scholarly journals Peer Review #1 of "Comparative investigation of parallel spatial interpolation algorithms for building large-scale digital elevation models (v0.1)"

2020 ◽  
Keyword(s):  
Peer Review ◽  
Spatial Interpolation ◽  
Large Scale ◽  
Digital Elevation Models ◽  
Comparative Investigation ◽  
Interpolation Algorithms ◽  
Digital Elevation

scholarly journals Comparative investigation of parallel spatial interpolation algorithms for building large-scale digital elevation models

2020 ◽  
Vol 6 ◽  
pp. e263 ◽  
Author(s):  
Jingzhi Tu ◽  
Guoxiang Yang ◽  
Pian Qi ◽  
Zengyu Ding ◽  
Gang Mei
Keyword(s):  
Computational Efficiency ◽  
Large Scale ◽  
Information Science ◽  
Digital Elevation Models ◽  
Least Square ◽  
Interpolation Algorithm ◽  
Moving Least Square ◽  
Interpolation Algorithms ◽  
Interpolation Accuracy ◽  
Digital Elevation

The building of large-scale Digital Elevation Models (DEMs) using various interpolation algorithms is one of the key issues in geographic information science. Different choices of interpolation algorithms may trigger significant differences in interpolation accuracy and computational efficiency, and a proper interpolation algorithm needs to be carefully used based on the specific characteristics of the scene of interpolation. In this paper, we comparatively investigate the performance of parallel Radial Basis Function (RBF)-based, Moving Least Square (MLS)-based, and Shepard’s interpolation algorithms for building DEMs by evaluating the influence of terrain type, raw data density, and distribution patterns on the interpolation accuracy and computational efficiency. The drawn conclusions may help select a suitable interpolation algorithm in a specific scene to build large-scale DEMs.

scholarly journals Identification of Micro-Scale Landforms of Landslides Using Precise Digital Elevation Models

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 117 ◽  
Author(s):  
František Chudý ◽  
Martina Slámová ◽  
Julián Tomaštík ◽  
Roberta Prokešová ◽  
Martin Mokroš
Keyword(s):  
Large Scale ◽  
Forest Canopy ◽  
Digital Elevation Models ◽  
Canopy Cover ◽  
Point Clouds ◽  
Tree Canopy ◽  
Automatic Identification ◽  
Optical Parameters ◽  
Micro Scale ◽  
Digital Elevation

An active gully-related landslide system is located in a deep valley under forest canopy cover. Generally, point clouds from forested areas have a lack of data connectivity, and optical parameters of scanning cameras lead to different densities of point clouds. Data noise or systematic errors (missing data) make the automatic identification of landforms under tree canopy problematic or impossible. We processed, analyzed, and interpreted data from a large-scale landslide survey, which were acquired by the light detection and ranging (LiDAR) technology, remotely piloted aircraft system (RPAS), and close-range photogrammetry (CRP) using the ‘Structure-from-Motion’ (SfM) method. LAStools is a highly efficient Geographic Information System (GIS) tool for point clouds pre-processing and creating precise digital elevation models (DEMs). The main landslide body and its landforms indicating the landslide activity were detected and delineated in DEM-derivatives. Identification of micro-scale landforms in precise DEMs at large scales allow the monitoring and the assessment of these active parts of landslides that are invisible in digital terrain models at smaller scales (obtained from aerial LiDAR or from RPAS) due to insufficient data density or the presence of many data gaps.

scholarly journals Improvements in large-scale drainage networks derived from digital elevation models

2006 ◽  
Vol 42 (8) ◽  
Author(s):  
Adriano Rolim Paz ◽  
Walter Collischonn ◽  
André Luiz Lopes da Silveira
Keyword(s):  
Large Scale ◽  
Digital Elevation Models ◽  
Drainage Networks ◽  
Digital Elevation

scholarly journals EVALUATION OF DIGITAL ELEVATION MODELS FOR GEOMORPHOMETRIC ANALYSES ON DIFFERENT SCALES FOR NORTHERN CHILE

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1229-1235 ◽  
Author(s):  
T. Kramm ◽  
D. Hoffmeister
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Large Scale ◽  
Thermal Emission ◽  
Digital Elevation Models ◽  
Regional Scale ◽  
Laser Altimeter ◽  
Absolute Deviation ◽  
Digital Elevation ◽  
Very High

<p><strong>Abstract.</strong> The resolution and accuracy of digital elevation models (DEMs) have direct influence on further geoscientific computations like landform classifications and hydrologic modelling results. Thus, it is crucial to analyse the accuracy of DEMs to select the most suitable elevation model regarding aim, accuracy and scale of the study. Nowadays several worldwide DEMs are available, as well as DEMs covering regional or local extents. In this study a variety of globally available elevation models were evaluated for an area of about 190,000&amp;thinsp;km<sup>2</sup>. Data from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30&amp;thinsp;m and 90&amp;thinsp;m, Advanced Land Observing Satellite (ALOS) World 3D 30&amp;thinsp;m and TanDEM-X WorldDEM&amp;trade; &amp;ndash; 12&amp;thinsp;m and 90&amp;thinsp;m resolution were obtained. Additionally, several very high resolution DEM data were derived from stereo satellite imagery from SPOT 6/7 and Pléiades for smaller areas of about 100&amp;ndash;400&amp;thinsp;km<sup>2</sup> for each dataset. All datasets were evaluated with height points of the Geoscience Laser Altimeter System (GLAS) instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite on a regional scale and with nine very high resolution elevation models from UAV-based photogrammetry on a very large scale. For all datasets the root mean square error (RMSE) and normalized median absolute deviation (NMAD) was calculated. Furthermore, the association of errors to specific terrain was conducted by assigning these errors to landforms from the topographic position index (TPI), topographic roughness index (TRI) and slope. For all datasets with a global availability the results show the highest overall accuracies for the TanDEM-X 12&amp;thinsp;m (RMSE: 2.3&amp;thinsp;m, NMAD: 0.8&amp;thinsp;m). The lowest accuracies were detected for the 30&amp;thinsp;m ASTER GDEM v3 (RMSE: 8.9&amp;thinsp;m, NMAD: 7.1&amp;thinsp;m). Depending on the landscape the accuracies are higher for all DEMs in flat landscapes and the errors rise significantly in rougher terrain. Local scale DEMs derived from stereo satellite imagery show a varying overall accuracy, mainly depending on the topography covered by the scene.</p>

Provincial large-scale topographic mapping

CISM journal ◽  
1989 ◽  
Vol 43 (1) ◽  
pp. 39-53 ◽  
Author(s):  
L.M. Sebert
Keyword(s):  
Large Scale ◽  
Digital Elevation Models ◽  
Topographic Mapping ◽  
Digital Cartography ◽  
Digital Elevation ◽  
Almost All

In 1977 the Surveys and Mapping Branch in Ottawa discontinued production of the 1:25 000 Series, which was the largest-scale mapping of the National Topographic System. Since that year all provinces except Manitoba and Saskatchewan have entered the large-scale mapping field by producing topographic series at scales from 1:10 000 to 1:20 000 inclusive. By October, 1988, this work covered a total of over 1 200 000 square km. Today this mapping continues with almost all being compiled by digital cartography. In many cases the contours are being derived from Digital Elevation Models. The cartographic styles developed by the various provinces, and the amount of mapping that has been done in each province, are recorded in this paper.

Sign in / Sign up

Export Citation Format

Share Document