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퍼지 논리와 지리공간정보를 이용한 공주지역 토지피복 변화 예측

Prediction of Land-cover Change in the Gongju Areas using Fuzzy Logic and Geo-spatial Information

장동호
한국환경영향평가학회 (Korean Society Of Environmental Impact Assessment)|2005.12|환경영향평가 (Journal of Environmental Impact Assessment)|제14권 제6호|pp. 387-402

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참고문헌

주제분류환경공학

초록

Abstract

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.

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