식생분석을 위한 고분광영상(Hyperspectral image) 활용방안

Abstract

Abstract Application of Hyperspectral Image Data for Vegetation Analysis Vegetation map is an essential environmental data for environmental research and Environmental Impact Assessment (EIA), but it requires intensive field sampling work and time. To minimize these inputs, remote sensing has been applied in forestry and planning to make land cover map or vegetation map. Moderate spectral resolution sensor provides enough spectral information to create land use/land cover map, but it is difficult to detect the subtle spectral reflectance differences among tree species or between healthy and stressed vegetation because of the rough spectral resolution. Hyperspectral sensor provides almost continuous spectral reflectance of vegetation that contains enough spectral information to differentiate tree species and vegetation status. With sufficient reference data, it is feasible to create a detailed vegetation map by using hyperspectral image. In addition to vegetation mapping, hyperspectral sensor has been tested and applied to various environmental researches and monitoring. Many studies have demonstrated the applicability of hyperspectral image for invasive species monitoring, agricultural management, and lake water quality monitoring. To operate hyperspectral sensor effectively, field surveyors and hyperspectral analysts should work closely together. Their communication and mutual understanding is essential to enhance the accuracy of hyperspectral image analysis.