Automated protocols for generating very high-resolution commercial validation products with NASA HEC resources

The volume of available remotely sensed data is growing at rates exceeding Petabytes per year. Over the past decade the cost for data storage systems and compute power have both dropped exponentially. This has opened the door for "Big Data" processing systems such as the Google Earth Engine, NASA Earth Exchange, and NASA Center for Climate Simulation (NCCS). At the same time, commercial very high-resolution (VHR) satellites have grown into a constellation with global repeat coverage that can support existing NASA Earth observing missions with stereo and super-spectral capabilities. Through agreements with the National Geospatial-Intelligence Agency NASA-GSFC is acquiring Petabytes of sub-meter to 4 meter resolution imagery from around the globe from WorldView-1,2,3,4 Quickbird-2, GeoEye-1 and IKONOS-2 satellites. Prior to 2008 these data were spatially disparate and were primarily used for evaluation and validation of coarser resolution data products. Current data collections often include repeat coverage in many large regions with contiguous coverage. These data are a valuable no-direct cost resource available for the enhancement of NASA Earth observation science that is currently underutilized. We propose to develop automated protocols for generating VHR products to support NASA earth observing missions. These include two primary foci: 1) On Demand VHR 1/4° Ortho Mosaics - Systematic VHR HEC processing to orthorectify and co-register multi-temporal 2 m multi-spectral imagery compiled as user defined regional mosaics to provide an easily accessible evaluation dataset for LCLUC program mapping efforts. We will apply a consistent image normalization approach to minimize the effects of topography, view angle, date and time of day of collection. This work builds on PI Neigh (cad4nasas.gsfc.nasa.gov) prior experience and experience of COI's Carroll and Montesano in processing of VHR data on GSFC's NCCS ADAPT (https://www.nccs.nasa.gov/services/adapt) cluster. We will work with experts in the generation of surface reflectance data to develop a process for normalizing the VHR data which will yield scientifically valid mosaics that can be used to investigate biodiversity, tree canopy closure, surface water fraction, and cropped area for smallholder agriculture. 2) On Demand VHR DEM generation – Systematic VHR HEC processing of available within track and cross track stereo VHR imagery to produce VHR digital elevation models with the NASA Ames stereo pipeline (https://ti.arc.nasa.gov/tech/asr/intelligent-robotics/ngt/stereo/). We will apply a consistent vertical normalization with ICESat to merge and mosaic DEMs systematically to provide products that can support other NASA missions for a number of different programs. These could potentially include earth surface studies on the cryoshpere (glacier mass balance, flow rates and snow depth); hydrology (lake/water body levels, landslides, subsidence) and biosphere (forest structure, canopy height/cover) among others. Successful development of a HEC protocol to process VHR data could foster surmounting prior spatial-temporal limitations found with using these data on an individual PI basis with broad benefits to many NASA programs.

Advance Earth system science knowledge through the identification, development, and demonstration of innovative information systems technologies

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