Digital Elevation Model Processing Research Articles

Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data

Abstract. Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.

Enhancing Digital Elevation Model Accuracy for Flood Modelling – A Case Study of the Ciberes River in Cirebon Indonesia

Topographic conditions represented by the Digital Elevation Model (DEM) are essential in flood inundation models. The DEM which is categorised as a Digital Surface Model (DSM) stores the height information, be-sides the ground and non-ground elevation required for preprocessing before being employed in hydrologic applications, particularly in relation to flood modelling by removing non-ground elevation along the flood plain and river channels. The improvement in the accuracy of flood inundation modelling is crucial in reduc-ing the impact of flood disasters. This study aims to compare the accuracy level of the DEM based on Ter-raSAR-X data with the filtering process using slope-based filtering and combining the cross-sectional river profile from the field measurement to the filtered DEM. The result confirms that the accuracy of the DEM product is improved via filtering to remove non-ground elevations and a significant improvement in accuracy by means of fused river profile information to filtered DEM. The results of adding river information to the DEM could provide a representation closer to the cross-sectional profile of the river based on field measure-ments within the accuracy level Mean Absolute Error 2.51 m, 2.72 m and 1.91 m in the left overbank, right overbank and centre of the river, respectively. The performance results of the 2-dimensional flood hydrody-namic modelling using HEC-RAS derived from the DEM before filtering, after filtering, and the addition of river information show increasing accuracy in flood depth at each stage of the DEM processing. There is an improvement in accuracy in flood depth of approximately 11.67% using the filtered DEM, besides an in-crease in accuracy in flood depth by 24.98% utilising the filtered DEM with added river channel information.

Caracterização morfométrica da bacia hidrográfica do rio Tapacurá, Pernambuco, Brasil

The morphometric characterization of a river basin represents an important mechanism for the management of water resources, as it is directly related to its hydrological regime. These characteristics can be obtained from the processing of Digital Elevation Models (DEM) in a Geographic Information System (GIS) environment. The present study sought to analyze the morphometric characteristics of the Tapacurá river basin, a sub-basin of the Capibaribe river that is located between the Zona da Mata and Agreste mesoregions of the state of Pernambucano, using DEM from airborne laser profiling (LiDAR) . The automatic delimitation of the basin was carried out, the extraction of its hydrographic network and, consequently, the obtaining of its geometric, hydrographic and relief morphometric parameters. From the results, it was verified that the Tapacurá river basin has an elongated shape, giving it a low propensity to floods, encompasses a regular drainage system, its main channel has a rambling shape and has elevations that vary from 40.06 m to 576.30 m. m. Knowledge of these characteristics constitutes an important instrument in the management and planning of water resources in the region, and can be used as a support for decision-making by managers and/or professionals in the area, in order to support the development of public policies that provide harmonious coexistence. between the population and water resources.

Topological Relationship‐Based Flow Direction Modeling: Stream Burning and Depression Filling

AbstractFlow direction modeling consists of (a) an accurate representation of the river network and (b) digital elevation model (DEM) processing to preserve characteristics with hydrological significance. In part 1 of our study, we presented a mesh‐independent approach to representing river networks on different types of meshes. This follow‐up part 2 study presents a novel DEM processing approach for flow direction modeling. This approach consists of (a) a topological relationship‐based hybrid breaching‐filling method to conduct stream burning for the river network and (b) a modified depression removal method for rivers and hillslopes. Our methods reduce modifications to surface elevations and provide a robust two‐step procedure to remove local depressions in DEM. They are mesh‐independent and can be applied to both structured and unstructured meshes. We applied our new methods with different model configurations to the Susquehanna River Basin. The results show that topological relationship‐based stream burning and depression‐filling methods can reproduce the correct river networks, providing high‐quality flow direction and other characteristics for hydrologic and Earth system models.

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

AbstractBroad‐scale mapping of stream channel and floodplain geomorphic metrics is critical to improve the understanding of geomorphic change, biogeochemical processes, riverine habitat quality, and opportunities for management intervention. The Floodplain and Channel Evaluation Tool (FACET) was developed to provide an open‐source tool for automated processing of digital elevation models (DEMs) to generate regional‐scale estimates of bank height, channel width, floodplain width, and a suite of other fluvial geomorphic dimensions that can be summarized at the stream reach‐ or catchment‐scale. FACET was tested on 3‐m DEMs covering the Delaware River watershed and 85% of the Chesapeake Bay watershed in the United States (U.S.) and on 1‐m DEMs for a subset of the study area. Accuracy was assessed from data collected at 67 field sites in the study area. FACET successfully measured geomorphometry for over 270,000 stream reaches (88% of streams attempted) in the study area. Factors that reduced the ability of FACET to accurately estimate geomorphic metrics included errors in DEM hydro‐conditioning, gradually sloping banks, incised stream channels, and the use of fixed input parameters to define buffer lengths. Even with these limitations, FACET was able to map regional patterns in stream and floodplain geomorphometry providing a robust dataset that can enhance modeling and management efforts throughout the mid‐Atlantic region, U.S.

Topographic hydro-conditioning to resolve surface depression storage and ponding in a fully distributed hydrologic model

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow.

Использование морфометрических показателей рельефа для почвенного картографирования пашни в условиях средней тайги в северной части Пермского края

The digital elevation model (DEM) matrix allows to reveal the relationship of the soil cover with morphometric parameters. Therefore, in the absence of the possibility of a large-scale field survey of soils, for territories with a high degree of erosion hazard, the data on the relief make it possible to carry out predictive large-scale soil maps. The aim of the work is to create a cartographic model of the soil cover of agricultural land based on the extrapolation of the results of DEM processing and to compare it with the existing large-scale soil map in similar natural conditions. The object of research is the territory of LLC “Selskoe” located in the Solikamsk urban district of the Perm region. Agricultural land use belongs to the northernmost agricultural lands in the region. The total area of research was 429 hectares of arable land. The plot includes 8 fields. For soil mapping, a digital elevation model ALOS 30 and a large-scale soil map of the key site were used, which characterizes part of the land use of the subsidiary farm “Voskhod”. Using the results of the classification of the relief according to the GIS SAGA TPI based landform classification algorithm as a contour base and the existing soil map of the key site, a soil map of LLC “Selskoe” was made by the extrapolation method. The steepness of the slopes and the topographic moisture index were used as auxiliary data. In conditions of complex relief, a clear dependence of the location of soils on relief elements has been established. By extrapolating data from a large-scale soil survey, 10 soil cartographic units were identified. According to the relief elements, podzolic, sod-podzolic, bog-podzolic and alluvial soils were identified. In terms of granulometric composition, light soils prevail, a small area is occupied by medium loamy soils.

Цифровые технологии дистанционного выявления и мониторинга развития бугров пучения и кратеров катастрофических выбросов газа в Арктике

In the course of the three years work in the Arctic with ArcticDEM digital elevation models (DEM), the researchers have obtained fundamentally new results on the natural catastrophic transformations of the landscapes of the Yamal Peninsula in the process of powerful gas blowouts and explosions. They have proved the possibility of detecting gas-explosive objects and processes during regional 4D monitoring based on DEM processing, and in the course of the retrospective 4D monitoring, have identified a number of potential gas blowout objects. The authors have identified disadvantages and proved the need for further improvement of the ArcticDEM data. They have built 3D-models of the areas of catastrophic induced gas blowouts during the drilling of exploration wells in the Arctic, including the Kumzhinskoye field. Using an unmanned aerial vehicle (drone DJI Mavic Pro), the researchers carried out aerial photography and built 3D models of a number of gas blowout craters. For the first time in Yamal, they performed an underground aerial photography of the gas blowout crater space C17, indicating the existence of a gas-sat

Digital Elevation Models of the Bottom in the Operational Oceanography System

A new area of oceanography, operational oceanography, involves a comprehensive assessment and forecast of the variability of the state of the marine environment. This requires systematic study of numerous natural parameters, the creation of integrated measurement systems for the properties of the water column and seafloor, rapid data collection and transmission systems, assimilation of new data in the model, etc. The seafloor has a significant impact on the hydrophysical state of the environment and vice versa; accordingly, information is needed on the state and properties of the bottom in the deployment area of various surveillance tools, including assessment of possible geohazards. The spatial distribution and possible variability of the geomorphological and geological–geophysical parameters of the bottom, which determine the geoacoustic properties, depends on the shape of the relief and its morphometric characteristics. Thus, the digital elevation model (DEM) is an essential component of marine geographic information systems and an essential element of operational oceanography. A DEM entails an organized structure of files containing vector representations of various types of spatial objects, information on their attributes, and topological relationships between them. The DEM displays the seafloor relief as a grid file with a resolution corresponding to a given scale. Methods for the direct spatial mathematical processing of DEMs make it possible to obtain a wide range of bottom surface characteristics, including morphometric. DEMs can have both independent practical application and act as parameters for systematizing, typifying, and zoning the seafloor. The paper outlines some areas of the possible use of DEMs in operational oceanography with a case study of the Arctic shelf.

A Novel Approach for Generation and Visualization of Virtual 3D City Model Using Open Source Libraries

Virtual 3D city models are digital representation of terrain surfaces, sites, buildings, roads, waterways, etc. In general, these models are used for presenting, exploring and analyzing the urban areas. These models are also used in domains of smart city, virtual reality, infrastructure planning, telecommunication, disaster management, real estate services, education, tourism and change detection. There are various approaches and commercial packages to generate virtual 3D city models. In this novel approach, we have not used any commercial package or tool toward generation and visualization of city model but instead developed in-house routines and used libraries from open source domain to generate and visualize real-time virtual 3D city models. Generation of 3D city models involves the imagery from high-resolution satellite, high-resolution digital elevation model (DEM) and vector shape files from open street maps (OSM) ( https://www.geofabrik.de/geofabrik/openstreetmap.html ) as inputs. Over and above virtual 3D city models, OSM vector layers of road network, river network and important places have been overlaid for making the virtual city model more informative. Toward realism, virtual trees are placed in the open spaces (as per shape file markings), Sun position and day/night effects, ambient condition effects and building texture, has been incorporated. To achieve generation of city model, we mosaicked preprocessed DEM scenes and images, resampled given datasets using cubic-resampling algorithm, registered the image, DEM and vector layers using phase correlation algorithm, and extracted the height information by processing of DEM and shape files. Vector layers are registered using latitude and longitude and overlaid over the 3D city model for information about the places, roads and water bodies. For efficient visualization and rendering of the model, open scene graph library and tiling-based approach are used in which tiles are replaced in the main memory by its sub-tiles based on viewer’s position. Mentioned approach is applicable to generate and visualize city model of any given area provided the DEM, imagery and OSM data. This paper mainly discusses the approach and advantages of this new cost-effective approach to develop virtual 3D city models using Indian Remote Sensing datasets.

Classificação morfológica na escala de detalhe no Pontal do Paranapanema, SP

O presente artigo visa apresentar a viabilidade da classificação morfológica em escala de detalhe do relevo em bacias hidrográficas, de acordo com as legendas propostas por Colangelo (1996), correspondendo às Unidades Elementares do Relevo; e do quinto táxon da taxonomia proposta por Ross (1992), referente aos tipos e formas de vertentes com o uso de técnicas de geoprocessamento. Para tanto foi tomado como estudo de caso duas sub-bacias hidrográficas do Rio Santo Anastácio, localizadas na região do Pontal do Paranapanema. Os compartimentos morfológicos foram classificados através do processamento de Modelos Digitais de Elevação - MDE e ortofotos em ambiente de Sistemas de Informações Geográficas – SIG. Estes dados foram disponibilizados pela Emplasa (2011), e são provenientes do projeto “Mapeia São Paulo”, último levantamento sistemático de dados topográficos e aerofotogramétricos realizados para todo o território do estado de São Paulo. Como resultado foram obtidas as nove classes possíveis de Unidades Elementares do Relevo e, ao menos, seis classes diferentes de tipos e formas de vertentes, confirmando, portanto, a viabilidade técnica e metodológica dos procedimentos adotados no que se refere ao tratamento dos dados utilizados para a realização da classificação morfológica na escala de detalhe em bacias hidrográficas da região do Pontal do Paranapanema.

Regular Grid DEM Data Processing Based on Hadoop

Digital Elevation Model (DEM) has been widely used in various sectors. But its data structure is special, and the amount of data is large. When it comes to big data or large-scale data simulation, the data processing of stand-alone mode often fails to meet the needs of users. This paper focuses on the Hadoop cloud computing platform for large data parallel processing and its built-in data types is limited, study the organization method of the regular grid DEM in the cloud computing platform, and designs the data types that applicable to the regular grid DEM processing in MapReduce framework. Finally, realize the parallelization processing of DEM and use non-source flood analysis as an example to verify the feasibility of data types.

Accuracy Assessment of Digital Elevation Model Generated by SAR Stereoscopic Technique Using COSMO-Skymed Data

Radargrammetry technique using the stereoscopic synthetic aperture radar (SAR) images is used for the generation of a digital elevation model (DEM) of a region requires only the amplitude images. SAR stereoscopic technique is analogous to the stereo-photogrammetric technique where the optical stereoscopic images are used for DEM generation. While the advantages of the SAR images are their indifference to atmospheric transparency and solar illumination conditions, the side-looking geometry of the SAR increases the complexity in the SAR stereo analysis. The availability of high spatial and temporal resolution SAR data in recent years has facilitated generation of high-resolution DEM with greater vertical accuracy using radargrammetric technique. In the present study, attempt has been made to generate the DEM of Dehra Dun region, India, from the COSMO-Skymed X-band SAR data-pair acquired at 8 days interval through the radargrammetry technique. Here, radargrammetric orientation approach has been adopted to generate the DEM and various issues and processing steps with the radargrammetry technique have been discussed. The DEM was validated with ground measured elevation values using a differential global positioning system and the root-mean-square error of the DEM was found as 7.3 m. The DEM was compared with the reference DEM of the study area generated from the Cartosat-1 stereo data with a model accuracy of 4 m.

Contour-based automatic crater recognition using digital elevation models from Chang'E missions

In order to provide fundamental information for exploration and related scientific research on the Moon and other planets, we propose a new automatic method to recognize craters on the lunar surface based on contour data extracted from a digital elevation model (DEM). Through DEM and image processing, this method can be used to reconstruct contour surfaces, extract and combine contour lines, set the characteristic parameters of crater morphology, and establish a crater pattern recognition program. The method has been tested and verified with DEM data from Chang’E-1 (CE-1) and Chang’E-2 (CE-2), showing a strong crater recognition ability with high detection rate, high robustness, and good adaptation to recognize various craters with different diameter and morphology. The method has been used to identify craters with high precision and accuracy on the Moon. The results meet requirements for supporting exploration and related scientific research for the Moon and planets.

A universal spectral analytical method for digital terrain modeling

ABSTRACTThere are three major mathematical problems in digital terrain analysis: (1) interpolation of digital elevation models (DEMs); (2) DEM generalization and denoising; and (3) computation of morphometric variables through calculating partial derivatives of elevation. Traditionally, these three problems are solved separately by means of procedures implemented in different methods and algorithms. In this article, we present a universal spectral analytical method based on high-order orthogonal expansions using the Chebyshev polynomials of the first kind with the subsequent Fejér summation. The method is intended for the processing of regularly spaced DEMs within a single framework including DEM global approximation, denoising, generalization, as well as calculating the partial derivatives of elevation and local morphometric variables.The method is exemplified by a portion of the Great Rift Valley and central Kenyan highlands. A DEM of this territory (the matrix 480 × 481 with a grid spacing of 30″) was extracted from the global DEM SRTM30_PLUS. We evaluated various sets of expansion coefficients (up to 7000) to approximate and reconstruct DEMs with and without the Fejér summation. Digital models of horizontal and vertical curvatures were computed using the first and second partial derivatives of elevation derived from the reconstructed DEMs. To evaluate the approximation accuracy, digital models of residuals (differences between the reconstructed DEMs and the initial one) were calculated. The test results demonstrated that the method is characterized by a good performance (i.e., a distinct monotonic convergence of the approximation) and a high speed of data processing. The method can become an effective alternative to common techniques of DEM processing.

Watershed delineation using hydrographic features and a DEM in plain river network region

Watershed delineation is a required step when conducting any spatially distributed hydrological modelling. Automated approaches are often proposed to delineate a watershed based on a river network extracted from the digital elevation model (DEM) using the deterministic eight-neighbour (D8) method. However, a realistic river network cannot be derived from conventional DEM processing methods for a large flat area with a complex network of rivers, lakes, reservoirs, and polders, referred to as a plain river network region (PRNR). In this study, a new approach, which uses both hydrographic features and DEM, has been developed to address the problems of watershed delineation in PRNR. It extracts the river nodes and determines the flow directions of the river network based on a vector-based hydrographic feature data model. The river network, lakes, reservoirs, and polders are then used to modify the flow directions of grid cells determined by D8 approach. The watershed is eventually delineated into four types of catchments including lakes, reservoirs, polders, and overland catchments based on the flow direction matrix and the location of river nodes. Multiple flow directions of grid cells are represented using a multi-direction encoding method, and multiple outflows of catchments are also reflected in the topology of catchments. The proposed approach is applied to the western Taihu watershed in China. Comparisons between the results obtained from the D8 approach, the ‘stream burning’ approach, and those from the proposed approach clearly demonstrate an improvement of the new approach over the conventional approaches. This approach will benefit the development of distributed hydrological models in PRNR for the consideration of different types and multiple inlets and outlets of catchments. Copyright © 2015 John Wiley & Sons, Ltd.

Analysis of a complex tectonic scenario based on 2D discrete wavelet analysis

Processing of digital elevation models is a hot issue for identifying tectonics features of an area. Medium resolution digital elevation models are interesting for analyzing topographic anomalies that may be related to regional phenomena, like ongoing or past tectonic processes. In order to perform this, the identification of these features from elevation models is the key issue. An effective approach is 2D discrete wavelet transforms. These perform a multi-scale decomposition, capable of giving numerically based evidence to details from digital elevation models, which sometimes may be concealed or unclear. These details can be associated to anomalies or singularities of the topography, possibly related to regional tectonic processes or, more in general, to landscape evolution phenomena, i.e. big landslides, erosion, etc.. Thus this can be an effective approach to territorial analysis.

RADAR INTERFEROMETRY APPLICATION FOR DIGITAL ELEVATION MODEL IN MOUNT BROMO, INDONESIA

This paper reviewed the result and processing of digital elevation model (DEM) using L-Band ALOS PALSAR data and two-pass radar interferometry method in Bromo Mountain region. Synthetic Aperture Radar is an advanced technology that has been used to monitor deformation, land cover change, image detection and especially topographic information such as DEM. We used two scenes of SAR imageries to generate DEM extraction which assumed there is no deformation effect between two acquisitions. We could derive topographic information using phase difference by combining two single looks complex (SLC) images called focusing process. The next steps were doing interferogram generation, phase unwrapping and geocoding. DEM-InSAR was compared to SRTM 90m that there were significant elevation differences between two DEMs such as smoothing surface and detail topographic. Particularly for hilly areas, DEM-InSAR showed better quality than SRTM 90 m where the elevation could have 25.94 m maximum gap. Although the processing involved adaptive filter to amplify the phase signal, we concluded that InSAR DEM result still had error noise because of signal wavelength, incidence angle, SAR image relationship, and only using ascending orbit direction.

Assessment of Potential Dam Sites in the Kabul River Basin Using GIS

The research focuses on Kabul River Basin (KRB) water resources infrastructure, management and development as there are many dams already in the basin and many dams are planned and are being studied with multi-purposes objectives such as power generation, irrigation and providing water to industry and domestics. KB has been centralized all water resources related information in an integrated relational geo-database this KB is centralized repository for information river basin management with the main objectives of optimizing information collection, retrieval and organization. In addition, in this paper information and characteristics of the KRB has been presented such as drainage network or hydrology, irrigation, population, climate and surface pattern other necessary features of the basin by the use of GIS in order to invest and implement infrastracture projects. The first step in doing any kind of hydrologic modeling involves delineating streams and watersheds, and getting some basic watershed properties such as area, slope, flow length, stream network density, etc. Traditionally this was (and still is) being done manually by using topographic/contour maps. With the availability of Digital Elevation Models (DEM) and GIS tools, watershed properties can be extracted by using automated procedures. The processing of DEM to delineate watersheds is referred to as terrain pre-processing. Besides that, it produced the necessary thematic maps, base maps and other detailed maps for illustrating of basin characteristics and features GIS Based.

Multi-Scale DEM Generalization Processing in Different Landform Areas

As a special kind of image, the grid-based digital elevation model (DEM) is directly related with the landform and topography feature. In the real word, there are various landforms, and the results of different methods for DEM processing vary greatly. However, the discussion of using different methods in different landform areas in DEM generalization is needed. Numerous methods have been proposed previously for DEM generalization without taking topographic factors into consideration, and the setting of threshold value of most algorithms is very subjective. Therefore, we investigate the DEM generalization, using two methods (z-tolerance method and compound method) in different landform areas and propose a new way for threshold values setting in generalization. The results show that the method we proposed is feasible and the compound method offers a better performance over z-tolerance method in most conditions, especially when comparing their performances of keeping streamline shape.