Achieving the Full Vision of Earth Observation Data Cubes

Steve Kopp, Peter Becker, Abhijit Doshi, Dawn J. Wright, Kaixi Zhang and Hong Xu
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Steve Kopp: Esri, 380 New York St, Redlands, CA 92373, USA
Peter Becker: Esri, 380 New York St, Redlands, CA 92373, USA
Abhijit Doshi: Esri, 380 New York St, Redlands, CA 92373, USA
Dawn J. Wright: Esri, 380 New York St, Redlands, CA 92373, USA
Kaixi Zhang: Esri, 380 New York St, Redlands, CA 92373, USA
Hong Xu: Esri, 380 New York St, Redlands, CA 92373, USA

Data, 2019, vol. 4, issue 3, 1-19

Abstract: Earth observation imagery have traditionally been expensive, difficult to find and access, and required specialized skills and software to transform imagery into actionable information. This has limited adoption by the broader science community. Changes in cost of imagery and changes in computing technology over the last decade have enabled a new approach for how to organize, analyze, and share Earth observation imagery, broadly referred to as a data cube. The vision and promise of image data cubes is to lower these hurdles and expand the user community by making analysis ready data readily accessible and providing modern approaches to more easily analyze and visualize the data, empowering a larger community of users to improve their knowledge of place and make better informed decisions. Image data cubes are large collections of temporal, multivariate datasets typically consisting of analysis ready multispectral Earth observation data. Several flavors and variations of data cubes have emerged. To simplify access for end users we developed a flexible approach supporting multiple data cube styles, referencing images in their existing structure and storage location, enabling fast access, visualization, and analysis from a wide variety of web and desktop applications. We provide here an overview of that approach and three case studies.

Keywords: data cube; image cube; image data cube; imagery; Landsat; Sentinel; earth observation; GIS; web services; web application; analysis; GIS (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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