Purpose – The aim of this paper is to propose a methodology based on the use of a simple and accessible database, such as Corine Land Cover (CLC), for providing an in depth evaluation of environmental sustainability. This evaluation has been carried out through the analysis of factors such as landscape and habitat composition, the level of biodiversity, the degree of anthropisation and soil sealing and the arable land availability.
Design/methodology/approach – Starting from the analysis of some of the existing approaches for the evaluation of environmental sustainability, this paper presents a GIS approach, based on the use of the Corine Land Cover (CLC), and other sources of geographical data, aimed at producing several thematic Environmental Sustainability Indicators, and one synthetic index.
Findings – The proposed methodology was found to enable a satisfactory assessment of the environmental state, at territorial scale, starting from an easy accessible land use data set. The adopted approach is tailored by the CLC, but can easily be adapted to other land cover/land use classification systems. The applications presented in this paper have been applied to a relatively small area, and other tests should be performed across Europe for a better evaluation of the methodology. However, the results obtained from the Emilia-Romagna case study, showed a realistic and coherent picture of the environmental status in the area. Similarly to other successful sustainability indexes and/or indicators, the main advantage of the LUSI is the possibility of synthesizing, as a single value, the environmental sustainability of a given territory.
Originality/value – The application of the proposed methodology relies essentially on land use data and can be easily executed in batch mode, using simple models or script in a GIS environment. Contrary to other environmental sustainability indicators, where the land use data are only a sub-set of the data required, LUSI core data set is represented by the Corine Land Cover, or other equivalent geographical database.
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