scholarly journals Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets

Silva Fennica ◽  
2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Katalin Waga ◽  
Jukka Malinen ◽  
Timo Tokola
Keyword(s):  
Laser Scanning ◽  
Spline Interpolation ◽  
Structural Condition ◽  
Poor Quality ◽  
Airborne Laser Scanning ◽  
Road Maintenance ◽  
Topographic Analysis ◽  
Forest Road ◽  
Airborne Laser ◽  
Pulse Density

Two different pulse density airborne laser scanning datasets were used to develop a quality assessment methodology to determine how airborne laser scanning derived variables with the use of reference surface can determine forest road quality. The concept of a reference DEM (Digital Elevation Model) was used to guarantee locally invariant topographic analysis of road roughness. Structural condition, surface wear and flatness were assessed at two test sites in Eastern Finland, calculating surface indices with and without the reference DEM. The high pulse density dataset (12 pulses m) gave better classification results (77% accuracy of the correctly classified road sections) than the low pulse density dataset (1 pulse m). The use of a reference DEM increased the precision of the road quality classification with the low pulse density dataset when the classification was performed in two-steps. Four interpolation techniques (Inverse Weighted Distance, Kriging, Natural Neighbour and Spline) were compared, and spline interpolation provided the best classification. The work shows that applying a spline reference DEM it is possible to identify 66% of the poor quality road sections and 78% of the good ones. Locating these roads is essential for road maintenance.–2–2

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 Employment, Utilization, and Development of Airborne Laser Scanning in Fenno-Scandinavian Archaeology—A Review

2020 ◽  
Vol 12 (9) ◽  
pp. 1411 ◽  
Author(s):  
Ole Risbøl ◽  
Daniel Langhammer ◽  
Esben Schlosser Mauritsen ◽  
Oula Seitsonen
Keyword(s):  
Research And Development ◽  
Cultural Heritage ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Heritage Management ◽  
Cultural Heritage Management ◽  
The North ◽  
Northern Fennoscandia ◽  
Airborne Laser ◽  
Pulse Density

This paper gives a presentation of how airborne laser scanning (ALS) has been adopted in archaeology in the North over the period 2005–2019. Almost two decades have passed since ALS first emerged as a potential tool to add to the archaeologist’s toolbox. Soon after, it attracted the attention of researchers within archaeological communities engaged with remote sensing in the Fenno-Scandinavian region. The first archaeological ALS projects gave immediate good results and led to further use, research, and development through new projects that followed various tracks. The bulk of the research and development focused on studying how well-suited ALS is for identifying, mapping, and documenting archaeological features in outfield land, mainly in forested areas. The poor situation in terms of lack of information on archaeological records in outfield areas has been challenging for research and especially for cultural heritage management for a long period of time. Consequently, an obvious direction was to study how ALS-based mapping of cultural features in forests could help to improve the survey situation. This led to various statistical analyses and studies covering research questions related to for instance effects on detection success of laser pulse density, and the size and shape of the targeted features. Substantial research has also been devoted to the development and assessment of semi-automatic detection of archaeological features based on the use of algorithms. This has been studied as an alternative approach to human desk-based visual analyses and interpretations of ALS data. This approach has considerable potential for detecting sites over large regions such as the vast roadless and unbuilt wilderness regions of northern Fennoscandia, and has proven highly successful. In addition, the current review presents how ALS has been employed for monitoring purposes and for landscape studies, including how it can influence landscape understanding. Finally, the most recent advance within ALS research and development has been discussed: testing of the use of drones for data acquisition. In conclusion, aspects related to the utilization of ALS in archaeological research and cultural heritage management are summarized and discussed, together with thoughts about future perspectives.

Forest road quality control using ALS data

2015 ◽  
Vol 45 (11) ◽  
pp. 1636-1642 ◽  
Author(s):  
Katalin Kiss ◽  
Jukka Malinen ◽  
Timo Tokola
Keyword(s):  
Laser Scanning ◽  
Road Surface ◽  
Airborne Laser Scanning ◽  
Forest Roads ◽  
Forest Road ◽  
Topographic Position ◽  
The Road ◽  
Topographic Position Index ◽  
Airborne Laser ◽  
Position Index

Good road conditions are necessary for the smooth transportation of forest machines and products. High-density airborne laser scanning data were used here to determine the quality of road surfaces and ditching systems. Forest roads in Kiihtelysvaara, Finland, were assessed in August 2013. Eight categories (structural condition, seasonal damage, drying, bridges, surface wear, visibility, coppicing, and flatness) have been inventoried and divided into three quality classes: poor, satisfactory, and good. The topographic position index, standardize elevation index, and hydrology tools were used on digital elevation models with different resolutions to test which categories could be derived. The road surface quality was most clearly related to surface wearing and flatness, and the topographic position index described the road surface best at resolutions of 0.20 m and 0.25 m; however, the standardized elevation index was superior at a 0.50 m resolution. The ditching system plays an important role in the drying of roads, and the hydrological tools and land facet analysis were most suitable for identifying the location of ditches and assessing their quality at 0.20 m and 0.25 m resolutions, respectively. The road surface was classified in all resolutions at least 66% correctly, whereas the ditches were classified in all resolutions at least 60% correctly. The results confirm that airborne laser scanning data can be used for obtaining quality information on forest roads.

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 Airborne laser scanning for terrain modeling in the Amazon forest

2018 ◽  
Vol 48 (4) ◽  
pp. 271-279 ◽  
Author(s):  
Mariana Silva ANDRADE ◽  
Eric Bastos GORGENS ◽  
Cristiano Rodrigues REIS ◽  
Roberta Zecchini CANTINHO ◽  
Mauro ASSIS ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Forest Canopy ◽  
Digital Terrain Model ◽  
Horizontal Resolution ◽  
Airborne Laser Scanning ◽  
Amazon Forest ◽  
Vegetation Density ◽  
Airborne Laser ◽  
Pulse Density ◽  
Forested Areas

ABSTRACT Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.

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
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