Scalable satellite data processing methods for ICESat-2, optical stereo and SAR/InSAR to understand cryosphere change

Modern constellations of Earth observation satellites offer exciting opportunities to observe and understand cryosphere change with unprecedented spatial and temporal coverage, resolution, and accuracy. This ever-growing data firehose requires new scalable processing approaches to extract local, regional, and global results and actionable insights for downstream applications. Mulit-modal data fusion (e.g., integration of commercial very-high-resolution optical stereo, laser altimetry, and high-resolution SAR/InSAR) can capture mm- to meter-scale surface change, offering new insight for a range of geophysical processes responsible for cryosphere change.

We highlight a set of scalable, open-source satellite data processing tools and approaches for high-mountain cryosphere science applications, including:

1) Sliderule Earth - an open-source service for on-demand, parallel processing of science data archives in the cloud. SlideRule allows the user to create customized, high-level, analysis-ready data products in near-real-time. SlideRule currently supports a suite of data products and algorithms for the NASA ICESat-2 and GEDI satellite laser altimetry missions, as well as many cloud-hosted raster datasets (e.g., PGC ArcticDEM/REMA strips and mosaics, Harmonized Landsat-Sentinel, ESA WorldCover 10m, USGS 3DEP airborne lidar).

2) Intra- and interannual snow depth measurements from ICESat-2 satellite laser altimetry and commercial optical stereo

3) Global annual high-resolution snow melt runoff onset maps for the past decade from the cloud-hosted archive of radiometric terrain-corrected (RTC) Sentinel-1 SAR backscatter

4) Fused InSAR and SAR feature tracking to map debris-covered ice and evolving high-mountain hazards, including the seasonal and interannual motion of glacier lake moraine dams.

These satellite datasets and approaches offer an improved understanding of the processes driving recent cryosphere change, which is essential to improve the models used for future projections, and to understand connections with the hydrologic cycle.