文章基本信息

标题：Land Cover Classification Using Airborne Laser Scanning Data and Photographs
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作者：P. Tymkow ; A. Borkowski
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：185-190
出版社：Copernicus Publications
摘要：The main purpose of this project was to investigate the possibility of using airborne laser scanning data as a source of information for supervised land cover classification of Widawa River valley. The project was done for the need of hydrodynamic modeling of .ood. Laser scanning data was used both as a sole and supplementary source of information about land cover. The second approach was based on non-metric aerial photographs taken during laser data acquisition. Aerial photographs were directly included in vector classification as RGB channels. They were also applied in GLCM texture features calculation. On the strength of laser scanning data and photographic features, large numbers of experiments were performed to find the best combination of data set and classification methods. In order to quantify the quality of the results, a confusion matrix was created for each case. As a quality parameters kappa coefficient, producer and user accuracy were proposed. These experiments demonstrated that scanning data, as the only source of information, is insufficient for land cover classification. However, by including altitudes and RGB and texture features in vector classification results improve. The replacement of differential model estimated on the basis of DSM and DTM with height variance gives comparable results. The inclusion of intensity image in the feature vector does not reduce false classification rate in a significant way. However this information is useful for water detection even if it is invisible on aerial photographs. The best results are obtained by an artificial neural network classifier
关键词：Airborne remote sensing; Surface roughness coefficient; Image understanding; Data Integration; Flood management; Land ; Cover