scholarly journals Evaluation of the Data Quality of Digital Elevation Models in the Context of Inspire / Hodnotenie Kvality Digitálnych Výškových Modelov V Kontexte Inspire

2013 ◽  
Vol 59 (2) ◽  
pp. 9-24 ◽  
Keyword(s):  
Data Quality ◽  
Quality Assessment ◽  
Digital Elevation Model ◽  
Slovak Republic ◽  
Digital Elevation Models ◽  
Geographic Information ◽  
Digital Elevation ◽  
The Family ◽  
Elevation Model

Abstract The contribution deals with the evaluation of the quality of geographic information in accordance with the ISO standards from the family of ISO 19100. The quality assessment was carried out on a sample of the data of the digital elevation model of the Slovak republic - DMR3. The selected data quality elements and sub-elements were evaluated using measures defined in the INSPIRE data specification for Elevation.

scholarly journals EVALUATION DIGITAL ELEVATION MODEL GENERATED BY SYNTHETIC APERTURE RADAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 57-62
Author(s):  
H. B. Makineci ◽  
H. Karabörk
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
European Space Agency ◽  
Mountain Area ◽  
Synthetic Aperture Radar Data ◽  
Radar Images ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. <br><br> One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. <br><br> It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

scholarly journals Digital Elevation Model Quality Assessment Methods: A Critical Review

2020 ◽  
Vol 12 (21) ◽  
pp. 3522
Author(s):  
Laurent Polidori ◽  
Mhamad El Hage
Keyword(s):  
Quality Assessment ◽  
Assessment Methods ◽  
Internal Quality ◽  
Surface Model ◽  
Model Quality ◽  
Topographic Features ◽  
Digital Elevation ◽  
Elevation Model ◽  
User Perspectives

Digital elevation models (DEMs) are widely used in geoscience. The quality of a DEM is a primary requirement for many applications and is affected during the different processing steps, from the collection of elevations to the interpolation implemented for resampling, and it is locally influenced by the landcover and the terrain slope. The quality must meet the user’s requirements, which only make sense if the nominal terrain and the relevant resolution have been explicitly specified. The aim of this article is to review the main quality assessment methods, which may be separated into two approaches, namely, with or without reference data, called external and internal quality assessment, respectively. The errors and artifacts are described. The methods to detect and quantify them are reviewed and discussed. Different product levels are considered, i.e., from point cloud to grid surface model and to derived topographic features, as well as the case of global DEMs. Finally, the issue of DEM quality is considered from the producer and user perspectives.

scholarly journals Digital elevation model validation with no ground control: application to the topodata dem in Brazil

2014 ◽  
Vol 20 (2) ◽  
pp. 467-479 ◽  
Author(s):  
Laurent Polidori ◽  
Mhamad El Hage ◽  
Márcio De Morisson Valeriano
Keyword(s):  
Digital Elevation Model ◽  
Visual Analysis ◽  
Ground Control ◽  
Ground Control Points ◽  
Geostatistical Approach ◽  
Digital Elevation ◽  
Elevation Model ◽  
Control Application ◽  
Statistical Indicators

Digital Elevation Model (DEM) validation is often carried out by comparing the data with a set of ground control points. However, the quality of a DEM can also be considered in terms of shape realism. Beyond visual analysis, it can be verified that physical and statistical properties of the terrestrial relief are fulfilled. This approach is applied to an extract of Topodata, a DEM obtained by resampling the SRTM DEM over the Brazilian territory with a geostatistical approach. Several statistical indicators are computed, and they show that the quality of Topodata in terms of shape rendering is improved with regards to SRTM.

Pemetaan Bahaya Tsunami Wilayah Kabupaten Serang Bagian Barat Menggunakan Sistem Informasi Geografis

2021 ◽  
Vol 10 (3) ◽  
pp. 233-241
Author(s):  
Padma Paramita ◽  
Sesa Wiguna ◽  
Fathia Zulfati Shabrina ◽  
Aida Sartimbul
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Digital Elevation Model ◽  
Accurate Method ◽  
Geographic Information ◽  
Tsunami Hazard ◽  
Disaster Mitigation ◽  
Hazard Map ◽  
Digital Elevation ◽  
Elevation Model

Indonesia merupakan negara yang memiliki potensi tinggi akan kejadian tsunami. Salah satu wilayah tersebut adalah Kabupaten Serang bagian barat. Saat ini evolusi teknologi penginderaan jauh dan Sistem Informasi Geografis (SIG) dapat dimanfaatkan untuk membantu upaya mitigasi. Tujuan penelitian ini adalah untuk menganalisis potensi tsunami dan menyediakan peta bahaya tsunami sebagai salah satu upaya mitigasi bencana berbasis Sistem Informasi Geografis (SIG) berdasarkan panduan dari Badan Nasional Penanggulangan Bencana (BNPB). Metode yang digunakan dalam penelitian ini adalah metode matematis yang dikembangkan oleh Berryman-2006. Metode ini merupakan metode yang sederhana namun cukup akurat dalam memperkirakan daerah yang berpotensi terdampak tsunami. Data Digital Elevation Model (DEM) dan shapefile rupa bumi yang bersumber dari Badan Informasi Geospasial (BIG) Indonesia merupakan data utama yang digunakan. Hasil analisis menunjukkan bahwa potensi bahaya tsunami di Kabupaten Serang bagian barat terdiri dari 3 kelas yaitu kelas rendah, sedang, dan tinggi yang didominasi oleh kelas bahaya tinggi dengan total luas area terdampak sebesar 377,64 ha. Peta bahaya tsunami ini selanjutnya dapat dijadikan sebagai salah satu basis informasi dalam perencanaan mitigasi bencana di Kabupaten Serang.  Indonesia is a country that has a high potential for tsunami events. One of these areas is the western part of Serang Regency. Currently, the evolution of remote sensing technology and Geographic Information Systems (GIS) can be utilized to assist mitigation efforts. The purpose of this study is to analyze the potential for tsunamis and provide a tsunami hazard map as one of the efforts to mitigate disasters based on Geographic Information Systems (GIS) based on guidelines from the National Disaster Management Agency (BNPB). The method used in this research is a mathematical method developed by Berryman-2006. This method is a simple but fairly accurate method for estimating areas potentially affected by a tsunami. Digital Elevation Model (DEM) data and the shapefile of the earth's appearance sourced from the Indonesian Geospatial Information Agency (BIG) are the main data used. The results of the analysis show that the potential tsunami hazard in the western part of Serang Regency consists of 3 classes, namely low, medium, and high classes which are dominated by high hazard classes with a total area of 377.64 ha affected. This tsunami hazard map can then be used as one of the information bases in disaster mitigation planning in Serang Regency.

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