Unmanned Aerial Vehicle Surveys Research Articles

Surveys of Large Waterfowl and Their Habitats Using an Unmanned Aerial Vehicle: A Case Study on the Siberian Crane

Waterfowl surveys, especially for endangered waterfowl living in wetlands, are essential to protect endangered waterfowl and to create a management scenario of their habitats. Unmanned aerial vehicles (UAVs) are powerful new tools for waterfowl surveys. In this paper, we propose one method for a habitat survey and another for a waterfowl species distribution survey. The habitat survey method obtained the waterfowl’s habitat and spatial distribution with a UAV automatic flight plan in the aggregation area. The waterfowl species distribution survey was used to detect and identify waterfowl species with high-spatial-resolution images from a free UAV flight plan in the aggregation area or areas where individuals were suspected to be present. The UAV-based data showed not only the area where waterfowl were found, but also additional ground surveys. The results showed that the species and locations of the waterfowl were recorded more accurately and efficiently using the distribution method based on the images from the UAV. The waterfowl habitat type and the number of waterfowl were obtained in detail using the habitat survey method. UAV-derived counts of waterfowl were greater (+37%) than ground counts. The results indicated the feasibility and advantages of using a low-cost UAV survey of large waterfowl in wetland regions with complex vegetation. This study provides one case study of large waterfowl numbers and habitat surveys. The UAV-based methods also provide a feasible and scientific way to obtain basic data for the protection and management of waterfowl.

GIS-Based Landslide Susceptibility Mapping of the Circum-Baikal Railway in Russia Using UAV Data

The investigation of hard-to-reach areas that are prone to landslides is challenging. The research of landslide hazards can be significantly advanced by using remote sensing data obtained from an unmanned aerial vehicle (UAV). Operational acquisition and high detail are the advantages of UAV data. The development of appropriate automated algorithms and software solutions is necessary for quick decision-making based on the received heterogeneous spatial data characterising various aspects of the environment. This article introduces the first phase of a long-term study about landslide detection and prediction that aims to develop an automatic algorithm for detecting potentially hazardous landslide areas, using data obtained by UAV surveys. As a part of the project, the selection of appropriate techniques was implemented and a landslide susceptibility (LS) map of the study site was developed. This paper presents the outcomes of the applied indirect heuristic approach of landslide susceptibility assessment using an analytical hierarchy process (AHP) in a GIS environment, based on UAV data. The results obtained have been tested on a real-world entity.

How do landscape elements affect public health in subtropical high-density city: The pathway through the neighborhood physical environmental factors

Purposes of this study are to explore associations between neighborhood landscape elements and public health in a subtropical high-density urban context, elucidate mediating effects of physical environmental factors, and propose corresponding neighborhood renewal strategies.Nine sampling sites were selected in Guangzhou, China, and public health data were collected from 438 participating residents using the MOS item short from health survey (SF-36 scale). Landscape elements of the neighborhoods, including greenness, blue spaces, walking trail systems, public squares, garden architecture, and dedicated sports spaces were mapped by unmanned aerial vehicle surveys. Seven physical environmental factors were measured: the heat stress index (HSI), relative humidity (RH), average wind speed (AWS), negative oxygen ions (NOI), <2.5 μM particulate matter (PM2.5), illumination (I), and noise (N). General linear models were used to explore differences between neighborhoods in landscape elements. Relationships between public health and both landscape elements and physical environmental factors, as well as the mediating pathways involved, were explored by correlation analysis and Mediation analyses.In subtropical high-density neighborhood, I, RH, HSI, NOI, and PM2.5 were significantly correlated with public health in the neighborhoods, as were greenness, blue spaces, walking trail systems, and public squares. Multiple mediation analysis showed that greenness, blue spaces and public squares significantly affected public health, with mediation by I, HSI and NOI. Landscape elements have close associations with public health, mainly mediated by effects on light, thermal, and atmospheric environments. These closely related landscape elements and physical environments need careful attention in neighborhood renewal efforts.

Rapid lake Michigan shoreline changes revealed by UAV LiDAR surveys

The recent record-breaking Laurentian Great Lakes water levels have led to severe erosion along many shorelines, but quantification of this erosion has not yet been widely reported. In this paper, novel shoreline measurements of Lake Michigan erosion, using a LiDAR-equipped unmanned aerial vehicle (UAV). The vehicle surveyed two beaches, Dune Acres and Beverly Shores, along the Indiana shoreline of southern Lake Michigan over the period 2018–2019, which are compared to existing aircraft-based LiDAR surveys. The UAV surveys reveal extensive shoreline erosion and recession at both beaches since the low water conditions of 2012–2013, with both beaches losing 70.7 and 64.8 m3/m of dry beach volume. Shoreline recession over this period was nearly 35 m for both beaches. In the period 2018–2019, the UAV measurements reveal continued beach erosion and the transition of beach topography to a steep, actively eroding foredune. Storm erosion resolved by short-interval surveys highlight the episodic nature of shoreline erosion, with 8 m3/m of material lost over a stormy two-week period at Dune Acres. While large, the erosion and recession observed at both beaches is in keeping with limited historical observations of shoreline change during high water episodes. However, the observed overall shoreline recession slopes of 1:29 (water level rise : recession) are much less than historical slopes, suggesting that the beaches are not yet in equilibrium with the high water levels and that erosion will continue in the foreseeable future while lake levels remain high.

Seasonal Surface Change of Urumqi Glacier No. 1, Eastern Tien Shan, China, Revealed by Repeated High-Resolution UAV Photogrammetry

The seasonal surface changes of glaciers in Tien Shan have seen little prior investigation despite the increase in geodetic studies of multi-year changes. In this study, we analyzed the potential of an Unmanned Aerial Vehicle (UAV) to analyze seasonal surface change processes of the Urumqi Glacier No. 1 in eastern Tien Shan. We carried out UAV surveys at the beginning and the end of the ablation period in 2018. The high-precision evolution of surface elevation, geodetic mass changes, surface velocity, and terminus change in the surveyed ablation area were correspondingly derived in combination with ground measurements, including stake/snow-pit observation and GPS measurement. The derived mean elevation change in the surveyed ablation area was −1.64 m, corresponding to the geodetic mass balance of approximately −1.39 m w.e. during the ablation period in 2018. The mean surface velocity was 3.3 m/yr and characterized by the spatial change of the velocity, which was less in the East Branch than in the West Branch. The UAV survey results were a little less than those from the ground measurements, and the correlation coefficient was 0.88 for the surface elevation change and 0.87 for surface displacement. The relative error of the glacier terminus change was 4.5% for the East Branch and 6.2% for the West Branch. These results show that UAV photogrammetry is ideal for assessing seasonal glacier surface changes and has a potential application in the monitoring of detailed glacier changes.

THE STUDY OF THE “CETUS” UNMANNED AERIAL VEHICLE FOR TOPOGRAPHIC AERIAL SURVEYING

The work aims to analyze and study the possibilities of using “Cetus” unmanned aerial vehicle (UAV) for performing topographic aerial surveys. The authors developed and tested aircraft-type UAV for topographic aerial photography. The studies were conducted on a specialized landfill, at which there is an appropriate number of situational points whose coordinates are determined with high accuracy. These points were used as both reference and control points. The obtained UAV aerial survey materials were subjected to a phototriangulation process to determine the orientation elements and to analyze, first and foremost, the angular orientation elements. The surveying was carried out on a mountainous territory, where the spatial coordinates of 37 situational points were determined by the method of ground-based GPS survey with an average accuracy of up to 0.05 m. These points were used as reference and control points. Aerial photography was performed in such a way that the scale of the images was as uniform as possible. The design solutions implemented in the Cetus UAV provide all the possibilities to perform aerial surveys of territories in strict compliance with the projected flight parameters. UAV equipment provides the necessary real-time correction of the position of the aerial camera. At the same time the optimum straightness of routes, stability of scales and mutual overlapping of pictures is reached. Regarding the accuracy of obtaining the spatial coordinates of the points of terrain objects, using “Cetus” UAV surveys, plans can even be made on a scale of even 1: 1000. As a result of the creation of the UAV “Cetus”, it became possible to perform the topographic aerial survey of the territories and to create large-scale orthophotos that fully meet the instructions. As a result of testing the “Cetus” UAV, it can be used in production processes when drawing up topographic plans for a large-scale series: 1: 1000 – 1: 5000, which will significantly save the cost of performing topographic work.

Influence of Sand Trapping Fences on Dune Toe Growth and Its Relation with Potential Aeolian Sediment Transport

This study provides insights into dune toe growth around and between individual brushwood lines of sand trapping fences at the dune toe of coastal dunes using digital elevation models obtained from repeated unmanned aerial vehicle surveys. Prevailing boundary conditions, especially sediment supply, as well as the porosity and arrangement of the installed sand trapping fences significantly influence the effectiveness of different configurations of sand trapping fences. The dune toe growth is significant immediately after constructing a new sand trapping fence and decreases over time. According to the results presented in this study, for sand trapping fences that have been in place longer, the protruding branch height and the porosity of the remaining branches play a minor role in trapping sand. Sand trapping fences with lower permeability favour localized coastal dune toe growth directly at their brushwood lines, whereas fences with higher porosity allow for more sediment deposition further downwind. The trend in dune toe changes can be roughly predicted by integrating potential sediment transport rates calculated with hourly meteorological data.

Evaluating the capability of a UAV‐borne spectrometer for soil organic carbon mapping in bare croplands

AbstractHigh‐resolution, field‐scale soil organic carbon (SOC) mapping in croplands is crucial for effective and precise agricultural management. Recent developments in unmanned aerial vehicles (UAVs) combined with miniaturized visible–near infrared spectrometers have enabled the rapid and low‐cost field‐scale SOC mapping. However, a field‐specific spectrotransfer model is often needed for such UAV‐based hyperspectral measurements, implying local sampling and model development are still required, and this hampers the widespread application of UAV‐based methods. In this study, we aim to test to what extent SOC prediction models derived from an existing regional soil spectral library (SSL) can be applied to UAV‐based hyperspectral data, without the need for additional field sampling. To this end, an UAV survey was conducted over a bare cropland within the Belgian Loam Belt for field‐scale SOC mapping. We evaluated two calibration approaches, one based on local sampling and model development, and one where we capitalized on an existing (laboratory‐based) regional SSL. For the local calibration approach, we obtained a good prediction performance with RMSE of 0.57 g kg−1 and RPIQ of 2.35. For the regional model, a spectral alignment procedure was needed to resolve the discrepancy between UAV‐ and laboratory‐based measurements. This resulted in a fair SOC prediction accuracy with RMSE of 0.93 g kg−1 and RPIQ of 1.45. The comparison of SOC maps derived from the two approaches, along with an external validation showed a high consistency, indicating that UAV‐based spectral measurements, in combination with SSLs have the potential to improve the efficiency of high‐resolution SOC mapping.

Assessment of the landslide process intensity on the bank of the Kuybyshev Reservoir using instrumental methods

The aim of the work was to survey and monitor dangerous exogeodynamic processes on the shoreline of the Kuibyshev reservoir. Field instrumental studies were used as the main method, including topo-geodetic survey of key morphological elements of the slope with ground control points, video and photo recording of the processes. Since 2019, unmanned aerial vehicle surveys have been chosen as the main method of research. The paper presents the results of long-term studies of the local landslide near Tetyushi, Republic of Tatarstan. As a result of 2003-2006 situational plans processing and results of UAV survey in 2019 quantitative data on the intensity of slope processes in the mass landslide were obtained.

Light-Weight Unmanned Aerial Vehicle Surveys Detect Dugongs and Other Globally Threatened Marine Species from the Andaman and Nicobar Islands, India

Light-Weight Unmanned Aerial Vehicle Surveys Detect Dugongs and Other Globally Threatened Marine Species from the Andaman and Nicobar Islands, India

Zoometric data extraction from drone imagery: the Arabian oryx (Oryx leucoryx)

SummaryData extraction from unmanned aerial vehicle (UAV) imagery has proved effective in animal surveys and monitoring, but to date has scarcely been used for detailed population analysis and individual animal feature extraction. We assessed the zoometric and feature extraction of the Arabian oryx (Oryx leucoryx) using data acquired from a captive population for comparison with reintroduced populations monitored by UAVs. Highly accurate scaled and geo-rectified imagery derived from UAV surveys allowed precise morphometric measurements of the oryx. The scaled top-view imagery combined with baseline data from known sex, age, weight and pregnancy status of captive individuals were used to develop predictive models. A bracketed index developed from the predictive models showed high accuracy for classifying the age group ≤16 months, animals with a weight &gt;80 kg and pregnancy. The pregnancy classification decision tree model performed with 91.7% accuracy. The polynomial weight predictive model performed well with relatively high accuracy when using the total top-view surface measurement. Photogrammetrically processed UAV-acquired imagery can yield valuable zoometric data, feature extraction and modelling; it is a tool with a practical application for field biologists that can assist in the decision-making process for species conservation management.

A screening approach for the correction of distortion in UAV data for coral community mapping

Unmanned Aerial Vehicle (UAV) may provide us super resolution data, however, they are often captured with artefacts and distortion. To investigate impact of distortion on the coral reef information, UAV surveys were deployed using multispectral sensor over two reefs in Bidong Island (Malaysia). Band-specific analysis of distortion revealed five different types of distorted images from the acquisition. This study optimized screening distorted images by comparing the seven distortion correction approaches and validated coral classification maps based on machine learning algorithms [support vector machine (SVM), random forest (RF) and artificial neural network (ANN)]. Results indicate that the screening the green band (b2) alone or the blue band (b1) combined with b2 of UAV data and SVM capable of generating the best coral classification maps, with an overall accuracy of 7–17% improved compared to that of orthomosaic without distortion correction. The proposed distortion correction method can be applied to similar coral environments. Highlights Five different types of artefacts and distortions found in UAV data. A optimized screening approach suggested to minimized image distortion. Distortion corrected data and SVM algorithm performed the best in coral habitat mapping. An overall accuracy of 7–17% improved compared to that of distortion uncorrected maps. A new photogrammetric contribution to the existing automatic orthorectification techniques.

Time of day impact on mapping agricultural subsurface drainage systems with UAV thermal infrared imagery

Due to economic and environmental considerations, there exists a need for effective, efficient, and nondestructive methods for locating buried agricultural drainage pipes. Previous research indicates that thermal infrared (TIR) imagery obtained with an unmanned aerial vehicle (UAV) has potential for mapping agricultural subsurface drainage systems, thereby warranting further investigation to determine the best time of day to conduct these UAV TIR surveys. Accordingly, a set of sunrise to sunset UAV TIR surveys were carried out at four different farm field sites in Ohio, U.S.A. Late morning through late afternoon UAV TIR surveys were generally found to work well for determining drainage system patterns. During late morning through late afternoon, the apparent radiant temperature of the soil surface over the drain lines was higher than between the drain lines (i.e., emitted TIR radiation from the soil surface over a drain line was greater than between the drain lines). Conversely, near sunrise or sunset, the UAV surveys often showed the apparent radiant temperature of the soil surface over the drain lines to be lower than between the drain lines (i.e., less emitted TIR radiation over the drain lines than between drain lines). Some excellent UAV TIR drainage mapping results were obtained near sunrise/sunset due to TIR drain line responses that were more easily distinguished from those of farm field operations. However, difficulties were occasionally encountered processing this sunrise/sunset TIR imagery, likely due to the impact on image quality from high relative humidity during these times of the day. Consequently, strictly on a consistency of success basis alone, late morning through late afternoon are the best times for locating drainage pipes with UAV TIR surveys; however, in certain cases, UAV TIR surveys at sunrise/sunset can provide exceptional drainage pattern recognition. These results provide valuable guidance for those considering UAV TIR drainage mapping surveys.

Comparative Analysis of Stockpile Volume Estimation using UAV and GPS Techniques

Mining operations involve the extraction of minerals of economic value from the earth. In surface mining operations, overburdens need to be stripped in other to reach the ore. Large volumes of waste as well as ore is stripped in the process. Various technologies have been used to aid in stockpile volume estimation. Notable among them are the Total Stations and Global Positioning Systems (GPS). However, labour, safety and time has challenged the use of these technologies. Unmanned Aerial Vehicle (UAV), commonly known as drone is an emerging technology for stockpile volume computations in the Mine. UAV technology for data collection is less labour intensive, safer and faster. Therefore, this study applied the UAV technology in an open pit to estimate stockpile volumes from a Mine. For the purpose of this study, GPS and UAV data were collected for measuring stockpile volumes of materials mined. The actual volumes of stockpiles A, B, C, D (Case 2), produced differences of 0.05% for A, 0.05% for B, 0.08% for C, 0.07% for D and 0.03% for A, -0.03% for B, 0.03% for C and 0.04% for D, for the GPS-based and the UAV-based techniques, respectively. The GPS-based technique generated moderate accuracies for volume estimation, but was time consuming and labour intensive, compared to the UAV-based technique; which was faster and less labour intensive. The UAV-based technique was the most accurate, safest and is capable of mapping large areas rapidly. It is therefore recommended that UAV survey be incorporated in stockpile volume estimation.&#x0D; Keywords: UAV, GPS, Stockpile, Mine, Total Stations

APPLICATION OF UAV SURVEYS FOR EVALUATING THE PRODUCTIVITY LEVELS OF TRADITIONAL AND MECHANISED FARMERS IN A CUSTOMARY LAND TENURE SYSTEM

Abstract. In most of Nigeria’s rural communities, land holdings are small and uneven; and this impacts significantly on their mechanisation potentials. This fragmented nature of the farmlands also inhibits the creation of an effective land market. This study utilised a digital orthomosaic generated from an Unmanned Aerial Vehicle (UAV) survey in evaluating the productivity levels of traditional and mechanised farmers in Okeho Community of Oyo State, South-Western Nigeria. The aerial survey was conducted with a DJI Phantom 4 Professional UAV covering 250 acres of traditional and mechanised farmlands to produce a very high resolution orthomosaic at 6 cm spatial resolution. Sixty-three respondents (61 traditional farmers and 2 mechanised farmers) were also interviewed using questionnaires. Their responses were keyed into a database with the Open Data Kit (ODK) data collector. The orthomosaic was classified into farmland units and a database of the farmers land holdings was created in ArcGIS software. Some parameters influencing their productivity were computed – Crop Field Fraction (CFF) and Crop Yield Index (CYI). The results showed that very few farmers had a shared equity on land (only 3%); most farms were acquired under freehold or lease. Also, only 1% of their farm sizes was larger than 5 acres. There was a sharp disparity in the crop field fraction (traditional farms – 32.2; mechanised farms – 68.8), and the productivity from the mechanised farmers surpasses that of the traditional farmers. It is recommended that the Government should support cluster farming systems among farmers to boost productivity.

Spatio-Temporal Estimation of Biomass Growth in Rice Using Canopy Surface Model from Unmanned Aerial Vehicle Images

The awareness of spatial and temporal variations in site-specific crop parameters, such as aboveground biomass (total dry weight: (TDW), plant length (PL) and leaf area index (LAI), help in formulating appropriate management decisions. However, conventional monitoring methods rely on time-consuming manual field operations. In this study, the feasibility of using an unmanned aerial vehicle (UAV)-based remote sensing approach for monitoring growth in rice was evaluated using a digital surface model (DSM). Approximately 160 images of paddy fields were captured during each UAV survey campaign over two vegetation seasons. The canopy surface model (CSM) was developed based on the differences observed between each DSM and the first DSM after transplanting. Mean canopy height (CH) was used as a variable for the estimation models of LAI and TDW. The mean CSM of the mesh covering several hills was sufficient to explain the PL (R2 = 0.947). TDW and LAI prediction accuracy of the model were high (relative RMSE of 20.8% and 28.7%, and RMSE of 0.76 m2 m−2 and 141.4 g m−2, respectively) in the rice varieties studied (R2 = 0.937 (Basmati370), 0.837 (Nipponbare and IR64) for TDW, and 0.894 (Basmati370), 0.866 (Nipponbare and IR64) for LAI). The results of this study support the assertion of the benefits of DSM-derived CH for predicting biomass development. In addition, LAI and TDW could be estimated temporally and spatially using the UAV-based CSM, which is not easily affected by weather conditions.

Evaluating Short-Term Tidal Flat Evolution Through UAV Surveys: A Case Study in the Po Delta (Italy)

The use of Unmanned Aerial Vehicles (UAV) on wetlands is becoming a common survey technique that is extremely useful for understanding tidal flats and salt marshes. However, its implementation is not straightforward because of the complexity of the environment and fieldwork conditions. This paper presents the morphological evolution of the Po della Pila tidal flat in the municipality of Porto Tolle (Italy) and discusses the reliability of UAV-derived Digital Surface Models (DSMs) for such environments. Four UAV surveys were performed between October 2018 and February 2020 on an 8 ha young tidal flat that was generated, amongst others, as a consequence of the massive sediment injection into the Po Delta system due to the floods of the 1950s and 1960s. The DSM accuracy was tested by processing (i.e., photogrammetry) diverse sets of pictures taken at different altitudes during the same survey day. The DSMs and the orthophotos show that the tidal flat is characterised by several crevasse splays and that the sediment provision depends strictly on the river. During the study period, the sediment budget was positive (gaining 800 m3/year and an average rate of vertical changes of 1.3 cm/year). Comparisons of DSMs demonstrated that neither lower flight altitudes (i.e., 20–100 m) nor the combination of more photos from different flights during the same surveys necessarily reduce the error in such environments. However, centimetric errors (i.e., RMSEs) are achievable flying at 80–100 m, as the increase of GCP (Ground Control Point) density is the most effective solution for enhancing the resolution. Guidelines are suggested for implementing high-quality UAV surveys in wetlands.

Assessment of the Influence of Survey Design and Processing Choices on the Accuracy of Tree Diameter at Breast Height (DBH) Measurements Using UAV-Based Photogrammetry

This work provides a systematic evaluation of how survey design and computer processing choices (such as the software used or the workflow/parameters chosen) influence unmanned aerial vehicle (UAV)-based photogrammetry retrieval of tree diameter at breast height (DBH), an important 3D structural parameter in forest inventory and biomass estimation. The study areas were an agricultural field located in the province of Málaga, Spain, where a small group of olive trees was chosen for the UAV surveys, and an open woodland area in the outskirts of Sofia, the capital of Bulgaria, where a 10 ha area grove, composed mainly of birch trees, was overflown. A DJI Phantom 4 Pro quadcopter UAV was used for the image acquisition. We applied structure from motion (SfM) to generate 3D point clouds of individual trees, using Agisoft and Pix4D software packages. The estimation of DBH in the point clouds was made using a RANSAC-based circle fitting tool from the TreeLS R package. All trees modeled had their DBH tape-measured on the ground for accuracy assessment. In the first study site, we executed many diversely designed flights, to identify which parameters (flying altitude, camera tilt, and processing method) gave us the most accurate DBH estimations; then, the resulting best settings configuration was used to assess the replicability of the method in the forested area in Bulgaria. The best configuration tested (flight altitudes of about 25 m above tree canopies, camera tilt 60°, forward and side overlaps of 90%, Agisoft ultrahigh processing) resulted in root mean square errors (RMSEs; %) of below 5% of the tree diameters in the first site and below 12.5% in the forested area. We demonstrate that, when carefully designed methodologies are used, SfM can measure the DBH of single trees with very good accuracy, and to our knowledge, the results presented here are the best achieved so far using (above-canopy) UAV-based photogrammetry.

Capturing hedgerow structure and flowering abundance with UAV remote sensing

AbstractHedgerows are an abundant and ecologically important feature of many rural areas. Their biodiversity value depends on composition, structure and availability of food resources, which can be significantly impacted by poor management. However, information about hedgerow condition is very limited due to field surveys being costly and labour‐intensive. Unmanned aerial vehicles (UAVs) equipped with miniaturized cameras could prove a more cost‐effective and time‐efficient hedgerow surveying solution while preserving a high level of detail unattainable with airborne or satellite sensors. This study explored whether UAV remote sensing is a viable alternative for performing hedgerow condition surveys at local scale, focusing on hedgerow structure and flowering abundance. We acquired UAV Red, Green and Blue (RGB) and multispectral nadir and oblique imagery of structurally different hedgerows and used them to generate 3D point clouds and models with SfM workflow. Height thresholding allowed extraction of hedgerow extents, with root‐mean‐square error (RMSE) of height and width ranging from 0.11 to 0.23 m. RGB flower classification showed poor relationship with ground measurements (R2 = 0.31–0.42) due to confusion with woody material of hedgerows. Inclusion of a near‐infrared channel in multispectral imagery significantly improved the relationship (R2 = 0.68–0.75, RMSE = 10%). Our study shows UAV remote sensing has high potential for performing detailed surveys of hedgerows, providing better characterization of structural variations and distribution of flowers than traditional ground surveys due to larger coverage. More comprehensive understanding of hedgerow, or other vegetated buffer strips, conditions offered by UAV surveys can enable better informed decisions on habitat management and biodiversity conservation in rural areas. Acquisitions over larger areas, potentially integrated with satellite remote sensing, can allow assessment of hedgerow connectivity over farm to landscape scales, contributing to better understanding of the hedgerow network and its role as a wildlife corridor.

Reactivation of Magma Pathways: Insights From Field Observations, Geochronology, Geomechanical Tests, and Numerical Models

AbstractField observations and unmanned aerial vehicle surveys from Caldera Taburiente (La Palma, Canary Islands, Spain) show that pre‐existing dykes can capture and re‐direct younger ones to form multiple dyke composites. Chill margins suggest that the older dykes were solidified and cooled when this occurred. In one multiple dyke example, an 40Ar/39Ar age difference of 200 kyr was determined between co‐located dykes. Petrography and geomechanical measurements (ultrasonic pulse and Brazilian disc tests) show that a microscopic preferred alignment of plagioclase laths and sheet‐like structures formed by non‐randomly distributed vesicles give the solidified dykes anisotropic elastic moduli and fracture toughness. We hypothesize that this anisotropy led to the development of margin‐parallel joints within the dykes, during subsequent volcanic loading. Finite element models also suggest that the elastic contrast between solidified dykes and their host rock elevated and re‐oriented the stresses that governed subsequent dyke propagation. Thus, the margin‐parallel joints, combined with local concentration and rotation of stresses, favored the deflection of subsequent magma‐filled fractures by up to 60° to form the multiple dykes. At the edifice scale, the capture and deflection of active intrusions by older ones could change the organization of volcanic magma plumbing systems and cause unexpected propagation paths relative to the regional stress. We suggest that reactivation of older dykes by this mechanism gives the volcanic edifice a structural memory of past stress states, potentially encouraging the re‐use of older vents and deflecting intrusions along volcanic rift zones or toward shallow magma reservoirs.