A multi-objective optimization approach for sustainable ecological protected areas planning

Interest in sustainable ecological protected area planning is increasing because of land uses conflicts and environmental pressure caused by rapid urban expansion in China. The optimal planning becomes a multi-objective non-deterministic polynomial-time (NP)-hard problem when searching for a quantitative solution and subjecting to spatial constraint. In this paper, a swarm intelligence algorithm, artificial bee colony (ABC), is introduced to solve the problem together with techniques of remote sensing (RS) and geographic information science (GIS). The optimal objective is to maximize both the ecological suitability and spatial compactness of selected protection area. Significant improvements have been made to extend the ABC algorithm applicable for ecological protected area planning in discrete domain. Then, the procedure of integrating RS, GIS, and ABC to solve the multi-objective spatial optimization problem is formed. And the approach is successfully applied to sustainable ecological protected area planning in Sanya region (a coastal tourist city in China). Effective outcomes have been obtained, which provides strong and firm support for decisions making.