Monitoring paddy rice phenology using time series MODIS data over Jiangxi Province, China

Paddy rice is one of the most important crops in the world. Accurate estimation and monitoring of paddy rice phenology is necessary for management and yield prediction. Remotely sensed time-series data are essential for estimation of crop phenology stages across large areas. Here, the paddy rice phe...

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Bibliographic Details
Published inInternational journal of agricultural and biological engineering Vol. 7; no. 6; p. 28
Main Authors Shihua, Li, Jiangtao, Xiao, Ping, Ni, Jing, Zhang, Hongshu, Wang, Jingxian, Wang
Format Journal Article
LanguageEnglish
Published Beijing International Journal of Agricultural and Biological Engineering (IJABE) 01.12.2014
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Summary:Paddy rice is one of the most important crops in the world. Accurate estimation and monitoring of paddy rice phenology is necessary for management and yield prediction. Remotely sensed time-series data are essential for estimation of crop phenology stages across large areas. Here, the paddy rice phenological stages were detected in Jiangxi Province, China. A comparison study was conducted using ground observation data from 10 agricultural meteorological stations, collected between 2006 and 2008. The phenological stages were detected using Moderate Resolution Imaging Spectroradiometer time-series enhanced vegetation index (EVI) data. Savitzky-Golay filter and wavelet transform were used to reduce the noise in the time-series EVI data and reconstruct the smoothed EVI time-series profile. Key phenological stages of double-cropping rice were detected using the characteristics of the smoothed EVI profile. The root mean square errors for each stage were ±10 days around the ground observation data. The results suggest that Savitzky-Golay filter and wavelet transform are promising approaches for reconstructing high-quality EVI time-series data.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:1934-6344
1934-6352
DOI:10.3965/j.ijabe.20140706.005