TY - GEN
T1 - Rice Plant Nitrogen Concentration Monitoring by Unmanned Aerial Vehicle-Based Imagery
AU - Nuryawati, Titin
AU - Baskoro, Ario Sunar
N1 - Funding Information:
This research was supported by Saintek - Kemenristekdikti Scholarship Program and Indonesian Center for Agricultural Engineering Research and Development, Indonesian Agency of Agricultural Research and Development, Ministry of Agriculture Indonesia.
Publisher Copyright:
© 2020 ACM.
PY - 2020/6/16
Y1 - 2020/6/16
N2 - 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.
AB - 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.
KW - plant nitrogen concentration
KW - Rice
KW - unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85090976666&partnerID=8YFLogxK
U2 - 10.1145/3400934.3400979
DO - 10.1145/3400934.3400979
M3 - Conference contribution
AN - SCOPUS:85090976666
T3 - ACM International Conference Proceeding Series
SP - 241
EP - 246
BT - Asia Pacific Conference on Research in Industrial and Systems Engineering, APCORISE 2020 - Proceedings
PB - Association for Computing Machinery
T2 - 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering, APCORISE 2020
Y2 - 16 June 2020
ER -