High-resolution Digital Elevation Models Research Articles

A Raster-oriented Method for Creating Eclipse Maps

Traditional total solar eclipse maps based on 19th-century calculation methods do not take full advantage of important refinements recently made possible by fast computers and high-resolution digital elevation models of both the Earth and the Moon. Ignoring the terrain of both bodies introduces errors on the order of kilometers in the ground track of the umbra and seconds in the duration and contact times of totality. While this has been understood to some degree for decades, it has not been visualized in maps until quite recently, revealing only in the last decade the surprising polygonal shape of the umbra. Beginning in December of 2016, we published maps and animations of the 2017 August 21 total solar eclipse created with a raster-oriented approach that relies on remote-sensing data sets and computer graphics techniques to produce more accurate maps and professional-quality animations. These were an important component of NASA’s public outreach for the 2017 eclipse.

Application of GIS Spatial Analysis for the Assessment of Storm Surge Inundation Risks in the Guangdong–Macao–Hong Kong Great Bay Area

This study evaluates the storm surge inundation risk in three anthropogenically infilled estuaries—Xichong, Renshan, and Kaozhouyang—located in the Guangdong–Macao–Hong Kong Great Bay Area, China. By integrating GIS spatial analysis with storm surge modeling, we conducted 204 numerical experiments to simulate storm surge inundation under varying typhoon intensities and astronomical tide conditions. Results revealed that coastal terrain plays a crucial role in influencing storm surge levels and inundation extents. Specifically, the pocket-shaped terrain in the Renshan and Kaozhouyang estuaries amplified storm surges, resulting in higher inundation levels compared to the relatively open terrain of Xichong. Furthermore, anthropogenically reclaimed land in these estuaries appear to be particularly vulnerable to storm-induced inundation. Overall, this study underscores the importance of considering coastline morphology and the anthropogenic modifications of coastal terrain in storm surge risk assessments, offering valuable insights for disaster prevention and mitigation strategies. The use of ArcGIS spatial analysis coupled with storm surge modeling, facilitated by high-resolution DEMs, provides a statistical risk assessment of inundation. However, more complex flooding dynamics models need to be developed, particularly when terrestrial bottom friction information, which is heavily modified by human activities, can be accurately incorporated.

An improvement on the assessment of ecosystem services value of urban wetlands under consideration of water yield at regional scale.

Urban wetlands are gaining more attention and showing more important play in the sustainability. Surge findings are attached on the assessment of Wetland Ecosystem Service Value (WESV) in urban areas. While determining WESV in urban areas, it is still difficult to capture the nature of wetlands due to neglecting the impact of related impervious surfaces. It is necessary to improve the existing evaluating methods of WESV when seeking the truth. In order to narrow this issue, based on InVEST model, this study employed Equivalent Factors (EF) to determine WESV in urban areas with a case of Hengyang City, China. The main materials of this study included high-resolution images, DEM, precipitation, evapotranspiration, soil, vegetation, and statistical yearbook of the case. By comparing the uncorrected results with precipitation corrected and water yield corrected results of WESV, this study confirmed that: (1) the corrected results can reflect more real status than uncorrected; (2) in terms of EF, the water yield factor is more conducive to finding the truth than precipitation. Through this study, the water yield factor can effectively reduce the adverse effects of climate and improve the accuracy when determining WESV in urban areas.

Digitally derived trail terrain metrics

ABSTRACT Trails are essential transportation infrastructure supporting access to protected natural areas and providing recreation to hikers, runners, cyclists, equestrians, motorists, and many more worldwide. The slope of trails and their surrounding terrain influences physical trail sustainability and difficulty of travel. This research examines methods for using high-resolution digital elevation models to measure terrain steepness near trails and along trails or potential trail routes by comparing geographic information system (GIS) derived measurements to field measurements from the Appalachian Trail. The analysis validates the use of digitally derived trail terrain metrics and provides guidance to improve their utility in future trail planning and assessment efforts.

Creating High-Resolution Precipitation and Extreme Precipitation Indices Datasets by Downscaling and Improving on the ERA5 Reanalysis Data over Greece

The aim of this study was to construct a high-resolution (1 km × 1 km) database of precipitation, number of wet days, and number of times precipitation exceeded 10 mm and 20 mm over Greece on a monthly and on an annual basis. In order to achieve this, the ERA5 reanalysis dataset was downscaled using regression kriging with histogram-based gradient boosting regression trees. The independent variables used are spatial parameters derived from a high-resolution digital elevation model and a selection of ERA5 reanalysis data, while as the dependent variable in the training stages, we used 97 precipitation gauges from the Hellenic National Meteorological Service for the period 1980–2010. These stations were also used for validation purposes using a leave-one-out cross-validation methodology. The results of the study showed that the algorithm is able to achieve better R2 and RMSE over the standalone ERA5 dataset over the Greek region. Additionally, the largest improvements were noticed in the wet days and in the precipitation over 10 and 20 mm, where the ERA5 reanalysis dataset overestimates the number of wet days and underestimates precipitation over 10 and 20 mm, while geographically, the ERA5 dataset performs the worst in the island regions of Greece. This indicates that the ERA5 dataset does not simulate the precipitation intensity accurately over the Greek region, and using our methodology, we were able to increase the accuracy and the resolution. Our approach delivers higher-resolution data, which are able to more accurately depict precipitation in the Greek region and are needed for comprehensive climate change hazard identification and analysis.

Shadow-constrained shape-from-shading for pixel-wise 3D surface reconstruction at the lunar south pole

ABSTRACT High-resolution digital elevation models (DEMs) of the lunar surface are crucial for lunar exploration missions and scientific research. The emergence of advanced technologies, such as Shape-from-Shading (SfS), has enabled the generation of pixel-wise high-resolution DEMs from monocular images of the lunar surface. However, SfS encounters significant challenges in locations with limited illumination, such as the lunar south pole, where the surface is largely covered by shadows. Therefore, this paper presents a novel shadow-constrained SfS approach for pixel-wise 3D surface reconstruction at the lunar south pole. The proposed approach uses multiple high-resolution images captured under different illumination conditions and an existing low-resolution DEM as the inputs and generates a high-resolution DEM with the same resolution as that of the input image through hierarchical SfS processing incorporating shadow constraints. Experiments were conducted using actual images collected by the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) at the lunar south pole. Comparisons with respect to photogrammetric DEMs generated from stereo NAC images show that the DEMs generated using the proposed approach exhibit the smallest root mean square error (RMSE). Moreover, shaded relief images rendered from the DEMs generated using the proposed approach demonstrate the highest similarity to the actual NAC images. Detailed profile comparisons further validate the effectiveness of the shadow constraint in optimizing 3D reconstruction in regions in proximity to shadows and within shadowed regions. The proposed shadow-constrained SfS approach can be used to generate high-resolution DEMs to support future missions to explore the lunar south pole, with applications including landing site evaluation and route planning for lunar probes or astronauts.

Hydrodynamic modeling of dam breach floods for predicting downstream inundation scenarios using integrated approach of satellite data, unmanned aerial vehicles (UAVs), and Google Earth Engine (GEE)

Dam breach floods pose significant threats to downstream areas, necessitating accurate prediction of inundation scenarios to mitigate potential damage. This paper presents a novel methodology for hydrodynamic modeling of dam breach floods, leveraging a comprehensive approach that integrates satellite imagery, unmanned aerial vehicles (UAVs), and Google Earth Engine (GEE) to forecast downstream inundation scenarios. Specifically, UAVs were utilized to generate high-resolution Digital Elevation Models (DEMs) of the flood-affected areas, ensuring precise representation of topography in the model. The approach incorporates Cartosat DEM data for catchment modeling, while NASA's Global Precipitation Measurement mission data, integrated with GEE, facilitated accurate estimation of rainfall in ungagged catchment areas. Furthermore, the Hydrological Engineering Center-Hydrological Modeling System was employed for rainfall-runoff simulation and flood hydrograph derivation, followed by application of the HEC River Analysis System (RAS) for hydrodynamic modeling under dam breach conditions. This integrated modeling approach was applied as a case study of Banaskantha district, Gujarat, India. The outcome was the generation of scenario maps based on HEC-RAS results, which include flood extent, water depth, and flow velocity, highlighting downstream areas affected by flooding. Validation of the hydrodynamic dam breach model performance was conducted using actual field measurements and simulated results, employing statistical analysis methods including Support Vector Regression (SVR) and linear regression to determine coefficient of determination (R2), Root-Mean-Square Error, and Mean Absolute Error of observed and simulated data. The coefficient of determination (R2) values for measured and simulated flow (0.91) and water level (0.86) calculated using SVR demonstrate strong correlation between observed and simulated values. This integrated study of hydrodynamic modeling in data-scarce areas aids in accurate estimation of future probable flooding in downstream areas in the event of a dam break, underscoring the potential of advanced surveying and modeling techniques in flood assessment and management. Ultimately, this integration of technologies aims to enhance community resilience and mitigate socioeconomic costs associated with dam breach floods.

Effects of digital elevation model resolution on rain-on-grid simulations: a case study in a Slovenian watershed

ABSTRACT The study evaluates the rain-on-grid (RoG) hydraulic model’s sensitivity to digital elevation model (DEM) resolution when simulating an extreme flood in Slovenia. The RoG model is validated against a high-resolution benchmark, showing strong agreement with a Kling-Gupta efficiency of 0.913 and Pearson correlation of 0.964 for a 1 m DEM. Differences are observed in peak shapes and concentration times, attributed to rainfall propagation in RoG grids. DEM resolution significantly impacts performance, with the largest decrease between resolutions of 1 and 5 m. Coarser DEMs yielded higher depths, indicating slope decreases and terrain smoothing. The study concludes that high-resolution DEMs (<1 m) are needed for adequate RoG performance, while commercially available coarser DEMs (30 m) degraded accuracy and should be avoided using this method. Differences from semi-empirical concentration time models are also discussed, and emphasis is placed also on the impacts on water velocity and numerical stability.

Post-seismic topographic shifts and delayed vegetation recovery in the epicentral area of the 2018 Mw 6.6 Hokkaido Eastern Iburi earthquake

The 2018, Mw 6.6 Hokkaido Eastern Iburi earthquake in Japan triggered over 10,000 landsliding in an area spanning about 500 km2, altering the local topography and leading to the accumulation of loose deposits on hillslopes and in valleys. However, a comprehensive post-seismic landslide inventory and an assessment of topographic changes are lacking, hindering a quantitative hazard assessment. Additionally, the extent of vegetation recovery in areas affected by coseismic landslides, a key indicator of post-seismic debris flow hazard, has not been evaluated. Here, we utilize high-resolution digital elevation models and multi-temporal satellite imagery to analyze topographic changes and vegetation dynamics in the earthquake’s epicentral area (seismic intensity &gt;5.5). We observe that the event roughened the overall gentle topography of the region and made the slopes steeper. Owing to the absence of significant rainstorms and snowmelt post 2018, only a few debris remobilizations (60) and new landslides (80) have occurred in the affected region. Moreover, we noticed a slow vegetation recovery in the post-seismic phase, suggesting that the likelihood of debris flows and gully erosion remains elevated, highlighting the need for continued monitoring and assessment.

Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model

In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. An in-depth study of snowmelt runoff is of great practical significance for optimizing water resource management, rational planning of water use, spring flood prevention, and disaster mitigation and prevention, and provides valuable data support for future research on snowmelt runoff.

Pliocene shorelines and the epeirogenic motion of continental margins: a target dataset for dynamic topography models

Abstract. Global mean sea level during the mid-Pliocene epoch (∼3 Ma), when CO2 and temperatures were above present levels, was notably higher than today due to reduced global ice sheet coverage. Nevertheless, the extent to which ice sheets responded to Pliocene warmth remains in question owing to high levels of uncertainty in proxy-based sea level reconstructions as well as solid Earth dynamic models that have been used to evaluate a limited number of data constraints. Here, we present a global dataset of 10 wave-cut scarps that formed by successive Pliocene sea level oscillations and which are observed today at elevations ranging from ∼6 to 109 m above sea level. The present-day elevations of these features have been identified using a combination of high-resolution digital elevation models and field mapping. Using the MATLAB interface TerraceM, we extrapolate the cliff and platform surfaces to determine the elevation of the scarp toe, which in most settings is buried under meters of talus. We correct the scarp-toe elevations for glacial isostatic adjustment and find that this process alone cannot explain observed differences in Pliocene paleo-shoreline elevations around the globe. We next determine the signal associated with mantle dynamic topography by back-advecting the present-day three-dimensional buoyancy structure of the mantle and calculating the difference in radial surface stresses over the last 3 Myr using the convection code ASPECT. We include a wide range of present-day mantle structures (buoyancy and viscosity) constrained by seismic tomography models, geodynamic observations, and rock mechanics laboratory experiments. Finally, we identify preferred dynamic topography change predictions based on their agreement with scarp elevations and use our most confident result to estimate a Pliocene global mean sea level based on one scarp from De Hoop, South Africa. This inference (11.6 ± 5.2 m) is a downward revision and may imply that ice sheets were relatively resistant to warm Pliocene climate conditions. We also conclude, however, that more targeted model development is needed to more reliably infer mid-Pliocene global mean sea level based on all scarps mapped in this study.

A High-Precision Sub-Grid Parameterization Scheme for Clear-Sky Direct Solar Radiation in Complex Terrain—Part I: A High-Precision Fast Terrain Occlusion Algorithm

In atmospheric modeling, sub-grid parameterization is an important method for studying the topographic effects of solar radiation using high-resolution Digital Elevation Model (DEM) data. For reducing the amount of computation, some approximate methods that can lead to errors are used in existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR). The lack of a high-precision fast terrain occlusion algorithm (HPFTOA) remains one of the biggest constraints in this field. This study proposed an HPFTOA. It mainly uses two kinds of acceleration algorithms. One method is to use a dynamic, lossless, and fast occlusion search radius. Another way is to use the rectangular grid for calculations within the accuracy of DEM data to avoid coordinate projection conversions. The test results indicate that the HPFTOA can carry out large-scale computation based on DEM data with a resolution of 90 m. Because it rarely uses approximation algorithms and considers the curvature of the Earth, SPS-CSDSR can achieve unprecedented precision. The HPFTOA can also be used in the fields of mountain solar energy assessment, remote sensing, and telemetry, including terrain-obscuring the probe. As computer performance improves and algorithms and execution code are optimized, the application prospects will be very broad.

Spatiotemporal distribution of environmental microbiota around animal farms adjacent to produce fields in central coast California

This study aimed to identify different environmental microbiota in animal farms adjacent to produce fields and to understand their potential flow pattern. Soil and water samples were collected from 16 locations during the winter, spring, summer, and fall seasons. In addition, a high-resolution digital elevation model helped to create a stream network to understand the potential flow of the microbiome. Metagenomic analysis of the 16 S rRNA gene revealed that soil and water samples from the four seasons harbor diverse microbiome profiles. The phylogenetic relationship of operational taxonomic units (OTUs) is separated by a maximum of 0.6 Bray-Curtis distance. Similarly, the Principal Component Analysis (P = 0.001) demonstrated the soil and water microbiome clustering across different locations and seasons. The relative abundance of Proteobacteria, Bacteroidetes, and Firmicutes was higher in the water samples than in the soil samples. In contrast, the relative abundance of Actinobacteria and Chloroflexi was higher in the soil compared to the water samples. Soil samples in summer and water samples in spring had the highest abundance of Bacteroidetes and Firmicutes, respectively. A unique microbial community structure was found in water samples, with an increased abundance of Hydrogenophaga and Solirubrobacter. Genera that were significantly abundant at a 1% false discovery rate (FDR) among seasons and soil or water samples, include Nocardioides, Gemmatimonas, JG30-KF-CM45, Massilia, Gaiellales, Sphingomonas, KD4-96, Bacillus, Streptomyces, Gaiella, and Gemmatimonadaceae. The relative abundance of pathogenic genera, including Mycobacterium, Bacteroides, Nocardia, Clostridium, and Corynebacterium, were significantly (at 1% FDR) affected by seasons and environmental type. The elevation-based stream network model suggests the potential flow of microbiomes from the animal farm to the produce fields.

Quantifying the Variability of “Fixed-Width” Buffers on Harvested Lands in Western Oregon and Washington

Abstract In contemporary forest management, buffers of unharvested trees are left along streams to protect riparian and aquatic ecosystems. Buffer regulations often focus on specific minimum width requirements, which aid in straightforward regulation and application, but minimum widths also suggest buffered edges are uniform and contain little variability. Conceptual papers suggest that alternative buffer configurations may offer greater flexibility in landscape-level protection, increase forest complexity, and enhance aquatic and riparian biodiversity. However, before considering alternatives to fixed-width buffers, it is necessary to quantify the inherent variability in current buffer practices present on the landscape. In this study, we used aerial imagery to quantify variability of buffer widths in two hundred randomly selected recently harvested units on managed land in Oregon and Washington with both fish-bearing and non-fish-bearing sections of stream. Wider buffers on larger streams had a greater magnitude of variability, but when normalized by stream size, variation was greater in smaller streams, and overall, variation ranged from 25% to 50% of the mean width. Despite local variability, buffer widths rarely fell below 9.14 m (30 ft). The variation quantified here provides an initial measure of variability to inform future management, given emerging interest in variable retention buffers. Study Implications: In contemporary forest management, riparian and aquatic habitat protection usually relies on minimum buffer width regulations. Minimum requirements create the perception that buffered edges are uniform distances from streams containing little variability, so conceptual papers have suggested alternative buffer configurations with variable retention edges to enhance ecological benefits. However, there are several reasons why, in practice, buffer widths may vary substantially from minimum sizes within and across harvest units under current forest management, but this potential variation has not been quantified. Before considering alternative riparian management options, it is necessary to quantify and understand the inherent variability in current practices. By utilizing high-resolution aerial imagery and digital elevation models, we quantified buffer width variation. Using a set of two hundred recently harvested units, we demonstrate notable buffer width variation across managed Pacific Northwest forests. We attribute the variation in buffer widths to the presence of road crossings, tributary junctions, underlying valley slope and slope variation, and flexibility in regulations that may be overlooked in broad evaluations of strict minimum widths. Understanding fundamental information about buffer width variability provides information about current practices and provides a standard against which proposed increases in variability may be compared.

Evaluating the impact of soil erosion on soil quality in an agricultural land, northeastern China

The impact of soil erosion on soil quality is still not systematically understood. The purpose of this study was thus to quantify the impact of soil erosion on soil quality and its change with slope morphology in an agricultural field, northeastern China based on radionuclide 137Cs, unmanned aerial vehicle derived high resolution digital elevation model, and soil sampling. 137Cs method yielded an average soil erosion rate of − 275 t km−2 yr−1 ranging from − 1870 to 1557 t km−2 yr−1. The soil quality index derived from total dataset (SQI_TDS) can be well explained by that derived from minimum data set (SQI_MDS) with a determination coefficient R2 of 0.874. SOM, sand, and cation exchange capacity in the MDS play more important roles than other soil indicators. Soil quality was significantly affected by soil erosion, with Adj. R2 of 0.29 and 0.33 for SQI_TDS and SQI_MDS, respectively. The spatial variations of soil erosion and soil quality were both affected by slope topography. Soil erosion must be controlled according to topographic and erosion characteristics in northeastern China.

Effects of input data accuracy, catchment threshold areas and calibration algorithms on model uncertainty reduction

AbstractLow resolution of input data and equifinality in model calibration can lead to inaccuracy and insufficient reflection of spatial differences, thereby increasing model errors. However, the impact of input data accuracy, catchment threshold area, and calibration algorithm on model uncertainty reduction has not yet been well understood. The sequential uncertainty fitting version 2 (SUFI‐2) that is linked with the Soil and Water Assessment Tool (SWAT) in the package called SWAT Calibration Uncertainty Programs (SWAT‐CUP) was introduced to quantify the effects of different input data resolutions on parameter sensitivity and model uncertainty in the Jinghe River watershed, and the effects of different sub‐basin delineations and other two calibration algorithms on model uncertainty were also comparatively analysed. (i) USLE_C, EPCO, ALPHA_BNK, and CN2 are the most sensitive parameters among all SWAT projects. When the change of digital elevation model (DEM) resolution is small, the sensitivity of parameters does not change obviously. When the DEM resolution changes significantly, BIOMIX, LAT_SED, USLE_K, and CH_N1 become highly sensitive parameters by replacing OV_N, SMTMP, SURLAG, and USLE_P. However, the change in land use resolution has little impact on parameter sensitivity, with only a slight change in the sensitivity ranking of specific parameters. (ii) Model uncertainty responded to changes in the resolution of DEM more than land use. Most of the runoff simulations had smaller uncertainties (P factor, R factor, percentage of bias [PBIAS]) than sediment. High resolution DEM data reduced model uncertainty, but the models with 2000 m DEM resolution also achieved small uncertainty. Small catchment threshold area leads to high uncertainty of the model, and large catchment threshold areas decrease the model uncertainty. The model has relatively good simulation effects in runoff and sediment when the catchment threshold area was 2000 km2. (iii) The SWAT model has different simulation deviations and uncertainties in different calibration algorithms, the SUFI‐2 and generalized likelihood uncertainty estimation (GLUE) algorithms show better applicability than particle swarm optimization (PSO). The NSE indicators of the three algorithms are in the following order: SUFI‐2 &gt; GLUE &gt; PSO for runoff, and GLUE &gt; SUFI‐2 &gt; PSO for sediment. This study helps us understand the cause, knowledge of which moves from the particular to the general by the comprehension of essence, power, and nature in reducing model uncertainty.

Active faults along Indonesia’s first high-speed rail line

Abstract The cities of Jakarta and Bandung, two vital hubs in the western part of Java, are now connected by a high-speed rail line. However, potential earthquake hazards arise as the line intersects two active faults in West Java. To address this concern, we conducted a detailed geomorphological analysis using high-resolution DEM data (8-meter resolution) combine with 30-m resolution data to locate fault lines along the rail infrastructure. In the north, the line intersects the West Java back-arc thrust, while in the south, it crosses the junction of the Lembang Fault and Cimandiri Fault in Padalarang. However, young deposits and vegetation still could obscure fault traces in specific areas observed from high-resolution DEM data. To overcome this challenge, we employed UAV drone mapping to capture finer geomorphology details. This information then combined with paleoseismology trenching to uncover the active structural features. The aim is to enhance the railway’s resilience; and build monitoring and early warning systems for the high-speed train operation system to seismic events.

Physical features of Adam’s Bridge interpreted from ICESat-2 based high-resolution digital bathymetric elevation model

Adam’s Bridge is a submerged ridge connecting India and Sri Lanka, generally regarded as a chain of shoals extending for ~ 29 km from Dhanushkodi on the Indian side to Talaimannar Island of Sri Lanka. A high-resolution digital bathymetric elevation model generated using the seafloor returned photons of ICESat-2 was used to understand the intricate details of Adam’s Bridge structure. Photons emanating from ICESat-2’s green laser have the potential to detect the seafloor up to a depth of ~ 40 m; taking a cue from this potentiality, in our research, we have accrued ~ 0.2 million photons representing the depth information and generated a 10 m resolution bathymetric data for the extent of Adam’s Bridge. Visual interpretations made from this bathymetric data through 3D perspectives with multi-directional lighting effects, and also with the derived parameters like contours, slope, and volumetric analysis, enabled us to recognize the current form of Adam’s Bridge’s physical features. The results from our research confirm that, in its entirety, Adam’s Bridge is a submarine continuation of Dhanushkodi and Talaimannar Island. Throughout the crest line of Adam’s Bridge, approximately 1.5 km on either side is highly undulating within the super-shallow water with occurrences of sudden depths. There is an asymmetry of transverse slopes to the base on both sides of Adam’s Bridge, indicating dominant transgression of material energy from the waters of the Gulf of Mannar compared to the Palk Strait. The volume of Adam’s Bridge computed in our research yielded a value of ~ 1 km3; interestingly, only 0.02 percent of this volume is above the mean sea level, and in general, the same is visible in optical satellite imagery—in total ~ 99.98 percent of the Adam’s Bridge is submerged in shallow and super-shallow waters.

A High-Resolution Digital Bathymetric Elevation Model Derived from ICESat-2 for Adam’s Bridge

This data descriptor elaborates the details of a high-resolution digital bathymetric elevation model generated for the region, namely, Adam’s Bridge, which encompasses a chain of shoals between Rameswaram Island, off the southeastern coast of Tamil Nadu, India, and Mannar Island, off the northwestern coast of Sri Lanka. The proposed dataset has taken advantage of the photon penetrability in the shallow waters by the green laser of ICESat-2 LiDAR to derive the seabed topography. Seafloor depths from ~0.2 million geolocated photons of ICESat-2 for the study area were accrued and interpolated to generate a 10 m digital bathymetric elevation model. Adam’s Bridge, an isthmus and submerged reefal assemblage in shallow and super-shallow waters, is a feature of scientific curiosity. Our dataset has the potential to enhance the understanding of Adam’s Bridge structure by providing substantial information to reconstruct its evolution.

A dataset of high-resolution digital elevation models of the Skeiðarársandur kettle holes, Southern Iceland

In studies of the relief evolution of smaller landforms, up to several dozen meters in width/diameter, digital elevation models (DEMs) freely accessible in different repositories may be insufficient in terms of resolution. Existing geophysical or photogrammetric equipment is not always available due to costs, conditions and regulations, especially for students or young researchers. An alternative may be the handy-held ground-based Structure from Motion technique. It allows us to obtain free high-resolution DEMs (~0.05 m) using open-source software. The method was tested on kettle holes of the glacial flood origin on Skeiðarársandur (S Iceland). The material was collected in 2022 at two outwash levels of different ages and vegetation cover. The dataset is available in the Zenodo repository; the first part is data processed in point clouds and DEMs, and the second includes original videos in MOV format. The data can be used as a reference to assess changes in the kettle hole relief in subsequent research seasons, as a methodological study for other projects, or for didactic purposes.