Abstract

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 study, an effective and simple method to map ITCs, and their stem diameter and aboveground biomass (AGB) is presented. ALS data were used to delineate ITCs and to extract ITCs’ height and crown diameter; then, using newly developed allometries, the ITCs’ diameter at breast height (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 (R 2 = .85 and .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 R 2 = .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.

Highlights

  • Forest structure influences both the carbon content of forests and its changes in time (Fischer et al, 2016)

  • The results showed that using only the Airborne laser scanning (ALS) information over an area and equations developed for a certain type of forest, it is possible to map accurately the diameter at breast height (DBH) and aboveground biomass (AGB) at individual tree crowns (ITCs) level, in other forests with similar characteristics

  • This is an important result because it demonstrates that using allometries developed using only local field data at a certain time, without the use of ALS data, we can predict ITC level attributes and forest structure over an extensive region covered with ALS data at any other time

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Summary

| INTRODUCTION

Forest structure influences both the carbon content of forests and its changes in time (Fischer et al, 2016). In a worldwide study, Jucker et al (2017) produced allometric equations by which tree diameter at breast height (DBH) and aboveground biomass (AGB) could be predicted from height and crown diameter measurements. These two tree attributes can be predicted with ALS data as they are the standard output of almost every individual tree crown (ITC) delineation method (Zhen, Quackenbush, & Zhang, 2016). Aboveground biomass for the field trees of the two datasets (Paneveggio: min. 1 kg, max. 4,086 kg, mean 406 kg; Pellizzano: min. 1 kg, max. 3,250 kg, mean 512 kg) was predicted using the models of Scrinzi, Galvagni, and Marzullo (2010) and field measured height, DBH, and species

| Methods
| MATERIALS AND METHODS
| Validation procedure
Findings
| DISCUSSION
Full Text
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