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MOSAICKING MEXICO - THE BIG PICTURE OF BIG DATA
Author(s) -
Florian Hruby,
S. Melamed,
R. Ressl,
D. Stanley
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b2-407-2016
Subject(s) - computer science , mosaic , terabyte , cloud computing , orthophoto , preprocessor , computer graphics (images) , remote sensing , computer vision , artificial intelligence , geography , archaeology , operating system
The project presented in this article is to create a completely seamless and cloud-free mosaic of Mexico at a resolution of 5m, using approximately 4,500 RapidEye images. To complete this project in a timely manner and with limited operators, a number of processing architectures were required to handle a data volume of 12 terabytes. This paper will discuss the different operations realized to complete this project, which include, preprocessing, mosaic generation and post mosaic editing. Prior to mosaic generation, it was necessary to filter the 50,000 RapidEye images captured over Mexico between 2011 and 2014 to identify the top candidate images, based on season and cloud cover. Upon selecting the top candidate images, PCI Geomatics’ GXL system was used to reproject, color balance and generate seamlines for the output 1TB+ mosaic. This paper will also discuss innovative techniques used by the GXL for color balancing large volumes of imagery with substantial radiometric differences. Furthermore, post-mosaicking steps, such as, exposure correction, cloud and cloud shadow elimination will be presented.

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