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Remote Sens. 2016, 8(12), 1015; doi:10.3390/rs8121015

Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager

1
Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ 08028, USA
2
NOAA Cooperative Remote Sensing Science and Technology Center (CREST), City University of New York, New York, NY 10031, USA
3
National Oceanic and Atmospheric Administration (NOAA), 1225 West Dayton St., Madison, WI 53706, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Xiaofeng Li and Prasad S. Thenkabail
Received: 8 September 2016 / Revised: 3 November 2016 / Accepted: 28 November 2016 / Published: 11 December 2016
View Full-Text   |   Download PDF [22322 KB, uploaded 20 December 2016]   |  

Abstract

An automated ice-mapping algorithm has been developed and evaluated using data from the GOES-13 imager. The approach includes cloud-free image compositing as well as image classification using spectral criteria. The algorithm uses an alternative snow index to the Normalized Difference Snow Index (NDSI). The GOES-13 imager does not have a 1.6 µm band, a requirement for NDSI; however, the newly proposed Mid-Infrared Sea and Lake Ice Index (MISI) incorporates the reflective component of the 3.9 µm or mid-infrared (MIR) band, which the GOES-13 imager does operate. Incorporating MISI into a sea or lake ice mapping algorithm allows for mapping of thin or broken ice with no snow cover (nilas, frazil ice) and thicker ice with snow cover to a degree of confidence that is comparable to other ice mapping products. The proposed index has been applied over the Great Lakes region and qualitatively compared to the Interactive Multi-sensor Snow and Ice Mapping System (IMS), the National Ice Center ice concentration maps and MODIS snow cover products. The application of MISI may open additional possibilities in climate research using historical GOES imagery. Furthermore, MISI may be used in addition to the current NDSI in ice identification to build more robust ice-mapping algorithms for the next generation GOES satellites. View Full-Text
Keywords: sea ice concentration; shortwave infrared; GOES imager; remote sensing sea ice concentration; shortwave infrared; GOES imager; remote sensing
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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).

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MDPI and ACS Style

Dorofy, P.; Nazari, R.; and, P.R.; Key, J. Development of a Mid-Infrared Sea and Lake Ice Index (MISI) Using the GOES Imager. Remote Sens. 2016, 8, 1015.

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