Abstract
This paper explores the potential application of a modified version of the Non-dominated Sorting Genetic Algorithm (NSGA)-II for land-use planning in Mediterranean islands that constitute a geographical entity with similar characteristics. Study area is the island of Naxos, which is a typical Mediterranean island. In order to monitor the land-use changes of the island for the period 1987-2010, object-based classification of three Landsat images has been carried out. The 1987 land-use classification defined the initial population for the Genetic Algorithm (GA) and the aim was to provide the optimal development scenario for Naxos island taking into consideration legislation, geological characteristics and environmental parameters. The GA was used in order to introduce land use changes while maximizing transformation suitability, compactness, economic return, and minimizing soil erosion. The output of the GA was compared to the actual development of the island. The outcomes confirmed the proposed algorithm’s convergence process, while the GA solutions eventually formed a Pareto Front and performed adequately across all objectives. The GA algorithm has proposed reduction of Irrigated farming land by 16%, increase of Dry farming land by 131%, and the maximum allowed by the defined constraints increase of Urban land (100%), mostly on the eastern and central part of Naxos. These changes significantly differ from the actual development of the island. Economic return after optimization increased by 18%, while soil erosion decreased from 1948 t/y to 1843 t/y.
Highlights
Resources have a prominent role in forming and implementing policies related to sustainable development [1]
This paper explores the potential application of a revised version of the Non-dominated Sorting Genetic Algorithm (NSGA)-II for land-use planning in the Mediterranean islands
The proposed NSGA-II algorithm was set to run for 15,000 generations in order to handle the described objectives, variables, and constraints
Summary
Resources have a prominent role in forming and implementing policies related to sustainable development [1]. Land is one of the most valuable resources, many RAPs are related to land-use allocation [1], a term used to describe “the process of allocating different activities or uses to particular units of an area within a region” [3]. Such problems are multiobjective and present substantial computational complexity because: 1) multiple, sometimes even conflicting-parameters should be analyzed; 2) a plethora of possible solution-combinations should be assessed; 3) complex interactions amongst the allocated land parcels should be investigated and 4) they are linked to many fields [3] [4]. Ever a unique solution optimizes these complex non-linear multiobjective problems sufficiently; these problems are characterized as non-deterministic polynomial problems and “require heuristic methods for executing optimization processes” [1]
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