The aim of this study is to compare remote sensing methods in the context of a vegetation mapping of an urban environment. The methods used was (1) a traditional per-pixel based method; maximum likelihood supervised classification (ENVI), (2) a standard object based method; example based feature extraction (ENVI) and (3) a newly developed method; Window Independent Contextual Segmentation (WICS) (Choros Cognition). A four-band SPOT5 image with a pixel size of 10x10m was used for the classifications. A validation data-set was created using a ortho corrected aerial image with a pixel size of 1x1m. Error matrices was created by cross-tabulating the classified images with the validation data-set. From the error matrices, overall accuracy and kappa coefficient was calculated. The object-based method performed best with a overall accuracy of 80% and a kappa value of 0.6, followed by the WICS method with an overall accuracy of 77% and a kappa value of 0.53, placing the supervised classification last with an overall accuracy of 71% and a kappa value of 0.38. The results of this study suggests object-based method and WICS to perform better than the supervised classification in an urban environment.

More and more people choose to watch television online through online video-on- demand services. For media corporations, such as the Modern Times Group (MTG), this means that video-on-demand will become an increasingly important source of revenue. Because video-on-demand is an online service, advertising products offered therein are in competition with other online advertising products. Currently, MTG’s video-on-demand advertising products are the same as on regular television, meaning they haven’t yet taken advantage of any advertising product development opportunities made possible by Internet technology. The purpose of this thesis is therefore to determine what MTG’s strategy should be to improve the competitiveness and revenue of their video-on-demand advertising products, and what key concerns need to be addressed in order to realize the determined strategy. By request of the commissioner, MTG, possible uses of segmentation to achieve the strategy are studied. The methods used to collect data include multiple interviews both at MTG and at their current advertising customers, as well as web analytics and a questionnaire. Both qualitative and quantitative analysis was used to answer the research questions. Findings suggest that MTG should strive to improve the engagement of their advertising products, through the use of contextual segmentation and self-segmentation. This goes against the current trend in online advertising, where segmentation is primarily used for ad targeting. The reason for not adhering to the trend is that MTG’s advertising customers operate in a television mindset, where ad targeting is of a very limited nature and engagement is of greater perceived value.