ESTIMASI PRODUKSI JAGUNG (Zea Mays L.) DENGAN MENGGUNAKAN CITRA SENTINEL 2A DI SEBAGIAN WILAYAH KABUPATEN JENEPONTO PROVINSI SULAWESI SELATAN

https://doi.org/10.22146/teknosains.36885

Laode Muhamad Irsan(1*), Sigit Heru Murti(2), Prima Widayani(3)

(1) Program Pascasarjana Penginderaan Jauh, Universitas Gadjah Mada
(2) Program Pascasarjana Penginderaan Jauh Universitas Gadjah Mada
(3) Program Pascasarjana Penginderaan Jauh Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Production is a real benchmark in successful crop management which is the most important output economically. Currently, corn production estimates are generally done by conventional means through field surveys. This conventional way requires a high cost and a long time. Appropriate agricultural management requires precise and accurate information or data to increase production and economic benefits. Sentinel 2A remote sensing satellite data is potential to be used in assessment of corn production estimation. The purpose of this research is to make land use mapping and corn production estimation by using spectral approach. Estimated data were obtained from Sentinel 2A image by mapping land use and modeling of vegetation index (NDVI, SAVI, MSAVI, TSAVI, EVI, and ARVI) then compared with data of corn production in the field. The result of data analysis shows land use mapping using Sentinel 2A image has 91% confidence level. Calculation of production estimation can show the accuracy of 74% with RMSE 0.69. The highest correlation is estimated production with EVI index model with regression correlation equal to 74% which shows strong correlation on both variables. Estimated production of corn in 2017 in Jeneponto Regency is 178,660,69 tons.

Keywords


Remote Sensing, Sentinel 2A Image, Vegetation Index, Production Estimation

Full Text:

PDF


References

[BPS], Badan Pusat Statistik. 2016. Kabupaten Jeneponto Dalam Angka. BPS Kabupaten Jeneponto. Tamalatea.

Chavez, P. S. (1996). Image-based atmospheric corrections-revisited and improved.
Photogrammetric Engineering & Remote Sensing, 62(9), 1025–1036.

Harahap, I.Y., Winarna, dan E.S. Sutarta. 2000. Produktivitas Tanaman Kelapa Sawit: Tinjauan dari Aspek Tanah dan Iklim. Pertemuan Teknis Kelapa Sawit I. Pusat Penelitian Kelapa Sawit. Medan 25-26 April 2000.

Howard, John A. 1991. Remote Sensing of Forest Resources : Theory and
Application
. Champman and Hall. London.

Jin, X., Ma, J., Zidan, W., Kaishan, S. 2015. Estimation of Maize Residue Cover Using Landsat-8 OLI Image Spectral Information and Textural Features. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun. China.

Murti, S. H. 2014. Pemodelan Spasial Untuk Estimasi Produksi Padi dan Tembakau Berdasarkan Citra Muliresolusi (Kasus Untuk Produksi Padi di Kabupaten Wonosobo dan Sragen, serta Produksi Tembakau di Kabupaten Temanggung, Provinsi Jawa Tengah), Disestasi, Universitas Gajah Mada. Yogyakarta.

Kementrian Pertanian RI. 2015. Statistik Pertanian 2015. Pusat Data dan Sistem Informasi Pertanian. Jakarta.

Kementrian Pertanian RI. 2016. Outlook Jagung. Pusat Data dan Sistem Informasi Pertanian. Jakarta.

Martono, D. N. 2008. Aplikasi Teknologi Penginderaan Jauh Dan Uji Validasinya Untuk Deteksi Penyebaran Lahan Sawah dan Penggunaan/ Penutupan Lahan. Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Yogyakarta, 47-56.

Rueda-Ayala, V., Kunapuli, S., dan Maiguashca, J. 2015. Development of Yield Prediction Models In The Maise Crop Using Spectral Data For Precision Agriculture Aplication. Ecuador Es Calidad, 2(1):16-22.

Skakun, S., Vermote. E., Jeans, C. R., dan Belen F. 2017. Cobined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assesment at Regional Scale, AIMS Geosciences, 3 (2): 163-186.

Soria, R. J., Y. Fernandes dan Rebeca G. R. 2004. Methodology for prediction of corn yield using remote sensing satellite data in Central Mexico, INIFAP, Meksiko.

Sugiyono. 2014. Statistik Untuk Penelitian. Bandung: Alfabeta.

Wahyunto, W., dan Bambang, H. 2006. Pendugaan Produktivitas Tanaman Padi Sawah Melalui Analisis Citra Satelit. Bogor: Peneliti Balai Besar Litbang Sumberdaya Lahan Pertanian.



DOI: https://doi.org/10.22146/teknosains.36885

Article Metrics

Abstract views : 3689 | views : 6377

Refbacks

  • There are currently no refbacks.




Copyright (c) 2019 Laode Muhamad Irsan, dkk

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.




Copyright © 2024 Jurnal Teknosains     Submit an Article        Tracking Your Submission


Editorial Policies       Publishing System       Copyright Notice       Site Map       Journal History      Visitor Statistics     Abstracting & Indexing