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

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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

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