Comparison of Long Short-Term Memory Networks and Random Forest for Sentinel-1 Time Series Based Large Scale Crop Classification

Comparison of Long Short-Term Memory Networks and Random Forest for Sentinel-1 Time Series Based Large Scale Crop Classification

To ensure future food security, improved agricultural management approaches are required. For many of those applications, precise knowledge of the distribution of crop types is essential. Various machine and deep learning models have been used for automated crop classification using microwave remote...

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Bibliographic Details
Main Authors: Felix Reuß, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Wolfgang Wagner
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Remote Sensing
Subjects:
crop classification
Sentinel-1
synthetic aperture radar (SAR)
recurrent neural network
long short-term memory network
random forest
Online Access:https://www.mdpi.com/2072-4292/13/24/5000

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https://www.mdpi.com/2072-4292/13/24/5000

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