In this thesis, an approach to automatically derive information about land cover from the remotely sensed data is presented. The data interpretation was done with classification process and performed in software eCognition Developer. The Object-based image analysis, which assignes the classes - for example land cover types, to clusters of pixels (=objects), was used. For the classification, products of two different data sources were combined - the orthophotos generated from aerial imagery and Normalized Digital surface model derived from LiDAR data. Five types of landscape elements were identified and classified.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:226365 |
| Date | January 2013 |
| Creators | Martinová, Olga |
| Contributors | Kalvoda, Petr, Hanzl, Vlastimil |
| Publisher | Vysoké učení technické v Brně. Fakulta stavební |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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