Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images
Abstract
:1. Introduction
2. Methodology
2.1. Particle Filter (PF) Theory
2.2. Particle Filter Implementation
2.2.1. Crop Phenology Model
2.2.2. Observation Model
2.2.3. Estimation
3. Data Set and Test Site
4. Results
4.1. Phenological State Estimation
4.2. Prediction of Key Dates
4.3. Estimation over Other Types of Rice
5. Discussion
5.1. State Estimation and Prediction
5.2. Methodology Generalisation
5.3. Summary of Advantages
5.4. Perspectives and Future Research Lines
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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(1) Initialisation | Generate N samples of from the initial PDF . |
(2) Prediction | Obtain the sample of from the transition PDF . |
(3) Measurement step | Compute the likelihood function. . |
(4) Update | Evaluate the importance weights from likelihood function. . |
(5) Normalisation | Normalise the weights . |
(6) Resampling | The effective number of particles () provides a measure of the number of particles with significant weight representing the posterior PDF. If this number is lower than a provided threshold () they are redistributed where the PDF is more likely. Reset to . |
Year | 2008 | 2009 | 2010 | 2011 | 2013 |
---|---|---|---|---|---|
Number of Parcels | 11 | 13 | 13 | 9 | 8 |
Images per Parcel | 15 | 16 | 15 | 14 | 6 |
Images Employed | 16 | 15 | 14 | 13 | 12 | |
---|---|---|---|---|---|---|
asymmetric Gaussian | RMSE | 7.2 | 8.1 | 9.2 | 11.0 | 14.0 |
MAE | 13 | 21 | 35 | 35 | 43 | |
Double-logistic | RMSE | 7.2 | 8.1 | 9.0 | 11.0 | 14.0 |
MAE | 13 | 21 | 37 | 39 | 43 | |
Savistzky-Golay | RMSE | 10.2 | 11.0 | 12.4 | 14.0 | 17.7 |
MAE | 20 | 26 | 45 | 47 | 69 |
Images Employed | 3 |
---|---|
RMSE | 8.3 |
MAE | 24 |
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De Bernardis, C.; Vicente-Guijalba, F.; Martinez-Marin, T.; Lopez-Sanchez, J.M. Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images. Remote Sens. 2016, 8, 610. https://doi.org/10.3390/rs8070610
De Bernardis C, Vicente-Guijalba F, Martinez-Marin T, Lopez-Sanchez JM. Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images. Remote Sensing. 2016; 8(7):610. https://doi.org/10.3390/rs8070610
Chicago/Turabian StyleDe Bernardis, Caleb, Fernando Vicente-Guijalba, Tomas Martinez-Marin, and Juan M. Lopez-Sanchez. 2016. "Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images" Remote Sensing 8, no. 7: 610. https://doi.org/10.3390/rs8070610