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UAV multispectral imagery in determination of paddy conditions

Author

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  • Andrea Oliver Enos
  • Khairul Nizam Tahar

Abstract

This study aims to determine the health condition of paddy by using UAV multispectral imagery. This involves determining the health of paddy by using NDVI and calculating the percentage of the healthy paddy area. The data was obtained from an altitude of 80 m with an 80% overlap. The selected study area was about 14,937.13 m2. This study reported that the very healthy paddy area was about 8,981.699 m2 (60.13%), and the healthy condition area was 3,398.481 m2 (22.75%). Meanwhile, the area of the unhealthy paddy region was 2,556.95 m2, whereby the percentage of the region was 17.12%. The accuracy assessment was based on the NDVI imagery and NDVI ground truth data, in which the root mean square error (RMSE) achieved ±0.057. The regression analysis showed that the relationship between NDVI from the multispectral UAV and spectrometer had a 90.53% correlation.

Suggested Citation

  • Andrea Oliver Enos & Khairul Nizam Tahar, 2022. "UAV multispectral imagery in determination of paddy conditions," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 21(2/3/4), pages 148-160.
    • Handle: RePEc:ids:ijgenv:v:21:y:2022:i:2/3/4:p:148-160
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