Object-based Evaluation of Lidar and Multispectral Data for Automatic Change Detection in Gis Databases
نویسنده
چکیده
The automatic interpretation of aerial and satellite images is one of the main important research topics in photogrammetry and image analysis. The aim of the interpretation is the recognition or verification of objects in images. The quality of the interpretation results depends among other factors on the information content of the input data. The more information in the input data the easier is the interpretation process. In this paper an approach is described that increases the quality of the interpretation process by using existing GIS data as prior information on the one hand and by combining multispectral and LIDAR data on the other hand. The approach is used for automatic change detection and is based on the evaluation of automatically derived training data sets from existing GIS data. For that reason no data dependent tuning factors have to be defined and no human interaction is necessary.
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