Judul: Analisis citra alos AVNIR-2 untuk pemantauan lahan sawah PT. Sang Gyang Seri, Kabupaten Subang
Abstrak: Dalam menyusun kebijakan pemerintah yang terkait masalah swasembada pangan, data produksi pangan memegang peranan yang penting. Untuk menunjang data tersebut, maka diperlukan pemantauan lahan sawah secara kontinyu. Penginderaan jauh merupakan teknologi yang dapat digunakan untuk tujuan tersebut. Salah satu produk penginderaan jauh yang relatif masih baru adalah citra ALOS (Advanced Land Observing Satellite) Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2). Penelitian ini dimaksudkan untuk mengkaji kinerja data ALOS AVNIR-2 yang diakuisisi pada tanggal 30 Juni 2009 dipadukan dengan teknik analisis pohon keputusan dengan sasaran utama mengidentifikasi wilayah panen dan penanaman baru (permulaan musim tanam) menggunakan algoritma QUEST dan CRUISE. Wilayah yang dijadikan lokasi penelitian adalah PT. Sang Hyang Seri, Kabupaten Subang, Jawa Barat. Analisis pohon keputusan menunjukkan bahwa Band 3 dari citra ALOS AVNIR-2 yang memiliki panjang gelombang 0,61 – 0,69 mikrometer cukup mampu berperan untuk memisahkan tiap fase penutupan lahan sawah baik menggunakan algoritma QUEST maupun CRUISE. Kedua algoritma juga menghasilkan akurasi yang cukup tinggi, yaitu 93,9% untuk QUEST dan 89,3% untuk CRUISE. Dengan demikian, algoritma QUEST lebih baik dibandingkan dengan CRUISE untuk tujuan pemantauan lahan sawah ini. Dalam analisis luasan diketahui bahwa luasan permulaan musim tanam merupakan luasan terbesar dibandingkan dengan luasan fase lainnya, yaitu 1690 Ha untuk QUEST dan 1625 Ha untuk CRUISE. Sedangkan kawasan bera diketahui merupakan luasan terkecil dari total luasan seluruhnya, baik menggunakan algoritma QUEST maupun CRUISE, yaitu 308 Ha untuk QUEST dan 337 Ha untuk CRUISE. Kata kunci: ALOS, AVNIR-2, padi, CRUISE, QUEST
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Judul: Pemantauan Fase Pertumbuhan Padi Menggunakan Sensor AVNIR dan PALSAR Polarisasi Penuh (Studi Kasus PT Sang Hyang Seri, Subang)
Abstrak: Rice is fundamental for most Indonesian people. Monitoring rice field is therefore important in order to obtain information required by food or agriculture planning. This task could be accomplished by using satellite-based remote sensing technology, including ALOS. In this research, ALOS capability in provision rice field information are explored through its two main sensors, i.e. optical-based AVNIR-2 and PALSAR, which is a SAR sensor, primarily focused on fully polarimetric data. ALOS PALSAR data used in this research were acquired in 2007 and 2009, while ALOS AVNIR images were attained in 2008 and 2009. This research shows that NDVI values based on AVNIR-2 fluctuate during both observations. In 2008 and 2009 images, the NDVI range was 0,238-0,549 and -0,209-0,516 respectively. The diversity of NDVI value in rice field was caused by varying growth phases such as vegetative, generative, mature, and pre- harvest. In this research, rice growth phase were studied using linear backscatter analysis using fully polarimetric (PLR) PALSAR image. In many phases, HH consistently produced higher backscatter coefficient compared to other linear polarization components, i.e. HV and VV. Analysis showed that HH is the most suitable polarization for monitoring rice field. This is due to the fact that HH polarization is more sensitive to variations of rice structure in different age levels. Classification using decision tree was implemented by exploiting QUEST and CRUISE algorithms. Using PALSAR image, classification accuracy based on CRUISE and QUEST was 56,36 % and 40 % respectively. Accuracy on AVNIR-2 was higher than PALSAR, i.e. 94,74 % and 90,91 % using CRUISE and QUEST respectively.
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Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
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