Spatial Data Formats
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Transcript of Spatial Data Formats
CS 128/ES 228 - Lecture 4b 1
Spatial Data Formats
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Stages of development:
1. Conceptual model: select the features of reality to be modeled and decide what entities will represent them
2. Spatial data model: select a format that will represent the model entities
3. Spatial data structure: decide how to code the entities in the model’s data files
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2. Spatial data models
1. Raster
2. Vector
3. Object-oriented
Spatial data formats:
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Raster format
Features represented by cell contents
Spatial precision limited by cell size
Surfaces modeled as continuous values
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Vector format Spatial precision
limited by number format
Discrete features explicitly represented
Surfaces shown by contours rather than continuous values
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Object-oriented formats
Leave details for Dr. Levine!
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Thematic data (a.k.a. “attribute data”)
Quantitative or descriptive
May represent 1 or many themes
Tied to a spatial reference
Represented differently in raster vs. vector formats
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Scales of measurement
Data Unit Scale
Resort name text Nominal
Resort ranking value Ordinal
Winter temp. oC Interval
Size of ski area m2 Ratio
Heywood et. al. 1998 – Table 2.1
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Spatial modeling in raster format
Basic entity is the cell
Region represented by a tiling of cells
Cell size = resolution
Attribute data linked to individual cells
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Tesselation
A closed shape or polygon that repeats on all sides without any gaps or overlaps
Three regular polygons tesselate the plane:
Square Equilateral triangle Hexagon
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Tilings
In 1922 Escher visited the Alhambra palace and saw the wall tilings of the Moors. He was excited to find other artists who had been captivated by tilings, but also made this revealing comment: "What a pity their religion forbade them to make graven images."
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Escher’s “tesselations”
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Raster model – close up
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Advantages of raster format
many data sets available
different file formats readily inter-converted
fast computer lookupand display
easy to overlay multiple themes
able to represent multiple continuous surfaces
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Limitations of raster format
poor representation of discrete objects
constant resolution throughout region modeled
exact boundary location difficult
network analysis nearly impossible
difficult to change projection or coordinate system