Analysis of server-side and client-side Web-GIS data processing methods on the example of JTS and JSTS using open data from OSM and geoportal. (August 2019)

• Record Type: Journal Article
• Authors: Kulawiak, Marcin; Dawidowicz, Agnieszka; Pacholczyk, Marek Emanuel
• Is Part Of: Computers & geosciences. Volume 129(2019)
• Page Start: 26
• Page End: 37
• Publication Date: 2019-08
• Subjects: OpenStreetMap -- Geoprocessing -- Web-GIS -- Performance -- JTS -- Architecture; Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2019.04.011
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: The last decade has seen a rapid evolution of processing, analysis and visualization of freely available geographic data using Open Source Web-GIS. In the beginning, Web-based Geographic Information Systems employed a thick-client approach which required installation of platform-specific browser plugins. Later on, research focus shifted to platform-independent thin client solutions in which data processing and analysis was performed by the server machine. More recently, however, the rapid development of computer hardware as well as software technologies such has HTML5 has enabled the creation of platform-independent thick clients which offer advanced GIS functionalities such as geoprocessing. This article aims to analyse the current state of Open Source technologies and publicly available geographic data sources in the context of creating cost-effective Web-GIS applications for integration and processing of spatial data. For this purpose the article discusses the availability and potential of Web-GIS architectures, software libraries and data sources. The analysis of freely available data sources includes a discussion of the quality and accuracy of crowd-sourced as well as public sector data, while the investigation of software libraries and architectures involves a comparison of server-side and client-side data processing performance under a set of real-world scenarios. The article concludes with a discussion of the choice of cost-effective Web-GIS architectures, software libraries and data sources in the context of the institution and environment of system deployment. Highlights: Performance of client and server data processing is comparable for smaller datasets. Coverage and quality of open data sources is satisfactory for many applications. Choosing the proper data and Web-GIS architecture for the task may yield cost savings.