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CryoLand – GMES Service Snow and Land Ice 2011 – 2015 EU FP7 Project No. 262925 Preparation of European Snow, Glacier and Lake/River Ice Services within.

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Presentation on theme: "CryoLand – GMES Service Snow and Land Ice 2011 – 2015 EU FP7 Project No. 262925 Preparation of European Snow, Glacier and Lake/River Ice Services within."— Presentation transcript:

1 CryoLand – GMES Service Snow and Land Ice 2011 – 2015 EU FP7 Project No. 262925 Preparation of European Snow, Glacier and Lake/River Ice Services within the Copernicus CryoLand Project ENVISAT MERIS 22 März 2011 Thomas Nagler 1 ; Gabriele Bippus 1, Helmut Rott 1 ; Christian Schiller 2 ; Sari Metsämäki 3, Olli-Pekka Mattila 3, Riitta Teiniranta 3 ; Kari Luojus 4 ; Hans Larsen 5 ; Rune Solberg 6 ; Oivind Due Trier 6 ; Eirik Malnes 7 ; Andrei Diamandi 8 ; Andreas Wiesmann 9 ; David Gustafsson 10

2 PRIMARY OBJECTIVE Develop, implement and validate an operational, sustainable service for monitoring snow and land ice as a Downstream Service within Copernicus Initiative of EC and ESA. The project prepares the basis for a future cryospheric component of the Copernicus Land Monitoring Service. PRIMARY OBJECTIVE Develop, implement and validate an operational, sustainable service for monitoring snow and land ice as a Downstream Service within Copernicus Initiative of EC and ESA. The project prepares the basis for a future cryospheric component of the Copernicus Land Monitoring Service. CryoLand – GMES Services Snow and Land Ice (FP7 Project 2011-2015) Contents: Products Specifications Example Products for Snow, Glaciers, Lake / River Ice Product Validation Preparation for Sentinels Access to Products Summary Announcement on „Satellite Snow Products Intercomparison & Evaluation Exercise - SnowPEX“

3 CryoLand User Group Hydropower companies Energy traders Hydrological services Meteorological services Climate monitoring institutions Avalanche warning centres Road, Railway and River Authorities Geotechnical & Construction companies Ecologists Reindeer herders Environmental agencies CRYOLAND USER GROUP: 60 Organisations from 15 European countries + 3 EU organisations: Product & Service Requirements and Specs Product & Service Testing and Evaluation CRYOLAND USER GROUP: 60 Organisations from 15 European countries + 3 EU organisations: Product & Service Requirements and Specs Product & Service Testing and Evaluation lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

4 Consolidated Snow Products and Services lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

5 Glacier & Lake/River Ice Products lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

6 Approach for product and service improvement towards user needs 1.User requirements / dialogue for improved product requirements and specification 2.Algorithm development / adjustment to match user needs 3.Generation of test products and validation for different regions and periods 4.User consultation and feedback on product and services 5.Final algorithms, fully validated products and services Algorithm development / adjustment Test products Validation User consultation / feedback Development cycle User Requirements for Products and Services Approved Algorithms, Validated Products and Services lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

7 Pan-European Fractional Snow Cover Product Product Specifications: –Domain: 72°N 11°W – 35°N 50°E –Projection: LatLon/WGS84 –Pixel size: 0.005° (ca 500 m) –Latency: < 1 day Status: –Algorithm: SCAMOD (SYKE) (550 nm Band) –Sensor: MODIS (Backup VIIRS, ) –Regional service integration, processing chain and portal implemented –Attached uncertainty map –Operational NRT Service for 2013/14 –Time series since 2000 in generation lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler Grey: Clouds 4/3/2013

8 Pan-European SWE Product Product Specifications: –Domain: 72°N 11°W – 35°N 50°E –Projection: LatLon / WGS84 –Pixel size: 0.1deg; ca 10 km –Temporal resolution: Daily –Latency: < 2 day Status: –Algorithm based on H-SAF and GlobSnow –Assimilates passive microwave observations and ECMWF weather station data lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler Grey: Mountains 4/3/2013

9 Melting Snow Area – Alps, Scandinavia 9 June 2006, ENVISAT ASAR WSM. Red – wet snow extent, Yellow – layover / foreshortening Innsbruck Binary map of wet snow from Multi-temporal SAR data 100 m pixel size Projection: Geographic, UTM, Lambert EA Austria Demonstration Products: Time series of Products uses archived ENVISAT ASAR data NRT service with Radarsat for Scandinavia spring 2013/14 lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

10 Snow Extent Product Quality Assessment Quality Assessment of Snow Extent Products is performed in different environments: Fractional SE products from high resolution optical images: Very High resolution images ( IKONOS, SPOT5, Quickbird) Landsat TM/ETM+ In-situ snow transects measured operationally by SYKE in Finland VHR Optical Images - Landsat TM/ETM+ - In-situ snow transects Accuracy assessment of SE products and services is still ongoing according to the planning of the project. lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

11 Accuracy Assessment of SE Products High and Very High resolution Images provide detailed snow information in mountains and forests (sparse->dense) and enable the quality assessment of CryoLand SE products in these areas. MODIS SCAMOD – Pan-European FSC versus In-situ Snow transects Syke Pixel (unforested) RMSDBIASR 10671417.3-3.930.89 Landsat TM 25.10.2003 lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

12 Concept for SENTINEL-3 Snow Mapping using SLSTR (AATSR) and OLCI (MERIS) Sentinel-3: SLSTR (AATSR): 0.5 – 1.6, -3.7  m+TIR; 1 km OLCI (MERIS): 0.4.-1.2  m; 300 m

13 AATSR 1 km MERIS/AATSR 300 m Preparation for Snow Mapping using SENTINEL-3 SLSTR & OLCI Input Data for FSC: SLSTR (AATSR): 0.5 - 3.7  m+TIR; 1 km OLCI (MERIS): 0.4.-1.2  m; 300 m Algorithm: MS Unmixing Local Adaptive Endmembers Fractional Snow Extent Map

14 Preparation for Snow Mapping using Sentinel-1 IWS Dual Pol Data Dynamic Range of Backscatter Ratio Sentinel-1 IWS TOPS Mode Swath ~250 km Dual Pol: Co, Cross (VV,VH) Resolution: 5 m Slant Range 20 m Azimuth ENVISAT ASAR Alternating Pol. IS 6 Polarisation VV and VH : - 7 Feb 2008 13 May 2008

15 Example of Wet Snow Map from ASAR AP VV & VH 13 May 2008 16/ October 2012 Sentinel-3 OLCI SLSTR Preparatory WSThomas Nagler Dual Pol: VV & VH

16 Processing Line of Glacier Area Product Product information: A standardized, semi- automated processing line using MS (V)HR satellite data and DEM ad input: ice snow detection automatic, manual post-processing required over debris covered areas. Product generation within CryoLand is done on User Request: selected glaciers in Austria, Greenland, Kyrgyzstan, Bhutan, and Norway Products generated according to GLIMS and INSPIRE standards lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

17 0.46 0.14 0.29 Ratio of Snow and Total Glacier Area Glacier Area Maps for Hohe Tauern Alps 1.9.2009, SPOT–5 (2.5 m, PAN + MS) Pasterze Glacier Area Change 1998 2009

18 Extent of Glacier Lakes Lake outburst observed between 2010/06/28 (red) and 2010/07/05 (blue) using SAR. Comparison with GLL (white) from Landsat 7 ETM+ of 2010/08/17. SAR Analyses: NORUT LS7 Analysis: ENVEO ENVEO, NORUT Glacier Lake Extent derived from optical satellite data and SAR data Method applies classification and manual post- processing and uses existing lake boundaries Glacier Lake Extent of multiple years for Lake Tininnilik, Greenland, Kyrgyzstan and Bhutan Validation is carried out with in-situ observations in collaboration with users lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

19 Lake Ice Extent - Product Lake Ice product 17 April 2013 The threshold reflectances were determined from time series of MODIS reflectance observations from the surroundings of in-situ measurements for snow cover thickness on ice. Reflectance (550 nm) Time full snow cover partial snow/ white ice cover clear ice/ columnar ice open water In-situ Snow depth Lake Ice Product: Daily, generated NRT 250 m pixel Covering Baltic drainage basin Sensor: MODIS SYKE Lake Ice Extent Lake Ladoga lissig | earsel | 3-6 feb 2016 | berne Thomas Nagler

20 Product and Information Exchange User Infrastructure GMES Space In-situ Data Auxiliary Data GMES Core Services Provided data Tools CryoLand GeoPortal GEOSS Common Infrastructure INSPIRE Portal Space (general) …… Portal https://cryoland.eu Protocols: CSW, WMS, WFS, WPS, PDP Products accessible by Geoportals, GIS Systems, Automatic Script Downloading

21 Summary Product and Service Specifications for potential Copernicus Snow and Land Ice Services were compiled together with a wide user group. Near Real Time Services for Pan-European FSC and SWE and lake / river ice products winter 2013/2014: Products are made available to the public through CryoLand System (https://www.cryoland.eu). Generation of glacier products in Alps, Scandinavia, Greenland and Himalayan Mountains as requested by CryoLand users. Validation of products and quality assessment using high resolution optical data and in-situ data is ongoing and specification of. Algorithms and processing lines are adapted to make use of advanced imaging capabilities of Sentinel satellites, testing with more data sets was limited due to the lack of suitable data sets.

22 S NOW PEX Satellite Snow Products Intercomparison & Evaluation Excercise An ESA initiative contributing to WMO Global Cryosphere Watch and WCRP CLiC carried out under the lead of ENVEO in cooperation with FMI, SYKE, EC and CCRS. US National Ice Center / NOAA/ NESDIS, Cryospheric Processes and RS Laboratory, City University of NY Global Snow Lab, Rudgers University Cryospheric Sciences Laboratory, NASA and associated international contributors

23 SnowPEX Objectives The primary objectives are Intercompare and evaluate global / hemispheric (pre) operational snow products derived from different EO sensors and generated by means of different algorithms, assessing the product quality by objective means. Evaluate and intercompare temporal trends of seasonal snow parameters from various EO based products in order to achieve well-founded uncertainty estimates for climate change monitoring. Elaborate recommendations and needs for further improvements in monitoring seasonal snow parameters from EO data. SnowPEX aims to bring together scientists and institutions of seasonal snow pack monitoring for assessing the quality of current satellite-based snow products derived from EO data, and working out guidelines for improvement. S NOW PEX organizes 2 International Workshops on Snow Product Intercomparison (IWSPI). The 1 st IWSPI is planned to be held in July 2014 in Washington DC (TBC). Point of Contact: thomas.nagler@enveo.at


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