• Journal of the Korean Geographical Society
• /
• v.37 no.4
• /
• pp.371-384
• /
• 2002

It is very important to predict the environmental changes in the land-surface as a way of prevention of sustainable nature. This study investigated the difference between the predicted and actual data of Anmyeon-do from 1981 to 2000 through a fuzzy logic operation using multi-spectral image. According to literature survey, maps, and ground truth data, the types of land-use have changed due primarily to shore reclamation or wild land and grassland fostering before the eighties. After the mid-eighties, however, a number of private residents and commercial stores quickly have spreaded throughout beach resorts and quasi-agricultural and forest areas. Moreover, shore and community regions were severely damaged in the nineties with increased farmland, due to the development of tour places and expansion of city area. The predicted result of the environmental changes in the land-surface using the fuzzy logic operation was almost similar to the state of Anmyeon-do obtained through the satellite image. Particularly, the flat lands near the shore was predicted to change slightly. This area is largely under development, thereby raising concerns on the shore environment. Thus, this method is applicable to conducting research on the change in the land-surface.

• Korean Journal of Remote Sensing
• /
• v.18 no.6
• /
• pp.305-317
• /
• 2002

The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.