Concepts in geography,
GIS and geographical
science
Paul Longley and David Ashby
CASA, University College London
Geographical Information Systems and Science
Longley P A, Goodchild M F, Maguire D J, Rhind D W
(2001) John Wiley and Sons Ltd
© John Wiley & Sons Ltd
Crime mapping, GIS, GISc
Rational, effective, efficient resource
allocation, transparent rules
Monitoring and understanding observed
spatial distributions
Understanding of the difference that
place makes
Understanding processes
Spatial is special
Superficially different concepts, common
operations, techniques, methods
multidimensional
voluminous
different areal units
large n (display)
spatial analysis methods
complex, time-consuming to update…
Uncertainty
It is impossible to make a perfect
representation of the world, so
uncertainty about it is inevitable
Imperfect or uncertain reconciliation
[science, practice]
[concepts, application]
[analytical capability, social context]
U1: Conception
Spatial uncertainty
Natural geographic units?
Implications
Î statistical (numerical ‘confidence’ in
boundaries or labels?)
Î cartographic (symbolizing vague
boundaries and labels?)
Î cognitive (people subconsciously force
things into categories and boundaries to
satisfy a deep need to simplify the world?)
U2: Measurement/representation
Direct vs. indirect indicators
subjective (ambiguous) conception of
linkage with phenomenon of interest
measurement errors may be systematic
composite indicators e.g. deprivation
A01: Global Connections
E28: Counter Cultural Mix
F36: Metro Multiculture
U3: Analysis
spatial analysis: 'the process by which
we turn raw spatial data into useful
spatial information ‘
good science on uncertain foundations?
Scale and Analysis
No. of geographic
areas
48
24
12
6
3
Correlation
.2189
.2963
.5757
.7649
.9902
Usable, not natural, units
Relationships typically grow stronger
when based on larger geographic units
Inappropriate scale can make pattern
oversimplified, crude, illusory
Boundaries often leaky not crisp and
well-defined (esp. if phenomena are
inherently fuzzy, vague, ambiguous)
MAUP
variability in outcomes of different
aggregations
scale + aggregation = MAUP
MAUP can be investigated, but not
resolved, through simulation of large
numbers of alternative zoning schemes
can rarely correct source of distortion
can try to quantify way in which it
operates and likely magnitude of
impacts
Consolidation
Uncertainty is more than error
Richer representations create
uncertainty!
Need for understanding of data and
sensitivity analysis
"Here are four rules for living with uncertainty:
1. Understand what you don't know about your data. Read the metadata. Don't use
data that have no provenance and cannot be researched.
2. Investigate alternative outcomes using what you know about the error in your
data. Try to get a sense of how wrong your analysis might be.
3. Rely on multiple data sources if you can. Data sets produced in different ways by
different vendors can act as checks and balances on error.
4. Document your own uncertainty in the notes you publish with your analysis. "