Judul: Identifikasi Kelembaban Tanah dengan Pemanfaatan Gelombang Mikro Sensor PALSAR Satelit ALOS (Studi Kasus Kabupaten Bekasi dan Sekitarnya)
Abstrak: Soil moisture one of important factor in determining the level of dryness of the land. Therefore, monitoring the characteristics of spatial and temporal distribution of soil moisture is essential. Effective method for monitoring soil moisture on a large scale is by remote sensing. This research using the image of the PALSAR ALOS satellite which is a type of SAR (Synthetic Aperture Radar) that is sensitive to soil moisture content. Detection of soil moisture content was obtained based on the dielectric constant values that derived from values of backscatter of radar image. The purpose of this research is to study the characteristics and identify the soil moisture levels in some areas land cover Bekasi District and it’s surrounding using PALSAR ALOS satellite imagery. There are two empirical models used in soil moisture model prediction, they are the Dubois and top models. Both methods are suitable for open areas with a relatively flat surface. Dubois used to predict the value of dielectric constant and surface roughness, on the other hand the Top models used to predict soil moisture based on the value of the dielectric constant. This research tried to study the six types of land cover of water bodies, paddy fields, fallow paddy fields, open land, the land building, and land vegetation. The results showed that the highest dielectric constant values are found in water bodies with an average value of 7.9 and the lowest is in the fallow paddy field with an average value of 5.2. The highest soil moisture values are found in the land of vegetation with an average value of 25% and the lowest is in the fallow paddy field with a value of 20%.
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Judul: Aplikasi dan Evaluasi Citra ALOS PALSAR Resolusi 50 m, Resolusi 12,5 m, dan Resolusi 6 m untuk Identifikasi Tutupan Lahan (studi kasus di Kabupaten Humbang Hasundutan, Kabupaten Tapanuli Utara, dan Kabupaten Samosir)
Abstrak: The application of remote sensing technology for rasionalization land resources data usage has more benefit than data collecting in conventional ways. Remote sensing techniques have been used in Indonesia for forest inventory and forest resources monitoring. Indonesia‟s geographical position where is in the tropics area that has vast cloud cover limits the use of optical satellite image data. To overcome the optical satellite image weakness, active remote sensing system (radar) is currently available. One of the satellites carrying radar sensor which was launched by the Japanese government is ALOS (Advanced Land Observing Satellite) with PALSAR (Phased Array type L-band Synthetic Aperture Radar) as its one of the sensor. This sensor is an active microwave sensor which has capability to penetrate thick cloud layer. The objective of this research is to analyze the ability of ALOS PALSAR satellite image of 50 m, 12.5 m, and 6 m resolutions on land cover classification at Humbang Hasundutan Regency, North Tapanuli Regency, and Samosir Regency. The observation has delivered 16 land cover classes, which are as follow: water body, harvested rice field, cultivating rice field, just-planted rice field, bushes, coffee plantation, dry land agriculture, town settlement, village settlement, bare land, nature forest, Eucalyptus plantation year 2010, Eucalyptus plantation year 2009, Eucalyptus plantation year 2006, Eucalyptus plantation year 2007, and Eucalyptus plantation year 2008. The result of digital interpretation of the ALOS PALSAR satellite image 50 m, 12.5 m and 6 m resolutions obtained 6 classes of land cover which are as follows: water body, rice field, dry land agriculture, settlement, bare land, and tree vegetation by different value of proportion correct. ALOS PALSAR of 50 m, 12.5 m and 6 m resolutions, each has proportion correct in consequence 62.1%, 50.5% and 68,9% Visual analysis, the result of ALOS PALSAR image with resolution 50 m obtained 8 classes of land cover,which are as follows: water bodu, dry land agriculuture, settlement, harvested rice field, young forest plantation, middle-old forest plantation, nature forest, dan bare land. Whereas, accuration and separability analysis of ALOS PALSAR image of 50 m resolution has regular accuracy value 59.15% and kappa accuracy 53.48%. The result of the interpretation raising-ability analysis of ALOS PALSAR image of 12.5 m and 6 m resolutions to the ALOS PALSAR image of 50 m resolution are able to provide additional land cover classes, clarify the delineation and make easier the identification of land cover at the satellite image.
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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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