Abstract
DEMs (Digital Elevation Model) are important data sources that describe the surface morphology, but they are not real 3D models and thus cannot meet the requirements for describing the land surface in 3D. LIDAR (Light Deteation and Ranging) point cloud data are true 3D data with high precision and a high density. Based on an analysis of the differences between DEM and point cloud data, including the corresponding acquisition methods, data structures and model construction methods, this paper proposes a 3D point set data model based on regular grid 2D data field for regional modeling. The feasibility of the model is tested through the upper and lower boundary modeling method. The experiments show that (1) the 3D point set data model based on regularly gridded 2D data field is compatible with complete DEM data and simplified point cloud data and has good applicability; (2) the newly built data model can be used in the true 3D modeling of simple surface entities with high efficiency when the amount of data is only doubled; and (3) the new data model can be generated by inputting DEM data and point cloud data and using a simplified algorithm to process the point cloud data in the same coordinate system. This approach has the potential for multiscale, including large-scale, and automatic output processing and has the potential to be widely generalized.
Highlights
As important digital representations of the Earth's surface, digital elevation models (DEMs) have been around for half a 20 century (Hu and Cao, 2013)
Based on an analysis of the differences between DEM and point cloud data, including the corresponding acquisition methods, data structures and model construction 10 methods, this paper proposes a 3D point set data model based on regular grid 2D data field for regional modeling
The experiments show that (1) the 3D point set data model based on regularly gridded 2D data field is compatible with complete DEM data and simplified point cloud data and has good applicability; (2) the newly built data model can be used in the true 3D modeling of simple surface entities with high efficiency when the amount of data is only doubled; and (3) the new data model can be generated 15 by inputting DEM data and point cloud data and using a simplified algorithm to process the point cloud data in the same coordinate system
Summary
As important digital representations of the Earth's surface, digital elevation models (DEMs) have been around for half a 20 century (Hu and Cao, 2013). LIDAR point cloud data, as a new 30 type of high-precision, high-density true 3D data collected in recent years, provide a reliable 3D data source for indoor positioning, 3D modeling, high-precision DEM production, etc. The data files recorded by LIDAR equipment are generally based on the Las format (Zhang et al, 2014) issued by the LIDAR committee of the American Society for Photogrammetry and Remote Sensing (ASPRS). This format contains a large 50 number of parameters, such as coordinates, colors, laser return points, and scanning angle ranges. A data model that is compatible with the two data types must consider data dimensionality reduction, point set thinning, and the support of true three-dimensional data
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