Machine Learning on the estimation of Leaf Area Index

Yasamin Afrasiabian, Ali Mokhtari, Kang Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The Leaf Area Index (LAI) is an important indicator in agriculture that can be considered a reliable plant growth parameter. The objective of this study is to make use of two different machine learning algorithms including Support Vector Machine (SVM), and Random Forest (RF) to improve the estimation of leaf area index using multispectral, thermal, and hyperspectral data. The results showed that RF was the best model to improve the accuracy of the LAI estimation compared to the simple linear regression (previous study) and SVM (R2 = 0.91 for RF and R2 = 0.87 for SVM). To evaluate the effects of spectral portions on LAI estimation without calculating the spectral indices, (SI) we inputted each pair of spectral bands for training and testing both RF and SVM. It was found that the best correlation was lower compared to use SIs. However, R2 variations were more homogeneous across the whole spectrum, which suggests that even by using multispectral broadband bands in RF and SVM, a good correlation will be achieved.

Original languageEnglish
Title of host publicationInformatik in der Land-, Forst- und Ernahrungswirtschaft - Fokus
Subtitle of host publicationKunstliche Intelligenz in der Agrar- und Ernahrungswirtschaft - Referate der 42. GIL-Jahrestagung
EditorsMarkus Gandorfer, Christa Hoffmann, Nadja El Benni, Marianne Cockburn, Thomas Anken, Helga Floto
PublisherGesellschaft fur Informatik (GI)
Pages21-26
Number of pages6
ISBN (Electronic)9783885797111
StatePublished - 2022
Event42. Jahrestagung 2022 der Gesellschaft fur Informatik in der Land-, Forst- und Ernahrungswirtschaft: Was bedeutet Kunstliche Intelligenz fur die Agrar- und Ernahrungswirtschaft, GIL 2022 - 42nd Annual Conference 2022 of the Society for Information Technology in Agriculture, Forestry and Food Industry: What does Artificial Intelligence mean for the Agricultural and Food industry, GIL 2022 - Ettenhausen, Switzerland
Duration: 21 Feb 202222 Feb 2022

Publication series

NameLecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
VolumeP-317
ISSN (Print)1617-5468

Conference

Conference42. Jahrestagung 2022 der Gesellschaft fur Informatik in der Land-, Forst- und Ernahrungswirtschaft: Was bedeutet Kunstliche Intelligenz fur die Agrar- und Ernahrungswirtschaft, GIL 2022 - 42nd Annual Conference 2022 of the Society for Information Technology in Agriculture, Forestry and Food Industry: What does Artificial Intelligence mean for the Agricultural and Food industry, GIL 2022
Country/TerritorySwitzerland
CityEttenhausen
Period21/02/2222/02/22

Keywords

  • Leaf Area Index
  • Random Forest
  • Support Vector Machine
  • hyperspectral
  • multispectral
  • thermal

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