assessment of accuracy in the identification of rock formations from aerial and terrestrial laser-scanning data
Clicks: 207
ID: 188047
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
30.4
/100
207 views
26 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #55 of 94 articles by views in población y desarrollo
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Rock formations are among the most spectacular landscape features both for experts and the public. However, information about these objects is often stored inaccurately in existing spatial databases, their corresponding elevations are missing, or the entire rock object is completely absent. Cartographic depiction is also reduced to a point of areal symbology of a largely generalized character. This paper discusses options in identifying and analyzing rock formations from two digital terrain models (DTMs), DMR 5G and DMR 5G+, and irregularly spaced points of airborne laser-scanning (ALS) data with different point densities. A semi-automatic method allowing rock formations to be identified from DTMs is introduced at the beginning of the paper. A method to evaluate elevation models (volume differences) is subsequently applied and a 3D model of a selected rock object is created from terrestrial laser-scanning data. Finally, positional and volumetric comparisons of that 3D object are performed in 2D, 2.5D, and 3D. The results of the pilot study confirmed that the digital terrain models studied are a reliable source in identifying and updating rock formations using the semi-automatic method introduced. The results show that DMR 5G model quality decreases with increasing fragmentation and relative rock formation height, while the proportion of gross errors increases. The complementary DMR 5G+ is better in terms of location and altitude.
| Reference Key |
paleek2018isprsassessment
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Václav Paleček;Petr Kubíček |
| Journal | población y desarrollo |
| Year | 2018 |
| DOI |
10.3390/ijgi7040142
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.