The SLEUTH urban growth model as forecasting and decision-making tool
Date
2008-05-09
Authors
Watkiss, Brendon Miles
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
Accelerating urban growth places increasing pressure not only on the efficiency of infrastructure
and service provision, but also on the natural environment. City managers are delegated the task of
identifying problem areas that arise from this phenomenon and planning the strategies with which to
alleviate them. It is with this in mind that the research investigates the implementation of an urban
growth model, SLEUTH, as a support tool in the planning and decision making process. These
investigations are carried out on historical urban data for the region falling under the control of the
Cape Metropolitan Authority. The primary aim of the research was to simulate future urban
expansion of Cape Town based on past growth patterns by making use of cellular automata
methodology in the SLEUTH modeling platform.
The following objectives were explored, namely to: a) determine the impact of urbanization on the
study area, b) identify strategies for managing urban growth from literature, c) apply cellular
automata as a modeling tool and decision-making aid, d) formulate an urban growth policy based on
strategies from literature, and e) justify SLEUTH as the desired modeling framework from
literature. An extensive data base for the study area was acquired from the product of a joint
initiative between the private and public sector, called “Urban Monitoring”. The data base included:
a) five historical urban extent images (1977, 1988, 1993, 1996 and 1998); b) an official urban buffer
zone or ‘urban edge’, c) a Metropolitan Open Space System (MOSS) database, d) two road
networks, and d) a Digital Elevation Model (DEM). Each dataset was converted to raster format in
ArcEdit and finally .gif images were created of each data layer for compliance with SLEUTH
requirements. SLEUTH processed this historic data to calibrate the growth variables for best fit of
observed historic growth. An urban growth forecast was run based on the calibration parameters.
Findings suggest SLEUTH can be applied successfully and produce realistic projection of urban
expansion. A comparison between modelled and real urban area revealed 76% model accuracy. The
research then attempts to mimic urban growth policy in the modeling environment, with mixed
results.
Description
Thesis (MSc (Geography and Environmental Studies))--Stellenbosch University, 2008.
Keywords
SLEUTH, Urban Growth Model, Forecasting, Decision-making, Dissertations -- Geography and environmental studies, Theses -- Geography and environmental studies, Cities and towns -- South Africa -- Cape Town -- Growth -- Forecasting -- Mathematical models, City planning -- South Africa -- Cape Town