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Determining the Yield of Rice Using the Leaf Area Index (LAI) in Iran

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Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management

Part of the book series: Water Science and Technology Library ((WSTL,volume 105))

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Abstract

Most of Iran’s rice production is cultivated in the north zone of the country and also a strategic crop for Iranians. The per capita consumption of rice is 35 kg/person. Therefore, knowledge about the characteristics of rice and particularly, yield is very important. One of the most important indicators to determine the growth period and yield of rice is the leaf area index (LAI). In this study, the LAI index obtained from the MCD15A2H product of MODIS was used to border rice cultivation areas and to obtain yield estimates. According to previous studies of famous Iranian rice (Shiroodi, Kados, Hashemi and Deylamani) cultivars in relation to leaf area index (obtained from ground measurements) and the number of fertile tillers, which has been calculated significantly and positively. In this study, the equation for estimating rice yield was generated. The yield estimation equation was tested in 22,107 rice fields with an area of 90,350 ha. The estimated yield results were compared with the actual rice yield cultivars. In 2018–2019, the real average yield of rice in the country was 4539 kg/ha, and the result of the estimated yield was 4794 kg/ha. The average error in the country was 908.85 kg/ha.

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Author information

Authors and Affiliations

  1. Department of Surveying Engineering, Technical and Vocational University, Kermanshah, Iran

    Hamid Rahimi

  2. Biology Laboratory Expert, Razi University, Kermanshah, Iran

    Shahnaz Karami Sorkhalije

  3. GIS Institute, Miarsaghf Road & Building Company, Tehran, Iran

    Hajar Marabi

Authors
  1. Hamid Rahimi
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  2. Shahnaz Karami Sorkhalije
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  3. Hajar Marabi
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Corresponding author

Correspondence to Hamid Rahimi .

Editor information

Editors and Affiliations

  1. Department of Biological and Agricultural Engineering, Zachry Department of Civil and Environment Engineering, Texas A&M University, College Station, TX, USA

    Vijay P. Singh

  2. Department of Civil Engineering, Rabindranath Tagore University, Bhopal, Madhya Pradesh, India

    Shalini Yadav

  3. Faculty of Science, Madhyanchal Professional University, Bhopal, India

    Krishna Kumar Yadav

  4. IHE Delft Institute for Water Education, Delft, The Netherlands

    Gerald Augusto Corzo Perez

  5. The School of Natural Resources and Department of Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA

    Francisco Muñoz-Arriola

  6. Madhyanchal Professional University, Bhopal, India

    Ram Narayan Yadava

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Rahimi, H., Karami Sorkhalije, S., Marabi, H. (2022). Determining the Yield of Rice Using the Leaf Area Index (LAI) in Iran. In: Singh, V.P., Yadav, S., Yadav, K.K., Corzo Perez, G.A., Muñoz-Arriola, F., Yadava, R.N. (eds) Application of Remote Sensing and GIS in Natural Resources and Built Infrastructure Management. Water Science and Technology Library, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-031-14096-9_7

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