Better ice information onboard ships ECDIS S-411

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1 Better ice information onboard ships ECDIS S411 DeMarine User Workshop Dr. Jürgen Holfort Head of German ice service at the Bundesamt für Seeschifffahrt und Hydrographie Vicechair of the JCOMM Expert team on sea ice January 2015

2 Ice characteristics relevant for shipping Pictures: Mikhail Dobrynin, Niels Fuchs Ice concentration Ice thickness Floe size Convergence / divergence Snow cover 2

3 Data transmission Data transmission to ship far up north is not possible with Inmarsat. It is possible using Iridium, but transmission is slow and more expensive. Iridium claims 10 kbit/sec but actual rates for compressed files are more like 2300 to 2400 bit/sec. Inmarsat coverage (Wikipedia) Iridium coverage (Wikipedia) 3

4 SAR Data Size: 200 to 900 MB About 200kb as small scale JPEG 4

5 Ice charts Size: 200 to 900 KB as vector PDF About 100 to 200kb as JPEG S411 starting at ~20kb, typical ~60kb

6 Model Ice charts Size: 200 to 900 KB as vector PDF About 100 to 200kb as JPEG S411 starting at ~20kb, typical ~60kb

7 S411 Ice Information Product Specification summary Development was led by the BSH as a part of JCOMM/ETSI. It was adopted as version 1.0 by JCOMM ETSI5, March 2014 with the latest version (June 2014) The S411 is fully based on the IHO S100 framework specification, Geography Markup Language (GML), Encoding Standard and the ISO series of standards. It is a vector product specification that is primarily intended for encoding the extent and nature of Sea Ice for navigational purpose. The application schema of ice information product contains 28 feature types with their attributes, enumerations, is based on the Ice Objects Catalogue (Version 5.1) and can be found in the ICE domain of the IHO Registry. The full schema as XML Schema File included in Annex B Data Product format (encoding). Ice information datasets use S100 Level 3a geometry which supports 0, 1, and 2 dimentional objects (points, line strings, polygons) The portrayal specification is based on Styled Layer Descriptors (SLD), follows OGC standards and supports 3 polygon portrayals, one according to the vessels ice capabilities, the second and third one being the WMO ice concentration/stages of development colour codes. Portrayals for line and point objects follow the WMO symbology and are implemented using SVGgraphics. Besides future ECDIS SDKs, the S411 data could actually be read and presented using open source GIS software (e.g. QGis) with python scripts from the national ice services available to convert shapefiles, specially SIGRID3 files, into the S411 format. From ETSI report to IHO

8 A simple way to read and portray S411. A short, 4 page long document describes how to read and portray S411 ice information in Quantum GIS (Version 2.0 or newer).

9 Qgis QGIS is an OpenSource Geographic Information System available at no cost for Linux, Windows, Mac OsX, BSD and Android at

10 An example of S411 data in Qgis Example of an S411 ice chart represented in Qgis using the respective S411 In the upper right the total ice concentration, in the lower right the stage of development. In the lower left is a concentration chart with additional symbols for pressure ridges, cracks, and rafted ice..

11 S411 BSH ice charts available in S411, as well as some charts from other ice services ( ftp://ftp.bsh.de/outgoing/eisbericht/s411/). It is planned to incorporate charts in S411 format into the JCOMM Ice Logistics Portals Climatological data (e.g. ice atlas) should also become available.

12 Different presentation of one S411 dataset WMO/IHO standard color scheme: * Concentration * Stage of development * (Ship capability) User defined color scheme: * Drift velocity * Divergence and convergence * (any other) 12

13 S411 parameters A whole set of ice parameters are defined in the IHO/WMO ice objects catalog. Used model parameters: Concentration Thickness/Stage of development Drift speed and direction Divergence and convergence Needed/nice to have parameters: Ridging strength and orientation Rafting Compacting strength Floe size Snow cover.

14 Route optimisation In the IRO2 project a fine resolution oceansea iceatmosphere model was embedded in an Arctic wide oceansea ice model with data assimilation. The model results were used for a ship specific ice route optimisation. Routes and model ice charts were directly presented on an ECDIS system.

15 Further development of S411 A) better iceberg objects (points lines and polygones?) B) changing portrayal according to scale: change colors to whitegrey at larger scales group together same symbols if the overlap join different overlapping symbols (e.g. rafted and ridged ice into a symbol denoting heavy ice.

16 S4112: ice from far away

17 S411 + S4112 close by: ice concentration

18 S411 + S4112 close by: ice stage of development

19 Ice characteristics relevant for shipping Pictures: Mikhail Dobrynin, Niels Fuchs Ice concentration Ice thickness Floe size Convergence / divergence Snow cover 19

20 Ice in SARdata Spatial resolution or temporal coverage? Envisat ASAR WSM, ~150m spatial resolution TerraSARX ScanSAR, ~18m spatial resolution 12th Polish German Seminar 20

21 SAR image classification sliding window to calculate texture values 1st and 2nd order texture parameters variance, entropy, GLCM Gulf of Riga, edges GLCM entropy Ice concentration published in BSH ice chart variance 12th Polish German Seminar 21

22 SAR image classification TerraSARX AMSR/E / AMSR2 (ARTIST Sea Ice ASI) TerraSARX ScanSAR, Bering Strait, result of inital image segmentation ice concentration derived from AMSRdata ice concentration of the image regions

23 SAR image classification inital image segmentation second segmentation step classification using additional informations derived from segments (shape, size, neighborhood) position and orientation of leads and cracks

24 Ice in SARdata Visual image interpretation water surface affected by wind new ice formation 24

25 Ice in SARdata: caveats frost flowers histogram of water surfaces depending on incidence angle (ENVISAT ASAR WSM) Atmospheric effects 25

26 Icebergs in SAR (Sentinel1) 26

27 Iceberg detection (TerraSARX) section of a TerraSARX Stripmap image (Disko Bay / 23rd April 2013) comparison of TerraSARX images taken over the Grand Banks with detections of airborne International Ice Patrol (IIP) ongoing From an DLR presentation by Gottwald to the polar space task group, 2014

28 Iceberg detection: caveats Detecting large icebergs (>100m) with SAR is a maturing science although significant challenges remain relative to: Detecting small icebergs, bergy bits and growlers Detecting icebergs in sea ice Detecting icebergs in differing sea states Differentiating icebergs from small vessels From Satellite Observational Requirements for Floating Ice Focusing on SAR by John Falkingham. From Astrium price list

29 Thanks for your attention