{"id":11731,"date":"2019-08-28T12:33:01","date_gmt":"2019-08-28T16:33:01","guid":{"rendered":"https:\/\/cnr.ncsu.edu\/geospatial\/?page_id=11731"},"modified":"2024-05-03T16:12:10","modified_gmt":"2024-05-03T20:12:10","slug":"near-real-time-decision-analytics","status":"publish","type":"page","link":"https:\/\/cnr.ncsu.edu\/geospatial\/research\/near-real-time-decision-analytics\/","title":{"rendered":"Creating Near Real-Time Decision Analytics"},"content":{"rendered":"\n\n\n\n\n
\"decision<\/figure>\n\n\n\n

Responding to Need<\/h2>\n\n\n\n

We believe that making discoveries through data should be possible for anyone, and that decision makers should have easy access to the robust scientific information they need to help them make tough choices.<\/p>\n\n\n\n

Our scientists combine experience in computer-human interaction, modeling, programming and geovisualization to produce systems that display data clearly, allow for intuitive interaction and help compare what-if scenarios of alternative futures.<\/p>\n\n\n\n

Learn more about the interdisciplinary researchers creating geospatial decision analytics:<\/p>\n\n\n

Faculty at the Frontier<\/span>\n\t\t<\/use>\n<\/svg>\n<\/span><\/a><\/div>\n\n<\/div>\n\n\n\n

Controlling Pest Invasion with PoPS<\/h2>

Every six months, our researchers meet with officials from the US Department of Agriculture and state agencies to run new simulations with our Pest or Pathogen Spread (PoPS) framework, using an interactive, web-based dashboard to test control strategies aimed at preventing the spread of invasive pests like spotted lanternfly.<\/p>

Watch PoPS in action<\/span>\n\t\t<\/use>\n<\/svg>\n<\/span><\/a><\/div>\n\n<\/div>\n\n<\/div>\n\n\n\n\n
\n
\"screenshot<\/figure>\n<\/div>\n<\/div><\/div>\n\n\n\n
\n
\n
\n
\n

DECISION ANALYTICS NEWS<\/h2>\n More<\/a>\n <\/div>\n
\n \n \n
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\n \"Flooded\n <\/div>\n <\/div>\n \n
\n

\n August 21, 2024<\/span>\n <\/p>\n \n

Using Machine Learning to Map Floods<\/h3>\n \n\n \n\t \t

A Ph.D. student at the Center for Geospatial Analytics trained a machine-learning model to create maps that could help identify potentially flood-prone areas in urban settings.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n \n

\n
\n \"Team\n <\/div>\n <\/div>\n \n
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\n May 01, 2024<\/span>\n <\/p>\n \n

Bridging Silos and More with GIS and Experiential Learning<\/h3>\n \n\n \n\t \t

During the Spring 2024 semester, our graduating professional master\u2019s students worked with industry, government and nonprofit partners to apply their knowledge and skills to pressing geospatial challenges.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n \n

\n
\n \"Bird\n <\/div>\n <\/div>\n \n
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\n December 14, 2023<\/span>\n <\/p>\n \n

The Varied Real-World Impacts of Experiential Learning<\/h3>\n \n\n \n\t \t

During the Fall 2023 semester, our graduating professional master\u2019s students worked with industry, government and nonprofit partners to apply their knowledge and skills to pressing geospatial challenges.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n \n

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\n \"Aerial\n <\/div>\n <\/div>\n \n
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\n June 27, 2023<\/span>\n <\/p>\n \n

New Tool Maps South Florida Fire Risk Pixel by Pixel<\/h3>\n \n\n \n\t \t

Center researchers designed a computer model called FireHydro to allow fire managers to map fire risk in South Florida on a day-to-day basis.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n \n

\n
\n \"Aerial\n <\/div>\n <\/div>\n \n
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\n May 04, 2023<\/span>\n <\/p>\n \n

Service Learning Partnerships Drive Innovation with GIS<\/h3>\n \n\n \n\t \t

During the Spring 2023 semester, our graduating professional master\u2019s students worked with industry, government and nonprofit partners to apply their knowledge and skills to pressing geospatial challenges.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n \n

\n
\n \"Raleigh\n <\/div>\n <\/div>\n \n
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\n December 15, 2022<\/span>\n <\/p>\n \n

GIS Service Learning to Support Public Lands, First Responders, City Planning and More<\/h3>\n \n\n \n\t \t

During the Fall 2022 semester, our graduating professional master\u2019s students worked with industry, government and nonprofit partners to apply their knowledge and skills to pressing geospatial challenges.<\/span>\n\t\t\t\n\t\t\t\n\t\t<\/svg><\/span><\/p>\n\t \t \n <\/div>\n\n <\/a>\n\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Responding to Need We believe that making discoveries through data should be possible for anyone, and that decision makers should have easy access to the robust scientific information they need…<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":11632,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"source":"","ncst_custom_author":"","ncst_show_custom_author":false,"ncst_dynamicHeaderBlockName":"ncst\/default-header","ncst_dynamicHeaderData":"{\"pageIntro\":\"We harness data as they become available to support faster, better informed decisions. We turn complex models and simulations into user-friendly discovery tools by developing sophisticated back-end algorithms and interactive front-end dashboards that visualize data clearly and quickly.\"}","ncst_content_audit_freq":"","ncst_content_audit_date":"","ncst_content_audit_display":false,"ncst_backToTopFlag":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-11731","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/pages\/11731","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/comments?post=11731"}],"version-history":[{"count":15,"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/pages\/11731\/revisions"}],"predecessor-version":[{"id":21766,"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/pages\/11731\/revisions\/21766"}],"up":[{"embeddable":true,"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/pages\/11632"}],"wp:attachment":[{"href":"https:\/\/cnr.ncsu.edu\/geospatial\/wp-json\/wp\/v2\/media?parent=11731"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}