| Summary: | Environmental conservation and land use planning usually need to automatically identify geographical sites satisfying particular criteria. The identification of sites becomes more complex when spatial configurations of the sites are part of the requirements since topological relations need to be considered in the analysis of
digital geographical data. The present research develops heuristic methods and mathematical approaches to automatically identify contiguous and compact sites to be afforested. In addition to spatial configurations, other criteria related to the identification of sites are part of this research: maximization of environmental performance, sediment fow reduction by means of afforestation of compact sites and budget restrictions in afforestation.
One of the results of the AFFOREST project (EU 5th Framework Programme for Research and Technological Development) was a Decision Support System (DSS) that is capable to identify high quality sites to be afforested (transformation of agricultural land into forest). Those sites maximize the Environmental Performance
(EP) in terms of three Environmental Impact Categories (EIC): carbon sequestration to be maximized, nitrate leaching to be minimized and ground water recharge to be maximized. To this end every EIC is represented by means of a map composed by a grid of cells (raster map), hence the objective is to identify a site made up of a
subset of cells maximizing the EP. The cells identified by means of the AFFORESTDSS form a fragmented site, nevertheless it is also useful to identify sites that are contiguous and compact. Compactness facilitates to articulate efficient policies to manage the afforested areas, in order t0 achieve not only environmental but
also economical benefits. This research develops new approaches to locate compact sites for maximizing EP.
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