Light detection and ranging (Lidar) is considered the most advanced technology to assess forest aboveground biomass (AGB). Currently, this technology is shared by different sensors ranging from ground [terrestrial laser scanning (TLS)], airborne [aerial laser scanning (ALS)] up to spaceborne ones, which entail different spatial scales. However, few studies tested the simultaneous and combined use of Lidar to estimate AGB, linking ground measurements up to satellite observations. To fill this gap, we performed a study in two Mediterranean forest types [i.e., mountainous beech (Fagus sylvatica) and black pine (Pinus nigra subsp. laricio)] with contrasting structures (i.e., broadleaf versus needleleaf forests), where field inventory, TLS, ALS, and the recent spaceborne Global Ecosystem Dynamics Investigation (GEDI) data were simultaneously acquired. A three-step procedure was followed, which involved (i) the validation of AGB estimates obtained from TLS against reference values obtained from conventional field inventory; (ii) the calibration and validation of AGB estimates derived from ALS against TLS measurements, and (iii) the calibration and validation of AGB estimates derived from GEDI against mapped AGB values obtained from ALS. Our main results indicated that TLS provides consistent measurements of AGB as compared with field measurements (R2 ranged between 0.6 and 0.9 and root-mean-square error ranged between 29% and 49%), indicating its potential as ground reference for airborne Lidar observations. The combined availability of ground, airborne, and spaceborne observations is suitable to link ground measurements up to satellite observations. Differences in Lidar performance between needleleaf and broadleaf forests are also considered and discussed. © 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).

Accurate estimates of tree biomass are strongly required for forest carbon budget estimates and to understand ecosystem dynamics for a sustainable management. Existing biomass equations for Mediterranean species are scarce, stand- and site-specific and therefore are not suitable for large scale application. In this study, biomass allometric equations were developed for stone pine (Pinus pinea L.), a Mediterranean tree species with relevant ecologic and economic interest. A dataset of 283 harvested trees was compiled with above- and belowground biomass from 16 sites in three countries (Italy, Spain, Portugal) representative of the species’ geographical Mediterranean distribution. A preliminary approach comparing the ordinary least squares method and the mixed model approach was performed in order to evaluate the most appropriate method for nested data in the absence of calibration data. To quantify the sources of error associated with applying biomass equations beyond the geographical range of the data used to develop them, a residual analysis was conducted. The allometric analysis showed low intra-specific variability in aboveground biomass relationships, which was relatively insensitive to the stand and site conditions. Significant differences were found for the crown components (needles and branches), which may be attributed to local geographical adaptation, site conditions and stand management. The root biomass was highly correlated with diameter at breast height irrespective of the geographical origin. Biased estimates were found when using site-specific equations outside the geographical range from where they were developed. The new biomass equations improved the accuracy of biomass estimates, particularly for the aboveground components of higher dimension trees and for the root component, being highly suitable for use in regional and national biomass forest calculations. It is, up to the present, the most complete database of harvested stone pine trees worldwide. © 2018

Tree biomass plays a key role in sustainable forest management and in determining forest carbon stocks. Accurate estimates based on species-specific empirical data are necessary for regional and national inventories and forest carbon management. In this study, we obtained allometric relationships for volume and aboveground biomass for stone pine (Pinus pinea) based on empirical data collected in four coastal stands in Italy. Root sampling was also performed. The results enabled generalized equations for volume and aboveground biomass to be developed. However, an analysis also showed several differences in biomass allocation in stone pine resulting from different stand characteristics, emphasizing the importance of stand-dependent factors for adjusting regional or national biomass calculations. Biomass expansion factors were also provided. This study provides tools to help forest managers in quantifying volume and biomass, thereby contributing to the accurate estimation of carbon sequestration and stocks in stone pine stands in Italy. © SISEF.