A Complete Procedure for Crop Phenology Estimation With PolSAR Data Based on the Complex Wishart Classifier

Empreu sempre aquest identificador per citar o enllaçar aquest ítem http://hdl.handle.net/10045/58529
Información del item - Informació de l'item - Item information
Títol: A Complete Procedure for Crop Phenology Estimation With PolSAR Data Based on the Complex Wishart Classifier
Autors: Mascolo, Lucio | Lopez-Sanchez, Juan M. | Vicente-Guijalba, Fernando | Nunziata, Ferdinando | Migliaccio, Maurizio | Mazzarella, Giuseppe
Grups d'investigació o GITE: Señales, Sistemas y Telecomunicación
Centre, Departament o Servei: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática
Paraules clau: Agriculture | Classification | Phenology | Polarimetry | Synthetic aperture radar (SAR)
Àrees de coneixement: Teoría de la Señal y Comunicaciones
Data de publicació: de novembre-2016
Editor: IEEE
Citació bibliogràfica: IEEE Transactions on Geoscience and Remote Sensing. 2016, 54(11): 6505-6515. doi:10.1109/TGRS.2016.2585744
Resum: A new methodology to estimate the growth stages of agricultural crops using the time series of polarimetric synthetic aperture radar (PolSAR) images is proposed. The methodology is based on the complex Wishart classifier and both phenological intervals and training areas are identified measuring the distances among polarimetric covariance matrices obtained from the time series of PolSAR data. Consequently, the computation of PolSAR features, which is the main step of state-of-the-art methods, is no longer needed, and the proposed approach can be applied in the same way to any crop type. Experiments undertaken on a dense time series of fully polarimetric C-band RADARSAT-2 images, collected at incidence angles ranging from 23° to 39°, in ascending/descending orbit passes, demonstrate that the proposed methodology can be successfully applied to retrieve the phenological stages of four different crop types. In addition, the effect of combining beams corresponding to different sensor's configurations has been evaluated, showing that it affects the retrieval accuracies. Validation with ground data shows the following: overall accuracy is between 54% and 86%; producer's accuracy (PA) and user's accuracy (UA) range between 21% and 100% and between 33% and 100%, respectively.
Patrocinadors: This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Projects TEC2011-28201-C02-02 and TIN2014-55413-C2-2-P.
URI: http://hdl.handle.net/10045/58529
ISSN: 0196-2892 (Print) | 1558-0644 (Online)
DOI: 10.1109/TGRS.2016.2585744
Idioma: eng
Tipus: info:eu-repo/semantics/article
Drets: © 2016 IEEE
Revisió científica: si
Versió de l'editor: http://dx.doi.org/10.1109/TGRS.2016.2585744
Apareix a la col·lecció: INV - SST - Artículos de Revistas

Arxius per aquest ítem:
Arxius per aquest ítem:
Arxiu Descripció Tamany Format  
Thumbnail2016_Mascolo_etal_IEEE-TGRS_final.pdfVersión final (acceso restringido)2,5 MBAdobe PDFObrir     Sol·licitar una còpia
Thumbnail2016_Mascolo_etal_IEEE-TGRS_accepted.pdfAccepted Manuscript (acceso abierto)2,63 MBAdobe PDFObrir Vista prèvia


Tots els documents dipositats a RUA estan protegits per drets d'autors. Alguns drets reservats.