Estimation of Nitrogen Content of Rice Crops Using Sentinel-2 Data

https://doi.org/10.22146/ijg.88571

Heni Agustina(1), Lalu Muhamad Jaelani(2*), Hartanto Sanjaya(3)

(1) Department of Geomatics Engineering, Faculty of Civil, Planning, and Geo-Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya 60111, Indonesia
(2) Department of Geomatics Engineering, Faculty of Civil, Planning, and Geo-Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya 60111, Indonesia
(3) Department of Civil Engineering, Faculty of Civil, Planning and Geo-Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya 60111, Indonesia and National Research and Innovation Agency, Gedung B.J. Habibie, Jl. M.H. Thamrin No. 8, Jakarta Pusat 10340,Indonesia
(*) Corresponding Author

Abstract


Nitrogen (N) is one of the most essential nutrients for rice crops. Farmers generally provide Nitrogen requirements in rice through fertilization, but the fertilization process is only based on an estimation without calculating the amount needed first. However, neither insufficient nor excessive nitrogen content is good for rice crops, and the nitrogen needs of rice crops are different at each growth stage. The nitrogen requirement in the generative phase is relatively high because the process of panicle formation and grain filling occurs at this stage. Several methods can be used to monitor nitrogen content in rice, one of which is using remote sensing methods. With the vegetation index approach, the nitrogen content of rice plants is estimated through data analysis of the light spectrum reflected by the leaf. Sentinel-2 satellite imagery was used in this research, and several vegetation indexes such as OSAVI, GNDVI, and SRRE were applied to form an estimation model using the regression method. From the results, three vegetation indexes positively correlate with nitrogen content in rice crops. The SRRE index gives the highest correlation coefficient value of 0.692, while the correlation coefficient value for GNDVI is 0.498, and OSAVI is only 0.470. The estimation map of the nitrogen content of rice crops was obtained based on the estimation model made by linear regression between SPAD-based nitrogen content data and the best vegetation index using the SRRE index. The analysis shows that the nitrogen content of rice plants estimated in the paddy fields of Karangjati Subdistrict is dominated by nitrogen values with optimum classification.


Keywords


Generative; Nitrogen; Sentinel-2; SPAD; Vegetation Index



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DOI: https://doi.org/10.22146/ijg.88571

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