Bibliographie
77 références — synchronisée depuis la bibliothèque Zotero BRASNAH
Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey
Measurement
Forest inventory (FI) surveys are cumbersome when field measurements are performed by manual means. We propose a semi-automated data collection approach using handheld mobile laser scanning (HMLS) to estimate and map key FI parameters. To this end, machine learning (e.g., random forest classifier for tree detection) and innovative algorithms (e.g., ellipse fitting for diameter estimation of noncircular trees) were used for the first time in FI surveying. After surveying nine plots, we compared HMLS-derived data against the field reference. HMLS-derived tree diameters (DBHs) were strongly correlated with the reference data at the single-tree level (𝑟 = 0.93–0.99; 𝑝 < 0.001). At the plot level, HMLS slightly overestimated DBHs in complex plots due to the influence of undergrowth and creepers on trunks. Yet, no statistically significant difference was found between the two datasets (𝑝 > 0.05). Overall, HMLS was concluded as efficient and effective tool for FIs, even if used alone.
Modelling internal tree attributes for breeding applications in Douglas-fir progeny trials using RPAS-ALS
Science of Remote Sensing
Coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is one of the most commercially important softwood species in North America. In British Columbia, Canada, breeding has increased volume gains between 20 and 30%, while 97% of seedlings come from improved seed sources. Branching traits in particular, have a strong influence on strength and stiffness of Douglas-fir wood; however, they are rarely measured. Remotely Piloted Aerial Systems and Airborne Laser Scanning Systems (RPAS-LS) produce high-density three-dimensional point clouds that can be used for the creation of internal geometric features describing individual tree branching structures. We analyzed a Coastal Douglas-fir progeny test trial located in British Columbia, Canada, and developed a new method to estimate branch attributes from RPAS-LS data for inclusion as selection criteria in tree improvement programs. Branch length, angle, width, and volume were estimated for each tree. Narrowsense heritability (the proportion of variation due to genetics) and genetic correlations were also estimated. The method extracted branch length with a correlation (r) of 0.93 compared to manual measurements. Using these branch attributes, results then show that branch angle had the highest heritability (0.277), while tree height and branch length had the highest genetic correlation (0.668). These findings are encouraging for forest managers as they indicate that branch level metrics should be considered when selecting trees in breeding programs.
Timber volume estimation based on airborne laser scanning — comparing the use of national forest inventory and forest management inventory data
Annals of Forest Science
Key message Large-scale forest resource maps based on national forest inventory (NFI) data and airborne laser scanning may facilitate synergies between NFIs and forest management inventories (FMIs). A comparison of models used in such a NFI-based map and a FMI indicate that NFI-based maps can directly be used in FMIs to estimate timber volume of mature spruce forests.
Terrestrial laser scanning vs. manual methods for assessing complex forest stand structure: a comparative analysis on plenter forests
European Journal of Forest Research
In continuous cover forestry, plenter silviculture is regarded as an elaborated system for optimizing the sustainable production of high-quality timber maintaining a constant but heterogeneous canopy. Its complexity necessitates high silvicultural expertise and a detailed assessment of forest stand structural variables. Terrestrial laser scanning (TLS) can offer reliable techniques for long-term tree mapping, volume calculation, and stand variables assessment in complex forest structures. We conducted surveys using both automated TLS and conventional manual methods (CMM) on two plots with contrasting silvicultural regimes within the Black Forest, Germany. Variations in automated tree detection and stand variables were greater between different TLS surveys than with CMM. TLS detected an average of 523 tree stems per hectare, while CMM counted 516. Approximately 9.6% of trees identified with TLS were commission errors, with 6.5% of CMM trees being omitted using TLS. Basal area per hectare was slightly higher in TLS (38.9 m3) than in CMM (38.2 m3). However, CMM recorded a greater standing volume (492.7 m3) than TLS (440.5 m3). The discrepancy in stand volume between methods was primarily due to TLS underestimating tree height, especially for taller trees. DBH bias was minor at 1 cm between methods. Repeated TLS inventories successfully matched an average of 424 tree positions per hectare. While TLS adequately characterizes complex plenter forest structures, we propose enhancing this methodology with personal laser scanning to optimize crown coverage and efficiency and direct volume measurements for increased accuracy of wood volume estimations. Additionally, utilizing 3D point cloud data-derived metrics, such as structural complexity indices, can further enhance plenter forest management.
Private forest owner willingness to mobilise wood from dense, small-diameter tree stands
Forest Policy and Economics
Forests are a source of renewable biomass, and their utilisation will play a vital role in the transition towards a climate-neutral economy. Small-diameter tree management could contribute to this transition via providing renewable biomass for sustainable uses and fostering tree growth towards long-lifecycle bioproducts. The utilisation of small-diameter trees in the EU is still low since new technologies and work models are required to make the operations economically profitable, environmentally sound, and socially attractive. The supply of biomass from small-diameter tree stands is dependent on forest owners with diverse perceptions on their forests and diverse ownership objectives. However, there is scarce research on forest owner perceptions on smalldiameter tree management, which encompasses home consumption, self-active work, and commercial forestry services. A survey in four EU countries was designed to identify the main factors affecting the motivation of forest owners to mobilise biomass from small-diameter stands. Factor and clustering analyses were used to identify four forest owner segments: weakly-engaged traders, well-being seekers, self-active profit-seekers, and well-informed service users. The willingness to utilise biomass from small-diameter tree stands and participate in the market was shaped by forest owner knowledge of forestry, economic and socio-cultural motivations, and sensitivity to service offerings. Forest owner preferences for market participation are heterogenous, and thus different policy implementation approaches are needed and proposed.
Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD)
Remote Sensing of Environment
Obtaining low vegetation data is important in order to quantify the structural characteristics of a forest. Dense three-dimensional (3D) laser scanning data can provide information on the vertical profile of a forest. However, most studies have focused on the dominant and subdominant layers of the forest, while few studies have tried to delineate the low vegetation. To address this issue, we propose a framework for individual tree crown (ITC) segmentation from laser data that focuses on both overstory and understory trees. The framework includes 1) a new algorithm (SSD) for 3D ITC segmentation of dominant trees, by detecting the symmetrical structure of the trees, and 2) removing points of dominant trees and mean shift clustering of the low vegetation. The framework was tested on a boreal forest in Sweden and the performance was compared 1) between plots with different stem density levels, vertical complexities, and tree species composition, and 2) using airborne laser scanning (ALS) data, terrestrial laser scanning (TLS) data, and merged ALS and TLS data (ALS + TLS data). The proposed framework achieved detection rates of 0.87 (ALS + TLS), 0.86 (TLS), and 0.76 (ALS) when validated with fieldinventory data (of trees with a diameter at breast height ≥ 4 cm). When validating the estimated number of understory trees by visual interpretation, the framework achieved 19%, 21%, and 39% root-mean-square error values with ALS + TLS, TLS, and ALS data, respectively. These results show that the SSD algorithm can successfully separate laser points of overstory and understory trees, ensuring the detection and segmentation of low vegetation in forest. The proposed framework can be used with both ALS and TLS data, and achieve ITC segmentation for forests with various structural attributes. The results also illustrate the potential of using ALS data to delineate low vegetation.
An Efficient Parallel Spatial Subdivision Algorithm for Object-Based Parallel Ray Tracing
Parallel ray tracing of complex scenes on multicomputers requires distribution of both computations and scene data to the processors. This is carried out during preprocessing and usually consumes too much time and memory. In this paper, we present an efficient parallel subdivision algorithm to decompose a given scene into rectangular regions adaptively and map the resultant regions to the node processors of a multicomputer. The proposed algorithm uses efficient data structures to find out the splitting planes quickly. Furthermore the mapping of the regions and the objects to the node processors is being performed while parallel spatial subdivision proceeds. The proposed algorithm is implemented on an Intel‘s iPSC/2 hypercube multicomputer and promising results are obtained.
Application of Real-time Positioning Systems to a Forest Stand for Precision Forest Management
Applications of Laserscanning in Forestry
. Introduction
DYNAMIQUE DU BOIS MORT ET IMPACT DES CRUES SUR QUELQUES ESPÈCES RIVERAINES D'UN PETIT FLEUVE CÔTIER MÉDITERRANÉEN « LA MASSANE»
ESTIMATION FOREST COVER MAP WITH FUSION LiDAR AND SENTINEL DATA
With the development of remote sensing technology, the information about the surface and the changes can be determined more precisely and more accurately. In this contex, forest cover density is one of the important froest structural parameter in forest management. This extremely important issue in forest management is determined with the help of various satellite images. A wide variety of satellite images are used for this purpose depending on the study. The forest cover map can be derived from the spectral properties of optical images and also derived from 3D point cloud data such as LiDAR data with high accuracy. In this study, point cloud forest cover map was determined using Sentinel-2 optical image and 3D LiDAR data in Turkey located in the wooded area in the province of Adapazarı. The benefits and shortcomings were revealed in terms of utilization possibilities and forest management in both studies. Then, the values of Forest Index (FI) and Normalized Difference Vegetation Index (NDVI), Enhanged Vegetation Index (EVI), Red Edge Ratio Vegetation Index (RERVI) were calculated and the results were compared in forest area. At the end of the study, user accuracy for forest cover density for LiDAR data and Sentinel data is very high with 76% and 85%.
Intersection of a Line and a Cone
METHODS FOR THE AUTOMATIC GEOMETRIC REGISTRATION OF TERRESTRIAL LASER SCANNER POINT CLOUDS IN FOREST STANDS
A combined analysis of multiple terrestrial laser scanner point clouds recorded from different positions requires a geometric registration of these scans. In most applications of terrestrial laser scanning, artificial tie points, which can be recognized automatically by proprietary scanner software, are placed in the scanning area. In this case, the scan positions have to be chosen in a way that they ensure a clear view to the tie points. These pre-scanning tasks may be often labour-intensive and time-consuming. Therefore, an automatic registration process without pre-assigned artificial tie points is aspired.
Méthodologie de quantification CO2 EcoTree
Pre and Post-logging Carbon Stocks: Case of the Forest Management Unit (Fmu) 08 003
Forest concessions granted to Cameroon are of growing interest for ecological, economic and social management. Despite the efforts made on forest carbon stocks estimates, little information and field data exist on post-logging effects on the carbon footprint. The present study carried out in an annual cutting plate 6-4 (1 167 ha) of the Forest Management Unit 08 003 aim to estimate carbon stocks before and after logging and to establish the carbon footprint. For the estimation of pre-logging biomass, the non-destructive method was used and trees inventory of diameter ≥ 10 cm was carried out in 21 plots of 250 × 20 m. Field measurements (width and length of logging roads, logging gaps and log yards) were made to calculate all the areas and carbon stocks affected by logging operations. Pre-logging carbon stocks were estimated at 202.06 tC/ha. The results from measurements of the different types of forest infrastructure show that logging under a simple management plan contributes to 12.11 % of the degradation of the cutting area (141.3 ha), which corresponds to 12.16 % of forest carbon (28 570. 86 tC). The skid trails represent the principal source of forest degradation (63.58 ha), which corresponds to 12,428.32 tons of carbon impacted. An increase in 71.78 % of carbon stocks in dead organic matter was observed. These results show that the use of sustainable management models and improved logging techniques would significantly reduce the area destroyed and also the carbon stocks.