Automated tree detection and crown delineation using airborne laser scanner data in heterogeneous East-Central Europe forest with different species mix

Smreček, Róbert; Sačkov, Ivan; Michňová, Zuzana; Tuček, Ján

doi:10.1007/s11676-017-0378-7

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…ITD algorithms from terrestrial laser scanning (TLS) data are also available [45], but their adaptability and performance with respect to aerial LiDAR data is still unclear. The success of ITD depends on multiple factors, such as the density and the stand configuration [27,[46][47][48], the point density of the LiDAR acquisition [49,50], the foliage condition [51][52][53], and the type of ITD algorithm that is applied (e.g., [30,42]). Research into ITD development is still actively needed to overcome the previously mentioned challenges and limitations.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level

et al. 2021

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UAV laser scanning (ULS) has the potential to support forest operations since it provides high-density data with flexible operational conditions. This study examined the use of ULS systems to estimate several tree attributes from an uneven-aged northern hardwood stand. We investigated: (1) the transferability of raster-based and bottom-up point cloud-based individual tree detection (ITD) algorithms to ULS data; and (2) automated approaches to the retrieval of tree-level (i.e., height, crown diameter (CD), DBH) and stand-level (i.e., tree count, basal area (BA), DBH-distribution) forest inventory attributes. These objectives were studied under leaf-on and leaf-off canopy conditions. Results achieved from ULS data were cross-compared with ALS and TLS to better understand the potential and challenges faced by different laser scanning systems and methodological approaches in hardwood forest environments. The best results that characterized individual trees from ULS data were achieved under leaf-off conditions using a point cloud-based bottom-up ITD. The latter outperformed the raster-based ITD, improving the accuracy of tree detection (from 50% to 71%), crown delineation (from R2 = 0.29 to R2 = 0.61), and prediction of tree DBH (from R2 = 0.36 to R2 = 0.67), when compared with values that were estimated from reference TLS data. Major improvements were observed for the detection of trees in the lower canopy layer (from 9% with raster-based ITD to 51% with point cloud-based ITD) and in the intermediate canopy layer (from 24% with raster-based ITD to 59% with point cloud-based ITD). Under leaf-on conditions, LiDAR data from aerial systems include substantial signal occlusion incurred by the upper canopy. Under these conditions, the raster-based ITD was unable to detect low-level canopy trees (from 5% to 15% of trees detected from lower and intermediate canopy layers, respectively), resulting in a tree detection rate of about 40% for both ULS and ALS data. The cylinder-fitting method used to estimate tree DBH under leaf-off conditions did not meet inventory standards when compared to TLS DBH, resulting in RMSE = 7.4 cm, Bias = 3.1 cm, and R2 = 0.75. Yet, it yielded more accurate estimates of the BA (+3.5%) and DBH-distribution of the stand than did allometric models −12.9%), when compared with in situ field measurements. Results suggest that the use of bottom-up ITD on high-density ULS data from leaf-off hardwood forest leads to promising results when estimating trees and stand attributes, which opens up new possibilities for supporting forest inventories and operations.

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Section: Introductionmentioning

confidence: 99%

Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level

et al. 2021

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On practice of integrated environmental mapping of urban areas taking into account pollution dissemination

Trubina¹,

Nikolaeva²

2020

G&C

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The high level of environment pollution is specific to urbanized territories. The efficient solution of city ecological problems requires considering urban environment as a dynamic system and taking its development over time and space into account. This can be achieved through a complex analysis of time and space dynamics of pollutants in accordance with natural conditions and city infrastructure. The study determines an approach to the environmental assessment of the urbanized territory based on geoinformation analysis and 3D cartographic modelling time and space dynamics of pollutants spreading in the urban environment. The approach to assessing it, taking into account the patterns of pollution dissemination is substantiated. The logical sequence of integrating heterogeneous environmental data for pollution distribution modelling is offered. The digital relief and terrain models of Novosibirsk city are formed. The environmental database of Novosibirsk city is developed. The city area zoning by composite index regarding environmental risk is given. A 3D model of pollution dissemination is developed.

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Parameterization of the Individual Tree Detection Method Using Large Dataset from Ground Sample Plots and Airborne Laser Scanning for Stands Inventory in Coniferous Forest

et al. 2021

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Highly accurate and extensive datasets are needed for the practical implementation of precision forestry as a method of forest ecosystem management. Proper processing of huge datasets involves the necessity of the appropriate selection of methods for their analysis and optimization. In this paper, we propose a concept for and implementation of a data preprocessing algorithm, and a method for the empirical verification of selected individual tree detection (ITD) algorithms, based on Airborne Laser Scanning (ALS) data. In our study, we used ALS data and very extensive dendrometric field measurements (including over 21,000 trees on 522 circular sample plots) in the economic and protective coniferous stands of north-eastern Poland. Our algorithm deals well with the overestimation problems of tree top detection. Furthermore, we analyzed segmentation parameters for the two currently dominant ITD methods: Watershed (WS) and Local Maximum Filter with Growing Region (LMF+GR). We optimized them with respect to minimizing the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Additionally, our results show the crucial importance of the quality of empirical data for the correct evaluation of the accuracy of ITD algorithms.

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Automated tree detection and crown delineation using airborne laser scanner data in heterogeneous East-Central Europe forest with different species mix

Cited by 3 publications

References 17 publications

Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level

Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level

On practice of integrated environmental mapping of urban areas taking into account pollution dissemination

Parameterization of the Individual Tree Detection Method Using Large Dataset from Ground Sample Plots and Airborne Laser Scanning for Stands Inventory in Coniferous Forest

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