An Observation Capability Metadata Model for EO Sensor Discovery in Sensor Web Enablement Environments
Year: 2014
Type: article
Abstract: Accurate and fine-grained discovery by diverse Earth observation (EO) sensors ensures a comprehensive response to collaborative observation-required emergency tasks. This discovery remains a challenge in an EO sensor web environment. In this study, we propose an EO sensor observation capability metadata model that reuses and extends the existing sensor observation-related metadata standards to enable the accurate and fine-grained discovery of EO sensors. The proposed model is composed of five sub-modules, namely, ObservationBreadth, ObservationDepth, ObservationFrequency, ObservationQuality and ObservationData. The model is applied to different types of EO sensors and is formalized by the Open Geospatial Consortium Sensor Model Language 1.0. The GeosensorQuery prototype retrieves the qualified EO sensors based on the provided geo-event. An actual application to flood emergency observation in the Yangtze River Basin in China is conducted, and the results indicate that sensor inquiry can accurately achieve fine-grained discovery of qualified EO sensors and obtain enriched observation capability information. In summary, the proposed model enables an efficient encoding system that ensures minimum unification to represent the observation capabilities of EO sensors. The model functions as a foundation for the efficient discovery of EO sensors. In addition, the definition and development of this proposed EO sensor observation capability metadata model is a helpful step in extending the Sensor Model Language (SensorML) 2.0 Profile for the description of the observation capabilities of EO sensors.
Source: Remote Sensing
DOI: 10.3390/rs61110546
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W2007019703