Spatial Resolution Digital Elevation Model Research Articles

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.

Bridging the gap between airborne and spaceborne imaging spectroscopy for mountain glacier surface property retrievals

Observations of glacier albedo are sparse, despite being a first-order control on net solar radiation and melt rates. Recent and forthcoming airborne and satellite imaging spectrometer missions increase our ability to record changes in albedo over time and space but will require an understanding of uncertainties, especially in areas of rugged terrain. Some of these uncertainties arise from the timing of acquisition and resolution of digital elevation models (DEM) that are used for topographic correction. We use the fine-resolution data (2 m) from the Airborne Coastal Observatory (ACO), an imaging spectroscopy and lidar remote sensing platform, to quantify the expected error from other airborne and satellite scale platforms. First, we describe our retrieval workflow - the Imaging Spectroscopy Snow and Ice Algorithm (ISSIA) that yields spatial retrievals of broadband albedo (BBA), optical grain size, and radiative forcing by light absorbing particles (RFLAP) using the coincident 2 m lidar DEM over mountain glaciers. We use two acquisitions over Place Glacier, British Columbia, Canada that represent typical spring and summer conditions as a baseline from which synthetic datasets were generated to represent data from coarser-scale imaging spectroscopy platforms. Each synthetic dataset was motivated by specific airborne and satellite platform scenarios and quantifies four sources of error: (1) DEM spatial resolution and elevation accuracy, (2) coincident vs non-coincident DEM collection, (3) imagery spatial resolution, and (4) spectral resolution. Use of a 30 m DEM introduced the most error in steep mountain terrain, which primarily increased error in the BBA and RFLAP retrievals. The timing of DEM acquisition mattered most for high-resolution imagery and in areas surrounding the glacier toe where mass loss occurred more rapidly. Coarse-resolution imagery did not fully capture spatial variability in surface properties and topography, which lowered variance and increased overall errors. Coarsening of spectral resolution from 5 nm to 10 nm had minimal impact on surface property retrieval and associated errors were independent of DEM or imagery resolution. A simple energy analysis showed that surface albedo error, due to topographic correction with coarse and non-coincident DEMs, resulted in melt rate errors ranging from 6 to 20% for airborne and 11–20% for satellite scenarios.

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.

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.

Development of a Water Quality Management Model for Dry Rivers in Arid Regions: Application on Wadi Rumah, Saudi Arabia

In dry rivers, urban wastewater discharge forms a pond in the dry period, and surface runoff shapes a longer pond in the wet period. A water quality management model developed for dry rivers is applied on Wadi Rumah in Saudi Arabia. The sub-basin was delineated from 30-m × 30-m spatial resolution digital elevation model. Hydrologic loss, runoff rates, and time of concentration were determined using the soil conservation service curve number, soil conservation service unit hydrograph methods, and Kirpich formula. Hydrologic Engineering Center Hydrologic Modeling System estimated the wet weather flows for 10 low-to-medium rainfall events. A steady-state hydrodynamic model including river flows, effluent discharge, and evaporation and infiltration losses estimated the hydraulic retention time for the explicit case of ponding conditions of dry rivers. Mass balance and first-order kinetics modeled the physical (total dissolved solid and total suspended solid), chemical (biochemical oxygen demand, dissolved oxygen, chemical oxygen demand, NH3, PO4, and Cl2), and microbiological (total coliform and fecal coliform) parameters. The hydrodynamic model and biokinetic rate coefficients were calibrated with satellite images, reported literature, and field measurements. A water quality index compared the aggregated water quality against the standards for 4 intended uses. The study yields “very good” water quality for restricted and unrestricted irrigation for the dry period, “fair” for livestock drinking, and “marginal” for fishery and recreation for the dry period, while water quality remained “marginal” for all the uses in the wet period. Water quality management implies regular water quality monitoring, continuous improvement of treatment facilities, and flood plain management initiatives for the long-term sustainability of dry rivers in arid regions.

An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcán Copahue (Argentina & Chile)

Lahars are debris flows originating at volcanoes with very erosive and destructive capabilities. Lahars constitute a serious hazard for the communities close to the Volcán Copahue, lying at the Argentina-Chile border. This study presents a comprehensive analysis of the sensitivity of the geographic information system (GIS) assisted model LAHARZ to the spatial resolution and quality of the digital elevation models (DEMs) for mapping lahar inundation areas within the context of Volcán Copahue. In addition, critical lahar volumes required to reach the nearby settlements are investigated, following a literature review to characterize plausible triggering mechanisms. We compared lahar inundation areas at the four main catchments of Volcán Copahue resulting from five DEMs: three 30-m spatial resolution datasets (SRTM, ASTER and AW3D30), the 12-m WorldDEM™, and a 5-m DEM derived from SPOT-7 data. Our sensitivity analysis shows that DEM spatial resolution and quality precipitate into the LAHARZ results. The interaction between the spatial resolution and the channel confinement constitutes the main control of the output geometries. Higher-spatial resolution DEMs (i.e. smaller pixel size) better depict channels and better define confined channels zones resulting in narrower output areas and longer runouts. For the same volume, the inundation areas obtained using the 5- and 12-m pixel DEMs are narrower and 2–3 km longer than when derived from any of the 30-m DEMs. At unconfined channels, LAHARZ is less sensitive to the spatial resolution and inundation areas tend to show ragged edges regardless of the input DEM. The quality of the DEM controls the inundation trajectories. These results highlight the importance of evaluating topographic models for LAHARZ simulations before the implementation of the model for hazard mapping. Our results suggest that lahars of volumes of 105–106 m3 would reach the nearest villages within a radius of 15 km from the volcano. More work is required to improve the knowledge on lahar deposits and in turn hazard assessment.

Evaluation of traditional rain-fed agricultural terraces for soil erosion control through UAV observation in the middle mountain of Nepal

The livelihood of most people in the mountainous region of Nepal depends on traditional farming practices. Farmers modify their lands by constructing narrow outward sloping terraces to control soil erosion in the mountain and hill of Nepal. However, preliminary observation reveals that farmers adopt different strategies to manage outward sloping terraces according to the amount of rainfall so as to avoid the impact from soil erosion due to excessive rainfall. Thus, this study aims to evaluate the effectiveness of the traditional practice of topographic management of outward sloping rain-fed terraces to control soil erosion. The study makes a comparative analysis of topographic values of terraces and the estimated rates of soil erosion in different rainfall regions. Topographic values were derived from high spatial resolution (20 cm) Digital Elevation Model (DEM) data acquired by Unmanned Aerial Vehicle (UAV). Revised Universal Soil Loss Equation (RUSLE) was used to estimate the rate of soil erosion based on this high-resolution DEM together with other required variables. The research revealed that the traditional practice of topographic modification is highly effective to control soil erosion, as no significant differences in the rates of soil erosion were found even though the amount of rainfall considerably varies at different sites.

Effect of DEM resolution on assessing hydrological connectivity in tropical and semi-arid basins of central Mexico

• Relief and vegetation should be considered for DEM resolution selection. • High resolution is needed where heterogeneous and dispersed vegetation is present. • Distance to sinks may explain spatial differences in the index of connectivity. • Results show a balance between accuracy and processing for selecting DEM resolution. • Our findings can be considered for hydrological modelling. Assessment of hydrological connectivity is a valuable tool for water management. It enables various environmental factors related to water-mediated transport of matter and energy within or between elements of a system to be identified and incorporated into hydrological models. The index of connectivity (IC) is widely used to quantify hydrological connectivity; however, it may be influenced by the spatial resolution of the digital elevation model (DEM), which is one of the common inputs, as pixel size modifies some basin parameters. Several DEMs available on open-access platforms, with spatial resolutions from 5 to 30 m (LiDAR, ALOS, MEC, ASTER, SRTM), were compared to identify differences between IC in two basins with contrasting environments (Site 1: steep slope terrain with warm-humid climate, and Site 2: gentle hill slopes with semi-arid climate). Differences in perimeters were analyzed using GLM Repeated Measures ANOVA, while for differences in IC, one-way ANOVA was used. Relationships between IC subtracted maps and basin parameters were explored with classification and regression trees (CART). Basin perimeters and IC varied as a function of DEM resolution, but environmental factors such as relief and land use/cover seemed to influence IC maps. Distance to sinks was one of the variables explaining spatial differences in IC between DEMs. The selection of DEM spatial resolution for hydrological connectivity analysis should be based on the characteristics of the study area, economic and technological issues, and whether the objectives can be met with the available DEM resolution.

The impact of terrain model source and resolution on snow avalanche modeling

Abstract. Natural hazard models need accurate digital elevation models (DEMs) to simulate mass movements on real-world terrain. A variety of platforms (terrestrial, drones, aerial, satellite) and sensor technologies (photogrammetry, lidar, interferometric synthetic aperture radar) are used to generate DEMs at a range of spatial resolutions with varying accuracy. As the availability of high-resolution DEMs continues to increase and the cost to produce DEMs continues to fall, hazard modelers must often choose which DEM to use for their modeling. We use satellite photogrammetry and topographic lidar to generate high-resolution DEMs and test the sensitivity of the Rapid Mass Movement Simulation (RAMMS) software to the DEM source and spatial resolution when simulating a large and complex snow avalanche along Milford Road in Aotearoa/New Zealand. Holding the RAMMS parameters constant while adjusting the source and spatial resolution of the DEM reveals how differences in terrain representation between the satellite photogrammetry and topographic lidar DEMs (2 m spatial resolution) affect the reliability of the simulation estimates (e.g., maximum core velocity, powder pressure, runout length, final debris pattern). At the same time, coarser representations of the terrain (5 and 15 m spatial resolution) simulate avalanches that run too far and produce a powder cloud that is too large, though with lower maximum impact pressures, compared to the actual event. The complex nature of the alpine terrain in the avalanche path (steep, rough, rock faces, treeless) makes it a suitable location to specifically test the model sensitivity to digital surface models (DSMs) where both ground and above-ground features on the topography are included in the elevation model. Considering the nature of the snowpack in the path (warm, deep with a steep elevation gradient) lying on a bedrock surface and plunging over a cliff, RAMMS performed well in the challenging conditions when using the high-resolution 2 m lidar DSM, with 99 % of the simulated debris volume located in the documented debris area.

An artificial intelligence approach to remotely assess pale lichen biomass

Although generally given little attention in vegetation studies, ground-dwelling (terricolous) lichens are major contributors to overall carbon and nitrogen cycling, albedo, biodiversity and biomass in many high-latitude ecosystems. Changes in biomass of mat-forming pale lichens have the potential to affect vegetation, fauna, climate and human activities including reindeer husbandry. Lichens have a complex spectral signature and terricolous lichens have limited growth height, often growing in mixtures with taller vegetation. This has, so far, prevented the development of remote sensing techniques to accurately assess lichen biomass, which would be a powerful tool in ecosystem and ecological research and rangeland management. We present a Landsat based remote sensing model developed using deep neural networks, trained with 8914 field records of lichen volume collected for >20 years. In contrast to earlier proposed machine learning and regression methods for lichens, our model exploited the ability of neural networks to handle mixed spatial resolution input. We trained candidate models using input of 1 × 1 (30 × 30 m) and 3 × 3 Landsat pixels based on 7 reflective bands and 3 indices, combined with a 10 m spatial resolution digital elevation model. We normalised elevation data locally for each plot to remove the region-specific variation, while maintaining informative local variation in topography. The final model predicted lichen volume in an evaluation set (n = 159) reaching an R2 of 0.57. NDVI and elevation were the most important predictors, followed by the green band. Even with moderate tree cover density, the model was efficient, offering a considerable improvement compared to earlier methods based on specific reflectance. The model was in principle trained on data from Scandinavia, but when applied to sites in North America and Russia, the predictions of the model corresponded well with our visual interpretations of lichen abundance. We also accurately quantified a recent historic (35 years) change in lichen abundance in northern Norway. This new method enables further spatial and temporal studies of variation and changes in lichen biomass related to multiple research questions as well as rangeland management and economic and cultural ecosystem services. Combined with information on changes in drivers such as climate, land use and management, and air pollution, our model can be used to provide accurate estimates of ecosystem changes and to improve vegetation-climate models by including pale lichens.

Assessment of the geomorphic indices in relation to tectonics along selected sectors of Borpani River Basin, Assam using Cartosat DEM data

• A total of eleven geomorphic indices were studied in detail for the assessment of tectonic activity along Borpani River. • Results indicates satellite imageries based Geomorphic indices can witnesses tectonic influences. • Overall tectonic activity indicates classes - active, moderately active and less active zones in the study region. • On average, 23.86%, 29.54%, and 46.58% of the geomorphic indices falls in active, moderately active and low active classes. We studied geomorphic indices related to tectonics along the Borpani River using Cartosat 10 m spatial resolution Digital Elevation Model (DEM) data. A total of 11 geomorphic indices such as transverse topographic symmetry factor (Tt), drainage basin asymmetry (AF), valley floor width to valley height ratio (Vf), bifurcation ratio (Rb), hypsometric integral (HI), basin elongation ratio (Re), basin shape index (Bs), circularity ratio (Rc), drainage density (Dd), relief ratio (Rh), hypsometric curves (HC) were studied to access the tectonics along the river in selected locations. Five locations along the river were selected for detailed analysis (sub-basin I, II a, II b, III, and IV). Horton's (1945) scheme was adopted for watershed delineation, while stream ordering was performed using Strahler's (1964) method. The results infer that the sub-basins along the Borpani River are tectonically active. In the case of sub-basin I, 3 geomorphic indices out of 11 falls in the category of highly active, and 2, 1, 2, and 4 indices out of 11 falls in the category of highly active in the case of sub-basins II a, II b, III, and IV. Similarly, 4, 1, 3, 6, 1 and 4, 8, 7, 3, 6 indices fall under moderately active and low active classes in sub-basins I, II a, II b, III, and IV. On average, 23.86 %, 29.54%, and 46.58% of the geomorphic indices fall in the active, moderately active, and low active classes.

ON THE EFFECT OF DEM QUALITY FOR LANDSLIDE SUSCEPTIBILITY MAPPING

Abstract. Generating precise and up-to-date landslide susceptibility maps (LSMs) in landslide-prone areas is important to identify hazard potential in the future. The data quality and the method selection affect the accuracy of the LSMs. In this context, the accuracy and precision of the digital elevation models (DEMs) used as input are among the most important performance elements. Therefore, the influence of DEM accuracy and spatial resolution in producing LSMs was investigated here. A high accuracy DEM with 5 m grid spacing produced from aerial photographs and the EU-DEM v1.1 freely accessible from Copernicus Land Monitoring Service with 25 m spatial resolution were used for producing two different LSMs using the Random Forest (RF) method in this study. The RF method has proven success for this purpose. A total of eight conditioning factors, which include topographical and geological features, was used as model input. The landslide inventory was derived with the help of aerial stereo images with 20 cm and 30 cm ground sampling distances. The performances of the LSMs were assessed with receiver operating characteristics (ROC) area under curve (AUC) values. In addition, the results were compared with visual inspection. The results show that although the AUC values obtained from the aerial DEM (0.95) and EU-DEM v1.1 (0.93) were comparable; based on the visual assessments, the LSM obtained from the higher resolution DEM was found more successful in detecting the landslides and thus exhibited better prediction performance.

Geodiversity of closed depressions in a high relief karst: Geoeducation asset and geotourism resource in the "Sierra de las Nieves" National Park (Málaga Province, Southern Spain)

Closed depressions are scale-invariant landforms that are the most distinctive and characteristic landform in karst terrains at the millimetre-to-kilometre scales. The purpose of this paper is twofold. The first is to raise awareness of the geoheritage and geoeducational asset provided by closed depressions in a high-relief karst massif with the objective of promoting geotourism in the Sierra de las Nieves National Park in Southern Spain, which was declared a national park in 2021. The second is to propose a general, sound methodological approach to achieve the first purpose that can be applied to other national parks and geoparks with karst terrains. This paper identifies the factors that generate geodiversity in closed depressions in karst and, although dissolution is the primary generator in the high relief karst massif analysed, five distinctive types of natural, closed depressions have been recognized and described together with particular cases that deserve consideration. A sixth type of closed depression comprises anthropic closed depressions. Lithology and tectonics are the two main geological factors that determine the different types of natural closed depressions. Closed depressions add value to the geomorphological and hydrogeological diversity of karst terrains, and they can be used at various levels both off-site and on-site for preparing exhibits at a visitor or interpretation centre; as a story resource for guided field tours; and for identifying geosites of special interest for geological itineraries. Generating interpretation methods is an important component of transferring scientific knowledge of, and interest in, karst landscapes to the various types of visitors to the recently declared Sierra de las Nieves National Park in Andalusia, Southern Spain. In addition, an extensive inventory of closed depressions can be used for their identification, mapping, conservation, protection, and management. Such an inventory, which can be obtained efficiently from high spatial resolution digital elevation models, also contributes to the promotion and dissemination of geomorphological science to the general public.

An Exploratory Evaluation of Multiscale Data Analysis for Landform Element Detection on High-Resolution DEM

The representation of landform element varies over multiple scales, or multiresolution digital elevation model (DEM) and its derivatives. When more details of land surfaces are available to be characterized based on the existing high spatial resolution elevation products, the influence of scale variation might become more significant. This poses a demand for determining a scale-independent approach being competent to support multiscale landform element detection on high-resolution DEMs. Although the practicability of the state-of-the-art scale-independent approaches have been reported on moderate-resolution DEMs, how these approaches perform based on the multiscale data including high and moderate spatial-resolution DEMs is still unexplored. This letter evaluates the performance of four scale-independent techniques including filtering, spatial pyramid, multiscale segmentation, and spatial-contextual approach in landform element detection on different spatial resolution DEMs. The experimental results show that spatial–contextual approach is more effective to support multiscale landform element detection than others.

Lake Level Reconstructed From DEM-Based Virtual Station: Comparison of Multisource DEMs With Laser Altimetry and UAV-LiDAR Measurements

Although the traditional water-level observation has been improved by wide application of satellite altimetry, the acquisition of fully-covered, long-term water level is impeded by the inadequacies of radar/laser altimetry sensors. Alternatively, the water level of lakes in various sizes can be obtained by combining multitemporal lake shorelines and superimposed topographic information [e.g., digital elevation model (DEM)]. However, the quantification and reduction approach of the uncertainty of water levels reconstructed from the topographic data remains largely unexplored. Therefore, this study aims to develop an improved DEM-based method for reconstructing long-term water levels for ungauged lakes. Before this, we first assessed the characteristics of vertical height uncertainties of DEMs varying with topographic slopes. Assessment results for DEM evaluated based on ICESat-2 show that higher spatial resolution DEMs (Shuttle Radar Topography Mission (SRTM) DEM and AW3D DEM) achieve a higher vertical accuracy with the mean absolute error (MAE) of 3.67 and 3.46 m, respectively, while the mean error will decrease to 1.8 m upon the slope below 1°. Our study confirms that terrain relief exerts strong influences on the DEM data quality. As the DEMs show higher error in steeper terrain, the proposed method first selects the lake bank sites at gentle slopes as the virtual stations and then reconstructs water-level series by superimposing lake shorelines over DEMs at the virtual stations. Results revealed that the reconstructed lake levels show strong correlations with the Hydroweb water level from altimetry data with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> close to 0.90. Furthermore, we found that unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR)-based DEM is expected to have much better performance in the virtual station method.

The impact of (DEM) Accuracy on the Watersheds areas as a function of spatial data

Digital Elevation Model (DEM) is main input for watershed modelling. Recently, (DEM) is available online for free in different accuracies, and spatial resolutions as a product of several remote sensing satellites. Hence, it is necessary to find out which one is the best for watershed modeling in the study area. In this study, the different accuracies 30m spatial resolution DEMs of (Copernicus, SRTM, and ASTER) can be examined by using Remote sensing (RS) and Geographic Information systems (GIS) techniques to delineate and calculate the topographic characteristics for five different size and topography watersheds (Swaidy, Garlond, Khuwayr Hirah, Naqab, and Kalak) located on both sides of the Mosul reservoir in the northeastern part of Iraq. The analysis results can be led to find that the Copernicus (GLO-30) 30 m resolution DEM is the optimum and most accurate DEM in the selected study area at the vertical accuracy (1.3521 m) and with 95% confidence level is (2.6502 m) represented by the minimum Root Mean Square Error (RMSE) of the elevations differences between check points (MOWR elevations and LIDAR DEM 1 m resolution) and the used DEMs. The watershed delineation and calculated topographic characteristics (watersheds boundary, elevations, area, perimeter and slope areas) are affected by DEM accuracy. Where the considerable accuracy of the differences is with the (Copernicus-SRTM) DEMS at the minimum RMSE of watersheds characteristics.

Generation of Homogeneous Slope Units Using a Novel Object-Oriented Multi-Resolution Segmentation Method

The generation of map units is a fundamental step for an appropriate assessment of landslide susceptibility. Recent studies have indicated that the terrain relief-based slope units perform better in homogeneity compared with the grid units. However, it is difficult at present to generate high-precision and high-matching slope units by traditional methods. The problem commonly concentrates in the plain areas without obvious terrain reliefs and the junction of sudden changes in terrain. In this paper, we propose a novel object-oriented segmentation method for generating homogeneous slope units. Herein, the multi-resolution segmentation algorithm in the image processing field is introduced, enabling the integration of terrain boundary conditions and image segmentation conditions in slope units. In order to illustrate the performances of the proposed method, Kitakyushu region in Japan is selected as a case study. The results show that the proposed method generates satisfactory slope units that satisfactorily reproduce the actual terrain relief, with the best within-unit and between-unit homogeneities compared with the previous methods, in particular at the plain areas. We also verify the effectiveness of the presented method through the sensitivity analysis using different resolutions of digital elevation models (DEMs) data of the region. It is reported that the presented approach is notably advanced in the requirements of the quality of DEM data, as the presented approach is less sensitive to DEM spatial resolution compared with other available methods.

Effect of digital elevation model spatial resolution on depression storage

AbstractSurface water storage—including wetlands and other small waterbodies—has largely been disregarded in traditional hydrological models. In this paper, the grid resampling method is adopted to study the influence of the digital elevation model (DEM) grid resolution on depression storage (DS) considering different rainfall return periods. It is observed that the DEM grid size highly affects DS, and the higher the grid resolution is, the larger the DS value. However, when the grid resolution reaches a certain value, the maximum DS value decreases. This suggests that a critical grid resolution value exists at which the water storage capacity of depressions is maximized, namely, 20 m in this work (except for the overall area simulation under infiltration). This phenomenon is further verified in two test cases with and without the infiltration process, that is, calculations of the local area and without infiltration area, respectively. This research may facilitate the accurate computation of the DS process, which is greatly affected by the grid resolution, thereby improving the reliability of hydrological models.

Towards Monitoring Waterlogging with Remote Sensing for Sustainable Irrigated Agriculture

Waterlogging is an increasingly important issue in irrigated agriculture that has a detrimental impact on crop productivity. The above-ground effect of waterlogging on crops is hard to distinguish from water deficit stress with remote sensing, as responses such as stomatal closure and leaf wilting occur in both situations. Currently, waterlogging as a source of crop stress is not considered in remote sensing-based evaporation algorithms and this may therefore lead to erroneous interpretation for irrigation scheduling. Monitoring waterlogging can improve evaporation models to assist irrigation management. In addition, frequent spatial information on waterlogging will provide agriculturalists information on land trafficability, assist drainage design, and crop choice. This article provides a scientific perspective on the topic of waterlogging by consulting literature in the disciplines of agronomy, hydrology, and remote sensing. We find the solution to monitor waterlogging lies in a multi-sensor approach. Future scientific routes should focus on monitoring waterlogging by combining remote sensing and ancillary data. Here, drainage parameters deduced from high spatial resolution Digital Elevation Models (DEMs) can play a crucial role. The proposed approaches may provide a solution to monitor and prevent waterlogging in irrigated agriculture.

Automatic mapping and spatial analysis of high spatial resolution closed terrain depressions and mounds on martian landscapes

The purpose of this paper is to illustrate a methodology for the automatic mapping and spatial analysis of high spatial resolution (metric scale) closed depressions and mounds on Mars landscapes. The proposed automatic procedure requires only a digital elevation model, a sink-filling algorithm and a basic map algebra operation all of which are available in the most commonly used Geographical Information Systems. Six high spatial resolution (1 m to 2 m) digital elevation models obtained from images of the High-Resolution Imaging Science Experiment (HiRISE) were selected as representatives of various Martian landscapes representing hypothesized aeolian, volcanic, hydrated, cratered, reticulate and sublimated terrains. This is not an exhaustive list of landscapes but it is representative of the variety of Martian landscapes. Metric spatial-scale closed depressions and mounds are commonly distributed in all the landscapes selected for this study and closed terrain depressions cover, on average, 25% of the Martian surface. Most closed depressions are small and shallow and have a complex shape. The area covered by mounds is more variable and is up to 36% in reticulate terrain and 43% in volcanic terrain. Again, most mounds are small, low and have complex shapes. For sublimated terrains the percentage covered by depressions, in the form of radiating araneiform channels, is equal to the percentage of mounds (material accumulated between the channels). Size distribution analysis reveals the fractal character of both closed depressions and mounds with the emergence of two main groups of landscapes. One group characterizes a detached geomorphology (aeolian and sublimated terrains), and the other group characterizes a connected geomorphology (volcanic, impact craters and reticulate terrain). The hydrated terrain is intermediate between the two main groups perhaps because of its plastic rheology. The proposed methodology is completely general and can be applied to any digital elevation model. The mapping and morphometric analysis of closed terrain depressions and mounds can assist planetary geologists in the mapping and interpretation of geological and geomorphological units and in the inference of geological processes.