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Second video - principles of
automated zone design
methods
Principles
• Need to achieve a set of zones that meet specific
design criteria (e.g. not too big, not too small,
sensible shapes, similar populations)
• Always a trade-off between competing objectives
• Natural human inclination to draw lines on a map
into order to subdivide a larger area
• Alternative approach to put together many small
areas as if completing a jigsaw - most
computational approaches are closer to this
Automated Zoning Procedure
(Openshaw, 1977)
• Initial random aggregation of building blocks into
groups (here called “tracts”)
• Compute statistics (shape, size, etc.)
• Swap building blocks between tracts
• If solution improved, keep the swap
• Try swapping another building block
• Try another starting aggregation
• Simulated annealing, tabu searching, etc.
refinements to avoid local suboptima
Automated zone design
• Iterative re-combination of input building blocks to
create output tracts which optimise pre-specified
design criteria
Building
blocks Tracts
“Best”
solution
Possible Solutions
Building blocks
• Building block zones may come from many different
sources (purpose-built or pre-existing)
• Need to be small relative to the output zones
• Most will be generated using a geographical
information system (GIS)
• Statistical information to evaluate the design
criteria needed for each building block
• May require use of confidential data in order to
design zones for which data can be published
Address polygon generation
Use GIS to generate
Thiessen (Voroni)
polygons around
each address
location
Postcode polygon creation
Dissolve boundaries
between address
polygons having
common postcodes
Building block considerations
• Big impact on zone design solution
• Output zone boundaries drawn from building block
boundaries: cannot be smoother, more realistic or
better-aligned to real-world features
• As number of building blocks increases: more
permutations, longer computation times and
(probably) more good solutions
Zone design criteria
• Hard constraints – must be met
• e.g. more than 100 people and 40 households
• e.g. must not cross local authority boundary
• Soft constraints – cannot be met exactly, but should
be treated as objectives
• e.g. zones should contain 125 households
• e.g. zone should be as compact in shape as possible
Design criteria - measurement
• Suitable statistical measures that can be repeatedly
recalculated for each of the design criteria
• e.g. disallow any zone with a population less than
threshold value
• e.g. solve for all building blocks within an external
boundary
• e.g. minimize sum of {squared differences from target
population size}
• e.g. minimize sum of {perimeter squared/area}
Automated OA design
Initial Random
Aggregation of
Building Blocks
Iterative Recombination
Design Constraints
(Contiguity, Thresholds,
Shape, Size, Homogeneity)
Output
Areas
Initial random
aggregation of
building blocks
into potential
tracts
How does it work?
Choose one
building block at
random as
candidate for
swapping into a
different tract
How does it work?
Make the swap
and evaluate the
impact on the
overall solution
How does it work?
If swap does not
result in an
improvement, go
back to the
previous
configuration
How does it work?
Choose another
building block at
random as
candidate for
swapping into
another tract
How does it work?
If the swap results
in an overall
improvement,
keep it as part of
the solution and
examine a new
potential swap…
How does it work?
Summary
• All data for evaluation need to be available at the
building block level
• Automated zone design based on iterative
recombination of building blocks, recalculating
design statistics at each iteration
• Design statistics indicate progress towards an
overall solution, less attractive permutations being
dropped in favour of more attractive ones
Reference
• Openshaw, S. (1977) A geographical solution to
scale and aggregation problems in region-building,
partitioning and spatial modelling Transactions of
the Institute of British Geographers NS 2, 459-72
Principles of automated_zone_design_methods

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Principles of automated_zone_design_methods

  • 1. Second video - principles of automated zone design methods
  • 2. Principles • Need to achieve a set of zones that meet specific design criteria (e.g. not too big, not too small, sensible shapes, similar populations) • Always a trade-off between competing objectives • Natural human inclination to draw lines on a map into order to subdivide a larger area • Alternative approach to put together many small areas as if completing a jigsaw - most computational approaches are closer to this
  • 3. Automated Zoning Procedure (Openshaw, 1977) • Initial random aggregation of building blocks into groups (here called “tracts”) • Compute statistics (shape, size, etc.) • Swap building blocks between tracts • If solution improved, keep the swap • Try swapping another building block • Try another starting aggregation • Simulated annealing, tabu searching, etc. refinements to avoid local suboptima
  • 4. Automated zone design • Iterative re-combination of input building blocks to create output tracts which optimise pre-specified design criteria Building blocks Tracts “Best” solution Possible Solutions
  • 5. Building blocks • Building block zones may come from many different sources (purpose-built or pre-existing) • Need to be small relative to the output zones • Most will be generated using a geographical information system (GIS) • Statistical information to evaluate the design criteria needed for each building block • May require use of confidential data in order to design zones for which data can be published
  • 6. Address polygon generation Use GIS to generate Thiessen (Voroni) polygons around each address location
  • 7. Postcode polygon creation Dissolve boundaries between address polygons having common postcodes
  • 8. Building block considerations • Big impact on zone design solution • Output zone boundaries drawn from building block boundaries: cannot be smoother, more realistic or better-aligned to real-world features • As number of building blocks increases: more permutations, longer computation times and (probably) more good solutions
  • 9. Zone design criteria • Hard constraints – must be met • e.g. more than 100 people and 40 households • e.g. must not cross local authority boundary • Soft constraints – cannot be met exactly, but should be treated as objectives • e.g. zones should contain 125 households • e.g. zone should be as compact in shape as possible
  • 10. Design criteria - measurement • Suitable statistical measures that can be repeatedly recalculated for each of the design criteria • e.g. disallow any zone with a population less than threshold value • e.g. solve for all building blocks within an external boundary • e.g. minimize sum of {squared differences from target population size} • e.g. minimize sum of {perimeter squared/area}
  • 11. Automated OA design Initial Random Aggregation of Building Blocks Iterative Recombination Design Constraints (Contiguity, Thresholds, Shape, Size, Homogeneity) Output Areas
  • 12. Initial random aggregation of building blocks into potential tracts How does it work?
  • 13. Choose one building block at random as candidate for swapping into a different tract How does it work?
  • 14. Make the swap and evaluate the impact on the overall solution How does it work?
  • 15. If swap does not result in an improvement, go back to the previous configuration How does it work?
  • 16. Choose another building block at random as candidate for swapping into another tract How does it work?
  • 17. If the swap results in an overall improvement, keep it as part of the solution and examine a new potential swap… How does it work?
  • 18. Summary • All data for evaluation need to be available at the building block level • Automated zone design based on iterative recombination of building blocks, recalculating design statistics at each iteration • Design statistics indicate progress towards an overall solution, less attractive permutations being dropped in favour of more attractive ones
  • 19. Reference • Openshaw, S. (1977) A geographical solution to scale and aggregation problems in region-building, partitioning and spatial modelling Transactions of the Institute of British Geographers NS 2, 459-72