Snow cover/Extent Demonstrator from Optical Sensors (SEDOS)

The area extent of the seasonal snow cover is a key parameter for a wide range of applications in meteorology, climate monitoring, global change research, hydrology, water management and ecology. This study develops and implements a prototype processing system for a new generation of snow extent products from Metop-SG/METimage. The prototype system is demonstrated and evaluated using data from the optical sensors of Sentinel-3 featuring similar spectral imaging bands as METimage.

Objectives

The primary objectives of the SEDOS study are:

• Develop, implement and validate an algorithm and prototype system to prepare for the generation of snow extent products from METimage which will be flown on Metop-SG, and FCI onboard of the MTG-I.
• Demonstrate and evaluate the developed methods and prototype system using data from the optical sensors SLSTR and OLCI onboard Sentinel-3 featuring similar spectral imaging bands as METimage. This task will include the generation and validation of a 1-year time series of daily snow cover products over Europe.
• Demonstrate the operational capabilities of the prototype system by generating a time series of Pan-European snow products from Sentinel-3 data in Near Real time.

Overview

The area extent of the seasonal snow cover is a key parameter for a wide range of applications in meteorology, climate monitoring, global change research, hydrology, water management and ecology. Observations of snow-cover extent from visible and infrared sensors, operating on polar-orbiting and geostationary satellites, have been widely used during the last decades. The different datasets vary in spatial resolution, repeat coverage and performance.

METimage to be flown on the upcoming Metop-SG satellite series will offer excellent capabilities for generating consistent, high quality, long-term datasets on snow cover extent from regional to global scale. The SEDOS project is aimed at the development, prototyping, quality assessment and demonstration of Snow Cover Extent/Fraction products as a precursor for a snow cover product based on METimage. The study logic is shown in Figure 2.

• The initial phase of the project deals with a review on the state-of-art of snow extent monitoring using optical satellite data, to be used for guiding the development and implementation of the snow retrieval algorithms and processing systems.
• The development and implementation of the snow retrieval algorithm follows an iterative cycle, including algorithm development and implementation as prototype software, the generation of test products and the evaluation of these products using reference datasets. Data from the sensors SLSTR and OLCI onboard Sentinel-3 are the main source for supporting algorithm development and for generating snow extent/ fractional snow cover (FSC) and cloud masking products for demonstration and validation.
• Based on the prototype software tools a processing system is designed and implemented following a modular design. Although the tool is developed using Sentinel-3 SLSTR / OLCI data it can be extended for using upcoming METimage and FCI data.
• The usability of the tool is demonstrated using Sentinel-3 SLSTR and OLCI data by generating a time series of snow products with Pan-European coverage in Near Real Time. The products are evaluated using in-situ data and snow products from high resolution satellite data such as Landsat-8 and Sentinel-2 following the ESA SNOWPEx protocol.

Project Team

ENVEO — Environmental Earth Observation IT GmbH, Innsbruck Austria (PI)

Finnish Environment Institute (SYKE), Helsinki, Finland