Lantini, Livia ORCID: https://orcid.org/0000-0002-0416-1077, Ardakanian, Atiyeh and Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937 (2026) From detection to interpretation: a decision-support framework for GPR-Based evidence in urban climate adaptation. In: EGU General Assembly 2026, 03-08 May 2026, Vienna, Austria. (In Press)

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Abstract

Urban climate adaptation strategies increasingly rely on trees as multifunctional assets for mitigating heat stress and improving urban liveability [1]. As tree planting and management accelerate in response to climate pressures, interactions between urban trees and subsurface infrastructure become increasingly relevant for planners, asset managers, and local authorities operating at neighbourhood to asset-management scales. Ground Penetrating Radar (GPR) is a well-established non-destructive technique for imaging shallow subsurface conditions and detecting tree root systems in urban environments [2], yet its contribution to adaptation-oriented decision contexts remains limited.

This limitation is not necessarily related to detection capability, as in some instances this depends on how GPR outputs are transformed and communicated beyond individual case studies. In climate adaptation settings, decisions concerning tree retention, monitoring, and intervention typically rely on surface-based indicators and qualitative risk categories [3], limiting the use of subsurface information for cross-site comparison and prioritisation within decision-support processes.

To address this gap, GPR data from multiple urban sites within the same local area were analysed to capture subsurface conditions around urban trees and their interaction with pavements and engineered layers. Rather than focusing on site-specific detection outcomes, the methodology introduced an intermediate analytical step in which GPR profiles were structured into repeatable spatial units and used to derive relative, non-prescriptive descriptors of subsurface conditions. These descriptors were explored through alternative indicator formulations, allowing different representations of subsurface variability and uncertainty to be examined while remaining grounded in the same geophysical observations. Within this framework, the resulting indicators were then synthesised at tree level to support decision-relevant interpretation, enabling subsurface conditions to be characterised in comparative terms and translated into high-level management tendencies, such as prioritisation for monitoring, further investigation, or intervention.

The study demonstrates that reframing GPR outputs within a stakeholder-oriented decision-support framework, rather than site-specific detection outcomes, enhances their relevance for climate adaptation and resilience planning. The proposed approach provides a transferable pathway for integrating geophysical evidence into evidence-based urban policy and asset management processes, by explicitly aligning geophysical interpretation with the scale and needs of real-world decision-making.

Item Type:	Conference or Workshop Item (Paper)
Identifier:	10.5194/egusphere-egu26-22982
Keywords:	Ground Penetrating Radar (GPR), Urban trees, Decision support framework, Urban resilience, Climate adaptation
Subjects:	Construction and engineering > Digital signal processing
Date Deposited:	21 May 2026
Dates:	Date Publication status 23 February 2026 Accepted 8 May 2026 Published Online
School, department or research centre:	School of Computing and Engineering The Faringdon Research Centre for Non-Destructive Testing and Remote Sensing
Keywords:	Ground Penetrating Radar (GPR), Urban trees, Decision support framework, Urban resilience, Climate adaptation
URI:	https://repository.uwl.ac.uk/id/eprint/14969

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