1. Global Earth Science Community
  2. Community Data System Programs
  3. ACCESS Projects
  4. Advanced Discovery, Processing, and Visualization Services for ICESat and ICESat-2 Altimeter Data

Advanced Discovery, Processing, and Visualization Services for ICESat and ICESat-2 Altimeter Data

Current approaches for the discovery and distribution of airborne and satellite remote sensing data are targeted primarily toward raster and/or point cloud datasets. These data are typically distributed on the web via a map-based GUI, with background optical imagery or shaded topography providing the spatial context for the data. Remote sensing measurements from profiling instruments such as laser/radar altimeters and atmospheric sounders present a different challenge. These observations are densely sampled along ground tracks that can be separated by kilometers or more and are largely independent of each other spatially. Profiling data are also information-rich, and often include vector (rather than scalar) measurements and many auxiliary parameters.

There are currently no open data access systems designed to address two critical user requirements for profiling data: 1) the ability to visualize vector data and auxiliary parameters along one or more individual tracks on a web-based map interface, and 2) simultaneous visualization of repeated tracks at the same location over time. NASA’s Ice, Cloud,and land Elevation Satellite (ICESat) and upcoming ICESat-2 missions use profiling laser altimeters to measure changes in the topography of Earth’s ice sheets, vegetation canopy structure, and clouds and aerosols. The unique data from these missions require a new paradigm for data access, to serve the needs of a diverse scientific community and to increase the accessibility and utility of these data for new users.

We propose to build a cyberinfrastructure platform for ICESat and ICESat-2 data discovery, access, and visualization. This platform will leverage and build upon the service-oriented architecture behind the OpenTopography system (TRL8+) that already provides integrated access and processing capabilities for high resolution topography data. The proposed work will also leverage development performed as part of the NASA Lidar Access System project, a collaboration between UNAVCO, OpenTopography, NASA's Goddard Space Flight Center, and the National Snow and Ice Data Center (NSIDC) that prototyped an ICESat data discovery interface and improved Geoscience Laser Altimeter System (GLAS) data products.

This cyberinfrastructure platform will include:

  1. An efficient, user-friendly map-based web interface to access ICESat (single beam) and ICESat-2 (multiple-beam) data, with the ability to subset by time and by track as well as to filter data on multiple engineering and data quality attributes.
  2. Visualization of the waveform/energy (ICESat-1) or photon (ICESat-2) distribution through the entire atmosphere and (separately) within the ground range window. In both cases, users would be able to visualize individual laser shots or horizontal stacks of multiple shots along profile.
  3. An efficient and highly scalable data management platform that includes intelligent tiered storage and distributed file systems for redundancy and fault tolerance.
  4. A standards-based API for enabling programmatic access to the data and processing capabilities for expert users and interoperability with other systems.

Profiling altimeter data are relevant to 5 of the 6 interdisciplinary science focus areas for NASA, with important applications in atmospheric science, terrestrial hydrology, sea level change, vegetation/biomass monitoring, and the cryospheric sciences. We envision a data access system that will broaden the use of the ICESat dataset well beyond its core cryosphere community, will be ready to serve the upcoming ICESat-2 mission when its datasets come online in 2017~2018, and will provide pathways for the inclusion of similar datasets from other profiling altimetry missions.

Adrian Borsa, University of California San Diego

Last Updated: Nov 15, 2017 at 2:34 PM EST