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GEOSECTIONING DNC ® Data

GEOSECTIONING DNC ® Data. Prototype and Development Project Phase V. David Turnbull 03 May 2006 NGA HydroVision Production Cell. Goals of Effort. Have an in-house automated capability to convert DNC ® data into a one-feature-one-time format to easily incorporate into any database.

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GEOSECTIONING DNC ® Data

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  1. GEOSECTIONING DNC® Data Prototype and Development Project Phase V David Turnbull 03 May 2006 NGA HydroVision Production Cell

  2. Goals of Effort • Have an in-house automated capability to convert DNC® data into a one-feature-one-time format to easily incorporate into any database. • Create and demonstrate a new prototype version of the DNC® where it is one-feature-one-time. • Gain the many side benefits created by having these automated tools.

  3. Concepts • Geo-sectioning • One Feature One Time • New Attribution to DNC® • Generalization and SCAMIN • Common tile sizes • Common Schema • Libraries based on one or more 1 degree tiles

  4. SCAMIN (Scale Minimum) • SCAMIN is used in some degree with the international community with S-57. • SCAMIN is the least scale in which a feature should be portrayed • Currently based mostly on HACG scale ranges • Harbor: 0-49,999 • Approach: 0-99,999 • Coastal group 1: 0-249,999 • Coastal group 2: 0-499,999 • General: 0-2,500,000

  5. Loaded 29 CDs into single Database • Development with Laser-Scan, Inc. (LSI) which gave Lamps2 an automated mass importer of DNC® CDs into a Gothic Object-Oriented (OO) Database • Loaded all 29 CDs into individual databases within the database in the NGA HydroVision Production Cell (NPC). • A single CD can be imported with a few clicks- • average time for a CD: 40 minutes • NPC has the latest of all the CDs loaded into the Gothic database • Also can run batch processing on multiple libraries

  6. Propagated Into Single Dataset • Chose the entire DNC17 since we had been maintaining it (last 3 phases as well) • All DNC17 data brought into a single dataset using a fully automated tool created within Lamps2

  7. New Attributes Added During Feature Propagation • New attribution is per individual feature or object and added automatically • New attributes: • Library Name-Name of the original library • “DNC17_h1708210_Baltimore” • Chart Identifier-Chart number feature came from • Chart Edition Number-Edition of Chart • Chart Scale (NEW FOR THIS PHASE) • Hydrographic Datum (soundings only)

  8. Geo-sectioned and Generalized Data • Originally manual • Now fully automated process (one click) • Step 1-initial SCAMIN attribute created and populated per feature based on library type. • Step 2- Pub Aid Number and Pub Number attributes added and populated from Text Attribute for Buoys, Beacons, and Lights • Step 3-Uses the Data Quality Areas (DQY) to spatially select the features and splits all line and area features at DQY boundaries.

  9. Geo-sectioned the Data (2) • Step 4- Process features by DQY and search within a defined radius to see if there are matching features of smaller scale. If there are, the SCAMIN attribute value is replaced with the smaller scale. (Point features only) • Lights-Additionally compares Publication Aid Number (PAN) and Range. If the range is not equal it looks at the PAN. If the PANs are equal it is a matching feature. If the PANs are not equal it produces a new QR light feature so that the compiler can visit it and determine if it is a different light or an error.

  10. Geo-sectioned the Data (3) • Step 5-Deletes unwanted, smaller scale, overlapped features. • Only the best scale features are kept within the DQY. • The data is now one-feature-one-time in a single dataset

  11. Created the New Tiles • Created Tiles within the new dataset using automated tile creator developed in the NPC using LULL, all tiles 1x1. • Areas which originally covered Harbors and Approach Datasets are now based on a 1 x 1 degree tile scheme. • Coastal and General areas are a maximum of 3 x 3 deg and a maximum of 9 1x1 deg tiles. • Tiles do not overlap, libraries do not overlap • Split data along new library boundaries (auto)

  12. New Datasets Based on Tiles • Each library will be made up of either 1 or many tiles up to a max of 9. • DNC17 divided into 246 tiles, 60 datasets • The new datasets are named incorporating the tile name, ex: h17hjfk • the h so that it will meet spec. All libraries start with h (easier for us to code for now) • 17 for DNC17 • hjfk for the tile that makes up the library

  13. New Libraries For DNC17

  14. Propagated Data to Datasets • Spatially queried each tile area and propagated the data from the single master dataset into each new tile library • Now fully automated for this phase

  15. Modified Files for Export • Changed export scripts to effect all libraries to be exported • Allows for export of the new attributes and tile sizes, now automated • Easy to modify the code/schema to accomplish this.

  16. Exported Data • All 60 libraries exported without viewing errors. • A cleanup process would be needed if we were to use it for production (edge-matching) • New attributes appeared properly structured within the VPF tables. • Created a Browse for the libraries (now automated) • Cut a CD of the new Prototype IV for DNC17.

  17. Test on ECDIS platforms • Gave to SPAWAR to modify COGENT to view the data and utilize SCAMIN. • Data views utilizing SCAMIN. • Load into various ECDIS platforms • FUND: Testing • ECPINS®: Testing • ICE: Testing • VMS: Testing

  18. Demonstration of SCAMIN • Created customized code within Lamps2 to demonstrate the SCAMIN value being used to “thin out” the visible data when zooming out/in. • Proof of concept, the ECDIS would have to be modified to utilize the SCAMIN attribute as SPAWAR has.

  19. Depth Distribution

  20. 500,000 view

  21. 250,000 view

  22. 100,000 view

  23. 50,000 view

  24. 25,000 view

  25. 10,000 view

  26. Benefits • We now can go to one-feature-one-time automatically in-house in order to populate the future NDME or NGA databases. • Proved that adding new attributes to the data properly will not kill the ECDIS functionality. • Size of the data on a CD is smaller. • Normal DNC17= 415 MB • Geo-sectioned DNC17= 274 MB • No duplication in collecting.

  27. Side Benefits • Have used it already for the foundation for the EPODS effort to supply one-feature-one-time data • Have used it to supply custom datasets to several customers (NAVO, TRANSCOM, HYSAS) • Utilized tools to create a One-Feature-One-Time Global DNC® coastline. • In process of using tools to create an ArcGlobe global DNC® model.

  28. What is next…Phase V • Further testing on ECDIS platforms • Finish display methods in Lamps2 to utilize the SCAMIN values for lines and areas. • Possibly Adding Chart limit feature class for Hardcopy. • Possibly creating a model using more SCAMIN bands similar to the IHO models • Possibly incorporating new agreed upon attributes from DNC2/Data Model/S57 efforts

  29. QUESTIONS?

  30. Know the Earth…Show the Way NATIONAL GEOSPATIAL-INTELLIGENCE AGENCY

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