scholarly journals Tree Density and Forest Productivity in a Heterogeneous Alpine Environment: Insights from Airborne Laser Scanning and Imaging Spectroscopy

Forests ◽  
2017 ◽  
Vol 8 (6) ◽  
pp. 212 ◽  
Author(s):  
Parviz Fatehi ◽  
Alexander Damm ◽  
Reik Leiterer ◽  
Mahtab Pir Bavaghar ◽  
Michael Schaepman ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Imaging Spectroscopy ◽  
Forest Productivity ◽  
Tree Density ◽  
Airborne Laser Scanning ◽  
Alpine Environment ◽  
Airborne Laser

scholarly journals Using Leaf-Off and Leaf-On Multispectral Airborne Laser Scanning Data to Characterize Seedling Stands

2020 ◽  
Vol 12 (20) ◽  
pp. 3328
Author(s):  
Mohammad Imangholiloo ◽  
Ninni Saarinen ◽  
Markus Holopainen ◽  
Xiaowei Yu ◽  
Juha Hyyppä ◽  
...  
Keyword(s):  
Tree Species ◽  
Laser Scanning ◽  
Sustainable Forest Management ◽  
Single Channel ◽  
Point Clouds ◽  
Tree Density ◽  
Airborne Laser Scanning ◽  
Tree Species Composition ◽  
Coniferous Trees ◽  
Airborne Laser

Information from seedling stands in time and space is essential for sustainable forest management. To fulfil these informational needs with limited resources, remote sensing is seen as an intriguing alternative for forest inventorying. The structure and tree species composition in seedling stands have created challenges for capturing this information using sensors providing sparse point densities that do not have the ability to penetrate canopy gaps or provide spectral information. Therefore, multispectral airborne laser scanning (mALS) systems providing dense point clouds coupled with multispectral intensity data theoretically offer advantages for the characterization of seedling stands. The aim of this study was to investigate the capability of Optech Titan mALS data to characterize seedling stands in leaf-off and leaf-on conditions, as well as to retrieve the most important forest inventory attributes, such as distinguishing deciduous from coniferous trees, and estimating tree density and height. First, single-tree detection approaches were used to derive crown boundaries and tree heights from which forest structural attributes were aggregated for sample plots. To predict tree species, a random forests classifier was trained using features from two single-channel intensities (SCIs) with wavelengths of 1550 (SCI-Ch1) and 1064 nm (SCI-Ch2), and multichannel intensity (MCI) data composed of three mALS channels. The most important and uncorrelated features were analyzed and selected from 208 features. The highest overall accuracies in classification of Norway spruce, birch, and nontree class in leaf-off and leaf-on conditions obtained using SCI-Ch1 and SCI-Ch2 were 87.36% and 69.47%, respectively. The use of MCI data improved classification by up to 96.55% and 92.54% in leaf-off and leaf-on conditions, respectively. Overall, leaf-off data were favorable for distinguishing deciduous from coniferous trees and tree density estimation with a relative root mean square error (RMSE) of 37.9%, whereas leaf-on data provided more accurate height estimations, with a relative RMSE of 10.76%. Determining the canopy threshold for separating ground returns from vegetation returns was found to be critical, as mapped trees might have a height below one meter. The results showed that mALS data provided benefits for characterizing seedling stands compared to single-channel ALS systems.

scholarly journals A two-phase inventory method for calculating standing volume and tree-density of forest stands in central Poland based on airborne laser-scanning data

2013 ◽  
Vol 74 (2) ◽  
pp. 127-136 ◽  
Author(s):  
Stanisław Miścicki ◽  
Krzysztof Stereńczak
Keyword(s):  
Laser Scanning ◽  
Stocking Density ◽  
Strong Relationship ◽  
Tree Density ◽  
Airborne Laser Scanning ◽  
Sample Plot ◽  
Forest Stands ◽  
Two Phase ◽  
Airborne Laser ◽  
Elevation Model

Abstract This paper describes a method of determining the stocking density and volume of forest stands based on airborne laser-scanning data. The aim of this study was to determine the relationship between ground-based measurements of standing volume and tree-density, and those acquired based on the Crown Height Model (CHM) interpolated from airborne laser scanning data. Data were collected from 34 sample plots of two sizes for the CHM analysis: 500 m2 (radius 12.61 m) and 1963.5 m2 (radius of 25.0 m): Trees for sampling were selected using two methods, those whose “centroid” was fully within the sample plot (the tree was considered to be within the sample plots if the centroid of the crown was inside the circle) and those at the “border” (the tree was included in the sample plot if, at least, one part of the contour of the crown was inside the circle). There was a strong relationship (R2 = 0.86) between standing volume measured in sample plots on the ground and the indices produced by the crown elevation model at the locations where the ground-based measurements were performed.

scholarly journals MAPPING LAND COVER IN THE TAITA HILLS, SE KENYA, USING AIRBORNE LASER SCANNING AND IMAGING SPECTROSCOPY DATA FUSION

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1277-1282 ◽  
Author(s):  
R. Piiroinen ◽  
J. Heiskanen ◽  
E. Maeda ◽  
P. Hurskainen ◽  
J. Hietanen ◽  
...  
Keyword(s):  
Land Cover ◽  
Data Fusion ◽  
Laser Scanning ◽  
Structural Parameters ◽  
Imaging Spectroscopy ◽  
Airborne Laser Scanning ◽  
Heterogeneous Landscape ◽  
Airborne Laser ◽  
Taita Hills ◽  
Pulse Density

The Taita Hills, located in south-eastern Kenya, is one of the world’s biodiversity hotspots. Despite the recognized ecological importance of this region, the landscape has been heavily fragmented due to hundreds of years of human activity. Most of the natural vegetation has been converted for agroforestry, croplands and exotic forest plantations, resulting in a very heterogeneous landscape. Given this complex agro-ecological context, characterizing land cover using traditional remote sensing methods is extremely challenging. The objective of this study was to map land cover in a selected area of the Taita Hills using data fusion of airborne laser scanning (ALS) and imaging spectroscopy (IS) data. Land Cover Classification System (LCCS) was used to derive land cover nomenclature, while the height and percentage cover classifiers were used to create objective definitions for the classes. Simultaneous ALS and IS data were acquired over a 10 km × 10 km area in February 2013 of which 1 km × 8 km test site was selected. The ALS data had mean pulse density of 9.6 pulses/m<sup>2</sup>, while the IS data had spatial resolution of 1 m and spectral resolution of 4.5–5 nm in the 400–1000 nm spectral range. Both IS and ALS data were geometrically co-registered and IS data processed to at-surface reflectance. While IS data is suitable for determining land cover types based on their spectral properties, the advantage of ALS data is the derivation of vegetation structural parameters, such as tree height and crown cover, which are crucial in the LCCS nomenclature. Geographic object-based image analysis (GEOBIA) was used for segmentation and classification at two scales. The benefits of GEOBIA and ALS/IS data fusion for characterizing heterogeneous landscape were assessed, and ALS and IS data were considered complementary. GEOBIA was found useful in implementing the LCCS based classification, which would be difficult to map using pixel-based methods.

scholarly journals New Advances in Automated Urban Modelling from Airborne Laser Scanning Data

2011 ◽  
Vol 5 (3) ◽  
pp. 196-208 ◽  
Author(s):  
D. F. Laefer ◽  
T. Hinks ◽  
H. Carr ◽  
L. Truong-Hong
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Airborne Laser ◽  
Urban Modelling

scholarly journals Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Image Data ◽  
Remote Sensing Image ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Detection Rates ◽  
Airborne Laser ◽  
Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

scholarly journals Airborne laser scanning reveals large tree trunks on forest floor

2021 ◽  
Vol 491 ◽  
pp. 119225
Author(s):  
Einari Heinaro ◽  
Topi Tanhuanpää ◽  
Tuomas Yrttimaa ◽  
Markus Holopainen ◽  
Mikko Vastaranta
Keyword(s):  
Forest Floor ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Large Tree ◽  
Airborne Laser
Sign in / Sign up

Export Citation Format

Share Document