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：2008
卷号：XXXVII Part B3b
页码：687-692
出版社：Copernicus Publications
摘要：Airborne laser scanning (ALS) is increasingly becoming a standard method for the collection of dense elevation models, especially in 3D urban mapping. However, automation in processing of ALS point-clouds involves handling huge datasets, irregular point distribution, multiple views, and relatively low textured surfaces. Since raster data structure is the most commonly used data representation method and is relatively easy to store and process, there comes a need to convert the ALS point clouds into raster data format. Since the ALS point clouds are rarely at the same location as the centre of the discretization grid, approximation is therefore required. A simple and most often used method is selecting a known point value to represent the grid. Such a point-to- point transformation often leads to serious information loss. Transformation of the ALS point clouds to grid is known as a special case of the change of support, because it changes the data volume from point to area. In this paper, we present block Kriging to model this kind of change of support towards rasterization of the ALS point clouds. The mathematic and algorithmic formulations are illustrated. Results from the UW campus show that the proposed method can better preserve the information in the ALS point clouds than the point-to-point transformation. Quality assessment is designed and conducted to evaluate the performance of block Kriging. Detailed error analysis is also provided to illustrate the accuracy of the proposed method
关键词：Airborne laser scanning; Point clouds; Rasterization; Block Kriging; Geostatistics
