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WP3 - Product and Service Generation


To define and implement algorithms to determine:
- Indicators (start and end of growing season) for ecosystem functioning in the boreal region using Sentinel-3
- Land cover change using Sentinel-3
- Snow state and coverage using Sentinel-1,-3
- Lake ice and state using Sentinel-1,-3
- Glacier parameters using Sentinel-1,-3
- Water bodies using Sentinel-1
- Soil freeze/thaw using Sentinel-1

Description of work and role of partners

WP3 - Product and Service Generation [Months: 9-28]

Lead beneficiary: GAMMA
The product processing is based on applying the target parameter-specific algorithms and methods to the preprocessed (intermediate) data coming from WP2. There can also be alternative algorithms and methods for a selection of parameters. Generation of products and services will be based on continuous time series of Sentinels data, which guarantees the availability of multiple, cloud free coverage of optical EO data received in required season in the areas of interest. Services based on highly automated processing chains will be supported. Particularly for snow products, a close interaction with WP4 is necessary in order to provide the accuracy characteristics as one product layer.

T3.1 - Land cover change and phenology for boreal zone [Months: 9-28]

This task focuses on the adaptation and implementation of methods for Land cover change & ecosystem functioning with Sentinel-data
- The methods for feature extraction (start and end of the growing season) from time-series developed in previous projects will be enhanced and made operational using the available archive of MODIS time-series at the beginning of the project. Methods will be transferred to Sentinel-3 SLSTR-derived time series after acquisition of sufficient data volume.
- Development of methods for change detection indicators, such as for locating core areas of change (man made and loss/ increase of biomass), based on medium resolution time-series of Sentinel-3. Sentinel-2 data are used for characterization of changes within selected pilot sites (e.g. including FP7 Geoland2 AFS sites). Development of local change product based on Sentinel-2 data is given higher priority compared to medium resolution product.
- Implementation of the above mentioned methods into the processing chains.

T3.2 - Snow for boreal forest and mountain zone [Months: 9-28]

This task focuses on the adaptation and implementation of snow monitoring algorithms to Sentinel-data.
- Adaptation of SCAmod-method for Fractional Snow cover for boreal forest and tundra
- Improvement of Fractional Snow cover retrievals utilizing Snow water equivalent data (from existing products within DUE-Globsnow and NRT in situ observations of snow depth)
- Provision of snow extent map with two-layer information on Fractional Snow Cover and Snow Water Equivalent
- Adaptation of snow mapping in mountain areas using Sentinel 3 SLSTR data
- Investigate capabilities for snow mapping using simultaneous acquired Sentinel-3 SLSTR and OLCI data
- Development of wet snow detection algorithms for Sentinel-1
- Implementation of the methods into prototype processing chains

T3.3 - Glaciers [Months: 9-28]

This task focuses on the development of algorithms for generation of glacier products to Sentinel-data.
- Adaptation of method and implementation of processing line for glacier outline mapping using Sentinel-2 MSI data (without debris-covered glaciers)
- Adaptation of method and development of processing line for generation of ice velocity maps using repeat pass Sentinel-1 and Sentinel-2 data
- Adaptation of methods for snow / ice mapping using multitemporal Sentinel-1 SAR data, Sentinel-2 MSI data, and Sentinel-3 SLSTR+OLCI data
- Implementation of the methods into the processing chains

T3.4 - Lake ice [Months: 9-28]

This task focuses on the adaptation and implementation of Lake ice algorithms to Sentinel-data.
- Adaptation of algorithm for the snow cover mapping on lake ice to Sentinel-data. Sentinel-2 MSI will be used in the development work, but the final product and processing lines will use SLSTR.
- Development of the algorithm for detection of lake ice extent using Sentinel-3
- Lake ice from Sentinel-1
- Lake ice state from Sentinel-1
- Implementation the prototype processing chains using adapted methods

T3.5 - Soil [Months: 9-28]

This task focuses on the adaptation and implementation of soil state algorithms to Sentinel-data.
- Develop and implement a Freeze/thaw mapping algorithm based on multi temporal Sentinel-1 backscatter and coherence information.
- Develop and implement modification to freeze/thaw algorithm, taking into account sensitivity of backscatter to vegetation.
- Develop and implement a permafrost subsidence map processing chain based on Sentinel-1 interferometric SAR data.
- Adapt methodology developed within the CCI_land cover for water body mapping with ASAR data to Sentinel-1 data and implement a water body mapping service.