Difference between time-of-flight and phase-shift laser scanners in tree measurements

Maalaserkeilauksen (Terrestrial Laser Scanning, TLS) on viime aikoina osoitettu soveltuvan hyvin puustoparametrien ratkaisemiseen. TLS on tarjonnut useassa tutkimuksessa lupaavia tuloksia esimerkiksi runkojen havaitsemisessa, rinnankorkeuden läpimitan (Diameter at Breast Height, DBH) mittaamisessa, rungon laadun ja muutoksen mittaamisessa sekä puunkorkeuden, puutilavuuden ja biomassan arvioinnissa. Vaikka TLS:n soveltuvuus metsämit-tauksissa on lupaava, on sen suurena ongelmana latvusten läpäisemättömyys. Monet edellä mainituista tutkimuksista on tehty vaihe-erokeilaimella. Osa on tehty pulssikeilaimella, mutta pulssikeilaimen ja vaihe-erokeilaimen välisiä eroja puustomittauksissa ei tiettävästi ole tutkittu. Jotta TLS-laitteistoa voidaan jatkossa hyödyntää laajemmin metsämittauksissa, tulee tietää, kumpi mittaustekniikka siihen parhaiten soveltuu. Tässä työssä verrattiin kahden keilausmenetelmän, pulssimittauksen (Time of Flight, ToF) ja vaihe-eromittauksen (Phase Shift, PS), eroja puustomittauksissa keilaamalla ja pistepilvistä mittaamalla kuudella koealalla. Tutkimuksessa suoritettiin puustomittaukset keilainkohtaisesti jokaiselle koealalle niin yksittäisen (Single-Scan, SS) kuin useamman (Multi-Scan, MS) keilauksen tapauksessa. Puustomittaukset tehtiin sekä manuaalisesti että automaattisesti. Manuaalimittauksissa mitattiin aineistosta havaittujen puunrunkojen lukumäärä, kokonaisten puiden lukumäärä sekä havaitun puun rungon ylin mitattavissa oleva läpimitta. Automaatti-mittaukset suoritettiin tähän tarkoitukseen kehitetyllä algoritmilla. Algoritmi etsi aineistosta kaikki mitattavissa olleet puunrungot, rakensi näkyvänä olleiden puunrunkojen perusteella runkokäyriä ja estimoi puiden korkeudet runkokäyrän perusteella. Tulosten mukaan pulssikeilaimen läpäisykyky on parempi kuin vaihe-erokeilaimen läpäisykyky, kun on kyse puustomittauksista. Jokainen läpäisykykyä indikoiva tulos oli pulssikeilaimella parempi niin SS- kuin MS-mittauksissa. Läpäisykyvyn erot olivat tulosten mukaan kuitenkin merkittävästi suuremmat SS-mittauksissa. Kun verrattiin pulssikeilaimella saatuja tuloksia vaihe-erokeilaimiin SS-tapauksessa, paranivat tulokset keskimäärin seuraavanlaisesti: kokonaisia puita saatiin 52 % enemmän näkyviin, puun runkoja saatiin 10 % enemmän näkyviin ja puunrunkojen läpimitat saatiin mitattua 13 % korkeammalta. Vastaavat luvut MS-tapauksessa olivat 37, 4 ja 10 %. Algoritmin avulla saatiin SS-tapauksessa rungon läpimitta mitattua pulssikeilaimella keskimäärin 6 % korkeammalta. Puita havaittiin samassa mittausasetelmassa keskimäärin noin 16 % enemmän pulssikeilaimen hyväksi. Vastaavat luvut MS-tapauksessa olivat noin 3 ja 7 %.Terrestrial laser scanning (TLS) has been proved to be a promising technique in tree measurements. In many studies TLS has been proved to provide some promising results in evaluating tree attributes such as number of stems, stem density, diameter at breast height (DBH), tree height, stem curves, stem volume, biomass, stem quality and change of stems. However, TLS measurements face the problem with the bad penetration through branches and leaves. Many previously mentioned studies have been done by using phase-shift (PS) laser scanners (LS). No studies about the difference between PS-scanners and time-of-flight (ToF) scanners in forest inventory could be found. In order to use TLS widely in forest measurements, the differences between TLS techniques have to be known. In this study, the differences between PS-technique and ToF-technique have been compared by scanning and analysing 6 test plots. Tree attributes were measured from each laser scan-ner in Single-Scan (SS) and Multi-Scan (MS) mode. The LS data was analysed manually and automatically. In the manual measurements the number of complete trees, number of stems and the height of the highest measurable point of the stem were measured. In automatic measurements the algorithm locates each stem, creates a stem curve and estimates a height for a tree. The results indicate a better penetration for the ToF-scanner when it is compared to the PS-scanner when it comes to tree measurements. In both measuring modes (SS and MS), each result indicated a better penetration for the ToF-scanner. The biggest difference between ToF and PS was in the SS-mode. The following percentages show how much the ToF results differed from the PS results in the SS-mode: 52 % in finding complete trees, 10 % in finding stems and 13 % in measuring the highest point of the measurable diameter. The corresponding results in the MS-mode were 37 %, 4 % and 10 %. In the automatic measurements, the highest point of the measurable diameter was 6 % better in ToF-data in the SS-mode. In the same mode algorithm found from ToF-data 16 % more stems compared to PS-data. Corresponding results for MS-mode were 3 and 7 %

Tree Water Status Affects Tree Branch Position

Physiological processes cause movements of tree stems and branches that occur in a circadian rhythm and over longer time periods, but there is a lack of quantitative understanding of the cause-and-effect relationships. We investigated the movement of tree branches in a long-term drought experiment and at a circadian time scale using time-series of terrestrial laser scanning measurements coupled with measurements of environmental drivers and tree water status. Our results showed that movement of branches was largely explained by leaf water status measured as leaf water potential in a controlled environment for both measured trees (R2 = 0.86 and R2 = 0.75). Our hypothesis is that changes in leaf and branch water status would cause branch movements was further supported by strong relationship between vapor pressure deficit and overnight branch movement (R2 = [0.57–0.74]). Due to lower atmospheric water demand during the nighttime, tree branches settle down as the amount of water in leaves increases. The results indicate that the quantified movement of tree branches could help us to further monitor and understand the water relations of tree communities

Tree Water Status Affects Tree Branch Position

Physiological processes cause movements of tree stems and branches that occur in a circadian rhythm and over longer time periods, but there is a lack of quantitative understanding of the cause-and-effect relationships. We investigated the movement of tree branches in a long-term drought experiment and at a circadian time scale using time-series of terrestrial laser scanning measurements coupled with measurements of environmental drivers and tree water status. Our results showed that movement of branches was largely explained by leaf water status measured as leaf water potential in a controlled environment for both measured trees (R2 = 0.86 and R2 = 0.75). Our hypothesis is that changes in leaf and branch water status would cause branch movements was further supported by strong relationship between vapor pressure deficit and overnight branch movement (R2 = [0.57–0.74]). Due to lower atmospheric water demand during the nighttime, tree branches settle down as the amount of water in leaves increases. The results indicate that the quantified movement of tree branches could help us to further monitor and understand the water relations of tree communities

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5ha forest was covered in ca. 10min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2-4cm RMSE of the diameter at the breast height estimates, and a 4-7cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.Peer reviewe

Feasibility of Mobile Laser Scanning towards Operational Accurate Road Rut Depth Measurements

This paper studied the applicability of the Roamer-R4DW mobile laser scanning (MLS) system for road rut depth measurement. The MLS system was developed by the Finnish Geospatial Research Institute (FGI), and consists of two mobile laser scanners and a Global Navigation Satellite System (GNSS)-inertial measurement unit (IMU) positioning system. In the study, a fully automatic algorithm was developed to calculate and analyze the rut depths, and verified in 64 reference pavement plots (1.0 m x 3.5 m). We showed that terrestrial laser scanning (TLS) data is an adequate reference for MLS-based rutting studies. The MLS-derived rut depths based on 64 plots resulted in 1.4 mm random error, which can be considered adequate precision for operational rutting depth measurements. Such data, also covering the area outside the pavement, would be ideal for multiple road environment applications since the same data can also be used in applications, from high-definition maps to autonomous car navigation and digitalization of street environments over time and in space

A backpack-mounted omnidirectional camera with off-the-shelf navigation sensors for mobile terrestrial mapping: Development and forest application

The use of Personal Mobile Terrestrial System (PMTS) has increased considerably for mobile mapping applications because these systems offer dynamic data acquisition with ground perspective in places where the use of wheeled platforms is unfeasible, such as forests and indoor buildings. PMTS has become more popular with emerging technologies, such as miniaturized navigation sensors and off-the-shelf omnidirectional cameras, which enable low-cost mobile mapping approaches. However, most of these sensors have not been developed for high-accuracy metric purposes and therefore require rigorous methods of data acquisition and data processing to obtain satisfactory results for some mapping applications. To contribute to the development of light, low-cost PMTS and potential applications of these off-the-shelf sensors for forest mapping, this paper presents a low-cost PMTS approach comprising an omnidirectional camera with off-the-shelf navigation systems and its evaluation in a forest environment. Experimental assessments showed that the integrated sensor orientation approach using navigation data as the initial information can increase the trajectory accuracy, especially in covered areas. The point cloud generated with the PMTS data had accuracy consistent with the Ground Sample Distance (GSD) range of omnidirectional images (3.5–7 cm). These results are consistent with those obtained for other PMTS approaches. View Full-Text Keywords: personal mobile terrestrial system; omnidirectional cameras; low-cost sensors; forest mapping; PMTS data quality </div

Performance Assessment of Reference Modelling Methods for Defect Evaluation in Asphalt Concrete

The deterioration of road conditions and increasing repair deficits pose challenges for the maintenance of reliable road infrastructure, and thus threaten, for example, safety and the fluent flow of traffic. Improved and more efficient procedures for maintenance are required, and these require improved knowledge of road conditions, i.e., improved data. Three-dimensional mapping presents possibilities for large-scale collection of data on road surfaces and automatic evaluation of maintenance needs. However, the development and, specifically, evaluation of large-scale mobile methods requires reliable references. To evaluate possibilities for close-range, static, high-resolution, three-dimensional measurement of road surfaces for reference use, three measurement methods and five instrumentations are investigated: terrestrial laser scanning (TLS, Leica RTC360), photogrammetry using high-resolution professional-grade cameras (Nikon D800 and D810E), photogrammetry using an industrial camera (FLIR Grasshopper GS3-U3-120S6C-C), and structured-light handheld scanners Artec Leo and Faro Freestyle. High-resolution photogrammetry is established as reference based on laboratory measurements and point density. The instrumentations are compared against one another using cross-sections, point-point distances, and ability to obtain key metrics of defects, and a qualitative assessment of the processing procedures for each is carried out. It is found that photogrammetric models provide the highest resolutions (10-50 million points per m2) and photogrammetric and TLS approaches perform robustly in precision with consistent sub-millimeter offsets relative to one another, while handheld scanners perform relatively inconsistently. A discussion on the practical implications of using each of the examined instrumentations is presented

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5ha forest was covered in ca. 10min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2-4cm RMSE of the diameter at the breast height estimates, and a 4-7cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation

Fotogrammetriset sovellukset rintasyövän diagnostiikassa

A twenty eight page newsletter created by the Boonshoft School of Medicine to document the current affairs of the school. This issue includes a variety of feature articles, alumni profiles, class notes, and more.https://corescholar.libraries.wright.edu/med_vital_signs/1108/thumbnail.jp