Cassie Mann
UEP 232
March 10, 2014
Assignment 4: Data Quality
Emergency Preparedness in Portland
My pretend project for this assignment is the development of an emergency preparedness and response
plan for the City of Portland, Maine. The purpose of the exercise is to map evacuation routes and locations of
key landmarks and resources that may be critical to effectively managing disaster response activities. This
includes roads, water access, and entities like schools, police stations, fire and EMS stations, and hospitals,
which might provide critical services or serve as meeting points or shelters during an emergency. For this
exercise I have also included a data layer showing bridges (including overpasses and larger spans), as knowing
the location of overpasses over city roads can be important to determining which roads can accommodate
oversized vehicles that may need to maneuver during an emergency or disaster response. In terms of positional
accuracy in this disaster response scenario, data need to be as accurate as possible to allow emergency vehicles
and rescue teams to move quickly, and to allow residents to easily access services like gathering places,
emergency shelters, and other resources. A difference of up to about fifteen or twenty feet would be acceptable
for resources like the police, fire and EMS, hospitals and schools, as these buildings generally have good
signage and, in an emergency scenario, would likely be quite busy and therefore noticeable for a pedestrian or
driver trying to find them. Bridges would need to be more accurate, particularly in terms of their placement
along a particular road. For example, if the map shows an overpass along a road, emergency vehicles may plan
to turn off of that road just before the overpass. But if the overpass is positioned inaccurately on the map, the
vehicles may not be able to turn off in time to avoid it, causing unnecessary delays.
Because this project is focused on the timely and efficient movement of people and emergency vehicles,
connectivity is especially important. The map needs to show how exactly the ambulances, fire trucks, or other
large vehicles can access any point in the city. Attribute accuracy is especially important for the resources like
hospitals, police stations, fire and EMS, and schools. While these entities are not as likely to be mislabeled (ie. a
liquor store being labeled “grocery”), mistakes in the attribute table could cause certain resources to either not
show up, or be classified incorrectly. It is very important that the data be complete, particularly in terms of the
road infrastructure and bridges. Missing data could cause significant delays, which are especially problematic in
an emergency scenario. Likewise, the data need to be current, ideally within five years.
Roads
For this project, I used road data from the Maine GIS Office (Next Generation 911 Roads) as well as the
2013 Census TIGER Centerlines. Both data sets are very current, as they were both updated in 2013. For the
most part, both road data layers had strong positional accuracy, tracking quite closely to the actual centerlines of
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Portland’s roads shown in the aerial imagery. The Census Centerlines tended to be more accurate, staying very
close to the centerlines shown in the aerial imagery. The Maine GIS data strayed most often from the center,
and at some points the distance between the two was considerable. In the image below, the distance between the
Census lines in orange and the Maine GIS lines in blue measures 37.9’ at the intersection of Middle Street and
Franklin Arterial. For this project, it is not a problem for the road lines not to adhere perfectly to the street
centerlines, therefore either data set’s positional accuracy would be acceptable.
Image 1: Road Accuracy and Completeness
The above image shows Franklin Arterial, a major thoroughfare in the city that runs from highway 295 to the
waterside area along Casco Bay. The Census TIGER Centerlines, in orange, do not connect at these
intersections, and for some reason, they do not run along Franklin Arterial at all. This incompleteness would be
a major problem for any disaster preparedness planning, as Franklin is a very important connector in the city.
The attribute table for the Maine GIS roads includes a lot of useful information that would be important
for this project, including road type (private, local, primary and secondary) and route numbers in addition to
road names, and information about the town and county where the road is located. The attribute table for the
Census TIGER Centerlines includes a lot of information, but not in a very easily digestible format. There is no
clearly labeled column for road type, or information about route numbers, or information about town or county
location. Having road type information would be particularly useful for this project, as planners could choose
the best type of road for easy evacuation or for oversized vehicles.
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In the image below, the Census 2013 TIGER Centerlines are shown in orange, while road data from the
Maine Office of GIS appears in light blue. At the below intersection, the Census TIGER lines do not connect to
form the intersection as the Maine GIS lines do. The Census TIGER line also stops abruptly along the block in
the lower-left corner, while the Maine GIS line continues to follow Hoyts Lane through to the next street. This
discrepancy can probably be explained by the fact that Gilbert Lane and Hoyts Lane are both essentially alleys,
though they are used as through-streets. This connectivity issue would be important for disaster response
planning, as the Census TIGER roads make it appear that the roads do not connect, which might cause the city
to plan a longer route than is necessary.
Image 2: Road Connectivity
Overall, while the Census TIGER Centerlines data track more closely to the road centerlines, the data is not as
complete, and lacks connectivity and valuable attribute information that would be important for this project.
The Maine GIS data would be better for this emergency preparedness planning scenario.
Hydrography
The positional accuracy of the Census TIGER hydrography shape file is not very strong, as evidenced
by the photo below. This is understandable given the intricate shape of the wharfs along Portland’s harbor, but it
still could create problems for mapping for emergency preparedness, as emergency boats or passenger vessels
would need to be able to plan for where they can dock to load and unload people and resources.
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Image 3: Census TIGER Hydrography Data
As seen above, the distance between the Census TIGER Hydrography data and the actual extent of the water in
the aerial image is up to 618 feet – an enormous difference. The Census data makes it appear that the edge of
the water is further out than it is in reality, which could cause confusion for this project’s planning.
Image 4: National Hydrography Data
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The National Hydrography Data Set shows far greater positional accuracy than the Census TIGER hydrography
data. As seen above, at its most inaccurate point, the data is only off by 102 feet, and otherwise it tracks very
closely to the shore and piers as shown in the aerial imagery. The National Hydrography Data Set would be best
for the purpose of this project.
Bridges
The Maine GIS data set on bridges was created in January, 2013, making it fairly current. According to the
metadata, the data set includes all bridges over public roads with spans greater than 10 feet. The positional
accuracy of this data set is very important, especially for overpasses that might be lower in height, under which
large vehicles might not be able to pass. As shown below, the positional accuracy of this data set is quite strong,
as each green square appears in the center of a bridge. However, the data set only includes one point for each set
of highway overpasses, rather than labeling each one separately. In the image below, the red circles indicate
bridges or highway ramps that are unmarked, making the data somewhat incomplete. This incompleteness could
present confusion for planners working on emergency preparedness, and therefore would not be ideal for this
project unless the additional bridges were added.
Image 5: Bridges
Hospitals
The hospital data set also comes from the Maine GIS Office, and was last updated in January 2013. Despite
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that update, the data set is missing one prominent hospital, Mercy Hospital’s Fore River Campus, which opened
in 2008. Because of that omission, this data set is not complete.
Image 6: Missing Hospital
Both of the hospitals shown in Portland are represented as single points on the map, and for both of them, the
point is located on top of the building, rather than at a street address. While the points are accurately placed on
the hospitals (rather than across or down the street), their placement on top of the buildings could cause
problems for emergency planning, as it would be important to be able to show people exactly where to enter the
hospital. For Maine Medical Center, the point is placed close to the hospital’s official listed address, 22
Bramhall Street, although, as shown below, the hospital’s main entrance is located around the corner, and the
emergency room entrance is on the opposite side of the building.
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Image 7: Hospital Entrance
The two hospitals shown, Maine Medical Center and Mercy Hospital, are well-known by residents and have
clear and prominent signage that would help mitigate confusion about entrance locations. Still, the omission of
the Mercy Fore River Campus is problematic and suggests that there might be other omissions elsewhere, so
this data set would not be complete enough for use in this project.
Fire/EMS Stations
The fire/EMS data also comes from the Maine GIS Office and was last updated in March 2014. The positional
accuracy for this data is very high. As shown below, the point on the map is located in the front driveway of the
fire station. The attribute contains complete information for the fire stations in Portland, and its data
corresponds with address information listed on the Portland Fire Company’s website. This data set would be
appropriate for use in the project given the positional accuracy and completeness of the data.
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Image 8: Fire Station
Police
Similar to the hospital data set, the police department location is marked by a point on top of the building, rather
than at the entrance. While this discrepancy could cause confusion for people looking for the entrance in an
emergency, the building does have a prominent sign above the entrance, which could mitigate this problem.
Given the positional accuracy and completeness of the data set, this data set would be appropriate for use in this
emergency preparedness project.
Image 9: Police Station Entrance
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Schools
The schools data set is also from the Maine GIS Office, and was last updated in November, 2013. Attribute
accuracy was a problem for this data set. The attribute table lists school names and addresses, but does not
include information about the type of school (ie. university, public, private, elementary, professional), therefore
the data includes several entries that might not typically be thought of as schools, and would be less appropriate
for incorporation into an emergency plan. For example, Pierre’s School of Cosmetology may not function well
as an emergency shelter the way an elementary school cafeteria would, yet it is still labeled as a school on the
map. It is also not well-known by residents as a school, so might cause some confusion.
Image 10: School Accuracy
The map also shows Cliff Island School and Peaks Island Elementary School to be located at 4 Church Street in
Portland. In reality, Cliff Island School is located on Cliff Island, and Peaks Island Elementary on Peaks Island,
and both islands are located in the middle of Casco Bay. This can probably be explained by the fact that both
islands are technically part of the City of Portland, so they may have some administrative offices located in
Portland. Still, the physical structures are located on the islands, not in downtown Portland. This discrepancy
casts some doubt on the attribute accuracy of the data set, and therefore on its value for this project.
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Image 11: School Entrance
Lastly, as was the case with the hospital and police data sets, the point on the map is located on top of the
school building, not near the entrance as in the case of the fire station. This could cause some confusion,
especially if schools were to be used as temporary shelters or resource centers during an emergency. People
would need to know where to go, and not all residents of the neighborhood would necessarily be familiar with
the school. While the main entrance to the school may have decent signage, other school entrances are often
unmarked, which could add to the confusion. Given the attribute inaccuracy and the potential for confusion
about the school entrances, this data would not be ideal for the purposes of this project.
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