Using GEDI lidar data and airborne laser scanning to assess height growth dynamics in fast-growing species:a showcase in Spain

摘要

Background:The NASA’s Global Ecosystem Dynamics Investigation(GEDI)satellite mission aims at scanning forest ecosystems on a multi-temporal short-rotation basis.The GEDI data can validate and update statistics from nationwide airborne laser scanning(ALS).We present a case in the Northwest of Spain using GEDI statistics and nationwide ALS surveys to estimate forest dynamics in three fast-growing forest ecosystems comprising 211,346 ha.The objectives were:i)to analyze the potential of GEDI to detect disturbances,ii)to investigate uncertainty source regarding non-positive height increments from the 2015–2017 ALS data to the 2019 GEDI laser shots and iii)to estimate height growth using polygons from the Forest Map of Spain(FMS).A set of 258 National Forest Inventory plots were used to validate the observed height dynamics.Results:The spatio-temporal assessment from ALS surveying to GEDI scanning allowed the large-scale detection of harvests.The mean annual height growths were 0.79(SD=0.63),0.60(SD=0.42)and 0.94(SD=0.75)m for Pinus pinaster,Pinus radiata and Eucalyptus spp.,respectively.The median annual values from the ALS-GEDI positive increments were close to NFI-based growth values computed for Pinus pinaster and Pinus radiata,respectively.The effect of edge border,spatial co-registration of GEDI shots and the influence of forest cover in the observed dynamics were important factors to considering when processing ALS data and GEDI shots.Discussion:The use of GEDI laser data provides valuable insights for forest industry operations especially when accounting for fast changes.However,errors derived from positioning,ground finder and canopy structure can introduce uncertainty to understand the detected growth patterns as documented in this study.The analysis of forest growth using ALS and GEDI would benefit from the generalization of common rules and data processing schemes as the GEDI mission is increasingly being utilized in the forest remote sensing community.