scholarly journals Explore Multivariable Spatio-Temporal Data with the Time Wave: Case Study on Meteorological Data

2012 ◽  
pp. 79-92 ◽  
Author(s):  
Xia Li ◽  
Menno-Jan Kraak
Keyword(s):  
Meteorological Data ◽  
Temporal Data ◽  
Spatio Temporal

scholarly journals Creating and evaluating web-based visualizations of multi-dimensional spatiotemporal data

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Jan Wilkening ◽  
Keni Han ◽  
Mathias Jahnke
Keyword(s):  
Spatiotemporal Data ◽  
Weather Data ◽  
Temporal Data ◽  
Web Based ◽  
Animated Maps ◽  
Different Types ◽  
Weather Parameters ◽  
Spatio Temporal ◽  
The Web

<p><strong>Abstract.</strong> In this article, we present a method for visualizing multi-dimensional spatio-temporal data in an interactive web-based geovisualization. Our case study focuses on publicly available weather data in Germany. After processing the data with Python and desktop GIS, we integrated the data as web services in a browser-based application. This application displays several weather parameters with different types of visualisations, such as static maps, animated maps and charts. The usability of the web-based geovisualization was evaluated with a free-examination and a goal-directed task, using eye-tracking analysis. The evaluation focused on the question how people use static maps, animated maps and charts, dependent on different tasks. The results suggest that visualization elements such as animated maps, static maps and charts are particularly useful for certain types of tasks, and that more answering time correlates with less accurate answers.</p>

A spatio-temporal data model for administrative division place names: a case study of Xiamen

2009 ◽  
Author(s):  
Liping Yang ◽  
Guangfa Lin ◽  
Ailing Chen ◽  
Youfei Chen ◽  
Xiaohuan Wen
Keyword(s):  
Data Model ◽  
Temporal Data ◽  
Place Names ◽  
Administrative Division ◽  
Spatio Temporal

scholarly journals Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2789
Author(s):  
Wenhui Li ◽  
Dongguo Shao ◽  
Wenquan Gu ◽  
Donghao Miao
Keyword(s):  
Quantile Regression ◽  
Climatic Factors ◽  
Meteorological Data ◽  
Central China ◽  
Data Sets ◽  
Jianghan Plain ◽  
Teleconnection Patterns ◽  
Spatio Temporal ◽  
Quantile Regression Method

Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconnection patterns, aimed at providing references for dealing with climate change and guiding agricultural activities. Both linear and multifactorial regression models were constructed based on the frequentist quantile regression and Bayesian quantile regression method, with the daily meteorological data sets of 17 national stations in the plain and teleconnection climate characteristic indices. The results showed that precipitation in JHP had stronger spatial variability than evapotranspiration. El Niño probably induced less precipitation in summer while the weakening Arctic Oscillation might lead to more summertime precipitation. The Nash-Sutcliffe efficiency (NSE) of the multifactorial and linear regression model at the median level were 0.42–0.56 and 0.12–0.18, respectively. The mean relative error (MRE) ranged −2.95–−0.26% and −7.83–0.94%, respectively, indicating the much better fitting accuracy of the multiple climatic factors model. Meanwhile it confirmed that the agricultural climate in JHP was under the influence from multiple teleconnection patterns.

scholarly journals Fuzzy spatio-temporal data modeling based on XML schema

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1663-1677 ◽  
Author(s):  
Xu Chen ◽  
Li Yan ◽  
Weijun Li ◽  
Fu Zhang
Keyword(s):  
Data Model ◽  
Spatial Information ◽  
Meteorological Data ◽  
Rapid Development ◽  
Xml Schema ◽  
Temporal Data ◽  
Time Data ◽  
Big Data Applications ◽  
Spatio Temporal ◽  
Space Data

With the rapid development of Internet and Big data applications, massive time and space data need to be processed. In order to manage space and time data, the key point is to build a correct data model. There are a lot of fuzzy temporal and spatial information in the real world, and XML has been a useful technology for dealing with various information in the context of Web. In this paper, we first study the fuzzy spatio-temporal data tree by extending the XML Schema and then propose a fuzzy spatio-temporal data model based on XML. Finally, we use the meteorological data to illustrate the validity and usability of the model.

scholarly journals Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data

2020 ◽  
Vol 65 (2) ◽  
pp. 1303-1320
Author(s):  
Hussien SH. Abdallah ◽  
Mohamed H. Khafagy ◽  
Fatma A. Omara
Keyword(s):  
Cell Phone ◽  
Temporal Data ◽  
Spatio Temporal
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