Detailed Digital Elevation Model Research Articles

UAS-LC-GNSS: Precision Surveying with a Low-Cost GNSS System for Commercial Drones

INGV (National Institute of Geophysics and Volcanology, Italy) is one of the institutions that studies and monitors the geophysical phenomena (earthquakes, volcanic eruptions, landslides, etc.) that occur on Earth. During these events, it is essential to carry out a large, detailed and fast map of the affected areas.If we think of the difficulties encountered during the mapping of the fault sources for the 2016 earthquake in central Italy, we can understand how the UAS (Unmanned Aircraft System) can be a valid “low-cost” alternative to the traditional methods of surveys.These devices, thanks to precision instrumentation such as GNSS (Global Navigation Satellite Systems) receivers and IMU (Inertial Measurement Unit) control units, allow a detailed reconstruction of the investigated areas, especially for small-scale analysis applications. These aircraft are based on multiple technologies and show great investigative capabilities, therefore they must be considered as complete systems.Starting from these concepts, we have developed a low-cost RTK/PPK (Real Time Kinematic/Post Processing Kinematic) GNSS survey system on “commercial” UAVs (Unmanned Aerial Vehicles), i.e. professional drones that are not created to be modified.We have demonstrated how the integration of a GNSS RTK/PPK module on commercial UAVs makes the system efficient for the reconstruction of a highly detailed and precise DEM (Digital Elevation Model), without using GCP (Ground Control Point), allowing to make precision measurements in areas that are difficult to explore and investigate.

Digital Elevation Model Development Of The Volga And Don River’s Delta And Application In Hydrological Modeling

The article describes the methodology for constructing digital elevation models for the vast delta areas of the Don and Volga rivers for further use in mathematical models of flooding from surges. The initial cartographic data and features of the delta regions are described. The methods of information processing are considered in detail. An algorithm for constructing a DEM has been developed to obtain highly detailed digital elevation models. The algorithm is based on combining the DEM of individual key features - land, the depths of the hydrographic network and the bathymetry of the receiving reservoir for the river. The topographic maps, maps of the navigable route depths, hydrographic maps, and satellite images Landsat-8 and Sentinel-2 were used to create the DEM of the Don and Volga river. To build individual DEMs, a raster of the absolute depth of the channels, a hydrography DEM, a land DEM, and a shelf DEM were created using geoinformation systems. To assess the possibility of using obtained DEMs in hydrological models based on HEC-RAS, we conducted training and verification calculations of water level during wind surge phenomena in Don Delta using different surface roughness coefficients. The calculation results show good reproducibility of observed water level fluctuation in the Don Delta using obtained DEM with a roughness coefficient of 0.0125. Also, we carried out similar calculations of storm surge phenomena in the Volga Delta using obtained DEM and combinations of various riverbed and not riverbed roughness coefficients. The combination of 0.007 for riverbed and 0.02 for not riverbed surfaces reproduces the observed water level fluctuation during storm surge phenomena in Volga Delta. The constructed DEMs for the Volga and Don deltas made it possible to reproduce the observed dynamics of river discharges and water level fluctuations during surge events. Such detailed DEMs, taking into account all the complexity of the coastal and delta relief, were created for the first time for the Volga and Don.

Simulation of overland flow in the Domica cave area flood events using the r.sim.water module

The flash floods are very important hydrometeorological situations affecting the Domica cave area. The flash floods depend on several factors such as the amount of precipitation, land cover, phenological phase of the vegetation, or soil infiltration rate. This paper focuses on the simulation of flood events occurring in the winter and summer seasons on the Silická plateau. The main aim of the paper is the evaluation of the effects of model parameterisation and interpretation of spatial aspects of the overland flow during the flood events. GRASS GIS software, specifically its r.sim.water module was used for hydro-logical modelling of the surface runoff. The simulation included a detailed digital eleva-tion model calculated from airborne laser scanning data and land cover derived from a detailed orthoimagery map. The infiltration rate parameter and the Manning’s roughness coefficient were estimated based on land cover classes. The simulation produced water depth maps describing flood events. The results showed that during the winter season in 2016, a smaller rainfall intensity was necessary for flood occurrence and that this phenomenon is primarily caused by frozen soil, through which no water is being infiltrated. The simulation of summer flood event in 2017 shows similar results of runoff accumulation but with higher rainfall intensity and infiltration rate. The flash flood event in 2021 turned out to be differ-ent, with such extreme rainfall intensity that even higher infiltration rate was insufficient in slowing the surface runoff. The results also proved the suitability of the chosen method for small-scale high-resolution hydrological simulations. URL: https://www.gcass.science.upjs.sk/

Determination of potential secondary lahar hazard areas based on pre-and post-eruption UAV DEMs: Automatic identification of initial lahar starting points and supplied lahar volume

• Lahar starts point (LSP) and supplied volume (SLV) constrain inundation prediction. • Uncertainty of LSP and SLV parameters are subjected to misinterpreted prediction. • Proposed PEARPY program aims to estimate actual values of the parameters. • The program produces a realistic lahar simulation with a satisfactory similarity. • High-detailed UAV DEM prevents over or underestimation of lahar run-out prediction. Secondary lahars, generated after volcanic eruptions, may pose significant threats to life and infrastructure. Secondary lahars typically develop from ash deposits and other volcanic debris that remobilize downstream via intense rainfall. The lahar inundation zone after eruptions must be predicted to minimize the impact. This prediction can be modeled based on digital elevation models (DEMs) and two parameters associated with lahar simulations: the lahar starting point (LSP), which indicates the potential locations at which a lahar flow may initiate, and supplied lahar volume (SLV), which is the lahar volume corresponding to each LSP. These parameters are typically determined by assumptions based on past lahar events, which may be unrealistic and often misinterpreted in the inundation prediction. To address this problem, this paper proposes an automated method to estimate the LSP and SLV based on pre-and post-eruption DEMs generated by unmanned aerial vehicle (UAV) images and simulate the inundation zone using the LAHARZ model. The study site is located in the southeast region of Mount Agung (Indonesia), and the objective is to mitigate the potential secondary lahar hazard after the 2017–2019 eruption crisis. Results show that the parameter estimations using the high-resolution UAV DEM and LAHARZ produce a realistic lahar simulation, with a satisfactory similarity of 82%, as verified against the lahar footprint. Moreover, we compare the results with those obtained using TerraSAR-X DEM and demonstrate the importance of using a detailed UAV DEM to avoid underestimating the lahar runout and ensure that the simulated inundation zones mimic real lahars.

Benthic macrohabitat classification and Madracis spp. coral patch distribution in a deep-sea marine protected area of Colombia

Corales de Profundidad National Natural Park (CPNNP), at the central Colombian Caribbean margin, has an extension of 142.195 ha with depths ranging from 34 to 1,234 m. The CPNNP’s essential ecological value is Madracis spp. as potential structure-forming deep-water coral; this work represents the first footages of these unique habitats for the Colombian Caribbean. In 11 sectors, remote video surveys are conducted, based on a detailed digital elevation model. From these sectors, four cover mesophotic zones (46–169m depth), and seven cover aphotic zones (up to 354m depth). After still images’ description and interpretation, a guide was generated with nine types of macrohabitats surrounding the coral formations of the CPNNP: soft substrate (mud/sand), soft substrate/rubble/rock with solitary corals, coral and shell rubble, rock/ledges with attached fauna, rugged stones with attached fauna, hard substrate with attached fauna, sandstone with attached fauna, soft substrate with burrows, and pockmark with attached fauna. Video transect analysis confirms the occurrence of Madracis spp., with coral patches as the main framework builder of the CPNNP. These patches comprise many clumped 50 to 80 cm high coral colonies that developed over slow slopes, with seafloor elevations between 107 and 233 m and textured soils of soft and not very compact ridges, associated with the macrohabitat sandstone with attached fauna. This information is being used for the management and monitoring of this unique protected area.

Mapping rill soil erosion in agricultural fields with UAV‐borne remote sensing data

AbstractSoil erosion by water is a main form of land degradation worldwide. The problem has been addressed, among others, in the United Nations Sustainability Goals. However, for mitigation of erosion consequences and adequate management of affected areas, reliable information on the magnitude and spatial patterns of erosion is needed. Although such need is often addressed by erosion modelling, precise erosion monitoring is necessary for the calibration and validation of erosion models and to study erosion patterns in landscapes. Conventional methods for quantification of rill erosion are based on labour‐intensive field measurements. In contrast, remote sensing techniques promise fast, non‐invasive, systematic and larger‐scale surveying. Thus, the main objective of this study was to develop and evaluate automated and transferable methodologies for mapping the spatial extent of erosion rills from a single acquisition of remote sensing data. Data collected by an uncrewed aerial vehicle was used to deliver a highly detailed digital elevation model (DEM) of the analysed area. Rills were classified by two methods with different settings. One approach was based on a series of decision rules applied on DEM‐derived geomorphological terrain attributes. The second approach utilized the random forest machine learning algorithm. The methods were tested on three agricultural fields representing different erosion patterns and vegetation covers. Our study showed that the proposed methods can ensure recognition of rills with accuracies between 80 and 90% depending on rill characteristics. In some cases, however, the methods were sensitive to very small rill incisions and to similar geometry of rills to other features. Additionally, their performance was influenced by the vegetation structure and cover. Besides these challenges, the introduced approach was capable of mapping rills fully automatically at the field scale and can, therefore, support a fast and flexible assessment of erosion magnitudes.

Boosted robustness of semi-implicit subgrid methods for shallow water flash floods in hills

The widespread availability of high-resolution Digital Elevation Models (DEM), has led to the development of subgrid numerical modeling techniques, based on Shallow Water Equations (SWE). Detailed DEM data is clustered as much as possible within a coarse grid cell that is preferably much larger than a raster pixel. This has considerable advantages for model efficiency, in particular for flood mapping. But overland flow on hills, key to rainfall-runoff, may have several problems with accuracy and stability. These issues arise especially during downhill flooding and with surface runoff on inclined planes. It is the focus of this paper. As robust solutions we propose: (1) a special volume correction equation with intrinsic wetting and drying but without stability constraints and, (2) a simple thin layer calculation that is accurate for runoff on coarse grids with sloping subgrids. Especially the combination (1) and (2) makes the subgrid method highly efficient on slopes, as is demonstrated by a few examples.

Assessing DEM quality and minimizing registration error in repeated geomorphic surveys with multi‐temporal ground truths of invariant features: Application to a long‐term dataset of beach topography and nearshore bathymetry

AbstractRemotely sensed digital elevation models (DEMs) and uncertainty‐based geomorphic change detection have become very practical tools for geoscientists, including for coastal research. Through the analysis of DEMs of differences (DoDs) and the provision of DEM quality, it allows monitoring complex landforms and confidently relating the changes observed to environmental forcing conditions.With continuing remote sensing advances, and as some monitoring programmes are reaching several decades of repeated data collection, it is timely to consider approaches that enable the reconciliation of DEMs of variable and potentially unknown quality before their subsequent geomorphic analyses. In this paper, we present an original workflow whereby composite data formed by fusing available measurements over invariant features serve as multi‐temporal ground truths for assessing repeated DEMs. Results of the evaluation enable identification of DEMs of lower quality (bias and precision) and correction of registration error (horizontal and vertical bias), and thus offer the in‐built capacity for estimating and improving change detection levels afforded by the data.The workflow was applied to a freely accessible multi‐sensor: RTK‐GNSS, terrestrial laser‐scanning, drone photogrammetry and multibeam echo‐sounding dataset of high‐resolution topographic and nearshore bathymetric DEMs collected at the macrotidal pocket beach of Porsmilin (France) over the period 2003–2019. Our results show that consistently high DEM precision can be achieved in a long‐term multi‐sensor dataset, but registration errors may be present and can be minimized through co‐registration with the purpose‐built ground truths. Although the study focuses primarily on measuring height discrepancies, which is directly relevant for DoD analysis, we show that the methods can also be used for dealing with horizontal error when high‐resolution imagery is available. Finally, the detailed DEM evaluations presented, in application to a rare dataset documenting beach and shoreface change for nearly two decades, provide original insights on the performance of usual topo‐bathymetric surveying techniques.

Geostatistical Resampling of LiDAR-Derived DEM in Wide Resolution Range for Modelling in SWAT: A Case Study of Zgłowiączka River (Poland)

A digital elevation model (DEM) is an essential element of input data in the model research of watersheds. Recently, progress in measurement techniques has led to the availability of such data with high spatial resolution. Therefore, simplification of DEMs to shorten the time of their processing is a significant, but insufficiently investigated issue. This study, gradually and with various methods, carried out a great simplification of a detailed LiDAR-derived DEM. Then, the impact of that treatment on the precision of the selected elements for modeling a watershed was assessed. The simplification comprised a reduction in resolution, with the use of statistical resampling methods, namely giving an average, modal, median, minimum, maximum, or the closest value to the pixels. This process was carried out in a wide range of pixel sizes, increasing by 50% each time (from 1 m to 1.5, 2.3, 3.4, 5.1, 7.6, 11, 17, 26, 38, 58, and 86 m, respectively). The precision of the obtained DEMs and the precision of the delineation of boundaries of the watershed and watercourses were assessed. With the systematic reduction in the resolution of a DEM, its precision systematically decreased. The changes in the precision of determining the watercourses and boundaries of a watershed were irregular, ranging from being very small, to mild, to significant. A method of giving the minimum value, that was simple with regard to computing, was singled out. In the determination of both the watercourses and the boundaries of a watershed, this method produced one of the best results for the higher resolution and for the lower resolution—considerably better than the other methods tested. The research was conducted on a flat agricultural catchment, and it can be assumed that the obtained conclusions can be considered for similar cases. For catchments with different characteristics, further research is advisable.

Granularity of Digital Elevation Model and Optimal Level of Detail in Small-Scale Cartographic Relief Presentation

One of the key applications of digital elevation models (DEMs) is cartographic relief presentation. DEMs are widely used in mapping, most commonly in the form of contours, hypsometric tints, and hill shading. Recent advancements in the coverage, quality, and resolution of global DEMs facilitate the overall improvement of the detail and reliability of terrain-related research. At the same time, geographic problem solving is conducted in a wide variety of scales, and the data used for mapping should have the corresponding level of detail. Specifically, at small scales, intensive generalization is needed, which is also true for elevation data. With the widespread accessibility of detailed DEMs, this principle is often violated, and the data are used for mapping at scales far smaller than what is appropriate. Small-scale relief shading obtained from fine-resolution DEMs is excessively detailed and brings an unclear representation of the Earth’s surface instead of emphasizing what is important at the scale of visualization. Existing coarse-resolution global DEMs do not resolve the issue, since they accumulate the maximum possible information in every pixel, and therefore also require reduction in detail to obtain a high-quality cartographic image. It is clear that guidelines and effective principles for DEM generalization at small scales are needed. Numerous algorithms have been developed for the generalization of elevation data represented either in gridded, contoured, or pointwise form. However, the answer to the most important question—When should we stop surface simplification?—remains unclear. Primitive error-based measures such as vertical distance are not effective for cartography, since they do not account for the landform structure of the surface perceived by the map reader. The current paper approached the problem by elaborating the granularity—a newly developed property of DEMs, which characterizes the typical size of a landform represented on the DEM surface. A methodology of estimating the granularity through a landform width measure was conceptualized and implemented as software. Using the developed program tools, the optimal granularity was statistically learned from DEMs reconstructed for multiple fragments of manually drawn 1:200,000, 1:500,000, and 1:1,000,000 topographic maps covering different relief types. It was shown that the relative granularity should be 5–6 mm at the mapping scale to achieve the clearness of relief presentation typical for manually drawn maps. We then demonstrate how the granularity measure can be used effectively as a constraint during DEM generalization. Experimental results on a combination of contours, hypsometric tints, and hill shading indicated clearly that the optimal level of detail in small-scale cartographic relief presentation can be achieved by DEM generalization constrained by granularity in combination with fine DEM resolution, which facilitates high-quality rendering.

Remote landslide mapping, field validation and model development – An example from Kravarsko, Croatia

The Kravarsko settlement area, in northern Croatia, has multiple landslides and damage to buildings and infrastructure caused by landslides. However, actual landslide investigation data for the wider Kravarsko area (pilot area PA1) is relatively sparse and no landslide inventory or typical landslide model exists. The aim of this research was to develop such a landslide inventory by integrating new approaches in geohazard research such as remote landslide mapping from high resolution digital elevation models (DEMs) and current and historical aerial images with existing and new geological data related to landslides. The conclusion is that detailed DEMs are more than adequate for the development of reliable landslide inventories but field checks are still necessary to account for the specific set of natural and man-made conditions found in the research area. The landslide inventory developed for Kravarsko has been field validated in a smaller validation area (VA1) and a typical simplified landslide model for PA1/VA1 was developed. Within the model, sliding is interpreted as complex with multiple generations of sliding and multiple sliding surfaces. Based on the analysis undertaken and the available field data, around 10-20% of urban structures are endangered in the Kravarsko area and anthropogenic activity was determined as an important landslide triggering factor for landslide activation or reactivation. Still the question remains of how to quantify the anthropogenic influence? The developed landslide inventory for PA1/VA1 could be used for local urban planning/development and endangerment assessment/evaluation.

Potential of airborne LiDAR data in detecting cultural landscape features in Slovakia

High-resolution Light Detection and Ranging (LiDAR) scanners provide detailed information on terrain surfaces, thus enabling the detection of the topographic signatures of historical anthropogenic landforms overgrown by trees or covered by the soil surface. This study aimed to examine the potential of incoming nationwide LiDAR data for detecting the cultural landscape features in Slovakia. We derived a detailed digital elevation model from LiDAR points and adopted upgraded visualisation techniques based on the combination of local relief models, sky view factor, slope steepness, and colour blending. We visually identified examples of different anthropogenic landforms and confirmed our findings with existing literature. In addition, we provide examples of previously unknown historical anthropogenic landforms discovered from LiDAR images. Finally, we discuss the potential and limits of LiDAR data in exploring and protecting different groups of historic anthropogenic landforms as remnants of past cultural landscapes in Slovakia.

Использование гибридного метода совместного анализа данных спутникового зондирования Landsat и беспилотных летательных аппаратов для реконструкции уровней воды и объемов водной массы в водоемах (на примере оз. Арахлей Забайкальского края)

The use of a hybrid method for reconstructing water levels and volumes of water mass in a reservoir is considered on the example of the Arakhley Lake of the Trans-Baikal Territory. The method makes it possible to obtain high spatial resolution cuts of water levels on the relief based on satellite images of the Landsat system of different time intervals and images from unmanned aerial vehicles (UAVs) as a source of a highly detailed digital elevation model. As a result of processing the Landsat satellite data, the values of the Arakhley Lake surface areas for the period 1987–2018 were obtained. Based on the results of the UAV survey, the water levels in the lake were extracted according to the survey dates corresponding to the areas. The root mean square error of water level determination (RMSE) was 0.23 m, which is lower than the horizontal resolution of the elevation model (0.3 m) obtained from the UAV data. Also, the characteristics of the water mass volume were obtained for the variable part of the lake volume for the period 1987–2018. The use of the hybrid method considered in the article will solve the problem of insufficient or complete absence of data on the long-term water regime of unexplored lakes and reservoirs. Evaluation of the possibilities of using this technology by comparing with the instrumental characteristics of water levels at the regime point of hydrological observations, shows the boundaries of its use, advantages and disadvantages. At the same time, the main advantage can be recognized as the possibility of obtaining time series of changes in levels and volumes over the past years in those lakes and reservoirs where there have never been ground observations and are unlikely to be. In the case of establishing the dependences of the water mass volume on the areas of the water surface, it becomes possible to perform operational hydrological monitoring of water bodies using only Landsat satellite images.

Riparian vegetation life stages control the impact of flood sequencing on braided river morphodynamics

AbstractWith riverine flooding set to be more frequent in many parts of the world as a result of climate change, the interactions between fluvial morphodynamics and riparian vegetation may depend in part on the sequence of flood events. This paper describes a laboratory study of the geomorphic adjustment of a braided river to sequences of floods across five different strengths of braidplain vegetation. By using alfalfa as a proxy for braidplain vegetation, the differing plant life stages were used to represent the varying strengths of biogeomorphic feedbacks across the floods. Boundary conditions were constrained by sets of experimental runs with both equilibrium sediment loads and deficit loads. Changes in bed topography were monitored and assessed using a detailed digital elevation model, digital imagery and continuous monitoring of the transported sediment. Results demonstrate that in absence of plant colonization, vegetation placed the rivers in a non‐equilibrium condition, in which riparian vegetation encouraged the development of new channels, increased the system channel width and enhanced topographic irregularity, these effects being more noticeable during the low‐flow periods. The morphodynamics was found to be less sensitive to variations in flood discharges as the vegetation influence (strength) increased from minimum to maximum, until vegetation began to die back and the impacts of flood sequences became yet again evident. Although the overall sediment transport rate was reduced under full‐grown vegetation conditions, the presence of the mature plants across the braid bars resulted in the greatest channel scour depths. Results are considered in light of expected changes in flood frequency with climate and likely morphodynamic responses of river systems as a result.

Mapping vegetation-induced obstruction in agricultural ditches: A low-cost and flexible approach by UAV-SfM

Drainage network efficiency plays a key role in terms of irrigation and control of floods generation in cultivated areas. A crucial aspect to consider in water resource and flood management risk is the assessment of the network storage capacity. The latter can be reduced by the uncontrolled growth of vegetation that can modify the ditch cross-section altering the hydrological response and network functionality. Therefore, the continuous monitoring of the potentially critical areas, where vegetation could obstruct the section, become a fundamental point that can be solved by the advanced in the high-resolution topographic technologies. In the last few years, the exploration of Structure from Motion (SfM) photogrammetry technique in parallel with Uncrewed Aerial Vehicles (UAVs) have increased the possibilities for the realisation of rapid, low-cost and very detailed Digital Elevation Models (DEM). The accurate and high-resolution DEM generated by UAV-SfM survey is fundamental to derive geomorphometric features of the agrarian landscape. This research aims to present a flexible and low-cost workflow to generate an accurate and high-resolution UAV-SfM DEM, in a large agrarian area of Taiwan, that can be used to automatically detect the drainage network and to map the vegetation into the ditches through the roughness index. The high roughness index values due to the presence of vegetation in the ditches were identified and compared with corresponding measurements in the field to validate and assess the methodology. The results confirm the effectiveness of the approach used and underline how the developed workflow could provide, on a farm scale and with an unusually high level of detail, useful, rapid and low-cost information to map vegetation obstruction in channel network. This data could become essential for stakeholders to precisely intervene on obstruction points, planning the ditches maintenance, and identify some numerical benchmarks to be included in flood risk models and in the computations of the storage size of the drainage network.

A Test on the Potential of a Low Cost Unmanned Aerial Vehicle RTK/PPK Solution for Precision Positioning.

This paper investigated the achievable accuracy from a low-cost RTK (Real Time Kinematic)/PPK (Post Processing Kinematic) GNSS (Global Navigation Satellite Systems) system installed on board a UAV (Unmanned Aerial Vehicle), employing three different types of GNSS Bases (Alloy, RS2 and RING) working in PPK mode. To evaluate the quality of the results, a set of seven GCPs (Ground Control Points) measured by means of the NRTK (Network Real Time Kinematic) technique was used. The outcomes show a RMSE (Root Mean Square Error) of 0.0189 m for an ALLOY Base, 0.0194 m for an RS2 Base and 0.0511 m for RING Base, respectively, on the vertical value of DEMs (Digital Elevation Models) obtained by a photogrammetric process. This indicates that, when changing the Base for the PPK, the solutions are different, but they can still be considered adequate for precision positioning with UAVs, especially when GCPs could be used with some difficulty. Therefore, the integration of a RTK/PPK GNSS module on a UAV allows the reconstruction of a highly detailed and precise DEM without using GCPs and provides the possibility to carry out surveys in inaccessible areas.

Integrating water-classified returns in DTM generation to increase accuracy of stream delineations and geomorphic analyses

High resolution topographic data has become widely available over the preceding decades and increasingly detailed digital elevation models are aiding in nearly every type of natural-resource related research. Digital terrain models (DTMs), which depict the ground surface topography devoid of vegetation or man-made structures, are particularly helpful in stream-related research. Historically, coarse resolution topographic data (e.g., several meters to tens of meters pixel size) did not afford evaluation of meter scale roughness elements exposed above the water surface within stream channels. The purpose of this study is to demonstrate how the integration of water-classified lidar returns in submeter resolution DTM-development may capture stream corridor topography and be useful for further stream-related research. Four reaches of streams draining the southeastern Blue Ridge Escarpment in southern North Carolina (USA) are assessed for reach positioning, length, and gradient. These parameters are chosen because they are foundational to many other forms of stream analysis (e.g., stream power, normalized channel steepness, chi, and others). Water-assigned lidar returns are included in 0.5- pixel size DTMs and compared to both a 0.5-m DTM generated without use of water returns (i.e., bare-earth) and a pre-processed, hydro-flattened 0.9-m bare-earth DTM. In steep bedrock channels, bare-earth only DTMs result in channels 12–23% shorter than water return integrated DTMs. Observations of stream positioning on DTMs that include water returns and comparisons to orthophotographs suggest a more consistent stream center line in relation to boulders and exposed bedrock within stream channels. Small streams do not benefit from the modified analysis methods because water-classified returns are not present in these channels. Nor do low gradient alluvial channels benefit because these streams tend to lack exposed bedrock or large roughness elements that might divert stream flows. Because so many geomorphic parameters are largely dependent on channel length, these findings have far-reaching implications in ongoing stream-related research. The methods presented here do not require new data collection or technology, but offer simple modifications to processing of existing data and should be considered on other high quality lidar datasets.

Combined hydroacoustic research of Lake Baikal

The article outlines the main approaches to studying the bottom topography of Lake Baikal and interpretation of bathymetric data. Measurement equipment and experimental data processing algorithms are described. A measuring complex is based on using the Kongsberg EM710S multibeam echosounder which allows one to take a detailed digital elevation model of the bottom. The paper demonstrates experimental results obtained during a series of expeditions to the Baikal in 2015 – 2019. Currently an area of about 12117 km2 (∼38%) of Lake Baikal bottom has been explored. Examples of a digital model of the Baikal bottom are also presented. The paper demonstrates 3D models of detected water columns showing intense of a gas bubbles emanation near the mouth of Selenga river, acoustic images of the Baikal Gigaton Volume Detector (Baikal-GVD), and a bathymetric map of Academician Ridge that was previously examined with the Mir 1 and Mir 2 in July 2009.

Mapping Soil Degradation on Arable Land with Aerial Photography and Erosion Models, Case Study from Danube Lowland, Slovakia

The presented study uses the recent colour aerial photographs, historical black and white aerial photographs, and detailed digital elevation model to assess the spatial distribution and long-term temporal dynamics of soil loss in agriculturally intensively exploited loess hilly land with a subcontinental temperate climate. The strongly eroded soils appear in the studied area as bright patterns, surrounded by darker soils, and they are well visible on aerial photos. Three approaches of interpretation of aerial photographs were tested: visual interpretation, pixel-based image classification, and object-based image classification. All three methods provided detailed maps of soil redistribution patterns. The bright areas as the areas of soil degradation characterized by erosion increased from 1949 until 2011 by 76%. A detailed map of areal erosion patterns was used for the validation of water erosion models. LS-factor of USLE and ED’ index of USPED were selected for expressing the relation of real erosion to the terrain. The relationship between surface morphology and real erosion is very complex, and the tested water erosion models do not express it sufficiently. Therefore, the first and second-order directional derivative of the surface elevations with respect to the tillage direction has been tested. The absolute value of the first-order directional derivative showed better results and better corresponded with the real erosion pattern than the other morphometric characteristics. The findings suggest that tillage is the dominant erosion factor in the area.

UAV-Derived Multispectral Bathymetry

Bathymetry is considered an important component in marine applications as several coastal erosion monitoring and engineering projects are carried out in this field. It is traditionally acquired via shipboard echo sounding, but nowadays, multispectral satellite imagery is also commonly applied using different remote sensing-based algorithms. Satellite-Derived Bathymetry (SDB) relates the surface reflectance of shallow coastal waters to the depth of the water column. The present study shows the results of the application of Stumpf and Lyzenga algorithms to derive the bathymetry for a small area using an Unmanned Aerial Vehicle (UAV), also known as a drone, equipped with a multispectral camera acquiring images in the same WorldView-2 satellite sensor spectral bands. A hydrographic Multibeam Echosounder survey was performed in the same period in order to validate the method’s results and accuracy. The study area was approximately 0.5 km2 and located in Tuscany (Italy). Because of the high percentage of water in the images, a new methodology was also implemented for producing a georeferenced orthophoto mosaic. UAV multispectral images were processed to retrieve bathymetric data for testing different band combinations and evaluating the accuracy as a function of the density and quantity of sea bottom control points. Our results indicate that UAV-Derived Bathymetry (UDB) permits an accuracy of about 20 cm to be obtained in bathymetric mapping in shallow waters, minimizing operative expenses and giving the possibility to program a coastal monitoring surveying activity. The full sea bottom coverage obtained using this methodology permits detailed Digital Elevation Models (DEMs) comparable to a Multibeam Echosounder survey, and can also be applied in very shallow waters, where the traditional hydrographic approach requires hard fieldwork and presents operational limits.