Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

TL;DR

This study provides a comprehensive analysis of the global distribution, adoption, and performance of Web Map Services (WMS) by monitoring over 46,000 services for a year, revealing insights into their stability, quality, and usage patterns.

Contribution

It introduces a distributed monitoring framework and a crawling method to assess the global status and performance of WMS, filling a knowledge gap in geospatial service analysis.

Findings

Monitored 46,296 WMSs over one year for performance and stability.

Analyzed server locations, provider types, themes, and service versions.

Identified major causes of request errors and performance issues.

Abstract

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.