Resolution Digital Elevation Model Research Articles

GIS-Based RUSLE Reservoir Sedimentation Estimates: Temporally Variable C-Factors, Sediment Delivery Ratio, and Adjustment for Stream Channel and Bank Sediment Sources

The empirical Revised Universal Soil Loss Equation (RUSLE) has been adapted to geographical information system (GIS) frameworks to study the spatial variability of soil erosion across landscapes and has also been used to estimate reservoir sedimentation. The literature presents contradictory results about the efficacy of using RUSLE in a GIS context for quantifying reservoir sedimentation, requiring further evaluation and validation of its estimates relative to measured reservoir sedimentation. Our primary objective was to determine if these contradictory results may be a function of the RUSLE’s inability to account for sediments derived from gullies, stream channels, or stream banks; the temporal variability of some of RUSLE’s empirically based factors such as the land cover/land management (C-) factor; and in some model renditions, the choice of value for the sediment delivery ratio (SDR). The usefulness of adjusting these estimates using a regional representative value of gully/stream bank sediment contributions was also assessed. High-spatial horizontal resolution (2 m) digital elevation models (DEMs) for 12 watersheds were used together with C-factor data for five representative years in a GIS-based RUSLE model that incorporates SDR within a sediment routing routine to study the impacts of choice of C-factor and SDR on reservoir sedimentation estimates. Choice of image date for developing C-factors was found to impact reservoir estimates. We also found that the value of SDR for some of the study watersheds would have to be unrealistically small to produce sedimentation estimates comparable to measured values. Estimates of reservoir sedimentation were comparable to measured data for 5 of the 12 watersheds, when the regionally based adjustment for gully/stream bank contributions was applied. However, differences remained large for the remaining seven watersheds. Statistical analysis revealed that certain combinations of geomorphic, pedologic, or topographic variables could be used to predict the degree of sediment underestimation with a significant and high level of correlation (0.72 < R2 ≤ 0.99; p-value < 0.05). Our findings indicate that the level of agreement between GIS-based RUSLE estimates of reservoir sedimentation and measured values is a function of watershed characteristics; for example, the area-weighted soil erodibility (K-) factor of the soils within the watershed and stream channels, the stream entrenchment ratio and bank full depth, the percentage of the stream corridor having slopes ≥ 21°, and the width of the stream flood way as a percentage of the watershed area. Within the context of GIS, these metrics are easily obtained from digital elevation models and publicly available soils data and may be useful in prioritizing reservoirs’ assessments for function and safety.

Modelling flood hazards impacted by ungauged river in urbanised area using HEC-RAS and GIS

Ilorin City is located downstream of Asa, Oyun and Awun River Basins. The Asa River is a major river that traverses the city and divides the metropolitan area into east and west, almost equally. The river often overflows its banks to inundate adjacent communities, influencing severe economic damage and impact on human lives. However, efforts to mitigate this have majorly been focused on dredging the Asa River channel which has not solved the problem. For an accurate spatial and temporal understanding of the risks of floods and their potential hazards, it is important to estimate floods using river hydrology. The objective of this study is to model steady flow of the rivers using flow data and to map flood-prone areas in Ilorin using HEC-RAS integrated with GIS. Using the HEC-GeoRAS extension in the GIS environment, the geometric data of the rivers were obtained from the 30 m resolution digital elevation model (DEM) and input into HEC-RAS applying Manning Co-efficient values of 0.04, 0.045, and 0.04. For each river, flow data (Q) was given as the upstream boundary condition while a normal depth of 0.001 was assigned for the downstream condition to model a steady flow and inundation extents. The result of the HEC-RAS model has shown the flood-prone areas along the river channels delineated. The floodplain map produced reveals the spatial distribution and extent of the high flood-risk areas in the Ilorin metropolis. The total flooded area covers approximately 60.95 km2 (18%) majorly along the river channels. This study has demonstrated that integration of hydraulic modelling using HEC-RAS and GIS process is capable of producing an inundation flood map with good accuracy that will aid in suggesting effective measures to mitigate the impact of flooding.

Terrain analysis and hydrogeomorphic investigation of the Sita-Swarna river basin, Udupi, SW India: Insights from remote sensing methods

Hydrogeomorphic characteristics of the Sita-Swarna river basin, Western Ghats, India, are investigated to understand the influence of lithology, structure and geological control on the channel morphology. For preliminary investigation, remote sensing, geomorphic and morphometric analysis was carried out, producing slope, aspect and lineament maps from a 30 m resolution Digital Elevation Model (DEM) with the help of GIS. Remote sensing analysis inferred a steep south-to-southwest slope with dominant lineaments trending NW and ENE to E in the middle reaches of the Sita-Swarna river basin. These lineaments are deduced to have possibly been instigated by faults, shear zones, dyke ridges, or subsurface structures that influence the surficial topography. Upland and pediment geomorphic zone were identified, inferring Western Ghats Escarpment (WGE) and gently coastward W-sloping dissected pediment surface. A comprehensive morphometric analysis is performed using various linear, areal, and relief parameters for basin characterization. The linear parameters infer that the basin is structurally controlled and shows moderate to high permeability and flood susceptible areas downstream. The calculated morphometric parameters for basin characterization reveals that the Sita-Swarna river basin is at the mature stage of development and highly asymmetrical with the westward tilt, which indicates a possible influence of paleo tectonism. Rapid runoff is observed due to the steep escarpment leading to less infiltration and flash flood possibility during heavy rainfall. The present study mainly establishes the potential application of remote sensing methods to quantify the hydrogeological aspects, basin morphometry and landscape evaluation in the tropical climatic zone.

Modelling of recreational trails in mountainous areas: An analysis of sensitivity to slope data resolution

This paper investigates how the spatial resolution of slope data affects the modelling of recreational trails in mountainous areas. It measures the impact of spatial resolution on a) the estimation of cost functions that link walking speeds and slope, and b) the modelling of moving times and mapping of routes using these functions. Cost functions that build on a mountain hike GPS record and slope data derived from a Digital Elevation Model (DEM) at varying resolutions are estimated and their ability to predict accurate moving times is evaluated. The cost functions are supplemented with recently published cost functions to map the quickest routes between the hike start and end points with least-cost-path analyses. The results indicate that spatial resolution has a critical influence in the modelling: the similarity between routes modelled at a same spatial resolution with distinct cost functions considerably surpasses that of routes simulated at varying resolutions with a same cost function. Furthermore, employing finer resolutions enhances the similarity between routes mapped with different cost functions, while also improving the accuracy of predicted moving times. These findings provide evidence that DEM resolution should receive prime attention in the modelling of trails with slope-dependent cost functions.

Atmosphere-aware photoclinometry for pixel-wise 3D topographic mapping of Mars

High-resolution topographic mapping is essential for scientific investigations and operational exploration of planets, such as Mars. Photoclinometry, which uses light scattered from a surface to reconstruct 3D topography, can retrieve subtle topographic details from monocular images. However, its performance is affected by the atmosphere of Mars, which alters surface reflectance mechanisms due to the scattering and absorption by aerosols. Therefore, specific treatments accounting for these atmospheric effects are needed to enable photoclinometric mapping of Mars. This paper presents a novel photoclinometric approach incorporating a radiative-transfer model of atmospheric scattering effects for pixel-wise 3D reconstruction of the Martian surface. The approach requires a high-resolution image, a corresponding coarse-resolution digital elevation model (DEM), and information of the optical depth as inputs. A radiative transfer model adapted to the Martian atmosphere is used to account for the atmospheric effects. The approach also allows directly adopting optical depth estimates from a global database (e.g., the Mars Climate Database). The approach was validated using different types of Mars orbiter images collected by cameras on-board the Mars Reconnaissance Orbiter and the Tianwen-1 Orbiter. The results indicate that the approach can achieve a geometric accuracy (in terms of root-mean-squared error (RMSE) of the elevation) of approximately 2 pixels of the image resolution and significantly enhances topographic details. In addition, we evaluated the approach using different settings for the optical depths and spatial resolutions of the input DEMs. The results show that overestimating the optical depth leads to overestimation of topographic amplitudes (e.g., deeper craters). On the other hand, underestimating the optical depth by the same amount as overestimation leads to a smaller increase in the RMSE. Moreover, coarsening the resolution of an input DEM increases the RMSE of the photoclinometric results. Nevertheless, photoclinometry improves both the RMSE and the resolution of the input DEM. This new approach serves as an effective means for applying photoclinometry for pixel-wise 3D topographic mapping of the Martian surface. This will facilitate exploitation of the large number of high-resolution monocular images of Mars in 3D topographic mapping of the planet.

Calibration of groundwater seepage against the spatial distribution of the stream network to assess catchment-scale hydraulic properties

Abstract. The assessment of effective hydraulic properties at the catchment scale, i.e., hydraulic conductivity (K) and transmissivity (T), is particularly challenging due to the sparse availability of hydrological monitoring systems through stream gauges and boreholes. To overcome this challenge, we propose a calibration methodology which only considers information from a digital elevation model (DEM) and the spatial distribution of the stream network. The methodology is built on the assumption that the groundwater system is the main driver controlling the stream density and extension, where the perennial stream network reflects the intersection of the groundwater table with the topography. Indeed, the groundwater seepage at the surface is primarily controlled by the topography, the aquifer thickness and the dimensionless parameter K/R, where R is the average recharge rate. Here, we use a process-based and parsimonious 3D groundwater flow model to calibrate K/R by minimizing the relative distances between the observed and the simulated stream network generated from groundwater seepage zones. By deploying the methodology in 24 selected headwater catchments located in northwestern France, we demonstrate that the method successfully predicts the stream network extent for 80 % of the cases. Results show a high sensitivity of K/R to the extension of the low-order streams and limited impacts of the DEM resolution as long the DEM remains consistent with the stream network observations. By assuming an average recharge rate, we found that effective K values vary between 1.0×10-5 and 1.1×10-4 m s−1, in agreement with local estimates derived from hydraulic tests and independent calibrated groundwater model. With the emergence of global remote-sensing databases compiling information on high-resolution DEM and stream networks, this approach provides new opportunities to assess hydraulic properties of unconfined aquifers in ungauged basins.

Hydrogeologic controls on barrier island geomorphology: Insights from electromagnetic surveys

Barrier islands provide a first line of defense for coastal communities against storms, hurricanes, and sea-level rise. The geomorphology of barrier islands exerts a major control on storm impact and island recovery. In turn, barrier island geomorphology is affected by subsurface hydrogeologic conditions. In this study, we investigated the relationship between subsurface hydrogeologic conditions and geomorphology of Padre Island, with a focus on the influence of human development. We measured apparent electrical conductivities using frequency-domain electromagnetic (FDEM) surveys and spatially correlated them with the island's morphology. The latter was generated from a 1 m resolution digital elevation model. Four distinct zones were identified from the observed variations in apparent conductivity and elevation, revealing their inverse correlation. The beach area (Zone I) exhibits the highest apparent conductivity (289.7 ± 66.3 mS/m) and the lowest elevations (1.4 ± 0.2 m). These trends are largely due to the proximity of the beach to saline groundwater and maritime floods. Conversely, the foredune area (Zone II) presents the lowest apparent conductivity (19.0 ± 3.4 mS/m) and the highest elevation (4.5 ± 0.4 m) due to a greater distance from saline waters, deeper groundwater levels, and relatively dry soil conditions. Human development has significantly impacted Zones III (east central zone) and IV (west central zone), contributing to an increase in apparent conductivity (Zone III: 40.3 ± 21.8 mS/m; Zone IV: 159.5 ± 83.0 mS/m) and a reduction in elevation (Zone III: 2.1 ± 0.5 m; Zone IV: 1.3 ± 0.4 m). Anthropogenic activities have modified hydrologic patterns, introduced conductive materials, and altered vegetation cover and soil composition. This research elucidates the interplay between subsurface electrical conductivity, surface morphology, and the impact of human development on barrier island geomorphology, providing crucial insights for coastal management and conservation efforts.

The effects of digital elevation model resolution on the PyFLOWGO thermorheological lava flow model

Topography is a fundamental factor influencing the emplacement of lava flows. We assess the impact of topographic resolution on the thermorheological PyFLOWGO model, specifically with digital elevation model (DEM) resolutions commonly available for Earth and other planetary bodies where flow modeling is relevant. We examined PyFLOWGO output parameters (e.g., channel length, core temperature, and flow velocity) to assess model sensitivity to topography in order to document model uncertainties and optimize future application. This study uses rheologic and topographic data from the Tolbachik, Russia 2012–2013 eruption as model constraints. Using moderate to lower resolution topographic data overestimates the channelized flow length by up to 35% due to differences in the distribution of slopes topographic variability at different resolutions and resulting effects on the modeled lava velocity down channel. Determining the impact of topography on thermorheological lava flow models such as PyFLOWGO is important to correctly interpret the results for channelized flows.

INFLUENCE OF DIGITAL ELEVATION MODEL RESOLUTION ON MAPPING TERRITORY SUSCEPTIBILITY TO LANDSLIDE DEVELOPMENT

Link for citation: Van B. Duong, Fomenko I.K., Duc T. Ta, Trung K. Nguyen, Zerkal O.V., Gorobtsov D.N., Hong D. Vu. Influence of digital elevation model resolution on mapping territory susceptibility to landslide development. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 164-181. In Rus. The relevance. Landslides are one of the most hazardous natural disasters in the world, causing significant economic damage and human deaths. For 20 years (1995–2014), 3876 landslides killed 163658 people and injured 11689 people, as reported by the U. Haque study (2019), based on the data from 128 countries. Excluding events triggered by earthquakes, the total number of fatal landslides from 2004 to 2016 was 4862, and most landslides (75 %) occurred in Asia. In Vietnam, particularly in the northern mountainous regions, landslides frequently caused considerable losses of life and property. The systematic evaluation of landslide hazards is a crucial component of Vietnam's disaster prevention strategy. The main aim of this study is to assess the landslide susceptibility of the Batxat district, Laocai province (Vietnam), using four digital elevation model resolutions (10, 30, 40, and 60 m) and nine landslide causative factors: slope aspect, elevation, slope, distance to roads, distance to faults, distance to drainage, average monthly precipitation, land use, and weathering crust. Object of the study is the landslide susceptibility in Batxat district, Laocai province, Vietnam. Methods: Certainty Factor method, fractal method. Results. The performed analyses indicated a statistically significant relationship between the distribution of landslides and the landslide causative factors in the study area. As a result, the territory was divided into five zones according to its susceptibility to the landslide process: very low, low, moderate, high, and very high. The very low landslide susceptibility zone is less than 10 % of the study area, while the very high susceptibility zone varies from 14,95 to 18,32 %, depending on the digital elevation model spatial resolution. Analysis of the Receiver Operating Characteristics curve revealed that all models, independent of digital elevation model resolution, have good prediction efficiency, with the area under the receiver operating characteristic curve over 70 %. In addition, the Receiver operating characteristic and fractal analysis results indicated that the model with a digital elevation model spatial resolution of 60 m has the highest accuracy. This significant conclusion may be explained by the fact that the accuracy of the landslide susceptibility assessment result is dependent not only on the digital elevation model resolution but also on the ratio of the digital elevation model resolution and the average area of landslides in the study area. This conclusion proves that it is necessary to depict landslide locations and their detailed morphological characteristics on the landslide inventory maps.

Automatic identification of sites prone to topographic seismic amplification effects by the current seismic codes

Current seismic codes provide proxies to estimate seismic amplification effects expected in correspondence of some morphological features. To make possible any empirical validation of these proxies, these features must be univocally identified on the basis of an automatic procedure. To this purpose, based on geomorphological considerations, a GIS-based numerical approach has been developed. The results of a morphometric analysis allowed the correct identification and mapping of the landforms of concern, at a detail corresponding to the resolution of the available digital elevation model (DEM). Some case-studies are provided to show the feasibility of the proposed approach.

Influential Topographic Factor Identification of Soil Heavy Metals Using GeoDetector: The Effects of DEM Resolution and Pollution Sources

Heavy metals (HMs) entering soils are redistributed by natural processes such as surface runoff and soil erosion. These natural processes are characterized by topographic factors (TFs, e.g., Topographic Wetness Index (TWI), Total Catchment Area (TCA), Slope, and Aspect), which are commonly quantified by a digital elevation model (DEM) of a certain spatial resolution. Nevertheless, few studies have examined how DEM resolutions affect the detection of influential TFs of soil HMs. In this study, we first applied the GeoDetector method to explore the coupling between the eight TFs and the concentrations of eight soil HMs under a gradient of DEM resolutions. We found that the important sorting of eight TFs on one HM at different resolutions is inconsistent. For example, for Hg, TWI emerged to be the dominant factor among the eight TFs at 90 m resolution, whereas TCA took the lead at 3000 m resolution. Moreover, the results strongly deny the existence of an optimal resolution (OR) among the HMs for any specific topographical factor. We further applied a source apportionment model (Positive Matrix Factorization—PMF) to explore the effects of five identified pollution sources and the underlying environmental processes on the inconsistent ORs. The main reason for such OR inconsistency is that each HM may be released from various sources and subsequently undergo environmental processes that are topographically modulated at different spatial scales. The main reason for such OR inconsistency is that each HM may have various sources and subsequent environmental processes that happen at different spatial scales. Moreover, each TF could simultaneously reflect different transport and transformation processes. Therefore, the apparent OR for one metal is jointly composed of the preferences of all the sources it contains; thus, it cannot be determined by the OR preferences of a single source alone. Based on the composition and intensity of pollution sources, we propose three possible strategies for a more robust GeoDetector analysis. The findings reported here provide new insights into the proper use of GeoDetector for selecting the appropriate DEM resolutions when identifying influential environmental factors.

Monitoring and Comparative Analysis of Hohhot Subway Subsidence Using StaMPS-PS Based on Two DEMS

The subway alleviates the traffic pressure in the city but also brings the potential risk of land subsidence. The land subsidence caused by the subway is a global problem that seriously affects the safety of subway operations and surrounding buildings. Therefore, it is very important to carry out long-term deformation monitoring on the subway system. StaMPS-PS is a time-series Interferometric Synthetic Aperture Radar (InSAR) technique that serves as an effective means for monitoring urban ground subsidence. However, the accuracy of external (Digital Elevation Models) DEM will affect the accuracy of StaMPS-PS monitoring, and previous studies have mostly used SRTM-1 arc DEM (30 m) as the external DEM. In this study, to obtain a more precise measurement of surface deformation caused by the excavation of the Hohhot subway, a total of 85 scenes of Sentinel-1A data from July 2015 to October 2021, as well as two different resolution digital elevation models (DEMs) (ALOS PALSAR DEM and SRTM-1 arc DEM), were used to calculate and analyze the subsidence along the subway line in Hohhot city. The StaMPS-PS monitoring results showed the ALOS PALSAR DEM, as an external DEM, had higher accuracy, and there was regional subsidence in both the construction processes of Line 1 and Line 2 of the Hohhot subway, with a maximum subsidence rate of −21.1 mm/year. The dynamic changes in subway subsidence were fitted using the Peck formula and the long short-term memory (LSTM) model. The Peck formula results showed the width and maximum subsidence of the settlement troughs gradually expanded during the construction of the subway. The predicted values of the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the LSTM model were less than 4 mm and 10%, respectively, consistent with the measured results. Furthermore, we discussed the factors that affect settlement along the subway line and the impact of two external DEMs on StaMPS-PS. The study results provide a scientific method for DEM selection and subsidence analysis calculations in the StaMPS-PS monitoring of urban subway subsidence.

Flood risk assessment of the river Benue catchment in Adamawa State Nigeria

Floods are one of the most devastating natural disasters that occur globally, causing loss of life and property. Adamawa, a state located in north-eastern Nigeria, is prone to flooding due to its location within the floodplains of the River Benue. The research examines the spatial distribution of flood risk, the role of altitude in determining flood risk levels, and the implications for population exposure. The investigation was carried out in the following local government areas, namely Yola-South, Demsa, Numan, Lamurde, Guyuk, Shelleng and Song. The study used a combination of remote sensing and geographic information systems (GIS) techniques to analyze the flood risks extent and exposure within the catchment. SRTM 30 Meters resolution Digital Elevation Model (DEM) data was used to derive catchment boundaries, stream networks and watershed characteristics. 500 years return period flood hazard raster along with a population raster of the settlements within the region of interest were also used. The findings reveal varying flood risk extents, with areas at lower elevations exhibiting higher flood risks. Additionally, the study identifies specific wards within each locality that are situated in different flood risk zones, highlighting the need for localized flood risk assessments. The results demonstrate a correlation between flood risk levels and the percentage of the population exposed to these risks. The study aligns with existing literature on flood risk, altitude, and population vulnerability, emphasizing the importance of considering these factors in flood risk management strategies. The findings contribute to a better understanding of flood risk patterns and can guide policymakers and stakeholders in implementing targeted interventions and developing effective disaster response plans. However, it is essential to contextualize the findings within the specific study areas and complement them with site-specific assessments and further research.

Influence of DEM resolution on topographic correction models using spot satellite image

Topographic correction models (TCMs) are valid on satellite image data preprocessing steps. Theillumination angle may be sensitive to different terrain slope and aspect conditions base on sun-terrain-sensorgeometry. Although the topographic correction is influenced by the sun azimuth and zenith angle, the correction resultcan be equally in the same image status. By contrast, the terrain factors change with different digital elevation model(DEM) resolution in the topographic correction equations and cause a significant effect. Slope is sensitive in ruggedterrain, and aspect is impressionable at flat surface at a coarse DEM resolution data. As the DEM resolution lead adistinct result on TCMs, this research is aimed to examine the impact of DEM resolution on the accuracy of terrainrepresentation and of the gradient determined. In this study, five TCMs, including cosine correction, C correction, SCS correction, SCS+C correction and Minnaert correction models are compared by different resolutions using SPOTimage data. The 5 meter DEM obtained from Ministry of the interior will be resampled to 10 to 500 meters to testthose topographic models sustainability on Lienhuachih Research Center. The accuracy of five topographic correctionmodels base on different DEM resolution will be evaluated by root-mean-square error (RMSE).

Aerial characterization of surface depressions in urban watersheds

Digital elevation models (DEM) are one of the most fundamental inputs for hydrological modeling. It has been a common practice to remove all surface depressions in a DEM as they are assumed to be data errors. The emerging technology of unmanned aircraft systems (UAS) provides an opportunity to re-examine this assumption at the hyperspatial resolution. This study was the first attempt to characterize small surface depressions in urban environments using UAS imagery. Using an urban area in south Texas as the study site, UAS flights were conducted to yield hybrid DEMs at the resolution of 8–14 cm, coupled with comprehensive ground truth collection. Surface depressions identified from the UAS DEMs were first corrected based on the vertical accuracy of DEMs and then validated through field surveys, with comparisons to two existing LiDAR DEMs (1-m and 10-m). The hydrological impacts of different DEM-derived estimates of catchment depression storage were examined using the Curve Number method across different design storms. Results show that the UAS DEMs outperformed the LiDAR DEMs in describing the microtopographic control of urban overland flow and associated hydrological connectivity across built and natural features. The 8-cm UAS DEM revealed 926% more depression storage than the 10-m LiDAR DEM. This demonstrates a compelling correlation between increasing DEM resolution and enhanced quantification of depression volume. Consequently, the increased depression storage reduced surface runoff by 41% under a two-year design storm and 13% under a 200-year design storm. The results suggest a strong relationship between the DEM resolution and the derived depression estimates, aligning with the fractal nature of watershed systems. Also, the results indicate that the centimeter-level UAS DEMs were not immune from problems. They could yield fake depressions caused by factors such as vegetation, temporary street objects, and underground sewer pipes. The findings of this study suggest the need to quantify the relationships between DEM resolution and associated hydrological attributes and develop new digital drainage analysis algorithms that could effectively incorporate UAS data into urban hydrological modeling.

The influence of roads on depressional storage capacity estimates from high-resolution LiDAR DEMs in a Canadian Prairie agricultural basin

The Canadian Prairies are a post-glacial agricultural landscape, where millions of small depressions store surface water, form wetlands and control runoff contributing area. Their management is key to flood and drought hydrology, groundwater recharge, ecological integrity, migratory bird habitat and agricultural productivity. Depression drainage and infilling is common in the region, where it is often used to increase cropped area. The regularly spaced, rural ‘grid-road‘ network also impedes drainage, but associated culvert drainage can mitigate those effects. Management of depressions can be informed by hydrological modelling, but accurate surface water storage capacity estimates are needed to ensure accurate model results. Simple representation of road embankments in digital elevation models (DEMs) neglects the effects of culvert drainage. Here, a raster-based depression-filling algorithm was used to delineate depressions from three LiDAR-derived DEMs: a 10-m DEM with roads intact, a 2-m DEM with roads intact, and a 2-m DEM with roads breached at culvert locations. Road breaching was conducted manually in the 2-m DEM to remove artifact depressions that form alongside roads where culverts exist. Results indicated that increasing DEM resolution from 10-m to 2-m in a 393.5 km2 basin did not significantly change depression area or storage capacity estimates; however, breaching roads in the 2-m DEM decreased depression area by 29% (from 98.5 km2 to 69.8 km2) and estimated storage capacity by 48% (from 47.4 × 106 m3 to 23.8 × 106 m3), compared to leaving roads intact in the 2-m DEM. Depressions delineated from the 2-m roads-breached DEM also covered 48% more area and offered 53% more storage capacity than Canadian Wetland Inventory (CWI) aerial-photograph delineated wetlands, which occupied 47.1 km2 with an estimated storage capacity of 15.5 × 106 m3. The implications of these results for the ability of hydrological models to calculate runoff contributing areas and streamflow are discussed.

The effect of DEM resolution on topographic wetness index calculation and visualization: An insight to the hidden danger unraveled in Bozkurt in August, 2021

Topographic Wetness Index, also known as the compound topographic index, (TWI) is a topographic indicator that calculates the potential of where water is likely to accumulate during excessive precipitation cycles resulting from abrupt atmospheric anomalies. High index values represent serious potential of water accumulation due to low slope, and the opposite for high slope. As expected from the term, slope, Digital Elevation Model (DEM) datasets play an important role in the calculation of TWI. DEMs are produced utilizing tachometry, GPS benchmarking, UAV, aerial or satellite image capture and LIDAR capabilities. However, no matter how it is generated, a DEM is as good as the actual ground sampling algorithm, on which the final resolution is based. Using six different DEM resolutions coming from three global and one national source presented in three different setting coverages, upper feeder basin of Bozkurt sub-province, Kastamonu, was analyzed emphasizing the urbanized part of the sub-province, which was devastated during the August 11th, 2021 flood. Coarser resolution missed the overall precision while the finer resolution captured it nicely. On the flip side, finer resolution excessively fragmented the questioned area while the coarser resolution formed a unity coinciding with the destructed area recorded during the event.

COSMO-SKYMED: A SATELLITE TOOL FOR MONITORING CULTURAL HERITAGE

Abstract. COSMO-SkyMed is the flagship Synthetic Aperture Radar (SAR) satellite constellation of the Italian Space Agency (ASI) that, among the many civilian applications for which it was originally conceived, is nowadays successfully exploited for cultural heritage applications. Current capabilities offered by both the First and Second Generations satellites are reviewed in light of the experience undertaken by ASI through data exploitation initiatives with scientific and commercial users, and more importantly in the framework of institutional projects and cooperation agreements such as those with the Colosseum Archaeological Park and the Italian Ministry of Culture (MiC). The interferometric nature of COSMO-SkyMed SAR acquisitions is the key feature exploited in structural and ground deformation monitoring of monuments and historical buildings, so as the constellation is currently the essential Earth Observation asset supporting MiC’s Extraordinary Plan of Monitoring and Conservation of Immovable Cultural Heritage. Further applications that could be enabled by COSMO-SkyMed data are explored through internal ASI research activity, such as the use of high resolution Digital Elevation Models (DEM) for topographic surveying of archaeological tells and condition assessment to estimate the impact due to natural and anthropogenic threats (e.g. looting, agriculture, destruction). Finally, current perspectives towards operational use and greater user uptake of COSMO-SkyMed for purposes of scientific downstream are opened by the new ASI programme Innovation for Downstream Preparation for Science (I4DP_SCIENCE).

Uncertainty in primary and secondary topographic attributes caused by digital elevation model spatial resolution

Digital elevation models (DEMs) are increasingly being used to explain different soil and site-related characteristics using a variety of modelled topographic properties and their frequencies. It is well known that the grid cell size of a raster DEM significantly affects derived primary and secondary topographic attirbutes, such as elevation, slope, topographic position index, and wind exposition index. This study investigates the impact of increasing DEM spatial resolution on spatial distortion (defined by mean absolute error (MAE)) in two contrasting sites and tests two different data-obtaining procedures (average plot vs. single point). Findings detected and quantified significant error(s) caused by coarsening DEM spatial resolution. In addition, the plot average measurement procedure was more representative for any bounded area than a value extracted from a single point measurement. These findings provide important guidance for creating and using topographic attributes across a range of applications. This study recommends using DEM resolution of <15 m to derive primary and secondary topographic attributes. However, the optimal resolution is scale dependent and related with landscape; henceforth, coarser resolution may be sufficient for representing large-scale topographic features.

Geomorphic floodplain mapping in small Mediterranean catchments using LiDAR data

Recent advances in remote sensing technologies along with the increased availability of topographic data have lately encouraged the development of automatic DEM (Digital Elevation Model)-based procedures for floodplain delineation. Geomorphic methods, establishing relationships between flood descriptors and morphologic catchment characteristics, appear particularly suitable to be implemented within a GIS algorithm. In the present work, four simplified geomorphic approaches based on “flow-depth scaling laws” (FD) or “flow-cross-sectional area scaling laws” (FA) with contributing area and two methods employing two different flood descriptors (Hydro-Geomorphic Method, HGM and Geomorphic Flood Index method, GFIM) have been applied for the preliminary evaluation of floodplain extent using high resolution DEMs (i.e. LiDAR at 1 and 2 m resolution) as the main input. Taking as a case study six of the largest basins located in southern Italy, the performances of these methods were evaluated and critically compared using government agency derived flood hazard maps as benchmarks. Results show that the adoption of FD especially when combined with morphology to formulate the GFIM, allows to efficiently predict the flood-prone areas with low computational costs. At the same time, performances of the flood mapping procedures based on “flow-area scaling laws”, although in principle more appealing, seem to be slightly lower. Overall, the proposed approaches can be applied for rough mapping of floodplains in ungauged basins or in data-scarce regions where standard flood hazard maps are unavailable.