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SkyVis, an Application of MATLAB in Meteorological Visualization
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9466-9826
Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.ORCID iD: 0000-0001-7557-4904
2003 (English)In: Proceedings of Nordic Matlab Conference 2003, 2003, 295-300 p.Conference paper, Published paper (Other academic)
Abstract [en]

We present a work in progress, Sky Vis, which makes it possible to synthesize realistic images of the sky using data from weather parameter data sets. A neural-network-based model is trained to predict the appearance of the sky from a weather parameter vector. Hourly measurements of weather parameters (like temperature and pressure) and corresponding images are used as training data. The images are decomposed into their eigen components using the principal component analysis (PCA) method. The image information is thus represented using a small number of coefficients. The results show that the main appearance is correct and that it is possible to distinguish between different types of weather. A limitation is that the method is not able to synthesize images with cloud details. This method is in contrast to many previous methods able to synthesize a sky image which varies with the current weather situation.

Place, publisher, year, edition, pages
2003. 295-300 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-13393OAI: oai:DiVA.org:liu-13393DiVA: diva2:20596
Conference
Nordic Matlab Conference, Copenhagen, October the 21st - 22nd, 2003
Available from: 2005-10-14 Created: 2005-10-14 Last updated: 2016-08-31
In thesis
1. Image Based Visualization Methods for Meteorological Data
Open this publication in new window or tab >>Image Based Visualization Methods for Meteorological Data
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization.

This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method.

In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification.

Place, publisher, year, edition, pages
Institutionen för teknik och naturvetenskap, 2004. 92 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1137
Keyword
Visualization, Meteorological Data, Artificial Neural Networks, High-Dynamic-Range images, Satellite Data, Classification
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-4325 (URN)91-85297-00-3 (ISBN)
Presentation
2004-12-17, K3, Campus Norrköping, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Note
Report code: LiU-Tek-Lic-2004:66.Available from: 2005-10-14 Created: 2005-10-14 Last updated: 2016-08-31

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Olsson, BjörnYnnerman, AndersLenz, Reiner

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