Data Storage and Editing

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Data Storage and Editing

• (Entity and attribute) DeMers Chapter 6
• http//www.iupui.edu/jeswilso/g438/lecture5/

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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

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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, TR
  grid, etc.

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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)

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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 120,000 or
  larger, and 1/50th of an inch for maps at scales
  smaller than 120,000."

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Accuracy Standards for Various Scale Maps

• 11,200 3.33 feet
• 12,400 6.67 feet
• 14,800 13.33 feet
• 110,000 27.78 feet
• 112,000 33.33 feet
• 124,000 40.00 feet
• 163,360 105.60 feet
• 1100,000 166.67 feet

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Accuracy Standards for Various Scale Maps

• 11,200 3.33 feet
• 12,400 6.67 feet
• 14,800 13.33 feet
• 110,000 27.78 feet
• 112,000 33.33 feet
• 124,000 40.00 feet
• 163,360 105.60 feet
• 1100,000 166.67 feet

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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

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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

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DIGITIZATION-continue
Tic

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1
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Geographic features
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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

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Entity Errors Vector

• 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

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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 -gt lines -gt 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

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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)

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

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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
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Digitization errors - Dangle Error (square)
Overshoot
Closed polygon
Undershoot
Natural feature
Acceptable dangle node e.g. end of roads
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Label point and sliver errors

• Polygon label point errors ( points -gt lines -gt
  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)

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Digitization errors-Labels

• Missing labels or too many labels

too many labels
missing labels
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Sliver polygon errors
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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

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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)

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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)

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Spatial Relationships(Topology)
Area Definition
Connectivity
Adjacency
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PolygonTopology
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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

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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.

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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

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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

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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)

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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)

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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

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Coordinate Transformation-continue

• Latitude (Ø) and longitude (?) must be converted
  to Decimal degrees (DD) e.g. Latitude 13 deg
  45 min/6055/360
• Project the decimal degrees to plane coordinate
  e.g. UTM

(50,80)
(5,8)
Map coordinates
Digitizer coordinate
(0,0)
(0,0)
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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

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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)

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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

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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

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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?