The understanding and implementation of object detection and classification algorithms help in deploying diverse applications of UAVs. The developed toolkit may serve as a starting point for future work further developing and evaluating the generic creation of GIS-based serious games. However, it has limited usefulness in creating more narrative-focused, fantastical games. Evaluating its capabilities using workshops as well as theoretical serious game frameworks points towards a strong ability to communicate geographic concepts and knowledge as well as to promote productive discussions. In addition to being used in a case study which involves the creation of a serious game together with a group of experts, four serious games described by previous literature are recreated using the toolkit. It allows users to define various serious games based on GIS datasets in less than 200 lines of code. This toolkit uses existing software design patterns in order to reach the desired level of generalization. Using this model, a technical toolkit is developed as part of an existing open source landscape visualization, the LandscapeLab. This is the primary motivation behind this thesis: it attempts to generalize the existing knowledge on serious planning games and connect them to the underlying GIS data, the geographical datasets which represent the real-world foundation behind them. It has been argued that this is due to the high complexity and cost that comes with developing them. However, although their usefulness is backed by strong scientific evidence, serious games are still not seeing much usage in the field. Instead of presenting finished plans to the population, they allow citizens to get involved in the planning process in an approachable way. Serious games are a promising tool in the field of landscape planning.

Ys flight simulator controls