期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 3 B
页码：259-262
出版社：Copernicus Publications
摘要：LiDAR (Light Detection and Ranging) is widely used in such fields as Digital Surface Model (DSM) production. It provides intensity data that reflect the material characteristics of objects, so it is possible that intensity data could be used for land-cover classification. In this study, we assessed the possibility of land-cover classification using LiDAR intensity data instead of the multi-spectral data that has commonly been used for classification. We converted LiDAR point data to a grid and assessed the separability of intensity data on some classes, including asphalt road, grass, house roofs, and trees. However, the grid data was very noisy because of errors during data acquisition or from the resampling processes. To solve this problem, we examined some resampling and filtering methods that can remove noise effectively while the original information is preserved as much as possible. From this study, we concluded that LiDAR intensity data could be used for land-cover classification
