Name
Title | ||
|---|---|---|
Polarimetric Information for Multi-Frequency SAR Classification of Heterogeneous Coastal Regions. |
Abstract | ||
|---|---|---|
In this study, polarimetric synthetic aperture radar (PoISAR)-based classification algorithms are considered to investigate the role played by polarimetric information in the classification process of coastal areas that call for heterogeneous scattering properties. Hence, a multi-frequency PolSAR dataset collected over the study area of the Yellow River delta (China) is exploited to point out benefits and limitations that characterize well-known unsupervised classification schemes. Experimental results show the potential and the drawbacks of the exploitation of multi-frequency and multi-polarization SAR measurements for challenging coastal area classification |
Year | Venue | Field |
|---|---|---|
2018 | IGARSS | River delta,Polarimetry,Computer science,Synthetic aperture radar,Remote sensing,Classification scheme,Polarimetric synthetic aperture radar,Statistical classification |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Del Buono | 1 | 21 | 8.09 |
| Ferdinando Nunziata | 2 | 215 | 41.25 |
| Maurizio Migliaccio | 3 | 467 | 82.94 |
| Xiaofeng Yang | 4 | 16 | 13.28 |
| Xiaofeng Li | 5 | 336 | 79.94 |