PEMANFAATAN NORMALIZED GREEN RED DIFFERENCE INDEX (NGRDI) UNTUK MENDUGA KADAR N-TOTAL PADA LAHAN PADI DI KABUPATEN PAMEKASAN

Zuelfiekar Akmil Rida; Kurniawan Sigit Wicaksono

doi:10.21776/ub.jtsl.2023.010.2.32

Authors

Zuelfiekar Akmil Rida Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya
Kurniawan Sigit Wicaksono Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

DOI:

https://doi.org/10.21776/ub.jtsl.2023.010.2.32

Keywords:

NGRDI, nitrogen, remote sensing, spatial, vegetation index

Abstract

Inefficient fertilization is the cause of decreased rice production. This is due to the inappropriate use of fertilizers. The absence of information on soil nitrogen content in their area causes farmers not to apply fertilizer properly. Analysis of soil nitrogen content in Pamekasan Regency requires much time, cost, and effort. Remote sensing methods can be used to obtain information on soil nitrogen levels by reducing the number of samples used. This study aims to estimate nitrogen content in rice fields using the vegetation index in the form of NGRDI (Normalized Green Red Difference Index). This research was conducted by purposive random sampling method based on 40 land map units formed in Pamekasan Regency, laboratory analysis, statistical analysis, and making distribution maps. The results showed that there was a significant relationship between the NGRDI pixel value and the nitrogen content, with a correlation value of -0.42. The regression equation results obtained from the NGRDI value with nitrogen content are y = -0.269x + 0.139. The accuracy test was carried out by the RMSE method, and the result was 0.027. This shows that the NGRDI index can estimate soil nitrogen content in Pamekasan Regency

Downloads

Download data is not yet available.

References

Anatoly, A., Gitelson, Y., Kaufman, J., Stark, R. and Rundquist, D. 2002. Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment 80(1):76-87. https://doi.org/10.1016/S0034-4257(01)00289-9

Antonia, S.A. dan Arfianto, E.D. 2015. Analisis faktor-faktor yang mempengaruhi profitabilitas perbankan (studi pada bank umum Go Public yang listed di Bursa Efek Indonesia Tahun 2011-2013). Diponegoro Journal of Management 4(2):148-159.

Atzberger. 2013. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sensing 5(2): 949-981. https://doi.org/10.3390/rs5020949

Badan Pusat Statistik. 2020. Luas Panen dan Produksi di Provinsi Jawa Timur 2019. https://pamekasankab.bps.go.id/pressrelease/2020/06/30/11/luas-panen-dan-produksi-padi-di-provinsi-jawa-timur-2019.html. Diakses pada tanggal 26 Mei 2022.

Balai Penelitian Tanah. 2009. Petunjuk teknis (edisi 2): Analisis Kimia Tanah, Tanaman, Air, dan Pupuk. Balai Besar Litbang Sumber Daya Lahan Pertanian. Badan Penelitian dan Pengembangan Pertanian. Departemen Pertanian, Bogor.

Bashit, N., Yudo P. dan Andri S. 2019. Klasifikasi berbasis objek untuk pemetaan penggunaan lahan menggunakan Citra SPOT 5 di Kecamatan Ngaglik. Jurnal Teknik 40(2):122-128.https://doi.org/10.14710/teknik.v39i3.23050

Efendy, M., Sidik, R.F. dan Muhsoni, F.F. 2014. Pemetaan potensi pengembangan lahan tambak garam di pesisir utara Kabupaten Pamekasan. Jurnal Kelautan 7(1):1-14.

ESA. 2015. Sentinel-2 User Handbook. ESA Standard Document User Handbook. European Space Agency.

Estes, J., Kline, K. and Collins, E. 2001. Remote Sensing. International Encyclopedia of the Social & Behavioral Sciences, doi:10.1016/B0-08-043076-7/02526-2.https://doi.org/10.1016/B0-08-043076-7/02526-2

Ghozali, I. 2016 Aplikasi Analisis Multivariete dengan Program IBM SPSS 23. Edisi 8. Semarang: Badan Penerbit Universitas Diponegoro.

Ginting, A. 2017. Pengaruh pemberian nitrogen dan fosfor terhadap pertumbuhan legum Calopogonium mucunoides, Centrosema pubescens dan Arachis pintoi. Universitas Jambi Press. Jambi.

Hunt, E., Cavigelli, M., Daughtry, C.., Mcmurtrey, J. and Walthall, C. 2005. Evaluation of digital photography from model aircraft for remote sensing of crop biomass and nitrogen status. Precision Agriculture 6:359-378, doi: https://doi.org/10.1007/s11119-005-2324-5.

Hutasuhut, A.W., Anggraeni, W. dan Raras, T. 2014. Pembuatan aplikasi pendukung keputusan untuk peramalan persediaan bahan baku produksi plastik blowing dan inject menggunakan metode ARIMA (Autoregressive Integrated Moving Average) di CV. Asia. Jurnal Teknik ITS. 3(2), doi: https://doi.org/10.12962/j23373539.v3i2.8114.

Munawar, A. 2011. Kesuburan Tanah dan Nutrisi Tanaman. Bogor (ID): IPB Press.

Murti, S.H. 2012. Pengaruh resolusi spasial pada citra penginderaan jauh terhadap ketelitian pemetaan penggunaan lahan pertanian di Kabupaten Wonosobo. Jurnal Ilmiah Geomatika 18(1):84-94.

Ngadenin, L. Subiantoro, K.. dan Widana, S. 2014. Studi awal geologi di wilayah Kabupaten Pamekasan untuk mendukung pemilihan calon tapak instalasi desalinasi nuklir. Eksplorium 35(1):29-42.

Patti, P.S., Kaya, E. dan Silahooy, C. 2018. Analisis status nitrogen tanah dalam kaitannya dengan serapan N oleh tanaman padi sawah di Desa Waimital, Kecamatan Kairatu, Kabupaten Seram Bagian Barat. Agrologia 2(1):51-58. https://doi.org/10.30598/a.v2i1.278

Sarwono, J. 2006. Metode Penelitian Kuantitatif dan Kualitatif. Yogyakarta: Graha Ilmu.

Supriyadi, S. 2007. Kesuburan tanah di lahan kering Madura. Jurnal Embryo 4(2):124-131.