Crop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategy
Contribuinte(s) |
Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal Universidad de Alicante. Instituto Universitario de Investigación Informática Señales, Sistemas y Telecomunicación |
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Data(s) |
30/05/2014
30/05/2014
01/06/2014
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Resumo |
In this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown. This project was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and in part by EU FEDER under Project TEC2011-28201-C02-02. |
Identificador |
IEEE Geoscience and Remote Sensing Letters. 2014, 11(6): 1081-1085. doi:10.1109/LGRS.2013.2286214 1545-598X (Print) 1558-0571 (Online) http://hdl.handle.net/10045/37746 10.1109/LGRS.2013.2286214 |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dx.doi.org/10.1109/LGRS.2013.2286214 |
Direitos |
© Copyright 2014 IEEE info:eu-repo/semantics/openAccess |
Palavras-Chave | #Agriculture #Kalman filter #Multitemporal #Phenology #Polarimetry #Rice #Synthetic aperture radar (SAR) #Teoría de la Señal y Comunicaciones |
Tipo |
info:eu-repo/semantics/article |