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：2000
卷号：XXXIII Part B3(/1+2)
页码：540-547
出版社：Copernicus Publications
摘要：Recently several papers have been published on the precisio n of Digital Terrain Models (DTM) which were produced by airborne laser-scanning. This precision is influenced by several factors, like navigation accuracy, quality of reference data but also by the way the "raw" laser scanner data is filtered. For the latter task mathematical models as well as algorithms can be used. A specific problem in quantifying the accuracy is the typical asymmetric error distribution of laser measurements when compared to reference data. The data show only small negative deviations to the terrain-surface (below the terrain- surface), ho wever, relatively large positive deviations due to vegetation or buildings (above the terrain-surface). This general problem must be taken into account. Two different approaches for the filtering of laser-scanner data are presented in this paper, namely the use of linear prediction and the use of dual rank filters. Both methods are presented and their results are compared. If linear prediction is used as filtering method, it must be applied iteratively, because otherwi se the results are strongly influenced by height points lying far above the mid-terrain-level. The use of linear prediction shows satisfactory results in forest areas, whereas other areas with steep terrain sho w problems which makes it necessary to locally adapt the method to the shape of the terrain. Using the above approach of dual rank filtering some pre-knowledge of the area of concern is required and very o ften the process of filtering is influenced by interactive procedures like restricting the filter process to special areas of interest, to avoid a smoothing of the "natural" terrain. Dual rank filters show very promising results especially when filtering artificial objects like buildings but require interactive control and so me pre-knowledge in order to properly set the necessary parameters
