scholarly journals An Evaluation of the Effects of UAS Flight Parameters on Digital Aerial Photogrammetry Processing and Dense-Cloud Production Quality in a Scots Pine Forest

2021 ◽  
Vol 13 (6) ◽  
pp. 1121
Author(s):  
Raul Sampaio de Lima ◽  
Mait Lang ◽  
Niall G. Burnside ◽  
Miguel Villoslada Peciña ◽  
Tauri Arumäe ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
Model Fitting ◽  
Ground Level ◽  
Point Clouds ◽  
Production Quality ◽  
Unmanned Aerial Systems ◽  
Aerial Photogrammetry ◽  
Wide Range ◽  
Scots Pine Forest

The application of unmanned aerial systems (UAS) in forest research includes a wide range of equipment, systems, and flight settings, creating a need for enhancing data acquisition efficiency and quality. Thus, we assessed the effects of flying altitude and lateral and longitudinal overlaps on digital aerial photogrammetry (DAP) processing and the ability of its products to provide point clouds for forestry inventory. For this, we used 18 combinations of flight settings for data acquisition, and a nationwide airborne laser scanning (ALS) dataset as reference data. Linear regression was applied for modeling DAP quality indicators and model fitting quality as the function of flight settings; equivalence tests compared DAP- and ALS-products. Most of DAP-Digital Terrain Models (DTM) showed a moderate to high agreement (R2 > 0.70) when fitted to ALS-based models; nine models had a regression slope within the 1% region of equivalence. The best DAP-Canopy Height Model (CHM) was generated using ALS-DTM with an R2 = 0.42 when compared with ALS-CHM, indicating reduced similarity. Altogether, our results suggest that the optimal combination of flight settings should include a 90% lateral overlap, a 70% longitudinal overlap, and a minimum altitude of 120 m above ground level, independent of the availability of an ALS-derived DTM for height normalization. We also provided insights into the effects of flight settings on DAP outputs for future applications in similar forest stands, emphasizing the benefits of overlaps for comprehensive scene reconstruction and altitude for canopy surface detection.

scholarly journals Vegetation Phenology Driving Error Variation in Digital Aerial Photogrammetrically Derived Terrain Models

2018 ◽  
Vol 10 (10) ◽  
pp. 1554 ◽  
Author(s):  
Tristan Goodbody ◽  
Nicholas Coops ◽  
Txomin Hermosilla ◽  
Piotr Tompalski ◽  
Gaetan Pelletier
Keyword(s):  
Vegetation Cover ◽  
Laser Scanning ◽  
Point Clouds ◽  
Vegetation Coverage ◽  
Unmanned Aerial Systems ◽  
Management Activity ◽  
Data Set ◽  
Aerial Photogrammetry ◽  
Terrain Models ◽  
Additive Mixed Models

Digital aerial photogrammetry (DAP) and unmanned aerial systems (UAS) have emerged as synergistic technologies capable of enhancing forest inventory information. A known limitation of DAP technology is its ability to derive terrain surfaces in areas with moderate to high vegetation coverage. In this study, we sought to investigate the influence of flight acquisition timing on the accuracy and coverage of digital terrain models (DTM) in a low cover forest area in New Brunswick, Canada. To do so, a multi-temporal UAS-acquired DAP data set was used. Acquired imagery was photogrammetrically processed to produce high quality DAP point clouds, from which DTMs were derived. Individual DTMs were evaluated for error using an airborne laser scanning (ALS)-derived DTM as a reference. Unobstructed road areas were used to validate DAP DTM error. Generalized additive mixed models (GAMM) were generated to assess the significance of acquisition timing on mean vegetation cover, DTM error, and proportional DAP coverage. GAMM models for mean vegetation cover and DTM error were found to be significantly influenced by acquisition date. A best available terrain pixel (BATP) compositing exercise was conducted to generate a best possible UAS DAP-derived DTM and outline the importance of flight acquisition timing. The BATP DTM yielded a mean error of −0.01 m. This study helps to show that the timing of DAP acquisitions can influence the accuracy and coverage of DTMs in low cover vegetation areas. These findings provide insight to improve future data set quality and provide a means for managers to cost-effectively derive high accuracy terrain models post-management activity.

Using LiDAR Point Clouds in Determination of the Scots Pine Stands Spatial Structure Meaning in the Conservation of Lichen Communities in “Bory Tucholskie” National Park

2019 ◽  
Vol 31 (1) ◽  
pp. 85-103
Author(s):  
Piotr Wężyk ◽  
Paweł Hawryło ◽  
Marta Szostak ◽  
Karolina Zięba-Kulawik ◽  
Monika Winczek ◽  
...  
Keyword(s):  
Spatial Structure ◽  
National Park ◽  
Laser Scanning ◽  
Ground Level ◽  
Point Clouds ◽  
Organic Layer ◽  
Active Protection ◽  
Scanning Lidar ◽  
Pine Stands ◽  
Biometric Features

Abstract The aim of the research carried out in 2018 and financed by the Forest Fund was the analysis of biometric features and parameters of pine stands in the area of the “Bory Tucholskie” National Park (PNBT), where a program of active protection of lichen was initiated in 2017. Environmental analyses were conducted in relation to selected biometric features of trees and stands using laser scanning (LiDAR), including ULS (Unmanned Laser Scanning; RIEGL VUX-1) and TLS (Terrestrial Laser Scanning; FARO FOCUS 3D; X130). Thanks to the application of LiDAR technology, the structure of pine stands was precisely determined by means of a series of descriptive statistics characterizing the 3D spatial structure of vegetation. Using the Trees Crown Model (CHM), the analysis of the volume of tree crowns and the volume of space under canopy was performed. For the analysed sub-compartments, GIS solar analyses were carried out for the solar energy reaching the canopy and the ground level due to active protection of lichen. Multispectral photos were obtained using a specialized RedEdge-M camera (MicaSense) mounted on the UAV multi rotor platform Typhoon H520 (Yuneec). Flights with a thermal camera were also performed in order to detect places on the ground with high temperature. Plant indices: NDVI, NDRE, GNDVI and GRVI were also calculated for sub-compartments. The data obtained in 2017 and 2018 were the basis for spatial and temporal analyses of 4-D changes in stands which were related to the removal of some trees and organic layer (litter, moss layer).

scholarly journals Combined Use of Terrestrial Laser Scanning and UAV Photogrammetry in Mapping Alpine Terrain

2019 ◽  
Vol 11 (18) ◽  
pp. 2154 ◽  
Author(s):  
Ján Šašak ◽  
Michal Gallay ◽  
Ján Kaňuk ◽  
Jaroslav Hofierka ◽  
Jozef Minár
Keyword(s):  
High Resolution ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Mutual Orientation ◽  
Close Range Photogrammetry ◽  
Combined Use ◽  
Wide Range ◽  
Close Range

Airborne and terrestrial laser scanning and close-range photogrammetry are frequently used for very high-resolution mapping of land surface. These techniques require a good strategy of mapping to provide full visibility of all areas otherwise the resulting data will contain areas with no data (data shadows). Especially, deglaciated rugged alpine terrain with abundant large boulders, vertical rock faces and polished roche-moutones surfaces complicated by poor accessibility for terrestrial mapping are still a challenge. In this paper, we present a novel methodological approach based on a combined use of terrestrial laser scanning (TLS) and close-range photogrammetry from an unmanned aerial vehicle (UAV) for generating a high-resolution point cloud and digital elevation model (DEM) of a complex alpine terrain. The approach is demonstrated using a small study area in the upper part of a deglaciated valley in the Tatry Mountains, Slovakia. The more accurate TLS point cloud was supplemented by the UAV point cloud in areas with insufficient TLS data coverage. The accuracy of the iterative closest point adjustment of the UAV and TLS point clouds was in the order of several centimeters but standard deviation of the mutual orientation of TLS scans was in the order of millimeters. The generated high-resolution DEM was compared to SRTM DEM, TanDEM-X and national DMR3 DEM products confirming an excellent applicability in a wide range of geomorphologic applications.

scholarly journals Design and Evaluation of Sensor Housing for Boundary Layer Profiling Using Multirotors

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2481 ◽  
Author(s):  
Ashraful Islam ◽  
Adam L. Houston ◽  
Ajay Shankar ◽  
Carrick Detweiler
Keyword(s):  
Boundary Layer ◽  
High Speed ◽  
Ground Level ◽  
Radiation Shielding ◽  
Unmanned Aerial Systems ◽  
Heat Sources ◽  
Wide Range ◽  
Artificial Heat ◽  
Aerial Systems ◽  
Airborne Sensors

Traditional configurations for mounting Temperature–Humidity (TH) sensors on multirotor Unmanned Aerial Systems (UASs) often suffer from insufficient radiation shielding, exposure to mixed and turbulent air from propellers, and inconsistent aspiration while situated in the wake of the UAS. Descent profiles using traditional methods are unreliable (when compared to an ascent profile) due to the turbulent mixing of air by the UAS while descending into that flow field. Consequently, atmospheric boundary layer profiles that rely on such configurations are bias-prone and unreliable in certain flight patterns (such as descent). This article describes and evaluates a novel sensor housing designed to shield airborne sensors from artificial heat sources and artificial wet-bulbing while pulling air from outside the rotor wash influence. The housing is mounted above the propellers to exploit the rotor-induced pressure deficits that passively induce a high-speed laminar airflow to aspirate the sensor consistently. Our design is modular, accommodates a variety of other sensors, and would be compatible with a wide range of commercially available multirotors. Extensive flight tests conducted at altitudes up to 500 m Above Ground Level (AGL) show that the housing facilitates reliable measurements of the boundary layer phenomena and is invariant in orientation to the ambient wind, even at high vertical/horizontal speeds (up to 5 m/s) for the UAS. A low standard deviation of errors shows a good agreement between the ascent and descent profiles and proves our unique design is reliable for various UAS missions.

scholarly journals Segmentation of LiDAR Data Using Multilevel Cube Code

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
So-Young Park ◽  
Dae Geon Lee ◽  
Eun Jin Yoo ◽  
Dong-Cheon Lee
Keyword(s):  
Spatial Data ◽  
Laser Scanning ◽  
Point Clouds ◽  
Airborne Laser Scanning ◽  
Lidar Data ◽  
Chain Code ◽  
Cloud Data ◽  
Airborne Laser ◽  
Wide Range ◽  
Scanning Systems

Light detection and ranging (LiDAR) data collected from airborne laser scanning systems are one of the major sources of spatial data. Airborne laser scanning systems have the capacity for rapid and direct acquisition of accurate 3D coordinates. Use of LiDAR data is increasing in various applications, such as topographic mapping, building and city modeling, biomass measurement, and disaster management. Segmentation is a crucial process in the extraction of meaningful information for applications such as 3D object modeling and surface reconstruction. Most LiDAR processing schemes are based on digital image processing and computer vision algorithms. This paper introduces a shape descriptor method for segmenting LiDAR point clouds using a “multilevel cube code” that is an extension of the 2D chain code to 3D space. The cube operator segments point clouds into roof surface patches, including superstructures, removes unnecessary objects, detects the boundaries of buildings, and determines model key points for building modeling. Both real and simulated LiDAR data were used to verify the proposed approach. The experiments demonstrated the feasibility of the method for segmenting LiDAR data from buildings with a wide range of roof types. The method was found to segment point cloud data effectively.

scholarly journals MOBILE INDOOR LASER SCANNING FOR 3D STRATA REGISTRATION PURPOSES BASED ON INDOORGML

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 241-245
Author(s):  
M. N. Hashim ◽  
M. I. Hassan ◽  
A. Abdul Rahman
Keyword(s):  
Data Acquisition ◽  
Web Application ◽  
Laser Scanning ◽  
Point Clouds ◽  
3D Modelling ◽  
3D Cadastre ◽  
The Right

Abstract. In Malaysia, the current 2D cadastre system is regularly updated by the National Mapping Agency (NMA) and Land Offices (LO). However, this 2D information may not be able to serve complex situations. The 3D strata acquisition and 3D modelling are important for strata title to manage the Right, Restriction and Responsibility (RRRs). This means there is a need for the system to be extended into 3D cadastre environment. One of the data acquisition techniques such as LiDAR from Mobile Laser Scanning (MLS) could be utilised to solve the problem. This research also discusses the 3D geospatial objects generated from the captured point-clouds, modelled in SketchUp and transformed into IndoorGML. In this study, Web application is developed as a platform for generating an integrated XML-IndoorGML schema. Thus, this research contributes on 3D strata modelling especially for the development of 3D strata registration in Malaysia.

scholarly journals Classification of Photogrammetric and Airborne LiDAR Point Clouds Using Machine Learning Algorithms

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 104
Author(s):  
Zaide Duran ◽  
Kubra Ozcan ◽  
Muhammed Enes Atik
Keyword(s):  
Machine Learning ◽  
Point Cloud ◽  
Point Clouds ◽  
Machine Learning Algorithms ◽  
Airborne Lidar ◽  
Aerial Photogrammetry ◽  
Feature Spaces ◽  
Wide Range ◽  
Extract Information

With the development of photogrammetry technologies, point clouds have found a wide range of use in academic and commercial areas. This situation has made it essential to extract information from point clouds. In particular, artificial intelligence applications have been used to extract information from point clouds to complex structures. Point cloud classification is also one of the leading areas where these applications are used. In this study, the classification of point clouds obtained by aerial photogrammetry and Light Detection and Ranging (LiDAR) technology belonging to the same region is performed by using machine learning. For this purpose, nine popular machine learning methods have been used. Geometric features obtained from point clouds were used for the feature spaces created for classification. Color information is also added to these in the photogrammetric point cloud. According to the LiDAR point cloud results, the highest overall accuracies were obtained as 0.96 with the Multilayer Perceptron (MLP) method. The lowest overall accuracies were obtained as 0.50 with the AdaBoost method. The method with the highest overall accuracy was achieved with the MLP (0.90) method. The lowest overall accuracy method is the GNB method with 0.25 overall accuracy.

scholarly journals 3D RECORDING AND MODELLING OF MIDDLE-AGE FORTRESS IN DENSE VEGETATION ENVIRONMENT

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 415-420
Author(s):  
M. Koehl ◽  
Y. Courtois ◽  
S. Guillemin
Keyword(s):  
World War I ◽  
Middle Ages ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Major Step ◽  
Terrain Model ◽  
Dense Vegetation ◽  
Aerial Photogrammetry ◽  
Pass Through

The Schwartzenbourg castle is a Middle-Ages fortress which was built in 1261. It is situated above the valley of Munster in Alsace, France. It was mainly used as a fortified place and a jail. In the early 15th century, the structure has deteriorated. Even after some repairs, it fell into ruins during the Thirty Years’ war (1618-1648) and stayed uninhabited. During World War I, the German army used the place as a vantage point and also built a blockhouse inside the ruins. Nowadays, the ruins are gradually collapsing and the remains of the old walls are completely covered by thick plants.<br><br> The goal of this project was to create a 3D-model of the site before closing its access, which became too dangerous for people. This modelling is divided into two elements: on one hand, a digital terrain model (DTM) of the site in order to replace the castle and to analyze the background of its original environment; on the other hand, a 3D modelling of the ruins of the castle invaded by the vegetation. Indeed, the main difficulty of the measurement is obviously the dense vegetation which hides the castle. Held back for years outside the castle, it has now become an integral part of the ruins. This vegetation is finally today usually the first threat of heritage buildings. After a preliminary inspection of the site as well as difficulties of the project, the first step consisted of the survey of the whole environment of the site. We will therefore describe the different phases of the survey with the initial implementation of a georeferenced network on site. We will present the terrestrial laser scanning (TLS) surveys, then complementary surveys carried out by aerial photogrammetry. To be implemented, we had to wait for an advanced autumn in order to have as few leaves on trees as possible. The major step of processing of point clouds described in this paper is then the extraction of a DTM by using techniques to pass through the vegetation, or better to segment the points into different classes, one of these that would be the soil i.e. DTM, another consists into wall parts of the ruins.

scholarly journals INDOOR MAPPING OF A COMPLEX CULTURAL HERITAGE SCENE USING TLS AND HMLS LASER SCANNING

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 605-612
Author(s):  
V. E. Oniga ◽  
A. I. Breaban ◽  
E. I. Alexe ◽  
C. Văsii
Keyword(s):  
Standard Deviation ◽  
Cultural Heritage ◽  
Long Range ◽  
Interior Design ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Acquisition Time ◽  
Wide Range

Abstract. Indoor mapping and modelling is an important research subject with application in a wide range of domains including interior design, real estate, cultural heritage conservation and restoration. There are multiple sensors applicable for 3D indoor modelling, but the laser scanning technique is frequently used because of the acquisition time, detailed information and accuracy. In this paper, the efficiency of the Maptek I-Site 8820 terrestrial scanner, which is a long-range laser scanner and the accuracy of a HMLS point cloud acquired with a mobile scanner, namely GeoSlam Zeb Horizon were tested for indoor mapping. Aula Magna “Carmen Silva” of the “Gheorghe Asachi” Technical University of Iasi is studied in the current paper since the auditorium interior creates a distinct environment that combines complex geometric structures with architectural lighting and for preserving its great cultural value, the monument has a national historical significance. The registration process of the TLS point clouds was done using two methods: a semi-automatic one with artificial targets and a completely automatic one, based on Iterative Closest Point (ICP) algorithm. The resulted TLS point cloud was analysed in relation to the HMLS point cloud by computing the M3C2 (Multiscale Model to Model Cloud Comparison), obtaining a standard deviation of 2.1 cm and by investigating the Hausdorff distances from which resulted a standard deviation (σ) of 1.6 cm. Cross-sections have been extracted from the HMLS and TLS point clouds and after comparing the sections, 80% of the sigma values are less or equal to 1 cm. The results show high potential of using HMLS and also a long-range laser scanner for 3D modelling of complex scenes, the occlusion effect in the case of TLS being only 5% of the scanned area.

scholarly journals Influence of Scan Density on the Estimation of Single-Tree Attributes by Hand-Held Mobile Laser Scanning

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 277 ◽  
Author(s):  
Barbara Del Perugia ◽  
Francesca Giannetti ◽  
Gherardo Chirici ◽  
Davide Travaglini
Keyword(s):  
Data Acquisition ◽  
Laser Scanning ◽  
Reference Data ◽  
Central Italy ◽  
Castanea Sativa ◽  
Tree Height ◽  
Point Clouds ◽  
Single Tree ◽  
Breast Height ◽  
Scan Path

Nowadays, forest inventories are frequently carried out using a combination of field measurements and remote sensing data, often acquired with light detection and ranging (LiDAR) sensors. Several studies have investigated how three-dimensional laser scanning point clouds from different platforms can be used to acquire information traditionally collected with forest instruments, such as hypsometers and callipers to detect single-tree attributes like tree height and diameter at the breast height. The present study has tested the performances of the ZEB1 instrument, a type of hand-held mobile laser scanner, for single-tree attributes estimation in pure Castanea sativa Mill. stands cultivated for fruit production in Central Italy. In particular, the influence of walking scan path density on single-tree attributes estimation (number of trees, tree position, diameter at breast height, tree height, and crown base height) was investigated to test the efficiency of field measures. The point clouds were acquired by walking along straight lines drawn with different spacing: 10 and 15 m apart. A single-tree scan approach, which included walking with the instrument around each tree, was used as reference data. In order to evaluate the efficiency of the survey, the influence of the walking scan path was discussed in relation to the accuracy of single-tree attributes estimation, as well as the time and cost needed for data acquisition, pre-processing, and analysis. Our results show that the 10 m scan path provided the best results, with an omission error of 6%; the assessment of single-tree attributes was successful, with values of the coefficient of determination and the relative root mean square error similar to other studies. The 10 m scan path has also proved to decrease the costs by about €14 for data pre-processing, and a saving of time for data acquisition and data analysis of about 37 min compared to the reference data.

Sign in / Sign up

Export Citation Format

Share Document