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Unformatted text preview: Spatial Analysis IV
Spatial Analysis IV
Optimization Optimization
Analysis of patterns to create improved
‘_________’ You’ll recall that GIS applications that focus
upon design are described as
uses
uses.
• As opposed to those that advance science which are
uses
termed as Methods that derive practical solutions to
that derive practical solutions to
everyday problems These methods are often implemented
as part of
as part of a
(SDSS)
(SDSS)
Enables GIS to provide instant feedback
GIS to provide instant feedback
upon ‘what if’ scenarios. Optimization: Area Suitability
Area Suitability
Determine which areas are best
suited to certain
by
taking into consideration many
relevant
.
• e.g. The best potential locations for the
Th
th
construction of a park Many different methods have been
different methods have been
developed to evaluate site suitability
• We’ll look at a few examples… Optimization: Area Suitability
Boolean Overlay Based Analysis
Operation is via polygon overlay, which is a
Mapping) process
Boolean overlay (or
The major steps:
major steps:
• Data Preprocessing – Collect datasets that representing
the individual requirements
• Suitability Ranking – The suitability of each dataset is
determined using
logic (0/1, or Yes/NO)
– e.g. only public owned land is suitable when looking at
ownership
ownership • Overlay – The
of the suitable areas from
each dataset will be the areas that
all the
pertinent requirements
pertinent requirements Optimization: Area Suitability
Simple example: Problem statement: select a site for a new park
statement: select site for new park
Criteria: on public land and current landuse type
being A
Data layers: ownership, landuses A Owner X
Owner Y
Public B Optimization: Area Suitability
Find suitable areas solely based on ownership
Owner X
Unsuitable
Owner Y
Public Suitable Find suitable areas solely based on landuse type Unsuitable A B Suitable Optimization: Area Suitability
Overlay The intersection of the suitable areas from each dataset will be
the areas that satisfy all the pertinent requirements
the areas that satisfy all the pertinent requirements The major drawback is that the boolean logic (i.e. a site is either
suitable or its not) produces abrupt
it
it
th
that don’t
reflect the
nature of many controlling factors Optimization: Area Suitability
Weighted Overlay
If the parameters under
consideration are
nature
nature… in • precipitation, temperature, elevation, distance
etc. …then the overlay of
will, generally speaking, be
insufficient
insufficient. objects • The overlay of continuous data requires
continuous datasets
– Raster; Spatial Analyst! Optimization: Area Suitability
Conversion
Spatial Analyst permits the
conversion of Discrete Data into
Continuous Data
This is useful if
you’re attempting
to
BOTH
data types
types Optimization: Area Suitability
Weighted Overlay (Cont.)
Indexing:
• The datasets that are evaluated may be quite
:
–
–
–
– Land Cost ($)
Proximity to services (miles)
Slope (degrees)
(degrees)
Etc. • Overlaying these factors in their
will not produce a meaningful result!
ill
• Thus an ordinal
applied to each of the datasets form
is – For example, on an Index of 110, 1 would be the
_______ suitable and 10 would be the __________! Optimization: Area Suitability
Weighted Overlay (Cont.)
Weighting:
• Some criteria are more important than others.
• This order of importance
order of importance
may be implemented by
your Indexed
datasets.
• e.g. 2 datasets upon a scale
of
of 13 are
are
by
by a %
of influence, then
to
create an output:
Top Left Cell
(2*0.75)+(3*0.25)=2.25 Optimization: Area Suitability
Weighted Overlay
(Cont.)
(Cont.)
Example:
• Identify potential
locations for a new
school Optimization: Routing Problems
Routing Problems
Ensures that the path of a vehicle is
the most
one possible!
• Especially important for service vehicles,
delivery trucks etc. whose routes differ from
day to day
day to day. Constrained to a given
• Discrete rather than continuous
rather than continuous . Optimization: Routing Problems
Routing Problems (Cont.)
Based upon the
• Distance or Time • The links within the network will have
links within the network will have
attributes that will allow the GIS to make an
intelligent decision:
– Length, Speed Limit, Traffic Lights, etc. Optimization: Routing Problems
Routing Problems (Cont.)
The traveling salesman problem
• Find the shortest tour from an
, through
a set of
, and back to the
.
• The potential number of tours will grow
with each additional destination
with each additional destination.
– Eventually, it will become untenable to evaluate all
the potential options. • Thus, GIS are designed to employ
GIS ______ – Algorithms designed to work
, and to come
to providing the best answer, without
guaranteeing that the best solution will be found. Optimization: Routing Problems
Routing service
technicians for
Schindler Elevator
Schindler Elevator
GIS
GIS is used to
partition the day’s
workload among
workload among
the
the crews and
trucks (color
coding) and to
optimize
optimize the route
to minimize time
and cost. ...
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 Spring '11
 roberts

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