articleRemote SensingApr 21, 2022GOLD OA

A Systematic Literature Review on Crop Yield Prediction with Deep Learning and Remote Sensing

Central Queensland University

Indexed incrossrefdoaj

Abstract

Deep learning has emerged as a potential tool for crop yield prediction, allowing the model to automatically extract features and learn from the datasets. Meanwhile, smart farming technology enables the farmers to achieve maximum crop yield by extracting essential parameters of crop growth. This systematic literature review highlights the existing research gaps in a particular area of deep learning methodologies and guides us in analyzing the impact of vegetation indices and environmental factors on crop yield. To achieve the aims of this study, prior studies from 2012 to 2022 from various databases are collected and analyzed. The study focuses on the advantages of using deep learning in crop yield prediction,…

Citation impact

304
total citations
FWCI
46.42
Percentile
100%
References
96
Citations per year

Authors

5

Topics & keywords

Keywords
  • Deep learning
  • Crop yield
  • Computer science
  • Machine learning
  • Artificial intelligence
  • Convolutional neural network
  • Yield (engineering)
  • Agricultural engineering
UN Sustainable Development Goals
  • Zero hunger
No related works found for this paper.