Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data

In this paper, the effects of different LiDAR point density on individual tree parameters including tree height and crown diameter were investigated for the coniferous tree species in the Qilian Mountain area within Gansu province, western China. 10 different density data were acquired in field survey area, with the minimum density of 0.234 points/m2 and the maximum density of 0.6941 points/m2 for per flight. By summing up the different flight data, the different density LIDAR data from 0.234 points/m2 to 5.226 points/m2 for extracting tree height and crown diameter can be analyzed. The result showed that the number of extraction points and the extraction accuracy of tree height and crown width arrived at relative high level in point density of about 2.5 points per m2. When the point density increased, the increased extraction points and the extraction accuracy of tree height and crown width became slow. It means that about 2.5 points per m2 of LiDAR data density may provide relative high accurate individual tree parameters estimation.

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Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

Forest Ecosystems ◽

10.1186/s40663-019-0212-0 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Wuming Zhang ◽

Shangshu Cai ◽

Xinlian Liang ◽

Jie Shao ◽

Ronghai Hu ◽

...

Keyword(s):

Tree Height ◽

Point Clouds ◽

Airborne Lidar ◽

Canopy Height ◽

Lidar Data ◽

Cloth Simulation ◽

Simulation Based ◽

Maximum Tree Height ◽

Airborne Lidar Data ◽

Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

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Investigation of fractal properties of the magnetic survey data array in the Pechenga ore region using two-dimensional wavelet analysis

Russian Geology and Geophysics ◽

10.1016/j.rgg.2017.02.002 ◽

2017 ◽

Vol 58 (9) ◽

pp. 1129-1137

Author(s):

V.A. Lyubchich

Keyword(s):

Wavelet Analysis ◽

Survey Data ◽

Magnetic Survey ◽

Two Dimensional ◽

Data Array ◽

Fractal Properties

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Estimating plot-level tree height and volume of Eucalyptus grandis plantations using small-footprint, discrete return lidar data

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133310365596 ◽

2010 ◽

Vol 34 (4) ◽

pp. 515-540 ◽

Cited By ~ 43

Author(s):

S.G. Tesfamichael ◽

J.A.N. van Aardt ◽

F. Ahmed

Keyword(s):

Eucalyptus Grandis ◽

Tree Height ◽

Mean Value ◽

Primary Objective ◽

Stand Age ◽

Lidar Data ◽

Maximum Height ◽

Density Level ◽

Local Maxima ◽

Small Footprint

This study explores the utility of small-footprint, discrete return lidar data in deriving important forest structural attributes with the primary objective of estimating plot-level mean tree height, dominant height, and volume of Eucalyptus grandis plantations. The secondary objectives of the study were related to investigating the effect of lidar point densities (1 point/m2, 3 points/m2, and 5 points/m2) on height and volume estimates. Tree tops were located by applying local maxima (LM) filtering to canopy height surfaces created at each density level, followed by buffering using circular polygons. Maximum and mean height values of the original lidar points falling within each tree polygon were used to generate lidar mean and dominant heights. Lidar mean value was superior to the maximum lidar value approach in estimating mean plot height (R2∼0.95; RMSE∼7%), while the maximum height approach resulted in superior estimates for dominant plot height (R2 ∼0.95; RMSE∼5%). These observations were similar across all lidar point density levels. Plot-level volume was calculated using approaches based on lidar-derived height variables and stems per hectare, as well as stand age. The level of association between estimated and observed volume was relatively high (R2=0.82—0.94) with non-significant differences among estimates at high lidar point densities and field observation. Nearly all estimates, however, exhibited negative biases and RMSE ranging in the order of 20—43%. Overall, the results of the study demonstrate the potential of lidar-based approaches for forest structural assessment in commercial plantations, even though further research is required on improving stems per hectare (SPHA) estimation.

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Contribution of some Acacia Species on Carbon Sequestration in Blue Nile State, Sudan

10.51527/v2i1.13me ◽

2021 ◽

pp. 97-105

Keyword(s):

Carbon Sequestration ◽

Wood Density ◽

Carbon Stock ◽

Tree Height ◽

Biomass Estimation ◽

Expansion Factor ◽

Wood Volume ◽

Crown Diameter ◽

Breast Height ◽

Acacia Seyal

Background: The current challenge is to reduce the uncertainties in obtaining accurate and reliable data of carbon stock changes and emission factors essential for reporting national inventories. Improvements in above ground biomass estimation can also help account for changes in carbon stock in forest areas that may potentially participate in the Reducing emissions from deforestation and forest degradation and other initiatives. Current objectives for such estimates need a unified approach which can be measurable, reportable, and verifiable. This might result to a geographically referenced biomass density database for Sudanese forests that would reduce uncertainties in estimating forest aboveground biomass. The main objective: of this study is to assess potential of some selected forest variables for modeling carbon sequestration for Acacia seyal, vr. Seyal, Acacia seyal, vr. fistula, Acacia Senegal. The specific objectives include development of empirical allometric models for forest biomass estimation, estimation of carbon sequestration for these tree species, estimation of carbon sequestration per hectare and comparing the amount with that reported to the region. A total of 10 sample trees for biomass and carbon determination were selected for each of the three species from El Nour Natural Forest Reserve of the Blue Nile State, Sudan. Data of diameter at breast height, total tree height, tree crown diameter, crown height, and upper stem diameters were measured. Then sample trees were felled and sectioned to their components, and weighed. Subsamples were selected from each component for oven drying at 105 ˚C. Finally allometric models were developed and the aboveground dry weight (dwt) and carbon sequestered per hector were calculated. The results: presents biomass equations, biomass expansion factor and wood density that developed for the trees. In case of inventoried wood volume, corrections for biomass expansion factor and wood density value were done, and new values are suggested for use to convert wood volume to biomass estimates. The results also, indicate that diameter at breast height, crown diameter and tree height are good predictors for estimation of tree dwt and carbon stock. Conclusion: The developed allometric equations in this study gave better estimation of dwt than default value. The average carbon stock was found to be 22.57 t/ha.

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Estimation of Tree Height and Forest Biomass Using Airborne LiDAR Data: A Case Study of Londiani Forest Block in the Mau Complex, Kenya

Open Journal of Forestry ◽

10.4236/ojf.2017.72016 ◽

2017 ◽

Vol 07 (02) ◽

pp. 255-269 ◽

Cited By ~ 5

Author(s):

Faith Kagwiria Mutwiri ◽

Patroba Achola Odera ◽

Mwangi James Kinyanjui

Keyword(s):

Forest Biomass ◽

Tree Height ◽

Airborne Lidar ◽

Lidar Data ◽

Airborne Lidar Data

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Detecting the Onset of Strain Localization Using Two-Dimensional Wavelet Analysis on Sandstone Deformed at Different Effective Pressures

Journal of Geophysical Research Solid Earth ◽

10.1029/2018jb015898 ◽

2018 ◽

Vol 123 (12) ◽

pp. 10,460-10,478 ◽

Cited By ~ 1

Author(s):

Roberto E. Rizzo ◽

David Healy ◽

Michael J. Heap ◽

Natalie J. Farrell

Keyword(s):

Wavelet Analysis ◽

Strain Localization ◽

Two Dimensional

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Prediction equations for estimating tree height, crown diameter, crown height and crown ratio of Parkia biglobosa in the Nigerian guinea savanna

African Journal of Agricultural Research ◽

10.5897/ajar12.276 ◽

2012 ◽

Vol 7 (49) ◽

pp. 6541-6543 ◽

Cited By ~ 3

Author(s):

Buba Toma

Keyword(s):

Tree Height ◽

Prediction Equations ◽

Parkia Biglobosa ◽

Crown Height ◽

Crown Diameter ◽

Guinea Savanna

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Rectangular Paper Scraps Recovery Based on a New Edge Detection

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.551.691 ◽

2014 ◽

Vol 551 ◽

pp. 691-695

Author(s):

Xin Cao

Keyword(s):

Mathematical Modeling ◽

Wavelet Analysis ◽

Edge Detection ◽

Cutting Conditions ◽

Two Dimensional ◽

Line Spacing ◽

National University ◽

Official Data ◽

Recovery Problem

For the regular rectangular paper scraps recovery problem, at first, I used the edge detection based on the improved wavelet analysis to numerically describe the outline of words on each of the pieces. Secondly, screening according to the line spacing to find out paper scraps which are located in the edge. Thirdly, do initial matching to select the best line as a benchmark for two-dimensional double match splicing. At last, I used two-dimensional double match to make the whole stitching come out. In this paper, the data would use the 2013 China National University Mathematical Modeling Competition topic B official data. The model not only can solve the problem of this article, also can be used to solve the problem of similar cutting conditions.

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