MeetingOfInterest:Meeting-324: Difference between revisions

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{{CSDMS meeting details template
{{CSDMS meeting details template
|MOI title meeting=AAG Annual Meeting 2019
|MOI title meeting=American Association of Geographers (AAG) Annual Meeting 2019
|MOI meeting city=Washington D.C.
|MOI meeting city=Washington D.C.
|MOI meeting state=District of Columbia
|MOI meeting state=District of Columbia
|MOI meeting country=United States
|MOI meeting country=United States
|MOI meeting startdate=2019/04/03
|MOI meeting startdate=2019/04/03
|MOI meeting enddate=2018/10/07
|MOI meeting enddate=2019/04/07
|MOI meeting figure=AMheader.jpg
|MOI meeting figure=AMheader.jpg
|MOI URL conference=https://annualmeeting.aag.org/AAGAnnualMeeting/Home.aspx
|MOI URL conference=https://annualmeeting.aag.org/AAGAnnualMeeting/Home.aspx
|MOI abstract deadline=2018/10/25
|MOI abstract deadline=2018/10/25
|MOI registration deadline=2019/02/23
|MOI registration deadline=2019/02/23
|MOI summary=Join fellow geographers, GIS specialists, environmental scientists, and other leaders for the latest in research and applications in geography, sustainability, and GIScience. The meeting will be held Wednesday, April 3, to Sunday, April 7, 2019. and will feature more than 6,000 presentations, posters, workshops, and field trips by leading scholars, experts, and researchers.
|MOI_CSDMS_yes_no=No
|MOI_CSDMS_yes_no=No
|MOI_highlight_sessions_yes_no=Yes
|MOI_highlight_sessions_yes_no=Yes
|MOI_add_conveners_yes_no=No
|MOI_add_conveners_yes_no=No
|Working group member=Terrestrial Working Group, Coastal Working Group, Education and Knowledge Transfer (EKT) Working Group, Hydrology Focus Research Group, Chesapeake Focus Research Group, Critical Zone Focus Research Group, Ecosystem Dynamics Focus Research Group, Coastal Vulnerability Initiative, Continental Margin Initiative, Artificial Intelligence & Machine Learning Initiative
}}
}}
{{CSDMS meeting sessions to highlight
{{CSDMS meeting sessions to highlight
|MOI highlighted session=Integrative modeling for coupled human and natural systems: linking models of human decision-making, land use, and environmental response
|MOI highlighted session=Integrative modeling for coupled human and natural systems: linking models of human decision-making, land use, and environmental response
|MOI URL to highlighted session=https://aag.secure-abstracts.com/AAG%20Annual%20Meeting%202019/sessions-gallery/23287
|MOI URL to highlighted session=https://goo.gl/r335wL
}}
}}
{{Conveners header template}}
{{Conveners header template}}
{{Define CSDMS interest groups
|Working group member=Terrestrial Working Group, Coastal Working Group, Education and Knowledge Transfer (EKT) Working Group, Hydrology Focus Research Group, Chesapeake Focus Research Group, Critical Zone Focus Research Group, Human Dimensions Focus Research Group, Ecosystem Dynamics Focus Research Group, Coastal Vulnerability Initiative, Artificial Intelligence & Machine Learning Initiative
}}

Latest revision as of 09:34, 4 March 2019


American Association of Geographers (AAG) Annual Meeting 2019
Washington D.C. District of Columbia, United States
03 - 07 April 2019
AMheader.jpg
Join fellow geographers, GIS specialists, environmental scientists, and other leaders for the latest in research and applications in geography, sustainability, and GIScience. The meeting will be held Wednesday, April 3, to Sunday, April 7, 2019. and will feature more than 6,000 presentations, posters, workshops, and field trips by leading scholars, experts, and researchers.

Sessions of interest
Integrative modeling for coupled human and natural systems: linking models of human decision-making, land use, and environmental response
https://goo.gl/r335wL


Of interest for:
  • Terrestrial Working Group
  • Coastal Working Group
  • Education and Knowledge Transfer (EKT) Working Group
  • Hydrology Focus Research Group
  • Chesapeake Focus Research Group
  • Critical Zone Focus Research Group
  • Human Dimensions Focus Research Group
  • Ecosystem Dynamics Focus Research Group
  • Coastal Vulnerability Initiative
  • Artificial Intelligence & Machine Learning Initiative