Lars Aurdal

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In this study we have looked into the problem of vehicle detection in high-resolution satellite images. Based on the input from the local road authorities, we have focused not only on highways, but also on inner city roads, where more clutter is expected. The study site is the city of Oslo, Norway. To do vehicle detection in these areas, we propose an(More)
— Ground cover classification based on a single satellite image can be challenging. The work reported here concerns the use of multitemporal satellite image data in order to alleviate this problem. We consider the problem of vegetation mapping and model the phenological evolution of the vegetation using a Hidden Markov Model (HMM). The different vegetation(More)
— This work concerns the alignment of growth seasons based on satellite data. This work is motivated by a high mountain vegetation classification problem in Norway. Vegetation classes are characterized by their temporal evolution through a growth season. Data of high spatial resolution, like LANDSAT data, are often temporally sparse. In order to get a(More)