Program Studi Teknik Geodesi Fakultas Teknik, Unversitas Diponegoro, Indonesia
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@article{JGUndip9958, author = {Ardiansyah Ardiansyah and Sawitri Subiyanto and Abdi Sukmono}, title = {IDENTIFIKASI LAHAN SAWAH MENGGUNAKAN NDVI DAN PCA PADA CITRA LANDSAT 8 (Studi Kasus: Kabupaten Demak, Jawa Tengah)}, journal = {Jurnal Geodesi Undip}, volume = {4}, number = {4}, year = {2015}, keywords = {}, abstract = { ABSTRAK Padi ( Oryza sativa, sp ) merupakan salah satu tanaman pertanian yang paling penting di Indonesia, karena beras merupakan makanan pokok lebih dari 90% penduduk Indonesia. Berdasarkan data Susenas-BPS, konsumsi beras di Indonesia per-kapita pada tahun 2013 sebesar 97,4045 kg/kapita/tahun. Berdasarkan Data Statistik Pertanian tahun 2014 Kementrian Pertanian, luas lahan sawah Indonesia pada tahun 2013 sebesar 8.112.103 ha. Pada tahun 2017, Pemerintah mempunyai misi mewujudkan Indonesia menjadi Swasembada Pangan. Oleh karena itu, Pemerintah harus dapat mengupayakan stabilitas pemenuhan kebutuhan pokok akan pangan, seperti pemetaan lahan sawah. Pemetaan lahan sawah yang akurat dapat menggunakan metode yang cepat dan mudah seperti Penginderaan Jauh. Pada penelitian ini , dilakukan identifikasi lahan sawah menggunakan citra Landsat 8 multitemporal berdasarkan Masa Tanam Padi 1 di Kabupaten Demak yang berkisar antara akhir bulan Oktober 2013 hingga awal bulan Maret 2014. Metode yang digunakan yaitu Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA) dan kombinasi kanal. Klasifikasi citra dilakukan dengan menggunakan sembilan kelas, yaitu air, pemukiman, m angrove , kebun, tegalan, sawah 1, sawah 2, sawah 3 dan sawah 4. Hasil analisis menunjukkan luas lahan sawah yang diperoleh dari metode PCA sebesar 50.009 ha, kombinasi kanal sebesar 51.016 ha dan metode NDVI sebesar 45.893 ha. Tingkat ketelitian pada metode PCA 84,848%, kombinasi kanal mempunyai ketelitian 81,818% dan NDVI mempunyai ketelitian 75,758%. Kata Kunci : sawah, Landsat 8 , NDVI, PCA, kombinasi kanal ABSTRACT Paddy (Oryza sativa, sp) is one of the most important agricultural sector in Indonesia, because rice is the main food for more than 90% of Indonesia's population. Based on BPS - Susenas data, consumption of rice per capita in 2013 amounted to 97 . 4045 k g /capita / year. Based on Statistical Data of Agriculture Ministry of Agriculture by 2014 , Indonesia rice field area in 2013 amounted to 8 , 112 , 103 ha. In 2017, the Government has the m ission of realizing Indonesia became s elf-sufficient in food . Therefore, the Government should be able to seek the stability of the fulfillment of basic needs for food, such as wetlands mapping. It’s accurate mapping can use a quick and easy method such as Remote Sensing. In this study , carried out the identification of rice fields using multitemporal Landsat 8 based on Rice Planting Time 1 st in Demak that range between the end of October 2013 to early March 2014. The methods which was used Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA) and c ombination bands. I mage classification is processed by using nine classes, those are water, settlements, mangrove, gardens, fields , rice field s 1 st , rice field s 2 nd , rice field s 3 rd and rice field s 4 th . The results showed the rice fields area obtained from the PC A method was 50,009 ha , combination bands was 51,016 ha and NDVI method was 45,893 ha . The accuracy level was obtained PCA method ( 84.848 % ), combination bands ( 81.818 % ), and NDVI method ( 75.758% ). Keywords : rice field s , Landsat 8 , NDVI, PCA, combination bands *) Penulis, Penanggungjawab }, issn = {2809-9672}, pages = {316--324} doi = {10.14710/jgundip.2015.9958}, url = {https://ejournal3.undip.ac.id/index.php/geodesi/article/view/9958} }
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ABSTRAK
Padi (Oryza sativa, sp) merupakan salah satu tanaman pertanian yang paling penting di Indonesia, karena beras merupakan makanan pokok lebih dari 90% penduduk Indonesia. Berdasarkan data Susenas-BPS, konsumsi beras di Indonesia per-kapita pada tahun 2013 sebesar 97,4045 kg/kapita/tahun. Berdasarkan Data Statistik Pertanian tahun 2014 Kementrian Pertanian, luas lahan sawah Indonesia pada tahun 2013 sebesar 8.112.103 ha. Pada tahun 2017, Pemerintah mempunyai misi mewujudkan Indonesia menjadi Swasembada Pangan. Oleh karena itu, Pemerintah harus dapat mengupayakan stabilitas pemenuhan kebutuhan pokok akan pangan, seperti pemetaan lahan sawah. Pemetaan lahan sawah yang akurat dapat menggunakan metode yang cepat dan mudah seperti Penginderaan Jauh.
Pada penelitian ini, dilakukan identifikasi lahan sawah menggunakan citra Landsat 8 multitemporal berdasarkan Masa Tanam Padi 1 di Kabupaten Demak yang berkisar antara akhir bulan Oktober 2013 hingga awal bulan Maret 2014. Metode yang digunakan yaitu Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA) dan kombinasi kanal. Klasifikasi citra dilakukan dengan menggunakan sembilan kelas, yaitu air, pemukiman, mangrove, kebun, tegalan, sawah 1, sawah 2, sawah 3 dan sawah 4.
Hasil analisis menunjukkan luas lahan sawah yang diperoleh dari metode PCA sebesar 50.009 ha, kombinasi kanal sebesar 51.016 ha dan metode NDVI sebesar 45.893 ha. Tingkat ketelitian pada metode PCA 84,848%, kombinasi kanal mempunyai ketelitian 81,818% dan NDVI mempunyai ketelitian 75,758%.
Kata Kunci : sawah, Landsat 8, NDVI, PCA, kombinasi kanal
Paddy (Oryza sativa, sp) is one of the most important agricultural sector in Indonesia, because rice is the main food for more than 90% of Indonesia's population. Based on BPS-Susenas data, consumption of rice per capita in 2013 amounted to 97.4045 kg/capita/year. Based on Statistical Data of Agriculture Ministry of Agriculture by 2014, Indonesia rice field area in 2013 amounted to 8,112,103 ha. In 2017, the Government has the mission of realizing Indonesia became self-sufficient in food. Therefore, the Government should be able to seek the stability of the fulfillment of basic needs for food, such as wetlands mapping. It’s accurate mapping can use a quick and easy method such as Remote Sensing.
In this study, carried out the identification of rice fields using multitemporal Landsat 8 based on Rice Planting Time 1st in Demak that range between the end of October 2013 to early March 2014. The methods which was used Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA) and combination bands. Image classification is processed by using nine classes, those are water, settlements, mangrove, gardens, fields, rice fields 1st, rice fields 2nd, rice fields 3rd and rice fields 4th.
The results showed the rice fields area obtained from the PCA method was 50,009 ha, combination bands was 51,016 ha and NDVI method was 45,893 ha. The accuracy level was obtained PCA method (84.848%), combination bands (81.818%), and NDVI method (75.758%).
Keywords : rice fields, Landsat 8, NDVI, PCA, combination bands
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Jurnal Geodesi Undip
Departemen Teknik Geodesi, Fakultas Teknik, Universitas Diponegoro