Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

Please use this identifier to cite or link to this item:
Información del item - Informació de l'item - Item information
Title: Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature
Authors: De Bernardis, Caleb G. | Vicente-Guijalba, Fernando | Martínez Marín, Tomás | Lopez-Sanchez, Juan M.
Research Group/s: Señales, Sistemas y Telecomunicación
Center, Department or Service: Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: Agriculture | Data fusion | Normalized difference vegetation index (NDVI) | Particle filter (PF) | Phenology | State space | Synthetic aperture radar (SAR) | Temperature | Time series
Knowledge Area: Teoría de la Señal y Comunicaciones
Issue Date: 5-Apr-2016
Publisher: IEEE
Citation: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016, 9(8): 3512-3523. doi:10.1109/JSTARS.2016.2539498
Abstract: In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.
Sponsor: This work was supported in part by Spanish Ministry of Economy and Competitiveness (MINECO) and in part by EU FEDER under Project TEC2011-28201-C02-02 and TIN2014-55413-C2-2-P.
ISSN: 1939-1404 (Print) | 2151-1535 (Online)
DOI: 10.1109/JSTARS.2016.2539498
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Peer Review: si
Publisher version:
Appears in Collections:INV - SST - Artículos de Revistas

Files in This Item:
Files in This Item:
File Description SizeFormat 
Thumbnail2016_De-Bernardis_etal_JSTARS_rev.pdfVersión revisada (acceso abierto)1,7 MBAdobe PDFOpen Preview

Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.