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Special Issue "Sea Surface Temperature Retrievals from Remote Sensing"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: 20 November 2017

Special Issue Editors

Guest Editor
Dr. Jorge Vazquez

Jet Propulsion Laboratory, Pasadena, CA 91109, USA
Website | E-Mail
Interests: remote sensing; physical oceanography; coastal dynamics; high resolution; validation; climate applications
Guest Editor
Dr. Xiaofeng Li

National Oceanic and Atmospheric Administration, NCWCP E/RA3, 5830 University Research Ct. Office #3216, College Park, MD 20740-3818, USA
Website | E-Mail
Phone: +1-301-683-3314
Interests: ocean remote sensing; physical oceanography; boundary layer meteorology; synthetic aperture radar imaging mechanism; multiple-polarization radar applications; satellite image classification and segmentation

Special Issue Information

Dear Colleagues,

We are actively seeking contributions to a Special Issue of Remote Sensing on “Sea Surface Temperature (SST) Retrievals from Remote Sensing." SSTs are currently retrieved from infrared sensors on both polar orbiting and geostationary platforms, as well as from microwave sensors. Infrared sensors have the advantage of retrievals at higher resolutions, but are limited to cloud free conditions, while microwave sensors are lower resolution, but essentially provide all weather retrievals. Geostationary satellites have the advantage of essentially viewing the same area on the Earth continuously, thus improving coverage.

Overview papers that address the current state of SST retrievals, from both infrared and microwave sensors, are encouraged. SST sensors, such as the Visible Infrared Imaging Radiometer Suite (VIIRS), provide, for the first time, a sub-kilometer resolution. Papers that address the accuracy of SST retrievals at these higher resolutions are encouraged.

Another important area is the application of quality information to SST retrievals. Papers that address, especially in coastal areas, the impact of quality flags on accuracy and coverage are also encouraged.

Thank you in advance for your consideration of a timely and important contribution to our state of knowledge of SST retrievals from satellites.

Dr. Jorge Vazquez
Dr. Xiaofeng Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Remote Sensing
  • Sea Surface Temperature
  • Infrared
  • Microwave
  • Accuracy

Published Papers (1 paper)

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Research

Open AccessArticle Evaluation of the Multi-Scale Ultra-High Resolution (MUR) Analysis of Lake Surface Temperature
Remote Sens. 2017, 9(7), 723; doi:10.3390/rs9070723
Received: 25 May 2017 / Revised: 30 June 2017 / Accepted: 7 July 2017 / Published: 13 July 2017
PDF Full-text (5576 KB) | HTML Full-text | XML Full-text
Abstract
Obtaining accurate and timely lake surface water temperature (LSWT) analyses from satellite remains difficult. Data gaps, cloud contamination, variations in atmospheric profiles of temperature and moisture, and a lack of in situ observations provide challenges for satellite-derived LSWT for climatological analysis or input
[...] Read more.
Obtaining accurate and timely lake surface water temperature (LSWT) analyses from satellite remains difficult. Data gaps, cloud contamination, variations in atmospheric profiles of temperature and moisture, and a lack of in situ observations provide challenges for satellite-derived LSWT for climatological analysis or input into geophysical models. In this study, the Multi-scale Ultra-high Resolution (MUR) analysis of LSWT is evaluated between 2007 and 2015 over a small (Lake Oneida), medium (Lake Okeechobee), and large (Lake Michigan) lake. The advantages of the MUR LSWT analyses include daily consistency, high-resolution (~1 km), near-real time production, and multi-platform data synthesis. The MUR LSWT versus in situ measurements for Lake Michigan (Lake Okeechobee) have an overall bias (MUR LSWT-in situ) of −0.20 °C (0.31 °C) and a RMSE of 0.86 °C (0.91 °C). The MUR LSWT versus in situ measurements for Lake Oneida have overall large biases (−1.74 °C) and RMSE (3.42°C) due to a lack of available satellite imagery over the lake, but performs better during the less cloudy 15 July–30 September period. The results of this study highlight the importance of calculating validation statistics on a seasonal and annual basis for evaluating satellite-derived LSWT. Full article
(This article belongs to the Special Issue Sea Surface Temperature Retrievals from Remote Sensing)
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