Marull J. & Mallarach J.M. 2005. “A GIS methodology for assessing ecological connectivity: application to the Barcelona Metropolitan Area”. Landscape and Urban Planning.

Abstract

We developed a new methodology for the assessment of landscape and ecological connectivity at regional scale. This method has been entirely formalized using mathematical language, is supported by a topological analysis of a 1:25,000 scale land use map, and has been developed using Geographic Information Systems (GIS). The method allows the elaboration of a diagnose of the connectivity of terrestrial landscape ecosystems, on the basis of a previously defined set of ecological functional areas, and a computational cost-distance model which includes the barrier effect. This last component takes into consideration the type of barrier, the distance impact, and the adjacent land use and vegetation type. We defined two new compound indices: one for ecological connectivity and another for the barrier effect. The practical interest of our model is that it not only allows a cost-effective assessment of the current situation, but it has predictive capabilities, allowing the quantitative assessment and comparison of the impacts resulting from different planning scenarios or different infrastructure alternatives on the landscape and ecological connectivity.
The application of this model to the Barcelona Metropolitan Area (BMA), 16% of which is currently classified as urban, showed that 65% of the BMA area is currently occupied by functional ecological areas, and that 18% is covered by artificial barriers, although they have a direct negative impact on 56.5% of the area. The model also allowed the identification of vulnerable spots, including 1.7% of the BMA that has a critical importance for ecological connectivity, as well as the network of landscape linkages and ecological corridors that offer a high restoration potential. Further applications of this methodology assessing the impacts of regional and urban plans on ecological connectivity, suggest than it could easily be extrapolated to other regions.