The volume of sub-meter remotely sensed data is growing at rates exceeding petabytes per year

Over the past decade costs for data storage systems and computing have both dropped exponentially. This has opened the door for big data processing using spaceborne optical imagery to characterize land surface phenomena in high-end computing (HEC; acronyms list on page 21) environments. Recent examples include google earth engine amazon web services cloud computing services NASA earth exchange and NASA center for climate simulation (nccs) advanced data analytics platform (adapt). At the same time a growing constellation of commercial very-high-resolution (VHR) satellites offer global 1-2-day repeat coverage that can complement NASA earth observing (EO) missions with stereo and super-spectral capabilities. Through no-direct-cost licensing agreements the national geospatial-intelligence agency (NGA) and NASA goddard spaceflight center (gsfc) are acquiring petabytes of archived digitalglobe (DG) 0.3 0.5 m panchromatic and 2 4 m multi-spectral imagery from around the globe. The DG archive includes data from 7 satellites including worldview-1 2 3 4 quickbird-2 geoeye-1 and ikonos-2. Prior to 2008 a limited number of EO VHR images were often used individually for evaluation and validation over small areas to compare to coarser resolution NASA EO data because these data were snapshots in space and time. Now the DG constellation enables repeat contiguous coverage over large regions. These data are a valuable EO resource for scaling global ecological and geological phenomena occurring at submeter scales that can enhance NASA EO science that occurs at moderate to coarse resolutions. This proposal seeks to provide tools as an application program interface (API) for mass processing spatially contiguous and temporally consistent archived NASA-gsfc DG VHR data that can only efficiently be performed on NASA HEC resources due to DG-NGA licensing limitations and computational requirements.