Title :
Remote sensing satellite sensor information retrieval and visualization based on SensorML
Author :
Hu, Chuli ; Chen, Nengcheng ; Wang, Chao
Author_Institution :
State Key Lab. for Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China
Abstract :
In the era of high-frequency occurrence of natural disasters, users are more urgently concerned with the sharing of the satellite sensor resources information and coordinating the complement of sensor observation. However, the capacity of discovering, retrieving and visualizing the sensor resource information accurately based on heterogeneous sensors over sensor network is very limited. This paper proposes the system architecture for effectively managing those heterogeneous and multiple sensors and their information, which is inspired by the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Initiative and based on one of its information model- Sensor Model Language (SensorML) of which Process Model is the core. The prototype "SensorModel VI. 0" is designed and implemented used to construct the standard model for unified management of multiple remote sensing satellite sensor resources information and demonstrate the model-based retrieval and visualization of related remote sensors and their information, which promotes the comprehensive accessing and collaborative planning/controlling the available remote sensor\´s information in time-critical disaster emergency.
Keywords :
data visualisation; disasters; geophysics computing; information dissemination; information resources; information retrieval; public domain software; remote sensing; OGC Sensor Web Enablement; Open Geospatial Consortium; Process Model; Sensor Model Language; SensorML; heterogeneous sensors; high-frequency occurrence; information model; multiple remote sensing satellite sensor resource information; natural disasters; remote sensing satellite sensor information retrieval; satellite sensor resources information sharing; sensor network; sensor observation; system architecture; time-critical disaster emergency; visualization; Data models; ISO standards; Information services; Orbits; Remote sensing; Satellites; Visualization; Model-based Management; Remote sensing; Satellite Sensor Information Model; Sensor Resource Intensive Information; SensorML;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6049956