DocumentCode :
119485
Title :
Vismate: Interactive visual analysis of station-based observation data on climate changes
Author :
Jie Li ; Kang Zhang ; Zhao-Peng Meng
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
fYear :
2014
fDate :
25-31 Oct. 2014
Firstpage :
133
Lastpage :
142
Abstract :
We present a new approach to visualizing the climate data of multi-dimensional, time-series, and geo-related characteristics. Our approach integrates three new highly interrelated visualization techniques, and uses the same input data types as in the traditional model-based analysis methods. As the main visualization view, Global Radial Map is used to identify the overall state of climate changes and provide users with a compact and intuitive view for analyzing spatial and temporal patterns at the same time. Other two visualization techniques, providing complementary views, are specialized in analysing time trend and detecting abnormal cases, which are two important analysis tasks in any climate change study. Case studies and expert reviews have been conducted, through which the effectiveness and scalability of the proposed approach has been confirmed.
Keywords :
climatology; data analysis; data visualisation; environmental science computing; interactive systems; time series; Global Radial Map; Vismate; abnormal case detection; climate change; climate data visualization; geo-related characteristics; highly interrelated visualization techniques; input data type; interactive visual analysis; model-based analysis method; multidimensional characteristics; spatial pattern analysis; station-based observation data; temporal pattern analysis; time trend analysis; time-series characteristics; visualization view; Data visualization; Image color analysis; Layout; Meteorology; Spatiotemporal phenomena; Time series analysis; Visualization; Climate changes; radial layout; spatiotemporal visualization; station-based observation data; visual analytics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/VAST.2014.7042489
Filename :
7042489
Link To Document :
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