Influence of Scan Density on the Estimation of Single-Tree Attributes by Hand-Held Mobile Laser Scanning

Nowadays, forest inventories are frequently carried out using a combination of field measurements and remote sensing data, often acquired with light detection and ranging (LiDAR) sensors. Several studies have investigated how three-dimensional laser scanning point clouds from different platforms can be used to acquire information traditionally collected with forest instruments, such as hypsometers and callipers to detect single-tree attributes like tree height and diameter at the breast height. The present study has tested the performances of the ZEB1 instrument, a type of hand-held mobile laser scanner, for single-tree attributes estimation in pure Castanea sativa Mill. stands cultivated for fruit production in Central Italy. In particular, the influence of walking scan path density on single-tree attributes estimation (number of trees, tree position, diameter at breast height, tree height, and crown base height) was investigated to test the efficiency of field measures. The point clouds were acquired by walking along straight lines drawn with different spacing: 10 and 15 m apart. A single-tree scan approach, which included walking with the instrument around each tree, was used as reference data. In order to evaluate the efficiency of the survey, the influence of the walking scan path was discussed in relation to the accuracy of single-tree attributes estimation, as well as the time and cost needed for data acquisition, pre-processing, and analysis. Our results show that the 10 m scan path provided the best results, with an omission error of 6%; the assessment of single-tree attributes was successful, with values of the coefficient of determination and the relative root mean square error similar to other studies. The 10 m scan path has also proved to decrease the costs by about €14 for data pre-processing, and a saving of time for data acquisition and data analysis of about 37 min compared to the reference data.

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A new drone laser scanning benchmark dataset for characterization of single-tree and forest biophysical properties

10.5194/egusphere-egu21-10677 ◽

2021 ◽

Author(s):

Puliti Stefano ◽

Grant D. Pears ◽

Michael S. Watt ◽

Edward Mitchard ◽

Iain McNicol ◽

...

Keyword(s):

Boreal Forests ◽

Laser Scanning ◽

Method Development ◽

Three Dimensional ◽

Point Clouds ◽

Benchmark Dataset ◽

Validation Dataset ◽

Tree Structures ◽

Single Tree ◽

Individual Trees

Survey-grade drone laser scanners suitable for unmanned aerial vehicles (UAV-LS) allow the efficient collection of finely detailed three-dimensional information of tree structures. This data type allows forests to be resolved into discrete individual trees and has shown promising results in providing accurate in-situ observations of key forestry variables. New and improved approaches for analyzing UAV-LS point clouds have to be developed to transform the vast amounts of data from UAV-LS into actionable insights and decision support. Many different studies have explored various methods for automating single tree detection, segmentation, parsing into different tree components, and measurement of biophysical variables (e.g., diameter at breast height). Despite the considerable efforts dedicated to developing automated ways to process UAV-LS data into useful data, current methods tend to be tailored to small datasets, and it remains challenging to evaluate the performance of different algorithms based on a consistent validation dataset. To fill this knowledge gap and to further advance our ability to measure forests from UAV-LS data, we present a new benchmarking dataset. This data is composed of manually labelled UAV-LS data acquired a number of continents and biomes which span tropical to boreal forests. The UAV-LS data was collected exclusively used survey-grade sensors such as the Riegl VUX and mini-VUX series which are characterized by a point density in the range&#160;1 &#8211; 10 k points m2. Currently, such data represent the state-of-the-art in aerial laser scanning data. The benchmark data consists of a library of single-tree point clouds, aggregated to sample plots, with each point classified as either stem, branch, or leaves. With the objective of releasing such a benchmark dataset as a public asset, in the future, researchers will be able to leverage such pre-existing labelled trees for developing new methods to measure forests from UAV-LS data. The availability of benchmarking datasets represents an important driver for enabling the development of robust and accurate methods. Such a benchmarking dataset will also be important for a consistent comparison of existing or future algorithms which will guide future method development.

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Single-tree Equations for Estimating Biomass of Trembling Aspen, Large Tooth Aspen and White Birch in Ontario

The Forestry Chronicle ◽

10.5558/tfc57169-4 ◽

1981 ◽

Vol 57 (4) ◽

pp. 169-173 ◽

Cited By ~ 12

Author(s):

I. S. Alemdag ◽

K. W. Horton

Keyword(s):

New York ◽

Tree Height ◽

Stem Bark ◽

Trembling Aspen ◽

White Birch ◽

Stem Wood ◽

Single Tree ◽

Breast Height ◽

Forest Regions ◽

Whole Tree

Ovendry mass of single trees of trembling aspen, largetooth aspen, and white birch in the Great Lakes — St. Lawrence and Boreal forest regions in Ontario was studied in relation to stem dimensions. Mass equations for tree components based on diameter at breast height outside bark and tree height were developed. Results were found more dependable for stem wood and the whole tree than for stem bark, live branches, and twigs plus leaves. Ovendry mass values were slightly higher than those reported for New York and northern Minnesota.

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Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

Forests ◽

10.3390/f10100905 ◽

2019 ◽

Vol 10 (10) ◽

pp. 905 ◽

Cited By ~ 3

Author(s):

Guerra-Hernández ◽

Cosenza ◽

Cardil ◽

Silva ◽

Botequim ◽

...

Keyword(s):

Laser Scanning ◽

Basal Area ◽

Remote Sensing Data ◽

Tree Height ◽

Point Clouds ◽

Volume Estimation ◽

P Value ◽

Test Statistic ◽

Individual Tree ◽

Significant Difference

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

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Individual Tree Measurement in Tropical Environment using Terrestrial Laser Scanning

Jurnal Teknologi ◽

10.11113/jt.v73.4329 ◽

2015 ◽

Vol 73 (5) ◽

Cited By ~ 1

Author(s):

Muhammad Zulkarnain Abdul Rahman ◽

Zulkepli Majid ◽

Md Afif Abu Bakar ◽

Abd Wahid Rasib ◽

Wan Hazli Wan Kadir

Keyword(s):

Laser Scanning ◽

Mean Squared Error ◽

Tree Height ◽

Point Clouds ◽

Tree Crown ◽

Individual Tree ◽

Branch Diameter ◽

Reference Tree ◽

Crown Volume ◽

Tree Branch

Detailed forest inventory and mensuration of individual trees have drawn attention of research society mainly to support sustainable forest management. This study aims at estimating individual tree attributes from high density point cloud obtained by terrestrial laser scanner (TLS). The point clouds were obtained over single reference tree and group of trees in forest area. The reference tree is treated as benchmark since detailed measurements of branch diameter were made on selected branches with different sizes and locations. Diameter at breast height (DBH) was measured for trees in forest. Furthermore tree height, height to crown base, crown volume and tree branch volume were also estimated for each tree. Branch diameter is estimated directly from the point clouds based on semi-automatic approach of model fitting i.e. sphere, ellipse and cylinder. Tree branch volume is estimated based on the volume of the fitted models. Tree height and height to crown base are computed using histogram analysis of the point clouds elevation. Tree crown volume is estimated by fitting a convex-hull on the tree crown. The results show that the Root Mean Squared Error (RMSE) of the estimated tree branch diameter does not have a specific trend with branch sizes and number of points used for fitting process. This explains complicated distribution of point clouds over the branches. Overall cylinder model produces good results with most branch sizes and number of point clouds for fitting. The cylinder fitting approach shows significantly better estimation results compared to sphere and ellipse fitting models.

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ALGORITHM FOR THE AUTOMATIC ESTIMATION OF AGRICULTURAL TREE GEOMETRIC PARAMETERS USING AIRBORNE LASER SCANNING DATA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-629-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 629-632 ◽

Cited By ~ 1

Author(s):

E. Hadaś ◽

A. Borkowski ◽

J. Estornell

Keyword(s):

Laser Scanning ◽

Tree Height ◽

Field Measurements ◽

Point Clouds ◽

Average Density ◽

Geometric Parameters ◽

Airborne Laser Scanning ◽

Maximum Height ◽

Airborne Laser ◽

Crown Base Height

The estimation of dendrometric parameters has become an important issue for the agricultural planning and management. Since the classical field measurements are time consuming and inefficient, Airborne Laser Scanning (ALS) data can be used for this purpose. Point clouds acquired for orchard areas allow to determine orchard structures and geometric parameters of individual trees. In this research we propose an automatic method that allows to determine geometric parameters of individual olive trees using ALS data. The method is based on the α-shape algorithm applied for normalized point clouds. The algorithm returns polygons representing crown shapes. For points located inside each polygon, we select the maximum height and the minimum height and then we estimate the tree height and the crown base height. We use the first two components of the Principal Component Analysis (PCA) as the estimators for crown diameters. The α-shape algorithm requires to define the radius parameter R. In this study we investigated how sensitive are the results to the radius size, by comparing the results obtained with various settings of the R with reference values of estimated parameters from field measurements. Our study area was the olive orchard located in the Castellon Province, Spain. We used a set of ALS data with an average density of 4 points m<sip>−2. We noticed, that there was a narrow range of the R parameter, from 0.48 m to 0.80 m, for which all trees were detected and for which we obtained a high correlation coefficient (> 0.9) between estimated and measured values. We compared our estimates with field measurements. The RMSE of differences was 0.8 m for the tree height, 0.5 m for the crown base height, 0.6 m and 0.4 m for the longest and shorter crown diameter, respectively. The accuracy obtained with the method is thus sufficient for agricultural applications.

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SIMULATING VARIOUS TERRESTRIAL AND UAV LIDAR SCANNING CONFIGURATIONS FOR UNDERSTORY FOREST STRUCTURE MODELLING

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w4-59-2017 ◽

2017 ◽

Vol IV-2/W4 ◽

pp. 59-65 ◽

Cited By ~ 2

Author(s):

M. Hämmerle ◽

N. Lukač ◽

K.-C. Chen ◽

Zs. Koma ◽

C.-K. Wang ◽

...

Keyword(s):

Laser Scanning ◽

3D Structure ◽

Tree Height ◽

Point Clouds ◽

Understory Vegetation ◽

Forest Plot ◽

Triangle Mesh ◽

Vegetation Modelling ◽

Efficient Planning ◽

Scanning Strategies

Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84&thinsp;m (15.30&thinsp;% of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31&thinsp;m (2.41&thinsp;%). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24&thinsp;m (2.15&thinsp;%). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

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MOBILE INDOOR LASER SCANNING FOR 3D STRATA REGISTRATION PURPOSES BASED ON INDOORGML

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w16-241-2019 ◽

2019 ◽

Vol XLII-4/W16 ◽

pp. 241-245

Author(s):

M. N. Hashim ◽

M. I. Hassan ◽

A. Abdul Rahman

Keyword(s):

Data Acquisition ◽

Web Application ◽

Laser Scanning ◽

Point Clouds ◽

3D Modelling ◽

3D Cadastre ◽

The Right

Abstract. In Malaysia, the current 2D cadastre system is regularly updated by the National Mapping Agency (NMA) and Land Offices (LO). However, this 2D information may not be able to serve complex situations. The 3D strata acquisition and 3D modelling are important for strata title to manage the Right, Restriction and Responsibility (RRRs). This means there is a need for the system to be extended into 3D cadastre environment. One of the data acquisition techniques such as LiDAR from Mobile Laser Scanning (MLS) could be utilised to solve the problem. This research also discusses the 3D geospatial objects generated from the captured point-clouds, modelled in SketchUp and transformed into IndoorGML. In this study, Web application is developed as a platform for generating an integrated XML-IndoorGML schema. Thus, this research contributes on 3D strata modelling especially for the development of 3D strata registration in Malaysia.

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Performance of stem denoising and stem modelling algorithms on single tree point clouds from terrestrial laser scanning

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2017.10.019 ◽

2017 ◽

Vol 143 ◽

pp. 165-176 ◽

Cited By ~ 14

Author(s):

Tiago de Conto ◽

Kenneth Olofsson ◽

Eric Bastos Görgens ◽

Luiz Carlos Estraviz Rodriguez ◽

Gustavo Almeida

Keyword(s):

Laser Scanning ◽

Terrestrial Laser Scanning ◽

Point Clouds ◽

Single Tree

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Evaluation of nonlinear equations for predicting diameter from tree height

Canadian Journal of Forest Research ◽

10.1139/x2012-019 ◽

2012 ◽

Vol 42 (4) ◽

pp. 789-806 ◽

Cited By ~ 18

Author(s):

Huiquan Bi ◽

Julian C. Fox ◽

Yun Li ◽

Yuancai Lei ◽

Yong Pang

Keyword(s):

Prediction Accuracy ◽

Laser Scanning ◽

Large Scale ◽

Inverse Function ◽

Tree Height ◽

Predictive Performance ◽

Systematic Evaluation ◽

Large Area ◽

Individual Tree ◽

Breast Height

With the emergence and advancement of airborne laser scanning technology over the past decade, individual tree height can be easily measured over a large area of forests with a comparable degree of accuracy to conventional ground-based methods. In laser scanning based large-scale forest inventories, the need to predict diameter from remotely sensed tree height calls for a systematic evaluation of equation forms as the first step towards a well-developed approach to developing diameter–height equations. This study evaluated more than 30 height–diameter equations in the forest biometrics literature to select candidates for deriving equation forms for diameter–height equations. The evaluation was based on four criteria: (i) the height–diameter function is inversable; (ii) the inverse function is continuous and monotonically increasing over a specified working range of total tree height; (iii) diameter at breast height is equal to zero when tree height equals breast height in the inverse function; and preferably, (iv) the inverse function has an inflection point that is consistent with biological expectations. A total of 12 candidate equation forms were derived, which included five two-parameter and seven three-parameter equations. The estimation properties and predictive performance of these 12 equation forms were further evaluated and compared through repeated sampling and fitting using data from 3581 trees destructively sampled for taper measurements from Pinus radiata D. Don plantations across New South Wales, Australia. Three equation forms, including the constrained Richards, Weibull, and the combined power and exponential function, displayed superior prediction accuracy and estimation properties and so were recommended as the primary equation forms for developing diameter–height equations. The remaining equation forms were marred by either lower prediction accuracy or poorer estimation properties or both. The three recommended equation forms should only serve as basic deterministic specifications upon which other tree and stand variables should be incorporated as predictors to further improve their predictive performance.

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Analysis of Dynamic Forest Structures Based on Hierarchical Features Extracted from Multi-Station LiDAR Scanning

Environmental Sciences Proceedings ◽

10.3390/iecf2020-07871 ◽

2020 ◽

Vol 3 (1) ◽

pp. 21

Author(s):

Xiuyun Lin ◽

Yulin Gong ◽

Yuan Sun ◽

Jiawen Jiang ◽

Yanli Zhang ◽

...

Keyword(s):

Volume Change ◽

Point Cloud ◽

Laser Scanning ◽

Tree Height ◽

Point Clouds ◽

Dynamic Monitoring ◽

Scanning Method ◽

Volume Model ◽

Liriodendron Chinense ◽

Hierarchical Features

This study aims at searching for characteristic parameters of tree trunks to establish a volume model and dynamic analysis of volume based on terrestrial laser scanning (TLS). We collected three phases of data over 5 years from an artificial Liriodendron chinense forest. The upper diameters of the tree stump and tree height data were obtained by using the multi-station scanning method. A novel hierarchical TLS point cloud feature named the height cumulative percentage (Hz%) was designed. The shape of the upper tree trunk extracted by the point cloud was equivalent to that of the analytical tree with inflection points at 25% and 50% of the height, and the dynamic volume change of the model, which was established by hierarchical features, was highly related to the volume change of the actual point cloud extraction. The obtained results reflected the fact that the Hz% value provided by multi-station scanning was closely related to the characteristic stumpage parameters and could be used to invert the dynamic forest structure. The volume model established based on point cloud hierarchical parameters in this study could be used to monitor the dynamic changes of forest volume and to provide a new reference for applying TLS point clouds for the dynamic monitoring of forest resources.

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