Pointclouds and rasterdata
Lidar, 3D Laser scanners and photography are used to map and monitor land areas and objects. These measurements result in point clouds and raster datasets. A point cloud consists of large amounts, often millions, of 3D points with per point one or more attributes. An example of pointcloud data is bathymetric data. Bathymetric data is of great importance for many marine information products such as navigation charts, environmental research and location optimization for wind turbines, cables and pipelines.
Photography and satellites deliver raster datasets. To reduce the amount of data point clouds are sometimes resampled to raster datasets.
Point clouds and raster datasets
Point clouds and raster datasets are easy to import and manage in GeolinQ. GeolinQ supports LAS, ASCII as well as GeoTiff as import file formats. Multiple attributes per point are supported. These attributes are to be configured by the user and must be linked to the attributes of the point in the input file. GeolinQ supports all EPSG coordinate transformation so virtually every point cloud in any coordinate systems can be imported.
Multiple dataset are combined to a single dataset holding the best available measured data in a specific area with Seamless Point Surface (SPS) Based on the metadata attributes of the datasets users can configure priority rules and selection criteria.New imported surveys are automatically integrated by SPS based on the configured selection and priority rules guaranteeing an always up-to-date DTM.
Using Pointclouds and rasterdata
Functionality is offered to configure color scales to visualize the data, calculate contours and export DTM’s. In addition DTM’s can be made available as map layers and data export options to end-users via Applicatiesservices.
Point cloud datasets are generally large and may contain millions or even a billion of points. Efficient storage, indexing, tiling and dynamic data pyramiding are used to allow fast retrieval and visualisation at all scale levels.