Automated tools to derive short-term glacier velocity from
high-resolution commercial satellite imagery
Abstract
Image feature tracking with medium-resolution optical satellite imagery
(e.g., Landsat-8) offers measurements of glacier surface velocity on a
global scale. However, for slow-moving glaciers (<0.1 m/day),
the larger pixel sizes (~15-30 m) and longer repeat
intervals (minimum of 16 days, assuming no cloud cover) limit temporal
sampling, often precluding analysis of sub-annual velocity variability.
As a result, detailed records of short-term glacier velocity variations
are limited to a subset of glaciers, often from dedicated SAR image
tasking and/or field observations. To address these issues, we are
leveraging large archives of very-high-resolution
(~0.3-0.5 m) DigitalGlobe WorldView/GeoEye imagery with
~monthly repeat interval and high-resolution
(~3-5 m) Planet PlanetScope imagery with
~daily-weekly repeat interval for the period from 2014
to 2019. We are using automated, open-source tools to develop
corrections for sensor geometry and image geolocation, and integrating
new, high resolution DEMs for improved orthorectification, reducing the
uncertainty of short-term (monthly to seasonal) velocity measurements.
These temporally dense records will be integrated with other velocity
products (e.g., NASA ITS_LIVE), which will allow us to study the
evolution of glacier dynamics, and its relationships with local
climatology, geomorphology, and hydrology on a regional scale. In this
study, we present initial results for surface velocity mapping for
glaciers in Khumbu Himalaya, Nepal and Mt. Rainier, USA. We are using
high-performance computing environments to scale this analysis to larger
glacierized regions in High Mountain Asia and Continental U.S.