Artificial Intelligence Algorithms for Rapeseed Fields Mapping Using Sentinel-1 Time Series: Temporal Transfer Scenario and Ground Sampling Constraints

Artificial Intelligence Algorithms for Rapeseed Fields Mapping Using Sentinel-1 Time Series: Temporal Transfer Scenario and Ground Sampling Constraints

This study aims to enhance rapeseed field detection accuracy using Sentinel-1 (S1) time series data and addressing challenges in collecting ground samples. The proposed solutions include model transfer between years without retraining and secondly, developing models with limited training samples. Th...

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Bibliographic Details
Main Authors: Saeideh Maleki, Nicolas Baghdadi, Cassio Fraga Dantas, Sami Najem, Hassan Bazzi, Nuria Pantaleoni Reluy, Dino Ienco, Mehrez Zribi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning (DL)
INCEPTIONTIME
long short-term memory fully convolutional network (LSTM-FCN)
multilayer perceptron (MLP)
random forest (RF)
rapeseed
Online Access:https://ieeexplore.ieee.org/document/10254255/

Internet

https://ieeexplore.ieee.org/document/10254255/

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