Conventional Field Measurements Research Articles

Mengekstrak Parameter Fungsi Skala Kanopi di Kawasan Konservasi Lembah Danum, Sabah Menggunakan Data Pesawat Udara LiDAR

Forest restoration is an effort to restore the growth and balance degraded forest ecosystems, through various approaches such as reforestation, land restoration, endangered species conservation, and forest fire prevention. Conventional field data collection challenges, such as limited spatial coverage, tall tree measurement difficulties, and human observation errors, hinder canopy-scale functional traits monitoring and extraction across forest treatments. The study addresses the importance of forest restoration and the challenges associated with conventional field measurements in extracting canopy scale functional traits by utilizing Airborne light detection and ranging (LiDAR) technology for more accurate information involving the old growth, natural regeneration, and active restored forests in Danum Valley Conservation Area and INFAPRO Sabah. The study utilized diverse processing algorithms, allometric equations, and correlative modeling methods. At the grid level, various LiDAR functional traits were calculated, leaf area index, gap fraction, and canopy density, alongside assessment of multiple correlative modeling strategies. Linear regression and analysis of variance analyzed relationships between LiDAR-derived and field-derived canopy scale functional traits between different forest treatments. The results showed high R-squared values ranging from 0.73 to 0.91, Anova F-statistics and probability values (p) showed that there is a strong relationship between the field data and predicted LiDAR values for three-canopy scale functional traits in different forest treatment types. These results indicate that LiDAR technology is effective in predicting canopy scale functional traits and has the potential to provide accurate and detailed information on forest restoration areas for future conservation and management efforts.

An Accuracy Assessment of Field and Airborne Laser Scanning–Derived Individual Tree Inventories using Felled Tree Measurements and Log Scaling Data in a Mixed Conifer Forest

Abstract On-the-ground sample-based forest inventory methods have been the standard practice for more than a century, however, remote sensing technologies such as airborne laser scanning (ALS) are providing wall-to-wall inventories based on individual tree measurements. In this study, we assess the accuracy of individual tree height, diameter, and volume derived from field-cruising measurements and three ALS data-derived methods in a 1.1 ha stand using direct measurements acquired on felled trees and log-scale volume measurements. Results show that although height derived from indirect conventional field measurements and ALS were statistically equivalent to felled tree height measurements, ALS measured heights had lower root mean square error (RMSE) and bias. Individual tree diameters modeled using a height-to-diameter-at-breast-height model derived from local forest inventory data and the software ForestView had moderate RMSE (8.3–8.5 cm) and bias (-3.0 – -0.3 cm). The ALS-based methods underdetected trees but accounted for 78%–91% of the field reference harvested merchantable volume and 71%–99% of the merchantable volume scaled at the mill. The results also illustrate challenges of using mill-scaled volume estimates as validation data and highlight the need for more research in this area. Overall, the results provide key insights to forest managers on accuracies associated with conventional field-derived and ALS-derived individual tree inventories. Study Implications: Forest inventory data provide critical information for operational decisions and forest product supply chain planning. Traditionally, forest inventories have used field sampling of stand conditions, which is time-intensive and cost-prohibitive to conduct at large spatial scales. Remote sensing technologies such as airborne laser scanning (ALS) provide wall-to-wall inventories based on individual tree measurements. This study advances our understanding of the accuracy of conventional field-derived and ALS-derived individual tree inventories by evaluating these inventories with felled tree and log scaling data. The results provide key insights to forest managers on errors associated with conventional field and ALS-derived individual tree measurements.

Light Scattering Method for Aerosol Sizing Based on Machine Learning.

Optical scattering has been widely used for aerosol sizing due to its noninvasive and real-time measurement. However, it is crucial to retrieve the particle size distribution (PSD) of aerosols without prior knowledge of the refractive index. Now, it has been a great challenge to measure the refractive index in situ. In this study, a novel PSD sensing method utilizing the light scattering angular spectrum (LSAS) and machine learning techniques is proposed to address this challenge. The complex nonlinear relationship between LSAS and PSD can be constructed while accounting for the refractive index of aerosols. A miniaturized prototype sensor is designed and tested on different sizes of aerosol samples. The experiment results showed that the maximum Kullback-Leibler divergence (DKL) of PSD is 0.07, which indicates that the sensing method can provide the ability for highly accurate aerosol PSD measurement without requiring prior knowledge of the refractive index. The compacted prototype sensor shows great potential for aerosol analysis in conventional field measurements outside the laboratory.

Calculating herbage utilization and intake by dairy cows under subtropical conditions using conventional field measurement techniques or the HerbValo method.

This study aimed to evaluate the HerbValo method in comparison to conventional field measurement techniques as a tool for estimating the herbage utilization and dry matter (DM) intake by grazing dairy cows under subtropical conditions. It was carried out during 18 months in a commercial farm of Southern Brazil. The herbage utilization was estimated monthly in two to four randomly selected paddocks (total n = 40) using the rising-plate meter or the double-sampling technique. In parallel, the herbage utilization was estimated by the HerbValo method, which is based on simple descriptions of the herd, supplements, pasture and grazing management. Values of herbage utilization estimated by field techniques were linearly (P < 0.01) related to those estimated by HerbValo, with no effect of pasture type (tropical vs. temperate) on the origin or on the slope of the regression (slope = 0.97; origin = -0.1; R2 = 0.81; rsd = 0.17 t DM/ha). At cow × day level, values of herbage intake estimated by field techniques were also linearly related to those estimated by HerbValo (P < 0.01; R2 = 0.82; rsd = 1.30 kg DM/cow/day). A negative linear relationship (P < 0.01) between herbage and supplement intake was obtained for both field (slope = -1.06; R2 = 0.72; rsd = 1.64) and HerbValo (slope = -0.92; R2 = 0.82; rsd = 1.08) approaches. Herbage utilization and intake by a dairy herd in a subtropical grazing-based system can be reliably estimated by the HerbValo method with the advantage of not requiring direct field pasture measurements.

Remote sensing-based techniques for water management in small-scale farms in arid climate

Abstract Accurate estimation of actual evapotranspiration () is a critical component in improving agricultural water management and water use efficiency. Remote sensing (RS) techniques provide a promising inexpensive tool for reliable crop water consumption estimations compared to conventional field measurements. Having agricultural land fragmentation and mixed cropping systems in the Nile River Delta, traditional methods of estimating are seemingly challenging. The present study aims to improve agricultural water management at the meso scale using RS-based techniques. Four RS-based methods were employed to estimate in mixed cropping farms at the Nile River Delta. The adopted methods include: (i) the Surface Energy Balance Algorithm for Land (SEBAL), (ii) the Simplified Surface Energy Balance algorithm (SSEB), (iii) Earth Engine Evapotranspiration Flux (EEFLUX) product, and (iv) the crop coefficient () method. The analysis of variance (ANOVA) test showed a significant difference between the employed RS-based techniques. During the winter season 2018–2019, the estimated varied from 331.33 mm/season to 389.34 mm/season, with an average of 358.76 mm/season. The irrigation efficiency was estimated to be about 55–63%, with an average of 59.55%. The study developed an algorithm to schedule the operation hours of irrigation pumps in the study area based on actual water requirements and pump capacity. The study highlights the relevance of RS methods and the importance of the equitable distribution of water in small farms to enhance water management.

Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest

Tree height is one of the most important tree attributes in forest inventory. However, using conventional field methods to measure tree height is a laborious and time-consuming process. Despite the great interest in the past to facilitate tree height measurements, new, upcoming solutions are not yet thoroughly investigated. In this study, we investigated the applicability of different close-range remote sensing options for tree height measurement in a complex lowland deciduous forest. Six sample plots in a pedunculate oak forest were measured in detail using conventional methods. Close-range remote sensing datasets used in this study represent solutions from low-cost sensors used for hand-held personal laser scanning (PLShh), unmanned–borne laser scanning (ULS) and unmanned aerial vehicle photogrammetry (UAVimage). Each tree in the sample plots was interactively measured directly from the point cloud, and correspondence of the field- and remote sensing measured trees was verified using tree positions collected during fieldwork. Cross-comparisons of different datasets were performed to evaluate the performances of different data sources in the tree height estimation with respect to crown class, tree height and species. All remote sensing data sources correlated well, e.g. biases between remote sensing sources were around ± 1%. The field-measured tree height in general correlated well with remote sensing data sources. The uncertainties and bias of the field measurements were dependent on the tree height and crown class. Field measurements tended to underestimate codominant and intermediate trees at the approximately 1 m magnitude, whilst remote sensing data sources were robust to crown classes. Low-cost ULS used in this study, and very likely in general, may not have enough penetration capability when measuring low and mostly occluded trees, causing missed treetops. PLShh gave tree height estimates closer to the real tree height than those derived from conventional field measurements for trees above 21 m height.

Hand-Held Personal Laser Scanning

The emergence of hand-held Personal Laser Scanning (H-PLS) systems in recent years resulted in initial research on the possibility of its application in forest inventory, primarily for the estimation of the main tree attributes (e.g. tree detection, stem position, DBH, tree height, etc.). Research knowledge acquired so far can help to direct further research and eventually include H-PLS into operational forest inventory in the future. The main aims of this review are: - to present the current state of the art for H-PLS systems - briefly describe the fundamental concept and methods for H-PLS application in forest inventory - provide an overview of the results of previous studiesÞ emphasize pros and cons for H-PLS application in forest inventory in relation to conventional field measurements and other similar laser scanning systems - highlight the main issues that should be covered by further H-PLS-based forest inventory studies.

Mesoscale magnetic rings: Complex magnetization reversal uncovered by FORC

In this work, we investigate mesoscopic amorphous magnetic rings prepared by ion-implantation. The analysis is carried out combining conventional magnetization vs field measurements alongside MOKE microscopy imaging and, for the first time, first-order reversal curves (FORCs). With the information extracted from the FORC diagram, we can identify the presence of typical onion and vortex magnetic configurations, and also determine with high resolution the fields connected to their formation, stability, and annihilation. Furthermore, depending on the field and history, two different onion configurations exist, characterized by the presence of transverse or vortex domain walls. The FORC data reveal the different reversible/irreversible nature of the annihilation of the two onion configurations, and a signal peculiar of the presence of vortex domain walls. All these crucial information are not accessible with conventional M(H) loops, demonstrating that FORCs offer a unique perspective for the investigation of the physical phenomena of magnetic elements with complex geometries.

Carbon stock assessment using forest canopy density mapper in agroforestry land in Berau, East Kalimantan, Indonesia

Abstract. Hartoyo APP, Prasetyo LB, Siregar IZ, Supriyanto, Theilade I, Siregar UJ. 2019. Carbon stock assessment using forest canopy density mapper in agroforestry land in Berau, East Kalimantan, Indonesia. Biodiversitas 20: 2661-2676. In the Reducing Emissions from Deforestation and forest Degradation (REDD+) program, remote sensing is the most important tool for measuring forest cover and carbon dynamic, including the utilization of software Forest Canopy Density (FCD) mapper. However, there have been rarely untested the accuracy of FCD applied in agroforestry landscapes to support carbon stock assessment compared to conventional field measurement data. This research was aimed to investigate the correlation between: (i) the value of FCD (%) and tree stand density (N/ha), (ii) the value of FCD (%) and basal area (m2/ha), (iii) the value of FCD (%) and total carbon stock (Mg C/ha), and iv) total carbon stock and percentage of canopy closure (%). Tree stand density, basal area, carbon stock and canopy profile were conventionally measured by trained members of local communities. The results of this study showed that the R2 between FCD and tree density was 37.7% (r = 61.4%), while the R2 between FCD and the basal area was 3.33% (r = 18.3%). The result of normality and heteroscedasticity tests showed that FCD was more accurate and precise in estimating the tree stand density model than the basal area model. Total carbon stock differed significantly (p&lt;0.1) from tree density with R2 = 27.7% (r = 27.3%). Total carbon can be predicted using FCD with total carbon (Mg C/ha) = 13.005 + 0.826 FCD. Our findings suggest that FCD can be used as a new method to estimate tree density and total carbon stock cheaply, efficiently and accurately to support carbon stock assessment in agroforest practices. In carbon assessment, total carbon stock can also be estimated using canopy closure measurement.

3D virtual intersection sight distance analysis using lidar data

Sight distance analyses require careful and detailed field measurements to facilitate proper engineering decision making regarding the removal of obstructions, establishment of regulatory and advisory speed limits, and the location of new access points, among numerous other purposes. However, conventional field measurements for these analyses present safety concerns because they require personnel to be in or adjacent to traffic lanes. They can also be time consuming, costly, and labor intensive. Furthermore, the predominantly two-dimensional (2D) methods involve simplifying assumptions such as a “standard” vehicle heights and lengths without considering the wide range of vehicles and drivers present on the road. Recently, many transportation agencies worldwide have begun to acquire mobile lidar data to map their roadway assets. These data provide a rich three-dimensional (3D) environment that enables one to virtually visit a site at any frequency and efficiently evaluate sight distances from the safety of the office. This study investigates advanced safety analysis methodologies for drivers’ sight distance based on high resolution lidar data. The developed simulation method enables users to virtually evaluate available sight distances in a 3D context considering a variety of objects, vehicle types, and multi-modal forms of transportation (e.g., bicycle, pedestrian). The feasibility of this technique was analyzed with a case study at an intersection located in Corvallis, Oregon, USA. The experimental results demonstrated the ability of the proposed methodology to capture significantly more detail on visibility constraints when compared with conventional measurements as well as provide more flexibility in the analysis.

Field Tests of the Vertical-Array Differential Target Antenna Coupling (DTAC) System

We have tested the Vertical-Array Differential Target Antenna Coupling (DTAC) system over a variety of well-characterized, buried targets. The DTAC system produces a primary field in the frequency range of 10 Hz to 10 kHz and records secondary magnetic fields from subsurface targets, relative to a reference frequency. The current DTAC system has higher power, compared with our earlier tests, and this system is suitable for either ground or airborne mapping of a wide variety of near-surface targets, which might be encountered in civil engineering, water resources, environmental characterization, mining, and other natural-resource exploration. Profiles over three well-characterized targets show a close agreement between the measured DTAC response and model simulations. Conventional field measurements using induced magnetic fields are also displayed and they do not show nearly as effective mapping of the targets. Another profile shows that the DTAC method has greatly reduced sensitivity to surface clutter, compared to conventional measurements.

Assessing Precision in Conventional Field Measurements of Individual Tree Attributes

Forest resource information has a hierarchical structure: individual tree attributes are summed at the plot level and then in turn, plot-level estimates are used to derive stand or large-area estimates of forest resources. Due to this hierarchy, it is imperative that individual tree attributes are measured with accuracy and precision. With the widespread use of different measurement tools, it is also important to understand the expected degree of precision associated with these measurements. The most prevalent tree attributes measured in the field are tree species, stem diameter-at-breast-height (dbh), and tree height. For dbh and height, the most commonly used measuring devices are calipers and clinometers, respectively. The aim of our study was to characterize the precision of individual tree dbh and height measurements in boreal forest conditions when using calipers and clinometers. The data consisted of 319 sample trees at a study area in Evo, southern Finland. The sample trees were measured independently by four trained mensurationists. The standard deviation in tree dbh and height measurements was 0.3 cm (1.5%) and 0.5 m (2.9%), respectively. Precision was also assessed by tree species and tree size classes; however, there were no statistically significant differences between the mensurationists for dbh or height measurements. Our study offers insights into the expected precision of tree dbh and height as measured with the most commonly used devices. These results are important when using sample plot data in forest inventory applications, especially now, at a time when new tree attribute measurement techniques based on remote sensing are being developed and compared to the conventional caliper and clinometer measurements.

Assessment of gully erosion using conventional field measurements: A case study from northern Ethiopia

I n Ethiopia, one of the poorest countries in the world, soil erosion by water contributes significantly to food insecurity of rural households and represents a real threat to sustainability of the existing subsistence agriculture (Hurni 1993; Sutcliffe 1993; Sonneveld 2002). Ethiopia has a total surface area of 111.8 million ha (276.3 million ac); 24% of the land area, and 45% of the area used for agriculture, is significantly affected by erosion. Studies by Fikru (1990) and Sertsu (2000) estimate an annual total soil loss of 2 billion m3 (71 billion ft3), which corresponds to an overall mean annual soil loss of 18 t ha−1 (8.0 tn ac−1). Other studies suggest erosion rates ranging from 16 to 300 t ha−1 y−1 (7.1 to 133.8 tn ac−1 yr−1) (Hurni 1993; Hawando 1989, 1995). In the Ethiopian highlands, annual soil loss reaches rates up to 200 to 300 t ha−1 (89.2 to 133.8 tn ac−1), while global soil loss can reach up to 23,400 million t y−1 (25,787 million tn yr−1) (FAO 1986). Compared to rill and interrill erosion rates measured in Europe (Cerdan et al. 2010), these soil losses are much higher. Occurrence of wide and deep gullies is a common observation…

Relationship between tree growth and physical dimensions of Fagus sylvatica crowns assessed from terrestrial laser scanning

Measurements of physical tree crown dimensions were of subjective character in the past, even though they can be considered important for the management of many silvicultural operations, such as timing of thinning operations. In our study we investigated if and how measures of physical crown dimensions of trees differed when quantified conventionally versus based on 3D-terrestrial laser scanning and how they are related to basal area increment. Some 24 randomly selected predominant or dominant beech trees between 90 and 110 yrs of age and of varying height were used as study trees. We hypothesized that tree crown dimensions obtained from scans are more closely related to tree radial growth than those obtained from conventional field measurements. It was found that from a variety of compared crown size characteristics the scan-based tree attributes mean crown radius, maximum area of the crown and crown projection area were most closely related to individual tree growth. We conclude that the horizontal extension of a tree crown in general is to be considered one of the most important drivers of tree growth. We also conclude that terrestrial laser scanning is a powerful tool to reliably measure physical crown dimensions and TLS-based measurements are more reliable than conventional ones.

Testing a new automated single ring infiltrometer for Beerkan infiltration experiments

The Beerkan method along with BEST algorithms is an alternative technique to conventional laboratory or field measurements for rapid and low-cost estimation of soil hydraulic properties. The Beerkan method is simple to conduct but requires an operator to repeatedly pour known volumes of water through a ring positioned at the soil surface. A cheap infiltrometer equipped with a data acquisition system was recently designed to automate Beerkan infiltration experiments. In this paper, the current prototype of the automated infiltrometer was tested to validate its applicability to the Beerkan infiltration experiment under several experimental circumstances. In addition, the accuracy of the estimated saturated soil hydraulic conductivity, Ks, and sorptivity, S, was assessed by applying different BEST algorithms to the data obtained with the infiltrometer. At this purpose, both analytically generated and real experimental data were used. The analytical assessment showed that the use of the infiltrometer along with BEST methods could lead to accurate estimates of the considered soil properties in most cases, which validated the design of the infiltrometer and its combination with BEST algorithms. Loamy soils and high initial water contents led to misestimating Ks and S or to failure of BEST algorithms, but advices about the infiltrometer design were developed to alleviate such problems. A comparison between the automated procedure and the original BEST procedure was made at three field sites in Sicily (Italy). Other experiments were carried out in an infiltration basin located in the pumping well field of Crépieux-Charmy (Lyon, France), in order to assess the ability of the automated infiltrometer to check clogging effects on Ks. The experiments showed that the automatic data collection increased measurement speed, allowed a more efficient data handling and analysis, and reduced sensitivity of the calculated hydraulic parameters on the applied BEST algorithm.

Geometrically explicit description of forest canopy based on 3D triangulations of airborne laser scanning data

Abstract Geometrically explicit parameterizations of the locations, orientations and properties of trees and canopy elements are useful for forest ecosystem modeling. Detailed reconstructions based on real tree geometry are, however, hard to obtain based on conventional field measurements and sampling. We describe and evaluate an alternative approach to reconstruct the forest canopy from sparse, leaf-off airborne laser scanning (ALS) data with a wall-to-wall coverage. The approach employs computational geometry and topological connectivity to generate filtrations, i.e., ordered sets of simplices belonging to the three-dimensional (3D) triangulations of the point data, and numerical optimization to select the set of simplices with a quasi-optimal relationship with field-measured forest biophysical attributes. The approach was evaluated by predicting the quantities and spatial patterns of biomass-related forest attributes according to the characteristics of the filtration. When the filtration parameters were optimized for 245 sample plots of 300 m2 located in southern boreal forest in Finland, the coefficients of determination (R2) between total volumes of the filtrations and basal area, stem volume, total above-ground biomass, and canopy biomass were 0.93, 0.87, 0.87, and 0.62, respectively. Considerably less accurate results (R2 = 0.44–0.64) were obtained when the filtration parameters were predicted with a limited number of the calibration field plots. However, these accuracies could be obtained with modest field training data of 20–30 plots. The proposed approach is a compromise between the parameterization of the forest scene by artificial tree/crown level turbid media and realistic 3D models. The results particularly suggest that obtaining coarse wall-to-wall descriptions does not require separate data acquisitions, but may be based on data existing due to previous practical inventories.

On Joint Roughness: Measurements and Use in Rock Mass Characterization

The paper focuses on the methods commonly used for measuring and quantifying the joint roughness in the current rock mass characterization practice. Among the different parameters traditionally employed to express roughness, major relevance seems to be gained by the “Joint Roughness factor” (jR) applied in the Palmstrom’s rock mass characterization index system, having this factor also been integrated in some quantitative methods recently proposed for estimating the geological strength index of a rock mass. Therefore, a new quantitative approach for a more objective estimation of this factor has been fine-tuned and is presented in the paper. The new method has been specifically designed to assist engineering geologists in gaining consistent values of jR on the base of conventional routine field measurements. It can suitably integrate and support the traditional semi-qualitative Palmstrom’s classification of joint roughness, mostly related to more subjective descriptions, to estimate the most representative values of jR to be considered for rock mass characterization. In its original definition, the factor jR is evaluated for two-dimensional joint profiles by the product of a small-scale roughness factor (the joint smoothness or unevenness factor, js) with a large-scale roughness factor (the joint waviness factor, jw). In order to reduce the subjectivity on the estimate of these partial factors, a simple analytic equation relating them with some parameters traditionally used to quantify 2D joint roughness is here proposed, providing a continuous gradation among the different ratings of the jR scale and also facilitating the implementation of the factor in probabilistic approaches for managing its inherent uncertainty and variability. The presented method applies best for characterizing hard rock masses well-exposed after blasting (e.g., in dam foundation or quarry slopes) or favourably outcropping on natural rocky slopes, where joint surfaces can generally be easily attained and analysed.

A Transient Thermography Method to Separate Heat Loss Mechanisms in Parabolic Trough Receivers

This paper describes a transient thermography method to measure the heat loss of parabolic trough receivers and separate their heat loss mechanisms. This method is complementary to existing stationary techniques, which use either energy balances or glass envelope temperature measurements to derive overall heat losses. It is shown that the receiver heat loss can be calculated by applying a thermal excitation on the absorber tube and measuring both absorber tube and glass envelope temperature signals. Additionally, the emittance of the absorber selective coating and the vacuum quality of the annulus can be derived. The benefits and the limits of the transient method are presented and compared to the established stationary method based on glass envelope temperature measurements. Simulation studies and first validation experiments are described. A simulation based uncertainty analysis indicates that an uncertainty level of approximately 5% could be achieved on heat loss measurements for the transient method introduced in this paper, whereas for a conventional stationary field measurement technique, the uncertainty is estimated to 17–19%.

실내 주광조도 분포 예측식의 제안 및 검증

In these days, most of the office buildings are being required to save energy for maintenance. lighting system constitutes 20% to 30% of the total annual electrical energy consumption in office buildings. As an energy saving strategy for lighting system, dimming control system based on illuminance sensors came into use. But the system is accompanied with many illuminance sensors to control lighting and needs a lot of initial investment. In this study, the prediction equation for indoor daylighting illuminance distribution is proposed through the review for conventional research results and field measurements. The proposed equation was verified by the comparison between predicted results and field measurement results. The developed prediction equation for daylighting can be used to control the indoor illuminance level with the limited sensor when dimming control system is operated.

Detecting Changes in Forest Structure over Time with Bi-Temporal Terrestrial Laser Scanning Data

Changes to stems caused by natural forces and timber harvesting constitute an essential input for many forestry-related applications and ecological studies, especially forestry inventories based on the use of permanent sample plots. Conventional field measurement is widely acknowledged as being time-consuming and labor-intensive. More automated and efficient alternatives or supportive methods are needed. Terrestrial laser scanning (TLS) has been demonstrated to be a promising method in forestry field inventories. Nevertheless, the applicability of TLS in recording changes in the structure of forest plots has not been studied in detail. This paper presents a fully automated method for detecting changes in forest structure over time using bi-temporal TLS data. The developed method was tested on five densely populated forest plots including 137 trees and 50 harvested trees in point clouds. The present study demonstrated that 90 percent of tree stem changes could be automatically located from single-scan TLS data. These changes accounted for 92 percent of the changed basal area. The results indicate that the processing of TLS data collected at different times to detect tree stem changes can be fully automated.