High Pulse Density Research Articles

Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density

Leaf area is a key structural characteristic of forest canopies because of the role of leaves in controlling many biological and physical processes occurring at the biosphere-atmosphere transition. High pulse density Airborne Laser Scanning (ALS) holds promise to provide spatially resolved and accurate estimates of plant area density (PAD) in forested landscapes, a key step in understanding forest functioning: phenology, carbon uptake, transpiration, radiative balance etc. Inconsistencies between different ALS sensors is a barrier to generating globally harmonised PAD estimates. The basic assumption on which PAD estimation is based is that light attenuation is proportional to vegetation area density. This study shows that the recorded extinction strongly depends on target detectability which is influenced by laser characteristics (power, sensitivity, wavelength). Three different airborne laser scanners were flown over a wet tropical forest at the Paracou research station in French Guiana. Different sensors, flight heights and transmitted power levels were compared. Light attenuation was retrieved with an open source ray-tracing code (http://amapvox.org). Direct comparison revealed marked differences (up-to 25% difference in profile-averaged light attenuation rate and 50% difference at particular heights) that could only be explained by differences in scanner characteristics. We show how bias which may occur under various acquisition conditions can generally be mitigated by a sensor intercalibration. Alignment of light weight lidar attenuation profiles to ALS reference attenuation profiles is not always satisfactory and we discuss what are the likely sources of discrepancies. Neglecting the dependency of apparent light attenuation on scanner properties may lead to biases in estimated vegetation density commensurate to those affecting light attenuation estimates. Applying intercalibration procedures supports estimation of plant area density independent of acquisition characteristics.

Cross-Comparison of Individual Tree Detection Methods Using Low and High Pulse Density Airborne Laser Scanning Data

Numerous individual tree detection (ITD) methods have been developed for use with airborne laser scanning (ALS) data to provide tree-scale forest inventories across large spatial extents. Despite the growing number of methods, relatively few have been comparatively assessed using a single benchmark forest inventory validation dataset, limiting their operational application. In this study, we assessed seven ITD methods, representing three common approaches (point-cloud-based, raster-based, hybrid), across coniferous forest stands with diverse structure and composition to understand how ITD and height measurement accuracy vary with method, input parameters and data, and stand density. There was little variability in accuracy between the ITD methods where the average F-score and standard deviation (±SD) were 0.47 ± 0.03 using a lower pulse density ALS dataset with an average of 8 pulses per square meter (ppm2) and 0.50 ± 0.02 using a higher pulse density ALS dataset with an average of 22 ppm2. Using higher ALS pulse density data produced higher ITD accuracies (F-score increase of 10–13%) in some of the methods versus more modest gains in other methods (F-score increase of 1–3%). Omission errors were strongly related with stand density and largely consisted of suppressed trees underneath the dominant canopy. Simple canopy height model (CHM)-based methods that utilized fixed-size local maximum filters had the lowest omission errors for trees across all canopy positions. ITD accuracy had large intra-method variation depending on input parameters; however, the highest accuracies were obtained when parameters such as search window size and spacing thresholds were equal to or less than the average crown diameter of trees in the study area. All ITD methods produced height measurements for the detected trees that had low RMSE (<1.1 m) and bias (<0.5 m). Overall, the results from this study may help guide end-users with ITD method application and highlight future ITD method improvements.

High cycle fatigue life improvement of superferritic stainless steel by laser shock peening without coating

The excellent mechanical properties, high thermal conductivity and corrosion resistance combined with moderate cost make superferritic stainless steels (SFSS) commercially attractive. Though these steels are finding increase uses in many applications where fatigue loadings are applied, few studies are devoted to study this theme. Even fewer works aim to investigate the fatigue improvement by surface treatments. Laser shock peening without coating (LSPwC), is a surface modification technology using high-energy laser with no absorbent coating that increases the fatigue life in many alloys. However, though LSPwC in SFSS UNS44600 has reported to produce beneficial compression residual stresses (CRSs) and strain-hardening surface layer, it also causes intergranular corrosion which avoids the improvement of low fatigue life (LCF). Thus, attempting to discern if this result remains in the HCF regimen, the present paper is focused on studying the influence of LSPwC on the high cycle life (HCF) of SFSS UNS S44600. The results showed that LSPwC enhances the HCF of SFSS UNS S44600, being the fatigue life improvement more pronounced with higher pulse density. This can be rationalized considering the main role of the induced CRS in slowing occurrence and growth of crack in corroded grains on HCF regimen. The examination of fracture surface by scanning electron microscopy (SEM) substantiates these fatigue results.

Effect of varied unmanned aerial vehicle laser scanning pulse density on accurately quantifying forest structure

ABSTRACT Airborne laser scanning (ALS) is increasingly used to estimate various forest characteristics. Technological improvements in unmanned aerial vehicles (UAVs) and drone laser scanning (DLS) sensors have permitted the acquisition of high pulse density datasets. There is an assumption that higher pulse densities yield greater accuracies in estimating forest characteristics. In this study, we investigated the effect of pulse density (.25, .5, 1, 5, 10, 50, 100 and 300 pulses m−2) on the ability to delineate individual tree crowns (ITCs) and estimate ITC height and crown horizontal diameter, in addition to plot-level leaf area index (LAI). The current study took place in an experimentally varied Pinus taeda L. forest, which included three stem densities: (i) 618; (ii) 1236; and (iii) 1853 trees per hectare (TPH). ITCs were classified directly from the DLS point cloud for each of the pulse densities. The correct delineation of ITCs relative to field tree-coordinates was relatively consistent (±5%) for pulse densities of 5 to 300 pulses m−2. ITC delineation accuracy decreased with lower pulse densities. Planting stem density did impact ITC delineation accuracy. Higher pulse densities, plots with 618 TPH correctly classified ~88% of ITCs, and plots with the 1853 TPH correctly classified ~50% of ITCs. Estimates of tree height were largely unaffected by changes in tree density. Root mean square error (RMSE) for tree height varied from .5 to 2.5 m at pulse densities of 300 to .25 pulses m−2, respectively. Estimates of crown horizontal diameter varied with regard to both pulse and stem density from 1.2 (300 ppm−2 and 1853 TPH) to 4.2 m (.25 ppm−2 and 618 TPH). RMSE varied among stem densities from .6 to 1.2 m as pulse density decreased. There was significant difference in ITC delineation accuracy, particularly when considering stem density, and the estimates of tree height and crown horizontal diameter among the DLS pulse densities used. The accuracy of predicted LAI was largely unaffected by changes in pulse density, when pulse density was above .5 pulses m−2. There was little or no difference in estimates of LAI at these pulse densities. Our results suggest that low-density DLS data may be capable of estimating plot-level forest metrics reliably in some situations, however once the analysis scale is reduced to the individual-tree-level, the influence of pulse density is more substantial. The results here provide guidance to forest managers who must balance metric estimation accuracy and price when planning new ALS or DLS acquisitions.

Extracting Canopy Closure by the CHM-Based and SHP-Based Methods with a Hemispherical FOV from UAV-LiDAR Data in a Poplar Plantation

Canopy closure (CC), a useful biophysical parameter for forest structure, is an important indicator of forest resource and biodiversity. Light Detection and Ranging (LiDAR) data has been widely studied recently for forest ecosystems to obtain the three-dimensional (3D) structure of the forests. The components of the Unmanned Aerial Vehicle LiDAR (UAV-LiDAR) are similar to those of the airborne LiDAR, but with higher pulse density, which reveals more detailed vertical structures. Hemispherical photography (HP) had proven to be an effective method for estimating CC, but it was still time-consuming and limited in large forests. Thus, we used UAV-LiDAR data with a canopy-height-model-based (CHM-based) method and a synthetic-hemispherical-photography-based (SHP-based) method to extract CC from a pure poplar plantation in this study. The performance of the CC extraction methods based on an angular viewpoint was validated by the results of HP. The results showed that the CHM-based method had a high accuracy in a 45° zenith angle range with a 0.5 m pixel size and a larger radius (i.e., k = 2; R2 = 0.751, RMSE = 0.053), and the accuracy declined rapidly in zenith angles of 60° and 75° (R2 = 0.707, 0.490; RMSE = 0.053, 0.066). In addition, the CHM-based method showed an underestimate for leaf-off deciduous trees with low CC. The SHP-based method also had a high accuracy in a 45° zenith angle range, and its accuracy was stable in three zenith angle ranges (R2: 0.688, 0.674, 0.601 and RMSE = 0.059, 0.056, 0.058 for a 45°, 60° and 75° zenith angle range, respectively). There was a similar trend of CC change in HP and SHP results with the zenith angle range increase, but there was no significant change with the zenith angle range increase in the CHM-based method, which revealed that it was insensitive to the changes of angular CC compared to the SHP-based method. However, the accuracy of both methods showed differences in plantations with different ages, which had a slight underestimate for 8-year-old plantations and an overestimate for plantations with 17 and 20 years. Our research provided a reference for CC estimation from a point-based angular viewpoint and for monitoring the understory light conditions of plantations.

Porous mullite fiber nonwoven separator materials containing Nano-MgO particles for the design of thermal batteries

Porous ceramic separator materials have been used to enhance the performance of thermal batteries but they are not sufficiently effective. In this study, we developed a porous ceramic fiber separator substrate using Mullite fiber (a kind of ceramic fiber) employing the wet-laid technology. The substrate was modified using magnesium acetate precursors to obtain a porous, flexible, strong ceramic fiber separator (CFS) containing Nano-MgO particles. Although the diameter of CFS exceeded 11.3 cm, it was relatively thin (approximately 0.3 mm). Application of CFS clearly improved the electrochemical performance of the conventional Li-B/LiF-LiCl-LiBr/FeS2 electrochemical system. Li-B/LiF-LiCl-LiBr/FeS2 electrochemical system fitted with CFS increases the specific capacity of the battery by 24% and yields a polarization resistance of 0.011 Ω even with a high current pulse density of 5000 mA·cm−2. The findings of this study demonstrate that CFS can effectively improve performance of current thermal battery electrochemical systems.

Process-property correlations in laser-induced graphene electrodes for electrochemical sensing

Laser-induced graphene (LIG) has emerged as a promising electrode material for electrochemical point-of-care diagnostics. LIG offers a large specific surface area and excellent electron transfer at low-cost in a binder-free and rapid fabrication process that lends itself well to mass production outside of the cleanroom. Various LIG micromorphologies can be generated when altering the energy input parameters, and it was investigated here which impact this has on their electroanalytical characteristics and performance. Energy input is well controlled by the laser power, scribing speed, and laser pulse density. Once the threshold of required energy input is reached a broad spectrum of conditions leads to LIG with micromorphologies ranging from delicate irregular brush structures obtained at fast, high energy input, to smoother and more wall like albeit still porous materials. Only a fraction of these LIG structures provided high conductance which is required for appropriate electroanalytical performance. Here, it was found that low, frequent energy input provided the best electroanalytical material, i.e., low levels of power and speed in combination with high spatial pulse density. For example, the sensitivity for the reduction of K3[Fe(CN)6] was increased almost 2-fold by changing fabrication parameters from 60% power and 100% speed to 1% power and 10% speed. These general findings can be translated to any LIG fabrication process independent of devices used. The simple fabrication process of LIG electrodes, their good electroanalytical performance as demonstrated here with a variety of (bio)analytically relevant molecules including ascorbic acid, dopamine, uric acid, p-nitrophenol, and paracetamol, and possible application to biological samples make them ideal and inexpensive transducers for electrochemical (bio)sensors, with the potential to replace the screen-printed systems currently dominating in on-site sensors used.Graphical abstract

Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets

Two different pulse density airborne laser scanning datasets were used to develop a quality assessment methodology to determine how airborne laser scanning derived variables with the use of reference surface can determine forest road quality. The concept of a reference DEM (Digital Elevation Model) was used to guarantee locally invariant topographic analysis of road roughness. Structural condition, surface wear and flatness were assessed at two test sites in Eastern Finland, calculating surface indices with and without the reference DEM. The high pulse density dataset (12 pulses m) gave better classification results (77% accuracy of the correctly classified road sections) than the low pulse density dataset (1 pulse m). The use of a reference DEM increased the precision of the road quality classification with the low pulse density dataset when the classification was performed in two-steps. Four interpolation techniques (Inverse Weighted Distance, Kriging, Natural Neighbour and Spline) were compared, and spline interpolation provided the best classification. The work shows that applying a spline reference DEM it is possible to identify 66% of the poor quality road sections and 78% of the good ones. Locating these roads is essential for road maintenance.–2–2

Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB) stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs) used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national level MRV systems for REDD+ emission reduction programs for tropical forests.

Impact of Slope, Aspect, and Habitat-Type on LiDAR-Derived Digital Terrain Models in a Near Natural, Heterogeneous Temperate Forest

Developments in airborne LiDAR data acquisition have provided better horizontal and vertical ground information in the form of 3D point clouds. This has led to satisfactory results of LiDAR-derived digital terrain models (DTMs), also across complex ecosystems like natural forest stands. However, data and site-driven factors such as spatial resolution (point density), topography (slope and aspect), and variation in forest habitat types affect the DTM accuracy. In addition, processing steps like ground filtering and interpolation of ground points may also result in differences in DTM quality. Here, a comparative study was designed by extracting DTMs from two LiDAR data sources (high- and low-density point clouds) and three ground-filtering algorithms (adaptive TIN algorithm with and without the use of mirror points as well as an interpolation-based algorithm). The accuracy of the DTMs was assessed in association with terrain parameter and forest habitat types across heterogeneous forest sites of Bavarian Forest National Park in southeastern Germany. Qualitative analysis was carried out by taking 8300 independent sets of DGPS-recorded sample points. In addition to deriving root-mean-square error (RMSE) and bias, analysis of variance (ANOVA) type II was conducted in a factorial design to assess the influential factors on the observed DTM random error. Results revealed these errors in the DTMs with occasional over- and underestimations up to 1.98 m compared to reference elevation values. DTMs produced from high pulse density LiDAR data were more accurate than those extracted from low pulse density. Furthermore, topographic and forest habitat-type factors significantly contributed to the DTM accuracy. Slope increment showed a direct relationship with DTM error, with higher errors observed in south, southwest, and west aspects. Furthermore, stands dominated by deciduous trees were associated with higher DTM error than other forest habitat types. The applied adaptive TIN ground-filtering algorithms with mirror points and the interpolation-based algorithm both produced comparatively lower error rates, which are, therefore, suggested to reduce interpolation error in DTMs across rugged and heterogeneous forested terrains.

Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data

Mapping tree species within urban areas is essential for sustainable urban planning as well as to improve our understanding of the role of urban vegetation as an ecological service. Urban trees contribute significantly in mitigating the urban heat island effect and supporting biodiversity. However, accurate and up-to-date mapping of urban tree species is difficult because of the time-consuming nature of field sampling, fine-scale spatial variation, and potentially high species diversity. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) with high pulse density (25point/m2) and hyperspectral imagery offer two different yet complementary approaches to estimating crown structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, we evaluate the potential of these technologies to map 15 common urban tree species using a Random Forest (RF) classifier in the City of Surrey, British Columbia, Canada. LiDAR-derived crown structural information was combined with hyperspectral-derived spectral vegetation indices for species classification. Results indicate an overall accuracy of 51.1%, 61.0%, and 70.0% using hyperspectral, LiDAR and the combined data respectively. The overall accuracy for the two most important and iconic native coniferous species improved markedly from 78.3% up to 91% using the combined data. The results of this research highlight that (1) the combination of structural and spectral information provided an improved classification accuracy than when used separately, and variables derived from LiDAR data contributed more to the accurate prediction of species than hyperspectral features; (2) higher classification accuracies were observed for evergreen species, species with distinguishable crown structure, and species undergoing flowering; (3) and finally the anthocyanin content index and photochemical reflectance index were the most important hyperspectral features for the discrimination of tree species in the spring budburst stage.

Surface modification of 17-4 PH stainless steel by laser peening without protective coating process

The objective of the present study was to examine the influence of laser peening without protective coating (LPwC) process on surface mechanical properties of precipitation hardened stainless steel 17-4 PH. Pulse densities, 2500 and 6250pulsescm−2, using a constant laser power density of 5.97GWcm−2 were chosen and their effect on residual stresses, micro-structure, micro-hardness, surface roughness and topography were investigated. Higher pulse density induced large compressive residual stresses and influenced up to depth of 600μm. It was confirmed from resulted larger lattice strain in LPwC processed 17-4 PH steel with higher pulse density. No phase transformation and microstructural change were observed, which represented pure mechanical effect of LPwC. Hardness was increased with depth of hardened layer up to 600μm for higher pulse density. However, the surface roughness was increased by the process, and resulted in more pronounced peening pattern. Surface topography revealed columnar structure after LPwC process.

Effect of Laser Peening without Coating on 316L austenitic stainless steel

Laser Peening without Coating (LPwC) is an innovative surface modification technique used for the in-suit preventive maintenance of nuclear reactor components using frequency doubled (green) laser. The advantage of LPwC is that the laser required for this technique is in milli joule range and the processes can perform in aqueous environment. This paper discussed the effect of LPwC on 316L austenitic stainless steel using low energy Nd: YAG laser with various laser pulse density. The base specimen and laser peened specimen were subjected to surface residual stress, surface morphology, micro hardness and potentiodynamic polarization studies. The laser peened surface exhibit significant improvement in surface compressive residual stress. The depth profile of micro hardness revealed higher strain hardening on laser peened specimens. Though corrosion potential reported an anodic shift,current density is found to be increased after LPwC for the specimen peened with higher pulse density.

The influence of LiDAR pulse density on the precision of inventory metrics in young unthinned Douglas-fir stands during initial and subsequent LiDAR acquisitions

LiDAR is an established technology that is increasingly being used to characterise spatial variation in stand metrics used in forest inventory. As the cost of LiDAR acquisition markedly declines with LiDAR pulse density, it is useful to identify how far pulse density can be reduced without compromising the precision of relationships between LiDAR and stand metrics. Using plot measurements and LiDAR data obtained from highly stocked and unthinned Douglas-fir plantations (Pseudotsuga menziesii [Mirb.] Franco), the objective of this research was to characterise the precision of regressions between LiDAR metrics and stand metrics (mean top height, Hm, volume, V and mean diameter, D) under a range of pulse densities using Digital Terrain Models (DTMs) representing two common scenarios. Under the first scenario, which represents an initial acquisition, the point cloud was sequentially culled and used for creation of a DTM and corresponding LiDAR cloud metrics. In the second scenario, which represents a subsequent acquisition, a DTM generated at high pulse density (10 pulses m−2) was used for the creation of the corresponding LIDAR cloud metrics. Models describing the precision of regressions between LiDAR metrics and stand metrics were developed at 10 pulses m−2. LiDAR data were culled to pulse densities ranging from 10 to 0.01 pulses m−2 and the impact of culling on the precision of these regressions was examined under the two scenarios. For the scenario with the culled DTM, precision of the three models remained stable until densities of 2 – 3 pulses m−2 were reached. Below this threshold, there was a gradual decline in precision to pulse densities of 0.7 – 1 pulses m−2 at which point the R2 was 95% of the maximum values. Further culling of the data resulted in a sharp decline in model precision for all three regressions. For the scenario where the DTM was held at a high pulse density, little change in the precision of the regressions was found until pulse densities of 0.04 to 0.2 pulses m−2 were reached. There was a sharp decline in precision below pulse densities of 0.04 pulses m−2 for all three models. This study was undertaken in highly stocked unthinned Douglas-fir stands located in areas with complex topography. Consequently, the pulse density thresholds described here are likely to be conservative and could be used to guide acquisition of high-quality LiDAR datasets for this species.

3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar

We developed a method to produce a 3-D voxel-based solid model of a tree based on portable scanning lidar data for accurate estimation of the volume of the woody material. First, we obtained lidar measurements with a high laser pulse density from several measurement positions around the target, a Japanese zelkova tree. Next, we converted lidar-derived point-cloud data for the target into voxels. The voxel size was 0.5cm×0.5cm×0.5cm. Then, we used differences in the spatial distribution of voxels to separate the stem and large branches (diameter>1cm) from small branches (diameter⩽1cm). We classified the voxels into sets corresponding to the stem and to each large branch and then interpolated voxels to fill out their surfaces and their interiors. We then merged the stem and large branches with the small branches. The resultant solid model of the entire tree was composed of consecutive voxels that filled the outer surface and the interior of the stem and large branches, and a cloud of voxels equivalent to small branches that were discretely scattered in mainly the upper part of the target. Using this model, we estimated the woody material volume by counting the number of voxels in each part and multiplying the number of voxels by the unit voxel volume (0.13cm3). The percentage error of the volume of the stem and part of a large branch was 0.5%. The estimation error of a certain part of the small branches was 34.0%.

A New PRI Transform for the Deinterleaving of Radar Pulses

This paper presents a new algorithm for the deinterleaving of radar signals, using the direction of arrival (DOA), carrier frequency (RF), and time of arrival (TOA). The algorithm is mainly applied to pulse repetition interval (PRI) signals. This algorithm consists of two steps: In the first step, a PRI transformation is used to the received pulses after pre-deinterleaved of frequency and DOA. In this step, radar signals having the same frequency and DOA are identified as the same class. In the second step, the number of existing emitters and their PRIs is determined by using TOA information. The algorithm for deinterleaving uses the information obtained from the previous analysis to reduce the PRI errors. The simulation results show that the algorithm is successful in high pulse density environments and for the complex signal types.

Surface Modification of Aluminium Alloys with Laser Shock Processing

An adequate residual stress variation and frequently also improved corrosion resistance of a material are key requirements for usability of numerous machine components in various applications. The aim of the investigation conducted was to determine optimum Laser Shock Processing (LSP) parameters for aluminium specimens in order to obtain the desired residual stress variation and improved corrosion resistance. LSP treatment was performed with a Q-switched Nd:YAG laser with a wavelength of 1064 nm. In order to statistically confirm the optimum process parameters, a factorial design was applied, in which the first experimental factor was pulse density, i.e. 900 and 2500 pulses/cm2, the second factor was the type of material used, i.e. aluminium alloys AlMgSiPb and AlSi1MgMn and the third factor was the direction of LSP surface sweep, i.e. longitudinal and transversal direction. The experiments made confirmed a characteristic influence of the first factor representing different pulse densities. An analysis of residual stresses confirmed that in processing with 2500 pulses/cm2 the highest compressive residual stresses were obtained. Potentiodynamic corrosion testing confirmed that the higher pulse density resulted in a stronger shift of pitting potential, which provided higher corrosion resistance.

Estimating tree size distributions and timber assortment recoveries for wood procurement planning using airborne laser scanning

ALS-based inventory methods are replacing traditional field inventories in the production of stand-level data for operative and management purposes. Despite the advances made in the species-specific inventories of mean stand variables, ALS has not succeeded in providing accurate growing stock descriptions for operative wood procurement planning, for example, containing information on tree quality, tree size distribution and the distribution of the logs in timber assortment classes. The aim of this thesis is to evaluate and develop ALS-based methods of predicting tree size distributions and timber assortment recoveries. The experimental work was carried out in two inventory areas both located in Eastern Finland: Matalansalo, representing a typical managed boreal forest, and Koli, located in the Koli National Park. The remote sensing material for Matalansalo consisted of low and high pulse density ALS data and digital aerial images, and the material for the Koli area of high density ALS data only. The investigated estimation methods were individual tree delineation (ITD) and areabased statistical approach (ABSA), which were also compared within the same test areas. The performance of ITD in estimating tree size distributions and theoretical timber assortment classes was found to be better than that of the compared methods (ABSA and field assessments) in cases where individual trees could be discerned from the ALS data. In the aggregate, the different ALS methods were comparable when estimating volume and basal area, but ITD tended to produce a bias in saw log volumes and tree size distributions because of the errors in tree delineation. It was stated that the errors in both of the methods, ITD and ABSA, were in correlation with the tree size distribution and the spatial distribution of tree locations. The estimation of theoretical and actual saw log recoveries was investigated using two area-based methods. The results of the linear regression indicated that it is possible to obtain accurate saw log recoveries using an area-based ALS method. The second method employed k-nearest neighbour imputation and harvester-collected stem data bank. The method produced species-specific saw log recoveries although the estimation accuracies were not as good as expected. The method could be improved by using a more representative stem data bank and additional search variables. The harvester data from final cuttings was found to be suitable material for validating the diameter distributions and theoretical saw log recoveries estimated from ALS data, although there were challenges considering the delineation of the stand, tree positioning accuracy and different bucking preferences. The use of stem data bank as an auxiliary data source was more challenging because the stem data bank did not include reliable information on stand delineation and bucking parameters.

Using airborne laser scanning to monitor tree migration in the boreal–alpine transition zone

The boreal tree line is expected to advance upwards into the mountains and northwards into the tundra due to global warming. The major objective of this study was to find out if it is possible to use high-resolution airborne laser scanner data to detect very small trees — the pioneers that are pushing the tree line up into the mountains and out onto the tundra. The study was conducted in a sub-alpine/alpine environment in southeast Norway. A total of 342 small trees of Norway spruce, Scots pine, and downy birch with tree heights ranging from 0.11 to 5.20 m were precisely georeferenced and measured in field. Laser data were collected with a pulse density of 7.7 m − 2 . Three different terrain models were used to process the airborne laser point cloud in order to assess the effects of different pre-processing parameters on small tree detection. Greater than 91% of all trees > 1 m tall registered positive laser height values regardless of terrain model. For smaller trees (< 1 m), positive height values were found in 5–73% of the cases, depending on the terrain model considered. For this group of trees, the highest rate of trees with positive height values was found for spruce. The more smoothed the terrain model was, the larger the portion of the trees that had positive laser height values. The accuracy of tree height derived from the laser data indicated a systematic underestimation of true tree height by 0.40 to 1.01 m. The standard deviation for the differences between laser-derived and field-measured tree heights was 0.11–0.73 m. Commission errors, i.e., the detection of terrain objects — rocks, hummocks — as trees, increased significantly as terrain smoothing increased. Thus, if no classification of objects into classes like small trees and terrain objects is possible, many non-tree objects with a positive height value cannot be separated from those actually being trees. In a monitoring context, i.e., repeated measurements over time, we argue that most other objects like terrain structures, rocks, and hummocks will remain stable over time while the trees will change as they grow and new trees are established. Thus, this study indicates that, given a high laser pulse density and a certain density of newly established trees, it would be possible to detect a sufficient portion of newly established trees over a 10 years period to claim that tree migration is taking place.

An energy-distribution strategy in fast-cutting wire EDM

The technical requirements of fast-cutting wire EDM are revealed in this paper. In addition to high input pulse energy, fast cutting (cutting speed > 200 mm 2/min) without damaging the electrode wire needs a high energy efficiency for maintaining a stable fast-cutting process and moderate wire temperature. Based on a synthesis of experimental results and pulse energy analysis, an energy-distribution diagram concerning the correlation between cutting speed and comprehensive machining conditions has been established to determine a suitable parameter combination for a stable fast-cutting process. High power density and high pulse density are found to be two basic requirements for a constant high cutting speed. Harmful energy loss has to be reduced, otherwise the wire temperature becomes too high due to the dissipated heat. According to the energy-distribution diagram, machining conditions such as cutting width, wire diameter and wire traveling speed are also considered in increasing the cutting speed. After an optimization of the energy distribution in fast-cutting wire EDM, a 4-fold improvement in cutting speed has been achieved whilst the wire service life remains almost unchanged. The surface conditions of the cut workpiece are examined through SEM microscopy: the surface roughness is lower than usually expected. A systematic approach is presented for a very fast cutting process. The achievements described here have practical significance in enhancing mold/die productivity as well as in transferring wire EDM into a general cutting alternative. With the cutting speed being increased, the inherent advantages of wire EDM can be used in many cutting cases.