Judul: Pemantauan Pertumbuhan Padi Menggunakan L-Band SAR Berbasis Teori Dekomposisi: Studi Kasus Subang
Abstrak: Food problems in Indonesia cannot be avoided, although Indonesia is often referred to as an agricultural country where predominant livelihood is farming. As a matter of fact, there are still a lot of food shortages along increasing number of inhabitants. Rice is the main staple food in Indonesia, therefore monitoring rice field is important information for better agricultural planning. Monitoring with optical remote sensing would be on stake for Indonesia or tropical regions considering high cloud cover. SAR (Synthetic Aperture Radar) provides an alternative in the provision of data for such purposes, especially with polarization technology. As a system that has its own energy source, irrespective to source of solar energy, a SAR system can operate day and night in virtually all weather conditions, because microwaves can penetrate clouds, smoke and rain. This property is very useful for time sensitive applications such as sensing of agricultural crops or natural disasters. Earlier studies primarily focused on the use of backscatter data. Further development of the SAR technology allows analysis of fully polarization SAR data, which are generally more complex than backscattering-based analysis. Fully polarization SAR analysis procedures that are currently inviting attention is the polarimetric decomposition. This study discusses an application of the Cloude-Pottier decomposition theory in assessment of growth phase of Ciherang rice. Using this theory, a complex fully polarimetric data can be converted into three units of analysis, i.e. Entropy (H), Alpha Angle (􀄮) and Anisotropy (A). In this study, blocks of rice cultivation owned by PT. Sang Hyang Seri, provided major field information for detailed analysis. This research indicated that the Cloude-Pottier decomposition theory was able to describe characteristics of different levels of rice growth. The analysis showed that Entropy played an important role in distinguishing plants age. Distribution of entropy corresponded to various phases of rice growth. Aging rice plants tend to coincide to increasing value of entropy. Entropy became smaller in young rice plants, because of a decrease in the number of leaves or density of plant canopy and therefore soil contribution was dominant. Although the alpha angle was found useful to describe scattering type, this parameter is less visible to contribute significantly to the interpretation of data.
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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: Infeksi Virus Parainfluenza Pada Anjing
Abstrak: Virus parainfluenza anjing termasuk famili Paramyxoviridae, berbentuk pleomorf dengan ukuran bervariasi (bergaris tengah antara 100-500 nm), berpembungkus peka ether, berisi genom RNA dan secara serologis mempunyai kesamaan dengan virus SV-5 kera; dikenak sebagai salah satu kausa penting dari sindrom "kennel cough". Infeksinya dapat mengenai anjing semua umur yang belum pernah terinfeksi atau mendapatkan vaksinasi mengakibatkan gejala klinis ringan yang terbatas pada traktus respirasi atu infeksi yang secara klinis tidak memperlihatkan gejala nyata. Gejala klinis yang nampak setelah masa inkubasi (1-5 hari) terlewati berupa batuk yang tidak berat selama beberapa hari, berbagai tingkat tonsilitis dan pharyngitis dan kadang-kadang ditemukan kenaikan temperatur rektal antara 1-2 derajat C dari temperatur normal rat-rata. Anjing terinfeksi mengandung virus pada traktus respirasi bagian atas dan bawah serta limfonoduli sampai hari ke 9 setelah infeksi. Penyebaran virus antar anjing terjadi secara aerogen.
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