3D models production technologiesProduction stages
Accurate definition of area of interest (AOI).
Model’s frame can be provided by customer as well as they can be created by our experts with compulsory client’s approval.
Images selection for each AOI.
We use high accuracy satellite images and stereo pairs with resolution 0.5-2.5m. Type of image is selected in accordance with 3D models accuracy requirements, suitable for customer. Always the most recent images are selected.
If in supplier’s archive the recent images are unavailable, we order direct shooting of AOI. Expected new images delivery time is from 2 week to 3 months, depending on weather conditions.
Satellite Images Types Being Used In Models Preparation Process
Data generation process.
Visual interpretation of data generation stages
Manual vectorization of contours and linear features from satellite images in MAPINFO, ERDAS, ARCGIS or other GIS-environments
Digital Terrain Model creation technology
DTM describes all the features of earth surface, position and outlines of nature objects, which are preventing signals propagation.
DTM can be created using three different methods:
- Digitization of terrain contour lines from topographic maps with 1:10000/25000/50000 scale (depending on maps availability) – is used for basic 3D models
- Usage of satellite images stereo pairs with resolution 2.5m – is used for basic 3D models
- Usage of high resolution satellite images stereo pairs – is used for stereo models
Vertical accuracy (Z) in DTM depending on usage of different initial data.
|Maps 1:50 000||Maps 1:10 000, 1:25 000||Satellite images stereo pairs with 2.5m resolution||Satellite images stereo pairs with 0.5-1 m resolution|
Usage of stereo pairs provides deeper terrain detailing in comparison with data extracted from topographic maps
DTM examples, made using different initial data and technologies
Clutter model producing technologies
Clutter model describes all the terrain and build-up area features, which are resulting on signal propagation. Such models of earth surface are being unified in different classes: classes of buildings, classes of water objects, classes of landscape objects and vegetation.
Main sources of data for clutter model creation are satellite images with resolution 0.5 – 2.5 m, depending on model type – Basic or Stereo. For each type of model the most recent images are being taken for the maximum data accuracy.
Types of images used for clutter models creation.
|Model||Type of image|
|Basic||Ikonos, QuickBird, EROS-B, WorldView, GeoEye, Cartosat 1, Allos|
|Stereo||Ikonos, EROSB, WorldView, GeoEye|
Clutter model is produced by photo interpretation of orthorectified satellite images.
Process is maintained in manual mode to gain the most precious correspondence of initial image and classification result.
Manual processing technology provides considerable better result (in comparison with automated) because it allows to classify clutters within many parameters, which are important for wireless networks planning, such as build-up density, its specific features and widths of the streets.
Clutter model sample
16 clutter classes are usually used in Basic model and 20 clutter classes – in Stereo model.
However clutters list can be extended or changed on client’s demand and for best fitting to territory specification for which 3D model is created.
Below there are two samples of different methods of clutter model creation – automated mode – not recommended and manual mode – best quality
Automated clutter generation
Quality of clutter model received by automated satellite images processing depends on quality of those images, quality of encrypting algorithms and presence or absence of final visual quality control procedures.
Manual clutter generation
In contrast to automated mode manual generation of clutter model which is currently recommended – is based on high qualification and reach experience in satellite images encrypting of our personnel. It allows to take into account all specific features of working with exact territory and with exact satellite images.