Real-time Kinematic Global Navigation Satellite Research Articles

Benchmarked RADARSAT-2, SENTINEL-1 and RADARSAT Constellation Mission Change-Detection Monitoring at North Slide, Thompson River Valley, British Columbia: ensuring a Landslide-Resilient National Railway Network

In this research note, we demonstrate the applicability of interferometric analyses (InSAR) of RADARSAT 2 (RS2), SENTINEL 1 (S1) and RADARSAT Constellation Mission (RCM) datasets to characterize and monitor landslides along a high-risk section of the national railway transportation corridor traversing the Thompson River valley, British Columbia. As a geomorphically active landform, the North Slide is an ideal case study for field-testing and evaluating slope change-detection monitoring incorporating satellite, aerial and ground-based geospatial technologies. RS2, S1 and RCM InSAR datasets provide valuable baseline spatial and temporal information on movement of the landslide near critical railway infrastructure when benchmarked with real-time kinematic (RTK) global navigation satellite system (GNSS) measurements, uninhabited aerial vehicle (UAV) photogrammetry, bathymetric soundings, and ground observations. We demonstrate that monitoring unstable slopes and infrastructure at risk with multiple high spatial- and temporal-resolution satellite SAR platforms is a cost-effective natural hazard management practice that also provides important geoscience information to help develop appropriate mitigation and climate adaptation measures.

Harvester Evaluation Using Real-Time Kinematic GNSS and Hiring Service Model

To reduce human drudgery and the risk of labor shortages in the Asian developing countries, the appropriate introduction of agricultural machinery, especially combine harvesters, is an urgent task. Custom hiring services (CHSs) are expected to contribute to making paddy harvesters prevalent in developing countries; however, the economic performance has been rarely quantified. The study was carried out to precisely evaluate the machine performance attributes of medium and large combine harvesters using the real-time kinematic (RTK) global navigation satellite system (GNSS) and to estimate the economic performance of CHSs of paddy harvesters in Japan, as a typical case of Asian countries. The financial profitability was evaluated by four major indicators: net present value, benefit–cost ratio, internal rate of return, and payback period. The financial indicators showed that both types of harvester could be considered financially viable. Thus, the investment in combine harvesters can be highly profitable for CHS business by a local service provider and custom-hire entrepreneur, providing a great opportunity to use a combine harvester without initial investment by general farmers. The findings demonstrated the high feasibility of CHSs of paddy harvesters in Japan, while they highlighted that further study is needed to estimate the feasibility of CHS in the other Asian developing countries.

Derivation of high-resolution orthophoto map from multirotor drone survey for application in infrastructure management

An orthophoto is a geometrically corrected aerial image that can be used in the same approach as map. It provides various geospatial information and therefore plays an important role in infrastructure management. This paper describes the methodology of an aerial survey using a multirotor drone and the processing of aerial images acquired from the survey to produce an orthophoto map. The survey work was carried out using Zenmuse X4S photogrammetric camera controlled by an autopilot multirotor drone at 200m above the ground. Optimal flight path for the autonomous mission was created and organized using the Map Pilot software. Five ground control points were laid within the survey area and their locations were determined using a real-time kinematic global navigation satellite system. Aerial images acquired from the survey were processed with the Pix4Dmapper photogrammetry software. The photogrammetric processing generated a 6 cm-resolution orthophoto map. The presented work demonstrates the practicality of multirotor drone survey and intelligent image processing for non-professionals in deriving high-resolution orthophoto map for application in infrastructure management.

Ice thickness distribution and volume estimation of Burqin Glacier No. 18 in the Chinese Altay Mountains

Information on the thickness distribution and volume of glacier ice is highly important for glaciological applications; however, detailed measurements of the ice thickness of many glaciers in the Chinese Altay Mountains remain lacking. Burqin Glacier No. 18 is a northeast-orientated cirque glacier located on the southern side of the Altay Mountains. This study used PulseEKKO® PRO 100A enhancement ground-penetrating radar (GPR) to survey the ice thickness and volume of Burqin Glacier No. 18 in summer 2018. Together with GPR surveying, spatial distributed profiles of the GPR measurements were concurrently surveyed using the real-time kinematic (RTK) global navigation satellite system (GNSS, Unistrong E650). Besides, we used QuickBird, WorldView-2, and Landsat TM to delineate accurate boundary of the glacier for undertaking estimation of glacier ice volume. GPR measurements revealed that the basal topography of profile B1–B2 was flat, the basal topography of profile C1–C2 presented a V-type form, and the basal topography of profile D1–D2 had a typical U-type topographic feature because the bedrock near the central elevation of the glacier was relatively flat. The longitudinal profile A1–A2 showed a ladder-like distribution. Glacier ice was thin at the terminus and its thickness increased gradually from the elevation of approximately 2620 m a.s.l. along the main axis of the glacier tongue with an average value of 80 (±1) m. The average ice thickness of the glacier was determined as 27 (±2) m and its total ice volume was estimated at 0.031 (±0.002) km3. Interpretation of remote sensing images indicated that during 1989–2016, the glacier area reduced from 1.30 to 1.17 km2 (reduction of 0.37%/a) and the glacier terminus retreated at the rate of 8.48 m/a. The mean ice thickness of Burqin Glacier No. 18 was less than that of the majority of other observed glaciers in China, especially those in the Qilian Mountains and Central Chinese Tianshan Mountains; this is probably attributable to differences in glacier type and climatic setting.

Autonomous Navigation of a Center-Articulated and Hydrostatic Transmission Rover using a Modified Pure Pursuit Algorithm in a Cotton Field.

This study proposes an algorithm that controls an autonomous, multi-purpose, center-articulated hydrostatic transmission rover to navigate along crop rows. This multi-purpose rover (MPR) is being developed to harvest undefoliated cotton to expand the harvest window to up to 50 days. The rover would harvest cotton in teams by performing several passes as the bolls become ready to harvest. We propose that a small robot could make cotton production more profitable for farmers and more accessible to owners of smaller plots of land who cannot afford large tractors and harvesting equipment. The rover was localized with a low-cost Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS), encoders, and Inertial Measurement Unit (IMU)s for heading. Robot Operating System (ROS)-based software was developed to harness the sensor information, localize the rover, and execute path following controls. To test the localization and modified pure-pursuit path-following controls, first, GNSS waypoints were obtained by manually steering the rover over the rows followed by the rover autonomously driving over the rows. The results showed that the robot achieved a mean absolute error (MAE) of 0.04 m, 0.06 m, and 0.09 m for the first, second and third passes of the experiment, respectively. The robot achieved an MAE of 0.06 m. When turning at the end of the row, the MAE from the RTK-GNSS-generated path was 0.24 m. The turning errors were acceptable for the open field at the end of the row. Errors while driving down the row did damage the plants by moving close to the plants’ stems, and these errors likely would not impede operations designed for the MPR. Therefore, the designed rover and control algorithms are good and can be used for cotton harvesting operations.

MAPPING ROADWAY DRAINAGE DITCHES USING MOBILE LIDAR

Abstract. Roadside ditches serve an important role for draining storm water. Over time vegetation growth, natural sediment deposits, and other debris can change grade of ditches. Effectively monitoring and identifying these changes to prioritize ditch maintenance is important from both a pavement preservation perspective and prevention of localized flooding. This study evaluates the performance of two mobile LiDAR systems for mapping the cross-section of roadside ditches in the presence of vegetation. The geometric quality of data collected by two different wheel-based LiDAR systems were investigated. The mapped ditches were reported and visualized in 2D images as well as 3D point clouds. The cross-sections of man-made drainage ditches were extracted and the quality of mapped ditches was assessed against Real-Time Kinematic Global Navigation Satellite Systems (RTK-GNSS) survey. The overall point cloud accuracy was 4 cm for the medium-grade system, and 1 cm for the high-grade system. The mapping accuracy is 2 cm (medium-grade system) and 1 cm (high-grade system) for solid surface. For rough mowed areas and areas with significant vegetation, the vertical accuracy was found to be 7 cm and 11 cm, respectively, for both wheel-based systems.

Evaluation of a Stereo Vision System for Cotton Row Detection and Boll Location Estimation in Direct Sunlight

Cotton harvesting is performed by using expensive combine harvesters which makes it difficult for small to medium-size cotton farmers to grow cotton economically. Advances in robotics have provided an opportunity to harvest cotton using small and robust autonomous rovers that can be deployed in the field as a “swarm” of harvesters, with each harvester responsible for a small hectarage. However, rovers need high-performance navigation to obtain the necessary precision for harvesting. Current precision harvesting systems depend heavily on Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) to navigate rows of crops. However, GNSS cannot be the only method used to navigate the farm because for robots to work as a coordinated multiagent unit on the same farm because they also require visual systems to navigate, avoid collisions, and to accommodate plant growth and canopy changes. Hence, the optical system remains to be a complementary method for increasing the efficiency of the GNSS. In this study, visual detection of cotton rows and bolls was developed, demonstrated, and evaluated. A pixel-based algorithm was used to calculate and determine the upper and lower part of the canopy of the cotton rows by assuming the normal distribution of the high and low depth pixels. The left and right rows were detected by using perspective transformation and pixel-based sliding window algorithms. Then, the system determined the Bayesian score of the detection and calculated the center of the rows for the smooth navigation of the rover. This visual system achieved an accuracy of 92.3% and an F1 score of 0.951 for the detection of cotton rows. Furthermore, the same stereo vision system was used to detect the location of the cotton bolls. A comparison of the cotton bolls’ distances above the ground to the manual measurements showed that the system achieved an average R2 value of 99% with a root mean square error (RMSE) of 9 mm when stationary and 95% with an RMSE of 34 mm when moving at approximately 0.64 km/h. The rover might have needed to stop several times to improve its detection accuracy or move more slowly. Therefore, the accuracy obtained in row detection and boll location estimation is favorable for use in a cotton harvesting robotic system. Future research should involve testing of the models in a large farm with undefoliated plants.

Comparative analysis of real-time kinematic and PPP techniques in dynamic environment

The main objective of this study is to assess the performance of the relative Real-time Kinematic (RTK) Global Navigation Satellite System (GNSS) Methods; i.e., Single-baseline & Network RTK, and Real-time Precise Point Positioning (RT-PPP); i.e., Trimble CenterPoint Real Time eXtended (RTX) Correction Service in a dynamic environment. For this purpose, a kinematic test was done within a vessel in Obruk Lake Dam in Çorum province, Turkey. The test area was situated in a deep valley and surrounded by high hills covered with dense trees. The real-time coordinates of each measurement epoch were simultaneously determined with Single-baseline RTK, Network RTK, and RTX RT-PPP methods by using three GNSS receivers. The real-time coordinates obtained from both RTK and RT-PPP methods were compared against the post-processed relative solution epoch-by-epoch. The results show that, the 3D position accuracies of real-time methods were found as ±6 cm, ±3 cm and ±7 cm for Single-baseline RTK, Network RTK and RT-PPP methods, respectively. This study demonstrates that although the Network RTK methods provided the best solution among the others, the positioning did not conduct most of the time due to the loss of cellular connection. This was also partially valid for the Single-baseline RTK method because the corrections from the base station via radio-link couldn’t be received due to the rough terrain conditions. However, it was possible to make positioning with RTX Real-time PPP technique using satellite delivery GNSS products (corrections) continuously and in a robust manner within the cm-level accuracy. Our study showed that the use of the global multi-GNSS RTX correction service outcompetes conventional RTK methods with providing consistent, reliable, and seamless cm-level accurate positioning almost without any interruption especially in challenging marine environments with severe terrain obstructions.

Using a calibrated upper living position of marine biota to calculate coseismic uplift: a case study of the 2016 Kaikōura earthquake, New Zealand

Abstract. The 2016 Mw=7.8 Kaikōura earthquake (South Island, New Zealand) caused widespread complex ground deformation, including significant coastal uplift of rocky shorelines. This coastal deformation is used here to develop a new methodology, in which the upper living limits of intertidal marine biota have been calibrated against tide-gauge records to quantitatively constrain pre-deformation biota living position relative to sea level. This living position is then applied to measure coseismic uplift at three other locations along the Kaikōura coast. We then assess how coseismic uplift derived using this calibrated biological method compares to that measured using other methods, such as light detection and ranging (lidar) and strong-motion data, as well as non-calibrated biological methods at the same localities. The results show that where biological data are collected by a real-time kinematic (RTK) global navigation satellite system (GNSS) in sheltered locations, this new tide-gauge calibration method estimates tectonic uplift with an accuracy of ±≤0.07 m in the vicinity of the tide gauge and an overall mean accuracy of ±0.10 m or 10 % compared to differential lidar methods for all locations. Sites exposed to high wave wash, or data collected by tape measure, are more likely to show higher uplift results. Tectonic uplift estimates derived using predictive tidal charts produce overall higher uplift estimates in comparison to tide-gauge-calibrated and instrumental methods, with mean uplift results 0.21 m or 20 % higher than lidar results. This low-tech methodology can, however, produce uplift results that are broadly consistent with instrumental methodologies and may be applied with confidence in remote locations where lidar or local tide-gauge measurements are not available.

Assessment of Centre National d'Études Spatiales Real-Time Ionosphere Maps in Instantaneous Precise Real-Time Kinematic Positioning over Medium and Long Baselines.

Precise real-time kinematic (RTK) Global Navigation Satellite System (GNSS) positioning requires fixing integer ambiguities after a short initialization time. Originally, it was assumed that it was only possible at a relatively short distance from a reference station (<10 km), because otherwise the atmospheric effects prevent effective ambiguity fixing. Nowadays, through the use of VRS, MAC, or FKP corrections, the distances to the closest reference station have been increased to around 35 km. However, the baselines resolved in real time are not as far as in the case of static positioning. Further extension of the baseline requires the use of an ionosphere-weighted model with ionospheric delay corrections available in real time. This solution is now possible thanks to the Radio Technical Commission for Maritime (RTCM) stream of SSR corrections from, for example, Centre National d’Études Spatiales (CNES), the first analysis center to provide it in the context of the International GNSS Service. Then, ionospheric delays are treated as pseudo-observations that have a priori values from the CLK RTCM stream. Additionally, satellite orbit and clock errors are properly considered using space-state representation (SSR) real-time radial, along-track, and cross-track corrections. The following paper presents the initial results of such RTK positioning. Measurements were performed in various field conditions reflecting realistic scenarios that could have been experienced by actual RTK users. We have shown that the assumed methodology was suitable for single-epoch RTK positioning with up to 82 km baseline in solar minimum (30 March 2019) mid and high latitude (Olsztyn, Poland) conditions. We also confirmed that it is possible to obtain a rover position at the level of a few centimeters of precision. Finally, the possibility of using other newer experimental IGS RT Global Ionospheric Maps (GIMs), from Chinese Academy of Sciences (CAS) and Universitat Politècnica de Catalunya (UPC) among CNES, is discussed in terms of their recent performance in the ionospheric delay domain.

Onion Bulb Counting in a Large-scale Field Using a Drone with Real-Time Kinematic Global Navigation Satellite System

Onion Bulb Counting in a Large-scale Field Using a Drone with Real-Time Kinematic Global Navigation Satellite System

Accuracy and precision evaluation of two low-cost RTK global navigation satellite systems

Two low-cost Real-time Kinematic Global Navigation Satellite Systems (RTK GNSSs) being the Emlid “Reach RTK” and the NavSpark “NS-HP” were evaluated in terms of positioning accuracy and precision. Each GNSSs’ rover unit was mounted on a field robot that travelled by manual remote control along a pre-defined test track in six repeated trials. The precision of the two systems was evaluated through F-test statistics.The combined accuracy of the two GNSSs was determined by comparing the positioning data to a fixed known distance between the GNSS antennas on the robot (472 mm). In three out of six trials, both GNSSs remained in fixed solution status, and showed a Root Mean Square Error (RMSE) of less than 50 mm, which was within the expected range. In two other trials, one of the GNSSs started in float solution status, and subsequently transitioned to fixed solution status. In these trials, the RMSE was still well within one meter, which was expected in float solution status. In one trial, a false fixed position status was encountered, where the NavSpark GNSS falsely claimed it was in fixed solution status. This issue needs to be alleviated in the future by improvements in signal conditioning, noise, and software, and/or by sensor fusion. Although the Emlid GNSS had superior localization performance, as its percentage of data in fixed solution status was 94.0% compared to 71.5% for the NavSpark GNSS, both were deemed promising for use on experimental field robots.

Crop Height Monitoring Using a Consumer-Grade Camera and UAV Technology

Recent advances in the ability to capture high spatial resolution images by unmanned aerial vehicles (UAVs) have shown the potential of this technology for a wide range of application including exploring the effects of different external stimuli when monitoring environmental and structural variables. In this paper, we show the application of UAV technology for crop height monitoring and modelling to provide quantitative crop growth data and demonstrate the remote sensing and photogrammetric capabilities of the technology to the farming industry. This study was carried out in a field trial involving a combination of six wheat varieties and three different fungicide treatments. The UAV imagery of the field trial site was captured on five occasions throughout crop development. These were used to create digital surface models from which crop surface models (CSMs) were extracted for the cropped areas. Crop heights are estimated from the photogrammetric derived CSMs and are compared against the reference heights captured using Real-Time Kinematic Global Navigation Satellite System (GNSS) to validate the CSMs. Furthermore, crop growth differences among varieties are analysed; and crop height correlations with grain yield as well as with independently estimated vegetation indices are evaluated. These evaluations show that the technology is suitable (with average bias range 2–10 cm depending on wind conditions relative to GNSS height) and has potential for quantitative and qualitative monitoring of canopy and/or crop height and growth.

Delineation of Agricultural Drainage Pipe Patterns Using Ground Penetrating Radar Integrated with a Real-Time Kinematic Global Navigation Satellite System

Better methods are needed for mapping agricultural drainage pipe systems. Prior research on small test plots indicates that ground penetrating radar (GPR) is oftentimes capable of detecting buried drainage pipes; however, the feasibility of employing this geophysical technique in larger field areas has not been adequately evaluated. Ground penetrating radar integrated with a Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) may be an effective and efficient means of mapping drain lines within agricultural fields. Therefore, GPR-RTK/GNSS was tested in three agricultural settings; with Site 1 and Site 2 located in Beltsville, MD, USA and Site 3 near Columbus, OH, USA. Soils at the three sites ranged from silty clay loam to loamy sand. A GPR unit with 250 MHz antennas was used to detect drainage pipes, and at Sites 1 and 2, a physical GNSS base station was utilized, while a virtual base station was employed at Site 3. The GPR-RTK/GNSS configurations used in this study delineated a complex rectangular drainage pipe system at Site 1, with one set of drainage pipes oriented southwest-northeast and a second oriented southeast-northwest. At Site 2, a herringbone drain line pattern was outlined, and at Site 3, random drain lines were found. When integrated with RTK/GNSS, spiral or serpentine GPR transects (or spiral/serpentine segments of a GPR transects) were utilized to provide insight on drain line directional trends. Consequently, given suitable field conditions, GPR integrated with RTK/GNSS can be a valuable tool for farmers and drainage contractors needing to map subsurface drainage systems.

A Precision Landing Test on Motion Platform and Shipboard of a Tilt-Rotor UAV Based on RTK-GNSS

A precision landing flight test of a tilt-rotor UAV called the TR-60M was performed on shipboard and motion platforms. The ship moved at 10 kt speed on the sea in a sea-state 2 condition, and the motion platform also moved at 10 kt speed between the edges of a runway while simulated with sea-state 2 motion during the flight test. All flight tests were performed using the automatic takeoff, hover, and landing function of TR-60M based on the relative navigation. This is called a real-time kinematic global navigation satellite system (RTK-GNSS). A total of 11 and 10 sorties of automatic takeoff and landing were performed to evaluate the landing accuracy on the running motion platform and shipboard, respectively. The accuracy of the precision landing test satisfied the requirements of shipboard landing in the sea-state 2 condition.

A UAV–RTK Lidar System for Wave and Tide Measurements in Coastal Zones

AbstractA lightweight and low-cost unmanned aerial vehicle (UAV) system for coastal wave and tide measurements is developed. This system is based on an assembly of a multirotor UAV, a robotic lidar, an altitude and heading reference system (AHRS), and a real-time kinematic (RTK) Global Navigation Satellite System (GNSS). A great advantage of the system is that it can be operated at low altitude in a few meters; the accuracy and spatial resolution can therefore be increased. When the system was moved up and down in 2–12 m, the root-mean-square error (RMSE) was approximately 5 cm compared to the ground truth value measured by a manual RTK GNSS. The system was operated in a hover mode to measure the tide and waves in the field. The results of using the UAV–RTK lidar system were consistent with those of in situ measurements using a pressure sensor. The root-mean-square errors between the two techniques for measurements of tidal elevation, significant wave height, and wave period were 4.9 cm, 4.8 cm, and 0.028 s, respectively. This finding suggests the system could be applied to measure instantaneous sea surface displacement. The system provides the potential for using a low-cost, extremely portable, and efficient tool for monitoring wave properties, topographic changes, and water-level gradients in coastal zones.

Analysis of the dynamic characteristics of a suspension bridge based on RTK-GNSS measurement combining EEMD and a wavelet packet technique

To investigate the dynamic characteristics of a self-anchored suspension bridge (i.e. Tianjin Fumin Bridge), a real time kinematic-global navigation satellite system (RTK-GNSS) is used to achieve the displacement responses of the structure. Seeing the defect in the positioning accuracy of RTK-GNSS, a combined method (EEMDWP) of ensemble empirical mode decomposition (EEMD) and wavelet packet (WP) analysis is firstly put forward to improve the precision of the vibration signals. Subsequently, fast Fourier transform and the random decrement technique are applied to estimate the natural frequency and the corresponding damping ratio of the structure. Meanwhile, to contrast the field measurement results, the finite element model (FEM) of the structure is established. Finally, the analysis results indicate that: (1) the RTK-GNSS technique is a powerful tool for monitoring the deformation of long-span bridges; (2) the proposed EEMDWP method is demonstrated to be better than the single EEMD or WP method; (3) the structural dynamic parameters are successfully obtained (i.e. the first natural frequency: 0.5873 Hz, the corresponding damping ratio: 2.12%); (4) the results from the field measurement are in agreement with the FEM with a difference of about 5% from each other.

Development of autonomous navigation system for rice transplanter

Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories. Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous path, which are extremely boring in terms of large-scale fields. The objective of this research was to develop an autonomous navigation system that automatically guided a rice transplanter working along predetermined paths in the field. The rice transplanter used in this research was commercially available and originally manually-operated. An automatic manipulating system was developed instead of manual functions including steering, stop, going forward and reverse. A sensor fusion algorithm was adopted to integrate measurements of the Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) and Inertial Measurement Unit (IMU), and calculate the absolute moving direction under the UTM coordinate system. A headland turning control method was proposed to ensure a robust turning process considering that the rice transplanter featured a small turning radius and a relatively large slip rate at extreme steering angles. Experiments were designed and conducted to verify the performance of the newly developed autonomous navigation system. Results showed that both lateral and heading errors were less than 8 cm and 3 degrees, respectively, in terms of following straight paths. And headland turns were robustly executed according to the required pattern. Keywords: autonomous navigation, rice transplanter, sensor fusion, headland turning DOI: 10.25165/j.ijabe.20181106.3023 Citation: Yin X, Du J, Noguchi N, Yang T X, Jin C Q. Development of autonomous navigation system for rice transplanter. Int J Agric & Biol Eng, 2018; 11(6): 89–94.

Measuring Vegetation Height in Linear Disturbances in the Boreal Forest with UAV Photogrammetry

Monitoring vegetation recovery typically requires ground measurements of vegetation height, which is labor-intensive and time-consuming. Recently, unmanned aerial vehicles (UAVs) have shown great promise for characterizing vegetation in a cost-efficient way, but the literature on specific methods and cost savings is scant. In this study, we surveyed vegetation height on seismic lines in Alberta’s Boreal Forest using a point-intercept sampling strategy, and compared them to height estimates derived from UAV-based photogrammetric point clouds. In order to derive UAV-based vegetation height, we tested three different approaches to estimate terrain elevation: (1) UAV_RTK, where photogrammetric point clouds were normalized using terrain measurements obtained from a real-time kinematic global navigation satellite system (RTK GNSS) surveys; (2) UAV_LiDAR, where photogrammetric data were normalized using pre-existing LiDAR (Light Detection and Ranging) data; and (3) UAV_UAV, where UAV photogrammetry data were used alone. Comparisons were done at two scales: point level (n = 1743) and site level (n = 30). The point-level root-mean-square errors (RMSEs) of UAV_RTK, UAV_LiDAR, and UAV_UAV were 28 cm, 31 cm, and 30 cm, respectively. The site-level RMSEs were 11 cm, 15 cm, and 8 cm, respectively. At the aggregated site level, we found that UAV photogrammetry could replace traditional field-based vegetation surveys of mean vegetation height across the range of conditions assessed in this study, with an RMSE less than 10 cm. Cost analysis indicates that using UAV-based point clouds is more cost-effective than traditional field vegetation surveys.

An investigation of the dynamic characteristics of super high-rise buildings using real-time kinematic–global navigation satellite system technology

This article aims to investigate the dynamic characteristics (e.g. natural frequency and damping ratio) for two super high-rise completed and uncompleted buildings. Real-time kinematic-global navigation satellite system technology is applied to observe the dynamic responses. To improve the positioning accuracy and avoid distortion of the results, a Type 1 Chebyshev high-pass digital filter is used. The natural frequencies and damping ratios of the buildings are determined using the fast Fourier transform analysis and random decrement technique combined with a logarithmic decrement method, respectively. The structural parameters are obtained. The results show that real-time kinematic-global navigation satellite system technology can provide the dynamic responses of super high-rise buildings in an efficient manner and that the dynamic characteristics from field measurements agree well with the results of the numerical simulation.