Achieving the Full Vision of Earth Observation Data Cubes

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.

JupyTEP IDE as an Online Tool for Earth Observation Data Processing

“…The huge size of EO data makes researchers look for new ways to process them. One of the new paradigms in this field is the use of EO data cubes (EODC), revolutionizing the way users can interact with EO data and a promising solution to store, organize, manage, and analyze EO data [23,24].…”

Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15 – exploring the potential of data cube

“…Currently, degradation of land through human activities is undermining the wellbeing of at least 3.2 billion people, pushing the planet towards a sixth mass extinction and costing more than 10 per cent of total Gross Domestic Product (GDP) (IPBES, 2018). (Boulton, 2018), the data cube concept has emerged as a solution lowering barriers and offering new possibilities to handle large spatio-temporal EO data (Baumann, Misev, Merticariu, & Huu, 2019;Kopp, Becker, Abhijit Doshi, Wright, & Hong, 2019;Lewis et al, 2016). Data cubes are a time-series multi-dimensional (e.g.…”

A Deep Learning Method to Accelerate the Disaster Response Process

“…Moreover, as the discussion about open data policies is maturing, these need to be supported with mechanisms for easy access and easy discovery of data. Indeed, there are considerable advances in storing and organizing huge volumes of satellite date, such as Earth Observations (EO) data cubes [10][11][12] which bring closer the vision of Digital Earth [13,14].…”