Cloud Optimized Raster Encoding (CORE): A Web-Native Streamable Format for Large Environmental Time Series

• Main Authors: Ionuț Iosifescu Enescu, Lucia de Espona, Dominik Haas-Artho, Rebecca Kurup Buchholz, David Hanimann, Marius Rüetschi, Dirk Nikolaus Karger, Gian-Kasper Plattner, Martin Hägeli, Christian Ginzler, Niklaus E. Zimmermann, Loïc Pellissier
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Geomatics
• Subjects: very large geodata; raster time series; environmental open data; open software; web-EGIS; data cube
• Online Access: https://www.mdpi.com/2673-7418/1/3/21

The Environmental Data Portal EnviDat aims to fuse data publication repository functionalities with next-generation web-based environmental geospatial information systems (web-EGIS) and Earth Observation (EO) data cube functionalities. User requirements related to mapping and visualization represent a major challenge for current environmental data portals. The new Cloud Optimized Raster Encoding (CORE) format enables an efficient storage and management of gridded data by applying video encoding algorithms. Inspired by the cloud optimized GeoTIFF (COG) format, the design of CORE is based on the same principles that enable efficient workflows on the cloud, addressing web-EGIS visualization challenges for large environmental time series in geosciences. CORE is a web-native streamable format that can compactly contain raster imagery as a data hypercube. It enables simultaneous exchange, preservation, and fast visualization of time series raster data in environmental repositories. The CORE format specifications are open source and can be used by other platforms to manage and visualize large environmental time series.