Trait-Based Framework for Monitoring Forest Land Use Intensity with Remote Sensing: A Conceptual Review

Kurzfassung

Forest Land Use Intensity (F-LUI) is a multidimensional and dynamic property of forest ecosystems that cannot be directly observed by Remote Sensing (RS). Existing approaches commonly quantify individual management activities, forest attributes or ecological responses and therefore capture only specific dimensions of forest-use intensity. This concept-driven narrative review proposes a trait-based conceptual framework in which forest traits constitute the common observational interface linking anthropogenic forest use, ecosystem responses and RS observations. Based on this principle forest traits and their spatial, temporal and functional expressions are interpreted within six complementary F-LUI indicator families: Trait, Genesis, Structure, Taxonomy, Function and Socio-economics. Rather than defining a universal F-LUI index, the framework provides a multidimensional, sensor-independent architecture for integrating RS with in situ observations, forest inventories, management information and environmental data. Emerging approaches including Artificial Intelligence (AI) and Foundation Models, multi-sensor data fusion, semantic technologies, Knowledge Graphs and Digital Twins may support its operationalisation. Key challenges remain in standardisation, uncertainty quantification, attribution of management effects and transferability across forest types, management regimes and spatial and temporal scales. The proposed framework provides an open and extensible basis for harmonised, reproducible and operational trait-based monitoring of F-LUI.