Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.
","abstract_html":"<p>Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.</p>","abstract_has_math":false,"creators":["Blinn, Christopher Michael"],"institution":null,"degree_name":"Master of Science","degree_level":null,"degree_discipline":"Department of Geography and Geology","degree_department":null,"school":null,"contributors":["Dr. Stuart Foster, Director, Dr. David Keeling, Dr. Jun Yan, Dr. Joshua Durkee, Kevin Cary"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-05-25T07:00:00Z","date_published":"2012-05-25T07:00:00Z","updated_at":"2026-07-24T06:08:16Z","subjects":["GIS","Geographical Information Systems","Severe weather","Maps","Geographic Information Sciences","Meteorology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wku.edu/theses/1153","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Stuart Foster, Director, Dr. David Keeling, Dr. Jun Yan, Dr. Joshua Durkee, Kevin Cary"]},{"key":"dc:creator","label":"Author","values":["Blinn, Christopher Michael"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Department of Geography and Geology"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["GIS","Geographical Information Systems","Severe weather","Maps","Geographic Information Sciences","Meteorology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wku.edu/theses/1153"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.
"]},{"key":"dc:title","label":"Title","values":["Creation of a Spatial Decision Support System as a Risk Assessment Tool Based on Kentucky Tornado Climatology"]}]}],"canonical_facts":{"dc:contributor":["Dr. Stuart Foster, Director, Dr. David Keeling, Dr. Jun Yan, Dr. Joshua Durkee, Kevin Cary"],"dc:creator":["Blinn, Christopher Michael"],"dc:description.abstract":["Tornadoes are one of Mother Nature’s deadliest phenomena. They affect a large region of the United States. The risk of tornadoes is contingent on dynamic atmospheric conditions that are most likely during spring but which can occur anytime of the year, making the storms challenging to forecast. Using geographical information systems (GIS), a web-based spatial decision support system (SDSS) was created to help understand the spatial dimension of tornado risk assessment. The risk values are calculated using Tornado Days rather than taking a crude density measurement. The SDSS hosts GIS web services that are displayed on an Adobe Flex application. The web application allows users to view, research, query and extract information from the attributes of the GIS files. There is also a dynamic risk tool which gives users the ability to click anywhere inside the study area and get the percentage of risk that a tornado will occur within 25 miles of that very point. The web application eliminates users and viewers from conducting their own research and GIS work. In addition, automated updating models and macros were created to update the tornado database on an annual basis.
"],"dc:identifier":["https://digitalcommons.wku.edu/theses/1153"],"dc:subject":["GIS","Geographical Information Systems","Severe weather","Maps","Geographic Information Sciences","Meteorology"],"dc:title":["Creation of a Spatial Decision Support System as a Risk Assessment Tool Based on Kentucky Tornado Climatology"],"dc:type":["Thesis"],"thesis:degree_discipline":["Department of Geography and Geology"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T06:08:16Z"}