The Surface Biology and Geology global imaging spectrometer is primarily designed to observe the chemical fingerprint of the Earth’s surface. However imaging spectroscopy across the visible to shortwave infrared (VSWIR) can also provide important atmospheric observations of methane point sources, highly concentrated emissions from energy, waste management and livestock operations. Relating these point-source observations to greenhouse gas inventories and coarser, regional methane observations from sensors like the European Space Agency (ESA) TROPOMI will contribute to reducing uncertainties in local, regional and global carbon budgets. We present the Multi-scale Methane Analytic Framework (M2AF) that facilitates disentangling confounding processes by streamlining analysis of cross-scale, multi-sensor methane observations across three key, overlapping spatial scales: 1) global to regional scale, 2) regional to local scale, and 3) facility (point source scale). M2AF is an information system that bridges methane research and applied science by integrating tiered observations of methane from surface measurements, airborne sensors and satellite. Reducing uncertainty in methane fluxes with multi-scale analyses can improve carbon accounting and attribution which is valuable to both formulation and verification of mitigation actions. M2AF lays the foundation for extending existing methane analysis systems beyond their current experimental states, reducing latency and cost of methane data analysis and improving accessibility by researchers and decision makers. M2AF leverages the NASA Methane Source Finder (MSF), the NASA Science Data Analytics Platform (SDAP), Amazon Web Services (AWS) and two supercomputers for fast, on-demand analytics of cross-scale, integrated, quality-controlled methane flux estimates.

The geospatial Imaging Spectroscopy Processing Environment on the Cloud (ImgSPEC; formerly GeoSPEC) pioneers an on-demand science data processing system (SDPS) producing user-customized Level 1 calibrated radiance to Level 3+ data products in anticipation for the 2017-2027 Earth Decadal Survey prioritized spaceborne global imaging spectrometer to advance the study of Surface Biology and Geology (SBG). SBG data volumes (~20 TB/day) of high dimensionality (>224 bands) would be infeasible to download and the breadth of applications of the data across dozens of disciplines presents a need to evolve the traditional NASA SDPS. ImgSPEC streamlines processing data into key SBG observables that have demonstrated algorithms at local-to-regional scales and may vary locally. As such, a traditional, monolithic SDPS could not fully exploit the information in SBG measurements. To remove this barrier to use, ImgSPEC demonstrates an on-demand SDPS prototype that improves imaging spectroscopy data discovery, access, and utility enabling shared knowledge transfer from advanced imaging spectroscopy users to less experienced users such as decision makers and the general public. We test three use cases: 1) standard data processing workflows, 2) customized variants of standard workflows, and 3) algorithm development of new workflows. We create collaborative algorithm development environments that offer services typically restricted to NASA SDPSs such as data product provenance and bulk processing. We leverage existing NASA-funded information technologies such as the hybrid on-premise/ cloud science data system (HySDS), the Multi-mission Algorithm and Analysis Platform (MAAP), ECOSIS – a crowd-sourced spectral database, and ECOSML – a crowd-sourced model database. We demonstrate ImgSPEC on the Terrestrial Ecosystem use case processing through to foliar traits and fractional cover, thus aligning with driving thrusts for the SBG Science and Applications Communities.