Mapping Grey Willow (Salix cinerea) stand architecture using airborne laser scanning: implications for large-scale tree weed control

2017 ◽  
Vol 18 (1) ◽  
pp. 66-70 ◽  
Author(s):  
James W. Griffiths ◽  
Clayson J. Howell ◽  
David Burlace
Keyword(s):  
Weed Control ◽  
Laser Scanning ◽  
Large Scale ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Salix Cinerea

Large-scale prediction of aboveground biomass in heterogeneous mountain forests by means of airborne laser scanning

2016 ◽  
Vol 46 (9) ◽  
pp. 1138-1144 ◽  
Author(s):  
M. Maltamo ◽  
O.M. Bollandsås ◽  
T. Gobakken ◽  
E. Næsset
Keyword(s):  
Aboveground Biomass ◽  
Laser Scanning ◽  
Large Scale ◽  
Airborne Laser Scanning ◽  
Mountain Forests ◽  
Airborne Laser ◽  
Model Predictions ◽  
Growing Conditions ◽  
Southern Norway ◽  
Forest Conditions

This study considered airborne laser scanning (ALS) based aboveground biomass (AGB) prediction in mountain forests. The study area consisted of a long transect from southern Norway to northern parts of the country with wide ranges of elevation along a long latitudinal gradient (58°N–69°N). This transect was covered by ALS data and field data from 238 plots. AGB was modeled using different types of predictor variables, namely ALS metrics, variables related to growing conditions (elevation, latitude, and climatic variables), and tree species information. Modelling of AGB in the long transect covering diverse mountainous forest conditions was challenging: the RMSE values were rather large (37%–70%). The effects of growing conditions on model predictions were minor. However, species information was essential to improve accuracy. The analysis revealed that when doing inventories of spruce-dominated areas, all plots should be pooled together when the models are developed, whereas if pine or deciduous species dominate the area in question, separate dominant species-wise models should be constructed.

scholarly journals ANALYSIS OF 3D BUILDING MODELS ACCURACY BASED ON THE AIRBORNE LASER SCANNING POINT CLOUDS

2018 ◽  
Vol XLII-2 ◽  
pp. 797-804 ◽  
Author(s):  
W. Ostrowski ◽  
M. Pilarska ◽  
J. Charyton ◽  
K. Bakuła
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Statistical Parameters ◽  
Airborne Laser ◽  
Building Models

Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term “3D building models” can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.

Detecting moose (Alces alces) browsing damage in young boreal forests from airborne laser scanning data

2016 ◽  
Vol 46 (1) ◽  
pp. 10-19 ◽  
Author(s):  
M. Melin ◽  
J. Matala ◽  
L. Mehtätalo ◽  
A. Suvanto ◽  
P. Packalen
Keyword(s):  
Boreal Forests ◽  
Laser Scanning ◽  
Large Scale ◽  
Airborne Laser Scanning ◽  
Large Herbivores ◽  
Clear Cut ◽  
Airborne Laser ◽  
Browsing Damage ◽  
The Difference ◽  
Moose Browsing

Large herbivores can have large impacts on their habitats through extensive browsing. Similarly, human actions can have large impacts both on habitats and on the animals utilizing the habitats. In Finland, the increase in clear-cut areas has been highly positive for moose in particular, because these areas provide an easy and abundant source of winter food. For the forest owners, moose browsing causes growth and quality losses or even the destruction of whole stand. We aimed to identify moose browsing damage from airborne laser scanning (ALS) data and to predict damaged areas. The data was used to detect the difference in forest structure caused by moose browsing (lost branches and twigs) in relation to reference areas without moose browsing. The damaged areas were located, measured, and confirmed by forestry professionals, and ALS data was collected after the damage. In the end, the structural differences that browsing caused proved to be clear enough to be detected with metrics calculated from ALS data. Many variables were significantly different between the damage and no-damage areas. With logistic regression, we were able to differentiate the areas with significant, large-scale damage from no-damage areas with a 76% accuracy. However, the model was too keen to predict false-positive cases (classifying no-damage areas as damaged). It was shown that ALS data can be used in detecting moose browsing damage in a case where the damage is extremely severe (like in here). Yet, to make the results more accurate, better field data about the damaged areas would be needed.

scholarly journals Machine Learning Algorithms to Predict Tree-Related Microhabitats using Airborne Laser Scanning

2020 ◽  
Vol 12 (13) ◽  
pp. 2142 ◽  
Author(s):  
Giovanni Santopuoli ◽  
Mirko Di Febbraro ◽  
Mauro Maesano ◽  
Marco Balsi ◽  
Marco Marchetti ◽  
...  
Keyword(s):  
Machine Learning ◽  
Laser Scanning ◽  
Large Scale ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Machine Learning Algorithms ◽  
Hierarchical Level ◽  
Height Distribution ◽  
Airborne Laser ◽  
Crown Density

In the last few years, the occurrence and abundance of tree-related microhabitats and habitat trees have gained great attention across Europe as indicators of forest biodiversity. Nevertheless, observing microhabitats in the field requires time and well-trained staff. For this reason, new efficient semiautomatic systems for their identification and mapping on a large scale are necessary. This study aims at predicting microhabitats in a mixed and multi-layered Mediterranean forest using Airborne Laser Scanning data through the implementation of a Machine Learning algorithm. The study focuses on the identification of LiDAR metrics useful for detecting microhabitats according to the recent hierarchical classification system for Tree-related Microhabitats, from single microhabitats to the habitat trees. The results demonstrate that Airborne Laser Scanning point clouds support the prediction of microhabitat abundance. Better prediction capabilities were obtained at a higher hierarchical level and for some of the single microhabitats, such as epiphytic bryophytes, root buttress cavities, and branch holes. Metrics concerned with tree height distribution and crown density are the most important predictors of microhabitats in a multi-layered forest.

Structure-level fuel load assessment in the wildland–urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

2016 ◽  
Vol 25 (5) ◽  
pp. 547 ◽  
Author(s):  
Nicholas S. Skowronski ◽  
Scott Haag ◽  
Jim Trimble ◽  
Kenneth L. Clark ◽  
Michael R. Gallagher ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Large Scale ◽  
Unit Area ◽  
Airborne Laser Scanning ◽  
Fuel Load ◽  
Spatial Averaging ◽  
Fuel Reduction ◽  
Wildland Urban Interface ◽  
Airborne Laser

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland–urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels in the WUI at the scale of individual structures by integrating aerial photography, airborne laser scanning and cadastral datasets into a hazard assessment framework. This methodology is appropriate for informing zoning policy questions, targeting presuppression planning and fuel reduction treatments, and assisting in prioritising structure defence during suppression operations. Our results show increased variability in fuel loads with decreasing analysis unit area, indicating that fine-scale differences exist that may be omitted owing to spatial averaging when using a coarser, grid-based approach. Analyses using a local parcel database indicate that approximately 75% of the structures in this study have ownership of less than 50% of the 30 m buffer around their building, illustrating the complexity of multiple ownerships when attempting to manage fuels in the WUI. Our results suggest that our remote-sensing approach could augment, and potentially improve, ground-based survey approaches in the WUI.

scholarly journals Airborne laser scanning applied to eucalyptus stand inventory at individual tree level

2018 ◽  
Vol 53 (12) ◽  
pp. 1373-1382 ◽  
Author(s):  
Diogo Nepomuceno Cosenza ◽  
Vicente Paulo Soares ◽  
Helio Garcia Leite ◽  
José Marinaldo Gleriani ◽  
Cibele Hummel do Amaral ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Large Scale ◽  
Tree Height ◽  
Point Clouds ◽  
Equation System ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Individual Tree ◽  
Local Maxima ◽  
Airborne Laser

Abstract: The objective of this work was to evaluate the application of airborne laser scanning (ALS) to a large-scale eucalyptus stand inventory by the method of individual trees, as well as to propose a new method to estimate tree diameter as a function of the height obtained from point clouds. The study was carried out in a forest area of 1,681 ha, consisting of eight eucalyptus stands with ages varying from four to seven years. After scanning, tree heights were obtained using the local maxima algorithm, and total wood stock by summing up individual volumes. To determine tree diameters, regressions fit using data measured in the inventory plots were used. The results were compared with the estimates obtained from field sampling. The equation system proposed is adequate to be applied to the tree height data derived from ALS point clouds. The tree individualization approach by local maxima filters is efficient to estimate number of trees and wood stock from ALS data, as long as the results are previously calibrated with field data.

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