Study on the grasp of forestry situation using IKONOS data and airborne LiDAR data

摘要

We have examined the performance of forest type classification using IKONOS data and LiDAR data. In order to cover a wide forest region, DEM (Digital Elevation Model), which provides various information including altitude, elevation difference and inclination and which derives from airborne LiDAR offering better understanding of geographical features, is considered to be particularly important. IKONOS data, on the other hand, can observe surface of the earth at a high resolution, and also offers not only spectral information but also the texture and the shape analysis. In this study, with spectral feature obtained from IKONOS data, tree height from LiDAR data, and texture feature, forest was classified into two types, such as natural and artificial forest. Tease results showed that spectral feature, tree height and texture feature are effective for classification of forest types.