Title: UAV multispectral imagery in determination of paddy conditions

Authors: Andrea Oliver Enos; Khairul Nizam Tahar

Addresses: Global-Trak Systems SdnBhd, 11A, Jalan USJ 1/33, Taman Subang Permai, 47600 Subang Jaya, Selangor, Malaysia ' Centre of Studies for Surveying Science and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, 40450 Shah Alam, Selangor Darul Ehsan, Malaysia

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.

DOI: 10.1504/IJGENVI.2022.126185

International Journal of Global Environmental Issues, 2022 Vol.21 No.2/3/4, pp.148 - 160

Received: 16 Mar 2021
Accepted: 24 Nov 2021
Published online: 14 Oct 2022 *

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