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Estimation and Uncertainty of Air Pollutant Concentrations using Spatial Interpolation

This scenario is provided by the Institute for Geoinformatics (IfGI) of the University of Muenster (Germany). The goal of the scenario is to provide estimates of air pollutant concentration including uncertainty information at places where no measurements are available. These estimates can then be used by domain scientists to correlate them to health data (e.g. respiratory system) and by decision makers to decide on action items.

The main steps are the following: A scientist searches for appropriate Sensor Observation Services providing air pollutant observations in the area of interest and for Web Processing Services providing interpolation processes. He then interpolates the observations to retrieve an estimate for a certain point/area of interest and visualizes the results. As these are estimates he also visualizes the interpolation error.

Scenario Implementation Instances
During AIP-3, the scenario will be implemented for:
  • Europe (Netherlands? - need to pick region)
  • North America (United States - need to pick region) 
Wiring Diagram

Scenario Steps

 Scenario Name
Engineering Use Cases
 Specialization of Use Cases
 CB-PD-01. Discovery of Sensor Observation Service (SOS) offering air pollutant observations and WPS offering kriging interpolation.


01.1. Scientist uses IP3 client application to submit a query to the IP3 Mediation Service and discover the presence datasets in SOS for the pollutant of interest.
N°. Name Desc.
 06Interact with ServicesActivity of client to consume services for datasets, sensors, models, workflows, etc
 Depending on the available metadata and search capabilities, different search specializations are possible (e.g. search on keywords, spatial extent, temporal extent, spatio-temporal extent, etc.) TBD
01.2. IP3 Mediation Service mediates the query request distributing it to the Air Qualtiy Community Catalog.
N°. Name Desc.
 06Interact with ServicesActivity of client to consume services for datasets, sensors, models, workflows, etc

01.3. Scientist browses SOSs returned by the query andselects one SOS.
N°.      Name  Desc.
 05     Presentation of Reachable Services & Alerts User presentation of information about available services, workflows, and alerts
 
01.4. Scientist searches for interpolation services by using keywords.
N°.  Name  Desc.
 06 Interact with Services Activity of client to consume services for datasets, sensors, models, workflows, etc
 
         01.5.  IP3 Mediation Service mediates the query             request distributing it to the Air Qualtiy                         Community Catalog. 
N°. Name Desc.
 06Interact with ServicesActivity of client to consume services for datasets, sensors, models, workflows, etc
 
        01.6. Scientist browses WPSs returned by the            query andselects one WPS. 
N°.     Name Desc.
 05    Presentation of Reachable Services & AlertsUser presentation of information about available services, workflows, and alerts
 
 AQH-D-02. Interpolation of air quality observations



 
02.1. Scientist creates PWS request by using the URL of the selected SOS and specifiying the intepolation method and its parameters in the client application

 
02.2. Scientist executes interpolation through the client application and retrieves the results.

A couple of specialized use cases is anticipated for describing Catalog Federation Mechanisms (mappings).
 02.3. As the resulting value surface is interpolated and thus contains estimates, each value has an associated interpolation error. To decide, whether the values are usable, scientist visualizes also the
error probability .
   
 02.4. Scientist uses results to inform decision makers about air quality at their points of interest.
   

Issues:

1. How can SOSs and WPSs be integrated in the AQ Community Catalog?
2. Certain area of interest has to be chosen for scenario.

Legend:

AIP-3 Services in blue
AIP-3 Products in red
AIP-3 Actors in orange
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Stefan Falke,
Jul 29, 2010, 3:26 AM
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