Correction of phenology-induced effects in forest canopy height models based on airborne laser scanning data. Insights from the deciduous mountain forests in Picos de Europa National Park in Spain

The comparison of ALS time-series is an important element of modern landscape conservation planning, especially to monitor forest ecosystems. Modellers must evaluate phenology when comparing ALS-based maps of ground elevation or canopy height between years. We showcase the scenario using a National Park in the NorthWest of Spain where bi-temporal ALS has been used to map deciduous mountain forests. We compare the 2010 and 2021 surveys using the same algorithms to interpret ALS data and to generate actionable products for managers, mainly digital terrain models and canopy height models. We implemented a hybrid approach to correct the discrepancies between the surveys, showing the problems arising from differences in phenology or the selection of the scaling. We quantified around 5% of the area suffered from >1 m difference in DTM and higher impact on CHM values. With the hybrid method, modellers can highly reduce the uncertainty when comparing two ALS surveys and derivable products. We provided a solid graphical and analytical diagnosis of these emerging problems in the context of multi-temporal ALS surveys testing the hybrid approach at two resolutions: 1 and 2 m, fine-grained scales. The assessment of phenology-induced effects is important under the context of nationwide ALS survey programmes currently in operation and on high-demand. Finally, we discuss and frame the hybrid-approach as a well-suited vector of canopy gap detection methods to support conservation planning and enforce species-specific habitat improvements.

Automated summary

Comparing ALS time-series is crucial for landscape conservation planning, especially in monitoring forest ecosystems. Modellers need to consider phenology when comparing ALS-based maps of ground elevation or canopy height between different years. This study demonstrates the comparison of two ALS surveys conducted in a National Park in Northwest Spain, using the same algorithms for data interpretation and generating digital terrain models and canopy height models. A hybrid approach was implemented to correct discrepancies caused by differences in phenology or scaling, reducing uncertainty and providing a solid evaluation of emerging problems in multi-temporal ALS surveys.