Rahmi, Ardia Tiara (2021) Analisis Kebutuhan Air Petak Tersier Berdasarkan Hasil Identifikasi Fase Tanam Menggunakan Citra Sentinel-2 Dan Google Earth Engine (Studi Kasus: Daerah Irigasi Sampean Lama, Kab. Situbondo). Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Terdapat beberapa wilayah di Indonesia yang kekuranga persediaan air untuk kebutuhan irigasi akibat pengaruh iklim, sehingga beberapa di antaranya sering kali mengalami gagal panen karena kekurangan air. Salah satu wilayah yang mengalami masalah tersebut adalah Kabupaten Situbondo. Hal ini dapat disebabkan karena jumlah debit yang keluar dari intake tidak mampu memenuhi seluruh kebutuhan air di petak sawah. Penelitian ini menggunakana indeks vegetasi NDVI dari Citra Sentinel 2 sebagai instrumen untuk mengidentifikasi fase tanam padi dan membuat peta distribusi fase tanam sebagai pedoman untuk menghitung kebutuhan air di petak-petak tersier Kabupaten Situbondo. Pada penelitian kali ini, peneliti akan menggunakan perangkat pengolah citra berbasis cloud yaitu Google Earth Engine dimana pemrosesan dan penyimpanan data dilakukan pada jaringan internet. Nilai NDVI tertinggi terjadi pada tanggal 26 Januari 2019 yaitu Fase Tanam Mid-Season Stage 1 dengan luas sawah 756,91 Ha dan nilai NDVI terendah didapat pada akhir fase tanam tanggal 11 Maret 2020 dengan luas sawah 489,09 Ha. Hasil klasifikasi terbimbing menggunakan metode Machine Learning Random Forest memberikan akurasi yang sangat baik dengan nilai OA 100% dan kappa sebesar 1 pada citra akuisisi 12 Desember 2019. Debit kebutuhan irigasi tertinggi terjadi pada tanggal 25 Februari 2020 sebesar 253,20 lt/dt dan debit kebutuhan air irigasi terendah terjadi pada tanggal 11 maret yang bertepatan dengan masa panen. Berdasarkan hasil perhitungan peneliti, kebutuhan air irigasi pada bulan Desember hingga bulan Januari sudah terpenuhi oleh curah hujan yang terjadi di wilayah UPT Pengairan Situbondo sehingga tidak membutuhkan debit irigasi dari saluran irigasi
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There are several areas in Indonesia that lack of water supply for irrigation needs due to climate influence, so that some of them often experience crop failure due to lack of water. One of the areas experiencing this problem is Situbondo Regency. This is because the amount of discharge that comes out of the intake is not able to meet all the water needs in the rice fields. This study used the NDVI vegetation index from Sentinel 2 imagery as an instrument to identify rice planting phases and create a planting phase distribution map as a guideline for calculating water demand in the tertiary plots of Situbondo Regency. In this research, researchers will use a cloud-based image processing device, namely Google Earth Engine, where data processing and storage is carried out on the internet network. The highest NDVI value occurred on January 26, 2019, namely the Mid-Season Stage 1 planting phase with a rice field area of 756.91 Ha and the lowest NDVI value was obtained at the end of the planting phase on March 11, 2020 with a rice field area of 489.09 Ha. The results of supervised classification using the Machine Learning Random Forest method provide excellent accuracy with an OA value of 100% and a kappa of 1 in the acquisition image on December 12, 2019. The highest discharge needs for irrigation occurs on February 25, 2020, amounting to 253.20 l / s and required discharge The lowest irrigation water occurs on March 11, which coincides with the harvest period. Based on the results of the researchers' calculations, the need for irrigation water from December to January has been fulfilled by the rainfall that occurred in the UPT Irrigation Situbondo area so that it does not need irrigation discharge from the irrigation channel.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Sentinel-2, NDVI, Planting Phase, Water Demand, Random Forest Sentinel-2, NDVI, Fase Tanam Padi, Kebutuhan Air, Random Forest |
| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing |
| Divisions: | Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis |
| Depositing User: | Ardia Tiara Rahmi |
| Date Deposited: | 03 Mar 2021 04:33 |
| Last Modified: | 21 Oct 2021 03:27 |
| URI: | http://repository.its.ac.id/id/eprint/83241 |
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