Transcript CHAPTER 13 * Spatial Data Modeling

UNIT 3 – MODULE 3:
Raster & Vector
SPATIAL DATA MODELS
• A spatial data model
represents real-world
conditions within a GIS
by relating geographic
features.
• There are two primary
ways that data is
modeled: raster and
vector.
Credit: BiodiversityGIS
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RASTER
• A collection of cells
(pixels) that are organized
into rows & columns,
making up a grid.
• Information is contained
within each cell: location
and value.
• Satellite & aerial images
are already formatted as a
raster (e.g. thematic,
surface and basemaps).
Credit: CUNY
VECTOR
• Made up of points, lines and
polygons.
• This model uses Cartesian
coordinates (x,y) to store a
spatial entity’s shape.
• Points represent the simplest
spatial entity, and lines connect
points to form polygons
• More complex line shapes
mean more points are required
to represent it.
Credit: www.lyzidiamond.com
RASTER VS VECTOR
Credit: Indiana University
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MORE RASTER VS VECTOR
Credit: www.landsurveyorsunited.com
Credit: City University of New York
Credit: Penn State
SPATIAL DATA STRUCTURE:
RASTER
Credit: www.innovativegis.com
SPATIAL DATA STRUCTURE:
VECTOR
Credit: www.innovativegis.com
RASTER PROS & CONS
• Advantage
– Simplicity: data structures are simple, as are
implementation of overlays.
– Very efficient for image processing.
• Disadvantage
– Data structures are less compacted.
– Topology is difficult to represent.
– Feature boundaries & cell boundaries are not
merged.
VECTOR PROS & CONS
• Advantage
– Good at representing topology.
– Can be adapted easily to scale changes.
– Can be used easily with attribute data.
• Disadvantage
– Data structures are very complex.
– More difficult to overlay data.
– Difficulties with image processing.
– Requires constant updating.