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Hyperspectral Estimation of Leaf Area Index of Winter Wheat Based on Akaike’s Information Criterion

  • Haikuan Feng
  • Fuqin YangEmail author
  • Guijun Yang
  • Haojie Pei
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

Abstract

Leaf Area Index (LAI) is an important parameter for assessing the crop growth and winter wheat yield prediction. The objectives of this study were(1) to establish and verify a model for the LAI of winter wheat, where the regression models, extended the Grey Relational Analysis (GRA), Akaike’s Information Criterion (AIC), Least Squares Support Vector Machine (LSSVM) and (ii) to compare the performance of proposed models GRA-LSSVM-AIC. Spectral reflectance of leaves and concurrent LAI parameters of samples were acquired in Tongzhou and Shunyi districts, Beijing city, China, during 2008/2009 and 2009/2010 winter wheat growth seasons. In the combined model, GRA was used to analyse the correlation between vegetation index and LAI, LSSVM was used to conduct regression analysis according to the GRA for different vegetation index order of the number of independent variables, AIC was used to select the optimal models in LSSVM models. Our results indicated that GRA-LSSVM-AIC optimal models came out robust LAI evaluation (R = 0.81 and 0.80, RMSE = 0.765 and 0.733, individually). The GRA-LSSVM-AIC had higher applicability between different years and achieved prediction of LAI estimation of winter wheat between regional and annual levels, and had a wide range of potential applications.

Keywords

Leaf area index Akaike’s Information Criterion Grey Relational Analysis Least Squares Support Vector Machine 

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Haikuan Feng
    • 1
  • Fuqin Yang
    • 1
    • 2
    • 3
    Email author
  • Guijun Yang
    • 1
  • Haojie Pei
    • 1
    • 2
  1. 1.Beijing Research Center for Information Technology in AgricultureBeijingChina
  2. 2.College of Geoscience and Surveying EngineeringChina University of Mining and TechnologyBeijingChina
  3. 3.College of Civil EngineeringHenan Institute of EngineeringZhengzhouChina

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