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Proceedings Paper

A WebGIS-based system for analyzing and visualizing air quality data for Shanghai Municipality
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Paper Abstract

An online visual analytical system based on Java Web and WebGIS for air quality data for Shanghai Municipality was designed and implemented to quantitatively analyze and qualitatively visualize air quality data. By analyzing the architecture of WebGIS and Java Web, we firstly designed the overall scheme for system architecture, then put forward the software and hardware environment and also determined the main function modules for the system. The visual system was ultimately established with the DIV + CSS layout method combined with JSP, JavaScript, and some other computer programming languages based on the Java programming environment. Moreover, Struts, Spring, and Hibernate frameworks (SSH) were integrated in the system for the purpose of easy maintenance and expansion. To provide mapping service and spatial analysis functions, we selected ArcGIS for Server as the GIS server. We also used Oracle database and ESRI file geodatabase to store spatial data and non-spatial data in order to ensure the data security. In addition, the response data from the Web server are resampled to implement rapid visualization through the browser. The experimental successes indicate that this system can quickly respond to user’s requests, and efficiently return the accurate processing results.

Paper Details

Date Published: 8 October 2014
PDF: 8 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 922119 (8 October 2014); doi: 10.1117/12.2060528
Show Author Affiliations
Manyi Wang, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Chaoshun Liu, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Wei Gao, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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