Front Mapping Research Articles

Steam generator efficiency optimization under uncertainty through multi-fidelity modeling

The steam generator is an essential equipment in power plants, and understanding its behavior with the aid of mathematical models allows for improved decision-making aiming toward better efficiency. Well-calibrated models can help identify new operating conditions that lead to efficiency enhancement. Unfortunately, due to the complexity of steam generators, computationally efficient models based solely on energy-mass balance usually present limiting simplifications. Alternatively, computational fluid dynamics can solve reacting flow phenomena but require a great amount of computational time. Purely data-driven models often extrapolate poorly as they do not necessarily contain the physical equations that drive the system’s behavior. In this scenario, the multi-fidelity approach is an attractive solution because it combines physics-grounded representation with a low computational footprint and allows for mapping the efficiency of the steam generator considering uncertainty propagation. This paper presents a multi-fidelity model that simulates the efficiency of a steam generator from the PECÉM power plant. The model is assembled by the sum of two Gaussian processes, trained using one high-fidelity and one low-fidelity dataset. The high-fidelity dataset is formed by the observed operation of the actual power plant at varying operating conditions. These same operating parameters are the input for the energy-mass balance model built using the EBSILON software to generate the low-fidelity dataset. The observed efficiency of the PECÉM power plant ranged from 82.89% to 84.37%, with a mean value of 83.58%. The resulting multi-fidelity model presents a root mean square error of 0.19%, which is six times lower than the error obtained by the energy-mass balance model. This model is then used for global sensitivity analysis and robust optimization. A Pareto front mapping expected efficiency and its confidence level is built by exploring not yet experimented operational points. Finally, data clustering allowed the identification of efficiencies around 86%, which adds 1.63% to the power plant’s maximum level.

Advancing Front Surface Mapping

AbstractWe present Advancing Front Mapping (AFM), a novel algorithm for the computation of injective maps to simple planar domains. AFM is inspired by the advancing front meshing paradigm, which is here revisited to operate on two embeddings at once, becoming a tool for compatible mesh generation. AFM extends the capabilities of existing robust approaches, supporting a broader set of embeddings (star‐shaped polygons) with a direct approach, without resorting to intermediate constructions. Our method only relies on two topological operators (split and flip) and on the computation of segment intersections, thus permitting to compute a valid embedding without solving any numerical problem. AFM is therefore easy to implement, debug and deploy. This article is mainly focused on the presentation of the compatible advancing front idea and on the demonstration that the algorithm provably converges to an injective map. We also complement our theoretical analysis with an extensive practical validation, executing more than one billion advancing front moves on 36K mapping tasks.

A high-resolution calving front data product for marine-terminating glaciers in Svalbard

Abstract. The mass loss of glaciers outside the polar ice sheets has been accelerating during the past several decades and has been contributing to global sea-level rise. However, many of the mechanisms of this mass loss process are not well understood, especially the calving dynamics of marine-terminating glaciers, in part due to a lack of high-resolution calving front observations. Svalbard is an ideal site to study the climate sensitivity of glaciers as it is a region that has been undergoing amplified climate variability in both space and time compared to the global mean. Here we present a new high-resolution calving front dataset of 149 marine-terminating glaciers in Svalbard, comprising 124 919 glacier calving front positions during the period 1985–2023 (https://doi.org/10.5281/zenodo.10407266, Li et al., 2023). This dataset was generated using a novel automated deep-learning framework and multiple optical and SAR satellite images from Landsat, Terra-ASTER, Sentinel-2, and Sentinel-1 satellite missions. The overall calving front mapping uncertainty across Svalbard is 31 m. The newly derived calving front dataset agrees well with recent decadal calving front observations between 2000 and 2020 (Kochtitzky and Copland, 2022) and an annual calving front dataset between 2008 and 2022 (Moholdt et al., 2022). The calving fronts between our product and the latter deviate by 32 ± 65 m on average. The R2 of the glacier calving front change rates between these two products is 0.98, indicating an excellent match. Using this new calving front dataset, we identified widespread calving front retreats during the past four decades, across most regions in Svalbard except for a handful of glaciers draining the ice caps Vestfonna and Austfonna on Nordaustlandet. In addition, we identified complex patterns of glacier surging events overlaid with seasonal calving cycles. These data and findings provide insights into understanding glacier calving mechanisms and drivers. This new dataset can help improve estimates of glacier frontal ablation as a component of the integrated mass balance of marine-terminating glaciers.

Monocular Road Scene Bird’s Eye View Prediction via Big Kernel-Size Encoder and Spatial-Channel Transform Module

A detailed representation of the surrounding road scene is crucial for an autonomous driving system. yellow The camera-based Bird’s Eye View map has been a popular solution to present the surrounding information, due to its low cost and rich spatial context information. Most of the existing methods predict the BEV map based on the depth-estimation or the trivial homography method, which may cause the error propagation and the absence of content. To overcome these drawbacks, we propose a novel end-to-end framework that employs the front monocular image to predict the road layout and vehicle occupancy. In particular, to capture the long-range feature, we redesign a CNN encoder with a large kernel size to extract the image features. For reducing the big difference between the front image features and the top-down features, we propose a novel Spatial-Channel projection module to convert the front map into the top-down space. Additionally, concerning the correlation between front view and top-down view, we propose the Dual Cross-view Transformer module to refine the top-down view feature maps and strengthen the transformation. Extensive evaluations on the KITTI and Argoverse datasets present that the proposed model achieves the state-of-the-art results for both datasets. Furthermore, the proposed model runs in 37 FPS on a single GPU, demonstrating the generation of a real-time BEV map. The code will be published at https://github.com/raozhongyu/BEV_LKA.

Performance assessment and Pareto front mapping of a novel truncated elliptic cavity solar receiver

Cavity-shaped receivers are new alternative heat collection elements for parabolic trough collectors that aim to reduce longwave thermal radiation. This study proposes a novel truncated elliptic receiver with front transparent and back opaque insulation for competitive performance without a vacuum. A novel analytical model, coupled with a ray tracing tool, is introduced to assess and maximize the performance of a standard-scale collector by varying the cavity’s depth, width, truncation fraction, and eccentricity, as well as the tube’s diameter ratio and eccentricity. The results show that the optical efficiency is driving the overall collector’s performance and the ellipse’s aspect ratio and truncation fraction should be set to around 1.5 and 0.42, respectively. The maximum energy and exergy efficiencies are 81.59 and 33.17 % for optical and thermal efficiencies of 90.90 and 89.76 %, respectively. These efficiencies are achieved when the cavity’s half-depth, half-height, truncated fraction, and eccentricity are 55.89 mm, 37.06 mm, 0.395, and 1.0, with tube eccentricity and diameter ratio of 0.16 and 1.063, respectively. The PTC’s energy and exergy efficiencies decrease by increasing the depth of the cavity and the two eccentricities and increase by increasing the truncated fraction and the tube diameter. The two efficiencies increase by 1.69 and 2.54 % when increasing the irradiance level and by 7.40 and 5.65 %, respectively, as the flow rate increases. As the ambient temperature increases, the energy efficiency enhances by 0.7 %, whereas the exergy efficiency degrades by 10.74 %. In contrast, the energy efficiency decreases by 11.59 %, and the exergy efficiency increases by 52.1 % as the inlet fluid temperature increases from 150 to 350 °C.

Bank Risk Literature (1978–2022): A Bibliometric Analysis and Research Front Mapping

This study maps the conceptual structure of the body of knowledge concerning bank risk to understand this research strand better. A bibliometric analysis including 671 publications from January 1978 to October 2022 was conducted to achieve the aim of the study. The analysis of descriptive indicators identifies the main traits of scholars debating bank risk in terms of the annual production of publications; most productive authors, countries, affiliations, and journals; and most cited articles in the dataset. This study performs a co-word analysis by adopting social network analysis tools to analyze the conceptual structure of the dataset. The results highlight growing academic interest in bank risk research topics, especially following the global financial crisis. The bibliometric analysis reveals three main topics concerning the consideration of bank risk: (1) the adoption of risk management and bank risk, (2) the use of bank risk during the financial crisis, and (3) the interrelations between corporate governance and bank risk.

Fast Ocean Front Detection Using Deep Learning Edge Detection Models

Small-scale ocean fronts play a significant role in absorbing the excess heat and CO2 generated by climate change, yet their dynamics are not well understood. Existing in-situ and remote sensing measurements of the ocean have inadequate spatial and temporal coverage to map small-scale ocean fronts globally. Additionally, conventional algorithms to generate ocean front maps are computationally intensive and require data with long lead times. We propose machine learning (ML) models to detect temperature and chlorophyll ocean fronts from unprocessed and radiometrically uncorrected satellite imagery by transfer learning from existing models for edge detection. We use two separate datasets: one based on conventional approaches to ocean front detection, and a second based on human annotated ground truth <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . The deep learning front detection approach significantly reduces the resources and overall lead times needed for detecting ocean fronts. The deep learning models are developed with resource-constrained edge compute platforms like CubeSats in mind, as such platforms can address the spatial and temporal coverage challenges. The highest performing models achieve accuracies of 96% and make predictions in milliseconds using unoptimized desktop CPUs and less than 100 MB of storage; these capabilities are well-suited for CubeSat deployment.

Low-Light Face Recognition and Identity Verification Based on Image Enhancement

After years of development, face recognition is now a relatively perfect technology. It is non-contact, intuitive, simple, accurate, and applicable to complex practical environments. To a certain extent, the application of deep learning has enhanced the accuracy of face recognition. But there are some defects with deep learning in detecting face objects of different types in different environments, calling for further explorations. Therefore, this paper explores the low-light face recognition and identity verification based on image enhancement. Specifically, light processing and Gaussian filtering were adopted to suppress and eliminate the low-light effect of low-light face images. The basic framework and objective function of the existing generative adversarial network (GAN) were modified. By learning the mapping of side and front faces in multi-pose face images in the image space, a cross-pose GAN was established to turn faces of different poses into front faces. The proposed model was proved effective through experiments.

Symplectic microgeometry, IV: Quantization

We construct a special class of semiclassical Fourier integral operators whose wave fronts are symplectic micromorphisms. These operators have very good properties: they form a category on which the wave front map becomes a functor into the cotangent microbundle category, and they admit a total symbol calculus in terms of symplectic micromorphisms enhanced with half-density germs. This new operator category encompasses the semi-classical pseudo-differential calculus and offers a functorial framework for the semi-classical analysis of the Schr\"odinger equation. We also comment on applications to classical and quantum mechanics as well as to a functorial and geometrical approach to the quantization of Poisson manifolds.

B-PO05-175 CONDUCTION VELOCITY MAPPING: VALIDATING TIME ANNOTATION AGNOSTIC METHOD FROM AN OPTICAL MAPPING REFERENCE STANDARD

Mapping cardiac conduction velocity may provide assessment of myocardial substrate, fiber anisotropy and zones of myocardium that may be critical to arrhythmia maintenance. However, validating new methodology is limited by the lack of a true reference standard. Optical mapping provides true local assessment of myocardial depolarization and true wave front mapping. To validate Omnipolar mapping technology derived wave speed (OT-WS) and wave direction (OT-DI) from an optical mapping standard. Optical mapping data was acquired from whole heart rabbit Langendorff model. Waves were produced by electrically stimulating the heart at the edge of the mapping field. Conduction velocity (CV) measurements were performed on a 4 x 4 array of virtual electrodes equally spaced by 2.4 mm, located in the middle of the mapping field. Traditional CV measurement methods based on local activation time (LAT, Dubois, Bayly) produced a gold standard of wave speed (LAT-WS) and direction (LAT-DI). These parameters were compared against OT-WS and OT-DI respectively. Beat to beat variability of speed and direction from both methods were also compared. 3 rabbit hearts experiments and 6 pacing locations were studied. Average OT-WS was 45.2 ± 10.6 cm/s, compared to 48.6 ± 14.6 for LAT_WS. OT-WS variability was comparable to LAT-WS (3.8 cm/s vs. 4.0 cm/s, p=0.85) as well as OT-DI variability versus LAT-DI (5.8° vs. 6.6°, p=0.76). OT measurements of speed and direction are comparable to gold standard in an optical mapping model without the need of LAT annotation. Beat-to-beat stability of OT measurements suggests OT might be superior predictor than LAT-based methods.

Islamic banking efficiency literature (2000–2020): a bibliometric analysis and research front mapping

PurposeThis paper aims to present a citation-based bibliometric review of Islamic banking efficiency literature from 2000 until August 2020 for analyzing the content of the literature and mapping future research directions.Design/methodology/approachUsing bibliometric citation analysis, this study reviews and examines a total of 278 documents from Web of Science (WoS) indexed sources coupled with content analysis.FindingsThe results identified that the growth of Islamic banking efficiency literature has begun to rise since 2008 with an annual growth rate of 12.5% while identifying the most influential aspects of Islamic banking efficiency literature in terms of topics, papers, authors and keywords. The outcomes of science mapping (i.e. co-citation network, bibliometric coupling and co-authorship network) reveal that there are three underlying research streams in Islamic banking efficiency literature: growth of Islamic banking efficiency literature, stability and genuineness of Islamic banking operations and the methods in Islamic banking efficiency literature.Originality/valueTo the best of the knowledge, this is the first bibliometric review paper on Islamic banking efficiency literature. It successfully unveils the scientific mapping of published WoS documents with a future research agenda also proposed based on the review outcomes. These findings can be used in efficiency-related initiatives by managers or regulators for managing Islamic bank operations worldwide.

Optimising Computational Fluid Dynamic Conditions for Simulating Copper Vertical Casting

A 2-D finite volume Computational Fluid Dynamic (CFD) model, using Ansys Fluent vR.1 of a vertically oriented upwards continuous casting (VUCC), was investigated for 8 mm, oxygen free copper (OFCu). The simulations enabled the mapping of the cast OFCu solidification front (SF) interface from liquid to solid. Optimisation of the simulation parameters were investigated which included mesh size and the Ansys specific ‘mushy zone’ constant (Amush), which is used to account for fluid flow dampening at SF within the model. Observations of the SF, the change in fluid volume in the die, the simulation convergence and the total simulation time, revealed that the optimised casting parameters were for mesh size 1×10-4 m and Amush 106 kg/m3s. These parameters were compared with the cast rod and highlighted qualitatively the relationship between grain growth direction and SF position during a casting pulse cycle.

Neural network and computational fluid dynamics modeling for the gelatinization kinetics of instant controlled pressure drop treated parboiled rice

AbstractEffects of treatment pressure (TP) and treatment time (TT) on the degree of gelatinization (DG) and its impact on the quality attributes of instant controlled pressure drop (ICPD) treated parboiled rice were investigated. Water diffusion and gelatinization kinetics were established for controlling the quality attributes of parboiled rice. Fick's second law was implemented for the evaluation of water diffusion kinetics. DG was fitted with first order reaction kinetics, which showed a rising trend of reaction rate constant from 0.03 to 0.05 s−1 with the variation of TP. Simulation of gelatinization temperature front and its effect on the gelatinization kinetics were modeled by applying computational fluid dynamics (CFD) approach. Process modeling of DG as a function of TP, TT, and moisture content (MC) was accomplished on the basis of 3‐7‐1 artificial neural network (ANN) architecture. Parboiled rice treated at 0.6 MPa TP showed the best quality in terms of broken percentage, ease of cooking, micro‐structural characteristics, and improved cooking and pasting properties.Practical applicationInstant controlled pressure drop (ICPD) treated parboiling process is an innovative approach for producing rice with improved quality attributes. Investigation of water diffusion and gelatinization kinetics is a vital aspect in order to control the milling quality of ICPD treated parboiled rice. Further, mapping of gelatinization temperature front is also necessary in order to control DG with the variation of ICPD treatment pressure and time. Therefore, this study was conducted to enumerate the effects of water diffusion and gelatinization kinetics on the quality attributes of ICPD treated parboiled rice.

SPATIO-TEMPORAL THERMAL FRONTS DISTRIBUTION DURING JANUARY-DECEMBER 2018 IN THE MAKASSAR STRAIT: AN IMPORTANT IMPLICATION FOR PELAGIC FISHERIES

Makassar Strait has been identified as an area of interesting studies for marine science and operational fisheries. It provides the unique ocean structures such as topographic feature, the main path of the Indonesia Throughflow (ITF) and dynamics of thermal fronts. The aims of this study were to map the dynamic spatial and temporal of the thermal fronts, and to describe their implications to the pelagic fisheries. We used satellite data of sea surface temperature (SST) for the period of January-December 2018 with spatial and temporal resolutions of 4 km and monthly, respectively. For fishery data, we used sampling data of skipjack tuna fishing ground distributions in October and December 2018. Thermal fronts throughout the year were estimated using a Single Image Edge Detection (SIED) algorithm and the available fishing ground data were overlain on the SST front map. The results showed that the spatial distributions of thermal fronts along Makassar Strait tended to be different every month. However, the thermal fronts were consistently detected near the upwelling area from June to September. Skipjack tuna fishing grounds associated with fish aggregating devices (FADs) developed in the northern area of upwelling in October. Two month later, the FADs and free swimming skipjack fishing grounds again well formed around the same location. It implies that the formation of the thermal fronts after upwelling contributes the positive effect on development of pelagic fishery especially skipjack in Makassar Strait.

Acoustic Wave Propagation in Standing Trees – Part 1. Numerical Simulation

The use of acoustic waves for assessing wood properties in standing trees has been investigated extensively in recent years. Most studies were experimental in nature and limited to direct measurement of wave velocities in trees using a time-of-flight (TOF) method. How acoustic waves propagate in a tree trunk and how tree diameter, species, stand age, and juvenile wood affect wave propagation behavior in standing trees are not well understood. In this study, we examined propagation patterns of acoustic waves in a virtual tree trunk through numerical simulation using COMSOL Multiphysics® software (COMSOL, Inc., Burlington, MA). The simulation was based on the elastic theory of a solid medium with the assumption of an orthotropic material for a standing tree. Extensive acoustic measurements were conducted on green larch log samples to validate the simulation results. Our results showed that the wave front maps of the tree model from numerical simulations were consistent with those obtained through TOF measurements of the log samples, indicating that the simulation results were accurate and reliable. Wave propagation patterns of the tree model revealed that the side surface-generated acoustic wave expanded as a dilatational wave within a 0-to 1.2m transit distance, as the wave moved up along the tree model, the shape of the wave front gradually flattened and the wave eventually transformed into a quasi-plane wave from a 2.4-m transit distance.

Evaluation of interface reflectivity and corneal aberrations following Descemet's stripping automated endothelial keratoplasty.

PURPOSE:This study aims to evaluate visual outcome after Descemet's membrane stripping automated endothelial keratoplasty (DSAEK) and relate to interface and corneal higher-order aberrations (HOAs).MATERIALS AND METHODS:We enrolled 16 eyes of 16 patients (eight males and eight females) in this interventional case series and followed DSAEK operation for about two to 20 months. OCULUS Pentacam, as well as other ophthalmic evaluations in follow-up visits, examined interface reflectivity and HOAs. Statistical relations were analyzed.RESULTS:There was statistically significant correlation between interface reflectivity and best corrected visual acuity (BCVA) (r = 0.56, P = 0.021). Pachymetry (central corneal thickness) and BCVA had a moderate correlation (r = 0.6, P = 0.013). There was no statistically significant correlation between pachymetry and follow-up time (r = −0.36, P = 0.16). Negative correlation between follow-up and interface reflectivity was also not statistically significant (r = −0.24, P = 0.35). Coma had a significant correlation with BCVA in cornea and cornea front maps (r = 0.74, P = 0.009 and r = 0.71, P = 0.013, respectively).CONCLUSION:Significant correlation between interface reflectivity and BSCVA was found, and anterior corneal HOAs are significantly higher than posterior HOAs.

Characterization of six clustered methane-air diffusion microflames through spectroscopic and tomographic analysis of CH* and C2* chemiluminescence

The current study presents an emission spectroscopic investigation of clustered microflames established on a burner consisting of six micro fuel nozzles surrounding a center air nozzle which has been designed for flame synthesis and characterization of microflames. We conducted spectrally resolved measurements of the chemiluminescence of C2* and CH* and compared these results to a tomographic method applied to filtered emission measurements of CH* emission which can yield spatially resolved three dimensional mapping of the flame front. The analysis of the spatial distribution of the integrated band emission of C2* and CH* showed that the emission of both species is generated in the same locations in the flame which are the thin flame sheets shown in the tomography results of CH*. The ratio of the C2* and the CH* emission from the emission spectroscopy measurements was used to determine a corresponding local equivalence ratio through empirically derived correlations for premixed flames reported in literature. The resulting equivalence ratio equals one when the flame zone established at the boundary between fuel and air, indicating that diffusion dominated flame zones are established. Under certain nozzle pitch and flow rate conditions, the equivalence ratio above the center air nozzle inside the merged flame became significantly greater than one, which indicates a local fuel rich premixed type flame zone being established.To determine distributions of rotational and vibrational temperatures throughout the entire flame, we used the spectrally resolved emission from C2* and CH*. The temperature associated with vibrational excitation was different for both species but remained constant throughout the entire flame region and was found no representation of the flame temperature but an artifact of the combustion reactions producing the chemiluminescence. The rotational temperature of di-atomic molecules, however, equilibrates rather quickly with the translational temperature and can accurately represent the gas-dynamic temperature of the flame. The temperature distributions found from the two species agreed qualitatively, the CH* temperature was consistently higher than the C2* temperature by about 200 K. Spatial resolution was assigned to the results from the spectroscopic measurements through a comparison with the tomographically analyzed images of the CH* chemiluminescence.

First steps towards real‐time weather front mapping using routine high‐resolution aircraft‐derived UK observations

First steps towards real‐time weather front mapping using routine high‐resolution aircraft‐derived <scp>UK</scp> observations

Seabird diving behaviour reveals the functional significance of shelf-sea fronts as foraging hotspots.

Oceanic fronts are key habitats for a diverse range of marine predators, yet how they influence fine-scale foraging behaviour is poorly understood. Here, we investigated the dive behaviour of northern gannets Morus bassanus in relation to shelf-sea fronts. We GPS (global positioning system) tracked 53 breeding birds and examined the relationship between 1901 foraging dives (from time-depth recorders) and thermal fronts (identified via Earth Observation composite front mapping) in the Celtic Sea, Northeast Atlantic. We (i) used a habitat-use availability analysis to determine whether gannets preferentially dived at fronts, and (ii) compared dive characteristics in relation to fronts to investigate the functional significance of these oceanographic features. We found that relationships between gannet dive probabilities and fronts varied by frontal metric and sex. While both sexes were more likely to dive in the presence of seasonally persistent fronts, links to more ephemeral features were less clear. Here, males were positively correlated with distance to front and cross-front gradient strength, with the reverse for females. Both sexes performed two dive strategies: shallow V-shaped plunge dives with little or no active swim phase (92% of dives) and deeper U-shaped dives with an active pursuit phase of at least 3 s (8% of dives). When foraging around fronts, gannets were half as likely to engage in U-shaped dives compared with V-shaped dives, independent of sex. Moreover, V-shaped dive durations were significantly shortened around fronts. These behavioural responses support the assertion that fronts are important foraging habitats for marine predators, and suggest a possible mechanistic link between the two in terms of dive behaviour. This research also emphasizes the importance of cross-disciplinary research when attempting to understand marine ecosystems.

Basking sharks and oceanographic fronts: quantifying associations in the north‐east Atlantic

Summary Understanding the mechanisms that link oceanographic processes and marine vertebrate space use is critical to our knowledge of marine ecosystem functioning, and for effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been observed in association with oceanographic fronts – physical interfaces at the transitions between water masses – exploiting foraging opportunities resulting from zooplankton aggregation. However, the scale, significance and variability of these associations have not previously been established. Here, we quantify the influence of thermal and chlorophyll‐a fronts on basking shark habitat use in the north‐east Atlantic. We use animal‐mounted archival tracking together with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to shark movements. We investigate levels of association with fronts occurring over two spatio‐temporal scales, (i) broad‐scale, seasonally persistent frontal zones and (ii) contemporaneous thermal and chl‐a fronts. Using random walk simulations and logistic regression within an iterative generalized linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Oceanographic metrics time‐matched to shark tracks indicate that sharks show a preference for productive regions and associate with contemporaneous thermal and chl‐a fronts more frequently than could be expected at random. Moreover, we highlight the importance of front persistence and cross‐frontal temperature step, which appear to interact to affect the degree of prey aggregation along thermal fronts in this shelf‐sea system. Our findings confirm that surface frontal activity is a predictor of basking shark presence in the north‐east Atlantic, both over seasonal timescales and in near real‐time. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the region.