GIS Assignment 4: GIS Data Quality Assessment
Tai Ullmann
For this assignment, my project is to identify neighborhoods in Boston that my cousin might
want to live in. He recently had a baby and is looking to move into Boston. His wife is a doctor and he is
a professor, so I am looking at several factors, including proximity to schools, libraries, hospitals and
open space. I would like to be able to recommend specific neighborhoods, so positional accuracy is very
important but could have an error up to several blocks. I would like the data to be accurate enough to
produce large scale maps. Required attributes include address information for schools, libraries and
hospitals. Open space data needs to include information on if the area is open to the public. It is
important the data is complete for open space, hospitals, libraries and schools. For schools I need
information to include both public and private schools through high school. Hydrology and streets can
be less complete and exclude the level of detail that includes alleys and small streams. The more recent
the data the better, however this project can include data from previous years, as many of the
establishments being measured do not change greatly over a couple of years. It is important streets and
hydrology are connected.
Compared to the aerial imagery, both the TIGER and MassGIS road data sets have errors – the
most visible being identified roads that do not exist (figure 1) and unidentified roads that do exist (figure
2) in the imagery data.
Figure 1.
Figure 2.
The MassGIS data set is based on 1:5,000 scale, with an accuracy of +/- around 13.33 feet. But,
looking at the map ,the quantitative positional accuracy ranges from 5 feet to 150 feet. The TIGER data
set quantitative positional accuracy is based on 1:100,000 and 1:24,000-scales, which accounts to an
accuracy of +/- 40 to 166.67 feet. It is important to note the error rate is probably higher, as more error
can occur when the data is digitized. Looking at the map, it seems the data is off by an estimated 30 feet
to 100 feet. In terms of its currency, the MassGIS data set is better for the project because the data was
updated in April 2012 and the TIGER data is from 2010. However, in terms of positional accuracy, the
TIGER data is better for the project as it has a lower quantitative positional accuracy error and includes
more roads than the MassGIS data set when compared to the aerial imagery data (figure 3). In terms of
attribute information required, either data set would work, as I don’t need any additional attribute
information. However, it is important to note the TIGER data has more information. The TIGER data set
seems to be most complete as it has more roads that do not exist in MassGIS.
Figure 3.
Figure 4
Similar to the road data, both MassGIS and TIGER
hydrology data have some errors. The MassGIS hydrology
data’s scale is 1:25,000, with an error around +/- 40 feet. The
TIGER data’s scale is based on 1:100,000 and 1:24,000-scales,
which accounts to an accuracy of +/- 40 to 166.67 feet. It is
unclear which scale is used. When comparing the data to the
imagery, on average, both dataset‘s quantitative positional
accuracy is off by around 80 feet (figure 4).
In terms of currency, the TIGER data is more current
as it is based off of the 2010 census and MassGIS hydrology
was updated in 2009. In terms of positional accuracy, both
data sets are off by the same amount. However, the MassGIS
data has more information and includes more water outlined
than the TIGER data. Furthermore, the MassGIS data has
better connectivity, as the TIGER data has many rivers that do
not connect with each other. Additional attribute information
is not required beyond the location of the river. However,
MassGIS has more attribute information as it classifies water
type. This information might be useful in further analysis.
The school location data is from MassGIS. The data
was refined either from 1:5,000 or 1:25,000 scale ortho
imagery. Thus, the positional accuracy ranges from around +/13 to 40 feet. I cannot provide an accurate quantitative
assessment of positional accuracy because I don’t know which
scales were used for each school and I don’t know how much
additional error occurred during the digitization process. The
data set seems complete because it includes public, private,
charter, collaborative, and special education schools from
preschool to high school for all of Boston. This covers the
school grades I am interested in, as well as both public and
private schools. This information was available in the data’s
metadata file. The data was last updated February 12, 2012,
which is current enough for my project. The attribute information seems quite accurate with a lot of
useful information. The attribute information includes the names, grades and type of school for each
point. It also includes contact information for the school and the current principle as of February 2012.
This is more information than I need but is useful for further analysis of a neighborhood.
The hospital information is also from MassGIS. The data scale is 1:25,000 with a corresponding
error of around +/-40 feet. I assume more error occurred during the digitization process. To my
knowledge, this data seems somewhat complete. The metadata explains the data only contains “acute
care” hospitals, which includes “the majority” of medical-surgical, pediatric, obstetric and maternity
beds. This makes me concerned that there are some hospitals missing that may not meet the acute care
guidelines. But it does seem to cover the entire area I am interested in. This data was last updated in
August 2009, which is a little out of date but current enough for this project. The attribute information is
less robust than the school data but does include the hospital name, address and if it has an emergency
room. This is helpful but it would be more useful if the attribute information contained more
information about the hospital types.
The library information is also from MassGIS. The metadata does not include a scale, so I cannot
provide the quantitative positional accuracy of the data. The data also seems incomplete. The metadata
says the dataset only includes libraries that meet the Massachusetts Board of Library Commissioners
requirements but that some libraries do not meet these requirements and thus, are not included.
However, libraries as part of schools are included – which is useful. The data was last updated October
2004, which is not current enough for this project. The attribute information is useful. It includes the
basic necessary information (name, address and type) but it also includes information on if the library is
part of a larger institution, as well as the method used to determine the location of the library. This is
very useful to determine how accurate some of the locations of the library are. I especially like the
breakdown of types of libraries, as it tells me which ones are open to the public and accessible to my
cousin.
The open space data is from MassGIS. The data uses a 1:25,000 scale, which corresponds to an
error of around +/- 40 feet. The data seems quite complete, however the metadata warns that open
space changes frequently and requires a collaborative effort. Therefore, there may be incomplete data
that requires more extensive research and knowledge of the area. This data was last updated on
September 21, 2012, which is very useful and the most current data used in the project. This is especially
helpful given the incomplete data warning. The attribute information is very robust. The most useful
information is the public access code, which shows if the area is open to the public. It is also helpful to
see what the primary purpose of the land is. The attribute information provides more than enough
information for my project needs.