다중분광 위성자료를 이용한 김 양식어장 탐지

Abstract

Recently, aquaculture farm sites have been increased with demand of the expensive fishspecies and sea food like as seaweed, laver and oyster. Therefore coastal water quality have beendeteriorated by organic contamination from marine aquaculture farm sites. For protecting ofcoastal environment, we need to control the location of aquaculture sites.The purpose of this study is to detect the laver aquaculture sites using multispectral remotelysensed data with autodetection algorithm. In order to detect the aquaculture sites, density sliceand contour and vegetation index methods were applied with SPOT and IKONOS data ofShinan area. The marine aquaculture farm sites were extracted by density slice and contourmethods with one band digital number(DN) carrying 65% accuracy. However, vegetation indexalgorithm carried out 75% accuracy using near-infra red and red bands.Extraction of the laver aquaculture site using remotely sensed data will provide the efficientdigital map for coastal water management strategies and red tide GIS management system.