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.
Highlights
The management of natural resources and complex ecosystems such as forests requires reliable information and data, in order to make well-founded and transparent decisions
It can be seen that terrestrial laser scanning (TLS) scans generally had lower detection rates, which became more pronounced with a lower threshold for dbh and an increasing sample plot radius
Using plot radii of 20 m, 15 m, and 10 m, and a lower dbh threshold of 10 cm, the respective average detection rates for personal laser scanning (PLS) were 98.76%, 98.95%, and 99.48%, while the respective values for TLS were 86.32%, 93.81%, and 98.35%e.nsU. 2s0i2n0g, 12a, lxoFwORerPEdEbRhRtEhVrIeEsWhold of 10 cm and plot radii of 20 m, 15 m, and 10 m, a re1s4poefc4t6ive detection rate of 100% was achieved on 90%, 70%, and 60% of the sample plots using PLS, while it was ondlyetaecchtiioenverdatoenof761%00,%35w%a,saancdhi6e%vedofotnhe90sa%m, 7p0le%p, laontds u60si%ngofTtLhSe. sample plots using PLS, while it was only achieved on 76%, 35%, and 6% of the sample plots using TLS
Summary
The management of natural resources and complex ecosystems such as forests requires reliable information and data, in order to make well-founded and transparent decisions. The lack of efficient inventory tools is an old and well-known challenge related to forest in-situ measurements [9] and, so, since the beginning of forest inventory, trials to improve efficiency have permanently enhanced techniques, instruments, and protocols [7]. These traditionally collected data are often used as reference values for the quality assessment of automatic sensor-based forest inventories
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