From portions of Chapter 8, 9, 10, &11
Real world is complex. GIS is used model reality.
The GIS models then enable us to ask questions of the data by performing spatial analysis functions.
Data layers must be prepared for optimal use in the spatial functions.
If data layers are large, the data can be split into smaller geographic areas called tiles.
Tiles allow faster processing and smaller file sizes.
GIS software then knows the tiles required for spatial functions or processing.
Data layer appears seamless to the user.
Classifications of Spatial Functions
cross 4 major categories:
Which functions are necessary for your
Company / agency?
Which functions are contained in
the GIS software package that your
Agency may purchase?
How are these spatial functions used?
Geometric Transformation:
Assign coordinates to data layer or
adjust one data layer to another
(Registration).
Rubber Sheeting:
Common type of registration.
Consists of master & slave layer
Master – more accurate layer
Slave- less accurate
Register (move) slave to master layer.
Link features (nodes) from slave to correct
position on master.
Process works like stretching a rubber sheet.
Rubber Sheeting Example
Works best if same number of nodes (or less)
exist in the slave layer as the master layer.
Edge Matching: Procedure to adjust position of features that extend across map sheet boundaries.
link nodes of features along edge of both maps
movement or adjusting only extends a certain distance the map edges (within red dotted line)
similar to rubber sheeting but movement is in restricted area
Line Coordinate Thinning:
Reduce the number of coordinate pairs to store
within the data layer.
Reasons to use:
Do not need detail
Reduce file size
Speed up display & spatial processing
Example: US state boundary map that was created
by combining each individual county polygon
boundaries
Integrated Analysis of Spatial & Attribute data:
Generalization: reduce the number of classifications by dissolving based on an attribute value.
Example reduces zoning use based on a field that contains the value of urban or rural.
NOACA example: combined individual zoning values (over 1000) for a 7 county area
to 15 generalized zoning types. Based on new field created- generalized zoning.
In MapInfo, generalization is done by selecting Table> Combine Objects using Column
Overlay:
Overlay one data layer on top of a second data layer to create a NEW data layer that is a subset of
the second data layer.
This function is also known as the “cookie cutter” method.
The bottom data layer can be split and the attribute data can be disaggregated based on the area.
In MapInfo, function is performed by selecting the feature(s), set target, split or disaggregate
Neighborhood Operations (Spatial SQL): within, contains, intersect
Specialized search function using topology to determine spatial
relationships between objects.
Within:
feature1 object’s centroid is inside
feature2 object
= centroid of feature
ie. P2 point (centroid) is within city polygon
Are P1 & P3 within the city polygon?
Line 90 (centroid) is within city polygon
What about line 101 & 80??
Contains:
feature1 object contains feature2 object
centroid
ie. city polygon contains P2
city polygon contains line 90’s centroid
Does the city polygon contain line 80 and
101? P1 or P3??
Intersect:
At least ONE node from feature 1 must be
inside or coincident or a line must cross
Feature 2
ie. all lines intersect the city polygon
Which parcels are within contaminated soil?
Answer is parcels
shaded orange
Spatial SQL in MapInfo
Spatial SQL
Which parcels are intersect contaminated soil?
Spatial SQL
The order of tables can change
the spatial SQL result.
If contaminated soil table listed
first, it is the base table & the
output of the SQL is one
contaminated soil record (polygon).
If parcel table listed first,
it is the base table & the
output of the SQL is many
parcel records (polygons)
Proximity Function: Buffering
Creates an area (polygon(s)) of a
specified width/ distance around one or
more spatial objects.
Points, lines, or polygons can be buffered
Buffering always results in a polygon(s)
Example is a 300 buffer from dirt roads (polylines)
Once buffer created, it can be saved to a new layer.
Then, using a spatial SQL, you can determine
if feature objects from other data layers are within
or intersect the buffer polygon.
Example: Buffering selected polygons at a constant distance in MapInfo & having the buffer result in
one buffer for each object
Buffer result
(3 buffer polygons)
Example: Buffering selected polygons at a constant distance in MapInfo & having the buffer result in
one buffer of all objects
Buffer result
(1 buffer polygon)