Modulation transfer functions, 3D scanning

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PROCEEDINGS ARTICLE | February 6, 1997

Field evaluation of antibiofouling compounds on optical instrumentation