2005, Vol.14, No.6

Journal of Environmental Impact Assessment 2023 KCI Impact Factor : 0.51

pISSN : 1225-7184
https://journal.kci.go.kr/kseia

For managing and utilizing a closed municipal solid waste landfill site in environmentallysecure conditions, it is necessary to verify the stabilization level of landfill gas(LFG) and waste.For assessing LFG and waste stabilization of an open-dumping municipal solid waste landfill(Salmi Landfill) which is located at the vicinity of Chungju Reservoir which flows into PaldangReservoir that has been used for Seoul Metropolitan water supplies, the history and thesurrounding characteristics of the landfill site were surveyed.In this study, waste and LFG samples obtained from landfill site were physically andchemically analyzed, and then the analysis results were evaluated on the basis of ‘The Criteria ofLandfill Waste Stabilization(CLWS)’ that were promulgated by Korean Ministry of Environment.Based on LFG composition of Salmi landfill, CH4 was as high as 68%. In CLWS regulation,the stabilization criteria of CH4 should be lower than 5%, and the criteria of C/N ratio shouldalso be lower than 1/10. The result showed that C/N ratio of landfilled waste ranged 17.4~24.7.From this results, it was concluded that the LFG and C/N ratio stabilization level of this landfillbased on the CLWS were still actively proceeding

The Eurasian otter(Lutra lutra) is listed as No. 330 in natural monument. To manage andconserve habitat for otters, it is critical to understand which habitat components are important forotters. The objectives of this study were to analyze otter habitat characteristics in accordance withland-cover map. We investigated otter spraints and sprainting site in Geoje Island from January toDecember, 2004. with GPS coordinates. The analysis of otter habitat use pattern was used byArcview ver. 3.2 with 1: 25,000 Topology Map and field data. Otter habitat use was stronglyrelated to sites in riparian vegetation riparian(dam or river) structures. In this study, Gucheon wasa site with high coverage of riparian vegetation and unconfined channels, thus recording highernumber of spraint densities than those of Yeonchocheon. Yeonchocheon was under constructionat lower stream areas so that otter habitat use was limited. This study suggests that securingsuitable forests and riparian vegetation zone is essential for conservation of otters.

In this study, we tried to predict the change of future land-cover and relationships betweenland-cover change and geo-spatial information in the Gongju area by using fuzzy logicoperation. Quantitative evaluation of prediction models was carried out using a prediction ratecurve using . Based on the analysis of correlations between the geo-spatial information andland-cover change, the class with the highest correlation was extracted. Fuzzy operations wereused to predict land-cover change and determine the land-cover prediction maps that were themost suitable. It was predicted that in urban areas, the urban expansion of old and new townswould occur centering on the Gem-river, and that urbanization of areas along the interchangeand national roads would also expand. Among agricultural areas, areas adjacent to nationalroads connected to small tributaries of the Gem-river and neighboring areas would likelyexperience changes. Most of the forest areas are located in southeast and from this result we canguess why the wide chestnut-tree cultivation complex is located in these areas and thepossibility of forest damage is very high. As a result of validation using the prediction ratecurve, it was indicated that among fuzzy operators, the maximum fuzzy operator was the mostsuitable for analyzing land-cover change in urban and agricultural areas. Other fuzzy operatorsresulted in the similar prediction capabilities. However, in the prediction rate curve of integrated models for land-cover prediction in the forest areas, most fuzzy operators resulted in poorer prediction capabilities. Thus, it is necessary to apply new thematic maps or prediction models in connection with the effective prediction of changes in the forest areas.