Estimating rainfed groundnut’s leaf area index using Sentinel-2 based on Machine Learning Regression Algorithms and Empirical Models

The leaf area index (LAI), a crucial biophysical indicator, is used to assess and monitor crop growth for effective agricultural management. This study assessed the LAI at the seedling stage after conducting a field experiment with rainfed groundnut. The study tests the performance of multiple machi...

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Veröffentlicht in:	Precision agriculture Jg. 25; H. 3; S. 1404 - 1428
Hauptverfasser:	Ekwe, Michael Chibuike, Adeluyi, Oluseun, Verrelst, Jochem, Kross, Angela, Odiji, Caleb Akoji
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.06.2024 Springer Nature B.V
Schlagworte:	Accuracy Agricultural management Agriculture Algorithms Atmospheric Sciences Biomedical and Life Sciences Chemistry and Earth Sciences Computer Science Crop growth Empirical analysis Estimation Gaussian process Groundnuts Kernel functions Leaf area Leaf area index Learning algorithms Leaves Life Sciences Machine learning Normalized difference vegetative index Physics Regression Regression analysis Remote Sensing/Photogrammetry Seedlings Soil Science & Conservation Statistics for Engineering Support vector machines Vegetation Seedling stage Machine learning algorithms LAI Vegetation indices Sentinel-2
ISSN:	1385-2256, 1573-1618
Online-Zugang:	Volltext
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