Judul: A RS/GIS–Based Multi-Criteria Approaches to Assess Forest Fire Hazard in Indonesia (Case Study: West Kutai District, East Kalimantan Province)
Abstrak: Many forest ecosystems in Indonesia have undergone rapid changes, which certainly influencing in the forest structure and fuel properties. In addition to forest structure and fuel changes, increased number of people living in these environments and frequent extreme droughts as impacts of climate changes has led to extraordinary fire events which leads to several environmental problems including loss of forest as carbon sink, loss of biodiversity, transboundary haze pollution, as well as significant economic losses. Better management of forests and fire problems require spatial-temporal assessment providing important information for identifying and prioritizing fire planning needs. Fire hazard map determining the fire vulnerable areas is important information required to take decisions on fire prevention and suppression activities. To be effective, a comprehensive consideration for forest fire hazard assessment must accomodate a wide range of important determining variables that encompass biophysical and anthropogenic factors leading to occurrence of fire. Combining geomatics technology, including remote sensing and geographic information systems with either statistical or analytical hierarchy process (AHP) approaches offer more efficient and powerful on data acquisition and analysis related to fire hazard assessment. In this research different approaches used for assessing forest fire hazard in West Kutai district at different temporal resolutions: short-term and long-term fire probability assessment. Keetch and Byram Drought Index (KBDI) as a drought index indicating the atmospheric dryness used for short-term fire potential assessment. While long-term assessment encompass two different approaches to spatially model fire probability: binary logistic regression model and analytic hierarchy process (AHP). The first model tried to base weights for fire occurence probability map based on historical fires as recorded by satellites (hotspots), while the AHP approach is based on judgement by asking experts in a systematic fashion. The result of this research showed that by combining between the daily KBDI indexs with hotspots occurences indicated that there is a strong positive association between KBDI index with hotspot occurences. The importance level of variable contributing to forest fire occurences resulted from both binary logistic regression model and the AHP model showed a quite similar pattern.
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Judul: Spatial Modelling on Susceptibility of Fires in Peatland, a Case Study in District of Bengkalis, Riau Province
Abstrak: Peatland is one of ecosystem types in Indonesia which plays important role in maintaning terrestrial carbons, hydrological cycles and preserving biodiversity. Recently, most of the peatland (forest and non forest) has been degraded. One of the causes of degradation is fire. This study was conducted to establish a model and map of peat fire risk in District of Bengkalis, Riau Province. The model was established by hotspot distribution as an indicator of fire occurrences. Environmental and infrastructure aspects were employed as supportive factors to fire. Factors which were used to describe the environmental aspect were landcover and vegetation types, peat depth, and greenness level of vegetation. Factors of infrastructure aspect were the distance of fire occurrences with road network, distance to the river network and to the center of villages. Weighting and scoring were the basis of model development using the method of Complete Mapping Analysis (CMA). The model suggested that peat fire is more strongly affected by infrastructure aspect when compared with environmental aspect with the weight of 0.658 and 0.342 respectively. This explains that fires occurred were triggered more by human factor rather than environmental factor. The chosen factor of infrastructure aspect is distance from occurenced fires of road network. The selected environmental aspects were landcover and vegetation types, peat depth and greenness level of vegetation. Seemingly, the distance of river and center of villages may not be the supportive factors of peat fires, as showed by the presence of hotspots in which found mostly in the area far from the river and village center. The model can explain the condition of average of fire occurrences with the validation of 80%. Therefore, it can be used as the referrence in developing and establishing of polic ies for peat fire prevention and suppression.
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Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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