IPM GIS Mapping: A Tale of Rats and Maps
NEHA 2014 AEC ConventionLas Vegas, NevadaJuly 10th, 2014
Joshua D. Witt, REHSEnvironmental Health Program ManagerUCLA Office of Environment, Health & Safety
Alan Chen, MPHEnvironmental Health Program InternUCLA Office of Environment, Health & Safety
www.ehs.ucla.edu
UCLA is a small city!
Founded
StudentsFaculty & Academic StaffStaff PersonnelTotal Campus PopulationAcresPeople/AcreNumber of UC CampusesUCLA Population Density
1919
41,341
10,875
31,262
83,478
419
199.2
10
#1
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This rodent found a home
Our assumptions
• UCLA will always have a baseline population of rodents due to the following factors:
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Current approach: IPM combined with rodent bait stations
• Open• Closed
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2008 2009 2010 2011 2012 20130
50
100
150
200
Nu
mb
er
of
Rod
en
t R
ep
ort
sNumber of rodent reports
-67%
Average 2009-2013: 59.6
2008: 181
Year
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Bait station analysis
• Sections include:– Building name– Bait station
number– Location– Status/condition
• Media– Pictures–Map of station
status
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How can we improve?• We shall synthesize and collate large amounts of
complex, intersecting information to create innovative solutions…using GIS
• Visualize• Question• Analyze• Interpret
What is GIS?
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What are our overarching goals?
• Demonstrate the viability and usefulness of the GIS project to:– Improve campus Integrated Pest
Management– Increase stakeholder focus and
cooperation– Advocate for situation-appropriate
resources
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The question of the hour:
• Where should we reallocate our rodent bait stations and focus our IPM energy to prevent rodent infestations?
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How did we do it?
• Program used: ESRI ArcGIS version 10.1– To be compatible with UCLA GIS-users
–Why is that important?• Some of them have data relevant to this
project
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Buildings serviced by EH&S
• 116/265 buildings (~44%)
• We do not service medical center or housing business units
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Question for YOU
•What might be some factors that contribute to rodent infestations?
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Trash Cans
• # of trash cans: 616
• Trash cans are not rodent proof
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Age of Building
• Demarcated by 10 year increments
• Shows susceptibility to rodent penetration
• Oldest currently existing building built in 1921
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Food Facilities
• Areas where the campus community consumes food
• 53 locations
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Dining Areas
10dining areas
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Rodent Harborage: Algerian Ivy
• 11 ivy patches
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Loading Docks
35loading docks
15are
conducive to pests
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Vending Machines
49 vending
machines
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Yearly rodent incident reports:2008-2013
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6 year collection of rodent incident reports: 2008-2013
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Bait Stations
269bait
stations
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GIS shrunk the data by 99.2%!
• 1903 data points converted to: • 16 maps– 8 maps of contributing factors– 6 maps of rodent reports, 1 for each individual
year 2008-2013 – 1 summary map of all rodent reports 2008-
2013– 1 map of bait station locations
• Synthesizing from 1903 to 16 is a giant leap. Can we go even farther? YES!
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Solution: Suitability Model• A model that weights locations relative
to each other based on given criteria
• Suitability models might aid in finding a favorable location for a new facility, road, or habitat for a species of bird
• Basically, a suitability model “puts it all together”
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Suitability Model: How we weighted our factors
1. Rodent Report Locations: 30%2. Trash Cans: 20%3. Building Age: 10%4. Food (facilities + dining areas):
10%5. Ivy: 10%6. Loading Docks: 10%7. Vending Machines: 10%
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Suitability Model: From 16 to 1
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What are the big takeaways?
• GIS visualization can “connect the dots”– New insight on areas needing bait stations
• How else could GIS help us (and YOU)?– GIS is the new version of John Snow’s
cholera map– Show that food-borne illness complaints
are correlated with location, type, size– Reveal that housing complaints are
clustered in a certain area
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Credits
• Credit for project management and creating the GIS maps goes to – Alan Chen, MPH – Airalee E. Rivera
• Special thanks to – Jennie Wung, REHS
Thank you!
