Data Processing


Data entry and work with attributes – If your company needs to process huge sets of spatial data we can help you. All operations on updating and merging tables and editing data in all types of geographical datasets are performed at Intetics.

Imagery interpretation
– The following types of processing spatial and aero imagery are offered:
GeoData Solutions: Data Entry

  • Classification means converting spectral raster data into a finite set of classifications that represent the surface types seen in the imagery. These may be used to identify vegetation types, anthropogenic structures, mineral resources, or transient changes in any of these properties. Additionally, the classified raster image can be converted to vector features (e.g. polygons) in order to compare them with other data sets or to calculate spatial attributes (e.g. area, perimeter).
  • Georeferencing is the process of accurately positioning the imagery relative to a map coordinate system. Once georeferenced, the imagery can be integrated with other georeferenced information.
  • Remote sensing data digitizing. Satellite, aerial and lidar data can be converted into any type of GIS file format with all the appropriate attributes and metadata.

GeoData Solutions: Imagery interpretation, Vectorization

Vectorization – At Intetics, we propose automatic, semiautomatic and manually converting paper spatial data into vector formats for modern geospatial software. We can process almost any thematic and topographic map. Thus, we can help organizations of different scales create high-quality vector data in any size.

Integration/aggregation – Our world consists of many datasets, which are often found in unexpected places. We are happy to help your organization gather all these data volumes into one neat and simple project. We can aggregate different types of data from different sources into one integrated project or workspace. This includes:

    GeoData Solutions: Data Integration

  • Conversion work to transform CAD data into GIS data and vice-versa.
  • Analyzing, classifying, streamlining and aggregating data collected from multiple sources or providers into one database in accordance with the organization’s standards.
  • Reengineering of existing spatial databases.