Zeqiang Chen

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Keywords: Active on-demand Data service Event-driven architecture Sensor web MODIS Fire a b s t r a c t Timely on-demand access to geospatial data is necessary for environmental observation and disaster response. However, traditional service methods for acquiring geospatial data are inefficient and cumbersome, which is not beneficial for timely data(More)
Keywords: BigTIFF GDAL WMS WCS On-demand NDVI MODIS a b s t r a c t By applying advanced Geospatial Data Abstraction Library (GDAL) and BigTIFF technology in a Geographical Information System (GIS) with Service Oriented Architecture (SOA), this study has derived global datasets using tile-based input data and implemented Virtual Web Map Service (VWMS) and(More)
Significant economic losses, large affected populations, and serious environmental damage caused by recurrent natural disaster events (NDE) worldwide indicate insufficiency in emergency preparedness and response. The barrier of full life cycle data preparation and information support is one of the main reasons. This paper adopts the method of integrated(More)
Remote sensing plays an important role in flood mapping and is helping advance flood monitoring and management. Multi-scale flood mapping is necessary for dividing floods into several stages for comprehensive management. However, existing data systems are typically heterogeneous owing to the use of different access protocols and archiving metadata models.(More)
BACKGROUND Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service(More)
Efficient information management and precise discovery of heterogeneous sensors in the Geospatial Sensor Web (GSW) are a major challenge. Intelligent sensor management requires a registry service to store and process sensor information efficiently. In this paper, we propose a Sensor Metadata Ontology (SMO) to achieve a unified semantic description for(More)
Comprehensive surface soil moisture (SM) monitoring is a vital task in precision agriculture applications. SM monitoring includes remote sensing imagery monitoring and in situ sensor-based observational monitoring. Cloud computing can increase computational efficiency enormously. A geographical web service was developed to assist in agronomic decision(More)
The provenance of observations from a Sensor Web enabled remote sensing application represents a great challenge. There are currently no representations or tracking methods. We propose a provenance method that represents and tracks remote sensing observations in the Sensor Web enabled environment. The representation can be divided into the description(More)