1. Earth Science Data Systems (ESDS) Program
  2. Competitive Programs
  3. Advancing Collaborative Connections for Earth System Science (ACCESS) Program
  4. NASA Open-Access Geo-Gridding Infrastructure (NOGGIn): An Integrated Service for Next-Generation Modeling, Analysis, and Retrieval Evaluation with Error Estimates

NASA Open-Access Geo-Gridding Infrastructure (NOGGIn): An Integrated Service for Next-Generation Modeling, Analysis, and Retrieval Evaluation with Error Estimates

Primary Investigator (PI): Thomas Clune, NASA's Goddard Space Flight Center
Co-Investigators (Co-PI): Kwo-Sen Kuo, Robert Wolfe, Asen Radov, Bill Putman: Goddard; S.J. Lin: NOAA; David Randall: Colorado State University; Michael Rilee: Rilee Systems


One of the biggest challenges for researchers working with multiple NASA datasets is that remote sensing instruments have different characteristics. One of these observation characteristics is the grid resolution. Regridding is the process of changing the grid underlying data values to a common grid, so researchers can align diverse data sets for comparison and analysis. Regridding is a time consuming and computationally intensive process. NASA Open-Access Geo-Gridding Infrastructure (NOGGIn), developed to address this issue, is an open-access web service that enables routine and systematic gridding, colocation, and comparison of remote sensing data.

NOGGIn is a regridding tool that can significantly increase research productivity by automating the regridding process. NOGGIn allows regridding to and from next-generation icosahedral and cubed-sphere grids, as well as traditional latitude-longitude grids, and supports a variety of binning methods, including kriging of Level 2 and Level 3 data. Kriging is a geostatistical procedure that creates an estimated surface from a scattered set of points.

What NOGGIn does:

  • Grids data onto next-generation icosahedral and cubed-sphere grids, as well as traditional latitude-longitude grids, with flexible temporal binning (e.g., by local time instead of UTC);
  • Employs multiple estimation techniques for computing grid-cell values, including kriging for reducing sampling bias;
  • Provides robust uncertainty estimates of gridded values;
  • Embeds provenance metadata, describing the operations applied, as well as the original data sources, to improve traceability; and
  • Allows for the introduction of additional estimation methods with a modular design.

NOGGIn’s functionality was demonstrated using MODIS atmospheric data and GPM/TRMM rainfall retrieval. The service will be integrated within NASA's Level-1 and Atmosphere Archive and Distribution System Distributed Active Archive Center (LAADS DAAC).

Last Updated: Jun 6, 2019 at 1:48 PM EDT