Influence of Scan Density on the Estimation of Single-Tree Attributes by Hand-Held Mobile Laser Scanning

Barbara Del Perugia,Francesca Giannetti,Davide Travaglini,Gherardo Chirici

doi:10.3390/f10030277

Abstract

Nowadays, forest inventories are frequently carried out using a combination of field measurements and remote sensing data, often acquired with light detection and ranging (LiDAR) sensors. Several studies have investigated how three-dimensional laser scanning point clouds from different platforms can be used to acquire information traditionally collected with forest instruments, such as hypsometers and callipers to detect single-tree attributes like tree height and diameter at the breast height. The present study has tested the performances of the ZEB1 instrument, a type of hand-held mobile laser scanner, for single-tree attributes estimation in pure Castanea sativa Mill. stands cultivated for fruit production in Central Italy. In particular, the influence of walking scan path density on single-tree attributes estimation (number of trees, tree position, diameter at breast height, tree height, and crown base height) was investigated to test the efficiency of field measures. The point clouds were acquired by walking along straight lines drawn with different spacing: 10 and 15 m apart. A single-tree scan approach, which included walking with the instrument around each tree, was used as reference data. In order to evaluate the efficiency of the survey, the influence of the walking scan path was discussed in relation to the accuracy of single-tree attributes estimation, as well as the time and cost needed for data acquisition, pre-processing, and analysis. Our results show that the 10 m scan path provided the best results, with an omission error of 6%; the assessment of single-tree attributes was successful, with values of the coefficient of determination and the relative root mean square error similar to other studies. The 10 m scan path has also proved to decrease the costs by about €14 for data pre-processing, and a saving of time for data acquisition and data analysis of about 37 min compared to the reference data.

Highlights

Collecting and updating different types of information on forest resources is an important task for forest ecosystems management and monitoring at different spatial scales
held mobile laser scanning (HMLS) systems have been recognized as promising tools to collect the 3D structure of a forest, with potential practical application in forest inventory and forest monitoring
With HMLS, accurate information on tree position and DBH can be obtained with lower survey times than those required by static terrestrial laser scanners and conventional field measurements

Summary

Introduction

Collecting and updating different types of information on forest resources is an important task for forest ecosystems management and monitoring at different spatial scales. In the last few decades, remote sensing technologies have played an important role in the optimization of forest measurements and estimation thanks to their advantage in collecting and updating information on forest resources. Forests 2019, 10, 277 between field measurements in sample plots (i.e., 200–530 m2 ), and remotely-sensed data to model forest variables (i.e., basal area, growing stock volume, dominant height), measured in field forest inventory plots [1,2]; and (ii) single-tree approach, which allows the derivation of information on single trees (i.e., diameter at breast height (DBH), height, volume) from high resolution remotely-sensed data [6]. Among the variety of remote sensing platforms, the laser scanner technology has an important role in forest inventories, as it allows the accurate three-dimensional (3D) reconstruction of the forest environment, capturing data useful for multiple scales in a fast and accurate way [4,5,7,8]. When ABA is used, ALS data are combined with field data (e.g., tree positioning, DBH, and tree height), which are usually acquired through traditional survey techniques, using callipers, hypsometers, compasses, and other measuring instruments

Objectives

Methods

Results

Discussion

Conclusion