scholarly journals LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest

2020 ◽  
Vol 12 (10) ◽  
pp. 1565 ◽  
Author(s):  
Alexandra Stefanidou ◽  
Ioannis Z. Gitas ◽  
Lauri Korhonen ◽  
Dimitris Stavrakoudis ◽  
Nikos Georgopoulos
Keyword(s):  
Regression Analysis ◽  
Wood Quality ◽  
Fire Behavior ◽  
Forest Health ◽  
Airborne Lidar ◽  
Forest Environment ◽  
Prediction Systems ◽  
Topographic Heterogeneity ◽  
In Fire ◽  
Airborne Lidar Data

Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality and forest health as well as a necessary input in fire behavior prediction systems such as FARSITE, FlamMap and BEHAVE. The present study focused on the potential of airborne LiDAR data analysis to estimate plot-level CBH in a dense uneven-aged structured forest on complex terrain. A comparative study of two widely employed methods was performed, namely the voxel-based approach and regression analysis, which revealed a clear outperformance of the latter. More specifically, the voxel-based CBH estimates were found to lack correlation with the reference data ( R 2 = 0.15 , r R M S E = 42.36 % ) while most CBH values were overestimated resulting in an r b i a s of − 17.52 % . On the contrary, cross-validation of the developed regression model showcased an R 2 , r R M S E and r b i a s of 0 . 61 , 18.19 % and − 0.09 % respectively. Overall analysis of the results proved the voxel-based approach incapable of accurately estimating plot-level CBH due to vegetation and topographic heterogeneity of the forest environment, which however didn’t affect the regression analysis performance.

scholarly journals Comparing the Performance of Ground Filtering Algorithms for Terrain Modeling in a Forest Environment Using Airborne LiDAR Data

2018 ◽  
Vol 25 (2) ◽  
Author(s):  
Carlos Alberto Silva ◽  
Carine Klauberg ◽  
Ângela Maria Klein Hentz ◽  
Ana Paula Dalla Corte ◽  
Uelison Ribeiro ◽  
...  
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Terrain Modeling ◽  
Forest Environment ◽  
Filtering Algorithms ◽  
Airborne Lidar Data

scholarly journals Assessing Legacy Effects of Wildfires on the Crown Structure of Fire-Tolerant Eucalypt Trees Using Airborne Lidar Data

2019 ◽  
Author(s):  
Yogendra K. Karna ◽  
Trent D. Penman ◽  
Cristina Aponte ◽  
Lauren T. Bennett
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Legacy Effects ◽  
Individual Tree ◽  
Tree Crowns ◽  
High Severity ◽  
Eucalypt Forest ◽  
Crown Width ◽  
In Fire ◽  
Airborne Lidar Data

Fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires but surprisingly very few studies have quantitatively assessed that recovery. Accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne lidar data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height, and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate- and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in lidar-based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate- and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites, and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne lidar data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in lidar and other remotely-sensed data at larger scales.

scholarly journals REVISED PROGRESSIVE MORPHOLOGICAL METHOD FOR GROUND POINT CLASSIFICATION OF AIRBORNE LIDAR DATA

2019 ◽  
Vol 6 (1-2) ◽  
pp. 31-38 ◽  
Author(s):  
Mohd Radhie Mohd Salleh ◽  
Muhammad Zulkarnain Abd Rahman ◽  
Zamri Ismail ◽  
Mohd Faisal Abdul Khanan ◽  
Mohd Asraff Asmadi
Keyword(s):  
Survey Data ◽  
Digital Terrain Model ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Major Step ◽  
Forest Environment ◽  
Local Slope ◽  
Filtering Method ◽  
Ground Survey ◽  
Airborne Lidar Data

Airborne Light Detection and Ranging (LiDAR) has been very effectively used in collecting terrain information over different scales of area. Inevitably, filtering the non-ground returns is the major step of digital terrain model (DTM) generation and this step poses the greatest challenge especially for tropical forest environment which consists of steep undulating terrain and mostly covered by a relatively thick canopy density. The aim of this research is to assess the performance of the Progressive Morphological (PM) algorithm after the implementation of local slope value in the ground filtering process. The improvement on the PM filtering method was done by employing local slope values obtained either using initial filtering of airborne LiDAR data or ground survey data. The filtering process has been performed with recursive mode and it stops after the results of the filtering does not show any improvement and the DTM error larger than the previous iteration. The revised PM filtering method has decreasing pattern of DTM error with increasing filtering iterations with minimum ±0.520 m of RMSE value. The results also suggest that spatially distributed slope value applied in PM filtering algorithm either from LiDAR ground points or ground survey data is capable in preserving discontinuities of terrain and correctly remove non-terrain points especially in steep area.

Heat Content Variation of Sierra Nevada Conifers

1998 ◽  
Vol 8 (3) ◽  
pp. 147 ◽  
Author(s):  
JW Van Wagdendonk ◽  
WM Sydoriak ◽  
JM Benedict
Keyword(s):  
Developmental Stage ◽  
Sierra Nevada ◽  
Fire Behavior ◽  
Heat Content ◽  
Behavior Prediction ◽  
Fuel Component ◽  
Standard Values ◽  
Prediction Systems ◽  
Fine Fuels ◽  
In Fire

A study of fuels of Siena Nevada conifer species showed that percent ash content, heat content with ash, and heat content without ash of needle and duff fuels significantly varied by species, fuel component, and developmental stage of the overstory. Ash and heat contents of woody fuels varied by species and fuel component but not by developmental stage. Bark fuels significantly differed by species, while no factor significantly affected cone fuels. Regional variation in ash and heat content was evident but small. However, the values reported here for heat content with ash for fine fuels averaged 2.50 MJ kg-1 higher than the standard values used in fire behavior prediction systems. Using standard values can result in significant under predictions of fireline intensity of an average of 16 percent for all species of up to 47 percent for Pinus albicaulis.

scholarly journals Assessing Legacy Effects of Wildfires on the Crown Structure of Fire-Tolerant Eucalypt Trees Using Airborne LiDAR Data

2019 ◽  
Vol 11 (20) ◽  
pp. 2433 ◽  
Author(s):  
Yogendra K. Karna ◽  
Trent D. Penman ◽  
Cristina Aponte ◽  
Lauren T. Bennett
Keyword(s):  
Airborne Lidar ◽  
Lidar Data ◽  
Legacy Effects ◽  
Individual Tree ◽  
Tree Crowns ◽  
High Severity ◽  
Eucalypt Forest ◽  
Crown Width ◽  
In Fire ◽  
Airborne Lidar Data

The fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires; however, surprisingly, very few studies have quantitatively assessed that recovery. The accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne LiDAR data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in LiDAR -based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne LiDAR data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in Light Detection and Ranging (LiDAR) and other remotely-sensed data at larger scales.

Données LiDAR aériennes: pertinence de l'interprétation visuelle pour la foresterie

2017 ◽  
Vol 168 (3) ◽  
pp. 127-133
Author(s):  
Matthew Parkan
Keyword(s):  
Cross Sections ◽  
Forest Edge ◽  
Airborne Lidar ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Small Areas ◽  
Interactive 3D ◽  
The Individual ◽  
Airborne Lidar Data ◽  
Stem Position

Airborne LiDAR data: relevance of visual interpretation for forestry Airborne LiDAR surveys are particularly well adapted to map, study and manage large forest extents. Products derived from this technology are increasingly used by managers to establish a general diagnosis of the condition of forests. Less common is the use of these products to conduct detailed analyses on small areas; for example creating detailed reference maps like inventories or timber marking to support field operations. In this context, the use of direct visual interpretation is interesting, because it is much easier to implement than automatic algorithms and allows a quick and reliable identification of zonal (e.g. forest edge, deciduous/persistent ratio), structural (stratification) and point (e.g. tree/stem position and height) features. This article examines three important points which determine the relevance of visual interpretation: acquisition parameters, interactive representation and identification of forest characteristics. It is shown that the use of thematic color maps within interactive 3D point cloud and/or cross-sections makes it possible to establish (for all strata) detailed and accurate maps of a parcel at the individual tree scale.

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

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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