Geog 458: Map Sources and Errors - PowerPoint PPT Presentation

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Geog 458: Map Sources and Errors

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Secondary data capture: a map in itself the model of reality; ... Some values are determined by other attributes. Zip code and State. County name and FIPS code ... – PowerPoint PPT presentation

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Title: Geog 458: Map Sources and Errors


1
Geog 458Map Sources and Errors
  • January 20, 2006
  • Data Storage and Editing

2
Outlines
  • Importance of data editing
  • Detecting and editing different types of errors
  • Entity errors
  • Attribute errors
  • Combining data of different sources
  • Transformation
  • Rubber-sheeting
  • Metadata content standards

3
1. Importance of data editing
  • Data input necessarily involves diverse errors
  • Primary data capture positional accuracy of GPS
    receivers, geometric distortion of air photo,
    malfunction of electronic scanners
  • Secondary data capture a map in itself the model
    of reality digitizing with no proper use of
    editing tool (e.g. snapping), vectorization
    without postprocessing, georeferencing with
    imprecise control points
  • Data transfer information loss caused by (1)
    file conversion (2) lack of communication (no
    metadata) (3) ignorance of GIS users
  • Data editing can determine whether to cut off
    chains of imperfection (from data input, to
    analysis, and decision-making)
  • Data editing is the process for detecting and
    eliminating errors inherent in data input, and
    avoiding error-prone analysis that may lead to
    wrongfully informed decision

4
2. Detecting errors in a single dataset
  • Reading (DeMers chapter 6) distinguishes between
    entity (spatial) and attribute (non-spatial)
    errors
  • Entity errors
  • Node errors dangling nodes, pseudo nodes
  • Polygon errors sliver, incorrect label point
  • Attribute errors
  • Incomplete values
  • Incorrect values

5
Node
  • What is node?
  • A node is an endpoint of an arc. The from-node is
    the first vertex in the arc the to-node is the
    last vertex. Arc-node relation defines
    connectivity
  • Node types
  • Normal
  • Dangling
  • Pseudo

6
Node errors
  • Dangling and pseudo nodes often identify
    automation errors however they can also be valid
    components of a feature
  • Dangling node, if not legitimate (e.g.
    cul-de-sac) may indicate errors
  • Pseudo node, if not legitimate (e.g. island,
    attribute change) may indicate errors
  • How do I check node errors?
  • GIS provides functionalities for labeling
    potential node errors
  • But most of error detection requires visual
    inspection
  • How do I fix node errors?
  • Interactive editing in a proper snapping
    environment Editor toolbar
  • Automated data cleaning with a reasonable
    tolerance level Topology toolbar

7
Displaying potential node errors
  • Dangling nodes
  • Pseudo nodes

8
Node errors
  • Why do I have to fix node errors?
  • Because it ensures correct topology that forms
    the basis for further analysis
  • It validates connectivity
  • If the data is used for network operations such
    as hydrological model or routing
  • It validates contiguity
  • If the data is used for spatial overlay such as
    point-in-polygon, intersection between line and
    polygon

9
Polygon errors
  • Most common polygon errors
  • Missing or multiple label points in arc/info
    coverage
  • Sliver polygon
  • How do I identify polygon errors?
  • Label error labelerrors in arc/info workstation
  • Sliver polygon select areas where its area is
    less than reasonably small value
  • How do I fix polygon errors?
  • Label error createlabels in arc/info workstation
  • Sliver polygon merge silver polygon to
    neighboring polygon (use eliminate in arc/info
    workstation)

10
Attribute errors
  • Missing attribute values
  • Compare the unique list of values to master list
  • Check -9999 (use query builder or selection tool)
  • Incorrect attribute values
  • Typing errors spelling check
  • Domain check compare the list of values to a
    range of possible values
  • Land use code should be within a certain range
  • Longitude in decimal degree should be minus for
    Seattle
  • Some values are determined by other attributes
  • Zip code and State
  • County name and FIPS code
  • Validate values using spatial overlay
  • Seattle-based company should be located in
    Northwestern US

11
Checking topology errors in geodatabase
  • Define topology rules
  • Make an edit that participates in topology using
    topology editor toolbar
  • Then you can validate the entire topology
  • Error inspector will list which edit violates
    rules
  • Based on output from error inspector, topology
    errors can be corrected or made as an exception
    if errors are not errors indeed (e.g.
    cul-de-sacs, attribute change in the road)

12
3. Combining data of different sources
  • When you work on data of different sources and
    they are not well aligned spatially even after
    projection change, it is necessary to make
    spatial adjustments of a layer to the layer with
    a higher accuracy
  • Two kinds of spatial adjustments transformation
    and rubber-sheeting
  • Transformation converts data from one coordinate
    system to another can be used to shift your data
    within a coordinate system (shift, rotate,
    enlargement and so on)
  • Rubber-sheeting is usually used to correct for
    geometric distortions they may be introduced by
    imperfect registration in map compilation, lack
    of geodetic control in source data, and so on.
  • Spatial adjustment allows you to improve data
    quality

13
Transformation
Source control point
Destination control point
? Displacement links
14
Rubber-sheeting
  • Rubber-sheeting adjusts source layer (dashed
    line) to target layer (solid line) based on
    displacement links
  • Source layer is adjusted to target layer by
    setting snapping properties

Edge-matching
15
4. Metadata Content StandardSection 2 Data
Quality
16
Data Quality Components
  • Positional accuracy how much is position on data
    in hand deviated from data with higher accuracy
    (need well-defined point, geodetic control, road
    intersection or data from survey)?
  • Attribute accuracy how much is attribute on data
    in hand deviated from data with higher accuracy?
  • Logical consistency is data topologically clean?
  • Completeness are geographic features exhaustive
    within study area? Does attribute contain all of
    information needed?

17
Questions
  • In the readings, common error types are
    identified as follows. Identify data quality
    components P, A, L, C for each.
  • Is there any missing geographic features in data
    entered?
  • Are all entities within registration marks?
  • Do all polygons have a label point?
  • Do all entities have the right location?
  • Do all entities have the right shape and size?
  • Are all attributes values entered?
  • Are nodes connected to arcs?
  • Does polygon has any sliver?
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