Abstract
This study aims to know prediction the productivity of rice by using Landsat Satellite data 8 in Karawang District. The research method used was descriptive, infrensial and modeling. For a presumes the productivity of the rice being estimated by using the Enhanced Vegetation Index (EVI). Prediction of productivity based on linear regression models between EVI from satellite imagery analysis results with the highest productivity of the rice plant of the Department of Agriculture Karawang District. The results showed that the analysis of Landsat 8 Satellite images obtained the average EVI value from 2017 and 2018, in 2017 the average EVI value was 0.36. while in the year 2018 average value of EVI was 0.48. Estimates of rice productivity in Karawang District 2017 and 2018 were obtained by using the regression equation model the relationship between EVI value and rice productivity yielding Anova obtained Sig = 0.000 <0.05, so that a significant model means the model can be used to estimate rice crop productivity. The z-Test Two Sample for Means statistical test for productivity on the EVI model and in the field shows that in 2017 Zhit = -0.0015 and 2018 Zhit = -0.0002 with areas of rejection and acceptance H0 then Zhit is located in the reception area which produces both results not real difference. This shows that the equation model can be said to be close to the yield of rice productivity in Karawang District and the prediction of rice productivity in the Karawang District in 2019 which is equal to 7.447 tons / ha.
Highlights
Peningkatan produksi baik dari sisi intensifikasi maupun ekstensifikasi, permasalahan terkait padi cukup beragam diantaranya terkait dengan distribusi produksi serta inventarisasi dan pernantauan area produksi
Nilai produktivitas per Kecamatan yang diperoleh merupakan angka pada hakikatnya adalah nilai rata-rata dari produktivitas seluruh lahan sawah yang ada di Kecamatan tersebut
Pendugaan Produktivitas Tanaman Padi Sawah Melalui Analisis Citra Satelit
Summary
Pengolahan Data Awal Pengolahan data terdiri dari koreksi radiometrik, geometrik dan proyeksi data citra. Koreksi radiometrik yang harus dilakukan pada data L1b (Produk Pustekdata) adalah Bow-tie, yaitu penghilangan adanya duplikasi baris, destripping. Pengolahan dapat dilakukan dengan bantuan SW antara lain ENVI, MRT Swath (produk USGS). Koreksi Geometrik dan proyeksi peta bisa dilakukan dengan bantuan SW ENVI, MRT Win (produk USGS). Pengolahan Data EVI Citra penginderaan jauh yang dianalisis dalam penelitian ini adalah hasil perekaman sensor Satelit Landsat-8 (OLI). Tanggal akuisisi yang dipilih adalah pada periode bulan April-Agustus 2018. Adapun persamaan untuk memperoleh nilai EVI seperti yang dirumuskan oleh Domiri (2005) yaitu: EVI. Domiri (2005) mengkombinasikan formula EVI akhir dengan SAVI dalam kondisi pengaruh atmosfer yang tidak signifikan yang diindikasikan oleh reflektansi kanal biru lebih besar dari reflektansi kanal merah. Sehingga algoritma komputasi EVI dapat ditulis sebagai berikut: If ρblue ρred orρred ρnir else
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