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학위논문 동서

GIS(Geographic information system)와 RS(Remote sensing)를 이용한 洛東江 河口의 砂洲植生에 관한 硏究

남춘희

부산: 東亞大學校 1999

iv,57장: 삽도; 26cm

학위논문(석사) 동아대학교 대학원: 생물학과, 1999

영문초록 : This study was carried out to find out the abilities of remote sensing techniques and geographic information system in ecology. Landsat TM image data was used for focusing vegetation analysis of sand bars and developing wetland database in Nakdong river estuary. Field survey of study area was conducted from march to september of 1998. Actual vegetation map was made based on field survey. Based on such surveyed result, attribute data was built for wetland database. The total number of plant species present in the study area were 36 family and 127 species. Among these, 78 species in Daemadeung, 101 species in Jangjado, 46 species in Sinjado, 10 species in Myeonggemery, 85 species in Baeghapdeung, 38 species in Namusitdeung and 31 species in new sand bars were identified. Landsat TM data was classified by unsupervised classification method into 5 classes such as, Phragmites australis community, mixed community, sand beach, Scirpus trigueter community, non-vegetation intertidal area. Vegetation index map of wetland vegetation was developed using NDVI(Normalized Difference Vegetation Index). The condition community ranked mixed community, P. australis community, S. trigueter community based on NDVI map. Water proximity map was developed at a buffer range of 60 m interval. The productivity of P. australis had hight amount of average standing biomass amounting 1273 g/㎡ in 60 m - 120 m buffer area from water. Based on the total amount of P. australis calculated using GIS overlay technique, the developed attribute data and water proximity map were developed. Total productivity of P. australis and S. trigueter in th study area was 824.59 t/㎡/yr and 455.88 t/㎡/yr. Considering the above results, it is desirable to use the remote sensing and GIS technique for producing vegetation classification, potential natural vegetation map, productivity map, and relative tables.

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