scholarly journals ForestScanner: A mobile application for measuring and mapping trees with LiDAR-equipped iPhone and iPad

2021 ◽  
Author(s):  
Shinichi Tatsumi ◽  
Keiji Yamaguchi ◽  
Naoyuki Furuya
Keyword(s):  
Mobile Application ◽  
Laser Scanning ◽  
Point Clouds ◽  
Multiple Points ◽  
Forest Inventories ◽  
3D Point Clouds ◽  
Alternative Means ◽  
Spatial Coordinates ◽  
Good Agreement

Terrestrial laser scanning (TLS) is becoming increasingly popular as an alternative means to conventional forest inventory methods. By gauging the distances to multiple points on the surrounding object surfaces, TLS acquires 3D point clouds from which tree sizes and spatial distributions can be rapidly estimated. However, the high cost and specialized skills required for TLS have put it out of reach for many potential users. We here introduce ForestScanner, a free, mobile application that allows TLS-based forest inventories by means of iPhone or iPad with a built-in LiDAR sensor. ForestScanner does not require any manual analysis of 3D point clouds. As the user scans trees with an iPhone/iPad, ForestScanner estimates the stem diameters and spatial coordinates based on real-time instance segmentation and circle fitting. The users can visualize, check, and share the results of scanning in situ. By using ForestScanner, we measured the stem diameters and spatial coordinates of 672 trees within a 1 ha plot in 1 h 39 min with an iPhone and in 1 h 38 min with an iPad (diameter ≥5 cm; detection rate = 100%). ForestScanner reduced the person-hours required for measuring diameters to 25.7%, mapping trees to 9.3%, and doing both to 6.8% of the person-hours taken using a dimeter tape and a conventional surveying method. The diameters measured by ForestScanner and diameter tape were in good agreement; R2=0.963 for iPhone and R2=0.961 for iPad. ForestScanner and the conventional surveying system showed almost identical results for tree mapping (assessed by the spatial distances among trees within 0.04 ha subplots); Mantel R2=0.999 for both iPhone and iPad. Our results indicate that ForestScanner enables cost-, labor-, and time-efficient forest inventories. The application can increase the accessibility to TLS for people beyond specialists and enhance resource assessments and biodiversity monitoring in forests worldwide.

scholarly journals 3D Point Clouds and Eye Tracking for Investigating the Perception and Acceptance of Power Lines in Different Landscapes

2019 ◽  
Vol 3 (2) ◽  
pp. 40 ◽  
Author(s):  
Ulrike Wissen Hayek ◽  
Kilian Müller ◽  
Fabian Göbel ◽  
Peter Kiefer ◽  
Reto Spielhofer ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Power Lines ◽  
Urban Landscapes ◽  
3D Point Clouds ◽  
Energy Turnaround ◽  
Visual Landscape

The perception of the visual landscape impact is a significant factor explaining the public’s acceptance of energy infrastructure developments. Yet, there is lack of knowledge how people perceive and accept power lines in certain landscape types and in combination with wind turbines, a required setting to achieve goals of the energy turnaround. The goal of this work was to demonstrate how 3D point cloud visualizations could be used for an eye tracking study to systematically investigate the perception of landscape scenarios with power lines. 3D visualizations of near-natural and urban landscapes were prepared based on data from airborne and terrestrial laser scanning. These scenes were altered with varying amounts of the respective infrastructure, and they provided the stimuli in a laboratory experiment with 49 participants. Eye tracking and questionnaires served for measuring the participants’ responses. The results show that the point cloud-based simulations offered suitable stimuli for the eye tracking study. Particularly for the analysis of guided perceptions, the approach fostered an understanding of disturbing landscape elements. A comparative in situ eye tracking study is recommended to further evaluate the quality of the point cloud simulations, whether they produce similar responses as in the real world.

scholarly journals BIM Supported Surveying and Imaging Combination for Heritage Conservation

2021 ◽  
Vol 13 (8) ◽  
pp. 1584
Author(s):  
Pedro Martín-Lerones ◽  
David Olmedo ◽  
Ana López-Vidal ◽  
Jaime Gómez-García-Bermejo ◽  
Eduardo Zalama
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Cloud Data ◽  
Industry Foundation Classes ◽  
3D Point Clouds ◽  
Conservation Actions ◽  
Heritage Building ◽  
2D Imaging ◽  
Digital Survey ◽  
Level 2

As the basis for analysis and management of heritage assets, 3D laser scanning and photogrammetric 3D reconstruction have been probed as adequate techniques for point cloud data acquisition. The European Directive 2014/24/EU imposes BIM Level 2 for government centrally procured projects as a collaborative process of producing federated discipline-specific models. Although BIM software resources are intensified and increasingly growing, distinct specifications for heritage (H-BIM) are essential to driving particular processes and tools to efficiency shifting from point clouds to meaningful information ready to be exchanged using non-proprietary formats, such as Industry Foundation Classes (IFC). This paper details a procedure for processing enriched 3D point clouds into the REVIT software package due to its worldwide popularity and how closely it integrates with the BIM concept. The procedure will be additionally supported by a tailored plug-in to make high-quality 3D digital survey datasets usable together with 2D imaging, enhancing the capability to depict contextualized important graphical data to properly planning conservation actions. As a practical example, a 2D/3D enhanced combination is worked to accurately include into a BIM project, the length, orientation, and width of a big crack on the walls of the Castle of Torrelobatón (Spain) as a representative heritage building.

scholarly journals Automated Visual Recognizability Evaluation of Traffic Sign Based on 3D LiDAR Point Clouds

2019 ◽  
Vol 11 (12) ◽  
pp. 1453 ◽  
Author(s):  
Shanxin Zhang ◽  
Cheng Wang ◽  
Lili Lin ◽  
Chenglu Wen ◽  
Chenhui Yang ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Laser Scanning ◽  
Large Scale ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Point Clouds ◽  
Traffic Sign ◽  
Traffic Signs ◽  
3D Point Clouds ◽  
Traffic Environment

Maintaining the high visual recognizability of traffic signs for traffic safety is a key matter for road network management. Mobile Laser Scanning (MLS) systems provide efficient way of 3D measurement over large-scale traffic environment. This paper presents a quantitative visual recognizability evaluation method for traffic signs in large-scale traffic environment based on traffic recognition theory and MLS 3D point clouds. We first propose the Visibility Evaluation Model (VEM) to quantitatively describe the visibility of traffic sign from any given viewpoint, then we proposed the concept of visual recognizability field and Traffic Sign Visual Recognizability Evaluation Model (TSVREM) to measure the visual recognizability of a traffic sign. Finally, we present an automatic TSVREM calculation algorithm for MLS 3D point clouds. Experimental results on real MLS 3D point clouds show that the proposed method is feasible and efficient.

scholarly journals Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring

2018 ◽  
Vol 10 (10) ◽  
pp. 1562 ◽  
Author(s):  
Kathryn Fankhauser ◽  
Nikolay Strigul ◽  
Demetrios Gatziolis
Keyword(s):  
Laser Scanning ◽  
Canopy Cover ◽  
Tree Height ◽  
Forest Monitoring ◽  
Unmanned Aerial Systems ◽  
Aerial Laser Scanning ◽  
Forest Inventories ◽  
Airborne Laser ◽  
Aerial Systems

Forest inventories are constrained by resource-intensive fieldwork, while unmanned aerial systems (UASs) offer rapid, reliable, and replicable data collection and processing. This research leverages advancements in photogrammetry and market sensors and platforms to incorporate a UAS-based approach into existing forestry monitoring schemes. Digital imagery from a UAS was collected, photogrammetrically processed, and compared to in situ and aerial laser scanning (ALS)-derived plot tree counts and heights on a subsample of national forest plots in Oregon. UAS- and ALS-estimated tree counts agreed with each other (r2 = 0.96) and with field data (ALS r2 = 0.93, UAS r2 = 0.84). UAS photogrammetry also reasonably approximated mean plot tree height achieved by the field inventory (r2 = 0.82, RMSE = 2.92 m) and by ALS (r2 = 0.97, RMSE = 1.04 m). The use of both nadir-oriented and oblique UAS imagery as well as the availability of ALS-derived terrain descriptions likely sustain a robust performance of our approach across classes of canopy cover and tree height. It is possible to draw similar conclusions from any of the methods, suggesting that the efficient and responsive UAS method can enhance field measurement and ALS in longitudinal inventories. Additionally, advancing UAS technology and photogrammetry allows diverse users access to forest data and integrates updated methodologies with traditional forest monitoring.

scholarly journals USING MOBILE LASER SCANNING DATA FOR FEATURES EXTRACTION OF HIGH ACCURACY DRIVING MAPS

2016 ◽  
Vol XLI-B3 ◽  
pp. 433-439 ◽  
Author(s):  
Bisheng Yang ◽  
Yuan Liu ◽  
Fuxun Liang ◽  
Zhen Dong
Keyword(s):  
Laser Scanning ◽  
Human Error ◽  
Traffic Accidents ◽  
Three Dimensional ◽  
Point Clouds ◽  
High Accuracy ◽  
3D Point Clouds ◽  
Assistant Systems ◽  
Novel Method ◽  
High Flexibility

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

scholarly journals UAV-BASED AUTOMATIC TREE GROWTH MEASUREMENT FOR BIOMASS ESTIMATION

2016 ◽  
Vol XLI-B8 ◽  
pp. 685-688
Author(s):  
M. Karpina ◽  
M. Jarząbek-Rychard ◽  
P. Tymków ◽  
A. Borkowski
Keyword(s):  
Tree Growth ◽  
Point Clouds ◽  
In Situ Measurements ◽  
Unmanned Aircraft ◽  
Volume Estimation ◽  
Biomass Estimation ◽  
Test Field ◽  
3D Point Clouds ◽  
Growth Estimation

Manual in-situ measurements of geometric tree parameters for the biomass volume estimation are time-consuming and economically non-effective. Photogrammetric techniques can be deployed in order to automate the measurement procedure. The purpose of the presented work is an automatic tree growth estimation based on Unmanned Aircraft Vehicle (UAV) imagery. The experiment was conducted in an agriculture test field with scots pine canopies. The data was collected using a Leica Aibotix X6V2 platform equipped with a Nikon D800 camera. Reference geometric parameters of selected sample plants were measured manually each week. In situ measurements were correlated with the UAV data acquisition. The correlation aimed at the investigation of optimal conditions for a flight and parameter settings for image acquisition. The collected images are processed in a state of the art tool resulting in a generation of dense 3D point clouds. The algorithm is developed in order to estimate geometric tree parameters from 3D points. Stem positions and tree tops are identified automatically in a cross section, followed by the calculation of tree heights. The automatically derived height values are compared to the reference measurements performed manually. The comparison allows for the evaluation of automatic growth estimation process. The accuracy achieved using UAV photogrammetry for tree heights estimation is about 5cm.

Assessing 3D point clouds from aerial photographs for species-specific forest inventories

2016 ◽  
Vol 32 (1) ◽  
pp. 68-79 ◽  
Author(s):  
Stefano Puliti ◽  
Terje Gobakken ◽  
Hans Ole Ørka ◽  
Erik Næsset
Keyword(s):  
Point Clouds ◽  
Aerial Photographs ◽  
Forest Inventories ◽  
3D Point Clouds ◽  
Species Specific

A novel method for extracting skeleton of fruit tree from 3D point clouds

2020 ◽  
pp. 2050051
Author(s):  
Shenglian lu ◽  
Guo Li ◽  
Jian Wang
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Point Clouds ◽  
Fruit Trees ◽  
Fruit Tree ◽  
Tree Canopy ◽  
3D Point Clouds ◽  
Novel Method ◽  
Manual Interaction ◽  
Traditional Approaches

Tree skeleton could be useful to agronomy researchers because the skeleton describes the shape and topological structure of a tree. The phenomenon of organs’ mutual occlusion in fruit tree canopy is usually very serious, this should result in a large amount of data missing in directed laser scanning 3D point clouds from a fruit tree. However, traditional approaches can be ineffective and problematic in extracting the tree skeleton correctly when the tree point clouds contain occlusions and missing points. To overcome this limitation, we present a method for accurate and fast extracting the skeleton of fruit tree from laser scanner measured 3D point clouds. The proposed method selects the start point and endpoint of a branch from the point clouds by user’s manual interaction, then a backward searching is used to find a path from the 3D point cloud with a radius parameter as a restriction. The experimental results in several kinds of fruit trees demonstrate that our method can extract the skeleton of a leafy fruit tree with highly accuracy.

scholarly journals TLS and SfM Approach for Bulk Density Determination of Excavated Heterogeneous Raw Materials

Minerals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 174 ◽  
Author(s):  
Peter Blistan ◽  
Stanislav Jacko ◽  
Ľudovít Kovanič ◽  
Julián Kondela ◽  
Katarína Pukanská ◽  
...  
Keyword(s):  
Bulk Density ◽  
Laser Scanning ◽  
Large Scale ◽  
Raw Materials ◽  
Terrestrial Laser Scanning ◽  
Mineral Resources ◽  
Point Clouds ◽  
Raw Material

A frequently recurring problem in the extraction of mineral resources (especially heterogeneous mineral resources) is the rapid operative determination of the extracted quantity of raw material in a surface quarry. This paper deals with testing and analyzing the possibility of using unconventional methods such as digital close-range photogrammetry and terrestrial laser scanning in the process of determining the bulk density of raw material under in situ conditions. A model example of a heterogeneous deposit is the perlite deposit Lehôtka pod Brehmi (Slovakia). Classical laboratory methods for determining bulk density were used to verify the results of the in situ method of bulk density determination. Two large-scale samples (probes) with an approximate volume of 7 m3 and 9 m3 were realized in situ. 6 point samples (LITH) were taken for laboratory determination. By terrestrial laser scanning (TLS) measurement from 2 scanning stations, point clouds with approximately 163,000/143,000 points were obtained for each probe. For Structure-from-Motion (SfM) photogrammetry, 49/55 images were acquired for both probes, with final point clouds containing approximately 155,000/141,000 points. Subsequently, the bulk densities of the bulk samples were determined by the calculation from in situ measurements by TLS and SfM photogrammetry. Comparison of results of the field in situ measurements (1841 kg∙m−3) and laboratory measurements (1756 kg∙m−3) showed only a 4.5% difference in results between the two methods for determining the density of heterogeneous raw materials, confirming the accuracy of the used in situ methods. For the determination of the loosening coefficient, the material from both large-scale samples was transferred on a horizontal surface. Their volumes were determined by TLS. The loosening coefficient for the raw material of 1.38 was calculated from the resulting values.

Terrestrial laser scanning and structure-from-motion photogrammetry concordance analysis for describing the surface layer of gravel beds

2019 ◽  
Vol 43 (2) ◽  
pp. 260-281 ◽  
Author(s):  
Andrew J Neverman ◽  
Ian C Fuller ◽  
Jon N Procter ◽  
Russell G Death
Keyword(s):  
Surface Layer ◽  
Structure From Motion ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Survey Method ◽  
Gravel Beds ◽  
Non Invasive ◽  
Sampling Biases

Terrestrial laser scanning (TLS) and structure-from-motion photogrammetry (SfMp) offer rapid, non-invasive surveying of in situ gravels. Numerous studies have used the point clouds derived from TLS or SfMp to quantify surface layer characteristics, but direct comparison of the methods for grain-scale analysis has received relatively little attention to date. Comparing equivalent products of different data capture methods is critical as differences in errors and sampling biases between the two methods may produce different outputs, effecting further analysis. The sampling biases and errors related to SfMp and TLS lead to differences in the point clouds produced by each method. The metrics derived from the point clouds are therefore likely to differ, potentially leading to different inputs for entrainment threshold models, different trends in surface layer development being identified and different trajectories for physical processes and habitat quality being predicted. This paper provides a direct comparison between TLS and SfMp surveys of an exposed gravel bar for three different survey periods following inundation and reworking of the bar surface during high flow events. The point clouds derived from the two methods are used to describe changes in the character of the surface layer between bar inundation events, and comparisons are made with descriptions derived from conventional pebble counts. The results found differences in the metrics derived using each method do exist, but the grid resolution used to detrend the surfaces and identify spatial variations in surface layer characteristics had a greater impact than survey method. Further research is required to understand the significance of these variations for quantifying surface texture and structure and for predicting entrainment thresholds and transport rates.

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