Depth Distribution Research Articles

Investigation on meshing characteristics of spiral bevel gear under wear fault evolution with assembly errors

Spiral bevel gears have the advantage of transmitting high torque and power comparing to helical gear and straight bevel gear. However, they are susceptible to wear due to factors such as high loads, poor lubrication, and surface imperfections resulting from machining. In this study, we propose an autonomous model for predicting tooth wear and analyze the meshing characteristics of spiral bevel gear (SBG) pairs under different assembly errors. Concurrently, we establish a finite element model to validate the accuracy of our meshing characteristic analyses. We also compare the distribution patterns of wear depth on the tooth surface with existing literature. Our investigation delves into meshing characteristics, encompassing transmission errors and Time-varying mesh stiffness (TVMS), considering wear evolution under assembly errors. The results demonstrate that the fluctuations in TVMS remain consistent across all four types of assembly errors examined. Gear tooth wear leads to an increase in gear backlash and fluctuations in unloaded transmission error. The meshing stiffness fluctuation of the SBG pair enlarges under wear evolution. Assembly errors result in shifts in the initial contact line and contact pattern, subsequently altering the distribution of wear depth. Different forms of assembly errors may cause a similar effect on the distribution of wear depth and meshing characteristics.

Simulation of 69 microbial communities indicates sequencing depth and false positives are major drivers of bias in prokaryotic metagenome-assembled genome recovery.

We hypothesize that sample species abundance, sequencing depth, and taxonomic relatedness influence the recovery of metagenome-assembled genomes (MAGs). To test this hypothesis, we assessed MAG recovery in three in silico microbial communities composed of 42 species with the same richness but different sample species abundance, sequencing depth, and taxonomic distribution profiles using three different pipelines for MAG recovery. The pipeline developed by Parks and colleagues (8K) generated the highest number of MAGs and the lowest number of true positives per community profile. The pipeline by Karst and colleagues (DT) showed the most accurate results (~ 92%), outperforming the 8K and Multi-Metagenome pipeline (MM) developed by Albertsen and collaborators. Sequencing depth influenced the accurate recovery of genomes when using the 8K and MM, even with contrasting patterns: the MM pipeline recovered more MAGs found in the original communities when employing sequencing depths up to 60 million reads, while the 8K recovered more true positives in communities sequenced above 60 million reads. DT showed the best species recovery from the same genus, even though close-related species have a low recovery rate in all pipelines. Our results highlight that more bins do not translate to the actual community composition and that sequencing depth plays a role in MAG recovery and increased community resolution. Even low MAG recovery error rates can significantly impact biological inferences. Our data indicates that the scientific community should curate their findings from MAG recovery, especially when asserting novel species or metabolic traits.

Depth profiling of implanted D in silicates: Contribution of solar wind protons to water in the Moon and terrestrial planets

The solar wind protons implanted in silicate material and combined with oxygen are considered crucial for forming OH/H O on the Moon and other airless bodies. This process may also have contributed to hydrogen delivery to planetary interiors through the accretion of micrometre-sized dust and planetesimals during early stages of the Solar System. This paper experimentally investigates the depth distribution of solar wind protons in silicate materials and explores the mechanisms that influence this profile. We simulated solar wind irradiation by implanting 3 keV D ions in three typical silicates (olivine, pyroxene, and plagioclase) at a fluence of sim 1.4 × 10 ions/cm . Fourier transform infrared spectroscopy was used to analyse chemical bond changes, while transmission electron microscopy (TEM) characterised microstructural modifications. Nanoscale secondary ion mass spectrometry (NanoSIMS) was employed to measure the D/ O ratio and determine the depth distribution of implanted deuterium. The newly produced OD band (at 2400–2800 cm –1 ) in the infrared spectrum reveals the formation of O–D bonds in the irradiated silicates. The TEM and NanoSIMS results suggest that over 73<!PCT!> of the implanted D accumulated in fully amorphous rims with a depth of 70 nm, while 25<!PCT!> extended inwards to sim 190 nanometres, resulting in partial amorphisation. The distribution of these deuterium particles is governed by the collision processes of the implanted particles, which involve factors such as initial energy loss, cascade collisions, and channelling effects. Furthermore, up to 2<!PCT!> of the total implanted D penetrated the intact lattice via diffusion, reaching depths ranging from hundreds of nanometres to several micrometres. Our results suggest that implanted solar wind protons can be retained in silicate interiors, which may significantly affect the hydrogen isotopic composition in extraterrestrial samples and imply an important source of hydrogen during the formation of terrestrial planets.

Evaluating interseismic deformation patterns in the North Tabriz Fault (Iran) using enhanced fitting of velocity field and analysis of surface deformation

Understanding the mechanisms and locations of interseismic strain accumulation along faults is essential for assessing earthquake hazards. However, the mechanical response during the transition from deep fault locking to creep behavior remains uncertain. Estimating the slip deficit within these transition zones is challenging. This study challenges the assumption of a constant depth distribution of interseismic slip rate along the fault over time and proposes variable locking depths as an alternative model. By rejecting the constant locking depth assumption, singularity issues during stress theorem resolution are resolved. To address this, we employ a methodology considering creep propagation within a fully elastic medium. This approach incorporates long-term deformation resulting from viscoelastic flow in the upper mantle and lower crust. Including viscoelastic effects improves the fit to interseismic deformation rates, yielding lower locking depths compared to fully elastic models. To conduct the investigation, the GPS velocity field is recovered using the forward problem and the boundary element method. Subsequently, a physics-based inversion approach, deep interseismic creep, is employed to determine interseismic deformation patterns on a strike-slip fault. Furthermore, this study examined the correlation between the dislocation parameters and their relationship, as well as established the probability distributions associated with each faulting parameter. This research highlights the importance of considering variable locking depths in understanding interseismic strain accumulation and the transition to creep behavior along faults. The findings contribute to improved earthquake hazard assessment and mitigation strategies by providing valuable insights into fault behavior mechanics along the North Tabriz Fault.

Pixel-wise matching cost function for robust light field depth estimation

Depth estimation has significant potential in industrial applications, such as robot navigation. Light Field (LF) technology captures both spatial and angular information of a scene, enabling precise depth acquisition. Stereo matching technology has been commonly used for this task in LF imaging. However, previous methods typically compute the matching cost by simply shifting images with predefined offsets, causing poor performance in regions with sudden depth distribution changes (e.g., edges). To address this issue, we propose a Pixel-wise Matching Cost Function (PMCF) to estimate depth in units of pixel, then design a pixel-based network, termed PixelNet, for depth prediction, which achieves top rankings on the HCI 4D light field benchmark. Specifically, our cost function consists of two modules: the range search strategy and the modulation mechanism. The range search strategy enables the network to iteratively optimize depth on a per-pixel basis, while the modulation mechanism effectively handles scene noise and occlusions. By integrating these two modules, our function enables the generation of depth maps with sharper edges and smoother surfaces, compared with previous methods. Finally, we design a pixel-based network and apply it to both synthetic and real-world scenes, demonstrating that our method outperforms state-of-the-art methods in both scenes. Furthermore, PixelNet can also function as a post-processing network that can be seamlessly integrated with existing methods for depth refinement.

A Depth Awareness and Learnable Feature Fusion Network for Enhanced Geometric Perception in Semantic Correspondence.

Deep learning is becoming the most widely used technology for multi-sensor data fusion. Semantic correspondence has recently emerged as a foundational task, enabling a range of downstream applications, such as style or appearance transfer, robot manipulation, and pose estimation, through its ability to provide robust correspondence in RGB images with semantic information. However, current representations generated by self-supervised learning and generative models are often limited in their ability to capture and understand the geometric structure of objects, which is significant for matching the correct details in applications of semantic correspondence. Furthermore, efficiently fusing these two types of features presents an interesting challenge. Achieving harmonious integration of these features is crucial for improving the expressive power of models in various tasks. To tackle these issues, our key idea is to integrate depth information from depth estimation or depth sensors into feature maps and leverage learnable weights for feature fusion. First, depth information is used to model pixel-wise depth distributions, assigning relative depth weights to feature maps for perceiving an object's structural information. Then, based on a contrastive learning optimization objective, a series of weights are optimized to leverage feature maps from self-supervised learning and generative models. Depth features are naturally embedded into feature maps, guiding the network to learn geometric structure information about objects and alleviating depth ambiguity issues. Experiments on the SPair-71K and AP-10K datasets show that the proposed method achieves scores of 81.8 and 83.3 on the percentage of correct keypoints (PCK) at the 0.1 level, respectively. Our approach not only demonstrates significant advantages in experimental results but also introduces the depth awareness module and a learnable feature fusion module, which enhances the understanding of object structures through depth information and fully utilizes features from various pre-trained models, offering new possibilities for the application of deep learning in RGB and depth data fusion technologies. We will also continue to focus on accelerating model inference and optimizing model lightweighting, enabling our model to operate at a faster speed.

Determination of the Ion—Solid Interaction Potential from the Experiment and Its Influence on the Profiles of Implanted Particles

Based on the analysis of the angular distributions of particles passing through thin gold films, the parameters of the potential that best describes the experiment are obtained. The resulting potential differs from the potential describing collisions in the gaseous phase by a noticeable change in the screening constant. The influence of the collision energy, the choice of potential, and the model of electron bremsstrahlung on the depth distribution of implanted particles is analyzed.

Study of seismic activity in the Haiyuan-Liupanshan region using automated microseismic detection techniques

Using continuous waveform data from 27 fixed seismic stations in Ningxia spanning nearly a decade from 2013 to September 2022, the automatic detection matching method (PALM) was employed to capture 34,373 seismic events across the region, which is twelve times more than manual cataloging during the same period. The events were used as a template to search for smaller seismic events in the Haiyuan-Liupanshan region. After location, a total of 14,741 microseismic events were detected. Based on this expanded dataset, we calculated b value and analysis the depth profiles of seismic. The findings indicate that the distribution of microseismicity has characteristics of zonation, clustering and interruption. Seismic activity aligns with active faults and closely correlates with tectonic zones. The areas with seismic gaps and low b-value zones indicate a higher stress level on the north side of the middle section of the Haiyuan Fault, which was also the epicenter of the magnitude 4.9 Pingchuan earthquake on December 31, 2023. The seismic profiles show that the regional earthquakes mainly occur at a depth of more than 30 km. The depth distribution of these earthquakes reflects the inclination of the fault and thus corresponds exactly to the actual conditions.

Interface defect state induced spin injection in organic magnetic tunnel junctions

This article analytically explores defect assisted spin injection in organic magnetic tunnel junctions (MTJs) [x/rubrene/Co, x = La2O3, LaMnO3, La0.7Ca0.3MnO3 (LCMO), La0.7Sr0.3MnO3 (LSMO)] employing nonequilibrium Green’s function (NEGF). Spin precession at ferromagnet (FM)/organic semiconductor (OSC) interface defect states have been considered while modeling the MTJ devices. Variations in voltage dependent parallel (RP) and antiparallel (RAP) resistances have been attributed to modified spin dependent scattering at modified spin resolved density of states of magnetic electrodes. Moreover, change in distribution of defect state depths at a spin injection interface has also been observed to modify RP/RAP, and hence, tunnel magnetoresistance (TMR) across the devices. Localization of defect state distribution due to a high spin split band may have resulted in large TMR for La2O3 devices. Nonlinear spin transfer torque (STT) in devices other than LSMO indicates compensation of spin damping, resulting in a high TMR response across the devices. Hence, the localization of defect state distribution and the choice of magnetic electrodes with high spin split bands may be exercised to realize spintronic devices for low power spin memory applications.

Decoupling Sources of Anthropogenic Influences on Sediments of the Visovac Lake (Krka National Park, Croatia) Using Multiparametric Approach.

Historical changes of sediment characteristics and levels of inorganic and organic contaminants were studied in dated sediment cores from the Visovac Lake, situated in the Krka National Park, Croatia, to identify the main sources of anthropogenic pressures on this highly protected system. Depth distributions of lithogenic elements showed a steady decrease of terrigenous inputs due to the reduction in agricultural activities in the area, which was particularly pronounced during the 1991-1995 war in Croatia. Vertical and longitudinal distributions of Cd and Zn indicated that they are predominately of anthropogenic origin. The historical profiles of these toxic metals coincide well with the recorded production of metal industry in the upper reach of the Krka River with a sharp decrease reflecting the interruption by the war and slow recovery afterwards. By contrast, the recovery of the tourist industry in Krka NP after the war was accompanied by increasing contamination by elements characteristic of boat and car traffic (Sn, Cu, Pb) as well as oil pollution. The contamination with polycyclic aromatic hydrocarbons and polychlorinated biphenyls was only moderate. Although levels of metallic and organic contamination can be considered relatively low, the observed shift from industrial to tourism-related sources indicated that touristic activities should also be regarded as a possible threat for this vulnerable karst aquatic ecosystem.

Influence of the oxidizing technique on the biocompatible and corrosion properties of Ti6Al4V in a physiological environment

This work aims to evaluate the corrosion and biocompatibility properties of oxide films generated on Ti6Al4V alloys using both traditional and novel methods. Oxide films were generated by anodization and plasma treatment to achieve a blue surface finish. The oxide films were then characterized and compared to a native film formed on the Ti6Al4V.Electrochemical tests, incorporating potentiodynamic tests and electrochemical impedance spectroscopy, were employed to define the electrochemical resistance of oxides in an environment simulating biological exposure. In vitro tests were conducted to study ion release and biocompatible properties over a 6-week period of exposure to a 0.9 wt% NaCl solution, at body temperature. Various spectroscopic techniques, including ToF-SIMS, XRD, and Raman analysis, were used to study the structure and chemistry of the oxide films. The sub-surface layer was analysed by microstructural investigation.The type of oxidation was found to have a key influence on the oxide composition, especially with respect to the depth distribution of the individual alloy elements through the oxide film. The oxidation process determines which of the alloying elements are released into the environment, as a result of the corrosion reactions.

Fatigue Life Assessment of Corroded AlSi10MgMn Specimens

This study investigates the influence of pre-corrosion damage on the fatigue behavior of AlSi10MgMn high-pressure die-cast specimens, using the statistical distribution of corrosion depths. The analysis is conducted on two different surface conditions: an unmachined rough surface (Ra=5.05μm) and a machined, polished surface (Ra=0.25μm). For the unmachined specimens, the corrosive damage manifests as homogeneously spread localized corrosion, whereas the polished specimens exhibit less uniform but deeper corrosion. The average corrosion depth of the polished specimens is found to be slightly higher (313 μm compared to 267 μm) with a broader depth distribution. Specimens are tested under a constant bending load amplitude in laboratory conditions at a stress ratio of R=0 until fracture. A fracture mechanics-based methodology is developed to assess the remaining fatigue life of corroded specimens, utilizing short and long crack fracture mechanical parameters derived from SENB specimens. This model incorporates a thickness reduction of the critical specimen cross-section based on the corrosion depth distribution and combines it with a small initial crack of the intrinsic defect size (aeff=14μm). Regardless of the surface condition, using the most frequent corrosion depth for thickness reduction provides a good estimate of the long-life fatigue strength, while using the 90th percentile depth allows for a conservative assessment.

Benthic litter in fishing grounds of the Northern Adriatic: Role of the trawling fleet as cleaners of the seafloor

This study represents the baseline of estimation of the potential service provided by fishermen as “cleaners of the sea”. The amount, composition and depth distribution of marine litter in fishing grounds of the Northern Adriatic seafloor has been investigated through the fishing for litter (FFL) scheme. Passive FFL campaigns were carried out by trawlers from two of the most important fishing ports in the northern Adriatic, Chioggia and Goro, from May 2020 to May 2021. Over the course of 256 days of fishing, over 6 tons of litter were removed from 265 km2 of seafloor. Abandoned, lost and derelict fishing gears (ALDFG) were the most represented litter category (48 % of the total litter), and of these 67 % were plastic ALDFG (mostly mussel socks and fishing nets). Fouling on plastic waste was analyzed to determine the fraction of collected litter items that could be destinated to recycling. Only a small percentage of the plastic litter analyzed was “clean” from adherent and/or encrusting organisms. Approximately 2.4 tons of plastic were recovered, but, due to the biological colonization of surfaces, they cannot be recycled by using the technologies present in the area.

A probabilistic time-dependent corrosion wastage model for offshore platforms based on reverse diffusion model

Corrosion wastage poses significant challenges to offshore platforms, making accurate corrosion depth prediction crucial for structural integrity and extending service life. This study addresses the limitations in measurement processes by integrating a reverse diffusion model into the traditional probabilistic corrosion wastage model, enabling comprehensive analysis of corrosion data. The reverse diffusion model effectively manages data uncertainty and noise, leading to a proposed probabilistic model that incorporates measurement uncertainty. This model not only mitigates data noise and errors but also improves the reliability and robustness of corrosion depth predictions for offshore platforms. Initially, statistical analysis of corrosion data from offshore mobile platforms confirmed that the corrosion rate and depth distribution of local components follow a Weibull distribution. The effectiveness of the reverse diffusion model was validated by comparing the probability distributions of original data with those processed using the model. Finally, leveraging the optimized data and an empirical corrosion model for ships, a probabilistic model for time-dependent corrosion wastage in offshore platforms was developed, and its reliability was assessed. The proposed model enhances the accuracy of corrosion predictions, contributing to better management of corrosion risks in offshore platform structures.

Dynamics of Bubble Plumes Produced by Breaking Waves

Abstract Bubble plumes play a significant role in the air–sea interface by influencing processes such as air–sea gas exchange, aerosol production, modulation of oceanic carbon and nutrient cycles, and the vertical structure of the upper ocean. Using acoustic Doppler current profiler (ADCP) data collected off the west coast of Ireland, we investigate the dynamics of bubble plumes and their relationship with sea state variables. In particular, we describe the patterns of bubble plume vertical extension, duration, and periodicity. We establish a power-law relationship between the average bubble penetration depth and wind speed, consistent with previous findings. Additionally, the study reveals a significant association between whitecapping coverage and observed acoustic volume backscatter intensity, underscoring the role of wave breaking in bubble plume generation. The shape of the probability distribution of bubble plume depths reveals a transition toward stronger and more organized bubble entrainment events during higher wind speeds. Furthermore, we show that deeper bubble plumes are associated with turbulent Langmuir number Lat ∼ 0.3, highlighting the potential role of Langmuir circulation on the transport and deepening of bubble plumes. These results contribute to a better understanding of the complex interactions between ocean waves, wind, and bubble plumes, providing valuable insights for improving predictive models and enhancing our understanding of air–sea interactions. Significance Statement This research contributes to understanding bubble plume dynamics in the upper ocean and their relationship with sea state variables. The establishment of a power-law relationship between the bubble penetration depth and wind speed, along with the association between whitecapping coverage and acoustic backscatter intensity, contributes to improved predictive capabilities for air–sea interactions and carbon dioxide exchange. The identification of the potential influence of Langmuir circulation on bubble plume dynamics expands our understanding of the role of coherent circulations in transporting bubble plumes. Additionally, this study presents a clear methodology using commercial sensors such as an ADCP, which can be easily replicated by researchers worldwide, leading to potential advancements in our comprehension of bubble plume dynamics.

Inundation Processes with Active Sediment Transportation in the Floodplain of West Rapti River, Nepal

The present study discusses flood hazard characteristics in the lower reaches of the West Rapti River based on the results obtained from field surveys and numerical computations using depth averaged 2-D numerical models for flood flow and associated sediment transportation. To evaluate the inundation process with sediment erosion and deposition in the floodplain, a new erosion term was introduced into the mass conservation equations for suspended sediment and bed sediment. The results obtained from numerical computations indicated that field data on the spatial distributions of depths for inundation, and sediment erosion and deposition can be evaluated by the numerical model. Thus, numerical predictions were performed for the inundated areas, and the accumulated volumes of sediment erosion/deposition for floods with return periods of 50, 100, and 200 years, as a step towards damage assessment and risk assessment due to floods with active sediment transportation in the floodplains.

Deep‐Focus Earthquake Mechanisms at the Subducting Nazca Plate (Peru‐Brazil Border): Cold Slab Behavior in a Warm Plate

AbstractWe calculate focal mechanisms and centroid depths for deep‐focus earthquakes (DFEs) along the Peru‐Brazil border. We obtained a total of 28 focal solutions for events with magnitudes between 4.2 and 7.5 Mw and occurring between 2014 and 2022. Focal mechanisms indicate predominance of normal faulting, demonstrating a rather uniform down‐dip compression (DDC) regime within the plate. The orientations of the nodal planes suggest that earthquakes tend to occur along faults parallel to the local slab strike, although other fault types are documented. Stress orientations derived from the focal mechanisms agree with patterns expected if faulting were initiated by transformational faulting on a metastable olivine wedge (MOW) under DDC. Centroid depths range between 557 and 659 km, defining a narrow seismic zone within the lower portion of the subducting plate and an aseismic upper portion. We suggest that DFEs nucleate through transformational faulting within a narrow MOW preserved at a colder slab segment right above the lower mantle and juxtaposed to a shallower, warmer segment at around 500 km depth. This thermal complexity was possibly produced through flat subduction initiated by the subduction of the Nazca Ridge. We speculate that subduction of other aseismic ridges is possibly controlling the thermal state of the Nazca slab as a whole and, consequently, the depth distribution of DFEs along the South America subduction front.

Characterization Study of Deep-Level Defect Spatial Distribution, Emission Mechanisms, and Structural Identification

Abstract The characterization of defects in semiconductor materials and devices is crucial for enhancing the performance and reliability of semiconductor products. This tutorial review focuses on Deep Level Transient Spectroscopy (DLTS) as the primary analytical tool, thoroughly discussing its distinct advantages in deep-level defect characterization. However, it is unable to reveal the concentration-depth distribution of deep-level defects, neglects the dependency of carrier emission rates on the electric field, and fails to accurately identify defect structures.
To overcome these limitations, two enhanced DLTS techniques have been developed to extend the capabilities of DLTS. These enhancements include the utilization of graded fill pulse technology to accurately map defect distributions at various depths within devices, facilitating individual defect characterization across different layers of multilayered structures; the application of varying electric field strengths to samples to delve into the intricate physical mechanisms of defects during carrier emission processes; and the adjustment of the duration of electric pulse injection to monitor signal growth trends, deducing the microstructure of defects. The paper integrates research findings from a wide array of field experts, meticulously outlines a description of how to obtain the depth distribution of defect concentration in devices, furnishes quantitative criteria for both the Poole-Frenkel effect and phonon-assisted tunneling mechanisms of carrier emission, and provides specific examples for distinguishing between interface states/bulk defects and point defects/extended defects. This enhances both the theoretical and practical knowledge in this field. The advanced DLTS techniques outlined provide crucial guidance for defect characterization and performance optimization in semiconductor devices with new structures and materials.

Stress modeling for the upper and lower crust along the Anninghe, Xianshuihe, and Longmenshan Faults in southeastern Tibetan plateau

Earthquake occurrence depth in the crust is related to stress, temperature, and brittle–ductile transition, which is also near the transition depth of the upper to lower crust. The composition variation between the upper and lower crust causes remarkable changes of rheological properties and variation in stress distribution. Clarifying the detailed stress distribution in the upper and lower crust is crucial for understanding the brittle–ductile transition and the stress environment of the seismogenic zone. The Southeastern Tibetan Plateau (SETP), with wide spread of active strike−slip faults and clustered earthquakes, provides a natural field for investigating the relationships between crustal stresses, deformation behaviors, and earthquake mechanics. By considering the rheological properties of granite and anorthite, this paper established stress models with different boundary depths (15, 20 and 25 km) between the upper and lower crust along the Anninghe, Xianshuihe, and Longmenshan Faults in the SETP with a horizontal strain of 6 × 10−4 extracted from in situ stress data. The stress model with different geothermal gradients and a boundary depth of 20 km between the upper and lower crust suggests two distinct types of the brittle–ductile transition below these three faults. Simultaneously, the stress model can account for the continuity of earthquake depth distribution below the Longmenshan Fault and the seismic gap below the Anninghe and Xianshuihe Faults. The continuity of earthquake depth distribution or seismic gap below these three faults can be explained by their different geothermal gradients. These findings provide new insights for understanding the stress environment of the seismogenic zone in the SETP. Our model reveals the relationships between differential stress, seismicity, brittle–ductile transition, and boundary depth of the upper and lower crust in the continental crust, and connects the multiple observations from geophysics and geology. Furthermore, our model provides insights for studying multiple processes in the continental crust, such as crustal deformation, fault slip, and earthquake occurring.

Spatial Distribution of Thaw Depth in Palsas Estimated From Optical Unoccupied Aerial Systems Data

ABSTRACTMaximum seasonal thaw depth, referred to as active layer thickness (ALT), is one of the key parameters used to monitor permafrost conditions. ALT maps based on interpolation of point measurements or derived from coarse or moderate spatial resolution satellite data often hide small‐scale spatial variations in thaw depth resulting from differences in surface characteristics and microtopography. To model and predict changes in hydrological and biogeochemical processes in permafrost areas accurately, high‐resolution remote sensing‐based estimations of ALT are needed. Therefore, we applied random forest (RF) regression on a set of topographical and spectral vegetation indices derived from optical unoccupied aerial systems data, Landsat 8 land surface temperature (LST) data, and field measurements to estimate thaw depths in palsas at three mires in north‐west Finland. We also analyzed differences in thaw depths between mires located at different elevations, between dome and plateau‐shaped palsas, and between different vegetation and surface cover classes. The RF models resulted in root mean square errors from 2.4 to 5.7 cm between predicted and observed thaw depths and the R2 values of 0.57–0.96. Height from the surrounding fen surface and LST were the most important variables in thaw depth models, although high‐accuracy results were also achieved without LST. The mean thaw depths did not differ between the sites with lowest and highest elevation, whereas the thaw depths were significantly deeper in dome‐shaped palsas compared to plateaus. The thaw depths were significantly different between vegetation cover classes only on plateau‐shaped palsas. The results indicate the high impact of the topography on the palsa thaw depth, thus highlighting the importance of accurate elevation models in spatial modeling of palsa ALT. The methodology presented in this study can be applied to other permafrost regions where field measurements of ALT are accompanied with high‐resolution topographical and multispectral data.