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The Swiss data cube, analysis ready data archive using earth observations of Switzerland

Authors :
Charlotte Poussin
Christian Ginzler
Charlotte Steinmeier
Vladimir Wingate
Bruno Chatenoux
Michael E. Schaepman
Claudia Roeoesli
Achileas Psomas
Diana-Denisa Rodila
Gregory Giuliani
Jean-Philippe Richard
Pascal Peduzzi
David Small
University of Zurich
Giuliani, Gregory
Source :
Scientific Data, Vol 8, Iss 1, Pp 1-11 (2021), Scientific data, Vol. 8 (2021) P. 295, Scientific Data
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

Since the opening of Earth Observation (EO) archives (USGS/NASA Landsat and EC/ESA Sentinels), large collections of EO data are freely available, offering scientists new possibilities to better understand and quantify environmental changes. Fully exploiting these satellite EO data will require new approaches for their acquisition, management, distribution, and analysis. Given rapid environmental changes and the emergence of big data, innovative solutions are needed to support policy frameworks and related actions toward sustainable development. Here we present the Swiss Data Cube (SDC), unleashing the information power of Big Earth Data for monitoring the environment, providing Analysis Ready Data over the geographic extent of Switzerland since 1984, which is updated on a daily basis. Based on a cloud-computing platform allowing to access, visualize and analyse optical (Sentinel-2; Landsat 5, 7, 8) and radar (Sentinel-1) imagery, the SDC minimizes the time and knowledge required for environmental analyses, by offering consistent calibrated and spatially co-registered satellite observations. SDC derived analysis ready data supports generation of environmental information, allowing to inform a variety of environmental policies with unprecedented timeliness and quality.<br />Measurement(s)surface reflectance • backscatterTechnology Type(s)satellite imagingSample Characteristic - LocationSwitzerland Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14635485

Details

Language :
English
ISSN :
20524463
Volume :
8
Database :
OpenAIRE
Journal :
Scientific Data
Accession number :
edsair.doi.dedup.....5c4efbd575f98185283c9c56653f2b7d
Full Text :
https://doi.org/10.1038/s41597-021-01076-6