Correlation Between Surface Modeling and Pulse Width of FWF-Lidar
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Surface modeling is the process of creating a 3D representation of any surface by manipulating polygons, vertices, and edges in three dimensions. The 3D model represents a physical body using a collection of 3D points in space and connected by several geometric entities. These processes mainly depend on the scenario used to generate the 3D points and the filtering methodology. Lidar is an active remote sensing technique, which has rapidly developed over the last decades to remotely determine the geometry of the Earth’s surface in a rapid and accurate way. However, the FWF-lidar system provides extra information for better 3D digital representation of the features and further improves the modelling for different applications. This paper discussed the correlation between FWF-lidar physical information and the potential to improve the quality of surface modeling. It also discusses the improvements in geometric point quality when integrating pulse width value in the filtering process based on a developed filtering scenario. In this scenario the pulse width value is used as an index to distinguish surface features and improve geometric filtering process. The scenario was tested and analyzed in vegetated and urban areas to show the improvements. The results show decreasing discrepancies between overlapping flight lines in terms of mean and STD values after integrating the pulse width values following Gaussian modeling.
KeywordsRemote sensing Lidar FWF Filtering Pulse width 3D modeling
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