Why multitemporal ALS forest metrics remain challenging: Insights from operational airborne laser scanning

Abstract. The increasing availability of large-scale and repeated operational airborne laser scanning (ALS) facilitates its use for multitemporal analyses and monitoring. In the last decades, single ALS acquisitions have been demonstrated to hold great potential for obtaining forest structural information. However, the robustness and reliability of ALS to accurately detect changes in complex forest structural parameters such as plant area index (PAI), from repeated ALS acquisitions have rarely been assessed. In this study, we evaluated the reliability and limitations of multitemporal mapping and interpretation of this structural trait, using the well-established canopy height (CH) as a reference metric. We used operational ALS data from a heterogeneous temperate forest in northern Switzerland from three years, 2014, 2019 and 2020, recorded with different sensor and flight settings. Our results showed that CH was largely unaffected by the differences in data acquisition, reaffirming it to be a robust trait and demonstrating that our data is usable for multitemporal analyses. For PAI, we applied and compared three estimation methods with varying complexity. PAI results were highly sensitive to various acquisition parameters, particularly the pulse repetition frequency, leading to large deviations between acquisitions. All tested PAI estimation methods exhibited similar problems, complicating the distinction between actual structural change and external effects. This study underscores the potential of operational ALS for multitemporal forest structure analyses but highlights the need for standardisation of recording parameters as much as possible, as well as methodological harmonization and calibration to ensure comparability in multitemporal analyses, particularly for complex forest structural traits.