PREDICTION OF PLANT GROWTH BASED ON STATISTICAL MEASUREMENTS USING SATELLITE IMAGE TIME SERIES

被引：0

作者：

Hachicha, Marva ^{[1
,2
]}

Louati, Mandi ^{[3
]}

Kallel, Abdelaziz ^{[1
,2
]}

Gastellu-Etchegorry, Jean-Philippe ^{[4
,5
]}

机构：

[1] Adv Technol Image & Signal Proc, Tunis, Tunisia

[2] CRNS, Digital Res Ctr Sfax, Sfax, Tunisia

[3] Natl Sch Elect & Telecommun Sfax ENETCom, Sfax, Tunisia

[4] Toulouse Univ, CESBIO, Toulouse, France

[5] Paul Sabatier Univ, CNRS, CNES, IRD, Toulouse, France

来源：

IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年

关键词：

Satellite image times series; NDVI; Sentinel-2; Statistical method; Forecasting; Markov chain model;

D O I：

10.1109/IGARSS39084.2020.9324547

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：136 / 139

页数：4

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