PhenoSwiss: Monitoring Land Surface Phenology over Switzerland using the Swiss Data Cube satellite Earth Observations time-series

We have received the good news that the project “PhenoSwiss: Monitoring Land Surface Phenology over Switzerland using the Swiss Data Cube satellite Earth Observations time-seriess” has been accepted.

This project jointly lead by UNIGE/GRID (Dr. Gregory Giuliani) & UZH/RSL (Dr. Claudia Röösli) is supported by the UNIGE-UZH Joint Seed Funding. Since mid-December 2017 the University of Zurich and the University of Geneva are officially strategic partners for Digital Science and Citizen Science.

The objective of the PhenoSwiss project is to bring together expertise of UZH/RSL on Land Surface Phenology  and UNIGE on the Swiss Data Cube.

In the framework of the ESA-funded GlobDiversity project (, UZH has develop a new algorithm for monitoring LSP. It has been tested and validated in the Laegern region (10 km2) and shows promising results. In order to provide national information on the biodiversity of terrestrial ecosystems and simultaneously generate a decision-ready product, the LSP monitoring algorithm now requires to be scaled up from the development stage to the operational level, encompassing entire Switzerland. Such a product could be readily used as a basis for the design, implementation and evaluation of policies, as well as developing policy advice, programs and regulation.
Consequently, the aims of the project are to use the SDC platform to:
(1) Implement the LSP algorithm developed by UZH and consider improvements;
(2) Generate an LSP product retrieval from EO data for the entire Switzerland to contribute to provide baseline data for monitoring biodiversity;
(3) Demonstrate the use and capability of processing open and freely available Big EO data on a cloud-computing platform;
(4) Review and evaluate the variability and evolution of satellite-derived growing season length (GSL) nationwide;
(5) Test start- and end-of-season metrics (SOS and EOS, respectively) for linear trends as well as for significant trend shifts over the study period;

The project will start in September 2019 for 1-year.

We would like to thank the UNIGE-UZH Joint Seed Funding for its support.