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Ljubljana, Slovenia

Imhof A.B.,Liquifer Systems Group LSG | Kotler J.M.,Leiden University | Pell S.J.,ARTi Aquabatics Research Team | Peljhan M.,SPACE SI
Proceedings of the International Astronautical Congress, IAC | Year: 2012

The arts offer alternative insights into reality - which is explored by science in general, and broadened by the activities conducted by the European Space Agency (ESA) and other space agencies. Similar to the way the members of ESA are ambassadors for spaceflight and science, artists and cultural professionals are ambassadors for human expression, experimentation, and exploration. In June 2011, the ESA Topical Team Arts & Science (ETTAS), held a three-day workshop at the European Astronaut Centre in Cologne, Germany. During this workshop, topics and ideas were discussed to develop cooperations between the arts, sciences and ESA to foster and expand the human and cultural aspects of space exploration, and at the same time offer a means of communication that aims to reach audiences beyond the scope of traditional space-related channels. The preliminary findings and consensus of the team was that establishing and sustaining a transdisciplinary professional community consisting of ESA representatives, scientists and artists would fuel knowledge transfer, and mutual inspiration. [Imhof et.al. 2012] Potential ways to provide a sustainable cooperation within and between the various groups were discussed and will be presented. A number of measures and mechanisms in order to initiate and conduct such an initiative and a more in- depth view regarding organizational measures, procedures and consequences, as well as a proposition on how to proceed are included in the preliminary findings. Overall, the involvement and cooperation between the Arts, Space Science Research and ESA will enhance in the citizens of the ESA member states the sense of public ownership of ESA results, and participation in ESA's research. Copyright © (2012) by the International Astronautical Federation.

Matko D.,SPACE SI | Rodic T.,SPACE SI | Blazic S.,SPACE SI | Music G.,SPACE SI
Advances in the Astronautical Sciences | Year: 2013

In the paper close formation flying equations are reviewed with respect to different manoeuvres and taking into account the required fuel consumption. Three scenarios are designed including parallel flying with in-track displacement demonstrating high-resolution optical dual satellite imaging and radar interferometric constellation, circumvolution as well as encircling of the target demonstrating debris observation and parallel flying with the radial displacement demonstrating fractionated spacecraft and accurate pointing of the formation. The designed scenarios were applied to a set of formation flying experiments, performed by SPACE-SI and OHB Sweden in September 2011 with Prisma satellites Mango and Tango. The results of the experiment are presented and the formation flying model predicted and measured data are compared.

Blazic S.,University of Ljubljana | Matko D.,SPACE SI | Bosnak M.,SPACE SI | Klancar G.,University of Ljubljana | Music G.,University of Ljubljana
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2014

The paper describes the experimental ADCS mode of the NEMO-HD satellite, built in the cooperation between SPACE-SI and Space Flight Laboratory, University of Toronto. In the experimental ADCS mode several imaging modes will be implemented such as fixed target observation, path tracking target observation, area sweep mode and spread area sweep mode. A Matlab-Simulink based simulator was designed, which accurately incorporates the astrodynamics and the kinematics of the satellite in real time. It also provides the images of the observed target by means of the Active-X connection to the Google Earth. The results of simulations demonstrate the applicability of the proposed imaging modes to be implemented on the NEMO-HD satellite, which is planned to be launched in 2015. © IFAC.

Ostir K.,SPACE SI | Veljanovski T.,Slovenian Academy of science and Arts | Kanjir U.,Slovenian Academy of science and Arts | Pehani P.,SPACE SI
Proceedings of the International Astronautical Congress, IAC | Year: 2012

Cities in Africa and developing countries in general are having difficulties coping with the influx of people arriving every day. Informal settlements (slums) are growing, and governments are struggling to provide even the most fundamental services to their populations. One of the tools that can be used to study these environments is satellite imagery, especially very high-resolution (VHR) images coming from systems such as 1KONOS, Quickbird, GeoEye and similar. Detection of informal settlements from satellite imagery is a challenging task due to their microstructurc and irregular shapes of buildings. Higher spatial resolution is necessary to identify and extract individual buildings, especially in slum communities that are characterized by small, densely packed shanties and other structures. In the paper we are dealing with the Kibcra (Nairobi, Kenya) slum that is composed of varying housing sizes, where roofs can be a combination of many different materials, and mainly unpaved road and path network. Typically this produces a spectral response, which is difficult to interpret, and makes traditional classification almost impossible. We have applied object-based classification on GeoEye and QuickBird imagery over a tree year period (from 2006 to 2009) to help differentiate slum rooftops and unpaved roads from non-build land and therefore residential areas or grasslands. Object-based segmentation automatically delimits segments on the image into homogeneous elements, which correspond to the real urban geographical objects on the Earth's surface. In the stage of classification all these homogeneous elements are classified into most appropriate classes. In addition to determination of the detailed urban structure we were also interested in the expansion of slum areas with change detection, which was analysed by comparison of images taken in different time sequences. The results of object-based analysis with morphology attributes were further used to estimate the potential population density in the slum area. There is a big discrepancy between different estimations on Kibera census, ranging from 1 to 2 million people, while no field survey was ever performed to assess the population. Different parameters were tested to estimate the potential population density scenarios. The paper will discuss merits and drawbacks of object-based image analysis in dense non-formal settlements analysis with remote sensing data. Overall, the use of the object-based image analysis holds great promise for dense urban environments and could be utilized in studies of urban change structure and corresponding population estimation. Copyright © (2012) by the International Astronautical Federation.

Marsetic A.,SPACE SI | Kokalj Z.,SPACE SI | Ostir K.,SPACE SI
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2011

Lossy compression is becoming increasingly used in remote sensing although its effect on the processing results has yet not been fully investigated. This paper presents the effects of JPEG 2000 lossy compression on the classification of very high-resolution WorlView-2 imagery. The k-nearest neighbor and support vector machine methods of the object based classification were used and compared. The results explore the impact of compression on the images, segmentation and resulting classification. The study proves that in general lossy compression does not adversely affect the classification of images; what is more, in some cases classification of compressed images gives better results than classification of the original image. Classification accuracy of support vector machines method indicates that compression ratios of up to 30:1 can be used without any loss of accuracy. The best result of the k-nearest neighbor method was obtained with the highest compression ratio (100:1), but the outcome cannot be trusted without reserve. In the study we found that the support vector machine method gives better classification results than the k-nearest neighbor and is also recommended for further research. In addition to the classification method, image segmentation, a basic step of object classification, plays an important role in the accuracy of the results.

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