Real-time Kinematic Global Positioning System Research Articles

Online Calibration for Networked Radar Tracking of UAS

The need for effective tracking mechanisms of small unmanned aircraft systems (sUAS) has become crucial as their use has increased in populated areas. This paper presents a practical tracking solution for sUAS using a network of phased array radars. Achieving optimal system performance while tracking the sUAS requires extrinsic calibration of the individual radar systems to a common frame of reference. We propose a straightforward calibration solution based upon the orthogonal Procrustes formulation that uses radar measurements from ground-mounted radar associated with real-time-kinematic global positioning system (RTK-GPS) data. Two variations of the calibration are provided: a batch processing method, and an online method for real-time adjustments. This paper provides a practical analysis of the advantages and disadvantages associated with both calibration methods. This assessment of the calibration methods, along with an evaluation of the radar network’s sUAS tracking ability, is validated by simulation studies and hardware tests. The hardware experiments especially provide valuable insights into the practical implications of the proposed tracking solution.

Dual-Frequency Multi-Constellation Global Navigation Satellite System/Inertial Measurements Unit Tight Hybridization for Urban Air Mobility Applications

A global navigation satellite system (GNSS) for remotely piloted aircraft systems (RPASs) positioning is essential, thanks to the worldwide availability and continuity of this technology in the provision of positioning services. This makes the GNSS technology a critical element as malfunctions impacting on the determination of the position, velocity and timing (PVT) solution could determine safety issues. Such an aspect is particularly challenging in urban air mobility (UAM) scenarios, where low satellite visibility, multipath, radio frequency interference and cyber threats can dangerously affect the PVT solution. So, to meet integrity requirements, GNSS receiver measurements are augmented/fused with other aircraft sensors that can supply position and/or velocity information on the aircraft without relying on any other satellite and/or ground infrastructures. In this framework, in this paper, the algorithms of a hybrid navigation unit (HNU) for UAM applications are detailed, implementing a tightly coupled sensor fusion between a dual-frequency multi-constellation GNSS receiver, an inertial measurements unit and the barometric altitude from an air data computer. The implemented navigation algorithm is integrated with autonomous fault detection and exclusion of GPS/Galileo/BeiDou satellites and the estimation of navigation solution integrity/accuracy (i.e., protection level and figures of merit). In-flight tests were performed to validate the HNU functionalities demonstrating its effectiveness in UAM scenarios even in the presence of cyber threats. In detail, the navigation solution, compared with a real-time kinematic GPS receiver used as the reference centimetre-level position sensor, demonstrated good accuracy, with position errors below 15 m horizontally and 10 m vertically under nominal conditions (i.e., urban scenarios characterized by satellite low visibility and multipath). It continued to provide a valid navigation solution even in the presence of off-nominal events, such as spoofing attacks. The cyber threats were correctly detected and excluded by the system through the indication of the valid/not valid satellite measurements. However, the results indicate a need for fine-tuning the EKF to improve the estimation of figures of merit and protection levels associated to the navigation solution during the cyber-attacks. In contrast, solution accuracy and integrity indicators are well estimated in nominal conditions.

Application of a Real-Time Field-Programmable Gate Array-Based Image-Processing System for Crop Monitoring in Precision Agriculture

Precision agriculture (PA) technologies combined with remote sensors, GPS, and GIS are transforming the agricultural industry while promoting sustainable farming practices with the ability to optimize resource utilization and minimize environmental impact. However, their implementation faces challenges such as high computational costs, complexity, low image resolution, and limited GPS accuracy. These issues hinder timely delivery of prescription maps and impede farmers’ ability to make effective, on-the-spot decisions regarding farm management, especially in stress-sensitive crops. Therefore, this study proposes field programmable gate array (FPGA)-based hardware solutions and real-time kinematic GPS (RTK-GPS) to develop a real-time crop-monitoring system that can address the limitations of current PA technologies. Our proposed system uses high-accuracy RTK and real-time FPGA-based image-processing (RFIP) devices for data collection, geotagging real-time field data via Python and a camera. The acquired images are processed to extract metadata then visualized as a heat map on Google Maps, indicating green area intensity based on romaine lettuce leafage. The RFIP system showed a strong correlation (R2 = 0.9566) with a reference system and performed well in field tests, providing a Lin’s concordance correlation coefficient (CCC) of 0.8292. This study demonstrates the potential of the developed system to address current PA limitations by providing real-time, accurate data for immediate decision making. In the future, this proposed system will be integrated with autonomous farm equipment to further enhance sustainable farming practices, including real-time crop health monitoring, yield assessment, and crop disease detection.

Structural control on the landscape evolution and avulsive behavior of rivers at mountain exits: The example of the Kosi River in eastern Nepal Himalaya

The Kosi River flows from the eastern Nepal Himalaya into the state of Bihar (India) and has experienced frequent avulsions, causing extensive flood-related damage. Because of this avulsive behavior, the Kosi is called the “Sorrow of Bihar.” The avulsion of 2008 was the most catastrophic avulsion event recorded for the Kosi and has been attributed primarily to hydrological and sedimentological processes that formed a super-elevated river channel and caused avulsion. Detailed topographic analysis of the region near the Kosi exit from the Himalaya, using mean-corrected and resampled 1-arc, Shuttle Radar Topography Mission (SRTM) and Real Time Kinematic Global Positioning System (RTK-GPS) datasets, reveals that the Kosi channel is super-elevated only relative to its eastern floodplain. The western floodplain elevation is similar to or higher than the Kosi channel in the region between the Kosi River exit from the main eastern Nepal Himalaya and the Kosi barrage at the Indo-Nepal border. Structurally, the Kosi exits the Himalaya in the transition zone between the closed Trijuga dun to the west and the Dharan salient to the east. The Trijuga dun is closed by the Main Frontal thrust (MFT)-related frontal topography or the Outer Churia Hills. The eastern slopes of these hills induce west-to-east topographic slope in the channel, such that topographic avulsion indices are highest only in the Outer Churia Hills affected parts of the Kosi Channel and the 2008 avulsion region. Therefore, our preferred model for the primary control on the channel's asymmetric, metastable, super-elevation is the influence of the tectonically controlled MFT-related Outer Churia Hills on the Kosi River channel. Geomorphological processes have operated in the Kosi channel in this backdrop. This study emphasizes that detailed structural and topographic analysis of river exits from mountain belts like the Himalaya can provide better insights into river channel metastability and avulsion worldwide.

A Comprehensive Comparison of Photogrammetric and RTK-GPS Methods for General Order Land Surveying

One of the main objectives of modern-day surveying is to maximize the efficiency and accuracy of mapping a landscape for natural features and elevations prior to the start of a construction project. This paper focuses on a comparison between terrestrial and aerial photogrammetry and real-time kinematic global positioning systems (RTK-GPSs) in terms of elevation accuracy, data expenditure, and time for each survey to be completed. Two sites in San Diego County were chosen to be studied with a combined area of about 1.14 acres, and a total station system was used to establish 572 control points between both areas. Two of the three methods investigated produced similar results in elevation and were well within the established standard, as the terrestrial photogrammetry averaged 0.0583 feet of error, the aerial photogrammetry averaged 0.345 feet of error, and the RTK-GPS averaged 0.0432 feet of error when compared to the total station ground truth. If data consumption is not a concern, the terrestrial photogrammetric method should be preferred to the aerial photogrammetric and RTK-GPS methods in topographic mapping and land monitoring due to the increase in time efficiency and in surface model detail while keeping within the Caltrans specified tolerance of error of 0.2 feet. For general order land surveys, the photogrammetric approach utilized with a Looq scanner would provide the most efficient and cost-effective survey while staying within the 0.2 foot tolerance of error. This method also allows for the utmost clarity of the resulting point cloud when analyzing terrain, break lines, or other features in the survey area.

Compaction quality assessment of highway using roller-integrated positive maximum kinetic energy increment detection technique

During conventional highway construction, quality control and acceptance (QC/QA) are based on limited spot tests of material density at random locations which may not comprehensively represent the entire compacted area and are vulnerable to potential biases. Based on roller-integrated positive maximum kinetic energy increment detection technique with real-time kinematic global positioning systems, this research adopted kinetic energy compaction value (KECV) as a real-time monitoring index for the highway compaction quality, and subsequently proposed an KECV-based assessment method to estimate the compaction quality of subgrade and pavement materials. Additionally, a global interpolation method (Green spline) was adopted to obtain estimates for both KECVs and compaction quality at any location on the work area, enabling the analysis of the passing rate of compaction quality for the entire work area. A case study on the Hengyong highway project in China indicates a highly linear correlation between the KECV and the compaction parameters, the compactness of LLL silt, and the relative density of cement-stabilized macadam; therefore, it can serve as a reliable index for monitoring compaction quality. Assessment of compaction quality on the entire work area can be fast and continuously achieved using the proposed method, which can effectively overcome the above limitation of conventional testing, timely feedback compaction information to avoid quality defects, and availably improve the construction quality of highways.

Vertical Accuracy of Google Earth Data

Digital Elevation Models (DEMs) are an important data source used in many engineering and Geographic Information System (GIS) applications. This paper illustrates a strategy for creating a DEM by utilizing elevation data from Google Earth and evaluating the vertical positional accuracy of the generated DEM adopting a well-defined methodology. To ensure the accuracy of the elevation data obtained from Google Earth, a thorough evaluation was done in three diverse small districts of the northern shoreline in Egypt. The evaluation process involved determining the ground coordinates of reference points utilizing two surveying techniques: total station and Real-Time Kinematic (RTK) Global Positioning System (GPS) surveys. These coordinates were compared with the ones predicated by the DEM generated by putting into service Google Earth's elevation data. Furthermore, the vertical accuracy was assessed using Shuttle Radar Topographic Mission (SRTM) data of Google Earth collected at two different periods in 2015 and 2023. The vertical accuracy of the Google Earth data is detailed utilizing Mean Error (ME), Maximum Absolute Error (MAE), and Root Mean Square Error (RMSE). According to the results, Google Earth's elevation data accuracy remains consistent from 2015 to 2023, and refining SRTM data does not improve the vertical accuracy. The vertical accuracy of the total station survey surpasses the one of the RTK GPS survey, and the elevation accuracy of the RTK GPS survey decreases with increasing height difference. In addition, the vertical accuracy of DEMs was found to be sufficient for some engineering applications but not accurate enough for precise engineering studies. The accuracy achieved in small height difference terrain can be utilized to produce large-scale cadastral maps, city plans, or land use maps. Finally, the elevation data offered by Google Earth can be utilized for preliminary studies at a low cost. However, to ensure the accuracy of these data, it is recommended that users compare them with reference data before implementation.

Enhancing survey field data with artificial intelligence: a real-time kinematic GPS study

Enhancing survey field data with artificial intelligence: a real-time kinematic GPS study

A Conceptual Approach to Harbor Object Detection: The Potential of 3D-LiDAR-based Sensor Fusion for High Precision ENC

In the advancing era of autonomous maritime navigation, the precision of Electronic Nautical Charts (ENCs) is critical. This study conceptualizes a framework to validate and rectify ENCs nearly in real-time, leveraging high-resolution 3D LiDAR, DGPS, and IMU data. The approach of this study includes a domain-specific point cloud filtering, object segmentation, classification in compliance with the S-101 standard classes and a georeferencing strategy. By comparing identified objects against ENC data, this study pinpoints discrepancies and augments the ENCs with up-to-date object information. An evaluation through field tests is proposed, complemented by Traffic Sequence Charts and reference calibration via Realtime Kinematic GPS, ensuring practical relevance of our framework to real-world conditions. The contribution of this paper lies in offering a comprehensive solution for ENC refinement, thereby facilitating safer autonomous navigation by verifying that ENCs are reflective of current environmental conditions.

Delayed Kalman filter for vision-based autonomous flight in ocean environments

This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle, performing autonomous take-off and landing on a moving vessel in ocean environments. The proposed flight hardware is composed of a general-purpose computing module connected to a low-cost inertial measurement, an real-time kinematics GPS, motor speed controller, and a camera, through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading such that the multiple tasks of control, estimation, and communication are executed simultaneously. The proposed flight system is verified with autonomous flight experiments on a United States Naval Academy research vessel operating in Chesapeake Bay. Two types of flight experiments are performed: autonomous flight utilizing real-time kinematics GPS for relative positioning, and vision-based autonomous flight, both for shipboard launch and landing.

Roles of Exposure Time and Geochemical Factors in the Characteristics of the Surface Sediments of the Hwangdo Tidal Flat, Taean, Cheonsu Bay, West Coast of Korea

The Hwangdo tidal flat is an intertidal landform located in Cheonsu Bay, Taean-gun, Chungcheongnam-do, on the west coast of Korea. The topographical characteristics of the semi-enclosed bay on the eastern side of the study area include waterways, sandbars, small islands, and tidal flats. In this study, data were acquired from tide gauges installed on the Hwangdo Bridge, and the height of the ellipsoid was measured using a real-time kinematics global positioning system (RTK-GPS). Digital elevation model (DEM) using Matrice 300 drone data were also acquired after processing. The geochemical sediment characteristics in the study area were analyzed, together with tidal-flat exposure-time characteristics based on environmental factors. Sediment data (n = 107) collected from October 25 to 28, 2022 (Korean local time) were used to classify sediment particles according to Folk and Ward (1957). Sedimentary facies ranged from coarse sand (sand:mud ratio = 9:1) to sandy silt (sZ) followed by muddy sand (mS) and slightly gravelly sandy mud ((g)sM). Total organic carbon (TOC) in the surface sediments was also characterized based on a particle-size analysis. The mean change in tidal height measured at Hwangdo Bridge during the sampling period was ~7.53 m (minimum: −3.86 m, maximum: +3.67 m). Based on the Boryeong’s sea level measurement tide data in 2022, the tidal area in the drone images ranged from 6.362 m2 (0.006 km2) at DEM +4.0 to 4,841,078 m2 (4.841 km2) at DEM −4.0 m, indicating an increase in the tidal-flat area according to the tidal level of up to ~800-fold. The daily average exposure time was 9.0 h (minimum: 1.5 h, maximum: 17.9 h). Based on the results of multivariate analysis using exposure times and a geochemical dataset, four groups were identified: upper, middle, and lower intertidal zones and regions with a relatively high organic-matter concentration. A determination of the main characteristics of the Hwangdo tidal flat according to their spatial distribution showed that, among various environmental factors, changes in the sand or clay sediment composition were determined by community factors. The results of this study demonstrate the four statistically processed groups of marine environmental characteristics in the Hwangdo tidal flats. Changes in sedimentary patterns, rather than in the exposure time, accounted for the differences in the sediment compositions of the upper, middle, and lower stations, a response that is expected to continue.

Utilizing Drone-Based Ground-Penetrating Radar for Crime Investigations in Localizing and Identifying Clandestine Graves.

The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system's performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.

Accurate and Robust Rotation-Invariant Estimation for High-Precision Outdoor AR Geo-Registration

Geographic registration (geo-registration) is a crucial foundation for augmented reality (AR) map applications. However, existing methods encounter difficulties in aligning spatial data with the ground surface in complex outdoor scenarios. These challenges make it difficult to accurately estimate the geographic north orientation. Consequently, the accuracy and robustness of these methods are limited. To overcome these challenges, this paper proposes a rotation-invariant estimation method for high-precision geo-registration in AR maps. The method introduces several innovations. Firstly, it improves the accuracy of generating heading data from low-cost hardware by utilizing Real-Time Kinematic GPS and visual-inertial fusion. This improvement contributes to the increased stability and precise alignment of virtual objects in complex environments. Secondly, a fusion method combines the true-north direction vector and the gravity vector to eliminate alignment errors between geospatial data and the ground surface. Lastly, the proposed method dynamically combines the initial attitude relative to the geographic north direction with the motion-estimated attitude using visual-inertial fusion. This approach significantly reduces the requirements on sensor hardware quality and calibration accuracy, making it applicable to various AR precision systems such as smartphones and augmented reality glasses. The experimental results show that this method achieves AR geo-registration accuracy at the 0.1-degree level, which is about twice as high as traditional AR geo-registration methods. Additionally, it exhibits better robustness for AR applications in complex scenarios.

GPS + Galileo + BDS-3 medium to long-range single-baseline RTK: an alternative for network-based RTK?

AbstractThanks to the development of the real-time kinematic (RTK) algorithm and the emerging Global Navigation Satellite System (GNSS), especially for Galileo and BeiDou-3, reliable positioning accuracy for medium and long-baseline RTK became possible globally. Moreover, with the development of the GNSS receiver hardware, baseline length limitations due to radio-based communications are removed thanks to internet-based communication. In this work, single-baseline RTK, incorporated partial ambiguity resolution with troposphere and ionosphere weighting, using GPS (G), Galileo (E), BeiDou-3 (C3) and multi-GNSS (GE and GEC3), is conducted with real GNSS data of EUREF Permanent GNSS network under three different cutoff angles (10°, 20°, and 30°) for six different lengths of baselines (~50, ~150, ~250, ~350, ~450, and ~550 km). The results show that the multi-GNSS RTK solution significantly contributed to the positioning accuracy and convergence time of the single-system RTK solutions. Based on the results, non-available epoch-wise solutions for the high-degree cutoff angles are more obvious for the single-system RTK, whereas multi-GNSS solutions provide 100% solutions for each cutoff angle and baseline. The results indicate that instantaneous and a few epochs single-epoch ambiguity resolution is feasible for 50, 150, 250 and 350 km baseline lengths for multi-GNSS RTK. Based on the positioning results, horizontal–vertical positioning improvements of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 50%–37%, 40%–35%, 55%–47%, 53%–54%, 57%–49% and 57%–49% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle. For 20° and 30° cutoff angles, the accuracy improvements are much higher. The convergence time improvements (n/e/u) of multi-GNSS RTK (GEC3) compared with the single-system GPS RTK are found as 86/92/75%, 77/67/72%, 75/77/83%, 53/56/52%, 69/49/62%, and 52/45/39% for 50, 150, 250, 350, 450 and 550 km, respectively, under a 10° cutoff angle.

Stochastic modeling with robust Kalman filter for real-time kinematic GPS single-frequency positioning

The centimeter-level positioning accuracy of real-time kinematic (RTK) depends on correctly resolving integer carrier-phase ambiguities. To improve the success rate of ambiguity resolution and obtain reliable positioning results, an enhanced Kalman filtering procedure has been developed. Based on a posteriori residuals of measurements and state predictions, the measurement noise variance–covariance matrix for double-differenced measurements is adaptively estimated, rather than approximated by an empirical function which uses satellite elevation angle as input. Since, in real-world situations, unexpected outliers and carrier-phase outages can degrade the filter performance, a stochastic model based on robust Kalman filtering is proposed, for which the double-differenced measurement noise variance–covariance matrix is computed empirically with a modified version of the IGG (Institute of Geodesy and Geophysics) III method in order to detect and identify outliers. The performance of the proposed method is assessed by two tests, one with simulated data and one with real data. In addition, the performance of F-ratio and W-ratio tests as proxies for the success of ambiguity fixing is investigated. Experimental results reveal that the proposed method can improve the reliability and robustness of relative kinematic positioning for simulation scenarios as well as in a real urban test.

Exploring distinct types of intertidal bars on either side of a small estuary using a multifaceted approach

Multiple intertidal bars are common sedimentary landforms found on low-gradient sandy coasts exposed to low to moderate wave energy with a significant tidal range. However, studying the factors that influence their morphology can be challenging due to limited high-resolution field data and tools for bedform analysis. To address this, a multifaceted approach was used to investigate the morphology of intertidal bars at two adjacent tidal beaches on the north and south coasts of a small estuary on the Lianyungang coast of China. This approach included repeated real-time kinematic-global positioning system (RTK-GPS) leveling, unmanned aerial vehicle (UAV) surveys, surface sediment sampling, satellite remote sensing analysis, and automated bedform analysis. The study revealed two distinct types of intertidal bars on either side of the estuary with similar hydrodynamic settings. The north coast presented low-amplitude ridges (also called ridges and runnels), while the south coast had sand waves. The north coast displayed 2–5 oblique, asymmetrical, and dynamic bars that appeared at the seaward end of the intertidal zone and migrated landward to eventually attach to the steep beach on the landward end of the intertidal zone, representing a life cycle. The south coast had 6–9 parallel, continuous, symmetrical, and stable sand bars occupying the lower part of the intertidal zone. Due to the nearly identical hydrodynamic background, the alongshore variability in sediment supply is suggested as a key factor driving the formation of distinct types of bars.

Real Time Kinematic (RTK) heave as a replacement of Motion Reference Unit (MRU) heave in hydrographic surveying works

Heave is one of the major contributors to errors in water depth measurements. Motion Reference Unit (MRU) measures the heave signal with high-level accuracy as well as other ship motions. Unfortunately, MRU has been reported to have some of drawbacks such as; heave drift error, influence of ship motion dynamic, In addition to its very expensive price Real-Time Kinematic (RTK) GPS uses dual frequency receiver and carrier phase differential technique under kinematic solution and provides very accurate position in all three components in real time. In addition, RTK GPS also calculates the low frequency changes in water level such as tidal oscillation. This research is an attempt to investigate the possibility of using the RTK GPS data to deduce the heave signal from the GPS height (tides - heave) instead of heave from MRU to correct the water depth. Moreover, to examine to what extent, RTK heave can be used as a backup to satisfy the International Hydrographic Organization (IHO) survey order standards. A comparison between the extracted RTK heave and MRU heave signals revealed a good agreement with a strong direct correlation of 0.96. As shown in figure 1 RTK heave as a replacement for MRU heave in hydrographic surveying was statistically validated with the use of a lot of methods of analysis such as Test of the Normality, Paired Samples T Test, Wilcoxon Signed Ranks Test, Heave Signals Frequency Adjustment , Descriptive Statistics for the Two Heave Signals , Descriptive Statistics for Each Signal Individually , Correlation and Trend, Analysis Between the Two Signals, Scatter Diagram and Trend, Standard Deviation and Uncertainty for Soundings, Characteristics of the Difference between Two Signals , Comparing the Surfaces by TIN Model. The results of this analysis provided the possibility of using RTK heave as a replacement for MRU heave in hydrographic surveying. Therefore, RTK GPS is not only used to provide precise position or tidal oscillations but also based on this study, can be used to measure heave accurately to correct the depth satisfying IHO survey standards. Received: 28 January 2023 Accepted: 26 April 2023 Published: 22 May 2023

Mapping subsurface defects and surface deformation along the artificial levee of the Lower Tisza River, Hungary

Artificial levees along alluvial rivers are major components of flood-risk mitigation. This is especially true in the case of Hungary, where more than one-third of the country is threatened by floods and protected by an over 4200-km-long levee system. Most of such levees were built in the nineteenth century. Since then, several natural and anthropogenic processes, such as compaction and erosion, might have contributed to these earth structures' slow but steady deformation. Meanwhile, as relevant construction works were scarcely documented, the structure and composition of artificial levees are not well known. Therefore, the present analysis mapped structural differences, possible compositional deficiencies, and sections where elevation decrease is significant along a 40-km section of the Lower Tisza River. Investigations were conducted using real-time kinematic GPS and ground-penetrating radar (GPR). Onsite data acquisition was complemented with an analysis using a Persistent Scatterer Synthetic Aperture Radar to assess general surface deformation. GPR profiles showed several anomalies, including structural and compositional discontinuities and local features. The GPR penetration depth varied between 3 and 4 m. According to height measurements, the mean elevation of the levee crown decreased by 8 cm in 40 years. However, the elevation decrease reached up to 30 cm at some locations. Sections affected by structural anomalies, compositional changes, and increased surface subsidence are especially sensitive to floods when measurement results are compared with flood phenomena archives.

Structure and topology of a brittle-ductile fault swarm at Crawford Knob, Franz Josef, New Zealand

ABSTRACT We present surface and structural models of a swarm of dm-scale subparallel faults exposed in a ∼2000 m2 glaciated outcrop near Franz Josef Glacier, in the Southern Alps of New Zealand. These structures are inferred to have slipped at ∼20 km depth in the hanging-wall Alpine Schist of the Alpine Fault under conditions that were variably brittle to ductile as the Pacific Plate was tilted and uplifted. Using field mapping, real-time kinematic GPS and digital images from a remotely piloted aircraft system, we have created a digital surface model of the outcrop and orthophotographs at a ground resolution of ∼1 cm to map compositional layering in the metasediments and the array of brittle-ductile faults displacing them. In order of decreasing relative age (and average thickness), displaced markers in the schist include primary psammite and pelite beds, quartz veins, and a deformational foliation. The surface models have been used to create 2-D transects and a 3-D model where faults are projected down-dip, to determine the connectivity, topology and intersection types of the fault swarm. Lithological variations, particularly the interface between pelitic and psammitic schist, were a primary control on the topology of the fault network and the spacing between faults.

Potential of Precise Fertilization through Adoption of Management Zones Strategy to Enhance Wheat Production

The variability in soil properties and crop yield can be overcome by adoption of smart farming practices through interpolation and mapping of spatial variability patterns. Geospatial technologies can be utilized to determine the cause of spatial variability in fields for site-specific application of fertilizer. This study was designed to quantify and identify the spatial variation in soil properties and wheat (Triticum aestivum L.) yield and to delineate prescription maps for precise application of fertilizer in a semi-arid subtropical region of Pakistan. To examine the variability in soil properties on the production of the considered crop, this study comprised two different fields and each field was divided into (20 × 20 m) grids. The samples of soil were collected at 15 cm and 30 cm soil depths before the fertilization to analyze the different soil characteristics i.e., nitrogen (N), electrical conductivity (EC), potassium (K), soil organic matter (SOM), phosphorus (P), and pH. The boundaries of selected fields and grid points were established with a real-time kinematics-global positioning system (RTK-GPS). The soil data were acquired with a soil proximal sensor at a depth of 7 cm after fertilization. The statistical analysis coefficient of variation (CV), geostatistical-analysis-nugget-to-sill ratio (N:S), and the interpolated maps (ArcGIS pro 2.3) were used to characterize the least to moderate variability of soil parameters and yield, demanding site-specific management of fertilizer application. Cluster analysis was conducted using Minitab 21, which classified soil and yield characteristics into five categories: “very good”, “very low”, “good”, “poor”, and “medium”, with an external heterogeneity and internal homogeneity both more than 60%. Significant relationships (p < 0.05) between soil and crop properties were used to develop the management zones (MZs) for the precise application of fertilizer in wheat fields. Significant differences (p < 0.05) in soil nutrients were found in the very high and very low productivity zones at both sampling times, which suggest delineating the MZs for precise application of fertilizer according to the need of crop and soil properties. The results revealed that the optimum number of MZs for the wheat fields was five and there was heterogeneity in the soil nutrients in five MZs. The findings of this study also highlight the necessity of predicting the crop and soil factors by using precision technologies to develop the prescription maps, because sampling and analysis of soil are expensive and time-consuming. Based on the demand of the soil and crops, site-specific fertilization can increase economic and environmental efficiency.