Data from: How to map forest structure from aircraft, one tree at a time

Forest structure is strongly related to forest ecology and it is a key parameter to understand ecosystem processes and services. Airborne laser scanning (ALS) is becoming an important tool in environmental mapping. It is increasingly common to collect ALS data at high enough point density to recognize individual tree crowns (ITCs) allowing analyses to move beyond classical stand level approaches. In this paper an effective and simple method to map ITCs, and their stem diameter and above ground biomass is presented. ALS data were used to delineate ITCs and to extract ITCs' height and crown diameter; then using newly developed allometries the ITCs' DBH and AGB were predicted. Gini coefficient of DBHs was also predicted and mapped aggregating ITCs predictions. Two datasets from spruce dominated temperate forests were considered: one was used to develop the allometric models, while the second was used to validate the methodology. The proposed approach provides accurate predictions of individual DBH and AGB (R2 = 0.85 and 0.78, respectively) and of tree size distributions. The proposed method had a higher generalization ability compared to a standard area based method, in particular for the prediction of the Gini coefficient of DBHs. The delineation method used detected more than 50% of the trees with DBH >10 cm. The detection rate was particularly low for trees with DBH below 10 cm, but they represent a small amount of the total biomass. The Gini coefficient of the DBH distribution was predicted at plot level with R2 = 0.46. The approach described in this work, easy applicable in different forested areas, is an important development of the traditional area based remote sensing tools and can be applied for more detailed analysis of forest ecology and dynamics.Paneveggio datasetThese are the data of the Paneveggio dataset. These are the data of the field measured trees. It is a table with five columns: 1) "PlotID": ID of the field plot; 2) "Height_m": field measured tree height in meters; 3) "CD_m": field measured crown diameter in meters; 4) "DBH_cm": field measured DBH in centimeters; and 5) "AGB_kg": field estimated AGB in kilograms.paneveggio_field_data.csvPellizzano datasetThese are the data of the Pellizzano dataset. These are the data of the detected ITCs. It is a table with six columns: 1) "PlotID": ID of the field plot; 2) "Height_m": ALS-derived height of the detected ITC in meters; 3) "CD_m": ALS-derived crown diameter of the detected ITC in meters; 4) "H_F_m": field measured tree height in meters of the tree associated to that ITC; 5) "DBH_F_cm": field measured tree DBH in centimeters of the tree associated to that ITC; and 6) "AGB_F_kg": field estimated tree AGB in kilograms of the tree associated to that ITC.pellizzano_itc_data.cs