TerraLogik was contracted by NAV CANADA to generate a 1:500,000-scale topographic base from 1:50,000-scale data for use in aeronautical navigation charts. TerraLogik used the raster analysis tools in FME, coupled with custom Python code and the GDAL open-source library, to create generalized contours at 1:500,000 scale from 1:50,000-scale DEMs covering Canada and the Northern United States. See how the WorkspaceRunner is used to perform this process - and reduced processing time from 24 hours to 1 hour per chart.

1. Using FME To Efficiently
Create National-Scale Vector
Contours From High-
Resolution DEM Data
Todd Lewis
President, TerraLogik.com

2. Outline
 Intro
 Problem Description
 Technical Issues
 Solution Approach w/ Demo Workspaces
 Q & A
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3. Introduction
 NAV CANADA produces navigation charts for
general aviation (Visual Flight Rules Navigation
Charts – VNC)
 Charts are used in visual conditions (3-5 nautical
miles visibility)
 Charts are based upon standards set by the UN
International Civil Aviation Org (ICAO) in
Montreal
 TerraLogik designed the processes and
procedures for topographic data supporting the
VNC
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4. 4
Hurry up Jake! Turn the prop and get in!
The owners are coming!!!

5. Problem Definition
 VFR Navigation Charts series composed of
52 charts covering the Canadian Territory,
and 7 Terminal Area Charts.
 VNC series contains 70+ layers of
topographic information from multiple
sources.
 ICAO specifications provide guidelines on
how to depict each layer of information.
 Application of ICAO guidelines is
inconsistent across the entire VNC series.
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6. Problem Definition (2)
 Fitness for Purpose is a key consideration:
 Lambert Conformal Projection to enable accurate great-
circle distance/bearing calculations
 Obstacle and terrain avoidance
 Cartographic considerations such as labeling, feature
context, scale, etc.
 Visual reference for navigation in-flight for
ground-based features, primarily:
 Water
 Roads/rail
 Utilities
 Landforms
 Built-up areas and remote buildings/structures
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7. Our Approach
 Standardize the depiction and
cartographic rules to consistently present
VNC terrain data across the entire chart
series.
 Develop automated processes to do the
heavy lifting in application of cartographic
rules to create a chart.
 Document procedures and workflows to
enable production operators to perform
their work within an ISO 9002
environment.
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8. Deliverable : Terrain Data File
 Produce a Terrain Data File with agreed-to:
 Format (# files, depictions, settings, etc.)
 Structure (level names, order, content/level)
 Content (level of detail to show, rules)
 Document procedures and workflows for
production of charts using ETL and CAD tools
 QA/QC checklists and manual editing procedures
to clean-up Terrain Data File before passing to
aeronautical information integration and pre-
press finishing procedures
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10. Terrain Data File

11. Topographic Data File

12. Labels Data File

13. Hypsometry Data File

14. Shaded Relief Data File

15. Elevation Technical Issues
 Contour and hypsometry required at 500-ft
intervals
 Elevation data not consistently available at
1:50,000-scale across Canada
 Integration with US data at border areas
 US data available at 1” below 49, and 2” in
Alaska
 Source data is CDED 1:50K, 1:250K, ASTER
GDEM, and USGS DEM
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16. 16
Charts Affected
by Elevation Issues:
•Alert
•Ellesmere
•Devon Island
•Baffin Bay
•Cumberland Peninsula
•Frobisher Bay
•Ungava
•Foxe Basin
•Inukjuak
Red is missing CDED data. Elevation data, where missing,
will be populated using NASA ASTER data.
•Coats Island
•Baker Lake
•Boothia
•Resolute
•Banks Island
•Hazen Strait
•Mackenzie Delta
•Amundsen Gulf
•Cambridge Bay
•Klondike
•Great Bear Lake
•Bathurst Inlet
•Rankin Inlet
•Yellowknife
•Fort Simpson
•Kitimat
•Anticosti
Winnipeg
Flin Flon
Rankin
Inlet
Resolute

17. Data Mismatch
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USGS Elevation
Data
Canadian
Elevation Data
CAN/US Border
Missing Data

18. Software Limitations
 Each VNC Chart is composed of 350-400
1:50,000 CDED tiles
 GIS & RS tools could create contour lines, but
determining hypsometric tint requires
polygon fills
 Chart borders present issues with
polygonizing contours
 Volume of data presents huge challenges for
processing and visualization
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19. Requirements
 Need to create:
 Hypsometric Polygons at 500’, 1000’, 2000’,
3000’, 5000’, 7000’, 9000’, 12000’
 Contours @ 500’ intervals <= 4000’
 Contours @ 1000’ intervals > 4000’
 350-400 1:50,000 tiles per chart
 Contours, hypsometry, spot elevations, and
the shaded relief need to align
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20. Solution Ingredients
 Transformer Loop
 RasterExpressionEvaluator Transformer
 GDAL for raster-to-vector conversion
 PythonCaller for coding GDAL
 WorkspaceRunner
 Generalizer
 Throw in some algorithms to:
 Select significant contours for print scale:
 Area/Perimeter > Tolerance
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21. Process: Tiles First
 Break raster into one band per contour
interval (1-18 bands total per tile)
 Batch process the above with
WorkspaceRunner Synchronous/Async:
 Time w/o Async: 20 hours
 Time w/ Async: 1.5 hours
 Convert each band into a vector polygon
layer
 Use PythonCaller and GDAL to perform
raster-to-vector conversion
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22. Process: Merge & Generalize
 Dissolve all polygons grouped by elevation
level (500,1000,1500,…)
 But need to look for depressions,
DonutHoleExtractor
 But need to densify for generalization
 Generalize
 Look for generalization errors, polygons w/
NaN for area are errors to be logged
 Evaluate for print scale using algorithm:
 Area/Perimeter > Tolerance (0.0005 or 0.001)
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23. Process: Symbolize
 Select Hypsometry values
 Remove depressions from hypsometric levels
 Convert all polygons to contour lines
 Change depression contours to normal
contours if on hypsometry level
 Output hypsometry and contours to
Microstation levels with symbology from seed
file
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24. Example Output (false color)

25. Questions? Todd Lewis
President
TerraLogik Information Systems Inc.
T: 613.862.0999
E: todd.lewis@terralogik.com