Improving Unmanned Aerial Vehicle Remote Sensing-Based Rice Nitrogen Nutrition Index Prediction with Machine Learning

Improving Unmanned Aerial Vehicle Remote Sensing-Based Rice Nitrogen Nutrition Index Prediction with Machine Learning

Optimizing nitrogen (N) management in rice is crucial for China’s food security and sustainable agricultural development. Nondestructive crop growth monitoring based on remote sensing technologies can accurately assess crop N status, which may be used to guide the in-season site-specific N...

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Bibliographic Details
Main Authors: Hainie Zha, Yuxin Miao, Tiantian Wang, Yue Li, Jing Zhang, Weichao Sun, Zhengqi Feng, Krzysztof Kusnierek
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Remote Sensing
Subjects:
fixed-wing uav remote sensing
nitrogen status diagnosis
random forest
precision nitrogen management
machine learning
Online Access:https://www.mdpi.com/2072-4292/12/2/215

Internet

https://www.mdpi.com/2072-4292/12/2/215

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