Lab Fellow Ben Roberts-Pierel highlights his favorite data exploration tools
MODIS data are commonly used for snow cover studies because of the available daily temporal resolution and, therefore, the potential to capture a highly dynamic environment. However, clouds pose a major problem for MODIS. This has traditionally been dealt with by temporal or spatial adjacency gap-filling but has been done largely ad hoc by researchers in post-processing.
I recently attended the American Association of Geographers (AAG) Annual Meeting and in my session at Dr. Dorothy Hall of Goddard Space Flight Center, one of the original researchers on the MODIS snow cover products, presented validation results for the newest version of the MODIS daily snow cover products, Version 6.1, which will be available around June of this year. The dataset will have a built-in ‘uncertainty band’ that allows the user to select how far back in time they want to use data to gap-fill. These data will be a welcome resource and will negate some of the diverse post-processing approaches utilized by many different researchers.
For more information on the project, interested researchers should see: https://modis-snow-ice.gsfc.nasa.gov/