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

Outlines 1. Importance of data editing 2. Detecting and editing different types of errors 1) Entity errors 2) Attribute errors 3. Combining data of different sources 1) Transformation 2) Rubber-sheeting 4. Metadata content standards

1. Importance of data editing Data input necessarily involves diverse errors Data input necessarily involves diverse errors Primary data capture: positional accuracy of GPS receivers, geometric distortion of air photo, malfunction of electronic scanners 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 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 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 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 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

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

Node What is 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 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 Node types Normal Normal Dangling Dangling Pseudo Pseudo

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

Displaying potential node errors Pseudo nodes Pseudo nodes Dangling nodes Dangling nodes

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

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

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

Checking topology errors in geodatabase Define topology rules Define topology rules Make an edit that participates in topology using topology editor toolbar Make an edit that participates in topology using topology editor toolbar Then you can validate the entire topology Then you can validate the entire topology Error inspector will list which edit violates rules 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) 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)

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 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 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) 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. 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 Spatial adjustment allows you to improve data quality

Transformation Source control pointDestination control point → Displacement links

Rubber-sheeting Rubber-sheeting adjusts source layer (dashed line) to target layer (solid line) based on displacement links 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 Source layer is adjusted to target layer by setting snapping properties Edge-matching

4. Metadata Content Standard Section 2: Data Quality

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)? 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? Attribute accuracy: how much is attribute on data in hand deviated from data with higher accuracy? Logical consistency: is data topologically clean? Logical consistency: is data topologically clean? Completeness: are geographic features exhaustive within study area? Does attribute contain all of information needed? Completeness: are geographic features exhaustive within study area? Does attribute contain all of information needed?

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