Use of weighted regression for estimating rice yield by satellite data

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  • TAKEZAWA Kunio
    National Agriculture and Bio-oriented Research Organization, National Agricultural Research Center
  • HAN Sung-Il
    Osaka Electro-Communication University & Kobe University (part-time lecturer)
  • NINOMIYA Seishi
    National Agriculture and Bio-oriented Research Organization, National Agricultural Research Center
  • HONGO Chiharu
    Center for Environmental Remote Sensing, Chiba University
  • TOKUI Kazuhisa
    National Agricultural Insurance Association
  • ITO Akihiko
    Space Engineering Development Co., Ltd.
  • TAKESHIMA Toshiaki
    Japan Aerospace Exploration Agency

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Other Title
  • 衛星データによる水稲収量推定における重み付き回帰の利用
  • エイセイ データ ニ ヨル スイトウ シュウリョウ スイテイ ニ オケル オモミツキ カイキ ノ リヨウ

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Abstract

Use of weighted regression is attempted for deriving regression equations which aim at estimating rice yield by satellite data give by ASTER sensor. It is assumed that satellite data and rice yield data are obtained in 2001 and 2002, and in 2004, all satellite data and a part of rice yield data are given. Then, the unobserved rice yield data in 2004 is to be estimated. For this purpose, multiple regression equations are obtained and predictive errors are estimated. The results indicates that use of weighted regression allows us to make the most of three-year data for beneficial estimation. The procedure suggested here is an attempt to utilize weighted regression for realizing regression which reflects the degree of validity of respective data, as well as a method for coping with inhomogeneity of variance of data. Moreover, use of additive model instead of multiple regression equation confirms the effect of weighted regression. The results given by additive model are shown to be more desirable than those by multiple regression equation.

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