Application of handheld laser scanning technology for forest inventory purposes in the NE Turkey

Abstract

Forest inventory (FI) is the most challenging stage of forest management and planning process. Therefore, in situ surveys are often reinforced by modern remote sensing (RS) methods for collecting forestry-related data more efficiently. This study tests a stateof-the-art data collection method for practical use in the Turkish FI system for the first time. To this end, forest sampling plots were conventionally measured to collect dendrometric data from 437 trees in Artvin and Saçınka Forest Enterprises. Then, each plot was scanned using a handheld mobile laser scanning (HMLS) instrument. Finally, HMLS data were compared against ground measurements via basic FI measures. Based on statistical tests, no apparent differences were found between the two datasets at the plot level (P < 0.05). There were also robust correlations for diameter breast height at individual tree level (r > 0.97; P < 0.01). Residual analysis showed that both positive and negative errors had a homogeneous distribution, except for plot 8 where tree stems were in irregular shapes due to anthropogenic pressures. When all plots' data were aggregated, average values for the number of trees, basal area, and timber volume were estimated as 535 trees/ha-1 , 49.6 m 2 /ha-1 , and 499.7 m 3 /ha-1 , respectively. Furthermore, secondary measures such as the number of saplings and slope were successfully retrieved using HMLS method. The highest overestimation was in timber volume with less than 10% difference at the landscape level. The differences were attributed to poor data quality of conventional measurements, as well as marginal site conditions in some plots. We concluded that the HMLS method met the accuracy standards for most FI measures, except for stand height. Thus, the Turkish FI system could benefit from this novel technology, which in turn supports the implementation of sound forest management and planning.

Handheld Laser Scanning Detects Spatiotemporal Differences in the Development of Structural Traits among Species in Restoration Plantings

“…However, if data geolocation is not considered necessary, permanent plot establishment, like the one defined in Section 2.2 will still allow scan co-registration over time. Although this technology has been shown to provide rapid inventory of forest plots [29,57,58], its uptake by forest restoration ecologists for the monitoring of restoration plantings is still lagging. The present study demonstrates the potential of remote sensing technology, and particularly the ZEB1 system, to monitor the development of structural traits over time to guide adaptive management and report on restoration effectiveness.…”

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

“…Cabo et al [54] showed that the performance of ZEB-REVO-based dbh measurement (RMSE 0.9-1.1 cm) was equivalent to that of TLS; there was no apparent differences in tree detection nor significant bias in dbh estimation. Vatandaşlar and Zeybek [57] found that ZEB-REVO-collected 3D data yielded slightly higher dbh values than conventional ground measurements. However, its correlation coefficients ranged between 0.978 and 0.998.…”

Remarks on Geomatics Measurement Methods Focused on Forestry Inventory

“…Maybe in the future, these instruments will be suitable for measurements in forestry due to them being inexpensive and easy to use compared to equipment that is expensive, often heavy, and difficult to process. Lidar on an iPhone or tablet today uses the viDOC Pix4D system to create high-quality 3D models of smaller objects using the GNSS RTK module [43,44].…”

“…A better solution is a handheld scanner-a personal laser scanner (PLS). Nowadays, there is more suitable equipment, such as ZEB-REVO (GeoSlam, Nottingham, UK), BLK2go (Leica, Heerbrugg, Switzerland) (introduced in April 2020), or other devices [35,[41][42][43][44].…”