Difference between revisions of "Use Case Template"

From Earth Science Information Partners (ESIP)
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====Primary Actors====
 
====Primary Actors====
Air quality analyst
+
Air quality analyst who seeks to understand the quality and behavior of the fire occurrence data in order to use it in modeling smoke emissions or analyzing the source of poor air quality due to smoke.
  
 
====Other Actors====
 
====Other Actors====
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===Preconditions===
 
===Preconditions===
 
*1.Satellite derived fire occurrence data are available
 
*1.Satellite derived fire occurrence data are available
*2.YYY validated
+
*2.Web services are available for conducting the spatial/temporal analysis
*3.ZZZ published
+
*3.Tools for creating analysis service flows are available.
  
 
===Postconditions===
 
===Postconditions===
*1.Datasets are ..
+
*1. A spatial-temporal analysis of fire occurrence data visualized in maps, time plots and tables.
*2.Appropriate action ...
+
*2. A better understanding of fir occurrence data quality and which satellites are most appropriate for air quality applications.
*3.Controls are ...
+
*3. Fire occurrence data is input to smoke emissions models and subsequent data analysis tools.
  
 
===Normal Flow (Process Model)===
 
===Normal Flow (Process Model)===

Revision as of 13:31, February 23, 2007

Use Case AQ.FireOccurence.1.a

Spatial and temporal analysis of satellite derived fire occurrence data

Purpose

Earth Information Exchange

To test web service orchestration for air quality data analysis.

Revision Information

Version 0.1.a

Prepared by: Stefan Falke Washington University and Northrop Grumman IT - TASC

created: February 23, 2007

Revision History

Modified by <Modifier Name/Affil>, <Date/time>, <Brief Description>

Use Case Identification

Use Case Designation

AQ.FireOccurence.1.a

Use Case Name

Short name: Fire location analysis

Long name: Spatial and temporal analysis of satellite derived fire occurrence data

Use Case Definition

Gathering and processing of fire occurrence data are very labor intensive. A web service based tool for semi-automating this analysis would allow analysis on historical and most recent data wherever and whenever needed (depending only on data availability and quality).

Smoke from biomass burning is an important component of air quality. Quantifying air pollutant emissions from wildfires and prescribed burning is one of the more uncertain inputs to air quality forecasting. Satellite data are being used to help improve the ability to accurately estimate emissions from fires. However, the quality of satellite dervired fire products for air quality applications is not well characterized:

  • multiple sensors detect fires - which to use?
  • missed detections (cloud cover)
  • false detections
  • spatial resolution limitations
  • temporal resolution limitations
  • size and types of fires detected

Two types of analyses conducted on satellite derived fire locations include:

  • satellite sensor - satellite sensor comparison
  • spatial coincidence of satellite with ground based observations

Through this use case, the air quality analyst works through the following steps:

  • Access sources of satellite fire location and fire perimeter data
  • Calculate area polygons using buffer analysis on satellite fire location data
  • Compare spatial and temporal correspondence of satellite polygons
  • Compare overlap of satellite polygons and surface fire perimeters
  • Generate spatial maps, temporal plots, and summary statistic tables

Actors

Primary Actors

Air quality analyst who seeks to understand the quality and behavior of the fire occurrence data in order to use it in modeling smoke emissions or analyzing the source of poor air quality due to smoke.

Other Actors

Preconditions

  • 1.Satellite derived fire occurrence data are available
  • 2.Web services are available for conducting the spatial/temporal analysis
  • 3.Tools for creating analysis service flows are available.

Postconditions

  • 1. A spatial-temporal analysis of fire occurrence data visualized in maps, time plots and tables.
  • 2. A better understanding of fir occurrence data quality and which satellites are most appropriate for air quality applications.
  • 3. Fire occurrence data is input to smoke emissions models and subsequent data analysis tools.

Normal Flow (Process Model)

  • 1)The user selects ...
  • 2)The user then ...
  • 3)The results of the XXX are ...
  • 4)The user ...

Alternative Flows

  • 1)The user selects the alternate ...
  • 2)The user then ...

Successful Outcomes

  • 1.Operation succeeds and user obtains QQQ.

Failure Outcomes

  • 1.Operation fails to return any XXX. Should instead YYYY.
  • 2.Illegal input of AAA, Should instead ZZZZ

Special Functional Requirements

None

Extension Points

  • <Cluster>.<SubArea>.<number>.<letter+1> something added or a variant.

E.g. AQ.Smoke.1.b something added or a variant

  • <Cluster>.<SubArea>.<number>.<letter+2> something added or a variant
  • <Cluster>.<SubArea>.<number>.<letter+3> something added or a variant

Diagrams

Use Case Diagram

State Diagram (optional)

Activity Diagram (optional)

Other Diagrams (optional)

Non-Functional Requirements (optional)

Performance

Reliability

Scalability

Usability

Security

Other Non-functional Requirements

Selected Technology

Overall Technical Approach

Architecture

Technology A

Description

Benefits

Limitations

Technology B

Description

Benefits

Limitations

References (optional)

Soja, et al., 2005: http://www.epa.gov/ttn/chief/conference/ei14/session12/soja.pdf Describes method used for analysis of fire locations/areas for May-August 2002 in Florida.