Rice Plant Nitrogen Concentration Monitoring by Unmanned Aerial Vehicle-Based Imagery

Titin Nuryawati, Ario Sunar Baskoro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Application of Unmanned aerial vehicles (UAVs) for remote sensing has given many advantages. The measurement of reflectance spectra in plant canopies can be the basis in detecting nitrogen content. Chlorophyll concentrations at different levels resulted in the reflectance spectra measured in the canopy, also being different. This study aimed to develop the method of Nitrogen monitoring using UAV imagery combined with Leaf Chart Color (LCC) to estimate plant nitrogen concentration in rice. To develop the Normalized Difference Vegetation Index (NDVI) indices, the Leaf Chart Color was used to measure the greenness of the leaf crop. A high-resolution digital camera modified with NDVI-7 filter mounted to UAV that sensitive to infrared wavelength. The flight altitude was 3, 10, and 15 m. To measure the strength of a linear association between LCC measurements and NDVI estimations, we used a Pearson one-tailed correlation. The Pearson coefficient indicates that the correlation is a strong negative correlation (-0.822) at 3 m altitude, weak correlation (-0.4562) at 10 m altitude, and no correlation at 15 m altitude.

Original languageEnglish
Title of host publicationAsia Pacific Conference on Research in Industrial and Systems Engineering, APCORISE 2020 - Proceedings
PublisherAssociation for Computing Machinery
Pages241-246
Number of pages6
ISBN (Electronic)9781450376006
DOIs
Publication statusPublished - 16 Jun 2020
Event3rd Asia Pacific Conference on Research in Industrial and Systems Engineering, APCORISE 2020 - Depok, Online, Indonesia
Duration: 16 Jun 2020 → …

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd Asia Pacific Conference on Research in Industrial and Systems Engineering, APCORISE 2020
Country/TerritoryIndonesia
CityDepok, Online
Period16/06/20 → …

Keywords

  • plant nitrogen concentration
  • Rice
  • unmanned aerial vehicle

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