Ontological Representation of Constraints for Geographical Reasoning

We describe a framework that supports multiple types of constraint-based reasoning tasks on a geo...graphic
domain, by exploiting a semantic representation of the domain itself and of its constraints. Our approach is
based on an abstract graph representation of a geographical area and of its relevant properties, for performing
the reasoning tasks.
As a test-bed, we consider the domain of Ecological Networks (ENs), which describe the structure of existing
real ecosystems and help planning their expansion, conservation and improvement by introducing constraints
on land use. While some previous work has been done about supporting the verification of compliance of fully
specified ENs, we aim at taking a significant step further, by addressing the automatic suggestion of suitable
aggregations of land patches into elements of the EN. This automated generation of EN elements is relevant
to support the human planner in the design of public policies for land use because it leverages automated tools
to carry out a possibly lengthy and error-prone task.