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Article

Spatio-Temporal Visualization Method for Urban Waterlogging Warning Based on Dynamic Grading

1
School of Geography, Nanjing Normal University, Nanjing 210023, China
2
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
3
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
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Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria
5
Jiangsu Meteorological Bureau, Meteorological Services Center, Nanjing 210008, China
6
Department of Geography, Faculty of Science, Masaryk University, 60177 Brno, Czech Republic
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(8), 471; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080471
Received: 1 June 2020 / Revised: 19 July 2020 / Accepted: 21 July 2020 / Published: 27 July 2020
With the acceleration of the urbanization process, the problems caused by extreme weather such as heavy rainstorm events have become more and more serious. During such events, the road and its auxiliary facilities may be damaged in the process of the rainstorm and waterlogging, resulting in the decline of its traffic capacity. Rainfall is a continuous process in a space–time dimension, and as rainfall data are obtained through discrete monitoring stations, the acquired rainfall data have discrete characteristics of time interval and space. In order to facilitate users in understanding the impact of urban waterlogging on traffic, the visualization of waterlogging information needs to be displayed under different spatial and temporal granularity. Therefore, the appropriateness of the visualization granularity directly affects the user’s cognition of the road waterlogging map. To solve this problem, this paper established a spatial granularity and temporal granularity computing quantitative model for spatio-temporal visualization of road waterlogging and the evaluation method of the model was based on the cognition experiment. The minimum visualization unit of the road section is 50 m and we proposed a 5-level depth grading method and two color schemes for road waterlogging visualization based on the user’s cognition. To verify the feasibility of the method, we developed a prototype system and implemented a dynamic spatio-temporal visualization of the waterlogging process in the main urban area of Nanjing, China. The user cognition experiment showed that most participants thought that the segmentation of road was helpful to the local visual expression of waterlogging, and the color schemes of waterlogging depth were also helpful to display the road waterlogging information more effectively. View Full-Text
Keywords: spatio-temporal visualization; urban waterlogging; disaster warning; visual granularity; dynamic grading spatio-temporal visualization; urban waterlogging; disaster warning; visual granularity; dynamic grading
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MDPI and ACS Style

Zhou, J.; Shen, J.; Zang, K.; Shi, X.; Du, Y.; Šilhák, P. Spatio-Temporal Visualization Method for Urban Waterlogging Warning Based on Dynamic Grading. ISPRS Int. J. Geo-Inf. 2020, 9, 471. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080471

AMA Style

Zhou J, Shen J, Zang K, Shi X, Du Y, Šilhák P. Spatio-Temporal Visualization Method for Urban Waterlogging Warning Based on Dynamic Grading. ISPRS International Journal of Geo-Information. 2020; 9(8):471. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080471

Chicago/Turabian Style

Zhou, Jingyi, Jie Shen, Kaiyue Zang, Xiao Shi, Yixian Du, and Petr Šilhák. 2020. "Spatio-Temporal Visualization Method for Urban Waterlogging Warning Based on Dynamic Grading" ISPRS International Journal of Geo-Information 9, no. 8: 471. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080471

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