Satellites, airplanes and drones use remote sensing techniques to map and monitor areas and objects. The results of these measurements are oftern delivered as raster data. A raster dataset consists of a large amount, often millions, of raster cells with per cell one or more attributes.
Point clouds are often resampled to raster datasets. Raster datasets can be combined in many different ways into new information products either new raster datasets or vector datasets. The satellite images used for weather forecasting are examples of raster datasets.
Raster data in GeolinQ
Raster data is easy to manage in GeolinQ. GeoTIFF as well as ASCII files can be imported. Multiple attributes per cell are supported (e.g. more spectral bands). During import cell attributes in the input file have to mapped to attributes of a raster cell in GeolinQ. GeolinQ supports all EPSG coordinate transformations so virtually every raster dataset in any coordinate system can be imported.
Raster data retrieval
Raster datasets can be queried on their metadata attributes. These attributes can easily be defined by the user. Also the ISO 19115 metadata standard is available. This standard can be used ‘as is’ or as a guideline for a custom metadata schema.
Raster datasets are generally large and may contain millions or even more than a billion of cells. Efficient storage, indexing, tiling and dynamic data pyramiding are used to allow fast retrieval and visualisation at all scale levels.