Prediction of Plant Growth Based on Statistical Measurements Using Satellite Image Time Series
| Autor: | Marwa Hachicha, Mahdi Louati, Jean-Philippe Gastellu-Etchegorry, Abdelaziz Kallel |
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| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
Markov chain Mean squared error Series (mathematics) Markov process Vegetation 010502 geochemistry & geophysics 01 natural sciences symbols.namesake Autoregressive model Statistics symbols Satellite Image Time Series Time series 0105 earth and related environmental sciences Mathematics |
| Zdroj: | IGARSS |
| Popis: | This paper presents new approaches to forecast the plant growth based on statistical methods: autoregressive and Markov chain models, using a time series of the normalized different vegetation index. Here, a monthly normalized different vegetation index time series was derived from Sentinel-2 over Limaya olive tree fields from January 2016 to November 2019. To ensure consistent prediction, processing is done over homogeneous clusters of vegetation. Finally, the performance of our approach is evaluated by means of the root mean square error between the predicted and true values. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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