Spatial Data Infrastructures for Big Geospatial Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (30 May 2022) | Viewed by 37465
Special Issue Editors
Interests: Earth science data and information systems; GIS; data science; semantics; cloud computing
Special Issues, Collections and Topics in MDPI journals
Interests: software system architecture; distributed computing; semantic web; geospatial analytics; geospatial AI
Interests: health GIS; VR/ARGIS; geospatial blockchain; semantic web; social web
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the past decades, information infrastructure, such as spatial data infrastructure (SDI), e-science, and cyberinfrastructure, have been benefiting scientific communities and supporting scientific research. The infrastructure could be used to exploit big data. Many national and international infrastructure projects have been conducted or are on-going, including Global Earth Observation System of Systems (GEOSS), the European Commission’s INSPIRE, and the U.S. NSF EarthCube. There are also many well-known groups working on geospatial infrastructure research and projects, including the intergovernmental Group on Earth Observations (GEO), Committee on Earth Observation Satellites (CEOS), United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM), IEEE GRSS Earth Science Informatics Technical Committee (ESI TC), U.S. Federation of Earth Science Information Partners (ESIP), and major space agencies around the world, including DLR, ESA, JAXA, NASA, NOAA, and USGS. The major international bodies setting standards for SDI, such as the Open Geospatial Consortium (OGC) and ISO TC 211, have over 400 organizational members and 40 country members, respectively.
Big geospatial data could take infrastructure-based approaches. On the one hand, large amounts of existing Earth science data are collected by remote sensors, taking advantage of the Internet of Things (IoT) and sensor web technologies. On the other hand, volunteered geographic information (VGI) and citizen sensors are bringing social content to geospatial data. Both could complement each other for enhanced data analysis and scientific discovery. These data, collectively annotated as big geospatial sensing data, can be acquired, visualized, analyzed, and shared through a computational cyberinfrastructure using open, extensible, and interoperable computational software. This Special Issue intends to collect current developments and future directions of using infrastructural methods, tools, and technologies to support big geospatial sensing data. We invite authors to submit their original papers. Potential topics include, but are not limited to:
- Data and information policies for spatial data infrastructure
- Data stewardship and preservation
- Provenance and quality
- Knowledge representation and information models
- Cyberinfrastructure, interoperability and standardization
- Data discovery and access
- Web-based services and analysis for big geospatial sensing data
- Semantic representation of the spatial and temporal relationships between entities in the geosciences (e.g., spatial and process ontologies, vocabularies, semantic web)
- Sensor web and applications
- Cloud computing
- Geospatial information, knowledge, and decision support systems
- Tools supporting spatial and temporal analyses of g geospatial sensing data and their applications
- Emerging information technologies and their applications in big geospatial sensing data
Prof. Dr. Peng Yue
Dr. Ingo Simonis
Prof. Dr. Maged N. Kamel Boulos
Guest Editors
Manuscript Submission Information
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Keywords
- Spatial Data Infrastructure (SDI)
- Cyberinfrastructure
- Geospatial Standards
- Big Geospatial Data
- Distributed Geospatial Data Management
- Geospatial Interoperability and Semantics
- Cloud Computing
- Big Geospatial Data Sensing
- Big Sensing Data Analytics
- Big Geospatial Data Processing
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