Types Of Digital Elevation Models Research Articles

Regional evaluation of global geopotential models and three types of digital elevation models with ground-based gravity and GNSS/levelling data using several techniques over Sudan

Abstract To evaluate the performance of the global geopotential models (GGMs) in a more unbiased way, ground-based gravity and GNSS/levelling datasets are highly required. In this study, the eight latest releases of the satellite-only and combined GGMs are evaluated on the regional scale using the available terrestrial gravity and GNSS/Levelling data over Sudan, considering the spectral consistency issue by applying the spectral enhancement method (SEM). The evaluation process consists of three stages: firstly, the eight GGMs are evaluated globally with each other by using different degree variances in terms of geoid heights, gravity anomalies, and signal-to-noise ratio (SNR); secondly, the GGMs are compared against the Earth Gravitational Model 2008 (EGM2008) on a regional scale over Sudan; thirdly, apply the SEM strategy by incorporating high (SEM_WITHOUT_RTM technique) and very-high (SEM technique) frequencies of the gravity field spectrum from the EGM2008 and high-resolution residual terrain model (RTM), respectively. For reliable robustness of the latter evaluation process, three different DEMs are used, namely, SRTM30, ASTER30, and GTOPO30. Our findings on the evaluation process using SEM_WITHOUT_RTM technique show improved gravity anomalies solutions regarding differences of standard deviations (STD) from 19–20.7 mGal to about 14 mGal. When applying the SEM technique, more improvements are achieved, providing STD differences in gravity anomalies and geoid heights of about 12 mGal and 45 cm, respectively. Among the three applied DEMs, it has been found that despite the slight refinements, the ASTER30 and GTOPO30 models show better performance than the SRTM30 model.

Predicting the Distribution of Mangrove Forests through Random Forest Algorithm by Combining Spectral Features and DEM Data

Using satellite data and machine learning-based classification methods for mangrove forest identification has gained popularity due to their effectiveness in producing high accuracy. Therefore, this research developed a random forest classification model using various dataset combinations representing spectral and topographical aspects to identify mangrove forests in Segara Anakan, Cilacap. We used the Sentinel-2 imagery acquired in 2022. Two types of digital elevation model (DEM) data were utilized, namely the National Digital Elevation Model (DEMNAS) and Multi-Error-Removed Improved-Terrain DEM (MERIT DEM). Another critical dataset used is the Normalized Difference Moisture Index (NDMI), derived from the ratio between near-infrared (NIR) and shortwave-infrared (SWIR) bands. The classification method used is the random forest algorithm on six different dataset combinations, including IMAGE, IMAGE+NDMI, IMAGE+DEMNAS, IMAGE+MERIT DEM, IMAGE+NDMI+DEMNAS, and IMAGE+NDMI+ MERIT DEM. The results showed that the combination of Image+DEMNAS and Image+NDMI+DEMNAS datasets was able to identify the mangrove forests more optimally. Incorporating DEM data alongside IMAGE and NDMI datasets resulted in a remarkable level of accuracy in mangrove forest mapping, exceeding 90%. DEM data has a very important role in increasing the classification accuracy of mangrove forests using the random forest algorithm.

Comparative Study of Different Types of Digital Elevation Models on the Basis of Drainage Morphometric Parameters (Case Study of Wadi Fatimah Basin, KSA)

Nowadays there are a lot of geospatial datasets available in the form of different types of Digital Elevation Models (DEMs) which were launched with different resolutions. These datasets are used for studying the physiographical features of the hydrographic basins through the tracing and extracting the elevation points, watershed boundaries, streamlines, flow directions and morphometric parameters assessment. Many researchers have used these datasets to study and evaluate the hydrologic behavior of the basins which is considered as the reflection of physiographic features of the hydrographic basins. In the Middle East especially in Saudi Arabia, the trend of using DEMs increased for hydrographic basin analysis and assessment of hydrologic behavior. So, there is an important question about the accuracy and sensitivity of these datasets which are acquired from different DEMs. This study deals with four types of DEMs, first is derivative from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER 30 m resolution), second is Shuttle Radar Topographic Mission (SRTM 90 m resolution), third is SRTM 30 m resolution and the fourth is the Advanced Land Observing STLT (ALOS 30 resolution). More than 35 morphometric parameters including drainage network, basin geometry, basin texture and basin relief characteristics were measured and calculated using these four types of DEMs and calibrated with topographic maps of 1:250 K and 1:50 K scale and also google earth maps. Results show that the SRTM 30 m is characterized by high accuracy and has a very good matching with google earth maps and topographic map of scale1:50,000. This research is dealing with the comparison of the morphometric parameters of the hydrographic basin based on the type of DEM. It is clear to conclude that the SRTM 30 resolution is the best type for hydrology and water resources study.

Цифровое моделирование рельефа Республики Мордовия

The authors present the experience of obtaining various types of digital elevation models on the territory of the Republic of Mordovia based on using GIS and geoinformation technologies. The possibilities of operative creating a series of derivative thematic geoinformation and cartographic models of several most important morphometric relief indicators characterizing the objects’ shape and structure are considered. The features of digital simulation based on triangulation irregular network (TIN) using Delaunay triangulation are shown in details. The matter of the resulting relief-TIN-models evaluation is analyzed. The features of the technique, the technological sequence of creation and examples of various options for DEM and derived geoinformation-cartographic materials of a number of territories of the Republic of Mordovia (Temnikovsky and Bolsheignatsky administrative regions, as well as Vindrey River Basin) using the capabilities of various software – the software package of scientific and engineering graphics Surfer and GIS ArcGIS are considered. The directions and possibilities of further theoretical and applied using various DEM variants and information obtained basing on geoinformational mapping and modeling the relief, are determined, especially in assessing the risk of emergency situations.

Sight Distance Studies on Roads: Influence of Digital Elevation Models and Roadside Elements

Sight distance plays an important role in road traffic safety. Two types of Digital Elevation Models (DEMs) are utilized for the estimation of available sight distance in roads: Digital Terrain Models (DTMs) and Digital Surface Models (DSMs). DTMs, which represent the bare ground surface, are commonly used to determine available sight distance at the design stage. Additionally, the use of DSMs provides further information about elements by the roadsides such as trees, buildings, walls or even traffic signals which may reduce available sight distance.This document analyses the influence of three classes of DEMs in available sight distance estimation. For this purpose, diverse roads within the Region of Madrid (Spain) have been studied using software based on geographic information systems. The study evidences the influence of using each DEM in the outcome as well as the pros and cons of using each model.

Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: a case study in Mizunami City, Japan

To mitigate the damage caused by landslide disasters, different mathematical models have been applied to predict landslide spatial distribution characteristics. Although some researchers have achieved excellent results around the world, few studies take the spatial resolution of the database into account. Four types of digital elevation model (DEM) ranging from 2 to 20 m derived from light detection and ranging technology to analyze landslide susceptibility in Mizunami City, Gifu Prefecture, Japan, are presented. Fifteen landslide-causative factors are considered using a logistic-regression approach to create models for landslide potential analysis. Pre-existing landslide bodies are used to evaluate the performance of the four models. The results revealed that the 20-m model had the highest classification accuracy (71.9%), whereas the 2-m model had the lowest value (68.7%). In the 2-m model, 89.4% of the landslide bodies fit in the medium to very high categories. For the 20-m model, only 83.3% of the landslide bodies were concentrated in the medium to very high classes. When the cell size decreases from 20 to 2 m, the area under the relative operative characteristic increases from 0.68 to 0.77. Therefore, higher-resolution DEMs would provide better results for landslide-susceptibility mapping.

Determination of long-term erosion rates in vineyards of Navarre (Spain) using botanical benchmarks

Abstract Grape production is an ancient and important activity, particularly in Spain. Within this country, Navarre is one of the best vine-producing regions. Despite the importance of the vine crop, any quantification of soil erosion rates on a pluri-decennial scale under this world-wide land use is scant. Considering that in Navarre grafting in vines was made until the 1990s directly in the field, and almost at soil surface level, the quantification of erosion/sedimentation rates around a single plant can be performed by using the large, identifiable callus forming around the graft as a palaeo-surface marker. Moreover, by sampling a number of vines evenly spread over the field, an erosion/sedimentation pattern within the study vineyards can also be defined by data interpolation. Our purpose in this paper is thus (i) to assess the erosion rates of vineyards of different ages in a Mediterranean area using the aforementioned botanical signal i.e., grafting callus, and (ii) to determine the topographic changes caused by the erosion processes in these fields. Some vineyards affected by soil erosion were selected to carry out our experiments. In the region of Navarre, 7 rain-fed vineyards of different ages (between 22 and 61 years old) were selected as experimental plots. To find out how far from the ground surface the graft was originally made, we sought vineyards close and (almost) contemporary to the studied ones, whose soil surface level has remained roughly invariant during the time. Also, 2 types of Digital Elevation Models (DEM) were created: (i) A DEM depicting the present land surface by using the actual elevation values of the soil surface, and (ii) another DEM aiming to recreate the former topography of the vineyard (i.e. that present near planting time). By performing in each vineyard a subtraction of the DEM representing the land surface at the moment of planting from the DEM of the present land surface, a new DEM quantifying the local soil loss/gain rates over the entire crop span is obtained. The present work reveals important overall erosion rates in vineyards of Navarre (ca. 3 kg m− 2 year− 1 or 2 mm year− 1) which, on average, greatly exceed even the most conservative soil loss tolerance thresholds. Moreover, the results suggest that tillage erosion is the leading soil loss process in the study vineyards rather than water erosion. Our innovative way of determining overall rates of soil surface changes in grafted vineyards appears to be a promising method to estimate long-term erosion/sedimentation rates not only in vines but also in other crops, providing a reliable botanical benchmark of the former soil surface. Furthermore, a spatial pattern of soil loss and gain can also be defined in the terrain. Furthermore, this soil loss assessment could be a valuable way, to some extent, to compensate for the lack of information on long-term erosion rates in cultivated areas of Navarre and Spain, as well as to validate long-term erosion models such as USLE or the like.

Analysis of landslide susceptibility in the Suusamyr region, Tien Shan: statistical and geotechnical approach

The Suusamyr region is located in the northern part of the Tien Shan Range in Central Asia. In 1992, this region was hit by the Ms = 7.3 Suusamyr earthquake triggering several large landslides along the Suusamyr Valley and on the southern slopes of the adjacent Suusamyr Range. One of these landslides had been investigated by geophysical and geotechnical methods in order to determine local trigger factors. The present paper focuses on the influence of geological and morphological factors upon landslide occurrence on a regional scale. The analysis is based on a digital data set including landslides triggered in 1992 and several older landslides as well as various types of digital elevation models (DEMs), ASTER image data, and geological and active fault maps. These data were combined to compute landslide susceptibility (LS) maps using statistical methods, Landslide Factor and Conditional Analyses (LFA, CA), as well as a geotechnical one, the Newmark's Method (NM). The landslide data set was also analyzed with respect to the size–frequency relationship.

Topography data harmonisation and uncertainties applying SRTM, laser scanner and cartographic elevation models

Abstract. Only a few studies have attempted to quantify topography-depending water fluxes, to evaluate retention and reservoir capacities and surface run-off paths within large river basins because data availability and data quality are critical issues to face this objective. It becomes most relevant if water balance has to be calculated in large or transboundary river basins. The advance of space based earth observation data offers a solution to this information problem. Therefore, this paper mainly focuses on weaknesses and strengths analyzing topography with SRTM (Shuttle Radar Topography Mission) digital height data and thus provides techniques for their improved application in river network derivation, floodplain analysis, watershed hydrology in large as well as in large river basins (>1000 km2). In the analysis different types of digital elevation models (DEM), terrain models (DTM) and land cover classification data (biotope map, Corine Land Cover 1994) have been used. The DHMs are generated from Airborne Laser Scanning (0.5 m), topographic maps (10.0/50.0 m) and SRTM at 30.0 m and 90.0 m spatial resolution. SRTM digital height models are generated by Synthetic Aperture Radar (SAR) and show a high spatial variance in urban areas, regions of dense vegetation canopy, floodplains and water bodies. As study area serve the Elbe basin (Czech Republic, Germany) with its sub-basins and the Saale river basin (Germany, different federal countries Saxony-Anhalt, Saxony and Thuringia).

Digital elevation data

The primary goal of the session Integration of Digital Elevation Data into Hydrologic Models, sponsored by the Surface Water Committee of the AGU Hydrology Section at the AGU 1989 Fall Meeting in San Francisco, was to provide an overview of the various types of Digital Elevation Model (DEM) data and methods used to incorporate these data into rainfall‐runoff models.