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Special Issue "Ocean Remote Sensing"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 August 2009)

Special Issue Editor

Guest Editor
Dr. James H. Churnside

Ocean Remote Sensing Working Group, NOAA Earth System Research Laboratory, CSD3, 325 Broadway, Boulder, Colorado 80305-3328, USA
Website | E-Mail
Phone: 1-303-497-6744
Interests: oceanography; climate; remote sensing; sonar; radar; lidar; radiometry; ocean color

Special Issue Information

The ocean covers three quarters of the surface of this planet, and is a major factor affecting conditions here. Life originated in the ocean, and continues because of the ocean’s affects on climate. It is also important for transportation, recreation, and resources that include food and pharmaceuticals. Despite this, no one can argue that the ocean is well understood. Measurements are very difficult, and remote sensing will have to play an increasing role in all aspects of ocean science. Important sensors include optical imagers and acoustics on submsersibles and surface ships; LIDAR, radar, multi- and hyper-spectral imagers, and optical and microwave radiometers on aircraft; and optical and microwave imagers and radiometers on satellites. Inferred quantities include ocean surface winds, sea-surface temperature and salinity, sea surface height, ocean color, bathymetry, and distribution and abundance of biota. This special issue attempts to bring together a wide variety of papers on the sensor technology and applications of ocean remote sensing.

Keywords

  • Oceanography
  • Climate
  • Remote Sensing
  • Sonar
  • Radar
  • Lidar
  • Radiometry
  • Ocean Color

Related special issue in Sensors journal: http://www.mdpi.com/journal/sensors/special_issues/ocean-remote-sensing

Published Papers (2 papers)

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Research

Open AccessArticle Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery
Remote Sens. 2012, 4(12), 3638-3665; doi:10.3390/rs4123638
Received: 7 September 2012 / Revised: 14 November 2012 / Accepted: 16 November 2012 / Published: 22 November 2012
Cited by 5 | PDF Full-text (1623 KB) | HTML Full-text | XML Full-text
Abstract
We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite ocean color imagery are related to a
[...] Read more.
We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite ocean color imagery are related to a variety of factors, including errors associated with sensor calibration, atmospheric correction, and the bio-optical inversion algorithms. In many cases, selection of an inappropriate or erroneous aerosol model during atmospheric correction can dominate the errors in the satellite estimation of the normalized water-leaving radiances (nLw), especially over turbid, coastal waters. These errors affect the downstream bio-optical properties. Here, we focus on the impact of aerosol model selection on the nLw radiance estimates by comparing Aerosol Robotic Network-Ocean Color (AERONET-OC) measurements of nLw and aerosol optical depth (AOD) to satellite-derived values from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We also apply noise to the satellite top-of-atmosphere (TOA) radiance values in the two near-infrared (NIR) wavelengths used for atmospheric correction, to assess the effect on aerosol model selection and nLw retrievals. In general, for the data sets examined, we found that as little as 1% uncertainty (noise) in the NIR TOA radiances can lead to the selection of a different pair of bounding aerosol models, thus changing nLw retrievals. We also compare aerosol size fraction retrieved from AERONET and size fraction represented by aerosol models selected during atmospheric correction. Full article
(This article belongs to the Special Issue Ocean Remote Sensing)
Open AccessArticle HF Radar Bistatic Measurement of Surface Current Velocities: Drifter Comparisons and Radar Consistency Checks
Remote Sens. 2009, 1(4), 1190-1211; doi:10.3390/rs1041190
Received: 26 October 2009 / Revised: 5 November 2009 / Accepted: 27 November 2009 / Published: 1 December 2009
Cited by 12 | PDF Full-text (872 KB) | HTML Full-text | XML Full-text
Abstract
We describe the operation of a bistatic HF radar network and outline analysis methods for the derivation of the elliptical velocity components from the radar echo spectra. Bistatic operation is illustrated by application to a bistatic pair: Both remote systems receive backscattered echo,
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We describe the operation of a bistatic HF radar network and outline analysis methods for the derivation of the elliptical velocity components from the radar echo spectra. Bistatic operation is illustrated by application to a bistatic pair: Both remote systems receive backscattered echo, with one remote system in addition receiving bistatic echoes transmitted by the other. The pair produces elliptical velocity components in addition to two sets of radials. Results are compared with drifter measurements and checks performed on internal consistency in the radar results. We show that differences in drifter/radar current velocities are consistent with calculated radar data uncertainties. Elliptical and radial velocity components are demonstrated to be consistent within the data uncertainties. Inclusion of bistatic operation in radar networks can be expected to increase accuracy in derived current velocities and extend the coverage area. Full article
(This article belongs to the Special Issue Ocean Remote Sensing)
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