Paper
18 October 2016 Image navigation and registration for the geostationary lightning mapper (GLM)
Roel W. H. van Bezooijen, Howard Demroff, Gregory Burton, Donald Chu, Shu S. Yang
Author Affiliations +
Proceedings Volume 10004, Image and Signal Processing for Remote Sensing XXII; 100041N (2016) https://doi.org/10.1117/12.2242141
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom
Abstract
The Geostationary Lightning Mappers (GLM) for the Geostationary Operational Environmental Satellite (GOES) GOES-R series will, for the first time, provide hemispherical lightning information 24 hours a day from longitudes of 75 and 137 degrees west. The first GLM of a series of four is planned for launch in November, 2016. Observation of lightning patterns by GLM holds promise to improve tornado warning lead times to greater than 20 minutes while halving the present false alarm rates. In addition, GLM will improve airline traffic flow management, and provide climatology data allowing us to understand the Earth’s evolving climate.

The paper describes the method used for translating the pixel position of a lightning event to its corresponding geodetic longitude and latitude, using the J2000 attitude of the GLM mount frame reported by the spacecraft, the position of the spacecraft, and the alignment of the GLM coordinate frame relative to its mount frame. Because the latter alignment will experience seasonal variation, this alignment is determined daily using GLM background images collected over the previous 7 days. The process involves identification of coastlines in the background images and determination of the alignment change necessary to match the detected coastline with the coastline predicted using the GSHHS database.

Registration is achieved using a variation of the Lucas-Kanade algorithm where we added a dither and average technique to improve performance significantly. An innovative water mask technique was conceived to enable self-contained detection of clear coastline sections usable for registration. Extensive simulations using accurate visible images from GOES13 and GOES15 have been used to demonstrate the performance of the coastline registration method, the results of which are presented in the paper.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roel W. H. van Bezooijen, Howard Demroff, Gregory Burton, Donald Chu, and Shu S. Yang "Image navigation and registration for the geostationary lightning mapper (GLM)", Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 100041N (18 October 2016); https://doi.org/10.1117/12.2242141
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image processing

Image registration

Clouds

Edge detection

Dysprosium

Nano opto mechanical systems

Charge-coupled devices

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