Calculating the prominence and isolation of every mountain in the world

2017 ◽  
Vol 41 (6) ◽  
pp. 788-802 ◽  
Author(s):  
Andrew Kirmse ◽  
Jonathan de Ferranti
Keyword(s):  
Digital Elevation Model ◽  
Global Scale ◽  
Digital Elevation ◽  
The World ◽  
Elevation Data ◽  
Elevation Model

A global-scale calculation identifies peaks in a digital elevation model (DEM) and computes their isolation and topographic prominence. A new DEM is presented that covers the entire globe at 90 meter resolution with no substantial voids or artifacts. All peaks with at least 1 kilometer of isolation are found, and the closest higher ground is identified. For prominence, all peaks with at least ∼30 meters are found, and the key saddle is identified. The prominence algorithm uses results from Morse–Smale topology to run in parallel on standard, freely available elevation data. Thirteen previously unknown “ultra-prominent” mountains with at least 1500 meters of prominence are listed.

scholarly journals Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions

2021 ◽  
Author(s):  
Shizhou Ma ◽  
Karen Beazley ◽  
Patrick Nussey ◽  
Chris Greene
Keyword(s):  
High Resolution ◽  
Digital Elevation Model ◽  
Smoothing Algorithm ◽  
Processing Efficiency ◽  
Spatial Approach ◽  
Digital Elevation ◽  
Elevation Data ◽  
Computer Based ◽  
Lidar Dem ◽  
Elevation Model

Abstract The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.

scholarly journals CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

2017 ◽  
Vol IV-4/W4 ◽  
pp. 203-207 ◽  
Author(s):  
A. İ. Durmaz
Keyword(s):  
Mobile Devices ◽  
Digital Elevation Model ◽  
Mobile Device ◽  
Point Clouds ◽  
Lidar Data ◽  
Government Agencies ◽  
Gps Data ◽  
Digital Elevation ◽  
The World ◽  
Elevation Model

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

scholarly journals Automated Conflation of Digital Elevation Model with Reference Hydrographic Lines

2020 ◽  
Vol 9 (5) ◽  
pp. 334
Author(s):  
Timofey E. Samsonov
Keyword(s):  
Spatial Analysis ◽  
Digital Elevation Model ◽  
Spatial Data ◽  
Drainage Network ◽  
Map Generalization ◽  
Data Types ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model ◽  
Different Sources

Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and mapping, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation.

scholarly journals DEMNAS: MODEL DIGITAL KETINGGIAN NASIONAL UNTUK APLIKASI KEPESISIRAN

OSEANA ◽  
2018 ◽  
Vol 43 (4) ◽  
Author(s):  
Marindah Yulia Iswari ◽  
Kasih Anggraini
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Digital Data ◽  
Coastal Hazards ◽  
Remote Sensing Images ◽  
Geospatial Information ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

DEMNAS : NATIONAL DIGITAL ELEVATION MODEL FOR COASTAL APPLICATION. DEM is a digital data which contain information about elevation. In Indonesia, DEM can be generated from elevation points or contours in RBI (Rupabumi Indonesia). DEM can be performed to research of coastal application i.e. inundation or tsunami. DEM can help to analyze vulnerability or evacuation zone for coastal hazards. DEMNAS is one product of BIG (Geospatial Information Agency) which consist of elevation data from remote sensing images. DEMNAS data has not been widely used and is still being developed but DEMNAS has an advantage of spatial resolution. DEMNAS has spatial resolution 0.27 arc-second, which is bigger than the spatial resolution of global DEM.

scholarly journals HydroSHEDS v2.0 – Refined global river network and catchment delineations from TanDEM-X elevation data

2021 ◽  
Author(s):  
Bernhard Lehner ◽  
Achim Roth ◽  
Martin Huber ◽  
Mira Anand ◽  
Günther Grill ◽  
...  
Keyword(s):  
High Resolution ◽  
Digital Elevation Model ◽  
Multiple Scales ◽  
Environmental Conservation ◽  
The Arctic ◽  
River Networks ◽  
Northern Latitude ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

<p>Since its introduction in 2008, the HydroSHEDS database (www.hydrosheds.org) has transformed large-scale hydro-ecological research and applications worldwide by offering standardized spatial units for hydrological assessments. At its core, HydroSHEDS provides digital hydrographic information that can be applied in Geographic Information Software (GIS) or hydrological models to delineate river networks and catchment boundaries at multiple scales, from local to global. Its various data layers form the basis for applications in a wide range of disciplines including environmental, conservation, socioeconomic, human health, and sustainability studies.</p><p>Version 1 of HydroSHEDS was derived from the digital elevation model of the Shuttle Radar Topography Mission (SRTM) at a pixel resolution of 3 arc-seconds (~90 meters at the equator). It was created using customized processing and optimization algorithms and a high degree of manual quality control. Results are available at varying resolutions, ranging from 3 arc-seconds (~90 m) to 5 minutes (~10 km), and in nested sub-basin structures, making the data uniquely suitable for applications at multiple scales. A suite of related data collections and value-added information, foremost the HydroATLAS compilation of over 50 hydro-environmental attributes for every river reach and sub-basin, continuously enhance the versatility of the HydroSHEDS family of products. Yet version 1 of HydroSHEDS shows some important limitations. In particular, coverage above 60° northern latitude (i.e., largely the Arctic) is missing for the 3 arc-second product and is of low quality for coarser products because no SRTM elevation data are available for this region. Also, some areas are affected by inherent data gaps or other errors that could not be fully resolved at the time of creating version 1 of HydroSHEDS.</p><p>Today, the TanDEM-X dataset (TerraSAR-X add-on for Digital Elevation Measurement), created in partnership between the German Aerospace Agency (DLR) and Airbus, offers a new digital elevation model covering the entire global land surface including northern latitudes. In a collaborative project, this dataset is used to extract HydroSHEDS v2.0, following the same basic specifications as version 1. DLR is processing the original 12 m resolution TanDEM-X data to create a hydrologically pre-conditioned version at 3 arc-second resolution. In this step, corrections with high-resolution vegetation and settlement maps are applied to reduce distortions caused by vegetation cover and in built-up areas. Following this preprocessing, refined hydrological optimization and correction algorithms are used to derive the drainage pathways, including improved ‘stream-burning’ techniques that incorporate recent data products such as high-resolution terrestrial open water masks and improved tracing of drainage pathways as center lines in global lake and river maps. The resulting HydroSHEDS v2.0 database will provide river networks and catchment boundaries at full global coverage. Release of the data under a free license is scheduled for 2022, with regions above 60° northern latitude being completed first in 2021.</p>

scholarly journals Synergetic merging of Cartosat-1 and RAMP to generate improved digital elevation model of Schirmacher oasis, east Antarctica

2014 ◽  
Vol XL-8 ◽  
pp. 517-524 ◽  
Author(s):  
S. D. Jawak ◽  
A. J. Luis
Keyword(s):  
Digital Elevation Model ◽  
Accuracy Assessment ◽  
East Antarctica ◽  
Interpolation Methods ◽  
Digital Elevation ◽  
Schirmacher Oasis ◽  
Elevation Data ◽  
Interpolation Techniques ◽  
Elevation Model ◽  
Better Than

Available digital elevation models (DEMs) of Antarctic region generated by using radar altimetry and the Antarctic digital database (ADD) indicate elevation variations of up to hundreds of meters, which necessitates the generation of local DEM and its validation by using ground reference. An enhanced digital elevation model (eDEM) of the Schirmacher oasis region, east Antarctica, is generated synergistically by using Cartosat-1 stereo pair-derived photogrammetric DEM (CartoDEM)-based point elevation dataset and multitemporal radarsat Antarctic mapping project version 2 (RAMPv2) DEM-based point elevation dataset. In this study, we analyzed suite of interpolation techniques for constructing a DEM from RAMPv2 and CartoDEM-based point elevation datasets, in order to determine the level of confidence with which the interpolation techniques can generate a better interpolated continuous surface, and eventually improves the elevation accuracy of DEM from synergistically fused RAMPv2 and CartoDEM point elevation datasets. RAMPv2 points and CartoDEM points were used as primary data for various interpolation techniques such as ordinary kriging (OK), simple kriging (SK), universal kriging (UK), disjunctive kriging (DK) techniques, inverse distance weighted (IDW), global polynomial (GP) with power 1 and 2, local polynomial (LP) and radial basis functions (RBF). Cokriging of 2 variables with second dataset was used for ordinary cokriging (OCoK), simple cokriging (SCoK), universal cokriging (UCoK) and disjunctive cokriging (DCoK). The IDW, GP, LP, RBF, and kriging methods were applied to one variable, while Cokriging experiments were employed on two variables. The experiment of dataset and its combination produced two types of point elevation map categorized as (1) one variable (RAMPv2 Point maps and CartoDEM Point maps) and (2) two variables (RAMPv2 Point maps + CartoDEM Point maps). Interpolated surfaces were evaluated with the help of differential global positioning system (DGPS) points collected from study area during the Indian Scientific Expedition to Antarctic (ISEA). Accuracy assessment of the RAMPv2 DEM, CartoDEM, and combined eDEM (RAMPv2 + CartoDEM) by using DGPS as ground reference data shows that eDEM achieves much better accuracy (average elevation error 8.44 m) than that of existing DEM constructed by using only CartoDEM (13.57 m) or RAMPv2 (41.44 m) alone. The newly constructed eDEM achieves a vertical accuracy of about 7 times better than RAMPv2 DEM and 1.5 times better than CartoDEM. After using accurate DGPS data for accuracy assessment, the approximation to the actual surface of the eDEM extracted here is much more accurate with least mean root mean square error (RMSE) of 9.22 m than that constructed by using only CartoDEM (RMSE = 14.15 m) point elevation data and RAMPv2 (RMSE = 69.48 m) point elevation data. Our results indicate that, the overall trend of accuracy for the interpolation methods for generating continuous elevation surface from CartoDEM + RAMPv2 point elevation data, based on RMSE, is as follows: GP1 > IDW > GP2 > OK > LP2 > DK > LP1 > RBF > SK > UK. In case of cokriging interpolation methods, OCoK yields more accurate eDEM with the least RMSE of 8.16 m, which can be utilized to generate a highly accurate DEM of the research area.. Based on this work, it is inferred that GP2 and OCok interpolation methods and synergistic use of RAMPv2 and CartoDEM-based point elevation datasets lead to a highly accurate DEM of the study region. This research experiment demonstrates the stability (w.r.t multi-temporal datasets), performance (w.r.t best interpolation technique) and consistency (w.r.t all the experimented interpolation techniques) of synergistically fused eDEM. On the basis of average elevation difference and RMSE mentioned in present research, the newly constructed eDEM may serve as a benchmark for future elevation models such as from the ICESAT-II mission to spatially monitor ice sheet elevation.

Merging of airborne elevation data and Radarsat data to develop a Digital Elevation Model

2005 ◽  
Vol 26 (1) ◽  
pp. 141-166 ◽  
Author(s):  
N. Baghdadi ◽  
S. Cavelier ◽  
J.‐P. Chiles ◽  
B. Bourgine ◽  
Th. Toutin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Digital Elevation ◽  
Elevation Data ◽  
Elevation Model

scholarly journals The draa Cerro Medanoso (Atacama, Chile) and its importance in the study of desert

2016 ◽  
pp. 25
Author(s):  
José F. Araya Vergara ◽  
Ricardo Vilaró
Keyword(s):  
Digital Elevation Model ◽  
Satellite Imagery ◽  
Morphological Analysis ◽  
Aerial Photos ◽  
Desert Pavement ◽  
Aster Gdem ◽  
Digital Elevation ◽  
The World ◽  
Long Time ◽  
Elevation Model

This work presents a morphological analysis of the Cerro Medanoso draa (Atacama Marginal Desert) and the type of contact with the desert pavements of neighboring glacis and piedmont. This study is based on an analysis of aerial photos, and a digital elevation model. Aster GDEM was used as a basis for the survey. Fieldwork observations covered two principal zones: the nucleus and the envelope. Following fieldwork, analysis of satellite imagery was conducted. It was possible to identify the following phases of formation: construction of a stellate nucleus, merging of the eastern envelope, merging of the southern envelope and merging of a complex western envelope. The southeastern facing envelope is much bigger than the northwestern facing one. Consequently, the construction of the complex draa is asymmetric. The correlation of this megadune with similar star and compound draas to other deserts in the world indicates that the closest analogue exists in Namibia, but without merging signals between the envelope and the nucleus. Star draas observed in other deserts exhibit a lack of this envelope. With reference to the neighboring piedmont, the beginning of its deflation must be necessarily correlative to the initial construction of the nuclear twin star draa. The later deflation could be responsible for the pulses, which formed the envelope. Therefore, the neighboring desert pavement and the draa are correlative landforms, which represent a very long time formation, in an important part of the desert history, as evidenced by the cited and referenced research works.

scholarly journals On the Vertical Accuracy of the ALOS World 3D-30m Digital Elevation Model

2017 ◽  
Author(s):  
Çaglar Bayık ◽  
Kazimierz Becek ◽  
Çetin Mekik ◽  
Mustafa Özendi
Keyword(s):  
Digital Elevation Model ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Reference Dataset ◽  
Digital Elevation ◽  
The World ◽  
Vertical Accuracy ◽  
Longitudinal Profiles ◽  
Elevation Model ◽  
Resolution Data

The digital elevation model (DEM) is one of the key geospatial datasets used in many fields of engineering and science for countless applications. In this contribution, we assess the vertical accuracy of the Advanced Land Observing Satellite (ALOS) World 3D-30m (AW3D30) DEM using the runway method (RWYM). The RWYM utilizes the longitudinal profiles of runways which are reliable and ubiquitous reference data. A reference dataset used in this project consists of 36 runways located at various points throughout the world. The same dataset was previously used to test the accuracy of WorldDEMTM.  Our study indicates that AW3D30 has a remarkably high RMSE of 1.78 m (one σ). However, while analyzing the results, it has become apparent that it also contains a widespread elevation anomaly. We conclude that this anomaly is the result of uncompensated sensor noise and the data processing algorithm (downsampling of the higher resolution data). We believe that this issue should be communicated to the user community. Also, we would like to note that the traditional accuracy assessment of a DEM, e.g., statistical assessment of the elevation differences = model – reference, does not allow for identification of these type of anomalies in a DEM.

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