Mars Reconnaissance Orbiter's Mars Color Imager (MARCI): A New Workflow for Processing Its Image Data

The Mars Reconnaissance Orbiter's (MRO's) Mars Color Imager (MARCI) has returned approximately daily, approximately global image data of Mars since late 2006, in up to seven different colors, from ultraviolet through near-infrared. To-date, that is over 5,300 Mars days of data, nearly eight full Mars Years, or more than 15 Earth years. The data are taken at up to nearly 500 m per pixel, and the nearly circular orbit of MRO and its consistent early afternoon imaging provide an unprecedented baseline of data with which to study Mars' atmosphere and surface processes. Unfortunately, processing MARCI data is difficult, fraught with exploding file sizes, issues that require work-arounds in free software, and other problems that make this a severely under-utilized data set. This article discusses a workflow to process MARCI data to their fullest, including suggestions on how to work around issues unique to MARCI and how the data work with the current version of the free software ISIS (Integrated Software for Imagers and Spectrometers). Discussion of some trades that can be made to dramatically speed data processing are also described. Examples of processed MARCI images, mosaics, and color composites are shown, demonstrating the abilities of this workflow on global, regional, and local areas at the full, 96 pixels per degree scale afforded by MARCI. Plain Language Summary The first modern spacecraft to orbit Mars was NASA's Mars Global Surveyor, which had the Mars Orbiter Camera that-among other imaging capabilities-provided global, daily images of Mars at about 7 km per pixel from 1999 through 2006. Its successor is the Mars Color Imager, or MARCI, onboard NASA's Mars Reconnaissance Orbiter, which has been taking images since 2006. MARCI builds daily, global images by imaging a swath of Mars at up to 0.5 km per pixel, once per orbit, and it orbits Mars about 13 times per day. These swaths are taken in seven different colors ranging from ultraviolet to infrared. Because of how MARCI was built and how its images are taken, processing its images into both a scientifically and visually useful product is difficult. Thus, MARCI data are not widely used. This article presents a new workflow built on open tools to process the data, discussion on how to get around some processing difficulties, and illustrates the workflow's success by showing several examples of how MARCI can be used to show a dynamic world of huge cloud systems, small dust storms, and surface changes.