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:2005
卷号:XXXVI-3/W24
出版社:Copernicus Publications
摘要:Laser scanning or LiDAR data are increasingly used in forestry applications but also e.g. in urban environments or for building reconstructions. Huge point clouds are usually converted to a grid or are pre-processed in specific software packages. In this paper we present a methodology to extract and delineate single trees from small footprint, high intensity laser scanning point data in a GIS environment. Additional image data are only used for visualisation purposes and for accuracy assessment. The objective was to demonstrate the potential of a fully GIS-based workflow. After various pre-processing steps within the GIS, we developed a local maxima algorithm to identify tree tops. Secondly, we developed a region growing algorithm to delineating the respective tree crowns. It utilizes the original laser point data and not a derived raster data set such as a DSM. The algorithm was tested for six test plots located within the National Park Bavarian Forest (Germany) which is considered a natural or near-natural forest. For these plots, the results of extensive field surveys were available. Dominant trees could be detected with an accuracy of 72.2% but the overall tree detection rate was 51%. Suboptimal scan sampling distribution hinders perfect tree crown delineation. Our main goal - to develop and demonstrate a complete GIS-based workflow from Laser data pre-processing, algorithm development, analysis, to visualisation etc. – was reached. However, locating and counting trees within the LiDAR point cloud, particularly in multi-tiered deciduous plots and juvenile stands, requires the assistance of field-validation data and some subjective interpretation
关键词:LiDAR; Laser scanning; region growing algorithm; GIS; identification; crown delineation