Judul: Estimating Above Ground Trees Biomass Of Forest Cover Using Field Measurement And QuickBird Image In Lore Lindu National Park-Central Sulawesi
Abstrak: Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting (Muukkonen and Heiskanen, 2006). The biomass of forest provides estimates of the carbon pools in forest vegetation because about 50% of it is carbon. Direct measurement of biomass on the ground is time consuming (expensive), and repeated measurements, if they occur at all, are generally limited to 10 year interval. The possibility that above ground forest biomass can be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass is possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The method of this research use an approach of estimating the biomass that combines field studies (forest inventory data), analysis of multispectral satellite imagery, allometric equation and statistical analysis. Forest cover type classification was utilized for analyzing the biomass per pixel in each different cover type. The classifications for each cover type by using the region based different spectral value in each observation plot refer to QuickBird Image. The field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The correlation analysis resulted the main regression equation in estimating the tree biomass of tropical forest, biomass=6E-05DBH2.6705 and biomass= 0.0065e 13.615 NDVI. There are 4 forest cover types observed in this research. Forest cover type A is natural forest without timber extraction (closed canopy). Forest cover type B is natural forest with minor extraction. Forest cover type C is natural forest with major timber extraction. Forest cover type D is agroforestry system. Forest cover type A and B has the higher biomass than C and D, it is about 596.41-618.66 ton/ha and 583.94-622.19 ton/ha. Forest cover type C is 446.65-468.50 ton/ha. Forest cover type D has the lowest biomass is about 193.31-214.34 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees v heterogeneity with minimum disturbance. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass.
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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: 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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