Machine learning-based early prediction of rice-growing fields using multi-temporal Sentinel-1 synthetic aperture radar and Sentinel-2 multispectral data-Reference-Cited by-同舟云学术

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Machine learning-based early prediction of rice-growing fields using multi-temporal Sentinel-1 synthetic aperture radar and Sentinel-2 multispectral data

Published:2024-08-14 Issue:03 Volume:18 Page:
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Son Nguyen-Thanh¹,Chen Chi-Farn¹,Lin Huan-Sheng¹,Cheng Youg-Sin¹,Chen Cheng-Ru¹,Syu Chein-Hui²,Zhang Yi-Ting²,Liu Tsang-Sen²,Toscano Piero³,Chen Shu-Ling⁴,Chen Shih-Hsiang⁴

Affiliation:

1. National Central University, Center for Space and Remote Sensing Research, Taoyuan City, Taiwan

2. Taiwan Agricultural Research Institute, Department of Agricultural Chemistry Division, Taichung City, Taiwan

3. Institute of BioEconomy-National Research Council, IBE-CNR, Sesto Fiorentino, Italy

4. National Taipei University, Department of Finance and Cooperative Management, New Taipei, Taiwan

Publisher

SPIE-Intl Soc Optical Eng

Reference88 articles.

1. Grain: world markets and trade,2024

2. Food Outlook – Biannual Report on Global Food Markets,2023

3. Rice: Importance for Global Nutrition

4. A Global Perspective on White Rice Consumption and Risk of Type 2 Diabetes

5. Global trends in wheat production, consumption and trade;Erenstein,2022

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