Forest Inventory with Long Range and High-Speed Personal Laser Scanning (PLS) and Simultaneous Localization and Mapping (SLAM) Technology

Abstract

The use of new and modern sensors in forest inventory has become increasingly efficient. Nevertheless, the majority of forest inventory data are still collected manually, as part of field surveys. The reason for this is the sometimes time-consuming and incomplete data acquisition with static terrestrial laser scanning (TLS). The use of personal laser scanning (PLS) can reduce these disadvantages. In this study, we assess a new personal laser scanner and compare it with a TLS approach for the estimation of tree position and diameter in a wide range of forest types and structures. Traditionally collected forest inventory data are used as reference. A new density-based algorithm for position finding and diameter estimation is developed. In addition, several methods for diameter fitting are compared. For circular sample plots with a maximum radius of 20 m and lower diameter at breast height (dbh) threshold of 5 cm, tree mapping showed a detection of 96% for PLS and 78.5% for TLS. Using plot radii of 20 m, 15 m, and 10 m, as well as a lower dbh threshold of 10 cm, the respective detection rates for PLS were 98.76%, 98.95%, and 99.48%, while those for TLS were considerably lower (86.32%, 93.81%, and 98.35%, respectively), especially for larger sample plots. The root mean square error (RMSE) of the best dbh measurement was 2.32 cm (12.01%) for PLS and 2.55 cm (13.19%) for TLS. The highest precision of PLS and TLS, in terms of bias, were 0.21 cm (1.09%) and −0.74 cm (−3.83%), respectively. The data acquisition time for PLS took approximately 10.96 min per sample plot, 4.7 times faster than that for TLS. We conclude that the proposed PLS method is capable of efficient data capture and can detect the largest number of trees with a sufficient dbh accuracy.

Single Tree Segmentation and Diameter at Breast Height Estimation With Mobile LiDAR

“…Wu et al [34] detected the street trees with a voxel-based marked neighborhood searching method, and the completeness and correctness for tree detection were over 98%. Gollob et al [35] used a new personal laser scanner to estimate the tree position, the detection rates were over 96% in different plots. Eric et al [16] used the cross sections of the point clouds to segment the tree trunks and removed the noise points by a point density-based criterion, the completeness of stem detection reached 95.2% and 88.4% in different plots.…”

“…For the DBH estimation with mobile laser scanning data, Gollob et al [35] estimated the DBH with the circular cluster method and root mean square error (RMSE) of the best DBH measurement was 2.32 cm. Chen et al [36] estimated the DBH with the personal laser scanning (PLS) system, and the RMSE was 1.58 cm in an arbor forest sample plot.…”

A Case Study of the Application of Hand-Held Mobile Laser Scanning in the Planning of an Italian Forest (Alpe Di Catenaia, Tuscany)

“…The scanner is easy to handle in forestry surveys thanks to the compact design (100 mm × 200 mm × 240 mm for the handheld part) and the longevity of battery capacity (3.50 hours continued). Finally, it can be equipped with an optional Firefly 8si camera with 4k resolution to record different videos of the sampling area, useful for forest quality aspect inspection (ZEB HORIZON ™ -GeoSLAM, 2020; Gollob et al, 2020;Ryding et al, 2015;Liang et al, 2015). At the end of March 2021, the traditional surveys and laser scannings with GeoSLAM GEOSLAM ZEB HORIZON ™) were performed in the same 20 areas identified in order to compare the results obtained.…”

“…Italia). GEOSLAM ZEB HORIZON ™ laser scanner is a hand-held mobile laser scanner containing SLAM technology that can be solved the problem of no GNSS 1 signal or poor signal under the forest canopy making it more practical for forest investigations (Gollob et al, 2020). 15 forest sample plots are selected to reflect different stand conditions in Mediterranean forests taking into count the development stage and density of the sub-canopy vegetation, as well as the species composition in the forest stands.…”

Indoor Mapping of a Complex Cultural Heritage Scene Using TLS and HMLS Laser Scanning

“…Over the last years, many comparative studies between TLS and HMLS point clouds have been conducted, for forest inventory applications (Gollob et al, 2020;Shao et al, 2020;Cabo et al, 2018;Bauwens et al, 2016;Ryding et al, 2015) and indoor mapping (Russhakim et al, 2019;Sirmacek et al, 2016). The comparison was made in terms of specific elements size, such as: tree height, diameter at breast height, segments lengths etc.…”