Name
Abstract | ||
|---|---|---|
Multispectral airborne laser scanning (ALS) data have recently become available. The objective of this letter is to study the feasibility of these data for road mapping-for road detection and road surface classification. The results are compared with the results of traditional aerial ortho images using object-based image analysis and Random Forest classification. The results demonstrate that the m... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LGRS.2016.2631261 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Roads,Artificial intelligence,Radio frequency,Lasers,Training,Surface topography,Shape | Computer vision,Laser scanning,Multispectral image,Remote sensing,Road surface,Multispectral pattern recognition,Artificial intelligence,Random forest,Aerial imagery,Road mapping,Mathematics | Journal |
Volume | Issue | ISSN |
14 | 3 | 1545-598X |
Citations | PageRank | References |
3 | 0.43 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kirsi Karila | 1 | 33 | 3.68 |
| L. Matikainen | 2 | 66 | 6.13 |
| Eetu Puttonen | 3 | 97 | 14.85 |
| Juha Hyyppä | 4 | 439 | 66.75 |