1. Data Storage and Editing
(Entity and attribute) DeMers Chapter 6

2. Introduction
Any analysis performs must be based on good data, correctly organized and in the proper format.
In raster, we may need to display each coverage to isolate illogical or out-of-place grid cells as we compare them to the input document
In vector systems, we may have to build in topology after the initial data input, to pinpoint any digitization errors
In case of entity-attribute agreement, we may need to output sample portions of our map for comparison against the original input material

3. Storage of GIS Databases
Raster: Attribute values for grid cells are the primary data stored in the computer. Values make up the actual grid and positions of grid cells catalogued relative to the order in which they appear e.g., if you store the origin of the grid, cell size, and number of rows and columns, all you need is the cell values
Vector: Common for GISs to store vector entities and associated attributes in separate files (reason for RDBMS). For example, in ArcView shape file format, entities are stored in one file, attribute in another, and projection info in a third file and Arc/Info Coverage ( workspace, entity directory, info directory )
Tiling - storage of individual sections (tiles) in predefined subsections. The purpose is to reduce volume of data needed for analysis of any particular section e.g., quad boundaries, T&R grid, etc.

4. The Importance of Editing the GIS Database
Most errors result from improper input
Generally, at least some errors will always occur and require editing, e.g., pushing the wrong digitizer button (vertices instead of node), pushing the wrong keyboard button when entering attribute information, and position errors in digitizing (shaky hand)
3 general types of error
Entity error - (position error), primarily associated with vector model (missing entities, incorrectly placed entities, disordered entities)
Attribute error ( occurs in both vector and raster models, typing errors, misspelling, etc.
Entity-attribute agreement error ( a.k.a., logical consistency, correctly type codes attached to wrong entities)

5. Accuracy
The degree to which information on a map or in a digital database matches true or accepted values
An issue pertaining to the quality of data and the number of errors contained in a data set or map
It is possible to consider horizontal and vertical accuracy with respect to geographic position
Attribute accuracy - conceptual, and logical accuracy
Level of accuracy required for particular applications varies greatly. Highly accurate data can be very difficult and costly to produce and compile
e.g., mapping standards employed by the United States Geological Survey (USGS): "requirements for meeting horizontal accuracy as 90 per cent of all measurable points must be within 1/30th of an inch for maps at a scale of 1:20,000 or larger, and 1/50th of an inch for maps at scales smaller than 1:20,000."

6. Accuracy Standards for Various Scale Maps
1:1,200 ± 3.33 feet
1:2,400 ± 6.67 feet
1:4,800 ± feet
1:10,000 ± feet
1:12,000 ± feet
1:24,000 ± feet
1:63,360 ± feet
1:100,000 ± feet

7. Accuracy Standards for Various Scale Maps
1:1,200 ± 3.33 feet
1:2,400 ± 6.67 feet
1:4,800 ± feet
1:10,000 ± feet
1:12,000 ± feet
1:24,000 ± feet
1:63,360 ± feet
1:100,000 ± feet

8. Precision
Refers to the level of measurement and exactness of description in a GIS database (e.g., number of decimal places)
Precise locational data may measure position to a fraction of a unit e.g. to the millimeter
Precise attribute information may specify the characteristics of features in great detail
Important to realize, however, that precise data--no matter how carefully measured--may be inaccurate
Level of precision required for particular applications varies greatly. Engineering projects such as road construction require very precise information measured to the millimeter. Demographic analyses of marketing or electoral trends can often make do with less, say to the closest zip code or precinct boundary

9. Why be concerned about error
Why be concerned about error? - The Problems of Propagation and Cascading
Discussion focused to this point on errors that may be present in single sets of data
”Doing" GIS usually involves comparisons of many sets of data. If errors exist in one or all of the data layers, the solution to the GIS problem generated from them may itself be erroneous
Inaccuracy, imprecision, and error may be compounded in GIS that employ many data sources

10. DIGITIZATION-continue
Tic 3 2 1 4
Geographic
features

11. Error Propagation and Cascading
Occurs when one error leads to another
Means that erroneous, imprecise, and inaccurate information will skew a GIS solution when information is combined
DeMers - "error prone data will lead to error prone analysis"
e.g., if a map registration point has been mis-digitized in one coverage and is then used to register a second coverage
Result = the second coverage will propagate the first mistake
In this way, a single error may lead to others and spread until it corrupts data throughout the entire GIS project

12. Entity Errors: Vector No extra entities have been entered
Six categories identified by DeMers/ESRI
All entities that should have been entered are present
No extra entities have been entered
Entities are in the right place and are of the correct shape and size
Entities that are supposed to be connected to each other are all polygons have a single label point which identifies them
All entities are within the outside boundary identified

13. Nodes and Vertices Specific types of entity errors in vector GIS
can involve points, lines, polygons, nodes, vertices, label points
nodes - denote ends of lines or point where polygon closes on itself
vertices - denote change or direction within a line
points -> lines -> polys
Nodes are used to show specific topological relationships, e.g.:
intersection of roads or streams
intersection between stream and lake
node errors include pseudo nodes and dangle nodes

14. Pseudo nodes Occur where lines connect with itself or other line
A line connects with itself to form a polygon, a.k.a. island pseudo node (fig. 6.1a, p. 161)
Also occur where two lines intersect (rather than crossing) (fig. 6.1b)
Pseudo nodes are not necessarily errors, but indicate the potential location of errors
e.g., pseudo node in the middle of a line representing a node can be used to separate road into two different speed limit zones
Others may indicate error, (pushed wrong button when digitizing, placed cursor at wrong location)

15. Pseudo node connects two and only two arcs
Digitization errors- Pseudo node (Diamond)
Pseudo node connects two and only two arcs
Pseudo node Not representing a serious errors
Pseudo node
Error

16. Dangle nodes A single node connected to a single line
Again, not necessarily and error, but may be
Can result from three possible mistakes: (fig. 6.2, p. 162)
Failure to close a polygon
Undershoot
Overshoot
Sometimes result from incorrect placement, sometimes from fuzzy tolerance and snapping distance
One method of general error detection is comparing digitized to original document at equivalent scales good for broad scale obvious errors, not for finer scale errors

17. DIGITIZATION
For linear features such as rivers, roads, railways it is important to digitize each section separately (start node and end node at a specified section) or use Route latter
Node

18. Digitization errors - Dangle Error (square)
Overshoot
Closed polygon
Undershoot
Road
Natural feature
Acceptable dangle node
e.g. end of roads

19. Label point and sliver errors
Polygon label point errors ( points -> lines -> polys)
Label point is used to associate a polygon with attributes
If label point is missing, or there are more than one, indicates error e.g., fig. 6.4, p. 163
Sliver polygon errors
Commonly result from incorrect practice of double digitizing
Can also result from overlay or merging operations which join coverages from different sources
Can be removed manually or by dissolving polygons less than a certain area and/comparing intended number of polys with actual number (Fig. 6.5, p.164)

20. Digitization errors-Labels
Missing labels or too many labels
too many labels
missing labels

21. Sliver polygon errors

22. How to correct digitization errors?
List digitization errors using the command (Nodeerrors and Labelerrors)
Using ARCEDIT to edit the coverage then use the commands (edit feature (ef) e.g. ef label, ef node, ef arc
Use a series of commands such as nodesnap, arcsnap, reshape, split, add, delete, move, copy, rotate, extend, and unsplit
For labels use Createlabels

23. Topology
Topology is the process of projecting complex surfaces to a simple ones
Topology is a procedure for explicitly defining spatial relationships connecting adjacent features (e.g., arcs, nodes, polygons, and points).
Different types of spatial relationships are expressed as lists of features e.g.
An area is defined by the arcs comprising its border
An arc is defined by set of points (X,Y)

24. Topology-Main Concepts
The three major topological concepts are:
Connectivity: Arcs connected to each other at nodes
Contiguity/Adjacency: Arcs have direction and left and right sides
Area Definition:: Arcs connected to surround an area define a polygon (area)

25. Spatial Relationships (Topology)
Area Definition
Connectivity
Adjacency 21 21 21

26. PolygonTopology

27. Advantages of Topology
Check for digitization errors (overshoot, undershoot, unclosed polygon, missing labels, too many labels)
Store data more efficiently (eliminate data redundancy-normalization)
Make spatial analysis more faster

28. Topology Topological data structures dominate GIS software.
Topology allows automated error detection and elimination.
Rarely are maps topologically clean when digitized or imported.
A GIS has to be able to build topology from unconnected arcs.
Nodes that are close together are snapped.
Slivers due to double digitizing and overlay are eliminated.

29. Creating topology in Arc/Info
After digitization and correction to digitization errors topology can be built
The command BUILD is used for point, line, or polygon coverages
The command CLEAN is used for line and polygon coverages
CLEAN never create topology for point coverage
BUILD never detect intersection of arcs and polygons

30. Topology commands
C:\[ARC] CLEAN [in-cov] {out-cov} {dangle-length} {fuzzy-tol}
C:\[ARC] CLEAN road1 road2 # 3.4
C:\[ARC] BUILD [in-cov] {POLY/ LINE/ POINT}
C:\[ARC] BUILD cities POINT
For features that have no intersection such as contours, BUILD with line option can be used
For features that have intersection such as roads and lots, it is better to first use CLEAN and then use BUILD

31. Tables created by topology
Arc Attribute Table (AAT)
Polygon Attribute Table (PAT)
Point Attribute Table (PAT) Area and perimeter = 0
Route Attribute Table (RAT)
Feature Attribute Table (FAT)
Node Attribute Table (NAD)

32. Hint for topology
Make a copy of the original data before start building topology
Make a known strategy for naming of the coverages
For example, names of raw coverages start with R e.g Rroads and Rlanduse
Keep coverage names less than or equal 8 characters and without extension (8.3)

33. Coordinate Transformation
The tablet coordinates must be converted to real world (map) coordinates
The commands that used for coordinate transformation are:
CREATE or GENERATE - used to create a master coverage
The (X,Y) of the tic file (Tic.dbf) must be set to map coordinates.
TRANSFORM - used to transform the coverage

34. Coordinate Transformation-continue
Latitude (Ø) and longitude () must be converted to Decimal degrees (DD) e.g. Latitude = 13 deg+ 45 min/60+55/360
Project the decimal degrees to plane coordinate e.g. UTM
(50,80)
(5,8)
Map
coordinates
Digitizer
coordinate
(0,0)
(0,0)

35. Generate
Generate can create a coverage from raw coordinates (Id, X,Y) e.g. from GPS
Create a file of tic coordinates e.g. Tic1 which is ACII with (TICID, X, Y)
Create a file of polygon coordinates e.g. poly1
GENERATE: INPUT Tic1 :TICS
GENERATE : INPUT Poly1: POLYS :Quit

36. Attribute Errors: Raster and Vector
Attribute errors generally more difficult to detect
Types include:
Missing attributes perhaps only kind of attribute error traceable without comparison to source material e.g., plot all polygons and color them according to a certain attribute, if color is missing, attribute is missing
Incorrect attribute values or text more difficult to detect one method is to plot all polygons and color them according to a certain attribute, if only one polygon has a certain attribute and there should be other, it may stick out, in general, involves direct comparison with source material)

37. Dealing With Projection Changes
Often times, regardless of input method, separate GIS data input for a project will be based on different projection systems
Necessary to transform all data to common system before use in integrated modeling examples in ArcView
Joining Adjacent Coverages: Edge Matching (Union)
Joining two adjacent coverages (usually of the same theme) together to produce a single data set that covers a broader region edge matching also done in raster systems

38. Conflation and Rubber Sheeting
Conflation and Rubber Sheeting: Refers to the registration (georeferencing) of two maps (vector or raster) in a non-linear way (Ovelay two maps)
Used to make maps of different sources spatially correspond with one another. Most often used in raster data using ground control points (GCPs). Conflation and rubber sheeting are synonymous terms according to DeMers (Figure 6.1, p. 174)
The need to geo-reference internal objects themselves not just the map corners (Rubber Sheeting)
Templating: " cookie cutting"
If you have multiple coverages of different extents, the template is used to "cookie cut" them all to the same extent

39. Exercise Characteristics of data storage in raster and vector
3 general types of error in spatial databases
Accuracy vs. precision
Error propagation and cascading of error in GIS
Types of errors in vector GIS
Types of errors in attribute data
The concept of topology - what is it, what types of Relationships are stored for point, line, and poly features, why do we need it in GIS?