GeolinQ
Spatial Data Management

Seamless Point Surface

Data acquisition solutions like multi-beam sonar systems, LIDAR en satellites produce datasets for designated measurement areas. In many cases the boundaries of the designated areas do not match the boundary of the information products. To solve this problem the datasets of the designated areas have to be integrated by manual work into a seamless data model without overlaps to create the needed information product. This is a time consuming process were errors are easily made and it is not guaranteed the best data is used for every location in the information product. Examples of these models are a depth model of a port area for navigation purposes, height data sets as input for flooding models or a mosaic of satellite datasets for vegetation mapping.

Combining datasets to a seamless dataset

GeolinQ offers the Seamless Point Surface (SPS) for automatic and flexible compilation of seamless data models based on multiple point cloud and raster datasets originated from different measurement areas. Based on the metadata attributes of the datasets users can configure priority rules. Based on these rules the overlap between the datasets are removed and the hull of the datasets in the SPS determined resulting to the best available data on any location. We call this process the deconflicting of the data. (See also the following illustration)    

New imported datasets are automatically integrated by Seamless point Surface (SPS) using the user configured selection and prioritizing rules. This means that when the metadata attributes of a new dataset correspond with the selection criteria’s the dataset is automatically added to the SPS. This results in a, selection and priority based guaranteed up-to-date SPS. Manual work for adding new datasets is history now.

Only the footprints of the datasets in the SPS are stored in GeolinQ. When retrieving a SPS, the required points or rasters are selected from the underlying datasets using their footprint as spatial restriction. This method eliminates redundant storage of point and rasterdata and allows fast SPS updating when datasets are added or removed.    

The footprints in the SPS and point- and raster data can be viewed in the GeolinQ viewer, can be accessed through web services and can be exported to a file. In all cases high performance is guaranteed. Users can make a spatial selection of the part of the SPS to export. This enables users to get the best available data for their work.

Detailed information of working with SPS is available via:SPS tutorial