Instructors & Participants |
Travel & Accommodations
Geographically Weighted Regression and Associated Statistics
Santa Barbara, CA
July 26 - July 30, 2004
CSISS, University of California, Santa Barbara
A. Stewart Fotheringham (coordinator) and Martin Charlton
(both of the University of Newcastle, UK) and Chris Brunsdon
(University of Glamorgan)
The standard procedure in the vast majority of empirical analyses
of spatial data is either to calculate a global statistic
or to calibrate a global model. The term ‘global’
implies that all the spatial data are used to compute a single
statistic that is essentially an average of the conditions
that exist throughout the study area in which the data have
been measured. Such a procedure is flawed when the relationships
being measured vary over space. Geographically Weighted Regression
(GWR) is a statistical technique that allows variations in
relationships over space to be measured within a single modelling
framework. The output from GWR is a set of surfaces, each
surface depicting the spatial variation of a relationship.
The technique is based on regular regression modelling but
can be extended in many different ways. It provides a great
richness in the results obtained for any spatial data set
and should be useful across all disciplines in which spatial
data are used.
The workshop will be based around a textbook: Fotheringham
A. S., C. Brunsdon, and M. Charlton, Geographically
Weighted Regression: the analysis of spatially varying relationships
(Wiley 2002), written by the presenters of the workshop. Each participant
will be provided with a copy of the text for the course. The
authors have also written windows-based, user-friendly software
for GWR, which will also be supplied to participants.
The workshop will be a mix of lectures and practical, computer-based
sessions. Topics to be covered include local statistics and
local models, the basics of GWR with examples, statistical
inference and GWR, GWR and spatial autocorrelation, extensions
to the basic GWR framework and concept, applications of specialized
GWR software, and visualizing the output in ArcGIS.
Exercises will be provided to participants but they will
also be expected to bring their own spatial data set for experimentation
with GWR. Participants will present the results of their GWR
analyses on their own data sets at the conclusion of the course.
There are no registration fees associated with CSISS workshops.
Eligibility for attendance is determined through a competitive
application process. Successful applicants are encouraged
to seek funding through their own institutions (advisors,
department chairs, etc.) to cover their transportation, accomodations,
and meals for the full period of the workshop. Accommodation
at Manzanita Village on the UCSB campus is highly recommended.
It is conveniently within walking distance of the workshop
and very favorably priced for the Santa Barbara region. Also
see Travel & Accommodations
for more information.