IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2022i1p113-d1021122.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/1/113/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/1/113/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wagener, Andreas & Zenker, Juliane, 2018. "Decoupled but not neutral: The effects of stochastic transfers on investment and incomes in rural Thailand," TVSEP Working Papers wp-008, Leibniz Universitaet Hannover, Institute for Environmental Economics and World Trade, Project TVSEP.
    2. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 265675, Collaborative Masters Program in Agricultural and Applied Economics.
    3. Glauber, Joseph W., 2017. "Agricultural insurance and the WTO:," IFPRI book chapters, in: Bouët, Antoine & Laborde Debucquet, David (ed.), Agriculture, development, and the global trading system: 2000– 2015, chapter 10, International Food Policy Research Institute (IFPRI).
    4. Yong Liu & A. Ford Ramsey, 2023. "Incorporating historical weather information in crop insurance rating," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(2), pages 546-575, March.
    5. World Bank, 2011. "Enhancing Crop Insurance in India," World Bank Publications - Reports 2748, The World Bank Group.
    6. Wynn, Katherine & Spangenberg, German & Smith, Kevin & Wilson, William, 2017. "Valuing Genetically Modified Traits in Canola Using Real Options," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(2), May.
    7. World Bank, 2011. "Kazakhstan : Agricultural Insurance Feasibility Study, Volume 2. Annexes," World Bank Publications - Reports 20780, The World Bank Group.
    8. F. G. Santeramo & B. K. Goodwin & F. Adinolfi & F. Capitanio, 2016. "Farmer Participation, Entry and Exit Decisions in the Italian Crop Insurance Programme," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 639-657, September.
    9. A Ford Ramsey, 2020. "Probability Distributions of Crop Yields: A Bayesian Spatial Quantile Regression Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 220-239, January.
    10. World Bank, 2012. "Agricultural Risk Management in the Caribbean : Lessons and Experiences, 2009-2012," World Bank Publications - Reports 13242, The World Bank Group.
    11. Smith, Vincent H. & Glauber, Joseph & Dismukes, Robert, 2016. "Rent Dispersion in the US Agricultural Insurance Industry:," IFPRI discussion papers 1532, International Food Policy Research Institute (IFPRI).
    12. Maichanou, Ahamadou, 2017. "La micro-assurance agricole indicielle au Niger‪," Économie rurale, French Society of Rural Economics (SFER Société Française d'Economie Rurale), vol. 359(May-June).
    13. Chi, Yichun & Zheng, Jiakun & Zhuang, Shengchao, 2022. "S-shaped narrow framing, skewness and the demand for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 105(C), pages 279-292.
    14. Visser, Martine & Jumare, Hafsah & Brick, Kerri, 2020. "Risk preferences and poverty traps in the uptake of credit and insurance amongst small-scale farmers in South Africa," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 826-836.
    15. Petraud, Jean & Boucher, Stephen & Carter, Michael, 2015. "Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru," 2015 Conference, August 9-14, 2015, Milan, Italy 211383, International Association of Agricultural Economists.
    16. Lipińska Izabela, 2016. "Managing the Risk in Agriculture Production: The Role of Government," European Countryside, Sciendo, vol. 8(2), pages 86-97, June.
    17. K.A. Naminova & N.T. Pavlova & M.P. Sarunova & D.V. Idzhilova, 2018. "Index Insurance as a Tool to Improve the Russian System of Insuring Risks of Agricultural Organizations with State Support," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 351-361.
    18. Mina, Christian D. & Reyes, Celia M. & Agbon, Adrian D. & Arboneda, Arkin, 2017. "Crop Insurance Program of the Philippine Crop Insurance Corporation: Integrative Report from the Five Case Regions in the Philippines," Discussion Papers DP 2017-39, Philippine Institute for Development Studies.
    19. Narayan Prasad Nagendra & Gopalakrishnan Narayanamurthy & Roger Moser, 2022. "Satellite big data analytics for ethical decision making in farmer’s insurance claim settlement: minimization of type-I and type-II errors," Annals of Operations Research, Springer, vol. 315(2), pages 1061-1082, August.
    20. Shweta Sinha & Nitin K. Tripathi, 2016. "Assessing the Challenges in Successful Implementation and Adoption of Crop Insurance in Thailand," Sustainability, MDPI, vol. 8(12), pages 1-20, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2022:i:1:p:113-:d:1021122. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.