scholarly journals A study of the generalization of the stand volume estimation method based on airborne LiDAR using models of spatial volume and stem volume －A case study of Sugi and Hinoki in Gifu prefecture－

2017 ◽  
Vol 56 (3) ◽  
pp. 70-80
Author(s):  
Kiyoshi TAKEJIMA
Keyword(s):  
Estimation Method ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Stand Volume ◽  
Spatial Volume ◽  
Gifu Prefecture

scholarly journals Height Extraction and Stand Volume Estimation Based on Fusion Airborne LiDAR Data and Terrestrial Measurements for a Norway Spruce [Picea abies (L.) Karst.] Test Site in Romania

2016 ◽  
Vol 44 (1) ◽  
pp. 313-323 ◽  
Author(s):  
Bogdan APOSTOL ◽  
Adrian LORENT ◽  
Marius PETRILA ◽  
Vladimir GANCZ ◽  
Ovidiu BADEA
Keyword(s):  
Picea Abies ◽  
Norway Spruce ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Individual Tree ◽  
Stand Volume ◽  
Empirical Modelling ◽  
The Individual

The objective of this study was to analyze the efficiency of individual tree identification and stand volume estimation from LiDAR data. The study was located in Norway spruce [Picea abies (L.) Karst.] stands in southwestern Romania and linked airborne laser scanning (ALS) with terrestrial measurements through empirical modelling. The proposed method uses the Canopy Maxima algorithm for individual tree detection together with biometric field measurements and individual trees positioning. Field data was collected using Field-Map real-time GIS-laser equipment, a high-accuracy GNSS receiver and a Vertex IV ultrasound inclinometer. ALS data were collected using a Riegl LMS-Q560 instrument and processed using LP360 and Fusion software to extract digital terrain, surface and canopy height models. For the estimation of tree heights, number of trees and tree crown widths from the ALS data, the Canopy Maxima algorithm was used together with local regression equations relating field-measured tree heights and crown widths at each plot. When compared to LiDAR detected trees, about 40-61% of the field-measured trees were correctly identified. Such trees represented, in general, predominant, dominant and co-dominant trees from the upper canopy. However, it should be noted that the volume of the correctly identified trees represented 60-78% of the total plot volume. The estimation of stand volume using the LiDAR data was achieved by empirical modelling, taking into account the individual tree heights (as identified from the ALS data) and the corresponding ground reference stem volume. The root mean square error (RMSE) between the individual tree heights measured in the field and the corresponding heights identified in the ALS data was 1.7-2.2 meters. Comparing the ground reference estimated stem volume (at trees level) with the corresponding ALS estimated tree stem volume, an RMSE of 0.5-0.7 m3 was achieved. The RMSE was slightly lower when comparing the ground reference stem volume at plot level with the ALS-estimated one, taking into account both the identified and unidentified trees in the LiDAR data (0.4-0.6 m3).

scholarly journals Mining Waste Volume Estimation Using Airborne Lidar Data and Historical Maps: A Case Study of Tailing Piles in Szklary, Lower Silesia

2021 ◽  
Vol 9 (1) ◽  
pp. 32
Author(s):  
Paweł Trybała ◽  
Wojciech Kaczan ◽  
Adam Górecki
Keyword(s):  
Mining Waste ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Novel Method ◽  
The Difference ◽  
Airborne Lidar Data ◽  
Waste Deposit ◽  
Lower Silesia ◽  
Potential Exploitation

Reliable feasibility analysis of potential exploitation of a mining waste deposit poses a great challenge. One of the most crucial parts of this process is the approximation of the deposit volume. In this case study we propose a novel method of tailing pile volume estimation using open remote sensing and cartographic data. For selected piles, the difference between the proposed and classical approach reach 50% of the pile volume, which is a significant change in the potential value of the deposit.

scholarly journals Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data

Sensors ◽  
2010 ◽  
Vol 11 (1) ◽  
pp. 278-295 ◽  
Author(s):  
Andreas Jochem ◽  
Markus Hollaus ◽  
Martin Rutzinger ◽  
Bernhard Höfle
Keyword(s):  
Empirical Model ◽  
Forest Inventory ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Inventory Data ◽  
Forest Inventory Data ◽  
Semi Empirical ◽  
Airborne Lidar Data

In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB) estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can be measured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA) is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71) in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation.

scholarly journals Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches

2020 ◽  
Vol 12 (9) ◽  
pp. 1513 ◽  
Author(s):  
Rodrigo Vieira Leite ◽  
Cibele Hummel do Amaral ◽  
Raul de Paula Pires ◽  
Carlos Alberto Silva ◽  
Carlos Pedro Boechat Soares ◽  
...  
Keyword(s):  
Volume Estimation ◽  
Airborne Lidar ◽  
Estimation Methods ◽  
Southeastern Brazil ◽  
Stem Volume ◽  
Stand Age ◽  
Support Vector ◽  
Accurate Information ◽  
Forest Plantations ◽  
Individual Tree

Forest plantations are globally important for the economy and are significant for carbon sequestration. Properly managing plantations requires accurate information about stand timber stocks. In this study, we used the area (ABA) and individual tree (ITD) based approaches for estimating stem volume in fast-growing Eucalyptus spp forest plantations. Herein, we propose a new method to improve individual tree detection (ITD) in dense canopy homogeneous forests and assess the effects of stand age, slope and scan angle on ITD accuracy. Field and Light Detection and Ranging (LiDAR) data were collected in Eucalyptus urophylla x Eucalyptus grandis even-aged forest stands located in the mountainous region of the Rio Doce Valley, southeastern Brazil. We tested five methods to estimate volume from LiDAR-derived metrics using ABA: Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), and linear and Gompertz models. LiDAR-derived canopy metrics were selected using the Recursive Feature Elimination algorithm and Spearman’s correlation, for nonparametric and parametric methods, respectively. For the ITD, we tested three ITD methods: two local maxima filters and the watershed method. All methods were tested adding our proposed procedure of Tree Buffer Exclusion (TBE), resulting in 35 possibilities for treetop detection. Stem volume for this approach was estimated using the Schumacher and Hall model. Estimated volumes in both ABA and ITD approaches were compared to the field observed values using the F-test. Overall, the ABA with ANN was found to be better for stand volume estimation ( r y y ^ = 0.95 and RMSE = 14.4%). Although the ITD results showed similar precision ( r y y ^ = 0.94 and RMSE = 16.4%) to the ABA, the results underestimated stem volume in younger stands and in gently sloping terrain (<25%). Stem volume maps also differed between the approaches; ITD represented the stand variability better. In addition, we discuss the importance of LiDAR metrics as input variables for stem volume estimation methods and the possible issues related to the ABA and ITD performance.

scholarly journals MATLAB Virtual Toolbox for Retrospective Rockfall Source Detection and Volume Estimation Using 3D Point Clouds: A Case Study of a Subalpine Molasse Cliff

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 75
Author(s):  
Dario Carrea ◽  
Antonio Abellan ◽  
Marc-Henri Derron ◽  
Neal Gauvin ◽  
Michel Jaboyedoff
Keyword(s):  
Point Cloud ◽  
Natural Hazard ◽  
Point Clouds ◽  
Volume Estimation ◽  
Natural Phenomena ◽  
Frequency Distributions ◽  
Erosion Rates ◽  
3D Point Clouds

The use of 3D point clouds to improve the understanding of natural phenomena is currently applied in natural hazard investigations, including the quantification of rockfall activity. However, 3D point cloud treatment is typically accomplished using nondedicated (and not optimal) software. To fill this gap, we present an open-source, specific rockfall package in an object-oriented toolbox developed in the MATLAB® environment. The proposed package offers a complete and semiautomatic 3D solution that spans from extraction to identification and volume estimations of rockfall sources using state-of-the-art methods and newly implemented algorithms. To illustrate the capabilities of this package, we acquired a series of high-quality point clouds in a pilot study area referred to as the La Cornalle cliff (West Switzerland), obtained robust volume estimations at different volumetric scales, and derived rockfall magnitude–frequency distributions, which assisted in the assessment of rockfall activity and long-term erosion rates. An outcome of the case study shows the influence of the volume computation on the magnitude–frequency distribution and ensuing erosion process interpretation.

Variance reduction in Ueno's method and cylinder sampling for forest volume estimation

1995 ◽  
Vol 25 (11) ◽  
pp. 1783-1794 ◽  
Author(s):  
Thomas B. Lynch
Keyword(s):  
Computer Simulation ◽  
Variance Reduction ◽  
Volume Estimation ◽  
Critical Height ◽  
Volume Estimate ◽  
Individual Tree ◽  
Stand Volume ◽  
Reduction Techniques ◽  
Antithetic Variates ◽  
Volume Equation

Three basic techniques are proposed for reducing the variance of the stand volume estimate provided by cylinder sampling and Ueno's method. Ueno's method is based on critical height sampling but does not require measurement of critical heights. Instead, a count of trees whose critical heights are less than randomly generated heights is used to estimate stand volume. Cylinder sampling selects sample trees for which randomly generated heights fall within cylinders formed by tree heights and point sampling plot sizes. The methods proposed here for variance reduction in cylinder sampling and Ueno's method are antithetic variates, importance sampling, and control variates. Cylinder sampling without variance reduction was the most efficient of 12 methods compared in computer simulation that used estimated measurement times. However, cylinder sampling requires knowledge of a combined variable individual tree volume equation. Of the three variance reduction techniques applied to Ueno's method, antithetic variates performed best in computer simulation.

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