Digitizing and Scanning. Primary Data Sources Measurements Field Lab Remotely sensed data already secondary? Creating geometries Definitely in the realm.

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Presentation transcript:

Digitizing and Scanning

Primary Data Sources Measurements Field Lab Remotely sensed data already secondary? Creating geometries Definitely in the realm of secondary data Digitizing Scanning

Why Do We Have To Digitize? Existing data sets are general purpose, so if you want something specific you have to create it In spite of 20+ years of GIS, most stuff is still in analog form Chances are somebody else has digitized it before; but data sharing is not what it should be

Digitizer Digitizing table 10” x 10” to 80” x 60” $50 - $2,000 1/100 th inch accuracy Stylus or puck with control buttons

The Digitizing Procedure Affixing the map to the digitizer Registering the map Actual digitizing In point mode In stream mode

Georeferencing at least 3 control points aka reference points or tics easily identifiable on the map exact coordinates need to be known

Digitizing Modes Point mode most common selective choice of points digitized requires judgment for man-made features Stream mode large number of (redundant) points requires concentration For natural (irregular) features

Problems With Digitizing Paper instability Humidity-induced shrinking of 2%-3% Cartographic distortion, aka displacement Overshoots, gaps, and spikes Curve sampling

Errors From Digitizing Fatigue Map complexity ½ hour to 3 days for a single map sheet Sliver polygons Wrongly placed labels

Digitizing Costs Rule of thumb: one boundary per minute ergo: appr. 65 lines = more than one hour

Automated Data Input (Scanning) Work like a photocopier or fax machine Three types: Flatbed scanners A4 or A3 600 to 2400 dpi optical resolution $100 to $2,000 Drum scanner practically unlimited paper size $10k TO $50k Video line scanner produces vector data

Requirements for Scanning Data capture is fast but preparation is tedious Computers cannot distinguish smudges Lines should be at least 0.1 of a mm wide Text and preferably color separation AI techniques don ’ t work (yet?) Symbols such as  are too variable for automatic detection and interpretation

Semi-automatic Data Input (Heads-up Digitizing) Reasonable compromise between traditional digitizing and scanning Much less tedious Incorporating your intelligence

Criteria for Choosing Input Mode Images without easily detectable line work should be left in raster format Really dense line work should be left as background image – unless it is really needed for automatic GIS analysis; in which case you would have to bite the bullet

Conversion from Other Databases Autocad.dxf and dBASE.dbf are de facto standards for GIS data exchange In the raster domain there is no equivalent;.tif comes closest to a “standard” In any case: merging data that originate from different scales is problematic – in the best of all worlds; there is no automatic generalization routine