Abstract
Recent Web technologies such as HTML5, JavaScript, and WebGL have enabled powerful and highly dynamic Web mapping applications executing on standard Web browsers. Despite the complexity for developing such applications has been greatly reduced by Web mapping libraries, developers face many choices to achieve optimal performance and network usage. This scenario is even more complex when considering different representations of geographical data (raster, raw data or vector) and variety of devices (tablets, smartphones, and personal computers). This paper compares the performance and network usage of three popular JavaScript Web mapping libraries for implementing a Web map using different representations for geodata, and executing on different devices. In the experiments, Mapbox GL JS achieved the best overall performance on mid and high end devices for displaying raster or vector maps, while OpenLayers was the best for raster maps on all devices. Vector-based maps are a safe bet for new Web maps, since performance is on par with raster maps on mid-end smartphones, with significant less network bandwidth requirements.
Highlights
IntroductionSince the introduction of modern Web maps (https://gistbok.ucgis.org/bok-topics/webmapping) that lets users zoom and pan around, there has been a relentless popularization of Web mapping [1,2]
Since the introduction of modern Web maps that lets users zoom and pan around, there has been a relentless popularization of Web mapping [1,2]
To build a Web mapping application for displaying the Life Quality Index (LQI) data as a layer over a base map, we considered three main technological alternatives, which are summarized in Figure 3: 1. Raster tiles: this alternative displays static images or bitmaps that are provided by a server
Summary
Since the introduction of modern Web maps (https://gistbok.ucgis.org/bok-topics/webmapping) that lets users zoom and pan around, there has been a relentless popularization of Web mapping [1,2]. The enabler to accomplish these Web maps is the idea of decomposing large and complex maps into many small tiles [3] that are downloaded, seamlessly joined together, and displayed on demand by a Web browser such as Google Chrome or Mozilla Firefox The practical impact of these technologies has been important, since they provided a simple way to enrich maps with geographic information from third parties [5,6], making Web mapping applications more flexible and even more widespread [7] Accompanying this evolution, standard formats for representing and transferring geographic data for the Web emerged. Notable examples are GeoJSON [8], an open standard format designed for representing simple geographical features, along with their non-spatial attributes, TopoJSON (https: //github.com/topojson/topojson-specification), a variant of GeoJSON that encodes topology stitching together shared line segments, and the Geography Markup Language (GML), an XML grammar for expressing geographical features [9]
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