Infrastructure Data Collection Solutions Measuring and GIS Referencing of Network Level Pavement Deterioration in Post-Katrina Louisiana March 19, 2008
Hurricane Katrina August 2005 I-10 I-610 West End Blvd. Interchange source: http://en.wikipedia.org/wiki/hurricane_katrina
Hurricane Katrina August 2005 Touched land August 29 2005 Directly hit District 02 including the City of New Orleans Over 1,800 people died as a result of the storm Property damage estimated at $81 Billion The DOTD and The Federal Emergency Management Agency (FEMA) were in discussions with regards to assigning funding appropriate to the damage done by the hurricane The DOTD contracted FWD testing for the district to assess the condition of the roads FEMA was not prepared to accept this data as proof of damage caused by Katrina, as there was no historical comparison Pavement distress data had been collectedonatwoyearcyclesince1994 Right Of Way imagery collected concurrently with the pavement data
Louisiana DOTD Statewide data collection had been collected on a two year cycle for over 10 years Collected Data Includes: Digital Videolog Pavement Imagery Distress Data Roughness Rutting Faulting All Collected data and imagery are associated to the Linear Referencing System as well as GPS
Fugro-Roadware Roadware Group is a division of Fugro World Wide Established in 1969 Largest automated collector of road data in North America Design, build, support & operate the ARAN Data elements collected GPS Data Pavement Images Rutting depths International Roughness Index (IRI) Right of Way Images
Pavement Condition Data Rear downward facing cameras Continuous pavement images of full lane width Distresses 2mm (0.08 inches) in size
Pavement Distress
Rutting Pair of INO Lasers Measure full transverse profile of the road surface Profile is evaluated to determine the depths of ruts
International Roughness Index (IRI) Laser SDP System 16 khz laser in each wheelpath Measures continuous profile of the roadway
GPS Data Trimble System Applanix POS (Position and Orientation System) Collected every 10 millimiles (52.8 feet) Two antennas to give vehicle heading
Right Of Way Images Wide angle High Definition images A single image every 5 millimiles (26.4 feet)
End Result Multi dimensional set of accurate condition data Data is linear referenced, but also accurately georeferenced Linear referencing is the typical way to view condition data GPS data typically used to verify road section segmentation We now have the ability to sort and analyze data spatially
Geo-Referenced Distress Data Pavement Distress rated according to LADOT specific rating protocol. Random (Miscellaneous) Cracking chosen for the purpose of this presentation
Segment Level Data
Segment Level Data
Station Level Data
Deterioration Curves COMPOSITE INTERSTATE DETERIORATION CURVE 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 ROUGHNESS INDEX AGE COMPOSITE CURVE Possible Modified Curve Post Katrina Single Year Curve
Deterioration Curves JOINTED INTERSTATE DETERIORATION CURVE 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 ROUGHNESS INDEX AGE CONCRETE CURVE Possible Modified Curve Post Katrina Single Year Curve
Summary TheDOTDwillbecomparingthedatafromthe3 consecutive cycles. Loaded into the PMS for analysis Planned treatments, life cycle costing, and deterioration curves will be reviewed Having had a comprehensive and integrated data collection, PMS, and GIS program will allow the DOTD to: Compare year over year data and imagery Analyze the impact of any major changes within District 02 Have a factual foundation for a discussion around the economic impact
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