Multitemporal LiDAR data for forest carbon monitoring in Mediterranean Forest

Forests are widely recognized as essential ecosystems for sequestering carbon and to mitigate the increase of atmospheric carbon dioxide, though could lose, or reduce this function under future climatic change. To maintain or improve carbon mitigation and to assess species adaptation to climate change small-scale forest monitoring is crucial, especially in Mediterranean forests where warmer and drier seasons are expected. Airborne Laser Scanner (ALS) data are efficiently used for defined carbon mapping, but few studies have used multi-temporal lidar surveys to evaluate carbon sequestration in Mediterranean forests. This study focuses on the forested area of Monte Morello (Florence, Central Italy) which was surveyed by ALS in 2008 and 2015 with scan densities of 1.5 and 4.4 pulse/m2, respectively. Herein, we compare the multitemporal ALS data with field forest inventory plots to estimate growing stock volume (GSV) and carbon sequestration in Mediterranean mixed broadleaved and coniferous forests. Independently of laser sampling rate we estimate, using an area-based approach, the forest GSVs and carbon sequestrations for 2008 and 2015 using random forests and a multiple linear regression model (R2 = 0.9; RMSE% = 17%). Based on the multitemporal maps, we derived information related to (i) forest growth, (ii) forest species carbon sequestration, (iii) small-scale forest management. The entire study area increased sequestered carbon by 58%, mainly for coniferous mixed forests. Overall, our study describes a well-suited technique for multitemporal ALS analysis and highlighting the potential of the use of multitemporal ALS data to map forest resources for forest management activities.