| Titre | Polarization signature analysis of paddy rice in southern China |
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| Auteur | Li, K; Zhang, F; Shao, Y ; Cai, A; Yuan, J; Touzi, R |
| Source | Canadian Journal of Remote Sensing vol. 37, no. 1, 2011 p. 122-135, https://doi.org/10.5589/m11-018 |
| Année | 2011 |
| Séries alt. | Ressources naturelles Canada, Contribution externe 20181148 |
| Éditeur | Informa UK Limited |
| Document | publication en série |
| Lang. | anglais |
| DOI | https://doi.org/10.5589/m11-018 |
| Media | papier; en ligne; numérique |
| Formats | pdf |
| Sujets | télédétection; géophysique |
| Programme | Direction du Centre canadien de télédétection |
| Diffusé | 2014 06 02 |
| Résumé | (disponible en anglais seulement)
Rice is one of the three largest food grains in the world. Radar remote sensing has been proven to be an effective tool for rice monitoring. With the emergence
of spaceborne polarimetric synthetic aperture radar (SAR) satellites, research on polarization backscatter behaviors and identification methods for rice are of great significance and attract the attention of remote sensing communities. The Zhazuo
area located in Guizhou province of southwest China was selected as the test site for this study. The RADARSAT-2 polarimetric data acquired on four different dates were used to analyze the polarization backscatter behaviors and temporal variation of
rice. Identification methods for rice based on polarization combinations and polarization decompositions were developed. The results indicated that HH with HH/HV was the optimal polarization combination for rice identification, with an accuracy of up
to 86.65%. Based on the Pauli decomposition, rice can be discriminated effectively, with an accuracy of about 87.00%. Furthermore, using combinations of different polarization decompositions the identification results were greatly improved. The
combination of the Pauli decomposition and the parameter ? derived from eigenvector-eigenvalue-based decomposition was best for rice identification, with an accuracy of up to 93.51%. © 2011 CASI. |
| GEOSCAN ID | 311502 |
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