scholarly journals Analysis of Side-Lap Effect and Characterization of Understory Vegetation Using Full-Waveform ALS

Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 6
Author(s):  
Pablo Crespo-Peremarch
Keyword(s):  
Forest Structure ◽  
Understory Vegetation ◽  
Voxel Size ◽  
Full Waveform ◽  
Pulse Density ◽  
The Mean ◽  
Waveform Lidar ◽  
Full Waveform Lidar ◽  
Structure Properties

Airborne full-waveform LiDAR (ALSFW) is able to register forest structure properties, essential for fire prevention, in more detail than airborne discrete LiDAR (ALSD). However, few studies have analyzed ALSFW methodological parameters (i.e., voxel size and assignation value) due to the complexity and lack of processing tools. In this paper we analyze the influence of the pulse density and ALSFW methodological parameters on the ALSFW metrics, as well as the characterization of understory vegetation through ALSFW. Results show that the influence of pulse density on ALSFW metrics may be modelled and the differences reduced by modifying ALSFW methodological parameters. Additionally, the potential of ALSFW for characterizing the mean height (R2 = 0.949) and volume (R2 = 0.951) of the understory vegetation was also proved.

scholarly journals Processing and analysis of airborne full-waveform laser scanning data for the characterization of forest structure and fuel properties

2020 ◽  
pp. 95
Author(s):  
P. Crespo-Peremarch ◽  
L. A. Ruiz
Keyword(s):  
Forest Structure ◽  
Laser Scanning ◽  
Software Tool ◽  
Understory Vegetation ◽  
Airborne Laser Scanning ◽  
Vegetation Density ◽  
Regression Methods ◽  
Full Waveform ◽  
Airborne Laser ◽  
Pulse Density

<p class="Bodytext">This PhD thesis addresses the development of full-waveform airborne laser scanning (ALS<sub>FW</sub>) processing and analysis methods to characterize the vertical forest structure, in particular the understory vegetation. In this sense, the influence of several factors such as pulse density, voxel parameters (voxel size and assignation value), scan angle at acquisition, radiometric correction and regression methods is analyzed on the extraction of ALS<sub>FW</sub> metric values and on the estimate of forest attributes. Additionally, a new software tool to process ALS<sub>FW</sub> data is presented, which includes new metrics related to understory vegetation. On the other hand, occlusion caused by vegetation in the ALS<sub>FW</sub>, discrete airborne laser scanning (ALS<sub>D</sub>) and terrestrial laser scanning (TLS) signal is characterized along the vertical structure. Finally, understory vegetation density is detected and determined by ALS<sub>FW</sub> data, as well as characterized by using the new proposed metrics.</p>

scholarly journals Characterization of Canopy Layering in Forested Ecosystems Using Full Waveform Lidar

2013 ◽  
Vol 5 (4) ◽  
pp. 2014-2036 ◽  
Author(s):  
Amanda Whitehurst ◽  
Anu Swatantran ◽  
J. Blair ◽  
Michelle Hofton ◽  
Ralph Dubayah
Keyword(s):  
Full Waveform ◽  
Waveform Lidar ◽  
Forested Ecosystems ◽  
Full Waveform Lidar

scholarly journals Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data

2014 ◽  
Vol 23 (2) ◽  
pp. 224 ◽  
Author(s):  
Txomin Hermosilla ◽  
Luis A. Ruiz ◽  
Alexandra N. Kazakova ◽  
Nicholas C. Coops ◽  
L. Monika Moskal
Keyword(s):  
Forest Structure ◽  
Forest Canopy ◽  
Structural Parameters ◽  
Mixed Forest ◽  
Lidar Data ◽  
Full Waveform ◽  
Precise Knowledge ◽  
Small Footprint ◽  
Waveform Lidar ◽  
Full Waveform Lidar

Precise knowledge of fuel conditions is important for predicting fire hazards and simulating fire growth and intensity across the landscape. We present a methodology to retrieve and map forest canopy fuel and other forest structural parameters using small-footprint full-waveform airborne light detection and ranging (LiDAR) data. Full-waveform LiDAR sensors register the complete returned backscattered signal through time and can describe physical properties of the intercepted objects. This study was undertaken in a mixed forest dominated by Douglas-fir, occasionally mixed with other conifers, in north-west Oregon (United States). We extracted two sets of LiDAR metrics using pulse detection and waveform modelling and then constructed several predictive models using forward stepwise multiple linear regression. The resulting models explained ~80% of the variability for many of the canopy fuel and forest structure parameters: aboveground biomass (R2=0.84), quadratic mean diameter (R2=0.82), canopy height (R2=0.79), canopy base height (R2=0.78) and canopy fuel load (R2=0.79). The lowest performing models included basal area (R2=0.76), stand volume (R2=0.73), canopy bulk density (R2=0.67) and stand density index (R2=0.66). Our results indicate that full-waveform LiDAR systems show promise in systematically characterising the structure and canopy fuel loads of forests, which may enable accurate fire behaviour forecasting that in turn supports the development of prevention and planning policies.

scholarly journals Analyzing the role of pulse density and voxelization parameters on full-waveform LiDAR-derived metrics

2018 ◽  
Vol 146 ◽  
pp. 453-464 ◽  
Author(s):  
Pablo Crespo-Peremarch ◽  
Luis Ángel Ruiz ◽  
Ángel Balaguer-Beser ◽  
Javier Estornell
Keyword(s):  
Full Waveform ◽  
Pulse Density ◽  
Waveform Lidar ◽  
Full Waveform Lidar

scholarly journals ANALYSIS OF THE SIDE-LAP EFFECT ON FULL-WAVEFORM LIDAR DATA ACQUISITION FOR THE ESTIMATION OF FOREST STRUCTURE VARIABLES

2016 ◽  
Vol XLI-B8 ◽  
pp. 603-610 ◽  
Author(s):  
P. Crespo-Peremarch ◽  
L. A. Ruiz ◽  
A. Balaguer-Beser ◽  
J. Estornell
Keyword(s):  
Forest Structure ◽  
Canopy Structure ◽  
Wilcoxon Test ◽  
Voxel Size ◽  
Paired Samples ◽  
Full Waveform ◽  
Pulse Density ◽  
Point Density ◽  
Voxel Value ◽  
Two Parameters

LiDAR full-waveform provides a better description of the physical and forest vertical structure properties than discrete LiDAR since it registers the full wave that interacts with the canopy. In this paper, the effect of flight line side-lap is analysed on forest structure and canopy fuel variables estimations. Differences are related to pulse density changes between flight stripe side-lap areas, varying the point density between 2.65&thinsp;m&lt;sup&gt;&minus;2&lt;/sup&gt; and 33.77&thinsp;m&lt;sup&gt;&minus;2&lt;/sup&gt; in our study area. These differences modify metrics extracted from data and therefore variable values estimated from these metrics such as forest stand variables. In order to assess this effect, 64 pairwise samples were selected in adjacent areas with similar canopy structure, but having different point densities. Two parameters were tested and evaluated to minimise this effect: voxel size and voxel value assignation testing maximum, mean, median, mode, percentiles 90 and 95. &lt;br&gt;&lt;br&gt; Student’s t-test or Wilcoxon test were used for the comparison of paired samples. Moreover, the absolute value of standardised paired samples was calculated to quantify dissimilarities. It was concluded that optimizing voxel size and voxel value assignation minimised the effect of point density variations and homogenised full-waveform metrics. Height/median ratio (HTMR) and Vertical distribution ratio (VDR) had the lowest variability between different densities, and Return waveform energy (RWE) reached the best improvement with respect to initial data, being the difference between standardised paired samples 1.28 before and 0.69 after modification.

scholarly journals ANALYSIS OF THE SIDE-LAP EFFECT ON FULL-WAVEFORM LIDAR DATA ACQUISITION FOR THE ESTIMATION OF FOREST STRUCTURE VARIABLES

2016 ◽  
Vol XLI-B8 ◽  
pp. 603-610
Author(s):  
P. Crespo-Peremarch ◽  
L. A. Ruiz ◽  
A. Balaguer-Beser ◽  
J. Estornell
Keyword(s):  
Forest Structure ◽  
Canopy Structure ◽  
Wilcoxon Test ◽  
Voxel Size ◽  
Paired Samples ◽  
Full Waveform ◽  
Pulse Density ◽  
Point Density ◽  
Voxel Value ◽  
Two Parameters

LiDAR full-waveform provides a better description of the physical and forest vertical structure properties than discrete LiDAR since it registers the full wave that interacts with the canopy. In this paper, the effect of flight line side-lap is analysed on forest structure and canopy fuel variables estimations. Differences are related to pulse density changes between flight stripe side-lap areas, varying the point density between 2.65&thinsp;m<sup>&minus;2</sup> and 33.77&thinsp;m<sup>&minus;2</sup> in our study area. These differences modify metrics extracted from data and therefore variable values estimated from these metrics such as forest stand variables. In order to assess this effect, 64 pairwise samples were selected in adjacent areas with similar canopy structure, but having different point densities. Two parameters were tested and evaluated to minimise this effect: voxel size and voxel value assignation testing maximum, mean, median, mode, percentiles 90 and 95. <br><br> Student’s t-test or Wilcoxon test were used for the comparison of paired samples. Moreover, the absolute value of standardised paired samples was calculated to quantify dissimilarities. It was concluded that optimizing voxel size and voxel value assignation minimised the effect of point density variations and homogenised full-waveform metrics. Height/median ratio (HTMR) and Vertical distribution ratio (VDR) had the lowest variability between different densities, and Return waveform energy (RWE) reached the best improvement with respect to initial data, being the difference between standardised paired samples 1.28 before and 0.69 after modification.

scholarly journals A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation

2021 ◽  
Vol 13 (4) ◽  
pp. 559
Author(s):  
Milto Miltiadou ◽  
Neill D. F. Campbell ◽  
Darren Cosker ◽  
Michael G. Grant
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Airborne Lidar ◽  
Memory Allocation ◽  
Lidar Data ◽  
Full Waveform ◽  
Waveform Lidar ◽  
Airborne Lidar Data ◽  
Full Waveform Lidar ◽  
Polygonal Model

In this paper, we investigate the performance of six data structures for managing voxelised full-waveform airborne LiDAR data during 3D polygonal model creation. While full-waveform LiDAR data has been available for over a decade, extraction of peak points is the most widely used approach of interpreting them. The increased information stored within the waveform data makes interpretation and handling difficult. It is, therefore, important to research which data structures are more appropriate for storing and interpreting the data. In this paper, we investigate the performance of six data structures while voxelising and interpreting full-waveform LiDAR data for 3D polygonal model creation. The data structures are tested in terms of time efficiency and memory consumption during run-time and are the following: (1) 1D-Array that guarantees coherent memory allocation, (2) Voxel Hashing, which uses a hash table for storing the intensity values (3) Octree (4) Integral Volumes that allows finding the sum of any cuboid area in constant time, (5) Octree Max/Min, which is an upgraded octree and (6) Integral Octree, which is proposed here and it is an attempt to combine the benefits of octrees and Integral Volumes. In this paper, it is shown that Integral Volumes is the more time efficient data structure but it requires the most memory allocation. Furthermore, 1D-Array and Integral Volumes require the allocation of coherent space in memory including the empty voxels, while Voxel Hashing and the octree related data structures do not require to allocate memory for empty voxels. These data structures, therefore, and as shown in the test conducted, allocate less memory. To sum up, there is a need to investigate how the LiDAR data are stored in memory. Each tested data structure has different benefits and downsides; therefore, each application should be examined individually.

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