Name
Title | ||
|---|---|---|
Investigation into Different Polarimetric Features for Sea Ice Classification Using X-Band Synthetic Aperture Radar. |
Abstract | ||
|---|---|---|
Satellite-borne synthetic aperture radar has proven to be a valuable tool for sea ice monitoring for more than two decades. In this study, we examine the performance of an automated sea ice classification algorithm based on polarimetric TerraSAR-X images. In the first step of our approach, we extract 12 polarimetric features from HH-VV dualpol StripMap images. In a second step, we train an artific... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/JSTARS.2016.2539501 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Sea ice,Synthetic aperture radar,Neural networks,Sea measurements,Marine vehicles,Ice thickness | Computer vision,Feature vector,Radar imaging,Polarimetry,Interferometric synthetic aperture radar,Synthetic aperture radar,Remote sensing,Inverse synthetic aperture radar,Artificial intelligence,Pixel,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
9 | 7 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ressel, R. | 1 | 12 | 3.43 |
| Singha, S. | 2 | 19 | 4.57 |
| Susanne Lehner | 3 | 116 | 15.23 |
| Anja Rösel | 4 | 5 | 2.13 |
| Gunnar Spreen | 5 | 2 | 3.13 |