AGRIS - International System for Agricultural Science and Technology

Synergetic use of Sentinel-1 and Sentinel-2 data for wheat-crop height monitoring using machine learning

2024

Nduku, Lwandile | Munghemezulu, Cilence | Mashaba-Munghemezulu, Zinhle | Ratshiedana, Phathutshedzo Eugene | Sibanda, Sipho | Chirima, Johannes George


Bibliographic information
Publisher
MDPI
Other Subjects
Sentinel-1; Support vector machine regression (svmr); Sdg-09: industry; Support vector machine regression; Optimized random forest regression (rfr); Crop height; Neural network regression (nnr); Sdg-15: life on land; Decision tree regression (dtr); Sdg-02: zero hunger; Innovation and infrastructure; Machine-learning algorithms; Random forest regression; Sentinel-2
Language
English
Format
application/pdf
License
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
ISSN
2624-7402
Type
Journal Article

2024-10-08
2024-10-08
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