left: Source data DEM, middle: Classification with 6 classes, right: Classification with 10 classes
In recent years various approaches for classifying digital surface models were developed. One of these algorithms is the so called topographic position index. The results of this algorithm are used for describing and explaining different real world phenomena, like the movement of wildlife or the position of archeological sites. In order to achive good classification results, different parameters and extensions have to be taken into account, for example:
The goal of this thesis is to analyze and extend an existing algorithm. The result of the classification shall determine regions, which are strongly endangered by extreme rains and wind speeds due to their spatial exposition. Statistical analysis of the classification results has to be done, using different data sources and data types. Programming work has to be done in Python.
Wird per js gefüllt...
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Duration of contract:
min 3 months
Remote Sensing Technology Institute
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