Most of the area in East Buru Utara Regency, Maluku Province are categorized as coastal lowlands, especially the Teluk Kayeli area. This area has the potential to be developed into a destination area for mangrove ecotourism destination due to its natural and preserved mangrove. The purpose of this study was to analyze the suitability of mangrove areas as an object of ecotourism attraction in Siahoni Village, Buru Utara Timur Regency, Maluku Province. The research approach is descriptive quantitative, using the survey method. Primary data including thickness, density, biota, and type of mangrove were collected through field observation at four observation stations, while secondary data including geographical condition, village monograph, and tide data were collected through literature study. Vegetation data were analyzed by measuring the relative density of each plant species and tourism suitability was analyzed by using tourism suitability index (TSI). Also, a SWOT analysis was also conducted to determine the strategy for developing mangrove ecotourism. Mangrove species observed in mangrove ecosystem at Teluk Kayeli, Siahoni Village consisted of Avicennia lanata, Sonneratia caseolaris, Bruguiera gymnorrhiza, Ceriops tagal, Nypa frutican, Rhizophora apiculata, Rhizophora mucronata, Rhizophora stylosa, Scyphyphora hydrophyllaceae, dan Xylocarpus granatum. The results showed that the TSI of mangroves at the observation station 1, 2, 3, and 4 were 65%, 72%, 72%, and 69%, respectively, and corresponded to the S2 category (suitable). Efforts to improve the suitability index of the mangrove area as an object of ecotourism attraction could be done through rehabilitation and reforestation, hence the environmental attraction and ecological function of the mangrove area could be improved.Keywords: ecotourism, Maluku, mangrove, tourism suitability index
The objectives of the research were to obtain correlation model between NDVI (Normalized Density Value Index) and Freshness Index, to examine the capability of Landsat-TM satellite to show opened green space in controlling the effect of heat island, to know the level of freshness in Ambon town, and to produce layout of opened green space of Ambon town in relation with the need of freshness of the communities. The result of the research showed that Landsat-TM satellite can be used to detect the green space area of the Ambon town. Based on the classification of NDVI through Landsat-TM satellite, the Ambon town has 899,9 hectares (3 %) of land without vegetation or scarcely vegetation, 1488,71 hectares (4 %) were low density of vegetation, 1495,34 hectares (4 %) were in middle density, and 32060, 58 hectares were in high density. NDVI had a positive correlation to the temperature and relative humidity which means that increasing of vegetation density decreased the temperature and increased the relative humidity of a certain area. Effect of the heat island to the Ambon town are identified 1267,93 hectares, and generally found in the central of town (District of Sirimau) and the new development area which followed the main road area.
Limited data and the lack of use of Remote Sensing Technology and Geographic Information Systems (GIS) to map areas that are potentially prone to forest and land fires in Ambon City are one of the obstacles in handling forest and land fires. This study aims to identify the factors that cause forest and land fires, determine the level of vulnerability to forest and land fires and produce a digital map of forest and land fires in Jazirah Leitimur Selatan, Ambon City. The data used are Landsat 8 OLI/TIRS C1 Level-1 path/row 109/62 satellite imagery acquired on October 28, 2017. Hotspot data was obtained from FIRMS and Lapan Fire Hotspot. Data processing is done by using the method of overlaying variables that trigger the occurrence of forest and land fires. The results showed that the Jazirah Leitimur Selatan has the potential to be prone to forest and land fires with 76.6% of the area included in the vulnerable to very vulnerable category, while 23.4% is in the non-prone category.
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