TY - JOUR
T1 - Drought Damage Assessment for Crop Insurance Based on Vegetation Index by Unmanned Aerial Vehicle (UAV) Multispectral Images of Paddy Fields in Indonesia
AU - Iwahashi, Yu
AU - Sigit, Gunardi
AU - Utoyo, Budi
AU - Lubis, Iskandar
AU - Junaedi, Ahmad
AU - Trisasongko, Bambang Hendro
AU - Wijaya, I. Made Anom Sutrisna
AU - Maki, Masayasu
AU - Hongo, Chiharu
AU - Homma, Koki
N1 - Funding Information:
This research was funded by JST SATREPS, grant number JPMJSA 1604.
Publisher Copyright:
© 2022 by the authors.
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Indonesia
KW - crop insurance
KW - drought
KW - rice
KW - unmanned aerial vehicle
KW - vegetation index
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U2 - 10.3390/agriculture13010113
DO - 10.3390/agriculture13010113
M3 - Article
AN - SCOPUS:85146700993
SN - 2077-0472
VL - 13
JO - Agriculture (Switzerland)
JF - Agriculture (Switzerland)
IS - 1
M1 - 113
ER -