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Drought Damage Assessment for Crop Insurance Based on Vegetation Index by Unmanned Aerial Vehicle (UAV) Multispectral Images of Paddy Fields in Indonesia

Author

Listed:
  • Yu Iwahashi

    (Graduate School of Agriculture, Kyoto University, Kyoto 6068224, Japan
    Graduate School of Agricultural Science, Tohoku University, Sendai 9808572, Japan)

  • Gunardi Sigit

    (Regional Office of Food Crops Service West Java Province, Cianjur 43283, Indonesia)

  • Budi Utoyo

    (Regional Office of Food Crops Service West Java Province, Cianjur 43283, Indonesia)

  • Iskandar Lubis

    (Faculty of Agriculture, IPB University, Bogor 16680, Indonesia)

  • Ahmad Junaedi

    (Faculty of Agriculture, IPB University, Bogor 16680, Indonesia)

  • Bambang Hendro Trisasongko

    (Faculty of Agriculture, IPB University, Bogor 16680, Indonesia)

  • I Made Anom Sutrisna Wijaya

    (Department of Agricultural and Bio-System Engineering, Udayana University, Badung 803611, Indonesia)

  • Masayasu Maki

    (Faculty of Food and Agricultural Sciences, Fukushima University, Fukushima 9061296, Japan)

  • Chiharu Hongo

    (Center for Environmental Remote Sensing, Chiba University, Chiba 2638522, Japan)

  • Koki Homma

    (Graduate School of Agricultural Science, Tohoku University, Sendai 9808572, Japan)

Abstract

Drought is increasingly threatening smallholder farmers in Southeast Asia. The crop insurance system is one of the promising countermeasures that was implemented in Indonesia in 2015. Because the damage assessment in the present system is conducted through direct investigations based on appearance, it is not objective and needs a long time to cover large areas. In this study, we investigated a rapid assessment method for paddy fields using a vegetation index (VI) taken by an unmanned aerial vehicle (UAV) with a multispectral camera in 2019 and 2021. Then, two ways of assessment for drought damage were tested: linear regression (LR) based on a visually assessed drought level (DL), and k-means clustering without an assessed DL. As a result, EVI2 could represent the damage level, showing the tendency of the decrease in the value along with the increasing DL. The estimated DL by both methods mostly coincided with the assessed DL, but the concordance rates varied depending on the locations and the number of assessed fields. Differences in the growth stage and rice cultivars also affected the results. This study revealed the feasibility of the UAV-based rapid and objective assessment method. Further data collection and analysis would be required for implementation in the future.

Suggested Citation

  • Yu Iwahashi & Gunardi Sigit & Budi Utoyo & Iskandar Lubis & Ahmad Junaedi & Bambang Hendro Trisasongko & I Made Anom Sutrisna Wijaya & Masayasu Maki & Chiharu Hongo & Koki Homma, 2022. "Drought Damage Assessment for Crop Insurance Based on Vegetation Index by Unmanned Aerial Vehicle (UAV) Multispectral Images of Paddy Fields in Indonesia," Agriculture, MDPI, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:gam:jagris:v:13:y:2022:i:1:p:113-:d:1021122
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    References listed on IDEAS

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    1. Naohiro Manago & Chiharu Hongo & Yuki Sofue & Gunardi Sigit & Budi Utoyo, 2020. "Transplanting Date Estimation Using Sentinel-1 Satellite Data for Paddy Rice Damage Assessment in Indonesia," Agriculture, MDPI, vol. 10(12), pages 1-18, December.
    2. Fullana-Pericàs, Mateu & Conesa, Miquel À. & Gago, Jorge & Ribas-Carbó, Miquel & Galmés, Jeroni, 2022. "High-throughput phenotyping of a large tomato collection under water deficit: Combining UAVs’ remote sensing with conventional leaf-level physiologic and agronomic measurements," Agricultural Water Management, Elsevier, vol. 260(C).
    3. Dadang Jainal Mutaqin & Koichi Usami, 2019. "Smallholder Farmers’ Willingness to Pay for Agricultural Production Cost Insurance in Rural West Java, Indonesia: A Contingent Valuation Method (CVM) Approach," Risks, MDPI, vol. 7(2), pages 1-18, June.
    4. Olivier Mahul & Charles J. Stutley, 2010. "Government Support to Agricultural Insurance : Challenges and Options for Developing Countries," World Bank Publications - Books, The World Bank Group, number 2432.
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