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

Laode Muhamad Irsan, Laode Muhamad Irsan and Sigit Heru Murti, Sigit Heru Murti and Prima Widayani, Prima Widayani (2019) ESTIMASI PRODUKSI JAGUNG (Zea Mays L.) DENGAN MENGGUNAKAN CITRA SENTINEL 2A DI SEBAGIAN WILAYAH KABUPATEN JENEPONTO PROVINSI SULAWESI SELATAN. Jurnal ilmiah Sains dan Teknologi, 8 (2). pp. 93-104. ISSN e-ISSN:2443-1311

Text ESTIMASI PRODUKSI JAGUNG (Zea Mays L.) DENGAN MENGGUNAKAN CITRA SENTINEL 2A DI SEBAGIAN WILAYAH KABUPATEN JENEPONTO PROVINSI SULAWESI SELATAN.pdf - Other Download (4MB)

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.

Item Type:	Article
Uncontrolled Keywords:	Remote Sensing, Sentinel 2A Image, Vegetation Index, Production Estimation
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mrs Ni Made Yunia Dwi Savitri
Date Deposited:	17 Nov 2022 01:33
Last Modified:	17 Nov 2022 01:33
URI:	http://eprints.triatmamulya.ac.id/id/eprint/1763

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