Accurate geolocation is essential to producing Earth Science Data Records (ESDRs) over heterogeneous terrestrial surfaces using the EOS MODIS and NPP VIIRS moderate resolution sensors. In particular, accurate operational geolocation is needed for generating temporally composited products needed to support accurate retrieval of biophysical parameters on multi-day temporal scales, and to enable inter-comparisons of multi-day composites. The proposal will address Terra and Aqua MODIS geolocation algorithm refinement and calibration/validation, as well as, evaluation of VIIRS geolocation algorithms. Both activities will be in support of higher level ESDRs.
The NASA EOS mission has demonstrated that it is possible to operationally produce geolocation data to the sub-pixel accuracies needed to generate ESDRs from the MODIS sensors. However, there is still room for refinement of the MODIS geolocation algorithms. Nearly global high quality SRTM elevation model data is now available at finer spatial resolutions than 1 km currently used by the MODIS geolocation algorithm. This finer resolution data has the potential to improve the geolocation of MODIS data in rough terrain (roughly 20% of the Earth�s land surface). However, research is needed to evaluation various approaches to improving the terrain correction, as well as to understand the potential benefits of using refined terrain corrected data to generate higher-level geophysical products, particularly those products that are challenged by rough terrain (e.g., snow cover, burn-scar and veg. cover change). The proposal will address refinement of the terrain correction algorithm and working with MODIS science team members to assess the impact on the higher-level products.
One of the key underlying capabilities needed to enable the extension of the terrestrial ESDRs from MODIS into the future, is the ability to accurately inter-compare data from VIIRS to the MODIS data record at the same Earth locations. As a member of the current VIIRS science team, the proposed PI, Robert Wolfe, has developed a detailed understanding of the geometric characterization of the VIIRS instrument and NPP satellite, understands the ancillary data requirements, and has begun to evaluate the accuracy of the operational VIIRS geolocation algorithm. As part of this current activity, an automatic filtering technique is being developed that will enable nearly autonomous long-term trending of geolocation data thereby making the long-term error analysis operational. The proposal will address continuing the work in understanding the VIIRS sensor and its pre-flight characterization, and in evaluation of automatic long-term trending techniques. The proposal will extend this activity into the VIIRS post-launch era, particularly in the areas of post-launch sensor geometric characterization, evaluation of the on-orbit geolocation algorithm performance, and evaluation of automated long-term trending of the VIIRS geolocation data.
