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Articles

Connected Geomatics in the big data era

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Pages 139-153 | Received 20 Oct 2016, Accepted 22 Mar 2017, Published online: 11 Apr 2017

Figures & data

Figure 1. Process of spatio-temporal data mining.

Figure 1. Process of spatio-temporal data mining.

Figure 2. Ubiquitous space-borne, air-borne and ground-based geospatial sensors.

Figure 2. Ubiquitous space-borne, air-borne and ground-based geospatial sensors.

Figure 3. 3D modeling through multi-angle tilt images.

Figure 3. 3D modeling through multi-angle tilt images.

Figure 4. Subsidence rate of the ground surface in Shanghai determined from PS-InSAR multi-temporal data analysis.

Figure 4. Subsidence rate of the ground surface in Shanghai determined from PS-InSAR multi-temporal data analysis.

Figure 5. Workflow of the OpenRS-Cloud service.

Figure 5. Workflow of the OpenRS-Cloud service.

Figure 6. Overall geometric correction of ZY-3 satellite imagery of China.

Figure 6. Overall geometric correction of ZY-3 satellite imagery of China.

Figure 7. LEO constellation of the integrated space-based real-time information service system.

Figure 7. LEO constellation of the integrated space-based real-time information service system.

Figure 8. SDE for the night-time light in the OBAOR region during 1993–2013.

Figure 8. SDE for the night-time light in the OBAOR region during 1993–2013.

Figure 9. Understanding the spatio-temporal spread and revolution of web hot events.

Figure 9. Understanding the spatio-temporal spread and revolution of web hot events.

Figure 10. Service-focused geospatial information framework.

Figure 10. Service-focused geospatial information framework.

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