Document Type: Research Paper
Gorgan university of agricultural sciences and natural resources
Associate Professor, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Science & Natural Resource
Assistant Professor, Engineering & Technological Collage, Golestan University
In this paper, Landscape Allocation using Genetic Algorithm (LAGA), a spatial multi-objective land use optimization software is introduced. The software helps in searching for optimal land use when multiple objectives such as suitability, area, cohesion and edge density indices are simultaneously involved. LAGA is a flexible and easy to use genetic algorithm-based software for optimizing the spatial configurations of land use. LAGA uses a steady-state genetic algorithm with one-point crossover and flip-mutation as genetic operators. A major novelty is that spatial changes are performed according to patch topology that allows to simultaneously integrate changes of different landscape elements that improves the speed and performance. Another feature of this software is that exclusion areas (i.e.: cities, roads and water bodies) can also be locked or un-locked in the optimization process. The program reads and writes maps in Arc ASCII raster format, which is supported by many GIS (e.g. ArcGIS/ArcView, GRASS, and IDRISI). LAGA has been applied in a case study to find optimum land use in the Gorgan Township. The results suggest that LAGA can be a useful tool to land use planning.