scholarly journals Detection of Individual Trees and Estimation of Mean Tree Height using Airborne LIDAR Data

2012 ◽  
Vol 20 (3) ◽  
pp. 27-38
Author(s):  
Se-Ran Hwang ◽  
Mi-Jin Lee ◽  
Im-Pyeong Lee
2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  

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.


2017 ◽  
Vol 07 (02) ◽  
pp. 255-269 ◽  
Author(s):  
Faith Kagwiria Mutwiri ◽  
Patroba Achola Odera ◽  
Mwangi James Kinyanjui

2020 ◽  
Vol 12 (3) ◽  
pp. 571 ◽  
Author(s):  
Chen ◽  
Xiang ◽  
Moriya

Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management.


2019 ◽  
Vol 163 ◽  
pp. 104871 ◽  
Author(s):  
Li Liu ◽  
Samsung Lim ◽  
Xuesong Shen ◽  
Marta Yebra

2014 ◽  
Vol 6 (8) ◽  
pp. 7592-7609 ◽  
Author(s):  
Hanieh Saremi ◽  
Lalit Kumar ◽  
Christine Stone ◽  
Gavin Melville ◽  
Russell Turner

FLORESTA ◽  
2014 ◽  
Vol 44 (2) ◽  
pp. 279 ◽  
Author(s):  
Mauricio Muller ◽  
Ana Paula Baungarten Kersting ◽  
Nelson Yoshihiro Nakajima ◽  
Roberto Tuyoshi Hosokawa ◽  
Nelson Carlos Rosot

AbstractIn the last decades, several studies have been conducted aiming to the extraction of forest variables from LiDAR data. Although such studies have indicated great potential, the high cost associated with LiDAR data acquisition process inhibits the technology to become an operational technique for forestry applications. The cost of a LiDAR survey, as for any other data collection techniques, is composed of fixed and variable costs. The variable portion, which can be optimized, is dependent, among other factors, on the number of flight hours. The flight time is mainly dependent on the flight configuration used for the survey. The objective of this paper is to investigate the impact of using different operational parameters on different species of forest plantations, to provide inputs for an adequate cost-benefit analysis. The different configurations are evaluated in terms of the number of individual trees automatically detected, individual height and volume, using the forest inventory as the reference data. The experiments have shown that compatible results are obtained using different configurations with flight time varying by a factor of 3.5 to 10 times. Also, for a given point density, preference should be given to the configuration based on a lower flying height.Keywords: Airborne LiDAR; remote sensing; progressive densification; forest mensuration; operational parameters; tree height; volume. ResumoInfluência da configuração de voo para aquisição de dados LiDAR na extração de dados de árvores individuais em plantios florestais. Nas últimas décadas, vários estudos têm sido realizados visando à utilização dos dados obtidos através da tecnologia LiDAR (Light Detection And Ranging) na obtenção de variáveis florestais. Embora tais estudos indiquem alto potencial do LiDAR para aplicações florestais, o elevado custo do levantamento dificulta sua operacionalização no meio florestal. O custo de um levantamento LiDAR, como em outros tipos de levantamentos, é composto de custos fixos e variáveis. A parcela de custos variáveis, a qual pode ser otimizada, encontra-se associada, dentre outros fatores, ao número de horas de voo. O tempo de voo depende principalmente da configuração de voo utilizada no levantamento. Este artigo visa analisar a influência da utilização de diferentes parâmetros operacionais para diferentes espécies de plantios florestais, objetivando prover insumos para uma adequada análise custo-benefício. As configurações são avaliadas em termos do número de árvores automaticamente identificadas, altura individual e volume, tendo como referência os dados do inventário florestal. Os experimentos realizados demonstraram que resultados comparáveis são obtidos com a utilização de diferentes configurações com tempo de voo variando de um fator de 3,5 a 10 vezes. Observou-se também que para uma dada densidade de pontos deve-se dar preferência à configuração que utilize menor altura de voo.Palavras-chave:      Laser scanner; sensoriamento remoto; parâmetros operacionais; altura; volume.


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