Collateral Landscapes: geospatial assessment of building materials’ local-scale impacts

The paper addresses the need for a procedure to complement mainstream global-scale metrics with a localised assessment of building material-generated local-scale impacts by first proposing a novel definition of Collateral Landscapes (CLs) to frame localised impacts within global manufacturing processes. Secondly, it proposes the Collateral Landscapes Impact Assessment Tool (CLIAT), which, at present, focuses on extractive activities and is primarily intended for planners and decision-makers to conduct preliminary assessments and prioritise and guide recovery operations. To establish measurable CLIAT parameters, eight Local Impact Categories were identified by grouping systematically reviewed local-scale indicators. Three of them (Visual Impact, Local Biodiversity Impact, and Local Water Footprint) were selected for the first CLIAT implementation and translated into three corresponding subindices. Each subindex relies on Potential Impact Indicators, which quantify the direct and indirect pressures exerted by an extractive activity, and Local Vulnerability Factors, which contextualise these pressures based on the territory’s specific susceptibility. Such parameters are computed through spatial data in a GIS environment. In addition to numerical values, the methodology’s output includes maps and multilayered diagrams. Furthermore, image atlases provide a human-eye perspective on the potentially exposed species and affected landscapes. The methodology is tested on six quarries of coloured marble located in Northern Italy, a territory characterised by high anthropogenic pressure. The application of the CLIAT tool enables the establishment of impact scores for each quarry and the categorisation of them into three impact profiles: high-impact (Quarry 5); an intermediate cluster (Q2, 3, 4, 6); and a lower-impact site (Q1). Such results show the tool’s ability to quickly prioritise recovery or impact-mitigation measures across a pool of extractive sites. To assess the methodology’s reliability, the Visual Impact subindex underwent a validation procedure showing a strong correlation between questionnaire scores and tool results, while the reliability of the whole tool’s scoring methodology was assessed through an uncertainty and sensitivity analysis that systematically perturbed raw data, weighting schemes, and aggregation rules, which provided evidence of CLIAT’s robustness.