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Information Journal Paper

Title

RICE YIELD ESTIMATION USING SATELLITE IMAGE PROCESSING

Pages

  13-24

Abstract

 In this paper, using image processing and remote sensing techniques, RICE YIELD ESTIMATION is performed for a region in Mazandaran province, North of Iran. Four Liss-III images from IRS-ID satellite have been used. Two of the images are from rice cultivation period and other two are from different times of the year. Geometric corrections have been performed on the images using ground control points. At first image pixels were classified to "rice" and "non-rice" classes using a2- class MLP neural network. Then rice farms were classified as "high yield" and "low yield" differentiations of rice cultivations using another MLP neural network. Estimation of rice yield for each of these classes of rice farms were then accomplished using an REF neural network model. Finally using the three mentioned neural network models, the estimation of rice yield for the whole region was performed Good results have been obtained from the models which are presented in the paper.

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  • Cite

    APA: Copy

    SORYANI, MOHSEN, GHADERI, R., & HASHEMI KAMANGAR, M.. (2008). RICE YIELD ESTIMATION USING SATELLITE IMAGE PROCESSING. SIGNAL AND DATA PROCESSING, -(1 (SERIAL 9)), 13-24. SID. https://sid.ir/paper/160777/en

    Vancouver: Copy

    SORYANI MOHSEN, GHADERI R., HASHEMI KAMANGAR M.. RICE YIELD ESTIMATION USING SATELLITE IMAGE PROCESSING. SIGNAL AND DATA PROCESSING[Internet]. 2008;-(1 (SERIAL 9)):13-24. Available from: https://sid.ir/paper/160777/en

    IEEE: Copy

    MOHSEN SORYANI, R. GHADERI, and M. HASHEMI KAMANGAR, “RICE YIELD ESTIMATION USING SATELLITE IMAGE PROCESSING,” SIGNAL AND DATA PROCESSING, vol. -, no. 1 (SERIAL 9), pp. 13–24, 2008, [Online]. Available: https://sid.ir/paper/160777/en

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