Machine learning approaches for rice crop yield predictions using time-series satellite data in Taiwan-Reference-Cited by-同舟云学术

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Machine learning approaches for rice crop yield predictions using time-series satellite data in Taiwan

Published:2020-08-15 Issue:20 Volume:41 Page:7868-7888
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Son Nguyen-Thanh^ORCID,Chen Chi-Farn^ORCID,Chen Cheng-Ru^ORCID,Guo Horng-Yuh¹,Cheng Youg-Sing²,Chen Shu-Ling³,Lin Huan-Sheng²,Chen Shih-Hsiang³

Affiliation:

1. Taiwan Agricultural Research Institute , Taichung City, Taiwan

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

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

Funder

Taiwan Agricultural Research Institute

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2020.1766148

Reference105 articles.

1. Machine Learning Regression Techniques for the Silage Maize Yield Prediction Using Time-Series Images of Landsat 8 OLI

2. Application of the CSM-CERES-Rice model for evaluation of plant density and nitrogen management of fine transplanted rice for an irrigated semiarid environment

3. Modeling Managed Grassland Biomass Estimation by Using Multitemporal Remote Sensing Data—A Machine Learning Approach

4. Evaluation of Ceres-Rice, Aquacrop and Oryza2000 Models in Simulation of Rice Yield Response to Different Irrigation and Nitrogen Management Strategies

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