Review of Cartographic Data Types and Data Models

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Review ofCartographic Data Types and Data Models
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GIS Data Models
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Raster Versus Vector in GIS Analysis

• Fundamental element used to represent spatial
  features
• Raster pixel or grid cell.
• Vector x,y coordinate pair.
• Area for which data values are stored in each
  system
• Raster must store value for each cell of the
  grid, which covers the entire study area.
• Vector stores locational data only for objects
  of interest within the study area.

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Modeling Geospatial Reality
Raster Model
Vector Model
Real World
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Coding Vector GIS
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Coding Vector GIS
Vector Mode Model of Reality
Reality
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Coding Raster GIS Data
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Coding Raster GIS Data
1 1 1 1 2 3 4 4 1 1 1 2 2
3 4 4 1 2 2 2 3 3 4 4 2 2
2 3 3 4 4 4 3 3 3 3 5 5
5 5 1 1 1 1 6 5 5 5 1 1 1
1 1 5 5 5 1 1 1 1 1 1 5 5
Raster Mode Model of Reality
Reality
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Minimum Mapping Unit

• Your MMU should influence what real-world
  features make it into your digital
  representation.
• Raster 51 of a cell?
• Vector is a stream wide enough to be its own
  polygon? Should a house be the footprint as the
  polygon or should it be a point?

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Representing Value and Location in Space Points

• Raster points
• location cell position as specified by row and
  column position within grid, which should be
  geo-referenced.
• value specified by the number stored for the
  cell.
• Vector points
• location position specified by single x, y
  coordinate pair.
• value stored as data values in attribute file
  and tied to the point by means of a geo-code.

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Raster Encoding
Points in the World Out There
Points Encoded as Raster
Resulting Image
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1
Point X Y
2
1 X1 Y1
2 X2 Y2
3
3 X3 Y3
4 X4 Y4
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Vector Encoding
Points in the World Out There
Points Encoded as Vector
Resulting Image
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Representing Value and Location in Space Lines

• Raster lines
• location linear set of contiguous cells, each
  identified by a row and column location and each
  having the same data value.
• value data value of each linear feature is
  represented by the cell value stored for each
  cell.
• Vector lines
• location ordered set of x,y coordinate pairs.
• value a geo-code assigned to the line is tied
  to a geo-code in an attribute file where the
  computer stores the data value or values for the
  line.

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Raster Encoding
Lines in the World Out There
Lines Encoded as Raster
Resulting Image
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Line X Y
1 X11 Y11 X12
Y12 . . .
. . . X1n Y1n

1
2 X21 Y21 X2n
Y2n
3
2
3 X31 Y31 X32
Y32 . . .
. . . X3n Y3n
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Lines in the World Out There
4 X41 Y41 X4n
Y4n
Vector Encoding
Lines Encoded as Vector
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Representing Values and Location in Space Areas

• Raster areas
• location region of contiguous cells all of
  which have the same data value.
• value data value stored for each cell is the
  data value for the area e.g., for population
  density, a density of 589 would be represented by
  assigning each cell comprising the area the value
  589.
• Vector areas
• location closed set of x,y coordinate pairs.
• value point within area is tied by means of a
  key to an attribute file value or values to be
  assigned to the area defined by the x,y
  coordinates.

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Raster Encoding
Areas in the World Out There
Areas Encoded as Raster
Resulting Raster Image
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Capturing Vector Data
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34005
Digitizing Polygon 1
Digitizing Polygon 2
Digitizing Polygon 3
Digitizing is funfor a short time
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Area X Y
1 X11 Y11
X1i
Y1i X11 Y11

2 X21 Y21 X2i
Y2i X21 Y21
3 X31 Y31 X3i
Y3i X31 Y31
Areas in the World Out There
Vector Encoding
Areas Encoded as Vector
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Representing Values and Location in Space Volume

• Raster volume
• location row and column position represents
  position on the surface.
• value cell data value represents the height of
  the surface at the location of the cell.
• Vector volume
• location x,y coordinates position triangles that
  comprise a TIN.
• value z data value stored for each x,y
  coordinate position.

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Whether Raster or Vector

• All Layers Must Be Geo-referenced and Rectified

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Set of Layers Comprise Geodatabase Layers Must be
Rectified
Earth
Assign Coordinate Values to Locations
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Raster Conventions
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Raster Database Conventions

• Divide entire study area in a regular grid of
  cells.
• Assign one and only one data value to each cell.
• Database consists of a set of maps or layers each
  of which depicts the same well-defined region or
  study area Washington Township in Gloucester
  County.
• Each layer describes a single characteristic of
  each cell within the study area e.g., land use.
• Describe multiple features with multiple layers.

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Raster Definitions

• Orientation angle between true north and the
  direction defined by the columns of the raster.

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Raster Definitions

• Region within a single layer, a set of
  contiguous cells that all have the same value.
• Zone all of the regions within a layer that
  have the same value.

In much of the GIS literature Arc Maps region
is called a zone and Arc Maps zone is called a
class.
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Raster Zone and Region
All of the forest taken together represents a
single zone.
Each individual set of contiguous forest cells
represents a single region.
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Cell Value Assignment Qualitative Data

• Predominant type or majority rules--category
  taking up largest proportion of cell determines
  cell value land use.
• Cell center value-cell gets value of category at
  its center.
• Presence or absence e.g., if phenomenon is
  present, cell takes value--road
• Precedence of types assign cell a value
  reflecting the most important category present.
• Number or proportion e.g., cell value number
  of items present in cell--wells

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Majority Rules Assignment
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Presence / Absence
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Precedence of Type
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Ratio Value
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Interpolated Value
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Objects

• GIS Features as Objects is a recent method of
  representing aspects of the real-world in GIS
• Example of the shift from specialty data to DBMS
  that are spatially-aware
• Non-planar, temporally shifting, topologically
  linked, rule-based actions

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Vector Geometry as Objects

• Parcels
• Planar geometries with attribute information
• Parcels as objects in a Cadastral carpet
• Objects with topology rules (dont overlap,
  unless)
• Members of regional features (zoning,
  municipality)
• Composed of surveyed parts (COGO, benchmarks)
• Keys that link to attribute tables (owner(s),
  assessments, plans, etc)

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Cadastre Example
benchmark
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Attributes as Objects

• Not only can multiple sets of geospatial features
  interact with rules, the attributes can be linked
  with one another, with their own set of rules and
  actions
• Ownership record linked to GIS parcel
• Search on multiple owners, records
• Removal of parcel warns about orphan owner
• Functions that can be performed by GIS analyst
  can be embedded in the actual database

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GIS Models
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GIS Models Over Time

• Simple Representation
• CAD model
• Data Analysis
• Raster model
• Data Collection
• Vector model
• Relational and Rules
• Object model

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Geodatabases
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Geodatabase vs Other Formats

• Coverages and Shapefiles stored geospatial and
  attribute data in different locations in
  different formats
• .shp (proprietary binary format)
• .dbf (dBase database format)
• Geodatabases store both geospatial and attribute
  data in the same structure

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Benefits and Drawbacks

• Benefits
• GIS data can now be handled like most other data,
  and stored in a RDBMS
• Greater flexibility and functionality
• Enterprise level of managing data
• Drawbacks
• Speed hit
• Even more rope to hang yourself with

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ESRI Geodatabases

• File Geodatabase
• Introduced in 9.2, the File Geodatabase is the
  latest, greatest file-based format from ESRI
• Personal Geodatabase
• Introduced in 8.x
• Based on Microsoft Access/Jet Engine
• ArcSDE
• Software (now part of ArcGIS core) that allows
  RDBMSs to act as GIS data stores.

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File Geodatabase

• Latest format
• Best modern format for large datasets
• What you should be using for significant work
• Stores data on disk in several files within a
  directory named geodatabase.gdb

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Personal Geodatabase

• Based on Microsoft Access
• Great for bringing outside data into ArcGIS
• Limited to 2GB
• Can become clunky and slow as amount of data
  increases
• Stores data in one file called geodatabase.mdb

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ArcSDE/Enterprise database

• Most likely stored on an entirely different
  machine from the one youre running ArcGIS on
• Same basic functionality as other GDBs
• Concurrent users
• Managed (hopefully) by a DB administrator

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Working with Geodatabases

• At a minimum, consider it similar to a
  subdirectory with shapefiles
• Unlike shapefiles, you can enforce extents,
  storage types, projections, topology rules,
  connectivity rules, network-specific rules, and
  so on
• This additional functionality is implemented
  through Feature Datasets

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Feature Datasets

• A folder within the GDB, it preserves
  projection and extent information for data within
  the folder (feature classes)
• To make it useful, you must set extent and
  projection information
• Put some forethought into it before specifying
  projection and extent!

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Feature Datasets

• After creating a GDB, right click and choose New
  gt Feature Dataset
• The dialog boxes will step you through setting
  the variables for the Feature Dataset

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Importance of Extent

• The Geodatabase will only bother with the
  information within the extent
• It will throw an exception if you attempt to put
  something that doesnt fit in the box
• ArcGIS can preserve the difference between two
  points down to the molecular level
• Setting the extent allows you to control the
  precision at which ArcGIS handles data
• Needlessly too precise, and youll have errors
  thatll never show up on the screen, but will
  still impact your data

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Defining New Jersey

• ProjectionNJ State Plane (feet)
• Extent ?
• Should it be tight?
• Should it extend outside the boundaries?

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Defining New Jersey

• In this case, Arc defaults to a grid of 0.00328
  feet
• Roughly 4/100ths of an inch
• About a hairs width
• 0.2 feet is slightly smaller than 1/4

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Balancing Precision and Functionality

• Your extent match the scale in which you are
  working
• Leave a little wiggle room
• Working in New Jersey? Some of NY, PA, DE should
  fall into your box.
• Greenland fits? Your box is a little too big.

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Additional Functionality

• In your Feature Dataset, right click and see what
  pops up under New gt
• Topology
• Geometric Network
• Network Dataset
• Etc

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Geodatabase as a container

• Each of these special datasets uses the GDB to
  store data specific to its framework
• Topology stores associated attribute tables,
  rules, and error information
• Network stores network edge attributes, turn
  tables, and driving/routing directions

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Normalization

• A normalized database is one that has little
  redundancy within its tables
• Record ID or some other key links to a table with
  those values
• Instead of storing Modified Agricultural
  Wetlands numerous times as text, store it once
  as text and refer to it using a key (2140)

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Normalization

• Work in a normalized environment
• Analogs
• Non-normalized Excel Spreadsheet
• Normalized well made Access DB (lookups)
• When distributing for the public, flatten the
  database out to one table per layer
• Make it a shapefile

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Geodatabase Environment

• Important to work in a GDB whenever possible
• Assured extents, projections, etc
• Quality control
• Greater number of tools at your disposal
• Export to other format (.shp) for distribution

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Going Further
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Standard Query Language

• SQL is the standardized method of interacting
  with a database
• Even Access allows you to use SQL
• Insert (update into a DBMS)
• Update (existing records in DBMS)
• Delete (remove records from DBMS)
• Where (limits your results)

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Select Statements

• Most common SQL query you will encounter
• Select By Attributes has this as the foundation
• Nothing more than SELECT FROM gis_layer WHERE

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Joins

• In ArcGIS or Access, you join two (or more)
  tables together using a primary key.
• If the keys match, the secondary tables are
  tacked on to the first
• Again, geospatial is special, so GIS has another
  type of join

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Spatial Joins

• Relationship not determined by key, but by
  proximity or connectivity
• Contains/Within/Overlaps
• One feature falls entirely within another
• Touches/Intersects/Crosses
• One feature touches another
• Equals or Disjoint

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Transactions

• Geodatabase edits are either committed or rolled
  back
• Edits performed in a multi-user environment are
  integrity checked
• Atomic-level editing and revisioning
• Race condition

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Versioning

• GIS tracks edits made and maintains a journal of
  all changes to the database
• This record keeping allows for roll backs to any
  date on record
• Keep one set of records while reverting another
• Same database methodology as Wikipedia

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Data, data, everywhere

• In the Internet age, massive amounts of data are
  compiled, transmitted and analyzed every second
• Understanding the storage and retrieval methods
  are critical
• Difference between drinking and drowning