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International Journal of Digital Earth Volume 7, 2014 - Issue 4: Analytical Geospatial Digital Earth
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Original Articles

An open source, server-side framework for analytical web mapping and its application to health

Simon MoncrieffCooperative Research Centre for Spatial Information, Department of Spatial Science, Curtin University, Perth, AustraliaCorrespondence[email protected]
,
Geoff WestCooperative Research Centre for Spatial Information, Department of Spatial Science, Curtin University, Perth, Australia
,
James CosfordCooperative Research Centre for Spatial Information, Department of Spatial Science, Curtin University, Perth, Australia
,
Narelle MullanCooperative Research Centre for Spatial Information, Department of Spatial Science, Curtin University, Perth, Australia
&
Andrew JardineCooperative Research Centre for Spatial Information, Department of Spatial Science, Curtin University, Perth, Australia
Pages 294-315 | Received 15 Feb 2012, Accepted 11 Mar 2013, Published online: 19 Apr 2013

Figures & data

Figure 1. (a) WMS method for generating thematic maps (e.g. GeoServer). (b) Dynamic, client-side styling method for generating thematic maps. (c) Dynamic, server-side styling method for generating thematic. (d) Proposed method for generating thematic maps.
Figure 1. (a) WMS method for generating thematic maps (e.g. GeoServer). (b) Dynamic, client-side styling method for generating thematic maps. (c) Dynamic, server-side styling method for generating thematic. (d) Proposed method for generating thematic maps.
Figure 2. Overview of the system design.
Figure 2. Overview of the system design.

Table 1. Attribute property metadata.

Figure 3. Analytical workflow used to generate a thematic map.
Figure 3. Analytical workflow used to generate a thematic map.
Figure 5. (a) Rate ratio styled using Equal Intervals. (b) Rate ratio styled using Natural Breaks.
Figure 5. (a) Rate ratio styled using Equal Intervals. (b) Rate ratio styled using Natural Breaks.
Figure 6. (a) Raw count, 18- to 24-year-old demographic. (b) The 18- to 24-year-old demographic as a proportion of the underlying population.
Figure 6. (a) Raw count, 18- to 24-year-old demographic. (b) The 18- to 24-year-old demographic as a proportion of the underlying population.
Figure 7. (a) Direct ASR for ICD-10 Chapter K. (b) Direct ASR for ICD-10 Chapter K, ages 18–35 (baselayer: © OpenStreetMap contributors, openstreetmap.org).
Figure 7. (a) Direct ASR for ICD-10 Chapter K. (b) Direct ASR for ICD-10 Chapter K, ages 18–35 (baselayer: © OpenStreetMap contributors, openstreetmap.org).

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