Molly Cooney-Mesker
UEP 232- GIS
March 8, 2012
Assignment 4: - GIS Quality Assessment
Benchmark Project (pretend)
I am working with the Food Project to identify potential
Medford
new outlets for food distribution in Somerville,
Massachusetts and more specifically the Union Square area
where there’s been a demonstrated high demand for fresh
food. Currently the Food Project sells food from their
Mystic River
farms to community supported agriculture, farmers
markets and hunger relief organizations. The organization
would like to expand their production and is investigating
Somerville
alternative outlets for distribution including neighborhood
Union Square
libraries and schools, for produce stand locations, and
grocery stores for retail. The Food Project is also
interested in looking at open spaces for additional
Cambridge
farmland. This analysis necessitates indentifying the
location and density (for ease of distribution) of grocery
stores, libraries, schools and open spaces in Somerville.
Data layers will include geocoded grocery stores addresses
Illustration 1: Somerville and Union Square in context of larger regions
(NAICS code 445110) and MassGIS data for library and
school locations. Additionally, road centerlines and hydrological features will be mapped for general
reference. These features will compared to ESRI World Imagery. Accuracy of road centerlines and
hydrographic features are analyzed for general reference by comparing data layers from MassGIS and 2010
Census TIGER data layers. All layers will be compared to ERSI World Imagery.
Analyzing the location, completeness and attribution accuracy of the grocery store, school, library and park
data layers is important for several reasons. First, the Food Project will create a strategic outreach plan for
businesses and community organizations based on the number and density of these services in the Union
Square area. For this purpose the positional accuracy is minimally important while the completeness and
attribution accuracy are essential. In terms of open land, the Food Project needs to analyze the quantity and
quality of open space (further analysis will be needed). This quality assessment will help establish the quantity
and location while identifying dataset issues as well as providing a snapshot of prohibitive environmental
factors. Again, the positional accuracy is less important than the completeness and attribution accuracy.
Table 1. Data benchmarks
Grocery Stores
Schools
Libraries
Open Spaces
Road Center Lines
Hydrography
Positional Accuracy
+/- 50 feet
+/- 50 feet
+/- 50 feet
+/- 100 feet
+/- 20 feet
N/A
Completeness
Important
Important
Important
Important
N/A
N/A
Required Attributes
Name and address
Name and address
Name and address
Type
Name
Name
Currency
Very current
Current
Current
Current
N/A
N/A
Road Centerlines
The road centerline data from MassGIS and 2010 Census TIGER were compared against one another and
ERSI World Imagery. For the purpose of the Food Project both road centerline datasets are equally useful.
Positional
The data is a close match with the exceptions of a few points of deviation. At the intersection of Somerville
Ave and Washington St. the Census TIGER centerlines outline the intersection differently. The TIGER data
includes both a centerline for the main straightaway as well as centerlines that for converging roads, which
results in redundant information (at least for the Food Project’s needs) with a difference between the data sets
of about 12.5 feet at the widest point of deviation (see illustration 1). The deviation between the two datasets
in centerline positions may be a result of the straightaway changing street names from Somerville to
Washington at this intersection. Both the MassGIS data and Census TIGER data show road centerlines in a
location that is appears there is no road, based on the image map and walking past this location (see
illustration 1). There is a difference in the two data set centerlines of about 40 feet at this mystery road
location. This level of inaccuracy is not significant for this project.
Currency
Considering the TIGER data is more current it doesn’t seem that significant changes were made to Union
Square streets between 2008 and 2010, however street improvements were implemented in 2010. The ERSI
imagery was also captured before the Union Square street improvements.
Completeness
Both datasets for this area are complete for the Union Square area of Somerville.
Attribute Accuracy
The names of the roads are consistent between data sets.
Illustration 2: MassGIS roads are magenta and TIGER roads are yellow
Hydrography
Hydrological layers from MassGIS two 2010 Census TIGER layers – both line and area files – were
compared against one another and ERSI World Imagery. The Census area data and MassGIS data match
almost exactly. Overall, both data sets equally meet the needs of the Food Project.
Positional
The three hydro datasets are close matches. There is some discrepancy in coverage between in the MassGIS
area dataset and the TIGER area dataset. MassGIS appears to either not be as precise or have collected data
in a wetter season. The TIGER line data aligns with the other two layers but provides additional data that is
not included in the other datasets.
Currency
The currency of water data is not important for the Food Project for this initiative.
Completeness
The census line data shows multiple Mystic river tributaries that the Census area and MassGIS area and ERSI
world imagery don’t reveal (see red circles areas in illustration 3). However, the census line data shows a break
in water where there is water in every other layer displayed (see yellow circle in illustration 3).
Attribute Accuracy
The linear water features include single-line drainage features while the area file contains data for larger
surface water features. 2010 Census water data includes a limited number of water feature names and the
MassGIS data includes no names. This level of inaccuracy is not significant for this project.
Illustration 3: Dark blue is MassGIS Data. Turquoise area layer and light blue line are 2010 Census TIGER.
Libraries
Positional
There is only one public library in the Union Square area as shown below. The library on the railroad tracks
(see illustration 4) was input into MassGIS with the incorrect address - 298 Washington Street. With little
knowledge of the area and only using
the image for reference it’s clear the
library is in the wrong position. The
Somerville Public Library site confirms
that the library’s address is 270
Washington Street.
Currency
The library data from MassGIS
represents a list of libraries that was last
updated October 2004. Based on
personal knowledge and the Somerville
public Library website, the data
remains accurate for Union Square.
However, the Food Project should be
cautious in using the MassGIS dataset
to identify libraries in other areas as
closures and openings of libraries have
likely occurred since 2004.
Library with
incorrect address
Illustration 4: Locations of schools (red triangles), libraries (green squares) and grocery stores
(yellow polygons) in the Union Square Area.
Completeness
The MassGIS data set is complete for Union Square.
Attribute Accuracy
The names and addresses of the libraries are included in the dataset which meets the Food Project’s needs.
Schools
Positional
MassGIS accurately located the one school in the immediate Union Square area. The data point is within 50
feet of the school’s front doors. This level of positional accuracy meets the needs of the Food Project (see
illustration 4).
Currency
Based on data from the Department of Education and was updated in December of 2008. With many of the
school reforms and budget cuts in Boston in recent years, the Food Project may want to verify MassGIS data
with the public school websites if going beyond the Union Square area.
Completeness
The data is complete for this area, however in looking at the data for Somerville more broadly, there were
schools missing. For the Food Project’s work in the immediate Union Square area the MassGIS data is
sufficient.
Attribute Accuracy
A very complete listing of school names, addresses, principals and phone numbers makes this data layer
extremely useful for the Food Projects purposes.
Grocery Stores
Positional
Grocery store locations were determined by geocoding Reference USA data with the ERSI Image Map using
the ArcGIS 10.0 North America Geocode service address locator. The stores in Union Square at the main
intersection (see illustration 4) are inaccurate between 20 and 50 feet of the actual store building.
Currency
The Reference USA data is updated monthly based on phone records.
Completeness
The data is complete based on personal knowledge of the area and google listings for grocery stores in this
area and will work for the Food Project.
Attribute Accuracy
In comparing with google listings and personal knowledge tthe Reference USA data seems to have good
attribute accuracy and includes store name and owner which is useful for the Food Project.
Open Spaces
Positional
The MassGIS data is accurate in the
position of the parks and the data will work
for the Food Project in this regard.
Currency
The currency of this data is not extremely
pertinent for Food Project, as the details of
open spaces don’t change frequently.
However, knowing that the data is a few
years old it’s helpful to have personal
knowledge of the area.
Completeness
The MassGIS layer is missing data for a
park on Sumer Street (see red circle in
illustration 5). The missing open space may
be a result of the data not being generated
from on-the-ground property surveying.
Illustration 5: Open Spaces in the Union Square area
This level of completeness does not meet
the needs for the Food Project. The organization might consider relying on the ERSI image data.
Attribute Accuracy
The MassGIS Protected and Recreational OpenSpace data represents parklands, forests, golf courses,
playgrounds, wildlife sanctuaries, conservation lands, water supply areas, cemeteries, school ball fields, and
other open land that may be classified as protected and/or recreational in use. These datalayers seem to be
accurate as compared to the ERSI image data but not all of these types of open spaces wil be usful to the
Food Project. The MassGIS data includes the parks names and owner (private, city, federal, non-profit, etc.)
This information will be very useful in the Food Project establishing potential sites for new farms.