Download Geog 458: Map Sources and Errors

Geog 458:
Map Sources and Errors
January 9 2006
Representing Geography
Outlines
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Importance of geographic representation
How do human conceptualize surroundings?
How is human conceputalization coded in
computer databases?
Reading Spatial Data Organization in FGDC
Metadata Content Standard
1. Importance of geographic
information
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What is geographic representation?
Why is geographic representation important?
What is representation?
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Viewing the real world (or surroundings, reality)
Forcing the real world into a manageable concept
Human conceptualization of the world
Putting the real world into a computer
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How would you represent the followings in a computer?
Does the same data model fit all?
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Vegetation, soil, traffic volume, land use, tornado, clouds…
Data modeling (building data model)
Why is representation important?
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Forms the basis of metadata organization
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Many operations depend on data model
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Identification, spatial data organization, entity and attribute
Routing
Spatial interpolation
Forms the basis for understanding data structure and
data format used in a GIS
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Vector, point, line, node, area, topology
Raster, pixel, tessellation, sampling, planar enforcement
2. How humans conceptualize
surroundings?
1)
2)
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4)
Object vs. field
Dimensionality
Space, time and attribute
Scale
Do-It-Yourself
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Exploring different ways to represent spatial concepts
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Group A: how land parcel is represented in a GIS
Group B: how elevation is represented in a GIS
Group C: how tornado is represented in a GIS
Group D: how traffic volume is represented in a GIS
Each group should discuss the representation of each
theme in terms of (1) object vs. field (2) dimensionality
(3) how space, time and attribute are organized (4)
appropriate scale of space and time
Land parcel & Elevation
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We can observe discrete boundary of land
parcel but we can’t observe that of elevation
Land parcel forms polygon in terms of
geometry, but elevation does not conform to
well-defined geometry
Identity change over time is gradual in the
corresponding time scale  temporal element is
largely ignored, the relation between space and
attribute determines representation
Traffic volume & Tornado
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Movement of things with some pronounced
properties across geographic path
Can have all dimensionalities by leaving out less
important details
Temporal element is important
Finer temporal scale is required to describe the
subject properly  attribute is largely ignored,
the relation between space and time determines
representation
(1) Object vs. Field
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Discrete object
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Continuous field
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Identifiable boundaries  easier for manipulation like a
tabletop object conceived easily by direct human experience
Building, population, county boundary
Variation in a given spatial scale  requires spatial sampling
scheme (tessellation)
Temperature, population density, tax rate per county
Any limitations?
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Soil boundary, mental map of localities
Planar enforcement (i.e. polygon doesn’t overlap)
(2) Dimensionality
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By identifying dimensionality of object, you can place them in
Euclidean geometry
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Zero-dimension (point)
One-dimension (line)
Two-dimension (area)
Three-dimension (volume)
Any limitations?
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Even though most of data format (e.g. shapefile) available in GIS is only
allowed to have one of possible dimensions, reality is that some object
(e.g. lake) can have multiple dimensions depending on scale and
applications
Multiple representation (i.e. representing geographic entities across
multiple scales)
(3) Space, Time, and Attribute
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Geographic information has three components:
space, time and attribute
Data model can be understood through
measurement framework
Measurement framework: all of three
components are not fully measured, but rather
one of them is measured, controlled, and fixed
respectively (Sinton 1978)
(4) Scale
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Scale determines the way in which phenomenon is described
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Scale influences the way humans cognize surroundings
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Astronomy, geography, human biology
Universe time, geological time, geographic time
Our experience of surroundings is quite different depending on scale: e.g.
tabletop object (direct experience) versus cities
Scale  human conceptualization  data model  GIS implementation
Representing reality in some geometry (e.g. city as point) is a
reasonable approximation only at a particular scale
Scale determines accuracy and thus fitness of use of data to
particular purposes
Is GIS a container of digital maps?
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Partially yes (mainly because we are used to it)
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But pitfall of limiting your thought on geographic representation
to this doesn’t help us explore other potential geographic
representations
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DRG, DLG, DOQQ, Satellite image
The way of describing geographic information is not necessarily limited
to point, line, polygon, and surface, but rather relational or propositional
(e.g. I live in Seattle, you should turn left at the intersection)  first-order
logic (deductive database)
City does not have geometry and attributes, but also has different
functions (as adminstrative unit, as economic unit, as ecological unit) 
object-oriented database
Geography is not the same as geometry indeed!
3. How is human conceptualization
coded in computer databases?
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Putting discrete objects into a computer (vector GIS)
1)
2)
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Putting continuous fields into a computer (raster GIS)
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Spatial primitives
Topology
Generalization algorithm
Gridded raster
TIN
Georelational model as a special case of vector
topological model (ArcInfo coverage)
(1) Spatial primitives
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Three spatial primitives are used to represent
discrete objects
Point: as a point (x, y)
 Line: as a set of vertices
 Polygon: as a set of vertices that form to close
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(2) Topology
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What is topology?
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Why is topology important?
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Non-metric properties of geographic objects that remain
constant when the geographic space of objects is distorted
(e.g. projection change, transformation)
From data perspectives, it validates geometric accuracy (e.g.
network connectivity, line intersection, overlap, duplicate lines)
 link to logical consistency in data quality
From analytics perspectives, it optimizes queries by storing
spatial relation information in a table
How are they stored in a table? (see next slide)
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Connectivity
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Containment
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Arc 2 connects from
11 to 12
Polygon C is
surrounded by arc 2,4,
9, and 6
Contiguity
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Polygon B/C in the
left/right of arc 6
(3) Generalization
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Douglas-Poiker algorithm
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Process for simplifying line by reducing the number of
vertices in its representation
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How it works?
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E.g. Cape Cod in 1:1,000,000 map  Cape Cod in 1:25K
For illustration, see Figure 3.17 at Longley et al (p. 82)
What does it achieve?
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It attempts to preserve pronounced changes in angle within a given
tolerance
It reduces the size of data, and speeds up the process for display and
further analysis
(4) Raster grid
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Variation in values are stored in each cell
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Many geographic data (e.g. satellite image, air photo) are
derived from this data structure
It takes up large space; it leads to development of many
different raster compression methods
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(5) TIN
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What is TIN?
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Triangulated Irregular Network
Represents a surface as contiguous non-overlapping
triangular plane where three points have different z-values
(See Figure 8.12 in Longley et al 2005 (p. 189)
Why is TIN popular?
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Allows for varying density in sampling points
Less storage because it stores only critical points (cf. raster
grid)
Georelational model
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Geometry of spatial object is stored in a file and
attribute is stored in a table
File is linked to attribute through a common
identifier
Separation between spatial and non-spatial
attribute
See Figure 8.10 (e.g. Arc/Info coverage)
4. Reading Spatial Data Organization
in CSDGM
Do-It-Yourself
Air Quality – Lake Monitoring Sites
Metadata from Geospatial One-Stop
What is Indirect Spatial Reference? Take any example.
What is Direct Spatial Reference Method?
What is STDS point and vector type?
What is “Entity Point”?
What is the difference between point and node?
Resources
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http://fgdc.gov/metadata/csdgm/03.html
http://mcmcweb.er.usgs.gov/sdts/SDTS_standard_nov97/part1b10.h
tml