Real-time Kinematic Global Navigation Satellite Research Articles

An efficient method for modeling and evaluating the bench terrain of open-pit mines

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.

Modified RTK-GNSS for Challenging Environments.

Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) is currently the premier technique for achieving centimeter-level accuracy quickly and easily. However, the robustness of RTK-GNSS diminishes in challenging environments due to severe multipath effects and a limited number of available GNSS signals. This is a pressing issue, especially for GNSS users in the navigation industry. This paper proposes and evaluates several methodologies designed to overcome these issues by enhancing the availability and reliability of RTK-GNSS solutions in urban environments. Our novel approach involves the integration of conventional methods with a new technique that leverages surplus satellites-those not initially used for positioning-to more reliably detect incorrect fix solutions. We conducted three tests in densely built-up areas within the Tokyo region. The results demonstrate that our approach not only surpasses the fix rate of the latest commercial receivers and a popular open-source RTK-GNSS program but also improves positional reliability to levels comparable to or exceeding those of the aforementioned commercial technology.

GNSS and LiDAR Integrated Navigation Method in Orchards with Intermittent GNSS Dropout

Considering the vulnerability of satellite positioning signals to obstruction and interference in orchard environments, this paper investigates a navigation and positioning method based on real-time kinematic global navigation satellite system (RTK-GNSS), inertial navigation system (INS), and light detection and ranging (LiDAR). This method aims to enhance the research and application of autonomous operational equipment in orchards. Firstly, we design and integrate robot vehicles; secondly, we unify the positioning information of GNSS/INS and laser odometer through coordinate system transformation; next, we propose a dynamic switching strategy, whereby the system switches to LiDAR positioning when the GNSS signal is unavailable; and finally, we combine the kinematic model of the robot vehicles with PID and propose a path-tracking control system. The results of the orchard navigation experiment indicate that the maximum lateral deviation of the robotic vehicle during the path-tracking process was 0.35 m, with an average lateral error of 0.1 m. The positioning experiment under satellite signal obstruction shows that compared to the GNSS/INS integrated with adaptive Kalman filtering, the navigation system proposed in this article reduced the average positioning error by 1.6 m.

Implementation of Proximal and Remote Soil Sensing, Data Fusion and Machine Learning to Improve Phosphorus Spatial Prediction for Farms in Ontario, Canada

One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to accurately reveal the spatial heterogeneity of P. Seven spatially variable fields located in Ontario, Canada are clustered into two zones; four fields are located in eastern Ontario and three others are located in western Ontario. This study compares Bayesian Additive Regression Trees (BART), Support Vector Machine regressor (SVM), and Ordinary Kriging (OK), along with novel data fusion concepts, to analyze integrated high-density spatial data layers related to spatial variability in soil available P. Feature selection and interaction detection using BART variable selection and Recursive Feature Elimination (RFE) for SVM were applied to 42 predictors, including soil-vegetation indices derived from PlanetScope multispectral imagery, high-density apparent soil electrical conductivity (ECa), and high-resolution topographic attributes derived from DUALEM-21S and a Real-Time Kinematic (RTK) global navigation satellite systems (GNSS) receiver, respectively. Modeling spatial heterogeneity of soil available P with BART showed higher accuracy than SVM and OK in both zones of this study when trained and tested on ground truth data from clusters of farms. A BART variable selection approach resulted in six auxiliary predictors of soil available P in the eastern zone, while only four predictors were selected to predict P in the western zone. RFE for SVM resulted in models with 15 and 12 auxiliary predictors in the eastern and western Ontario zones. Topographic elevation was the most influential predictor of soil available P in both zones. Compared with the SVM and OK methods, BART exhibited lower average RMSE values for individual fields of 1.86 ppm and 3.58 ppm across the eastern and western Ontario zones, respectively, along with higher R2 values of 0.85 and 0.83, respectively. In contrast, SVM had RMSE values for individual fields in the eastern and western Ontario zones, respectively, averaging 5.04 ppm and 7.51 ppm and R2 values of 0.27 and 0.43. RMSE values for soil available P in individual fields across the eastern and western Ontario zones averaged 4.77 ppm and 7.81 ppm, respectively, with the OK method, while R2 values averaged 0.19 and 0.44. The selection of suitable auxiliary predictors and data fusion, combined with BART spatial machine learning algorithms, have potential to be a useful tool to accurately estimate spatial patterns in soil available P for agricultural fields in Ontario, Canada.

Dynamic rail wear measurement: integration of RTK GNSS, IMU, and laser

Currently, laser sensors are widely utilized in railway systems for monitoring rail wear. However, the lack or insufficiency of rail waist data poses a challenge to accurately match profiles and calculate wear. In this paper, we propose a novel approach for dynamic rail wear monitoring that comprises three major modules: a filtering methodology to smooth rail profile data, fine compensation to calibrate the angle distortion, and fast profile alignment. Initially, the AF technique and Kalman filter are applied to reconstruct the profile. This is followed by integrating real-time kinematic global navigation satellite system, inertial measurement unit, and laser to precisely correct the rail profile dynamic distortion. Additionally, genetic algorithms-least squares method is used for rapid determination of the R20mm center of the profile. Rigorous testing and trials have demonstrated that our proposed approach achieves precision as low as 0.03 mm with significant potential in dynamic rail wear monitoring.

Integration of carbon dioxide sensor with GNSS receiver for dynamic air quality monitoring applications

Air pollution is a significant problem in big cities due to the rapid increase of anthropogenic activities and severe traffic congestion. Therefore, real-time and micro tools for air monitoring are urgently necessary for fast and better policy decision-making. The current city air monitoring tool is typically static and serves a macro area. This study introduces technology development to integrate the air quality sensor with the satellite-based navigation receiver. This study used a carbon dioxide (CO2) MH-Z19C sensor and real-time kinematic global navigation satellite system (RTK GNSS) U-Blox F9P with GNSS Trimble NetR9 receiver. The field air quality monitoring (CO2 observed in ppm) and the movement velocity (vehicle speed observed in km/h) were recorded on two main roads of Jakarta by using a survey vehicle. The study compares the observation results of the non-integrated system (NIS) and integrated technology system (IS). The two systems generated the CSV database (CO2 and vehicle speed); however, IS generated the automatic synchronized and error-free data output. The statistical regression analysis of CSV data (CO2 and vehicle speed) between the NIS and IS reported significant results, which means both are reliable. Still, the NIS did not require manual synchronization, with some possibility of error. The R square values show a significant gap (speed 0.99 over CO2 0.144), indicating that IS needs further development as the CO2 data varies due to technicality. The finding presents that integrating the CO2 sensor and GNSS receiver generates a more effective time synchronization process and a reliable error removal technique in developing the CSV data. This finding is a significant reference in developing the integrated satellite-based receiver system with external environmental sensors.

Experimental Study of Seamless Switch Between GNSS- and LiDAR-Based Self-Localization

A self-localization method that can seamlessly switch positions and attitudes estimated using normal distributions transform (NDT) scan matching and a real-time kinematic global navigation satellite system (GNSS) is successfully developed. One of the issues encountered in this method is the sharing of global coordinates among the different estimation methods. Therefore, the three-dimensional environmental maps utilized in the NDT scan matching are created based on the planar Cartesian coordinate system used in the GNSS to obtain accurate information regarding the location, shape, and size of the actual terrain and geographic features. Consequently, seamlessly switching between different methods enables mobile robots to stably obtain accurate estimated positions and attitudes. An autonomous driving experiment is conducted using this self-localization method in the Tsukuba Challenge 2022, and the mobile robot completed a designated course involving more than 2 km in an urban area.

Design and Experiment of a Breakpoint Continuous Spraying System for Automatic-Guidance Boom Sprayers

Repeated and missed spraying are common problems during the working of boom sprayers, especially in the breakpoint continuous process. Therefore, the present study investigated a breakpoint continuous spraying system for automatic-guidance boom sprayers based on a hysteresis compensation algorithm for spraying. An operational breakpoint identification algorithm, which combines a real-time kinematic global navigation satellite system (RTK-GNSS) and wheel odometer, was proposed; a pre-adjusted proportional-integral-derivative (PID) control algorithm for the opening degree of the proportional control valve was designed in thus study. Tests were conducted to establish equations correlating the opening degree of the proportional control valve, pump output flow rate, and main pipeline flow rate, with an R2 ≥ 0.9525. The time to adjust to the target flow rate was experimentally tested. The breakpoint identification accuracy of the RTK-GNSS and RTK-GNSS + wheel odometer was experimentally assessed. A field spraying deposition variation experiment was conducted. According to the results, the system effectively eliminated missed spraying, with a maximum repeated spraying distance of ≤3.3 m, and it achieved a flow control error within 3%. This system also reduced the repeated spraying area and enhanced the pesticide spraying quality of breakpoint continuous spraying for automatic-guidance boom sprayers.

A Multi-Scale Anti-Multipath Algorithm for GNSS-RTK Monitoring Application.

During short baseline measurements in the Real-Time Kinematic Global Navigation Satellite System (GNSS-RTK), multipath error has a significant impact on the quality of observed data. Aiming at the characteristics of multipath error in GNSS-RTK measurements, a novel method that combines improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and adaptive wavelet packet threshold denoising (AWPTD) is proposed to reduce the effects of multipath error in GNSS-RTK measurements through modal function decomposition, effective coefficient sieving, and adaptive thresholding denoising. It first utilizes the ICEEMDAN algorithm to decompose the observed data into a series of intrinsic mode functions (IMFs). Then, a novel IMF selection method is designed based on information entropy to accurately locate the IMFs containing multipath error information. Finally, an optimized adaptive denoising method is applied to the selected IMFs to preserve the original signal characteristics to the maximum possible extent and improve the accuracy of the multipath error correction model. This study shows that the ICEEMDAN-AWPTD algorithm provides a multipath error correction model with higher accuracy compared to singular filtering algorithms based on the results of simulation data and GNSS-RTK data. After the multipath correction, the accuracy of the E, N, and U coordinates increased by 49.2%, 65.1%, and 56.6%, respectively.

High-precision plant height measurement by drone with RTK-GNSS and single camera for real-time processing

Conventional crop height measurements performed using aerial drone images require 3D reconstruction results of several aerial images obtained through structure from motion. Therefore, they require extensive computation time and their measurement accuracy is not high; if the 3D reconstruction result fails, several aerial photos must be captured again. To overcome these challenges, this study proposes a high-precision measurement method that uses a drone equipped with a monocular camera and real-time kinematic global navigation satellite system (RTK-GNSS) for real-time processing. This method performs high-precision stereo matching based on long-baseline lengths (approximately 1 m) during the flight by linking the RTK-GNSS and aerial image capture points. As the baseline length of a typical stereo camera is fixed, once the camera is calibrated on the ground, it does not need to be calibrated again during the flight. However, the proposed system requires quick calibration in flight because the baseline length is not fixed. A new calibration method that is based on zero-mean normalized cross-correlation and two stages least square method, is proposed to further improve the accuracy and stereo matching speed. The proposed method was compared with two conventional methods in natural world environments. It was observed that error rates reduced by 62.2% and 69.4%, for flight altitudes between 10 and 20 m respectively. Moreover, a depth resolution of 1.6 mm and reduction of 44.4% and 63.0% in the error rates were achieved at an altitude of 4.1 m, and the execution time was 88 ms for images with a size of 5472 × 3468 pixels, which is sufficiently fast for real-time measurement.

Impact of Additional Antenna Groundplanes on RTK-GNSS Positioning Accuracy of UAVs

Abstract. Precise position information is important for terrestrial and airborne surveying systems, such as unmanned aerial vehicles (UAVs). Those systems often rely on real-time kinematic (RTK) global navigation satellite systems (GNSSs) for position determination, where the GNSS antenna mounting environment impacts the GNSS position accuracy to a great extent. This paper investigates the impact of different supplementary groundplane shapes, sizes, and materials on multi-band patch and helical GNSS antennas at both, the UAV rover and RTK base station with respect to the achievable position accuracy. The groundplanes consist of solid aluminum sheets or copper plated printed circuit boards (PCBs) and are mounted directly underneath the GNSS antennas. Appropriate supplementary groundplanes are found to significantly improve the GNSS position accuracy in the majority of test cases.

An Experiment in Determining the High-water Mark

As a boundary of the seashore, the high-water mark (HWM) is relevant to the public, the State, and other rights holders in the coastal zone. Unlike most fixed property boundaries that are surveyed and beaconed, the HWM is subject to dynamic natural coastal processes and moves over time. Its location is difficult to determine, and the precision of this determination is unknown. This paper reports on an experiment to measure the precision (variability/repeatability) of the location of the HWM at a variety of sites near Cape Town, by volunteer participants. Four sites were chosen along stable (non-mobile) shores along the open, high energy oceanic shores south of Cape Town on the Cape Peninsula. One of these sites exhibits large variation in coastal terrain and type – at this site three sets of measurements were undertaken, bringing the total number of experimental sites to six. Surveying was undertaken in the South African national control survey system using network real-time kinematic global navigation satellite systems (GNSS).
 This experiment shows that the professional land surveyors located the HWM to ±1,6m, coastal engineers to ±4,1m, and the group of ‘others’ to ±4,2m. The professional land surveyors determined the height of the HWM to ±0,4m over all sites, compared to ±0,7m for all participants. The HWM is likely to be about 4 - 5m above the lowest astronomic tide. However, the line is not a contour – it is affected by weather and local variations in the coastline such as slope and seashore composition. The averaged heights of the HWM at each of the sites for all participants showed a range of 1,3m. Since the boundaries of the seashore cannot be determined with precision, property, cadastral and environmental law needs to continue to respect the nature of this environment and the limitations of locating the HWM.

Performance tests of geodetic receivers with tilt sensors in obstructed environments using the NRTK GNSS technique

Abstract The Department of Lands (DOL), Thailand, has adopted the Network-based Real-Time Kinematic (NRTK) Global Navigation Satellite System (GNSS) surveying technique using a Virtual Reference Station (VRS) to support cadastral surveys since 2011. Determining accurate coordinates of parcel boundary markers at building corners or near fences and walls is difficult because a GNSS range pole cannot be leveled with a circular bubble. This study aims to evaluate the performance of the receivers equipped with tilt sensors for horizontal and vertical positioning. Two types of tilt sensors used for evaluation were a magnetometer and micro-electro-mechanical system (MEMS) and an inertial measurement unit (IMU). Conducting the NRTK GNSS surveying tests was based on the pole tilt angles of 0°, 15°, 25°, 35°, and 45° from a plumb line in controlled and obstructed environments. The IMU-based tilt sensor had more advantage of accurately positioning over the MEMS sensor. The results showed that using the IMU, better than 4 cm horizontal positioning accuracy was achievable when the pole was tilted by 15° or less under non-multipath and open-sky conditions. The vertical accuracy was of a few centimeter levels and least sensitive to tilt angles using either type of sensor. However, none of the sensors precisely compensated for pole tilt in strong-multipath and complex environments, causing increased horizontal errors in decimeter levels.

Under the Sand: Navigation and Localization of a Micro Aerial Vehicle for Landmine Detection with Ground-Penetrating Synthetic Aperture Radar

Ground-penetrating radar mounted on a micro aerial vehicle (MAV) is a promising tool to assist humanitarian landmine clearance. However, the quality of synthetic aperture radar images depends on accurate and precise motion estimation of the radar antennas as well as generating informative viewpoints with the MAV. This paper presents a complete and automatic airborne ground-penetrating synthetic aperture radar (GPSAR) system. The system consists of a spatially calibrated and temporally synchronized industrial grade sensor suite that enables navigation above ground level, radar imaging, and optical imaging. A custom mission planning framework allows generation and automatic execution of stripmap and circular GPSAR trajectories controlled above ground level as well as aerial imaging survey flights. A factor graph based state estimator fuses measurements from dual receiver real-time kinematic (RTK) global navigation satellite system (GNSS) and an inertial measurement unit (IMU) to obtain precise, high-rate platform positions and orientations. Ground truth experiments showed sensor timing as accurate as 0.8 µs and as precise as 0.1 µs with localization rates of 1 kHz. The dual position factor formulation improves online localization accuracy up to 40 % and batch localization accuracy up to 59 % compared to a single position factor with uncertain heading initialization. Our field trials validated a localization accuracy and precision that enables coherent radar measurement addition and detection of radar targets buried in sand. This validates the potential as an aerial landmine detection system.

Inventory of natural processes with nautical charts, real-time kinematic global navigation satellite systems (RTK-GNSS), and unmanned aerial vehicle (UAV), Trindade Island, Brazil

The volcanic Trindade Island is a remote Brazilian offshore territory in the South Atlantic, located ca. 1.140 kilometers east of the southeast coast of Brazil. The island’s permanent exposure to geological hazards requires assessment. However, the lack of erosion and landslides temporal data impedes predictive geohazard analyses. Therefore, we compiled pre-existing data from nautical charts and surveyed the surface terrain on Trindade Island to generate Digital Terrain Models (DTMs) and comparative accuracy analyses. The DTM based on pre-existing data shows the lowest accuracy (root mean square error - RMSE: 12.3 m) yet is adequate for regional studies. In contrast, the DTM developed from real-time kinematic global navigation satellite systems (RTK-GNSS) has the highest vertical accuracy (RMSE: 0.48 m), but spatial variability of ground elements was underestimated and limited to meter-sized (and larger) elements. The DTM obtained using the unmanned aerial vehicle (UAV) with ground control points (GCP), on the other hand, presented lower accuracy (RMSE: 2.37 m) than the RTK-GNSS model but still allowed observation of centimetric (and larger) ground features. For geohazard assessment on Trindade Island, models that allow fine-scale studies are needed. A UAV with GCP provides such standards and proved to be the most viable option in remote and complex sites as well. Hence, this study, the first to allow multi-temporal analysis of geohazard assessment on Trindade Island, offers a viable solution for similar analyses in other remote locations.

DIFFERENCES BETWEEN 2009 AND 2016 REVISIONS BASED ON COORDINATES IN GDM2000

The Geocentric Datum of Malaysia (GDM200) is realised with respect to International Terrestrial Reference Frame (ITRF) 2000 at epoch 2nd January 2000. In comparison with the 2000 frame, ITRF2014 has significant improvement in terms of its definition and realisation. Moreover, several great earthquakes that struck the Indonesian region for the past decades have deformed the tectonic plate, resulting in a shifted GDM2000. These earthquakes, followed by post-seismic activities, has caused GDM2000 to become obsolete. Following that, the Department of Survey and Mapping Malaysia (DSMM) has taken the initiative to revise the coordinate of Malaysia Real-Time Kinematic Global Navigation Satellite Systems (GNSS) Network (MyRTKnet) stations in GDM2000 into a new set of coordinates. Therefore, this paper presents an effort to analyse the differences between coordinates in GDM2000 based on 2009 and 2016 revisions. In order to measure the discrepancy, forty-seven (47) MyRTKnet stations in Peninsular Malaysia were chosen to estimate the differences between the two (2) revisions. The coordinates obtained from MyRTKnet stations were then projected into Rectified Skewed Orthomorphic (RSO) coordinate system to compute the differences in horizontal position and ellipsoidal height. The finding showed that the discrepancy ranges from 0.8 to 11.8 cm, with the smallest values at SETI station and the biggest value at KRAI station. Meanwhile, for the differences in ellipsoidal height, LIPI station has the biggest value of 8.1 cm, followed by the smallest value of 0.4 cm at SETI station. In conclusion, as the differences in revision gave impact on the changes of coordinates of MyRTKnet stations in Peninsular Malaysia, the frequent revision of GDM2000 should also consider the latest frame to give better positional accuracy, and a proper datum transformation (ITRF2014 to ITRF2000) need to be implemented for mapping purposes.

Dynamic monitoring of an offshore jacket platform based on RTK-GNSS measurement by CF-CEEMDAN method

Offshore platforms are constantly exposed to dynamic forces by winds, waves, currents and earthquakes, which can easily lead to damage to the platforms during their serviceable lifetime. The real-time and continuous dynamic monitoring of offshore platforms in service plays an important role in reducing the risk of structural failure, instability and even destruction. In this study, a two-step approach was presented to capture the dynamic response of an offshore jacket platform based on the real-time kinematic global navigation satellite system (RTK-GNSS), which combines a Chebyshev filter and complementary ensemble empirical mode decomposition with adaptive noise (hereinafter referred to as CF-CEEMDAN). In the first step, the RTK-GNSS technique was employed to measure the dynamic displacements of the offshore platform under ambient excitations. Different from traditional accelerators, this technique has no unavoidable errors caused by double integration and directly measures the real-time and continuous dynamic displacements of the offshore platform at site. Next, a CF-CEEMDAN filter was developed to weaken the influence of the background noise in the RTK-GNSS signals. In the second step, the natural excitation technique and eigensystem realization algorithm (NExT-ERA) was applied to estimate the modal parameter (i.e. the first natural frequency) of the platform with filtered RTK-GNSS signals. In order to evaluate the efficiency of the proposed approach, a nonlinear signal with additive noise was firstly introduced to assess the effect of the CF-CEEMDAN method, and a finite element model of the platform was established to predict the natural frequency for comparison. The results prove that the CF-CEEMDAN filter not only has a better noise reduction effect than single CF or CEEMDAN method but also effectively improve the accuracy of RTK-GNSS technique to monitor the dynamic displacements of offshore platforms. Furthermore, the natural frequency obtained by experiment and NExT-ERA analysis is consistent with the predicted value based on finite element model.

UAV-based very high resolution point cloud, digital surface model and orthomosaic of the Chã das Caldeiras lava fields (Fogo, Cabo Verde)

Abstract. Fogo in the Cabo Verde archipelago off western Africa is one of the most prominent and active ocean island volcanoes on Earth, posing an important hazard both to local populations and at a regional level. The last eruption took place between 23 November 2014 and 8 February 2015 in the Chã das Caldeiras area at an elevation close to 1800 ma.s.l. The eruptive episode gave origin to extensive lava flows that almost fully destroyed the settlements of Bangaeira, Portela and Ilhéu de Losna. During December 2016 a survey of the Chã das Caldeiras area was conducted using a fixed-wing unmanned aerial vehicle (UAV) and real-time kinematic (RTK) global navigation satellite system (GNSS), with the objective of improving the terrain models and visible imagery derived from satellite platforms, from metric to decimetric resolution and accuracy. The main result is a very high resolution and quality 3D point cloud with a root mean square error of 0.08 m in X, 0.11 m in Y and 0.12 m in Z, which fully covers the most recent lava flows. The survey comprises an area of 23.9 km2 and used 2909 calibrated images with an average ground sampling distance of 7.2 cm. The dense point cloud, digital surface models and orthomosaics with 25 and 10 cm resolutions, a 50 cm spaced elevation contour shapefile, and a 3D texture mesh, as well as the full aerial survey dataset are provided. The delineation of the 2014/15 lava flows covers an area of 4.53 km2, which is smaller but more accurate than the previous estimates from 4.8 to 4.97 km2. The difference in the calculated area, when compared to previously reported values, is due to a more detailed mapping of the flow geometry and to the exclusion of the areas corresponding to kīpukas (outcrops surrounded by lava flows). Our study provides a very high resolution dataset of the areas affected by Fogo's latest eruption and is a case study supporting the advantageous use of UAV aerial photography surveys in disaster-prone areas. This dataset provides accurate baseline data for future eruptions, allowing for different applications in Earth system sciences, such as hydrology, ecology and spatial modelling, as well as to planning. The dataset is available for download at https://doi.org/10.5281/zenodo.4718520 (Vieira et al., 2021).

PHOTOGRAMMETRIC MAPPING FROM HIGH-RESOLUTION STEREO IMAGERY AND COMPARATIVE ANALYSIS USING EXISTING DATA

The launch of the very high resolution (VHR) sensor satellites has paved the way for further exploitation of the capabilities of stereo satellite imagery for many applications and most importantly in the extraction of topographical details. Advances in digital technologies in the photogrammetric technique provide more accurate and up to date topographic representation, while traditional methods of topographic mapping are time-consuming and require large technical support. This paper explores the methods of production and an analysis of the capabilities of the high-resolution stereo imaging system for the extraction of features (topographic map) and generation of digital elevation model (DEM). This study uses high-resolution GeoEye-1 stereo pair images. For qualitative assessment, topographic features were extracted by digitizing the georeferenced stereo pair images and overlapped to form a DEM and orthophoto within the Summit Evolution software. Georeferencing was carried out using the existing Ground Control Points (GCPs) and Check Points (CPs) established using Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) technique. For quantitative assessment, a total of 7 existing GCPs were considered suitable for use and 5 CPs were established as a check for accuracy of the output. The accuracy of the CPs was evaluated by computing Root Mean Square Error (RMSE). The average horizontal RMSE for the left image and right image were 1.17150098m and 0.819334672m respectively and the average vertical RMSE was 1.605898565m. Additionally, the standard deviation for elevation data from generated DEM using photogrammetric technique and existing elevation data of RTK-GNSS technique were computed, which resulted in 15.91286667 and 16.59529228 respectively. The accuracy was evaluated by comparing the results of the data extracted using stereo satellite images and those extracted from ground measurement techniques (Total station and RTK-GNSS). The comparative analysis showed that stereo pair images provide a viable alternative to other ground mapping techniques providing results within the acceptable range. Based on error estimation and analysis, it concludes that, if strict photogrammetric processing model and ground control points are employed, high-resolution satellite imagery can be used for the accurate generation and update of the topographic maps, DEM and digital orthophotos, which can be further be used as a reference for comparative analysis applications.

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.