Next Article in Journal
Transformation of Schema from Relational Database (RDB) to NoSQL Databases
Previous Article in Journal
Experimental Data of a Floating Cylinder in a Wave Tank: Comparison Solid and Water Ballast
Previous Article in Special Issue
National Open Data Cubes and Their Contribution to Country-Level Development Policies and Practices
Open AccessEditorial

Earth Observation Open Science: Enhancing Reproducible Science Using Data Cubes

1
Institute for Environmental Sciences, University of Geneva, Bd Carl-Vogt 66, CH-1205 Geneva, Switzerland
2
United Nation Environment Programme, Science Division, GRID-Geneva, 11 Chemin des Anémones, CH-1219 Châtelaine, Switzerland
3
Group on Earth Observations, 7bis Avenue de la Paix, Case Postale 2300, 1211 Geneva, Switzerland
4
National Aeronautics and Space Administration, Langley Research Center, MS 457, Hampton, VA 23681, USA
5
Geoscience Australia, GPO Box 378, Canberra, ACT 2601, Australia
*
Author to whom correspondence should be addressed.
Data 2019, 4(4), 147; https://doi.org/10.3390/data4040147
Received: 21 November 2019 / Accepted: 21 November 2019 / Published: 25 November 2019
(This article belongs to the Special Issue Earth Observation Data Cubes)
Earth Observation Data Cubes (EODC) have emerged as a promising solution to efficiently and effectively handle Big Earth Observation (EO) Data generated by satellites and made freely and openly available from different data repositories. The aim of this Special Issue, “Earth Observation Data Cube”, in Data, is to present the latest advances in EODC development and implementation, including innovative approaches for the exploitation of satellite EO data using multi-dimensional (e.g., spatial, temporal, spectral) approaches. This Special Issue contains 14 articles covering a wide range of topics such as Synthetic Aperture Radar (SAR), Analysis Ready Data (ARD), interoperability, thematic applications (e.g., land cover, snow cover mapping), capacity development, semantics, processing techniques, as well as national implementations and best practices. These papers made significant contributions to the advancement of a more Open and Reproducible Earth Observation Science, reducing the gap between users’ expectations for decision-ready products and current Big Data analytical capabilities, and ultimately unlocking the information power of EO data by transforming them into actionable knowledge. View Full-Text
Keywords: open science; reproducibility; earth observations; data cube; analysis ready data; remote sensing; satellite imagery open science; reproducibility; earth observations; data cube; analysis ready data; remote sensing; satellite imagery
MDPI and ACS Style

Giuliani, G.; Camara, G.; Killough, B.; Minchin, S. Earth Observation Open Science: Enhancing Reproducible Science Using Data Cubes. Data 2019, 4, 147.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop