Judul: Penggunaan Citra Satelit Sentinel-2 untuk Menduga Nilai Biomassa Atas Permukaan Tanah (Studi Kasus: Kawasan Restorasi Pesanguan, Lampung)
Abstrak: Hutan berperan penting dalam mitigasi perubahan iklim karena berfungsi sebagai penyimpan karbon yang diserap dari atmosfer melalui proses fotosintesis. Biomassa di atas permukaan tanah (AGB) dalam tegakan pohon adalah cadangan karbon terbesar dalam hutan. Untuk menduga biomassa dapat menggunakan penginderaan jauh. Penelitian ini bertujuan mencari kanal spektral radians pada citra satelit Sentinel-2 untuk menduga nilai AGB melalui Analisis Komponen Utama (AKU). Analisis ini memerlukan data pengukuran peubah persamaan allometrik di lapangan pada petak 4, 5A, dan 5B, sehingga diperoleh persamaan regresi yang dapat menjelaskan hubungan antara biomassa dengan variabel nilai spektral radians pada setiap kanal citra Sentinel-2B dan NDVI. Nilai rata-rata cadangan karbon hasil pengukuran lapang pada petak 4, 5A, dan 5B berturut-turut adalah 52,1 ± 31,5; 32,7 ± 15,7; dan 42,5 ± 16 ton C ha-1. Persamaan regresi linear yang terbentuk adalah biomassa = 150,573 – 4,217X1 – 1,61X2 + 0,131X3 – 2,915X4 – 29,503X5 + 234,006X6 dengan X adalah band 4, 5, 8A, 11, 12, dan NDVI. Model ini menghasilkan nilai karbon pada masing-masing petak sebesar 45,8 ± 3,2; 37 ± 11,5; dan 46,5 ± 8,6 ton C ha-1. Hasil model menunjukkan bahwa spektral radians Sentinel-2 dapat digunakan untuk menduga nilai AGB. Namun, nilai RMSE (25,7 ton C ha-1) antara hasil pengukuran allometrik di lapang dengan model menunjukkan adanya hubungan yang belum dapat dijelaskan melalui persamaan tersebut. Akurasi hasil dari persamaan ini masih perlu ditingkatkan melalui perbaikan metode pengukuran lapangan untuk mengukur AGB seluruh vegetasi yang tumbuh dan meningkatkan jumlah titik sampelnya., Forest plays an important role in mitigating climate change as they serve as carbon storage absorbed from the atmosphere through photosynthesis. Aboveground biomass (AGB) in tree stands is the largest carbon reserve in forests. Estimating biomass can be performed using remote sensing. The study aimed to identify spectral band in Sentinel-2 satellite imagery to estimate AGB values through Principal Component Analysis (PCA). This analysis requires measurement data for allometric equations in the field in plots 4, 5A, and 5B, so that regression equations can be obtained that can explain the relationship between biomass and spectral radiance value variables in each Sentinel-2B and NDVI image channels. The average value of carbon stocks of field measurement results on plots 4, 5A, and 5B is 52,1 ± 31,5; 32,7 ± 15,7; and 42,5 ± 16 tons C ha-1. The linear regression equation generated is biomass = 150,573 – 4,217X1 – 1,61X2 + 0,131X3 – 2,915X4 – 29,503X5 + 234,006X6 with X being bands 4, 5, 8A, 11, 12, and NDVI. This model produces a carbon value on each plot of 45,8 ± 3,2; 37 ± 11,5; and 46,5 ± 8,6 tons C ha-1. The results of the model suggest that spectral radiance Sentinel-2 can be used to estimate AGB values. However, the RMSE value (25,7 tons C ha-1) between the results of allometric measurements in the field and the model shows an unexplained relationship through the equation. The accuracy of the results of this equation still needs to be improved through improved field measurement methods to measure the AGB of the entire growing vegetation and increase the number of sample points.
Keyword: PCA, allometric, biomass, carbon stock, spectral radiance

Judul: Model Penduga Biomassa Hutan Alam Lahan Kering Menggunakan Citra ALOS PALSAR Resolusi 50 M di Areal Kerja PT. Trisetia Intiga
Abstrak: The increase of Green House Gases (GHG), particularly carbon dioxide in the atmospheric is one factor that affect the global warming. One cause of the increase was due to emission of carbon that came from deforestation and land degradation. In the mitigation process for reducing the impact of global warming, one crusial activity is estimation of carbon sequestered in the vegetation. Commonly, carbon content sequestered at vegetation is derived from biomass estimation either from above ground biomass or below ground biomass. In this study, the focus was on estimation of the above ground biomass using remote sensing technology. Nowdays, the development of remote sensing techniques had been widely used for providing various information related to natural resources. Indonesia which is located in the tropical region, have several handicaps in using optical remote sensing due to cloud covers during wet season and smoke and haze during dry season. For the above reason, this study emphasizes on the use of radar image technology for estimating the above ground biomass. In this study the used radar image is ALOS PALSAR (Advance Land Observing Sattelite – Phase Array L-band Synthetic Aperture Radar), that had been launched in Januari 2006 by the Japanese government. This sensor is an active microwave sensor which has capability to penetrate thick cloud layer. An active microwave sensor be accepted dan reflectanced by several diresction that usually called polarization. Polarization is the vector direction from electromagnetic microwave on vertical line (V) and horizontal line (H). The main objective of this study is to develop the biomass estimation model using 50 meter resolution of ALOS PALSAR image in concession of PT. Trisetia Intiga, Central Kalimantan. Biomass model was developed by analyzing the relationship between backscatter value and field biomass. Backscatter value from tree polarization images, namely HH, HV, and HH/HV were analyzed simultaneously with field biomassa that derived using Ketterings allometric equation. In this study the obtained stand structure equation, Y=2482 ℮-0,04X with negative exponential or J-reverse form having realtively steep slope. From the stand structure equation, then it can be concluded that stand condition within the study area is belonged to logged over area secondary forest, where tree density with diameter less or equal to 60 cm is relatively low in comparison with the smaller tree size. From 30 sample plots measured, the above ground biomass is ranged from 68,03 ton/ha to 599,43 ton/ha with coefficient of variation (CV) equal to 50,29%. Proportionaly, the highest biomass is come from tree biomass (64,97%), then followed by biomass of necromass (20,13%), pole biomass (12,16%), sapling biomass (2,75%), litter biomass (3,3x10-5), and undergrowth biomass (5x10-5). The correlation and regretion analyses between backscatter value and field biomass show that there are 38 statistically significant equations having R² ≥ 50%. However, the verification analysis found that only two models identified as the best models having no-significant X²-test, low RMSE (Root Mean Square Error), low bias, and mean deviation < 10%. The best models are: 1) AGB = 3880.40613930209exp (0.250184794335192 HV) with coefficient determination (R²) of 56% and RMSE of 0.47%. 2) AGB = 1022.27050600692 exp (-0.0114464608949151 HV²)
Keyword: 

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.
Keyword: