scholarly journals FOREST STEM VOLUME CALCULATION USING AIRBORNE LIDAR DATA

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 265-270
Author(s):  
I. Büyüksalih ◽  
S. Bayburt ◽  
M. Schardt ◽  
G. Büyüksalih
Keyword(s):  
Near Infrared ◽  
Tree Height ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Allometric Functions ◽  
Airborne Lidar Data ◽  
The City ◽  
Field Plots

Airborne LiDAR data have been collected for the city of Istanbul using Riegl laser scanner Q680i with 400&amp;thinsp;kHz and an average flight height of 600&amp;thinsp;m. The flight campaign was performed by a helicopter and covers an area of 5400&amp;thinsp;km<sup>2</sup>. According to a flight speed of 80 knot a point density of more than 16 points/m<sup>2</sup> and a laser footprint size of 30&amp;thinsp;cm could be achieved. As a result of bundle adjustment, in total, approximately 17,000 LAS files with the file size of 500&amp;thinsp;m by 700&amp;thinsp;m have been generated for the whole city. The main object classes Ground, Building, Vegetation (medium, high) were derived from these LAS files using the macros in Terrasolid software. The forest area under investigation is located northwest of the city of Istanbul, main tree species occurring in the test site are pine (pinus pinaster), oak (quercus) and beech (fagus). In total, 120 LAS tiles covering the investigation area have been analysed using the software IMPACT of Joanneum Research Forschungsgesellschaft, Graz, Austria. First of all, the digital terrain model (DTM) and the digital surface models (DSM) were imported and converted into a raster file from the original laser point clouds with a spatial resolution of 50&amp;thinsp;cm. Then, a normalized digital surface model (nDSM) was derived as the difference between DSM and the DTM. Tree top detection was performed by multi – resolution filter operations and tree crowns were segmented by a region growing algorithms develop specifically for this purpose. Breast Height Diameter (BHD) was calculated on the base of tree height and crown areas derived from image segmentation applying allometric functions found in literature. The assessment of stem volume was then calculated as a function of tree height and BHD. A comparison of timber volume estimated from the LiDAR data and field plots measured by the Forest Department of Istanbul showed R2 of 0.46. The low correlation might arise either from the low quality of the field plots or from the inadequacy of the allometric functions used for BHD and stem volume modelling. Further investigations therefore will concentrate both on improving the quality of field measurements and the adoption of the allometric functions to the specific site condition of the forests under investigation. Finally stand boundaries of the forest area made available by the forest department of Istanbul were superimposed to the LiDAR data and the single tree measurements aggregated to the stand level. <br><br> Aside from the LiDAR data, a Pleiades multispectral image characterized by four spectral bands (blue, green, red and near infrared) and a GSD of 2.8&amp;thinsp;m has been used for the classification of different tree species. For this purpose the near infrared band covering the spectral range of 0.75&amp;thinsp;μm to 0.90&amp;thinsp;μm has been utilized and the IMPACT software used.

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.

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

2017 ◽  
Vol 07 (02) ◽  
pp. 255-269 ◽  
Author(s):  
Faith Kagwiria Mutwiri ◽  
Patroba Achola Odera ◽  
Mwangi James Kinyanjui
Keyword(s):  
Forest Biomass ◽  
Tree Height ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals ACCURACY ASSESSMENT OF LIDAR-DERIVED DIGITAL TERRAIN MODEL (DTM) WITH DIFFERENT SLOPE AND CANOPY COVER IN TROPICAL FOREST REGION

2015 ◽  
Vol II-2/W2 ◽  
pp. 183-189 ◽  
Author(s):  
M. R. M. Salleh ◽  
Z. Ismail ◽  
M. Z. A. Rahman
Keyword(s):  
Tropical Forest ◽  
Digital Terrain Model ◽  
Canopy Cover ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Terrain Slope ◽  
Airborne Lidar Data

Airborne Light Detection and Ranging (LiDAR) technology has been widely used recent years especially in generating high accuracy of Digital Terrain Model (DTM). High density and good quality of airborne LiDAR data promises a high quality of DTM. This study focussing on the analysing the error associated with the density of vegetation cover (canopy cover) and terrain slope in a LiDAR derived-DTM value in a tropical forest environment in Bentong, State of Pahang, Malaysia. Airborne LiDAR data were collected can be consider as low density captured by Reigl system mounted on an aircraft. The ground filtering procedure use adaptive triangulation irregular network (ATIN) algorithm technique in producing ground points. Next, the ground control points (GCPs) used in generating the reference DTM and these DTM was used for slope classification and the point clouds belong to non-ground are then used in determining the relative percentage of canopy cover. The results show that terrain slope has high correlation for both study area (0.993 and 0.870) with the RMSE of the LiDAR-derived DTM. This is similar to canopy cover where high value of correlation (0.989 and 0.924) obtained. This indicates that the accuracy of airborne LiDAR-derived DTM is significantly affected by terrain slope and canopy caver of study area.

Accuracy Assessment of LIDAR-Derived Elevation Value Over Vegetated Terrain in Tropical Region

2015 ◽  
Vol 73 (5) ◽  
Author(s):  
Zamri Ismail ◽  
Muhammad Zulkarnain Abdul Rahman ◽  
Mohd Radhie Mohd Salleh ◽  
Abdul Razak Mohd Yusof
Keyword(s):  
Mixed Forest ◽  
Reference Points ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Understorey Vegetation ◽  
Crown Cover ◽  
Class 1 ◽  
Airborne Lidar Data ◽  
Slope Class

Airborne LiDAR has been widely used to generate good quality of Digital Terrain Model (DTM). Normally, good quality of DTM would require high density and quality of airborne LiDAR data acquisition which increase the cost and processing time. This study focuses on investigating the capability of low density airborne LiDAR data captured by the Riegl system mounted on an aircraft. The LiDAR data sampling densities is about 2.2 points per m2. The study area is covered by rubber trees with moderately dense understorey vegetation and mixed forest. The ground filtering procedure employs the adaptive triangulation irregular network (ATIN) technique. A reference DTM is generated using 76 ground reference points collected using total station. Based on this DTM the study area is divided into different classes of terrain slopes. The point clouds belong to non-terrain features are then used to calculate the relative percentage of crown cover. The overall root mean square error (RMSE) of elevation values obtained from airborne LiDAR data is 0.611 m. The slope of the study area is divided into class-1 (0-5 degrees), class-2 (5-10 degrees), class-3 (10-15 degrees) and class-4 (15-20 degrees). The results show that the slope class has high correlation (0.916) with the RMSE of the LiDAR ground points. The percentage of crown cover is divided into class-1 (60-70%), class-2 (70-80%), class-3 (80-90%) and class-4 (90-100%). The correlation between percentage of crown cover and RMSE of the LiDAR ground points is slightly lower than the slope class with the correlation coefficient of 0.663.

scholarly journals Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data

Sensors ◽  
2010 ◽  
Vol 11 (1) ◽  
pp. 278-295 ◽  
Author(s):  
Andreas Jochem ◽  
Markus Hollaus ◽  
Martin Rutzinger ◽  
Bernhard Höfle
Keyword(s):  
Empirical Model ◽  
Forest Inventory ◽  
Volume Estimation ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Inventory Data ◽  
Forest Inventory Data ◽  
Semi Empirical ◽  
Airborne Lidar Data

In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB) estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can be measured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA) is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71) in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation.

scholarly journals Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data

2014 ◽  
Vol 6 (8) ◽  
pp. 7592-7609 ◽  
Author(s):  
Hanieh Saremi ◽  
Lalit Kumar ◽  
Christine Stone ◽  
Gavin Melville ◽  
Russell Turner
Keyword(s):  
Pinus Radiata ◽  
Tree Height ◽  
Airborne Lidar ◽  
Stem Diameter ◽  
Lidar Data ◽  
Airborne Lidar Data

scholarly journals A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data

2016 ◽  
Vol 89 (4) ◽  
pp. 422-433 ◽  
Author(s):  
Carlos Alberto Silva ◽  
Carine Klauberg ◽  
Andrew T. Hudak ◽  
Lee A. Vierling ◽  
Veraldo Liesenberg ◽  
...  
Keyword(s):  
Principal Component ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Eucalyptus Plantations ◽  
Principal Component Approach ◽  
Component Approach ◽  
Airborne Lidar Data

Tracking tree mortality across sites with repeat LiDAR data

2021 ◽  
Author(s):  
Toby Jackson ◽  
Matheus Nunes ◽  
Grégoire Vincent ◽  
David Coomes
Keyword(s):  
Forest Structure ◽  
Tree Mortality ◽  
Mortality Rates ◽  
Landscape Scale ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Forest Types ◽  
Large Tree ◽  
Airborne Lidar Data ◽  
Field Plots

&lt;p&gt;Repeat airborne LiDAR data provides a unique opportunity to study tree mortality at the landscape scale. We use maps of canopy height derived from repeat LiDAR (two or more scans collected a few years apart) to detect changes in forest structure. Visually, the most obvious changes are caused by large treefall events, which are difficult to study using field plots due to their rarity. While repeat LiDAR data provides exciting new possibilities, validation is a challenge, since we cannot easily determine how many trees have died and we may miss trees which are dead but still standing. I will discuss our progress so far, studying large-tree mortality rates across multiple countries and forest types.&lt;/p&gt;

scholarly journals Assessing Alluvial Fan of Bergama Using High Resolution DEM Generated from Airborne LiDAR Data

2020 ◽  
Author(s):  
Beycan Hocaoğlu ◽  
Müge Ağca
Keyword(s):  
High Resolution ◽  
Flood Plain ◽  
Alluvial Fan ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Morphological Process ◽  
Digital Elevation ◽  
Geomorphological Evolution ◽  
Airborne Lidar Data ◽  
The City

Topography represented by high resolution digital elevation models are able to inform past and present morphological process on the terrain. High resolution LiDAR data taken by the General Directorate of Map at the surroundings of the Bergama city shows great opportunities to understand the morphological process on alluvial fan on which the city is located and the flood plain of Bakır&ccedil;ay river near the alluvial fan. In this paper the LiDAR data collected in 2015 have been used to create DEM&rsquo;s to understand the geomorphological evolution of the alluvial fan and the flood plain around it. Since the proximal roots and medial parts of the alluvial fan have been the scene for a long human settlement most topographical traces of the morphological process have been distorted. Nevertheless, the traces of past and present morphological process at the distal fan which consist the contact zone with the flood plain are very clear on the DEM created from LiDAR data. The levees and some old courses of Bergama and Bakır&ccedil;ay rivers have been shown on the maps which are also important to understand the ancient roads which follows these levees.

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