Author/Authors :
Kamyab، H.R. نويسنده PhD Graduate, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Science & Natural Resource,Golestan, Iran. , , Salmanmahiny، A.R. نويسنده Associate Professor, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Science & Natural Resource, Golestan, Iran. , , Shahraini، M. نويسنده Assistant Professor, Collage of Engineering & Technological, Golestan University, Golestan, Iran. ,
Abstract :
In this paper, Landscape Allocation using Genetic Algorithm (LAGA) is introduced as aspatial multi-objective land use optimization software. The software helps in searching for optimal land use when multiple objectives suchassuitability, area, cohesion, and edge density indices are simultaneously involved. LAGA is flexible and easy to use 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 changes of different landscape elements to integrate simultaneously; this improves the speed and performance of the process. Another feature of this software is that exclusion areas (i.e. cities, roads and water bodies) can be locked or unlocked 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 to Gorgan Township as a case study to find optimum land use. The results suggest that LAGA can be a useful tool for land use planning.
