Topographic Model Research Articles

Evaluating the Signal Contribution of the DTU21MSS on Coastal Mean Dynamic Topography and Geostrophic Current Modeling: A Case Study in the African–European Region

With the accumulation of synthetic aperture radar (SAR) altimetry data and advancements in retracking algorithms, the improved along-track spatial resolution and signal-to-noise ratio have significantly enhanced the availability and precision of sea surface height (SSH) measurements, particularly in challenging environments such as coastal areas, ocean currents, and polar regions. These improvements have refined the accuracy and reliability of mean sea surface (MSS) models, which in turn have enhanced the precision of mean dynamic topography (MDT) and geostrophic current models. However, in-depth research is required to quantify the specific contributions of SAR altimetry to these critical regions and their impacts on the MSS, MDT, and geostrophic currents. Given that DTU21MSS (Technical University of Denmark MSS 2021) incorporates a substantial amount of SAR altimetry data, this study utilized independent Sentinel-3A altimetric observations to evaluate the signal improvements of DTU21MSS compared with DTU15MSS, with a focus on its performance in polar, coastal, and current regions. In addition, a least-squares-based approach was employed to assess the impact of the improved MSS model on the deduced MDT and geostrophic current signals. The numerical results revealed that DTU21MSS achieved an accuracy improvement of ~8% within 20 km offshore compared with DTU15MSS. In the polar regions within 100 km offshore, DTU21MSS exhibited a maximum signal enhancement of ~0.1 m, with overall improvements of 10–20%. The DTU21MSS-derived MDT solution demonstrates better consistency with validation data, reducing the standard deviation of misfits from 0.058 m to 0.054 m. Signal enhancements of maximumly 0.1 m were observed in the polar regions and the Mediterranean/Red Sea. Furthermore, improvements in the MSS and its error information could directly enhance the deduced MDT models, highlighting its foundational role in precise oceanographic modeling.

Moho topographic inversion of the South China Sea based on genetic algorithm

The Parker-Oldenburg method is a commonly used classical interface inversion method for Moho topographic inversion. However, this method is excessively reliant on two hyperparameters − the Moho density contrast and the average Moho depth. Due to the failure to take into account the effect of non-linear terms and computational inefficiencies, this previous method leads to a significant bias in the hyperparameters estimation, which renders it impossible to invert the finer Moho topography. To address this issue, we propose a new method that utilizes the genetic algorithm to estimate more accurate hyperparameters. Synthetic test results illustrate that the differences of the estimated Moho density contrast and average Moho depth from our method and the true values are only 0.044 g/cm3 and 0.729 km, respectively. Compared with the improved Bott’s method, the errors were reduced by 12.28 % and 2.23 %, respectively. To further illustrate the effectiveness of our method, we apply this method to the Southwestern Sub-basin of the South China Sea, where the Moho density contrast and average Moho depth are determined to be 0.61 g/cm3 and 19.18 km, respectively by imposing seismic data constraints. The Moho topography is then inverted based on these determinations, revealing that the Moho topography ranges from 6.3 km to 24.9 km in the study area and exhibits pronounced undulations. Compared to other Moho topography models, our Moho topography is more accurate.

Geological and mining mapping approach by coupling geological and geophysical field data: application to the Central Domain of the Mbere division (Adamawa-Cameroon)

This study is based on the coupling of geological field data with geophysical studies in the geological mapping of the Central Domain of the Mbere Division (Adamawa-Cameroon). The first step was to calculate the residual grid associated with the geophysical data that will be used for the mapping of the basement. The second step before mapping consisted in calculating the analytical signal associated with the residual grid, used to interpret the geological formations under cover or in intrusion. Subsequently, a geological mapping approach based on the categorisation of geophysical signatures into ranges using the Encom Discover program was adopted. This approach is based on the analysis of the relief of geophysical anomalies. The process of categorisation which is done iteratively, takes into consideration in the same georeferenced space, the resolution of the input data, the variation of the field considered and the structural model previously interpreted. The result of the categorisation is then compared to the spatial distribution of outcrop data to build the geological model. The application of this approach to the Central Domain of the Mbere Division led to the production of a synthetic geological map at a scale of 1/75,000. The superposition of this map to the topographic model allows to observe a concordance between the Cretaceous basins represented by their edge faults and the topographic depression zones. The various mineral indicators (primary and secondary) collected during the fieldwork, combined with the geological model (1:75,000 scale) as well as the Cretaceous deposits and vein intrusion models were used to create the mineral indicators and targets map for this sector. All these models can thus be used to underpin mineral exploration projects in the study area.

Linking deep-time subduction history to modern day expressions of dynamic topography

Dynamic topography refers to vertical deflections of Earth’s surface from viscous flow within the mantle. Here we investigate how past subduction history affects present dynamic topography. We assimilate two plate reconstructions into TERRA forward mantle convection models to calculate past mantle states and predict Earth’s present dynamic topography; a comparison is made with a database of observed oceanic residual topography. The two assimilated plate reconstructions ‘Earthbyte’ and ‘Tomopac’ show divergent subduction histories across an extensive deep-time interval within Pacific-Panthalassa. We find that introducing an alternative subduction history perturbs our modelled present-day dynamic topography on the same order as the choice of radial viscosity. Additional circum-Pacific intra-oceanic subduction in Tomopac consistently produces higher correlations to the geoid (more than 20% improvement). At spherical harmonic degrees 1–40, dynamic topography models with intra-oceanic subduction produce universally higher correlations with observations and improve fit by up to 37%. In northeast Asia, Tomopac models show higher correlations (0.46 versus 0.18) to observed residual topography and more accurately predict approximately 1 km of dynamic subsidence within the Philippine Sea plate. We demonstrate that regional deep-time changes in subduction history have widespread impacts on the spatial distribution and magnitude of present-day dynamic topography. Specifically, we find that local changes to plate motion histories can induce dynamic topography changes in faraway regions located thousands of kilometres away. Our results affirm that present-day residual topography observations provide a powerful, additional constraint for reconstructing ancient subduction histories.

Investigating Sampling Bias in Seismological Research Through Secondary Variable: Insights from VS30 Datasets of Mainland China, Japan, Türkiye, and Taiwan

Abstract Sampling bias is an inevitable issue in seismological research, especially in collecting seismic site condition data due to operational constraints. It impacts data representativeness and subsequent model performance. Previous researches give insufficient consideration to this issue. Some researches worked on raw data directly. Some others used conventional declustering methods that rely on data spatial distribution and proved to be ineffective. This study investigates sampling bias in seismological research by employing a debiasing method that incorporates secondary variables, focusing on VS30 datasets from mainland China, Japan, Türkiye, and Taiwan. Quantifying analysis showed that, when considering topographic slope as the secondary variable, the sampling biases in the mainland China and Taiwan dataset are more pronounced. When examining the secondary variable of geology age, the sampling biases in the Japan and Türkiye datasets that are not readily discernible through visual inspection of spatial distributions become apparent. By investigating the sampling bias of the Türkiye and mainland China dataset using semivariogram as the secondary variable, this study reveals hidden bias within the Türkiye dataset, despite its well-distributed appearance. This finding further illustrates the limitations of relying solely on spatial distribution to detect sampling bias. In addition, the study examined the impact of sampling bias on resulting models. The topographic slope-based VS30 proxy models of debiased data in the four regions demonstrate significant effects of debiasing on modeling outcomes. Notably, the debiased models exhibit a homogenized trend comparing to original models in the low topographic slope range, indicating the possibility of a globally consistent relationship.

Spinal cord evaluation in multiple sclerosis: clinical and radiological associations, present and future.

Spinal cord disease is important in most people with multiple sclerosis, but assessment remains less emphasized in patient care, basic and clinical research and therapeutic trials. The North American Imaging in Multiple Sclerosis Spinal Cord Interest Group was formed to determine and present the contemporary landscape of multiple sclerosis spinal cord evaluation, further existing and advanced spinal cord imaging techniques, and foster collaborative work. Important themes arose: (i) multiple sclerosis spinal cord lesions (differential diagnosis, association with clinical course); (ii) spinal cord radiological-pathological associations; (iii) 'critical' spinal cord lesions; (iv) multiple sclerosis topographical model; (v) spinal cord atrophy; and (vi) automated and special imaging techniques. Distinguishing multiple sclerosis from other myelopathic aetiology is increasingly refined by imaging and serological studies. Post-mortem spinal cord findings and MRI pathological correlative studies demonstrate MRI's high sensitivity in detecting microstructural demyelination and axonal loss. Spinal leptomeninges include immune inflammatory infiltrates, some in B-cell lymphoid-like structures. 'Critical' demyelinating lesions along spinal cord corticospinal tracts are anatomically consistent with and may be disproportionately associated with motor progression. Multiple sclerosis topographical model implicates the spinal cord as an area where threshold impairment associates with multiple sclerosis disability. Progressive spinal cord atrophy and 'silent' multiple sclerosis progression may be emerging as an important multiple sclerosis prognostic biomarker. Manual atrophy assessment is complicated by rater bias, while automation (e.g. Spinal Cord Toolbox), and artificial intelligence may reduce this. Collaborative research by the North American Imaging in Multiple Sclerosis and similar groups with experts combining distinct strengths is key to advancing assessment and treatment of people with multiple sclerosis spinal cord disease.

The evolving three-dimensional landscape of human adaptation.

Over the past 3 million years, humans have expanded their ecological niche and adapted to more diverse environments. The temporal evolution and underlying drivers behind this niche expansion remain largely unknown. By combining archeological findings with landscape topographic data and model simulations of the climate and biomes, we show that human sites clustered in areas with increased terrain roughness, corresponding to higher levels of biodiversity. We find a gradual increase in human habitat preferences toward rough terrains until about 1.1 million years ago (Ma), followed by a 300 thousand-year-long contraction of the ecological niche. This period coincided with the Mid-Pleistocene Transition and previously hypothesized ancestral population bottlenecks. Our statistical analysis further reveals that from 0.8 Ma onward, the human niche expanded again, with human species (e.g., H. heidelbergensis, H. neanderthalensis, and H. sapiens) adapting to rougher terrain, colder and drier conditions, and toward regions of higher ecological diversity.

GIS Modelling for Prediction of Tsunami Inundation Areas in Coastal Areas of Malang Regency

Abstract This study utilizes Geographic Information System (GIS) modeling to predict potential tsunami inundation areas along the coastal regions of Malang Regency. The capabilities of GIS in this research integrate regional topography and land use data to model tsunami inundation scenarios accurately. The topographic modeling process employs Alos Palsar Digital Elevation Model (DEM) data, which provides detailed elevation information critical for assessing inundation risks. Three altitude scenarios 10 meters, 15 meters, and 20 meters are analyzed to gauge the extent and height of potential tsunami waves. In the 10-meter scenario, the areas most susceptible to inundation include Donomulyo, Bantur, and Gedangan, highlighting these zones as critical areas for immediate attention. As the scenario elevation increases to 15 meters, Gedangan, and Sumbermanjing Wetan emerge as the most vulnerable regions, suggesting a broader risk as tsunami wave heights escalate. The 20-meter scenario further accentuates the vulnerability of Gedangan and Sumbermanjing Wetan Districts, which exhibit the widest potential inundation areas. By identifying the most at-risk areas, this research provides valuable insights for policymakers and planners to develop targeted strategies to mitigate the impact of tsunamis. Advanced GIS modeling is a crucial tool in enhancing the preparedness and resilience of coastal communities against tsunami hazards.

2D Magnetotelluric Resistivity Structure Modeling Using Finite Element Method Based on Vector Triangular Grid and Its Application to Lembang Fault MT Data

Abstract Magnetotellurics is one of the geophysical exploration techniques that relies on the natural fluctuations of electromagnetic waves to delineate their influence on the Earth. The primary focus of this method is to reveal the structure of Earth’s subsurface with the value of resistivity. The application of numerical approaches in magnetotelluric modeling has proven to be an efficient method in various theoretical studies in the field of geophysics, particularly in the context of modeling two-dimensional structures. This research explains a 2D resistivity structure modeling using a vector finite element method. This approach utilizes the edges of elements as vector bases. The presented results include response values such as apparent resistivity and impedance phase at the surface. The study employs the standard model from COMMEMI as a reference to validate the modeling program. Furthermore, the results from this modeling program are compared with the outcomes of the modeling program developed by Weaver et al. The good results were obtained with error values for each model for layered and homogeneous Earth < 3%. Additionally, for the reference model COMMEMI, errors of 3.4393% and 1.4050% were obtained for TE and TM modes, respectively. Furthermore, apparent resistivity and impedance phase results closely approximated the reference values for the topography model. Subsequently, in the application to field data, specifically the Lembang Fault, errors were obtained for the TE and TM modes within the range of 1.16 – 9.16% for each MT data acquisition site.

Successive Tsunamigenic Events Near Sofu Seamount Inferred From High‐Frequency Teleseismic P and Regional T Waves

AbstractAn unexpected major tsunami from the region near Sofu Seamount was observed on 8 October 2023. Sofu Seamount is located approximately 600 km from the coast of Japan. Due to far epicentral distances and the successive occurrence of seismic events, the conventional seismic analysis to reveal the accompanying seismic sequence cannot work well. We investigated high‐frequency teleseismic P and regional T waves from the accompanying seismic sequence during the tsunamigenic events near Sofu Seamount. Envelope shapes of teleseismic P and regional T waves were similar, indicating that T‐wave envelopes also reflected source properties of seismic sequence. During seismic events near Sofu Seamount, observed regional envelopes were characterized by weak body waves and large amplitude T waves with durations of 39–68 s. According to numerical simulations of seismic wave propagation using a realistic topography model, characteristics of T waves exhibit weak slope‐angle and strong source‐depth dependencies. Strong T waves with durations less than 60 s only appeared in results with sources at depths ≤0.5 km below the seafloor. We concluded that high‐frequency radiation of the accompanying seismic sequence during the tsunamigenic events near Sofu Seamount possibly occurred at shallower depths just below the seafloor. If seismic and tsunami sources coincide, shallower source depths might cause tsunamigenic uplifts. The observed peak seafloor uplifts and T‐wave amplitudes during tsunamigenic events were scaled. This result suggests the possibility of tsunami forecasting based on T‐wave amplitudes from submarine volcanoes.

Mitigating Disparate Elevation Differences between Adjacent Topobathymetric Data Models Using Binary Code

Integrating coastal topographic and bathymetric data for creating regional seamless topobathymetric digital elevation models of the land/water interface presents a complex challenge due to the spatial and temporal gaps in data acquisitions. The Coastal National Elevation Database (CoNED) Applications Project develops topographic (land elevation) and bathymetric (water depth) regional scale digital elevation models by integrating multiple sourced disparate topographic and bathymetric data models. These integrated regional models are broadly used in coastal and climate science applications, such as sediment transport, storm impact, and sea-level rise modeling. However, CoNED’s current integration method does not address the occurrence of measurable vertical discrepancies between adjacent near-shore topographic and bathymetric data sources, which often create artificial barriers and sinks along their intersections. To tackle this issue, the CoNED project has developed an additional step in its integration process that collectively assesses the input data to define how to transition between these disparate datasets. This new step defines two zones: a micro blending zone for near-shore transitions and a macro blending zone for the transition between high-resolution (3 m or less) to moderate-resolution (between 3 m and 10 m) bathymetric datasets. These zones and input data sources are reduced to a multidimensional array of zeros and ones. This array is compiled into a 16-bit integer representing a vertical assessment for each pixel. This assessed value provides the means for dynamic pixel-level blending between disparate datasets by leveraging the 16-bit binary notation. Sample site RMSE assessments demonstrate improved accuracy, with values decreasing from 0.203–0.241 using the previous method to 0.126–0.147 using the new method. This paper introduces CoNED’s unique approach of using binary code to improve the integration of coastal topobathymetric data.

An overset-grid finite-difference algorithm for seismic wavefield propagations modelling in the polar coordinate system with a complex free-surface topography

Summary Nowadays, finite-difference method has been widely applied to simulate seismic wavefield propagation in a local seismic model with a complex topography by utilizing curvilinear grids and traction image method in Cartesian coordinates system. For a global seismic model in polar coordinate system, it is still a challenge for the conventional finite-difference method to deal with the grid singularity at the center and the topographic free surface at the top. In this study, we develop a finite-difference method in polar coordinates for seismic wavefield propagation in the 2D global model. In the proposed finite-difference method, the overset-grid algorithm is used to handle the grid singularity at the center, and the curvilinear grid technique as well as the traction image method are applied to implement free-surface boundary condition on the complex topography. The proposed finite-difference method is validated in flat and topographic free-surface models by comparing synthetic waveforms with reference solutions. The seismic wavefield propagation in a realistic Mars profile is computed by the proposed finite-difference method. The proposed finite-difference method is an efficient and accurate method for seismic wave modeling in the polar coordinate system with a complex free-surface topography.

Machine learning to predict morphology, topography and mechanical properties of sustainable gelatin-based electrospun scaffolds

Electrospinning is an outstanding manufacturing technique for producing nano-micro-scaled fibrous scaffolds comparable to biological tissues. However, the solvents used are normally hazardous for the health and the environment, which compromises the sustainability of the process and the industrial scaling. This novel study compares different machine learning models to predict how green solvents affect the morphology, topography and mechanical properties of gelatin-based scaffolds. Gelatin-based scaffolds were produced with different concentrations of distillate water (dH2O), acetic acid (HAc) and dimethyl sulfoxide (DMSO). 2214 observations, 12 machine learning approaches, including Generalised Linear Models, Generalised Additive Models, Generalised Additive Models for Location, Scale and Shape (GAMLSS), Decision Trees, Random Forest, Support Vector Machine and Artificial Neural Network, and a total of 72 models were developed to predict diameter of the fibres, inter-fibre separation, roughness, ultimate tensile strength, Young’s modulus and strain at break. The best GAMLSS models improved the performance of R2 with respect to the popular regression models by 6.868%, and the MAPE was improved by 21.16%. HAc highly influenced the morphology and topography; however, the importance of DMSO was higher in the mechanical properties. The addition of the morphological properties as covariates in the topographic and mechanical models enhanced their understanding.

UAV Modelling of Proglacial Landscapes, Axel Heiberg Island Nunavut

This project involved using a UAV to create digital models and products that enhance visualization and understanding of the moraines of White and Thompson Glaciers, Axel Heiberg Island, Nunavut. UAV surveying offers an effective alternative to high-resolution satellite imagery for documenting highly dynamic proglacial landscapes. Proglacial landforms and sediments provide insights into glacier characteristics and the behavior of glacier termini. UAV surveying allows for high-resolution examination of moraine features and the creation of digital elevation models (DEMs) that facilitate topographic modeling and the detection of changes. A Mavic 3M Drone was employed with UGCS flight planning software. UGCS flight planning software was selected for its ability to create orthomosaic flight plans that consider ground elevation, ensuring accurate Ground Sampling Distance (GSD). A 2m Arctic DEM was uploaded to UGCS prior to planning flight routes, allowing for more precise measurements. Post processing was done in Drone2Map and Agisoft Metashape to create both 2D orthomosaics and 3D models respectively. The results of this work will be used as a visual tool to study current aspects of the moraines, including extent, depositional processes, and present hydrodynamic energy environments. This information will be compared to historical air photos and previous studies to examine changes the moraines over a sixty-year period.

Seafloor Topography Recovery Using the Observation Data of Tiangong-2 Interferometric Imaging Radar Altimeter

Tens of years of altimetry sea surface height (SSH) data has continuously contributed to the development of global seafloor topography models because it can be used to precisely retrieve the gravity variation caused by seafloor topography. The development and application of altimeter has come to a new era from conventional nadir-looking altimeters to interferometric wide-swath altimeters as the successful launch of the Interferometric Imaging Radar Altimeter on board Chinese Tiangong 2 space laboratory (TG2 InIRA). Compared with conventional altimeters, the observation efficiency of TG2 InIRA has been greatly improved. This paper presents for the first time the results of seafloor topography derived from TG2 InIRA data in west Pacific Ocean and South China Sea regions. The root mean squared errors (RMSE) of the recovered topographies by gravity-geologic method (GGM) referring to the shipborne measurements in these two regions are 69.882 and 50.110 m, respectively. The recovered topographies are also evaluated by comparing with five well-known topography models. Furthermore, two subareas in west Pacific Ocean region are selected to conduct a supplemental experiment showing that more revisits can help achieve better recovery. The RMSE of the more revisited subarea is 66.808 m, while the RMSE of the less revisited subarea is 79.273 m.

Study of the Impact of Surface Topography on Wear Resistance

The surface texture parameter is a real reflection of the surface topography, which is closely related to the tribological properties of the surface, and the study of the correlation between the surface texture parameter and wear resistance is of great significance in revealing the tribological influence mechanism of the surface and realising the functional manufacturing of the surface. This paper takes the ball-end milling surface as the research object, establishes the three-dimensional simulation model of the surface topography, and analyses the surface topography and the surface texture parameter change rule. Based on the improved correlation analysis model, the correlation characteristics between the surface texture parameters, and between the surface texture parameters and the relative wear rate of per unit sliding distance KV, were investigated, and the prediction model of KV was established based on the surface texture parameters Sku, Sa, Sxp, Sp, and Ssk, and the correctness of the model was verified by experiments. The study in this paper provides a new idea to further reveal the relationship between surface topographical features and wear resistance and to guide the functional manufacturing of surfaces.

A New Precise Point Positioning with Ambiguity Resolution (PPP-AR) Approach for Ground Control Point Positioning for Photogrammetric Generation with Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are now widely preferred systems that are capable of rapid mapping and generating topographic models with relatively high positional accuracy. Since the integrated GNSS receivers of UAVs do not allow for sufficiently accurate outcomes either horizontally or vertically, a conventional method is to use ground control points (GCPs) to perform bundle block adjustment (BBA) of the outcomes. Since the number of GCPs to be installed limits the process in UAV operations, there is an important research question whether the precise point positioning (PPP) method can be an alternative when the real-time kinematic (RTK), network RTK, and post-process kinematic (PPK) techniques cannot be used to measure GCPs. This study introduces a novel approach using precise point positioning with ambiguity resolution (PPP-AR) for ground control point (GCP) positioning in UAV photogrammetry. For this purpose, the results are evaluated by comparing the horizontal and vertical coordinates obtained from the 24 h GNSS sessions of six calibration pillars in the field and the horizontal length differences obtained by electronic distance measurement (EDM). Bartlett’s test is applied to statistically determine the accuracy of the results. The results indicate that the coordinates obtained from a two-hour PPP-AR session show no significant difference from those acquired in a 30 min session, demonstrating PPP-AR to be a viable alternative for GCP positioning. Therefore, the PPP technique can be used for the BBA of GCPs to be established for UAVs in large-scale map generation. However, the number of GCPs to be selected should be four or more, which should be homogeneously distributed over the study area.

Climate‐Driven Projections of Future Global Wetlands Extent

AbstractWetlands are crucial components of the Earth's system, interacting with various processes such as the hydrological cycle, energy exchanges with the atmosphere, and global nitrogen and carbon cycles. The future trajectory of wetlands is anticipated to be influenced not only by direct human activities, but also by climate change. Here we present our assessment of climate‐driven global changes in wetlands extent, focusing on the main wetland complexes. We used an approach based on the Topographic Hydrological model (TOPMODEL) and soil liquid water content projections from 14 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our analysis reveals a consistent decrease in wetlands extent in the Mediterranean, Central America, and northern South America, with a substantial loss of 28% in the western Amazon Basin for the end of the 21st century (2081–2100) under the SSP370 scenario. Conversely, Central Africa exhibits an increase in wetlands extent, except in the Congo Basin. Nevertheless, most of the areas studied (80%) present uncertain results, due to conflicting projections of changes between the models. Notably, we show that there is significant uncertainty among CMIP6 models regarding liquid soil water content in high latitudes. By narrowing our focus to 10 models, which seem to better represent the thawing of permafrost, we obtain a better inter‐model agreement. We then find a modest declines in the overall global area (<5%), but an average loss of 13% beyond 50°N. Specific areas like the Hudson Bay Lowlands experiencing a 21% decrease and the Western Siberian Lowlands a 15% decrease.

Formation Technique of a 3D Ground Topographic Numerical Model for Environmental Impact Prediction using Digital GIS Databases, Contour Lines and Constrained Delaunay Triangulation

Formation Technique of a 3D Ground Topographic Numerical Model for Environmental Impact Prediction using Digital GIS Databases, Contour Lines and Constrained Delaunay Triangulation

The Characteristics and Variation of the Golden Eagle Aquila chrysaetos Home Range

Satellite tracking allows for novel investigations into golden eagle home range characteristics. Understanding home range characteristics is important for conservation and for assessing the potential impact of landscape changes from forest planting, wind farms, etc. Small sample sizes, inconsistent definitions and methods restricted several previous studies. Our study involved 69 resident tagged eagles with over one year of data across five Scottish regions. Home range size was estimated from 95% isopleth contours extracted from Utilisation Distributions. Above a small threshold, estimated range size was not affected by the number of records but at least one year of data is required, largely because of the breeding and non-breeding seasonal differences. There were no significant range size differences between birds tagged as range holders and those previously tagged as nestlings. Across four regions, with considerable intra-regional variation, planar 95% isopleths did not differ (medians, km2): Argyll 58.9, Northwest Highlands 61.7, Northeast Highlands 89.3, South of Scotland 91.9. Ranges in the isolated Outer Hebrides region were exceptionally small, at 24.0 km2. Estimated range area was usually reduced to 70–80% of the planar area when restricted to usable habitat, as estimated by the Golden Eagle Topography (GET) model. Applying measures of known unsuitable habitat (closed-canopy commercial forest and wind turbines) further reduced usable open land. Loss of otherwise suitable habitat was substantially due to commercial forest. Larger ranges had larger extents of suitable habitat (according to GET), with no apparent optimum of preferred GET habitat. Range size was not different across a year between the sexes. Breeding ranges were smaller, and females’ breeding ranges were much smaller than those of males, but larger than males’ ranges in the non-breeding season. Breeding attempt duration was probably also influential. Our study provides novel insights into golden eagle home range characteristics and can guide further research and practical applications.