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Background The University of Wisconsin-Madison is home to a research team called Advanced Baseline Imager Live Imaging of Vegetated Ecosystems (ALIVE). The team, working remotely and led by Prof. Paul Stoy, PhD, is building a gradient-boosting regression model using geostationary satellites to estimate terrestrial carbon and water fluctuations in near real-time. The team trains its models using GOES-R and other public satellite and meteorological datasets. In trying to process this data, they ran into the central problem when working with raster data for time series analysis – the data’s format, mainly NetCDF and GeoTIFF, is not conducive to time-series analysis. This experience inspired them to strive to create output datasets that are analysis-ready for various applications. During AM…

Situation Overview Sylvera rates projects in the voluntary carbon market with the goal of enabling their customers to invest in the most meaningful initiatives. In order to produce these ratings, Sylvera relies on satellite imagery from providers such as Copernicus, USGS, and NASA. Prior to adopting Arraylake, the engineering team downloaded data across multiple geotiff files stored on individual machines and ran algorithms on the data in a local environment. This process worked for a time but as they began to scale they realized their workflow was not viable. They needed a modern platform to help them manage data and collaborate more effectively. Solutions Assessment As Sylvera looked to improve their data pipeline, they analyzed 3 solutions: One was building a tool in house, which, …