creating terrain models with fme - excellence center for fme · 1 creating terrain models with fme...
TRANSCRIPT
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Background
EU Noise Directive
– Calculate noise from roads with
annual daily traffic > 8000
New model and application for
noise calculation
– Nord2000 (Nordic model)
– NorStøy
Norstøy terrain model
requirements
– ESRI ASCII GRID
– 10x10m grid size
– Elevation in cm
– Integer values
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Input data
Vector data from the base map
– Elevation data, Hydrography, Constructions, Road situation, Railway data and Airport data
Format
– QUADRI
• The format for GIS/LINE, from Norkart
• FME Reader: GDMMAPPER
– File based (4 files pr dataset)
– One set of files pr theme pr municipality
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Other data
Road buffer
– The area that the terrain model shall cover
Tiles
– Grid with 5x5km squares
– Used in loops, to reduce memory usage
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Working with terrain models
Base data DEM Generation DEM
80% Data preparation
15% Interpolation
5% Final preparation
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Challenges
Memory usage
– Large data amounts
– Detailed data
– Long objects
Identifying data that represent the surface
– Remove bridges etc
Bad 3D-geometry
– No elevation
– Some vertices missing elevetaion
Integer output values
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Reducing memory usage
"Umbrella" workspaces
– WorkspaceRunner
Data preparation
– Handle theme/municipality files one by one
– Clip to Road buffer
Terrain modelling
– Generate model in tiles one by one
– Merge at the end
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The process
Data preparation
Model tiles
Terreng.gdb
(Geodatabase)
Complete model
Base data
(QUADRI)
Topg.asc
(ESRI ASCII
GRID)
*.asc
(ESRI ASCII
GRID)
Sections.mdb
- Road buffer
- GRID tiles
(Geodatabase)
Loop through themes
and municipalities
Loop through tiles
Merge tiles
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Step 1: Data preparation
Result
– Geodatabase Terrain.gdb
Features transformed into four classes
– 3D Points
– 3D Lines (contour lines)
– Breaklines
– Flat areas (lakes, parking areas etc)
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Data preparation - Filter
Features that are supposed to
represent the terrain surface
– Feature type
– Vertical level (attribute)
• Remove bridges, tunnels etc
Clip against road buffer
– Extra buffer of 500m ensure
the model close to the road
buffer edge
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Data preparation - Geometry cleaning
Remove spikes
– Critical for the model!
Remove features without elevation
Figur her!
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Data preparation - Geometry cleaning
Self intersection
Split long lines (chopper)
Generalization
– Resolution of 10x10m in the model
– generalize with 1m tolerance
Scaler and CoordinateRounder
– Elevation values in integer cm
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Data preparation - Flat areas
Flat areas:
– Lakes, ocean, parking areas etc
Calculate standard deviation for vertex elevations
Areas with standard deviation < 50cm are considered to be flat
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Data preparation - result
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Step 2: Model tiles
Result
– ESRI Ascii GRIDs pr tile
Overlap of 50m between models
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Model tiles generation
1. DEM Generator– Output: DEM Points
2. PointOnArea between DEM Points and Flat areas– 3D Forcer for points within
flat areas
3. Clip DEM Points against Tile and Road Buffer
4. CoordinateRounder– Integer values for all
coordinates
5. NumericRasterizer – Convert to raster
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Step 3: Complete model
RasterMosaicker
– Merge all model tiles into one complete model
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Quality
Given the 10x10m resolution– The accuracy of the input data is "good enough" – The best indication on the quality of the model is the age of the base
data• Man made changes in the terrain
Old data New data
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Man made change: gravel pit
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Metadata
From prepared data:
– Extract year from date updatet
– Converts to raster with Year updated as value
Convert the raster to polygons
Export to ESRI Shape
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Questions