Geographical Information Systems (GIS) are used for several types of spatial planning
but so far they have not been used for optimal patch design. Optimal patch design is a
generic spatial problem in which the objective is to design spatially explicit landuse maps
when both the composition and configuration of patches are important criteria. There are
many applications in conservation, forestry management, watershed management and the
management of large military estates.
This thesis describes a new autonomous computer program, the genetic algorithm for
optimal patch design (GAPD). GAPD combines four components: a genetic search
algorithm, a parameterised region growing (PRG) program, raster GIS measurement
functions and multi-criteria decision-making methods. The key component is the PRG
which translates between the aspatial domain of the search algorithm and the spatial
domain of the GIS. GAPD generates landuse maps that optimise the configuration and
composition of patches to meet multiple objectives for a given set of input maps and
criteria.
The theories of landscape ecology are used to establish a framework for formulating
optimal patch design problems. The thesis describes the conceptual design of GAPD and
its implementation and test, first as a prototype for solving single patch problems and
then as a fully functional system for solving multi-objective multi-patch problems. The
feasibility of GAPD was established by investigations of issues concerning the
representation and measurement of configuration in raster data structures and by testing
the efficiency and effectiveness of GAPD with simple problems. GAPD was further
evaluated in five hypothetical problems designed to cover a range of different scenarios.
The results are promising and show that GAPD has potential as a decision support tool.
The final section recommends a number of topics for further research covering technical
developments of GAPD, the application of GAPD to real problems and investigations
of general issues of optimal patch design