Applicability of open-source web mapping libraries for building massive Web GIS clients

被引:28
作者
Farkas, Gabor [1 ]
机构
[1] Univ Pecs, Doctoral Sch Earth Sci, Ifjusag St 6, H-7624 Pecs, Hungary
关键词
Approximate Learning Curve for [!text type='Java']Java[!/text]script; Client-side library; Comparison; Massive client; Software metrics; Web GIS;
D O I
10.1007/s10109-017-0248-z
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
The increasing capabilities of web browsers and the growing spread of JavaScript have an impact on the development of web-based GIS systems. While in traditional Web GIS applications the client-side component is only responsible for creating representation models, modern geographically enabled JavaScript libraries have extended capabilities, making them capable of doing extensive tasks, like complex geographical analyses. This paper identifies the most capable libraries for being the basis of a Web GIS client (Cesium, Leaflet, NASA Web World Wind, OpenLayers 2, and OpenLayers 3) and compares them. The libraries are compared by their GIS feature coverage and some quality metrics. OpenLayers 3 is identified for being the most capable library by supporting nearly 60% of the examined GIS features, its small size, and moderate learning curve. For comparing the learning curves of JavaScript libraries, a new metric named Approximate Learning Curve for JavaScript is proposed, which is based on other software metrics.
引用
收藏
页码:273 / 295
页数:23
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