Nolan Nicaise
22 November 2013
Intro to GIS: Assignment 6
Over the River and Through the Woods:
A GIS-Assisted Exercise in Bicycle Touring Route-Finding
1: Briefly describe your project goals and the spatial questions it will address.
The project will use GIS tools to produce a route map of “least cost” for a multi-day road bicycle
tour of Massachusetts. The route must avoid areas of dense population, avoid roadways with heavy
traffic, avoid areas of steep grade, travel close to areas where tent camping is possible (state parks
or federal lands), travel close to gas stations or grocery stores for water fill-up, prioritize scenic
(agricultural and forested) areas, and travel within 5 miles of selected Massachusetts attractions.
Reason for the analysis: Bicycle routes bring economic stimulation to the cities and towns that they
pass (Pruetz, 2013). Bicycling saves fossil fuels, promotes healthy living, and is a fun activity for
vacationing. Massachusetts boasts many historic and scenic sites, including Mount Greylock,
Walden Pond, and the Quabbin Reservoir. Connecting these sites with a safe bicycle route is
important in promoting cycle tourism in Massachusetts. It also is of practical use for me, as I plan
on using the route this summer.
Spatial questions that the project will address: Are there contiguous areas of scenic areas in
Massachusetts? Are camping areas connectable via bicycle in one day (no more than 60 road
miles)? Are camping areas within bicycle-friendly distance of tourism destinations in
Massachusetts? Are bicycle-friendly roadways within bicycle-friendly distance of tourism
destinations in Massachusetts? Are camping areas within bicycle-friendly distance of “RailTrails”
or other off-road bike paths?
2: Provide at least four briefly annotated examples of similar analyses that used GIS:
A) Bocian, Erika. 2012. Using GIS for Safe Bicycle Routing in Morris County, New Jersey.
Master’s Thesis. Department of Humanities and Social Sciences, Northwest Missouri State
University, Maryville, Missouri.
<http://www.nwmissouri.edu/library/Theses/BocianErika/Bocian_Thesis_Final.pdf>
a. This article describes several ways to evaluate bicycle suitability. It first introduces
the Bicycle Compatibility Index, which scores a road based on the presence of a bike
lane or wide paved shoulder, the width of that bike lane or paved shoulder, vehicles
per hour, traffic speed, presence of a parking lane, and roadside land use.
Furthermore, a Bicycle Level of Service was discussed. This measure includes
volume of traffic, speed limit, percentage of heavy vehicles, adjoining land use,
frequency of driveways and parking spaces, pavement surface condition, and width
of lane. The article then describes the methodology used to create a route finding
program for bicyclists in Morris County, NJ. This article is very useful to me because
it outlines a similar project, to design bicycle suitability scores for roadways that can
be used for way-finding. However, the project differs in that it covers only one
county, whereas my project encompasses the entire state of Massachusetts. Some of
the steps, including calculating grade for each road individually cannot apply to my
project. Likewise, the author used county-supplied traffic density estimates,
something that cannot be replicated for a state-wide project like mine.
b. Interestingly, the author attached the slope/grade raster to individual road
segments through a spatial join, using the mean slope value over which that road
segment (using a 5-foot buffer to make the road a polygon) passed. I do not know
that this will be possible for the entire state of Massachusetts, unless the roads are
broken into short road segments already (which they are with the EOCRoads_Arc
layer). The author of this article manually broke the roads of the county into road
segments.
c. The author reclassified layers based on their cost. For example, the street class was
reclassified as 9999 for Interstate Highways, 40 for arterials, and 0 for local roads. I
would like to emulate this reclassification method.
d. Finally, the author presented some statistics that may be useful for me in
determining my criteria. For example, the author cited the American Association of
Highway and Transportation Officials’ Guide for Development of Bicycle Facilities as
stating that roads with grades over 11% are not recommended for bicycles. I will
use 11% as my maximum acceptable grade for any road.
B) Pruetz, Rick. 2013. Prosperity Comes in Cycles: Bicycle trails can pump up local economies.
Planning, The Magazine of the American Planning Association. November 2013.
a. This source did not explain a process that used GIS, and it will not contribute to my
four required sources, but I did think that it was worth including, as it sparked my
interest in this particular project. This article discusses specifically the off-road (not
to be confused with “cross-country”) path that connects Pittsburgh and Washington,
D.C., for cyclists. The trail, which recently opened, has shown great promise in
providing economic stimulation for the many towns that it passes. Massachusetts
could see similar economic promise by promoting bicycle tourism routes across the
state. My project will explore whether a network of roads exists already that could
serve as a safe and enjoyable bicycle route.
C) Huang, Yuanlin, and Ye Gordon. 1995. Selecting Bicycle Commuting Routes Using GIS.
Berkeley Planning Journal.
a. This article explains a procedure for using GIS to select suitable bicycle routes. The
outlined procedure selects routes based on the following criteria: travel time, auto
traffic, grade of roadway, and road surface conditions. While I may not select those
particular criteria, I can still apply parts of the procedure.
b. This study suggests building a spatial database first—compiling data layers for
terrain, street network, population, auto traffic, and road conditions. I will also
compile as much information as I can on a database, although some of the elements
may not be accessible, as some information does not exist on a state scale (such as
traffic volume and road surface conditions).
c. The article was helpful in explaining some of the data layers that would be helpful.
However, it was not helpful in the overall analysis. It used complex calculations and
a Triangular Irregular Network surface to determine the slope of each road segment.
I feel that I am not advanced enough to use some of such methods.
D) Pedley, Andrew. 2012. Transportation network analysis for bicycle suitability in Lincoln
Nebraska using Geographic Information Systems (GIS). Environmental Studies
Undergraduate Student Thesis. University of Nebraska-Lincoln.
<http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1101&context=envstudtheses
>.
a. This article explained the process for creating a Bicycle Compatibility Index for a
section of Lincoln, Nebraska. The author described the process of obtaining road
centerline data, calculating the Curb Lane Width using AutoCAD software, and
estimating the Curb Lane Volume of traffic based on conversations with Lincoln
Public Works. The author noted that he was unable to find data regarding parking
occupancy and percentage of heavy vehicles. I assume that I, too, will not be able to
find such data. He eliminated these variables from the evaluation of Bicycle
Compatibility Index, and I plan to do the same.
b. Interestingly, this author used MS Excel to calculate the BCI for each street and then
joined the table to the base street map on ArcMap. I do not think that I will use MS
Excel as an external table tool, but it is good to know that that is an option. Similar
to the study in Morris County, New Jersey, this study was able to calculate the BCI
per road segment with the roads as a line (vector) file. This situation requires that
the road segments are short enough to be representative of the landuse, slope,
traffic volume around them. Too long of a road segment, and those generalizations
are not valid. I will have to be careful about this if I am to calculate the BCI using
vector data.
E) Mitchell, Jay. (Unknown Year of Publication). “Indiana State Route Bicycle Suitability
Rating Criteria DRAFT”. Indiana Department of Transportation Bike and Pedestrian
Program.
a. This publication lists criteria for determining the suitability of a roadway for
bicycling. It is very helpful. It lists specific bicycle-safe limits for vehicle speed,
commercial vehicle volumes, overall traffic volumes, lane width, lane configuration,
and shoulder type. I doubt that I can use all of these criteria, but knowing the
Indiana standard for the criteria that I do have data for is helpful.
3: Provide a list of the GIS data layers you will use plus any tabular data sets.
Data Set
Name
Variable
Description & Importance
Data Source Agency
Sceninv_poly
Scenic Areas
This data layer was created by the
MassGIS > MA
MA Department of Environmental
Department of
Management in 1981 to identify
Environmental
significant cultural, historic, and
Management > MA
scenic landscapes. Scenic landscapes
Landscape Inventory
are important to long-distance
Project
bicycle travel because they increase
the pleasure of the ride and the
satisfaction of bicycle tourists.
Biketrails_A
Bicycle Trails
rc
This data layer was created by the
Mass GIS > MA
MA Department of Environmental
Department of
Management in 2002. It is a line
Environmental
layer that marks the Rail Trails that
Management
are open to walking, jogging,
rollerblading, skiing, horse riding,
snowmobiling, and bicycling. This
layer is important because such Rail
Trails offer the safest and most
pleasurable routes for cyclists and
should be considered with roadways
for possible cross-state routes. This
layer may be inaccurate when
beyond a 1:50,000 scale.
Openspace_
poly
Open Space
This layer combines data layers that
MassGIS > Executive
represent parklands, forests, golf
Office of Energy and
courses, playgrounds, conservation
Environmental Affairs
lands, etc. This layer is useful for this
analysis because open space can
increase the beauty of an area and
increase the satisfaction of bicyclists.
Eotroads_arc Road
This layer was created by the
Classification,
MassDOT in 2012. It may be the
Right/Left
most useful layer for me in this
Shoulder Type,
project, because it includes
Right/Left
information necessary to establish a
Shoulder Width,
Bicycle Compatibility Index, such as
Number of
the road class, the speed limit, the
Travel Lanes,
width of the road, and average daily
Surface Type,
traffic volume. While many roads
Surface Width,
have NULL values in some of the
Speed Limit,
cells, many of the roads that I will be
Truck Route,
looking are, in fact, filled with data.
MassGIS > MassDOT
Average Daily
Traffic
Img_elev5k_i
Elevation
This raster layer shows the elevation
MassGIS > Digital
of the surface of Massachusetts in 5m
Orthophoto imagery
X 5m cells. This layer is important
project
for finding the grade change per road
segment, as steep grades can be
dangerous or unpleasant for cyclists.
Later dated to February 2005.
?
Camping sites
This layer has yet to be identified. It
will be a point layer of the camping
sites in the state of Massachusetts.
This is important because a bicycle
tourist will want to camp for the
night every 50-90 miles of travel.
4: The data creation, processing, and/or analysis steps that you expect to perform.
A) Remove all unwanted road classes using a select by attributes and exporting a new layer for
road classes 2, 3, 4, and 5.
B) Remove all unwanted roads based on speed limit. Select roadways that have speeds in
excess of 54 miles per hour, invert the selection, and export a new layer based on the
selection.
C) Remove all roads that are not paved in asphalt or concrete. Select roadways based on
surface type and export selection to a new layer.
D) Remove all roads that are not wide enough. Select roads that have >=11 foot wide lanes and
export the selected data.
E) Remove roads that have more than 10,000 vehicles per day and only two lanes. Select roads
with 2 lanes or less. Select within the selection for roads that have more than 10,000
vehicles per day (ADT). Invert the selection and export the selected data.
F) Remove roads that have more than 40,000 vehicles per day and more than 2 lanes. Select
roads that have more than 40,000 vehicles per day. Select within the selection for roads
that have more than 2 lanes. Invert the selection and export the selected data.
G) Convert elevation raster to slope.
H) Spatial join the slope raster to the road segment layer and average the slope values for each
segment. If I cannot spatial join a raster to a line segment, I will add a 6-foot buffer to the
line segments and then spatial join the slope raster to the polygon with the average slope
value calculated. I will then join the tables of the polygons and the line segments based on
the road ID.
I) Calculate distance to open space or scenic landscapes. I will create a raster for Euclidian
distance to open space areas or scenic landscape areas. I will then reclassify the distance
raster, with 0 being within the open space or scenic area, and 5 being far away. I will then
spatial join the raster to the roadway layer (or use the buffer polygon technique as
mentioned above).
J) Calculate distance to camp sites. I will create a raster for Euclidian distance to the camp site
points. I will reclassify the distance raster so that areas close to the campsites get the value
of 0 and areas far from the campsites get the value of 5. I will then spatial join the raster to
the roadway later (or use the buffer polygon technique as described above).
K) Reclassify fields. I will give scores between 1 and 5 for different criteria, including ADT,
shoulder width, speed limit, slope, and distance to open space or scenic areas. I will then
create a road evaluation field and calculate the compatibility of the road segment by adding
the different criteria (with 0 being the most compatible for cycling). I may have to play
around with the weighting of the criteria.
L) Convert the road layer to a raster, keeping the calculated compatibility field as the cell
value.
M) All cells that are not roads in the new raster will be reclassified with a value of 9999.
N) A least cost analysis will be conducted on the new raster to find the path of least cost for a
cyclist travelling across the state or to a location of interest (such as Mt. Greylock).
5: The products you hope to include on your poster (e.g., maps, table).
I hope to include maps that show the different components of the analysis. For instance, I will
include a map that shows the camping sites, a map that shows the open spaces and scenic
landscapes, a map that shows roads with speed limits under 55mph, and a map that shows the
slope/grade of roads. I will then show the maps converging towards one larger map of the bike
suitability of roadways in Massachusetts. Finally, I will have one map that shows the application of
the bike suitability on a map showing a least cost route from Arlington, MA, to Mount Greylock near
West Adams, MA. I will also have a table that shows my criteria, reclassification, and weighting
(similar to the Bryce Canyon poster near the doors of the GIS lab).