Enhancing Crop Yield Prediction Utilizing Machine Learning on Satellite-Based Vegetation Health Indices

Enhancing Crop Yield Prediction Utilizing Machine Learning on Satellite-Based Vegetation Health Indices

Accurate crop yield forecasting is essential in the food industry’s decision-making process, where vegetation condition index (VCI) and thermal condition index (TCI) coupled with machine learning (ML) algorithms play crucial roles. The drawback, however, is that a one-fits-all prediction model is of...

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Bibliographic Details
Main Authors: Pham, Hoa Thi, Awange, Joseph, Kuhn, Michael, Van Nguyen, B., Bui, L.K.
Format: Journal Article
Language:English
Published: MDPI 2022
Subjects:
Science & Technology
Physical Sciences
Technology
Chemistry, Analytical
Engineering, Electrical & Electronic
Instruments & Instrumentation
Chemistry
Engineering
crop yield prediction
vegetation condition index (VCI)
thermal condition index (TCI)
independent component analysis (ICA)
principle component analysis (PCA)
machine learning
WINTER-WHEAT YIELD
RICE YIELD
MODEL
DROUGHT
CORN
Online Access:http://hdl.handle.net/20.500.11937/88918

Internet

http://hdl.handle.net/20.500.11937/88918

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