Hidden Markov Models for Real-Time Estimation of Corn Progress Stages Using MODIS and Meteorological Data

Hidden Markov Models for Real-Time Estimation of Corn Progress Stages Using MODIS and Meteorological Data

Real-time estimation of crop progress stages is critical to the US agricultural economy and decision making. In this paper, a Hidden Markov Model (HMM) based method combining multisource features has been presented. The multisource features include mean Normalized Difference Vegetation Index (NDVI),...

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Bibliographic Details
Main Authors: Guoxian Yu, Yuanzheng Shao, Hong Tang, Genong Yu, Liping Di, Lixin Wu, Yonglin Shen
Format: Article
Language:English
Published: MDPI AG 2013-04-01
Series:Remote Sensing
Subjects:
fractal dimension
hidden Markov model (HMM)
phenology
time series
Online Access:http://www.mdpi.com/2072-4292/5/4/1734

Internet

http://www.mdpi.com/2072-4292/5/4/1734

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