Resolution Digital Elevation Model Research Articles

Stereo bathymetry to monitor small seasonal agriculture water ponds in ungauged areas

Abstract. Small reservoirs represent a critical water supply to farmers across semi-arid regions, but their hydrological modelling suffers from data scarcity and highly variable and localised rainfall intensities. Over 200,000 ancient rainwater harvesting reservoirs (“tanks”) exist across South India, but with their complex history, considerable size variation, and widespread distribution, understanding the hydrological role of these tanks has been difficult. Fortunately, the last decade has seen improvements in sensors and technologies that enhance our ability to assess the hydrological role of these tanks. In particular, high-resolution Digital Elevation Model (DEMs), now much easier to produce, can be used to improve the characterization of tanks and their surrounding watersheds. Here, a high-resolution DEM is created during the lowest reservoir conditions using Pléiades stereoscopy, and along with two global DEMs, compared with volume estimates from a field-derived UAV reference DEM for a set of tanks in South India. This study demonstrates that a Pléiades-derived DEM can capture accurate reservoir geometry and, when simulating water volume, achieves volumetric differences of 2–8% compared to our UAV reference data. The Pléiades-derived-DEM produced an equivalent height bias less than the expected bias for the recently launched Surface Water and Ocean Topography (SWOT) mission. Deriving high-resolution tank bathymetry from space during low-water conditions provides an opportunity to systematically and repeatably measure tank volume. These results are encouraging in efforts to utilize very high resolution DEMs chosen at an appropriate hydrological time, particularly in regions where water management and security is paramount.

Effects of Digital Elevation Model Resolution on Unmanned Aerial Vehicle-Based Topographic Change Detection in Human-Altered Landscapes

UAV-based topographic change detection is widely used in geoscience communities. The change detection involves comparison of two digital elevation models (DEMs) produced by UAV surveys, which are affected by the DEM resolution. Coarse resolution DEMs introduce errors in change detection, but the DEM resolution effect remains poorly understood. Moreover, effective strategies for mitigating the resolution effect have yet to be investigated. This study generated UAV-based DEMs at resolutions ranging from 0.1 m to 10 m with various resampling methods. The impact of DEM resolution on topographic change detection was then evaluated by analyzing the difference of DEM (DoD) and volume budget errors with indices such as mean error (ME), standard deviation (STD), and Moran’s I. The results from two human-altered landscapes showed that the random errors of DoD increase rapidly with the DEM resolution coarsening, while DoD systematic errors (spatial distribution of errors) become stable after 4 m resolution. The volume budget errors also increase with DEM coarsening. Coarser resolution DEMs tend to underestimate the volume budget (gross erosion, gross deposition, and net changes). Moreover, selecting an appropriate method for generating DEM is beneficial in decreasing the errors caused by the resolution effect. Among the seven methods (MAX, MIN, MEAN, BIL, NEAR, NEB, and TIN), the BIL method is optimum for mitigating both DoD and volume errors. The NEAR, NEB, and TIN methods are equivalent, and they are superior to the aggregation methods (MAX, MIN, MEAN). The slope of DoD (SDoD) should be considered when selecting a resolution for change detection. Large errors tend to appear in areas with large SDoD and vice versa. Coarse resolution DEMs are tolerable in areas with low SDoD, while high resolution DEMs are necessary in areas with large SDoD.

Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data

Landform maps are important tools in assessment of soil- and eco-hydrogeomorphic processes and hazards, hydrological modeling, and natural resources and land management. Traditional techniques of mapping landforms based on field surveys or from aerial photographs can be time and labor intensive, highlighting the importance of remote sensing products based automatic or semi-automatic approaches. In addition, the time-intensive manual labeling can also be subjective rather than an objective identification of the landform. Here we implemented such an objective approach applying a random forest machine learning algorithm to a set of observed landform data and 1m horizontal resolution bare-earth digital elevation model (DEM) developed from airborne light detection and ranging (LiDAR) data to rapidly map various landforms of a hilly landscape. The landform classification includes upland plateaus, ridges, convex slopes, planar slopes, concave slopes, stream channels, and valley bottoms, across a 400 km2 hilly landscape of the Ozark Mountains in northeastern Oklahoma. We used 4200 landform observations (600 per landform) and eight topographic indices derived from 2 m, 5 m and 10 m resolution LiDAR DEM in random forest algorithm to develop 2 m, 5 m and 10 m resolution landform models. We test the effectiveness of DEM resolution in mapping landforms via comparison of observed landforms with modeled landforms. Results showed that the approach mapped ∼84% of observed landforms when covariates were at 2 m resolution to ∼89% when they were at 10 m resolution. However, predicted maps showed that the 2 m resolution covariates performed better at capturing accurate landform boundaries and details of small-sized landforms such as stream channels and ridges. The approach presented here significantly reduces the time required for mapping landforms compared to traditional techniques using aerial imagery and field observations and allows incorporation of a wide variety of covariates. The landform map developed using this approach has several potential applications. It could be utilized in hydrological modeling, natural resource management, and characterizing soil-geomorphic processes and hazards in a hilly landscape.

Tectonic Activity Analysis of the Laji-Jishi Shan Fault Zone: Insights from Geomorphic Indices and Crustal Deformation Data

Fault segmentation plays a critical role in assessing seismic hazards, particularly in tectonically complex regions. The Laji-Jishi Shan Fault Zone (LJSFZ), located on the northeastern margin of the Tibetan Plateau, is a key structure that accommodates regional tectonic stress. This study integrates geomorphic indices, cross-fault deformation rate profiles, and 3D crustal electrical structure data to analyze the varying levels of tectonic activity across different segments of the LJSFZ. We extracted 160 drainage basins along the strike of the LJSFZ from a 30 m resolution digital elevation model and calculated geomorphic indices, including the hypsometric integral (HI), stream length-gradient index (SL), and channel steepness index (ksn), to assess the variations in tectonic activity intensity along the strike of the LJSFZ. The basins were categorized based on river flow directions to capture potential differences across the fault zone. Our results show that the eastern basins of the LJSFZ exhibit the strongest tectonic activity, demonstrated by significantly higher SL and ksn values compared to other regions. A detailed segmentation analysis along the northern Laji Shan Fault and eastern Jishi Shan Fault identified distinct fault segments characterized by variations in SL and ksn indices. Segments with high SL values (>500) correspond to higher crustal uplift rates (~3 mm/year), while segments with lower SL values exhibit lower uplift rates (~2 mm/year), as confirmed by cross-fault deformation profiles derived from GNSS and InSAR data. This correlation demonstrates that geomorphic indices effectively reflect fault activity intensity. Additionally, 3D crustal electrical structure data further indicate that highly conductive mid- to lower-crustal materials originating from the interior of the Tibetan Plateau are obstructed at segment L3 of the LJSFZ. This obstruction leads to localized intense uplift and enhanced fault activity. These findings suggest that while the regional stress–strain pattern of the northeastern Tibetan Plateau is the primary driver of the segmented activity along the Laji-Jishi Shan belt, the direction of localized crustal flow is a critical factor influencing fault activity segmentation.

Settlement Suitability Analysis: The Case of Bursa City

Abstract: Nowadays, the existing built-up area texture in cities has started to shift towards areas that are not suitable for settlement. In this sense, settlement suitability analyses play a critical role in the realisation of sustainable development goals. Detailed analyses are required to formulate an effective settlement strategy in regions with large and diverse natural features such as Bursa. In this study, in order to determine the areas suitable for settlement in the study area, which covers the borders of Osmangazi, Nilüfer and Yıldırım districts, which are the central districts of Bursa city, a settlement suitability analysis was carried out with the Analytical Hierarchy Process (AHP) method using 9 parameters consisting of slope, elevation, lithology, land use, precipitation, temperature, distance to stream, distance to fault and erosion. The main underlying data used in the study are 10m resolution Digital Elevation Model (DEM), lithology, land use, erosion, precipitation, and temperature (WorldClim) data of Bursa city. As a result of the analysis, it was determined that 9% of the city is very suitable, 44% is less suitable and 47% is not suitable. The area where the city was established is in very suitable and moderate suitable class. It is observed that the settlements established in the study area, especially in the areas close to the fault line and the main river branch, are in the moderate suitability class. In addition, it has been determined that the erosion risk is in the low class, and the settlements far from the main river branch and fault line are in the very favourable class. While it is observed that Bursa city is located at appropriate values in terms of topography, it is seen that especially the southern part of the city is not sufficiently suitable in terms of distance to fault lines. The results obtained aim to contribute to sustainable settlement planning and to provide a guide for the methods and processes to be used in settlement suitability analysis.

A synergic approach using the model and remote sensing data for flood monitoring in under-observed transboundary rivers

ABSTRACT The southern plain of Nepal recognized as the ‘granary of Nepal’, confronts recurrent monsoon-induced flooding, posing a substantial threat to its pivotal role as a major agricultural contributor to the national economy. As an analysis, this study employs advanced satellite imagery to delineate historical floods in nine flood-prone transboundary basins and compares the rainfall-induced model-based inundation in the West Rapti Basin (WRB) to validate the result. The extent of flooding was mapped between 2015 and 2022 using Sentinel-1 Synthetic Aperture Radar data processed on Google Earth Engine. Hydrodynamic modelling centred on the WRB, incorporated daily measured precipitation data with varying return periods over a 10 m resolution digital elevation model generated through an in situ survey. The model was calibrated for the August 2017 flood event with Nash–Sutcliffe efficiency greater than 70% and validation reasonably with satellite-derived flood maps with Cohen's Kappa value of 0.58 and an overall accuracy metric of 0.84. This synergic approach integrates climatology, remote sensing data, and hydraulics to monitor transboundary river floods in Nepal where precise hydro-meteorological data are limited, thus, offering continuous all-weather monitoring.

Morphometric and morphotectonic characteristics of a Tropical River Basin, North Kerala, India using geospatial technology

ABSTRACT This study delves into morphometric and morphotectonic analyses to unveil the evolutionary trajectory of Kerala's Korapuzha river basin. Employing advanced GIS and remote-sensing techniques, we explore the basin's geomorphological evolution and landform development. Our approach integrates data from a 1:50,000 scale toposheet and a 30 m resolution Digital Elevation Model (DEM), facilitating a detailed evaluation of basin characteristics. Through subdivision into KB-1 and KB-2 sub-basins, distinct morphometric patterns and morphotectonic features are discerned. The elongated basin configuration suggests ongoing tectonic activity, profoundly shaping its unique geomorphic evolution. To unravel tectonic influences, we employ morphometric indices, including the Relative Active Tectonic Index (IRAT), revealing neo-tectonic activity and dynamic landscape changes. Our study enriches our understanding of the Korapuzha river basin's evolution, illuminating the interplay between tectonic forces and geomorphic processes. Offering insights into tropical river systems, it contributes to broader landscape dynamic comprehension and informs sustainable land management practices. The IRAT calculation for the Korapuzha basin is based on the average of five geomorphic index classes, with resulting classifications indicating varying levels of tectonic activity. KB-1 and KB-2 sub-basins’ IRAT values enumerated as 2.2 and 2, respectively hence fall into classes 4 and 3, indicating low and moderate tectonic activity, respectively. The presence of tectonism in the study area revealed from geomorphic indices and IRAT, was acknowledged and evinced precisely by following the analysis of the SL index and GLA index method.

Hydrological Connectivity Response of Typical Soil and Water Conservation Measures Based on SIMulated Water Erosion Model: A Case Study of Tongshuang Watershed in the Black Soil Region of Northeast China

The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55–27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage.

Impact Assessment of Digital Elevation Model (DEM) Resolution on Drainage System Extraction and the Evaluation of Mass Movement Hazards in the Upper Catchment

Impact Assessment of Digital Elevation Model (DEM) Resolution on Drainage System Extraction and the Evaluation of Mass Movement Hazards in the Upper Catchment

Evaluating the impact of DEM interpolation algorithms on relief index for soil resource management

Abstract Soil resource management is fundamentally integral to environmental sustainability and agricultural productivity. The digital elevation model (DEM) is the fundamental data for analyzing landform surfaces, which introduces an opportunity to obtain a broad spectrum of terrain factors to simplify interpreting the patterns and processes in the geoscience field. The accuracy and resolution of DEM are crucial for their effective use, and many algorithms have been developed to interpolate digital elevation data from a set of known points. Although primary topographic variables derived from grid datasets are important, secondary variables, such as the relief index (RFI), play a more critical role in understanding the complicated relationship between soil properties and landform attributes. The RFI is attained from a DEM by calculating the elevation range within a given neighborhood surrounding a central cell. It is an essential predictor of soil natural resource management that measures the degree of differentiation surface relief. In addition, it is beneficial for perceiving the landscape and its management. This study presents a comprehensive zonal analysis comparing the RFI values derived from multiple interpolation-based DEMs. It investigates deterministic and geostatistical interpolators, such as inverse distance weighted and natural neighbor across distinct zones with diverse topographical characteristics. The findings indicated a high correlation between the RFI and the reliability of the DEM, and the natural neighbor technique provided superior performance against others. The results revealed that the choice of spatial interpolation technique significantly affects the accuracy and reliability of RFI models.

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.

Investigation of the Basin Characteristics through Morphometric Analysis of Hadejia River Sub-Basin: Implications for Groundwater Recharge

Understanding the geohydrological properties of a drainage basin in relation to the topographical feature and its flow patterns depends heavily on morphometric analysis. Estimating a watershed's frequency of infiltration and runoff as well as its other hydrological characteristics is also helpful. The study was conducted using Geographical Information System (GIS) techniques with the aim of establishing relationship between surface morphometry, underlying geology and groundwater recharge. For detailed measurement and analysis, Digital Elevation Model (DEM) and high resolution imageries were employed for basin delineation, slope characterization, channel network extraction and stream ordering in order to derive the linear, areal, and relief aspects of morphometric parameters. The findings showed that a total number of 116 streams joined the 4th order stream in which 83 streams were 1st order, 25 streams were 2nd order, 7 streams were 3rd order and the major trunk was 4th order stream, occupied an area of 1486.86km2. The stream network's drainage system exhibits dendritic design. The results further indicate that the values for stream frequency, infiltration number, drainage density, drainage texture, length of overland flow, elongation ratio and basin relief are 0.08, 0.032, 0.41km/km2, 0.023, 1.22km, 0.54 and 28.59m respectively. The observed values of both linear, areal and relief parameters were generally low. Low values for the areal and relief criteria indicates that the sub-basin is at its youthful stage of development and possesses very good permeable subsurface formation and prospect with the possibility of high potential groundwater resources. The result help us understand the connections between hydrological variables and geomorphological parameters as guidance and/or decision-making instruments for the authorities to develop decisions for the environmentally friendly growth of the basin, water supply planning, water budgeting, and disaster mitigation within the Hadejia river sub-basin.

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.

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

AbstractTopography and the computational mesh grid are fundamental inputs to all two‐dimensional (2D) hydrodynamic models, however their resolutions are often arbitrarily selected based on data availability. With the increasing use of drone technology, the end user can collect topographic data down to centimeter‐scale resolution. With this advancement comes the responsibility of choosing a resolution. In this study, we investigated how the choice of mesh grid and digital elevation model (DEM) resolutions affect 2D hydrodynamic modeling results, specifically water depths, velocities, and inundation extent. We made pairwise comparisons between simulations from a 2D HEC‐RAS model with varying mesh grid resolutions (1 and 2 m) and drone‐based lidar DEM resolutions (0.1, 0.25, 0.5, 1, and 2 m) over a 1.5 km reach of Stroubles Creek in Blacksburg, Virginia. The model was rerun for up to ±4% change in floodplain roughness to determine how the DEM and mesh grid changes relate to an equivalent change in roughness. We found that the modeled differences from resolution change were equivalent to altering floodplain roughness by up to 12% for depths and 44% for velocities. The largest differences in velocity were concentrated at the channel‐floodplain interface, whereas differences in depth occurred laterally throughout the floodplain and were not correlated with lidar ground point density. We also found that the inundation boundary is dependent on the DEM resolution. Our results suggest that modelers should carefully consider what resolution best represents the terrain while also resolving important riparian topographic features.

A new approach to flood susceptibility analysis of urbanised alluvial fans: the case of Bursa City (Türkiye)

AbstractFloods stand out as one of the most significant disasters impacting human life, causing widespread economic and social damage across the globe. Numerous research studies have concentrated on comprehending the contributing factors of flooding. Despite the prevalence of morphometry-based basin flood susceptibility analyses in existing literature, a comprehensive examination that encompasses anthropogenic features in alluvial fans is notably lacking. This study aims to evaluate the flood susceptibility of alluvial fans and their catchments in urbanised areas, integrating individual and collective basin/fan (B/F) morphometry and land use characteristics with flood inventory data. The study area selected for this investigation is the basin and fan systems situated on the northern slope of the Uludağ Massif (2543 m), the highest point in the Marmara Region, northwestern Türkiye. Twelve basin morphometric parameters were applied to 5 m resolution Digital Elevation Model data, while six fan morphometric and anthropogenic parameters were applied to alluvial fans. In addition, the results were assessed using the Normalised Morphometric Flood Index method to mitigate subjectivity in result ranking. According to the integrated basin/fan flood susceptibility results obtained through bivariate analysis, B/F6 exhibits a very high susceptibility, while B/F1, B/F3, B/F2, B/F5, B/F4, and B11/F8 demonstrate high susceptibility. B7, 8, 9, 10/F7 display a moderate potential for generating floods. These findings align significantly with historical flood events in the basin/fan area.

Comprehensive Analysis of Landform and Land Use/ Land Cover Mapping of Waghora Watershed Using Sentinal-2B and SRTM-DEM Data

This paper aims to integrate the use of high spectral resolution a remote sensing data of Sentinel-2B imagery along with the Digital Elevation Model (DEM) derived from the SRTM stereo data to delineate the landforms and analyze the land use and land cover in Waghora watershed, Sausar tehsil, Chhindwara district, situated on basaltic terrain in northern Deccan plateau. A 30 m resolution DEM of the study area was generated, capturing terrain parameters like elevation, slope, aspect, hillshade, and drainage. Sentinel-2B (10 m) images from two seasons were collected FCC (false colour composite) and were prepared by ARCGIS software. combination of Sentinel-2B imagery, SRTM-DEM data, and ground truth verifications to delineate eight major landforms in the studied area. Slope information, extracted from high-resolution DEMs, reveals 4 distinct slope classes. The landforms, including Plateau, Escarpment, Foot Slope, Upper Pediment, Lower Pediment, Valley, Interfluve, and Mound, are characterized based on visual interpretation and geological context. Each landform exhibits unique features, elevation ranges, and dominant land use/cover types, such as single crop cultivation, forest, or degraded land. This detailed terrain analysis aids in land-use planning and environmental management initiatives. The land use/land cover analysis utilizes Sentinel-2B data to identify five classes: degraded forest, double crop, single crop, orchard, and land with and without scrubs. Dense forest dominates 24.2% of the watershed, while double crop and single crop lands cover 36.7% and 24.2% respectively. Orchards occupy a minimal 0.8% of the area, and wastelands account for 5.7%. The relationship between landforms, slope, and land use/cover reveals dominant forestation on steep escarpments, while valleys and interfluves support double cropping due to gentle slopes and depositional processesThe study elucidated connections to examine diverse biophysical phenomena. It highlights the effectiveness of employing SRTM-DEM and Sentinel-2B imagery for analyzing geomorphic characteristics and mapping land use/land cover, offering significant perspectives for land management and planning approaches.

Multiscale Analysis of High Resolution Digital Elevation Models Using the Wavelet Transform

A technique is proposed for choosing the optimal wavelet basis in terms of decorrelation of the spectral coefficients of the wavelet basis when solving the problem of representation of digital elevation models. In the course of the work, it was revealed that the selection of the spectral transform basis significantly affects the accuracy of the representation of the original model. The proposed method to the decomposition of digital elevation models based on the discrete wavelet transform does not require large computational costs. A technique is proposed for selection the optimal wavelet basis from the position of the minimum mean square error of the reconstructed signal, when quantizing the high-frequency expansion coefficients. Expressions are obtained for generating scaling and wavelet functions in space. The method developed to represent digital elevation models has good properties, which allows to significantly increase the resolution of digital elevation models in the implemented regional geoinformation system.

Digital topographic analysis and lineament interpretation south of the Lena Delta, North Siberia: Landscape expression of its tectonic activity

This study applies semi-automated techniques to analyze the landforms, morphostructure, and geology of the Kharaulakh and Chekanovsky sectors, south of the Lena Delta, northern Siberia. High-resolution data, including TanDEM-X 30 m spatial resolution Digital Elevation Models (DEM), 2 m spatial resolution ArcticDEM Digital Surface Models (DSM), and Sentinel-2 satellite imagery, serve as the basis for the analysis. Digital terrain classification and identification of tectonic lineaments are performed using the Benthic Terrain Modeler (BTM) and Linear Extraction (LINE) algorithm, respectively. Additionally, a hypsometric analysis is conducted to assess areas of potential neotectonic activity. 873 lineaments are identified, primarily in NE-SW and E-W orientations. NW-SE lineaments perpendicular to the lithological and fold belt strikes in the Kharaulakh Ridge suggest inheritance from original depositional settings or later compressional tectonics, now appearing as valleys and weak zones facilitating erosion and river incision. Longer N-S or NNW-SSE lineaments in the Kharaulakh Sector are associated with thrust sheets of the Verkhoyansk fold-and-thrust belt and Cenozoic graben structures linked to the formation of the Laptev Sea Rift System and ongoing regional deformation. The Chekanovsky Sector, marked by epiplatform blocks and hills, presents a dissected plateau with steep valleys. Here, high hypsometric integral values are attributed to compression and uplift near the southwestern boundary of the Laptev Sea Microplate.

An Overview of the Importance of DEM Resolution in Soil Erosion Assessment

Soil erosion is a geomorphic process that can cause hazards and socioeconomic losses. These processes occur through subsurface and overland flows. We conducted a literature review on the importance of digital elevation model (DEM) resolution in soil erosion assessment. This review article presents the state of the art regarding the importance of the resolution of DEM in soil erosion assessment. It explains why DEM resolution is important for understanding how erosion is assessed. Further research is needed, however, to better explore the connectivity and morphology of soil erosion, including its subsurface watershed and behavior, as well as several challenges faced in using DEMs for soil erosion analysis. Understanding quantitative variables that initiate soil erosion and considering multihazard assessments can aid in developing techniques and assisting decision makers in designing accurate systems. Exploring soil erosion also needs improved high-resolution tools (e.g., unmanned aerial vehicles) that enable more reliable predictions of soil erosion and the detection of erosion-affected regions. Addressing these knowledge gaps will enhance our understanding of subsurface and surface erosion, contribute to a better understanding of landscape evolution, and further improve the development of effective strategies and techniques for soil erosion control. The research findings are highly transferable in diverse geographical contexts worldwide.