Next Article in Journal
A Sequential Optimization Calibration Algorithm for Near-Field Source Localization
Previous Article in Journal
Study of a Compression-Molding Process for Ultraviolet Light-Emitting Diode Exposure Systems via Finite-Element Analysis
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1404; doi:10.3390/s17061404

Hyperspectral IASI L1C Data Compression

Department of Information and Communications Engineering, Universitat Autònoma de Barcelona, 08193 Bellaterra, Spain
*
Author to whom correspondence should be addressed.
Received: 20 March 2017 / Revised: 8 June 2017 / Accepted: 9 June 2017 / Published: 16 June 2017
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [45593 KB, uploaded 16 June 2017]   |  

Abstract

The Infrared Atmospheric Sounding Interferometer (IASI), implemented on the MetOp satellite series, represents a significant step forward in atmospheric forecast and weather understanding. The instrument provides infrared soundings of unprecedented accuracy and spectral resolution to derive humidity and atmospheric temperature profiles, as well as some of the chemical components playing a key role in climate monitoring. IASI collects rich spectral information, which results in large amounts of data (about 16 Gigabytes per day). Efficient compression techniques are requested for both transmission and storage of such huge data. This study reviews the performance of several state of the art coding standards and techniques for IASI L1C data compression. Discussion embraces lossless, near-lossless and lossy compression. Several spectral transforms, essential to achieve improved coding performance due to the high spectral redundancy inherent to IASI products, are also discussed. Illustrative results are reported for a set of 96 IASI L1C orbits acquired over a full year (4 orbits per month for each IASI-A and IASI-B from July 2013 to June 2014) . Further, this survey provides organized data and facts to assist future research and the atmospheric scientific community. View Full-Text
Keywords: IASI instrument; hyperspectral remote sensing; data compression; lossless; near-lossless and lossy compression IASI instrument; hyperspectral remote sensing; data compression; lossless; near-lossless and lossy compression
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

García-Sobrino, J.; Serra-Sagristà, J.; Bartrina-Rapesta, J. Hyperspectral IASI L1C Data Compression. Sensors 2017, 17, 1404.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top