Summary from OGC AIP Committee
- Primary responses: EPA, ESIP AQ Cluster, ICT4EO, ISPRA, Northrop Grumman, VIEWS, Washington Univ
- Contributing responses: CIESIN, Compusult, ESA, ESRI, GOES-R and GMU, INCOSE, NASA World Wind, NOAA NCDC GOSIC, NOAA SNAAP
- Topics
- Air Quality and Human Health
- Proposing formation of a GEOSS Air Quality Community of Practice
- Wildland fire example
- AIRNow system proposed with interoperable interfaces
- user-defined areas for selected variables calculated by WPS
- SensorWeb which might apply best to AirQuality if the air sensors
- State of environment, emissions, and human health.
- intercontinental pollutant transport model
- Decision system pattern for AQ
- Global surfaces of population counts, densities, and quality measure of population-weighted mean geographic unit area, at two scales.
- Development of RM-ODP viewpoint descriptions
Further Analysis
EPA
Key Personnel
Phil Dickerson, EPA
Tim Dye, Sonoma Technology, Inc.
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
ESIP AQ Cluster
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
ICTeEO
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
ISPRA
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
Northrop Grumman
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
VIEWS
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility
Washington Univ
Key Personnel
Scenario
Infrastructure
Catalogues, Clearinghouse, Metadata
Data Product Access: service, schema, encoding
Sensors and Models Access: service, schema, encoding
Workflow for derived product and alert generation
Clients
Test Facility