Detection of Laver Aquaculture Site of Using Multi-Spectral Remotely Sensed Data

다중분광 위성자료를 이용한 김 양식어장 탐지

  • Jeong, Jongchul (Dep. of Geographical Information System Engineering Namseoul University)
  • 정종철 (남서울대학교 지리정보시스템공학과)
  • Received : 2005.05.17
  • Accepted : 2005.06.09
  • Published : 2005.06.30

Abstract

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

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