BEGIN:VCALENDAR VERSION:2.0 PRODID:-//jEvents 2.0 for Joomla//EN CALSCALE:GREGORIAN METHOD:PUBLISH BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:19700308T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:19701101T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:c82b7d2845e70f3adb100c4fb67d0c5658 CATEGORIES:Webinars SUMMARY:FICUS: a Spatiotemporal Risk Analysis System DESCRIPTION:
Observations on the Implementation of a General Purpose Spatiote mporal Risk Analysis System Supporting Black Swan Theory strong>
A recording of this session can be found here on the UCGIS Webinar channel.
Dr. Ehlschaeger's presen tation can be downloaded from here (pdf). < /p>
Risk analyses for geospatial activities are constantly undermined by plans that have been created by multiple organizations for unfamiliar geogr aphies, involving imprecise data model and uncertain model parameters. More over, those responsible often have little capacity to communicate about com plex geo-temporal patterns with fellow information creators, analysts, and planners across the globe. Over the past decade, the University of Illinois at Urbana-Champaign, Colorado State University, and the US Army Corp of En gineers’ Engineer Research & Development Center has been collabor ating to construct a neighborhood-scale social, infrastructural, and enviro nmental modeling system that quantifies the uncertainty of all input data, propagates that uncertainty through tightly coupled space-time models, and visually presents uncertainty information and intuitive insights to planner s and analysts. The Framework Incorporating Complex Uncertain Systems em> (FICUS) is a computational framework that supports all the functions of a general purpose geographic and temporal analysis system with a focus on risk analysis. FICUS minimizes the Uncertain Geographic Context Problem (UG CoP), propagates uncertainty using the Object Modeling System as its comput ational framework and contains interdependent urban infrastructure network models to forecast network failures. It can tightly couple models from R, P ython, and NetLogo as well as most popular programming languages, and it it self is free and open source.
This presentation will discuss the theo retical and practical benefits of using an uncertainty quantifying, uncerta inty propagating, and uncertainty visualizing geographic information system for risk analysis with a case study in the Philippines. We will focus our discussions on the techniques that minimize or can even eliminate UGCoP, ca libration and validation in a multi-verse risk analysis paradigm, and cogni tive issues of understanding risk using Black Swan Theory.
Pr esenter: Dr. Charles (Chuck) Ehlschlaeger is a geographer with t he Engineering Research & Development Center – Construction Engin eering Research Laboratory (ERDC-CERL) of the US Army Corps of Engineers. He also teaches within the geography department at UIUC and the GIS Program at Johns Hopkins University.
You can find additional details about F ICUS and Dr. Ehlschaeger here.
A recording of this sessi on can be found here on the UCGIS Webinar channel.
Dr . Ehlschaeger's presentation can be downloaded from here (pdf ).
DTSTAMP:20240329T065427 DTSTART;TZID=America/New_York:20180926T150000 DTEND;TZID=America/New_York:20180926T160000 SEQUENCE:0 TRANSP:OPAQUE END:VEVENT END:VCALENDAR