What is the Swiss Data Cube?
Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental variability. Some of these environmental issues can be monitored using remotely-sensed Earth Observations (EO) data that are increasingly available from a number of freely and openly accessible repositories. However, the full information potential of EO data has not been yet realized. They remain still underutilized mainly because of their complexity, increasing volume, and the lack of efficient processing capabilities.
EO Data Cubes (DC) are a new paradigm aiming to realise the full potential of EO data by lowering the barriers caused by these Big data challenges and providing access to large spatio-temporal data in an analysis ready form.
The main objectives of the Swiss Data Cube (SDC) is to support the Swiss government for environmental monitoring and reporting and enable Swiss scientific institutions (e.g., Universities) to facilitate new insights and research using the SDC and to improve the knowledge on the Swiss environment using EO data.
Switzerland is currently knowing one of its most important drought of the last 40 years. Prolonged heat and dryness conditions during late spring, summer, and early autumn of 2018 has led to drought in most European countries (see). Different lakes in Switzerland are suffering from water shortages and their water levels are declining. This is […]
On October 15, we had a meeting with the University of Zurich/Remote Sensing Laboratories (UZH/RSL), with David Small and Michael Schaepman, to define Sentinel-1 Analysis Ready Data. Two UNIGE/GRID team members will go to Zurich in early November to discuss and initiate S1 data ingestion. On October 16-17, we had the visit of Charlotte Steinmeier, […]
The Swiss Data Cube team has recently received a grant to support Armenian colleagues from the Center for Ecological-Noosphere Studies (CENS) and the Institute for Informatics and Automation Problems (IIAP) of the National Academy of Sciences in developing the first version of an Armenian Data Cube. The project is entitled “ADC4SD: Armenian Data Cube for […]
Dear colleagues, Remotely sensed Earth Observations (EO) data have already exceeded the petabyte-scale and are increasingly freely and openly available from different data holdings. This poses a certain number of issues in terms of volume (e.g., data volumes have increased 10x in the last 5 years); velocity (e.g., Sentinel-2 is capturing a new image of […]