UAV multispectral imagery in determination of paddy conditions

Andrea Oliver Enos and Khairul Nizam Tahar

International Journal of Global Environmental Issues, 2022, vol. 21, issue 2/3/4, 148-160

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.

Keywords: precision agriculture; multispectral camera; UAV; unmanned aerial vehicle; remote sensing; vegetation index. (search for similar items in EconPapers)
Date: 2022
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