berkshireflyer · berkshire flyer market research report respectfully submitted to the berkshire fl...

$: BerkshireFLYER · BERKSHIRE FLYER MARKET RESEARCH REPORT RESPECTFULLY SUBMITTED TO THE BERKSHIRE FL YER WORKING GROUP DECEI\l.1BER 18, 2017 BY The Students of MA TH-444 Operations$
BERKSHIRE FLYER MARKET RESEARCH REPORT

RESPECTFULLY SUBMITTED TO THE BERKSHIRE FL YER WORKING GROUP DECEI\l.1BER 18, 2017

BY

The Students of MA TH-444 Operations Research

\Villiam Fines-Kested; Jacob Foley, W. Hasty, Evan Kalinowsky, Taurus Londono, Brogan Mulhern, Megan Richardson, Shijie Wang

Massachusetts College qf Liberal Arts 375 Church Street, North Adams, MA 01247

mclaflyer@gmail . com

BerkshireFLYER

Contents

I. Background ... ..... .. .. ... .. ...... .. .. . .. ... .... .. ... . ... .. ... ................ .. . ..... ... .... .... ..... 4

A. The Berkshire Flyer Working Group (BFWG) .................. . . .......... .. . . ........... .4

B. The Berkshire Flyer Operations Research Group (BFOR) ........ . . .. . . ..... . . ... ..... .4

II. The P1·oposed Service: Routes and Trackage .. .. ... ... .. .. ... .... . .. ... .. .. .... .. .... . ...... .5

III. Market Research . ... . .. ...... .. ... ....... ........... ............. ....... ... .... ...... .. .. .... ..... 9

A. I11formationfrom Attractions and Lodgings in Berkshire County . .............. ....... 10

B. Berkshire Flyer Ridership Survey ................................ ..... .. ... . . .. .. . . ....... .. 11

C. Statistical Analysis of Survey Data ... .. .. ....... .. ............... . .. .. . . .... .... ... .. .. ...... 15

D. Berkshire County homeowners who live in Ne'.11 York City .. .......... .. ..... ... . .... .. . 15

E. Service Economy . .. .. ... ... .... .. .. .. ... ... ..... ... ... .. .. .. ... . . .. .. . . .. ...... ... .. ... . ... .. . 18

IV. Future Research ..... ... ... ... .... ... .. . ... .. ..... ...... .. .. .. . .. ... .. ..... ............ ... . ....... 19

References................. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ....... .. ... . ..... . .. .. .... ... . ....... 21

Appendix A: Attractions and Lodgings in Berksk re County . .. ........ .... ...... ..... ....... 23

Appendix B: MCLA Flyer E-mail Sent to Attrac ions & Locations . ...... .. ... .. .. ... ..... 29

Appendix C: E-mail conespondence with Attra' tions & Locations . . ..... ...... ... ....... .30

Appendix D: Berkshire Flyer Ridership Surve~ ....... ... ... . .. ............. ...... ... .. ... .... .34

Appendix E: Berkshire Flyer Ridership Survey aesults ...... .................. ... . ... ........ 39

Appendix F: Statistical Analysis of Data ..................... .. ..................... ............ 50

Appendix G: Maps of Tax Bill Addresses for Individual Municipalities . ...... ........... 51

Appendix H: Python Code for Generating Maps and Reports .. .......... ...... .. .. ... ..... 64

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List of Figures

Fig. l Empire Corridor South . ... . .... . ................................................................... 6 Fig. 2 Track ownership of proposed routes for the Berkshire Flyer service .................... 7 Fig. 3 CSX-owned subdivisions south of Castleton-on-Hudson ................................... 8 Fig. 4 Proposed site of new connection track for Route 2 ........................................... 9 Fig. 5 Berkshire Flyer Ridership Survey: Response to section 1 question 1 ................... 12 Fig. 6 Berkshire Flyer Ridership Survey: Response to section 1 question 2 ................... 12 Fig. 7 Berkshire Flyer Ridership Survey: Response to section 3 question l ................... 13 Fig. 8 Berkshire Flyer Ridership Survey: Response to section 3 question 5 ................... 14 Fig. 9 Berkshire Flyer Ridership Survey: Response to section 4 question 4 ................... 15 Fig. 10 NYC metro mailing addresses for Berkshire County homeowners from select . cities/towns .................................................................................................... 16 Fig. 11 ZIP codes overlaid on Voronoi diagram for stations along proposed route .......... 17 Fig. 12 BRTA bus routes in Berkshire County as of July, 2017 ... ......... ... .. ... . ............ . I 9

List of Tables

Table I: Summer attendance at representative sample of Berkshire county attractions/lodgings ................................................................................. ... .... . I 0

Table II: Berkshire County cities/towns with highest number of property-owners in New York City ........................................... ~ ......................................................... 17

Table III: Numbers of tax bills mailed within 30 and 50 mile radii of six stations along p1·oposed route .............................................................................................. 18

Table IV: Facebook users "who have expressed an interest in 01· like pages related to" .... 20

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I. Background

A. The Berksl1ire Flyer Working Group (BFWG)

The Berkshire Flyer Working Group was established to study seasonal passenger rail service between New York City and Pittsfield, Massachusetts. This ongoing effort was inspired by the successful CapeFlyer, a weekend service between Boston and Cape Cod that operates from Memorial Day to Labor Day. Operated jointly by the Cape Cod Regional Transit Authority ( CCRT A), the Massachusetts Bay Transportation Authority (MBTA), and Massachusetts Department of Transportation (MassDOT), the CapeFlyer cruried 13,663 passengers across t 5 weeks of service in 2016, earning approximately $230,000 in revenue that year [I]. Like the CapeFlyer, the proposed Berkshire Flyer service would be seasonal, running on weekends during the summer.

Legislation leading to the formation of the Berkshire Flyer Working Group (BFWG) was sponsored by Massachusetts state Senator Adam Hinds, D-Pittsfield, as part of the fiscal year 2018 (FY18) budget [2]. Regarding the proposed service) Hinds said in a statement that "transportation improvements are critical for the economic development of the region and the Common\\ealth. NYC/Berkshire Rail would be an economic boon for OW" communities, cultlll"al attractions, stores, restaurants and lodging."

In addition to Senator Hinds, the Working Group includes Astrid Glynn, Rail and Transit Administrator at MassDOT, Representative Tricia Farley-Bouvier, D-Pittsfield, Billy Keane of the Berkshire County Board of Realtors, Michael Kapnik, director Western Massachusetts Office of the Governor, Matthew Russett, community outreach coordinator for U.S. Rep. Richard Neal D-Springfield, Clete Kus, transportation program manager, Berkshire Regional Planning Commission, Elliot Sperling, transportation planner at MassDOT, Nathaniel Kams, executive director, Berkshire Regional Planning Commission, Francisca Heming, district 1 highway director at MassDOT, Lenox, Jonathan Butler, president and CEO, I Berkshire, Eddie Sporn, Robin Road Consulting, Jay Green, Berkshire Scenic Railway, Robe1t Malnati, administrator, Berkshire Regional Transit Authority, Deanna Ruffer, director of community development, City of Pittsfield, and Alfred "A.J.11 Enchill, district aide to Senator Hinds.

Intended to attract tourism to Berkshire County from New York City, the Berkshire Flyer service may also help to address concerns about population decline in the Berkshires. According to Hinds, "When you look at our population in the Berkshires there's that 20 to 30 year-old gap and folks who might want to start a family here and take advantage of the cost of living and quality of living but wanting to maintain a connection to other economic center, in this case namely New York City."

B. Tlte Berkshire Flyer Operations Researcll Group (BFOR)

The Berkshire Flyer Operations Research (BFOR) group is comprised of the eight undergraduate students enrolled in Dr. Erin Kiley's MA TH-444 (Operations Research) course at the Massachusetts College of Liberal Arts. The BFOR group was created to fulfill the

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requirements of a course project designed to assist the BFWG in carrying out an initial pilot study on the proposed Berkshire Flyer service.

The BFOR Group sought to provide quantitative support to the BFWG's objective, which, according to MassDOT representative Astrid Glynn, is "to find facts about potential ridership on a line that would use existing passenger rail track up New York state, then would cross into Massachusetts at \Vest Stockbridge." [3] Details regarding the proposed serv-ice are discussed in greater depth in Section II.

The BFOR group conducted its research in three phases: ( 1) E-mailed lodging and attractions lists provided by the Berkshire Flyer Working Group; in

addition, reviewed bus ridership (Berkshire Regional Transport Authority). (2) Created a survey to be disseminated by participating businesses (lodgings and

attractions). The survey is intended to reach potential riders, and requested that the survey be posted on the social media accounts of various establishments in the Berkshires.

(3) Analyzed the survey results, synthesized findings in a report submitted to the Berkshire Flyer 'Working Group.

The BFOR group has a personal investment in the establishment of the proposed service; at least one of its members lived and worked in New York City while regularly commuting to the Berkshires, as have many of their family and friends. They can personally attest to the appeal of more conYenient rail service between New York City and Berkshire county for travelers coming from either location. Ind~ they're hopeful that future sen ice will consider younger individuals who may want to settle in the Berkshires while maintaining economic ties with New York City.

II. The Proposed Service: Routes and Trackage

Two potential routes have been identified for the proposed Berkshire Flyer service. ''Route l" would go from Pittsfield to Albany-Rensselaer to New York City utilizing only existing track and Amtrak service. "Route 2" would go from Pittsfield to Castleton-on-Hudson (part of Schodack, NY) to New York City, bypassing Albany-Rensselaer and requirjng 3,000 teet of new connection track as well as the use of 11 miles of CSX-owned track for which there is no existing Amtrak-CSX agreement. A third option involves increasing the frequency of service between Albany-Rensselaer and Pittsfield to align with existing service between New York Penn Station and Albany-Rensselaer.

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Fig. l Empire Conidor South [4]

Both proposed routes for new service would utilize at least part of the Empire Conidor South (Fig. 1), a 142-mile line which runs from New York Penn Station through the Hudson Valley to approximately one mile north of Albany-Rensselaer station. This includes Amtrak's Empire Connection, a 10.8-rnile portion of the West Side Line from Penn Station to the SpuytenDuyvil bridge (connecting Manhattan to the Bronx neighborhood of Spuyten-Duyvil); here, track joins the Metro-North Railroad Hudson Line ( o\\ned and operated by the Metropolitan Transportation Authority) which runs from Spuyten-Duyvil to Poughkeepsie, NY.

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" Troy ·Rens s e I a

CSX Berkshire Suhdivision

~ · Adams

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Fig. 2 Track ownership of proposed routes for the Berkshire Flyer sen·ice [ 5]

The southern portion of the Hudson Line is a section from Spuyten-Duyvil to CrotonHarmon (21.4 miles), while the double-tracked northern portion runs from Croton-Harmon to Poughkeepsie (40.3 miles). Maximum speeds along the northern portion of the Metro-North Hudson Line range from 60-90 mph ( 60-70 mph due to curvature just north of Croton-Harmon, and up to 90 mph beyond the Hudson Highlands).

The Hudson Subdivision, a 38.6-mile line owned by CSX Transportation and leased by Amtrak, runs from Poughkeepsie to Albany-Rensselaer. The relatively straight section allows for speeds of up to 110 mph, the highest maximum speeds on the Empire Corridor South.

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/ ... ___ CSX HUDSON SUSDIVISiON ,~ -.. _ (to Castleto\l-on ... Hudson) I Soutil 5,(tr,p.::k:<.~

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CSX BERKSHIRE SUBDIVISION

CSX SCHODACK SUBDIVISION

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Fig. 3 CSX-0~11ed subdivisions south of Castleton-on-Hudson [6]

Route 2 would involve the use of CSX's Schodack Subdivision (Fig. 3), a line which branches off of the Hudson Division at Suyvesant. 3,000 feet of new c.onnection track would join this with CSX's Berkshire Subdivision just south of Castleton-on-Hudson, where New York State's Route 9J and NY 912M (the New York State Thruway's Berkshire Connector) meet. As mentioned above, a total of 11 miles of track would be utilized for which there is cuITently no Amtrak-CSX agreement.

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Fig. 4 Proposed site of new connection track for Route 2 [7]

III. Market Research

Our class group (BFOR) solicited information from attractions and lodgings in Berkshire County, lists of which were provided by the BFWG. We obtained e-mail addresses and telephone numbers for these attractions and lodgings, and sent an e-mail to each requesting data on the proportion of their visitors/customers/guests who were from the New York City metropolitan area (see Appendices A~B).

We created a Google account, "MCLA Flyer,'' from which attractions/locations were emailed. A Google surYey was de\ eloped that we hoped would be disseminated to any member lists that be might be kept by these attractions/lodgings, and/or shared on social media accounts. Each e-mail included a request for relevant information and a link to the survey (see Appendices B-D).

A total of 70 attractions, 6 chambers of commerce, and 173 lodgings were contacted. Of these, 20 attractions, 2 chambers of commerce, and 10 lodgings responded. 1 Berkshire, Berkshire Theatre Group, Mass MoCA, and the town of North Adams agreed to post a link to our survey on their respective social media accounts (e.g. Facebook)> yielding approximately 450 responses.

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A. Information from Attractions and Lodgings in Berkshire County

Data vvas obtained regarding seasonal attendance from five representati\'e attractions/lodgings in Berkshire County. These businesses responded to ow· e-mail by proYiding numbers of guests/customers/visitors during the swnmer season, as well as the percentage of these \•isitors from the New York City metropolitan area (see Table I). E-mail correspondences with these businesses are available in Appendix C.

TABLE I Seasonal attendance at representative sample of Berkshire county attractions/lodgings

Attraction/Lodging

Berkshire Scenic Railway Museum

Gateways Inn & RestaW'ant

\V.E.B. Du Bois National Historic Site

Canterbury Fann B&B

Berkshire Theatre Group

Frelinghuysen Morris House & Studio

a May 2016-December 2017 b Approximate values. c June 15-September 15, 2017. d July-September 2017. eJune-August 2017.

Seasonal attendance Percentage of visitors from NYC Metro Area

10,12111 5.7%

1,500b.d 40%

1 80b,d '

10%

280 75%

7,500b,d 16%

2,500b 50%

Berkshire Scenic Railway Museum is a non-profit organization with a mission "to preserve the history of railroading, particularly in the Berkshire Hills of Western Massachusetts.·· [8] Featuring a number of vintage locomotives and passenger cars, BSRM offers educational exhibits, restorations, and service on traditional and historic train rides.

The Gateways Inn & Restaurant is a bed and breakfast located at the Procter mansion at 51 Walker Street in downtown Lenox. It has been featured in Gladys Magazine, called "'the must-stay place" in Lenox by Luxury Report Magazine, named one of the "Best Places to Stay in Massachusetts" by The Hotel Guru, and is the winner of a 2014 "Best of New England - Editor's Choice" award by Yankee Magazine [9]. From June 15th to September 15th, the Gateways Inn had approximately 1,500 guests, of which an estimated 40% (600) were from New York City; this becomes 75% (1 ,125) ifNew Jersey and Connecticut are included.

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The W.E.B. Du Bois National Historic Site, at 612 South Egremont Road in Great Barrington, hosts the boyhood homesite of the African-American intellectual and civil-rights activist W.E.B. Du Bois. Listed on the National Register of Historic Places, it is currently operated an all-volunteer committee. The five-acre site includes guided tours along an interpretive trail [10]. During tour season, from July to September, the site receives approximately 60 visitors per month; 10% of visitors stated that they were from New York City.

Canterbury Farm is a nordic center and bed & breakfast located at 1986 Fred Snow Road in Becket. Open to the public throughout the year, Canterbury Farm offers seasonal outdoor activities (from skiing and snowshoeing to hiking, swimming, and kayaking) as well as lodging and musical events. The historic site, built in 1780 beside a 50-acre lake [11], hosted 280 guests during the summer of2017; 75% (210) were from New York City. Guests stayed at the farm two days on average.

Berkshire Theatre Group is a non-profit organization that came about when when Berkshire Theatre Festival merged with The Colonial Theatre, two of Berkshire County's oldest performing arts venues. Both institutions have long and storied histories, each the site of hundreds of stage productions [12]. Berkshire Theatre Group now operates the Fitzpatrick Main Stage (83 East Main Street in Stockbridge), the Unicom Theatre (6 East Street, Stockbridge)) and The Colonial Theatre (111 South Street, Pittsfield). From June to August of 2017, the Berkshire Theatre Group saw approximately 7,500 ticket orders; of these, 1,200 (16%) were made by people from the New York City metro area.

Frelinghuysen Morris House & Studio is the home of American abstract artists George L.K. Morris and Suzy Frelinghuysen. The 46-acre estate at 92 Havvthome Street in Lenox allows visitors to vie~ the couple's artwork and lh.-ing quarters firsthand [13]. Frelinghuysen Morris House & Studio is open from late June to early October, and receives approximately 2,500 visitors every season; roughly 50% are from the New York metro area.

B. Berkshire Flyer Ridership Survey

The Berkshire Flyer Ridership Survey was created using Google forms (see Appendix D for the full survey). As mentioned in Section II, our class (BFOR) emailed the survey link (https://goo.gl/forms/isHQRkn3NMJorDL43) to 70 attractions, 6 chambers of commerce, and 173 lodgings (all but the chambers of commerce were obtained from a list provided by the working group; see Appendix A). We asked the establishments if they would be willing to share the surve) with their customers/members/visitors via any existing mailing lists or social media accounts. Social media solicitation attracted the majority of the responses.

It's important to acknowledge that our results do not represent a random sample of potential passengers; respondents were mostly those who follow Berkshire County-based businesses on social media (and therefore do not represent the target demographic, i.e. New Yorkers), and respondents were necessarily restricted to those inclined to participate in online surveys regarding Berkshire County rail tra\·el. Nevertheless, as of December 17, 2017, there have been over 450 responses. Full response data was automatically compiled into a spreadsheet where it is ordered by submission date (see Appendix E).

The survey is composed oftv.-elve questions divided into four sections; four demographic questions were optional. Section 1 asked respondents, "Are you in fa\-or of expanding rail service between the Berkshires and NYC?" and "Would you use this service if it existed?" If respondents answered the latter by selecting either "I would not use this service but I know

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people that would" or "I would not use this service and I do not know anyone that would," the survey's branching behavior brought them to the last section (section 4), which asks how much they currently pay for transportation to the Berkshires as well as (optionally) the respondent's race and income (see Appendix D).

Are you in f avor of expanding rail service betvveen the Berkshires and NYC?

e ves e No

Fig. 5 Berkshire Flyer Ridership Survey: Response to section 1 question 1 as of Dec. 17, 2017

Respondents were then asked if they would use the service or if they knew friends/family that would. The majority of respondents indicated that they would either personally use the service or knew someone who would.

V"Jcu-!d you use this service if it existed?

e I :iuld per, ona USP. tm<; ;eMcP.

e M~ tnencr ·1rr r and I would use cus seivite

e I f..'\Jd not 1.se this :01:1\ ~e "UI I mow pe()l): 2 : " .; I '(IU1d

8 I 'Ol.'d no: i..: e 1 ~ ~ -: ~..e and I do n()( ~now .. n,or., u d' o..Jd

Fig. 6 Berkshire Flyer Ridership Survey: Response to section 1 question 2 as of Dec. 17, 2017 (If respondents indicated that they would not use this service, sections 2 and 3 were skipped)

The survey asked participants about the frequency and duration of their visits in the Berkshires. The majority of respondents indicated that they would use the service on a monthly basis; however, another third of the respondents indicated that.they would use the service yearly.

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Hlow often would you use this service?'

• Mr.mU1lt V''r:.:; ty

Fig. 7 Berkshire Flyer Ridership Survey: Response to section 3 question I as of Dec. 17, 2017

The typical time spent visiting the Berkshires ranged from a few days to more than one week. lt is worth mentioning that a large group of respondents (approximately 40%) already lived in the Berkshires. The following were the three most popular responses:

• A few days (31.3%) • More than a week (18.4%) • A week (6.9%)

Participants were asked the reason they would be visiting the Berkshires, and provided some of the the following responses:

• Cultural attractions (30.5%) • Visiting friends and family (25.3%) • Hiking/camping/fishing (3.3%) • Skiing/snowboarding (1.2%)

Most other respondents indicated that they already lived in the Berkshires.

The participants were also asked what their final destination would be when coming to the Berkshires. While responses varied widely, the top destinations mentioned were the following cities/towns:

• Pittsfield (22.4%) • North Adams (15.5%) • Lenox ( 13.8<yo) • Williamstown (9.5%) • Great Barrington (9.1 %) • Lee (2.9%)

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Our class (BFOR) was also interested in obtaining infonnation on the maximum amount respondents would be willing to pay over current rates in order to bjpass Albany-Rensselaer (Route 2). When asked how much more the respondent would be willing to pay to cut twenty minutes off the current travel time to NYC, responses ranged from $0-$200, with som_e respondents noting that they were unsme or gave answers such as .. Whatever it took." The upper range of responses were large enough to suggest that respondents may were entering the total prices they were willing to spend; our group had intended the question to refer only to additional money spent in order to save twenty minutes of travel time. A lack of clarity in the phrasing of the question may have led to the responses.

In an effort to minimize inappropriate skewing of data, we decided that $60 would be the upper maximum for a reasonable response. Responses that did not fall between the range of $0~ $60 were treated as if the response was left blank. With this in mind, the average amount of money a respondent would be willing to pay on top of the cost of travel in order to save twenty minutes per trip is $23.32 (see Appendix E).

\'Vhat wourd be your seating preference aboard the train?

• Co.:;Ch d e.;.s

• f!ll!1less ctass f lfSI claSS


Finally, BFOR asked respondents about their total household income. We obtained the follo~ing responses:

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(OPTIONAL) \fiihat is your household';s total income?

• !.~~ ;.; ' ll1'l\ SZ·:> 000 • S~'IO 000 lo )70 000

P u.n?•i..tn ~ · "'i. eco

e :..~ o.v ,•:f!>C! '{l ~ 1::!:l n<;i e J 1 ~,o "ilo:.1 •,o !200 ooo • "it(~Y& 1'1<.\'l ~J.4·00 00\.l


C. Stlltistical Am1/ysis of Survey Data

By analyzing the data collected from survey, we identified unreliable responses by removing any that had the following: words where numerical values were needed, incomplete or only half-answered responses, and any duplicate responses. At the time of the statistical analysis, there were approximately 200 survey responses, of which only about 120 were useful.

Our analysis showed that only household total income has a statistically significant impact on whether a respondent would ride alone or with family (household income was found to account for more than 62.4% of original data).

As the total household income increases, fewer people would choose to travel by themselves when using the Berkshire Flyer ser\'ice. For those whose household income is between $70,000 to $100,000, 54% would choose to go on their ovrn while 48% among those who made $100,000 to $150,000 would do so, and 43% of those who made $150,000 to $200,000, and 38% of those made greater than $200,000. For more details of the statistical analysis. see Appendix F.

D. Berkshire County ltomeowners who live i11 New York City

In order to better gauge potential ridership for the Berkshire Flyer service, BFOR sought to determine the number of Berkshire County homeovmers whose prope1ty tax bills were sent to addresses in the New York metropolitan area. This population consists of individuals who own properties in the Berkshires while living in New York City; this includes those who own second homes, seasonal residences, rental properties, etc. Those who own second homes in the Berkshires presumably maintain reliable patterns of travel from Ne'A York City, and may represent an untapped market for futw-e rail service.

Information was obtained from the Massachusetts Bureau of Geographic Information (MassGIS) ArcGIS Online Web mapping platform [14). Standardized parcels data were downloaded for every t0\\11 in Berkshire County north of Great Bat.Tington (see Appendix G). Owner addresses with zip codes between 10001 and 11980 were considered to be within the New York metropolitan area. Esri's ArcGIS was used to plot addresses for nine Berkshire towns

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with the greatest numbers of tax bills mailed to New York addresses; Alford, Becket, Hancock, Lee, Lenox, Pittsfield, Stockbridge, Williamsto\\n, and West Stockbridge (Fig. 10 and Table II).

In Figure 11, the broader Hudson Valley area is shown, and six stations along the proposed route have been used to generate a Voronoi diagram, which shows colored regions where each point is closest, geographically, to the station within that region. The six stations used to generate the Voronoi cells were New York Penn Station (NYP), Yonkers (YNY), Croton-on-Hudson (CRT), Poughkeepsie (POU), Rhineciiff (Rill), and Hudson (HUD). Dots are shown on the map for ZIP codes that are within 30 miles of each station. Oeospatial coordinates of ZIP codes was done using the zipcodes package for the python progranuning language [ 15], and distance to each station was computed by the script in Appendix H .

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All Tax Bills

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Fig. 11 ZIP codes overlaid on Voronoi diagram of stations along proposed route.

TABLE II Berkshire County cities/towns with highest number of property-owners in NYC

City ff own Tax bills Tax bills mailed to NYC

metro zip codesa

Alford 523 92

Becket 4082 294

Hancock 960 186

Lee 3059 171

Lenox 2879 211

Pittsfield 18694 166

Stockbridge 1959 271

Williamstown 2761 73

West Stockbridge 1120 114 0Zip codes between l 0001 to 11980 were considered to be within the New York metropolitan area. ~ew Yark Penn Station

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TABLE III l Numbers of tax bills mailed within 30 and 50 mile radii of six stations along proposed route

I Report automatically generated by Python on the basis of MassGIS data.

City name

Adams

Alford

Total tax bills NY/NJ 30 mile SO mile NYP30 NYPSO YNY30 YNYSO CRT30 CRTSO POU30 POUSO RHl30 RHl50 HUD30 Hl S

3638 21 15 17 6 6 2 2 3 3 0 0 0 1 4 523 124 112 121 77 83 15 15 12 15 l l 0 0 7

Becket

Cheshire

CLARKSBURG

DALTON

Egremont

Florida

4082 377 317 345 145 154 88 88 64 82 2 2 2 2 16 1733 25 16 21 10 10 2 2 2 s 0 0 0 0 2 845 11 6 10 ·2 2 3 3 l l 0 0 0 1 0

Great Barrington

HANCOCK

Hinsdale

LANESBORO

Lee

LENOX

New Ashford

NORTH ADAMS

Peru

PITISFIELD

Richmond

SAVOY

Sheffield

STOCKBRIDGE

Washington

West Stockbridge

WILLIAMSTOWN

WINDSOR

2772 24 19 '-2 11 13 1 1 2 3 1252 259 241 254 169 171 36 36 27 38

693 26 13 17 8 8 2 2 l 4 4136 329 301 314 197 205 40 40 39 44 960 280 224 248 77 81 4S 45 59 79

1528 88 81 84 17 17 20 20 15 18 2054 81 71 74 16 18 23 23 17 18 3059 246 219 236 124 134. 46 46 32 39 2879 280 255 266 135 143 57 57 51 53

208 10 6 9 2 3 3 3 1 2 5393 72 51 62 30 35 5 5 3 3

792 33 28 32 10 11 4 4 4 7 18694 292 252 268 111 117 43 43 45 51

1260 109 100 103 54 57 9 9 19 19

572 20 17 18 7 7 2 2 4 s 2804 221 208 215 139 143 20 20 32 35 1959 365 342 357 222 233 so so 58 62 603 35 29 31 12 13 4 4 12 13

1120 143 132 139 86 90 24 24 13 16 2761 101 94 96 57 58 9 9 19 19 901 26 22 23 14 14 3 3 3 4

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3

0

3

1 2

1

1

2

0

2

2

2

0

0

1

2

0

0

0

0

0 3

3 6

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2 25 2

1 13 1

1 15 ;l

2 10

0 0

2 10 1

2 8

3 so 5

0 18 1 0 4 1 16 l

2 10 1

0 1

0 9

0 8 0 2

Totals 67221 3598 3171 3382 1738 1826 556 556 538 638 17 17 24 27 298 :s.1

E. Service Economy

Once New Yorkers reach the Pittsfield Intermodal Station, there will be a demand for transportation serYices to get them to their final destination. These include: public bus service provided by the Berkshire Regional Transit Authority (BRTA), taxi service (e.g. Rainbow Taxi), as well as Uber, Lyft, Zipcar and Turo. Use of these services represents another economic benefit of bringing New Yorkers to Berkshire County.

BRTA provides fixed route bus service across Berkshire CoWlty, from Williamstown to Great Barrington, Monday tlu-ough Satw-day. A map of all BRT A bus routes (as of July 2017) is provided in Fig. 11; The lack of Sunday bus service as well route limitations may need to be addressed in order to better accommodate passengers disembarking from a potential Berkshire Flyer service in the near future.

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Fig. 12 BRTA bus routes in Berkshire County as of July, 2017 [17]

IV. Future Research

Our group (BFOR) realized that businesses would be more willing to share the survey on social media only after it became clear that no business was willing to share our survey via direct, mass e-mail to their customers/members. It's also worth considering that relatively few businesses responded to our e-mails, despite our attempts to follow up with all attractions and lodgings. This may be due in part to the timing of the project (mostly undertaken during the Thanksgiving and winter holiday season).

Although several organizations based in Berkshire County shared our survey on social media, responses were mostly restricted to Berkshire residents·. In order to disseminate our survey to potential ridership in the New York metropolitan area, we explored the option of

19

targeted advertising on Facebook. To this end, we created a Facebook account, "MCLA Flyer.'' We determined that advertisements on Facebook can be targeted to users based on their interests (e.g. "Berkshires,'' .. Tanglewood," etc). Our preliminary research re\·ealed relevant numbers of users and their respective interests (see Table III).

It's likely that many New Yorkers who already travel to locations such as upstate New Y mk for recreation would also visit the Berkshires if a convenient public transit option were available. Thus, it's important to identify individuals in this untapped market. Using Facebook's targeted advertising to reach New York City users who have expressed interests in, e.g., "camping," ''train travel," "Amtrak vacations." etc .. remains an unexplored opportunity.

TABLE IV Facebook users "who have expressed an interest in or like pages related to"

Interest Number of Facebook users

'"Lenox, Massachusetts" 883,980

"Tanglewood" 295,310

"Berkshire County, Massachusetts" 186,510

"Jacob's Pillow Dance" 129,410

"Pittsfield, 1-tassachusetts" 113,110

"The Berkshires" 90,610

"Massachusetts Museum of Contemporary 51,520

Art"

"Nonnan Rockwell Museum" 46,980

'"Massachusetts Audubon Society" 46,460

"Clark Art Institute" 17,920

'Tanglewood Music Festival" 15,910

Alternative social media platforms on which targeted survey advertising could take place include Twitter, lnstagram, Pinterest, Tumblr, Google+, and Linkedln. These options have yet to be explored. Nevertheless, while Facebook tailors the reach of an advertising campaign to the given budget size, it's clear that such adve1tising will require at least some financial investment in order to reach potential ridership in New York City.

20

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REFERENCES

[I] "CapeFL YER increases ridership over 201 5," capecodtimes.com, 28-Sep-201 6. [Online]. Available: http://www.capecodtimes.com/news/20160928/capeflyer-increases-ridership-o\'er-2015.

[2] Mary C. Serreze I Special to The Republican, "Working group begins studying passenger rail between New York City and the Berkshires/' masslive.com, 22-Sep-2017. [Online]. Available: http://W\\-w.masslive.com/politicstmdex.ssf/2017/09/working group to stud) passeng.html.

[3] H. Bellow, "First step for Berkshire Flyer rail prospects: Measuring potential passengers;' The Berkshire Eagle, 27-Sep-2017. [Online]. Available: http://v.."V>.-v.-.berkshireeagle.com/stories/first-step-for-berkshire-flyer-rail-prospects-measuringpotential-passengers,520475. [4] New York State Department of Transportation. (2014). High Speed Rail Empire Corridor Program Tier I Drqfi Environmental Impact Statement (Project I.D. No. S93 7 .51 ). [Online]. Available: https://www.dot.ny.gov/empire-corridor/deis.

[5] Adapted from: New York State Department of Transportation. (2016). Map o,f Jli-ew York Stale Railroadi; [Online]. Available: https:/ /w\!\ w .dot.ny .goY/diYisions/operating/opdm/passenger-rail/railroadsmap.

[6] Adapted from: "CSX System Map," CSX.com. [Online]. Available: https:/,'wwv. .csx.com/index.cfm/customers/maps'csx-system-map/.

[7] Adapted from: Google Maps. (2017). [Online]. Available: https://'\-\ww.google.com/maps/@42.4997611,-73. 7600347,2512m/data=!3ml!1 e3 .

(8] "About the Berkshire Scenic Railway Museum Collection," Berkshire Scenic Railway Museum - About Us. (Online]. Available: http://,".r\\w.berkshirescenicrailroad.org/aboutus.php.

[91 .. Press Room & Accolades I Gateways Inn & Restaurant Lenox, MA," Gateways Inn & Restaurant. [Online j. Available: https://gatewaysinn.corn/press-room-accolades/.

[10] Du Bois National Historic Site. [Online]. Available: http://W\\w.duboisnhs.org.'.

[l l] A. Campbell, "Cross-Country Skiing and Bed & Breakfast in the Berkshires · Canterbury Farm;' Canterbury Farm - Nordic Center - Bed & Breakfast. [Online]. Available: http://w~w.canterbl!fY·farms.com/.

[ 12] "l nfo," Berkshire Theatre Group. [Online]. Available: https: //wv. "\\' .berkshiretheatregroup.org/about/info.

[13] "About the Frelinghuysen Morris House & Studio," Frelinghuysen Morris House & Studio. [Online]. Available: http://w\\w.frelinghuysen.org/about.html.

21

[14] A.rcGIScom News. [Online]. Available: http://massgis.maps.arcgis.com/home/index.html.

[ 15] zipcodes pack.age. Downloaded from https://github.com/seanpianka/zipcodes .

fl6] Adapted from: ArcGIS.com. [Online]. Available: http:! /WW\:\-.arcgis.com/home/webmap!Yiewer.html.

[17] Adapted from: BRTA Routes. [Online]. Available: http://geo-massdot.opendata.arcgis.com/datasets/b1ta-routes.

22

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Appendix A: Attractions and Lodgings in Berkshire County

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Appendix B: MCLA Flye1· E-mail Sent to Attractions & Locations

Greetings from the students of MA TH-444 Operations Research at the Massachusetts College of Liberal Arts!

Our class has teamed up with the Berkshire Flyer working group (which includes members of the Massachusetts state government and MassDOT) to analyze a possible passenger train service from New York City to Berkshire County. The Berkshire Flyer would provide seasonal, weekend service from NYC's Penn Station to Pittsfield. Our class project involves gathering data on potential ridership, and you may be able to he1p!

[Attraction name] has been identified as a potential destination for travelers from New York City who might use the Berkshire Flyer service. We'd definitely be interested in any data on your [ members!Yisitors/guests ], including:

[The proportion of your members coming from the New York City metropolitan area--ZIP codes or area codes would be helpful] The proportion of yow- [visitors/guests] coming from the New York City metropolitan area--ZIP codes or area codes are helpful The number of [visitors/guests] per day/week/month, over the past few summers [The numbers of visits by members per day/week/month, over the past few summers] Dmations of visits [if applicable---e.g., would ask a resort. but not a museum]

To further help with our research on future Berkshire Flyer service, our class has also developed a survey, linked here: https://goo.gL'forms/mTb3LbMg5eAebiii2.

We are hoping that this survey ~ill reach people who might regularly travel from New York City to the Berkshires, and therefore \vonder whether it would it be possible for you to e-mail this survey to yow- members? If needed, we can edit the survey to create a version specific for [attraction name] Please let us know!

We look fon¥ard to hearing from you at your earliest convenience.

Thank you, in advance, for your help!

The students of MA TH-444 Operations Research

Massachusetts College of Liberal Arts 375 Church Street North Adams, MA 01247

on behalf of

The Berkshire Flyer Working Group http://""·~~ .massdot.state. ma. us/planning/Main/CurrentStudies/BerkshireFI} er Study .aspx

29

Appendix C: E-mail correspondence with Attractions & Locations

SSR'l;.~ h~s bee-n a m~mber ot ~h~ working group so v~e are familiar v..iith it.

L~:i me ta1-;e t:his ~ci r.n~r r.-~)aril io t~is.cuss th; bes! ap!)foach. Wf: do b;;r·; s ~ m~Jiling list of visit~rs ca11 .-:~rtain;y g~t an ~tie~ .:')f ho:,.-;• m .. !\r;y come from th?. NYC area · howe-v~~ . it mavbe rnure di'ffkdt t•o q~t >?ta<:.~ nmn::.~rs ,as the !1c};~ t'$ p1.;rc.has&d p.er 1:-ontn<:t :a1e not r~~adiJv &:·ocessib!ii;. in th<1t mann~r but l'il giv·B 1't ::r J-00it..

\iYe may t•:>v he i Hs to -::~rid Glj~ a t~u9-st-ed email to NYC attendees - alE .. o z•:im;:thing I'!~ f'tf(\l<a 'o rn~E·a1-ch · ~ lii:a!c

Givs me it1 t i?t a:-&~ flf gei hac~ wi~h yo1:1. Thant,'.i> for r€'achln9 oiJt io us, K~"'~r.

h,>t\n .',1 Chirt;?>m~i"':l SnI>e r.~ ·tH~ .atl~n ~: 1.""'r~)1~1 ()p .~~~1~i\~n~

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Tha1:k !tl'.::il H> r r11.i1:h f,1..l~· ~:;l;i.;!.f!-;;~J '.}v · tlLiav.;:;y oo social media• Om 1Jlfu.<·~ll~W; 1k •l '1!1:'!} ~~!i~M;.G~ dirJ~d ~;·~d be thls Fnday th~ ~{:ith

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.i±!~ ~.i;i?.r.~ f.lf I.M fr:\ ... !H (~,.r;;1'lii.i:"1& l~t...;1·~;-J; ;:h r.,~~~;.;.~i :lt.wm~ts Coo~~t-7 rn· ~.Jti,;tU: ! .::-~~

TM £.\l'r.;..~ ;fu~"" rfr~,. 't*'Jm~ ~r.111 t~mlJfl ~IN? };\\"iHW.massdct.Ma11i ma. i1S;p1ann!ng.Ma;n ·C~":e!i~S!O{~:es;

b·~··bsh'ri?flie.l'S!'l.•cy asmt

G~~ I u.p . [J.t~C t ? ;?~iH ''tt 17 :~] P~~ R:&.:w.~~ Srit.~rer-ti <becl£1•@tf rt.s:.ii~the?.tre.<;'<'IZ· ~ ~ i':'T. DB..m MCLA Siltlrlt~r r.t~; T~Nnk you 1Q>f 1~~ach.,r111 m.rt n;~}J:n~\n~J Vfo; vm-y impii.H~;;mt ttcpir.. \Vh"ilrt is yo;.<: d1:1!ad!ine for r.~:(:•H1 vin~~ this tt:;:~ut> lH th<:: 1• ~!~;.;niiffi<'l' WH aw h<:~PPV it«~· pos~. your ril J:U l\ei ~$W'tl<-~Y Or1 so\ inl m 1:td ia f.iot '.·S:t ~ec~~· Bri~;thr:~r~l.~

31

Linda Frd irJg lruys.;,~·1 ~ ~··} i ~ .~ •t>

Ht..>i!Q Studt:'at.'i>,

~ Dec 14 <4 t~.ays ::t90}

~·~r~:!: f.:S ;,;n .i:r;xcl:rpt from !l.l !r rm:iilng ljs~ ~! io11..'ing thE1 NYC tf.i'..¥M and zip c:udes, you wlll ~~n·:I the au.scl1m~nt .::bt..'Ve. Tilf:ii~~ peoul<;) 1·1ave 2iti 1~r vis!Wd or ;t,tFJ men1be-1~. Also,~ \1ave jus! sent out the st!:Vf!y to our &mail list ViR have apr.roxirn~tely 2500 visitors~' se~wn · Ttie percenta9~ of NYC <Jrea resident; is .<t!Jout Si)'~';' . t1 o·:r~1.·er '.h••t ls noquct NYC. l/)9 am oper\ 1 ;fays f.I we.~}; from ;ate Jun~ to Early Odober. (i':\1d lucl.: \!'.itll !he ~r~~tt 1 suggest 'f'~l' fi.r;d the fai:-~IY.>ok Pl 9f.> ·wh~il .is ;.e! up ftwpenple seelcin9 !~S from i.he f:,Jetro-NoriJ.1 !:':i.R St1'!tfOn tit Wals~?.ic t~ GD Of L;)rwx. You may get a lot of info Ulere or po'5i ~>om!t~ing. 6i!;H::· £;;·~ ·e:I ~,.. t.:n~.~ f1~~.~~n(:ht~~r~n

G.~mt~~rbury F~inn B&B has been h:le11t.1foed a~ a pot-antial destinafon for travel~rs tr.:;m \k~w York Sity who might ~we Hie Berk.shire F!yef se1Mce. We'd definitely be intef-est~d in any data on y{Jrn gu,-::5~3 , 1nd Jding.

• The pni pcrtion of youf guests coming from the Nt-'V\' York City metropolitan ,ar~ ;::; -- Zll:i coC-:.:::··h or area cod~s .are helpfLll: During the summer 75% come from New York. During t!~c wH1h:.r 1110-st .come :from CT a.i1d t.1A ·

"' The q.umtJer .of g 'Jestsp er daytweek.fmonth, over the. past few summers Summer 2U) !<:•dg\ng WS t?l days (nl'd.Y ,inc.Jude two persons). Wi£lter: 80 lc>d9ing us.er clay;, (may includ<=> two ;c>\~'f.SCfl~),, Skf:ing da~' ticket holders vanes between 60-200 persons per day.

Hop·.\: th:::. mformatlon tie1ps.

Linda Bacon

32

1

1

1

1

J

l i J.:w 27

·fo o)n.)i•'-"\~ y·our il"iicitu• ;' \ri;:; dat.;:~ t!'i br>;~.U ·t>n 10~ 20 1~ :mi! JIJ1! fot.<r seasons loCJu r -::~~:s-on i$ .July · .$9p1emoor 1w· .. ·~·f ',hi'':.Orc,, :>-:ilt~..l'r! tl¥·v w;.-s·~ W\1ffil iJ;"B f:~YC m-"t1ooolil.iiln ;;r~a ····hen a~,k;:i;;( Tk~· ,, ., ... ~:rnti€ m.m·1b-:·r r>f l'i ~, .tm~ per •ntmih is f>l1 Th 's tfo~s. not indude vi.sltvr:- to th-e ~it~ b-Gfori! v. ?fl~ oo-erutmg

'"""""' ~

(:~·l ~;~o'!}.~ St:Ul!'~S fa1mrr,u · JOUit; \!1$'N'.l 2J~ 1 7 J.01.11 •gJ..ticl€

t:.o• 2'~fff-'Hl ··24 135 21 PM M\;l .rl. B;.:.rl;shifn Ft.:(:.-r ~·.n.~-f.'.":ifi£-:=-'lillg5 ('f!:iiTI Jbt.• siuden."'.> nt Mt\H t- •. 14~ {)p<~o~ns Rr~;t:·i:.<1.h ~t tile M#~!;~~"is C.;-,~e; ... i:<~ uf ~..iOCfill /'-.'15'

(..'tu: f ~!'~- has !.i";~m·:·-\1 •rtp v-:1.•n lhi~ Si';ri~S!':l e f l fcq '.~'.111.W"-J b!CUp '~ . .fijd; ~11-!J.-d~ 0io!:f 11to{':! <> ~)f'fi'J'!! M~,5•:;1~r.J1;;..15~lif; !;{Hlfl ~Wt::Ulif:jo!:fl1 '.1n{l f,~,'fSS[tOT": tf; ~·i~f~li!' ,~ p;:l:'..>~~~ J'O<l'!".S<m~1~r tn.,F1~ ~,,~,k~~ ~mm ~>~ '·fort\ Ci% ta f};;~~k'.. Y'r~ .m Cctm1o/. ·mr.: Bmt~'lhh1~ H:~~r "~"'t1u<)rt J)H.\'<'ide S•~o'1~;t;'l1<:1L r.;Jekot:~nd ·~~:+:1:.i~/..) ·ir~fr;'t 'l\IYC't> P'i'.i>mi ~,t;1'joo 1o P'~i:.si~M. f~n ..,i~~;i; ~wr·PJ-Cd Wl'"<:-o~•·r,;» f.t.alt:Mf~i~f£1 ~.la!·;;i M jl;-i',~f.!:iP;1 ii~•!4'1~ <ilnd ~~t1 ni.1:~' h~ aJ~ to:> k1t;: ·i~;

VI F;:: £~ i)-i1 !.1·~; N;ti!utr:.i! t IM\Joc f;.~f! ~,~, k·m fti-.:wf.illr-:tl """' '* !F'1-1~~~:~ ~1:.-..aficm f~ I rt1t•.;:.i.r~;. ft1)tf1 f-ic : 'f-~ Cit\' w£•H v1'4ghl tas;;; tl 1u H;t~~~hir~ Ftfcs !~..,, · ;;;: W!!.d ti;,.-t",;;i"re~ bi.· ...-rt·:~n!;·f~J 'l!'I tm:\ <t,1ta en i;·o...i.1 ~~ . .1t:::'lr~£Jtfi<!!'b, itl::!o~lfl!)

l t~ ::~~~;.r.,•'f€lfD i-4' ;'·IJ.l !f Y.i•.:i:f11r,:. f.11!'!4-t:i.f IT~OO~~s rnWOl1'!} ji'f;m '/~p,~ ~<:r.~i \ .;n;k ti~·:; ~ lf.e-~~1.1pi::.~·"1i~ \ ;;1.1~.i---llP r;,r:i.;11~ .. Dr ;~re•~ ::i~rk::s ·1n.1uli1 .'n h!"r~ttil -~l!~ mnrrrL~r ;ti ·.i~<.t~~ ~.":.ir ::.i~.V·'""'~~tkil'i1~M'l.1~ : tJV,:?r. th<~ :pa\t 1t~·w ~;tm(\13ffil:i'';

·:c, t.!fih-r.'f h~• 'tt~'h mu re:·,13;)td'l .,., ti:rtL~m F1f'1 ~ih.;.o fly~~ '-''l.~r·fil:,,, . \>.tl'l d;1Ss har- ;,$..;.!, 1.>::r:-.~iog.\~l a Si.Ht;'f!}' it1w;..:d ~r.erc. \·,nps ,:300 ct"i-O rrn;;.1"'lTbJlb!.t~.A.ebi!i2 i1i

tt:.~ ...:re tttlpiJ19 lh;i,11his i.;u:ve; ~:1' nMd1 P'~t-.1 "'tu' t. •i~t:f r<"--gu:ilrlv ua~;-8 fmm t .€•11· "fo!f\ r.ll:] ti;~ Bm\shims .an.rl 1~&Hf "~ -.'ti!1dl'I" '• · ~:1t1"l" it '11'.;.."l,,ld it~ i'(l•>sil.1?." fot yo.1.il to ~~-'nai ih~ •... m1.;.:v !fl ._>in~· • ~:oldtrl>M li:-;1 ·~;0&,1 m1~h'.t ha-.1(::: ~ n.li?t.~xd Vs*1 nm t·.1~ t~ If~ ~mvey tt~

·~lt~~e ::!! !>;\{\rdnrr. !i(;'"~ L..1ft· r~r W' EB. r.:: .. 1 lfr.ois. ~~ <ilhi>ti ~I H~t>ri<~ :'.N!;. p;l:';.'t£\'; :i-t ll~', ~ir;m,:(~

"llro<:'lr~ JULJ. 1n .Ot.W:ttrl<.'1 !l'!f V04N ~ ·;he· ;;.;t-~1t?:. uf ~V~iH-4.-M. Vi9<'•ur .... 11n;: Hc~~i:<n :h on beh.U -~r ·r!'u: Deil(t,1>ir~ ~·f.¥ \'\"(;t(ift~ Cn:.a1f,)

33

Appendix D: Berkshire Flyer Ridership Survey

Section l of 4

Berkshire Flyer Ridership Survey

The Uo;;rls$hi1e .f.l7M Group is e1arn i:ning the possibility of establish·ing a sea:son.sl M!~kand pa:>$€fiQ¥.1 :o.<.n1k-e l:>f.·tween t-l'lifaf.1.eJd i;Jld Nf::~v York Ci~y by ~Xl>t:1na:.ng Amtrak's existir1g options.

I.~., r:t~I resecreh is needed tc determine the fe\\'sltili!y i:1f thit- ilrC'$lf.iSJL Sr:. W& WBnt 1".l a~k f'':l 'J th~ foll.~111,irtg ~11&-sti<JM In t:i~ h<:i!;le r.it tl'O'irr9 ;Ji:::':! to 11w5l•Jm11 i+.;:.· d~!mand ft;ir 1his ty!Xl Qf serv~.

Are you in favor of expanding rat! service between the Berkshires and NYC?

Would you use this service if it existed? "

My 1riends/ fa.m;ly and 1....-·0L1ld use thi.s wi<~i:4!' .

. .

34

1

l

J

Secbon 2 of '

Section title (optional)

What is your age?

Sec"Jon 3 0 f 4

Section title (optional)

How often would you use this service? \T

.., ,..

35

How long do you typically spend visiting the Berkshires?

A single day

Mor.J than o wsek

For what reasons would you be visiting the Berkshires?

H1Y.lno/cemplng/frshlng

i;v rtural attraztlans

'kfllng fr er:d~ and farnily

What is your final destination when coming to the Berkshires? *

Gr ellt B:irrlngton

Pittsf~kl

Wllllorro'\cwn

36

l

]

l I

l J

J

What woukl be your seating preference aboard the train?

Service on currently existing lines changes trains at Albany-Rensselaer station, and takes around 5 hours; if the Berkshire Flyer were to run a dedicated train on this same Une, It would take around 4 hours. If the new service were to bypass Albany-Rensselaer, the traveJ time could be further redUced by around 20 minutes. What is the maximum amount you would pay. in order to bypass Albany-Rensselaer on the new service?

Section title ( optiona I)

How much do you currerrtly pay for transportation to the Berkshires?

(OPTIONAL) Are you of Hispanic, Latino, or Spanish orlgin?

fl'4l

*

37

(OPTIONAL) What is your household's total income?

Less than $30,00\l

(OPTIONAL) Check any that apply.

White

/l~kir1

Na1ive I lawaHiiln or Pacific lsli::11v.fei:

38

)

I I I I I I

]

I I l

J

w -0

.._

'\'1mj:ot..-mp /~!\'.f y.'.,Wild1 ¥00 ,,~ """ 111!1'1\i't,'il ii 11.lw ~)W ;~ t.3)'W !>11'.ilf W1'\ll NJOij;Oj':'J wt1Wli'lhi 7~uriWMht.>tdtr..1;:;~ ~~m cli~l(O!>t'i>:(tJPTIONALJ Wlllli ~ Y' Wiii1@~ ?!l:llz1'f 'r~ ht'11!f; t,ilt lliti- th~ l!Ol'Ji~1U11ll IU'?l1H«~1o lllilt W.XI~. II~ ~n tu pc1~~$ !ltO.~ Wt $10,®0 ~11:.iw~1711;~1dlH~ lw®lll P-flW.•lrwrd .. MI ~toollly !~~. IWOMll:l 1M111\.\lWn NifflhAJ.lr1111 Oe~!lh~ 143 "15 ~1) Whitt ii.10,00l lo) l10.000 11/lt'.IC,i' 10:~no y~ M)'ME1'¥1~mlly ll'lil 1 •3,~l fNA111ll1 A~d-il)l(I wc.11 Ni,:rtll Alh1!1~ Ql;ith"" Sil:~ ~H.IJ !ti Wl'!I! 130.IKIO II> $70,0C-C lll~i'il.O l'/ ~-JllM ¥115 lwd r._,. UM this 4P!ll'lll.lll IM l llr.l#t ~t\'lpll'Jhl\1111!,4. ~~} NII lllhorl.I:$ ~.'Ill $30,COO 11imow 1;3fl:27 Yff : ~ Pttton~I, '* UMMM Ytl.rtv h•.: l!.!'~ ~;Y.;. l\'l !J~!~~~ ~cl\<;1 C:.oh Gti111dtf ~ ~ Wl'itW ~.ooo IO $1/JO,(;;XI ~ t/~itl!W t:l f.4·VYt.~ MYMtndl!lflill'lllyMd hl~M ~~ ~J.t.t.'dt.Jnllwttk ~~~ Lllnox ~nm UC ~No ~tr; $100,COOC0$150,000 11~1.117 ~ W:U Vt!t Myfll•!llltiflmlty !11~ I •'1""2 Yi.1!:111 ~11~ llltl llllll'tMl11111 thtallf:;W LM, Llf\OIC, OtCoid\ di ~ (k{;, ':"<llh, tiN!> WWll'I tl00,000 fl\ $11SO,OOO

111~~l71 1:0\!:3t Y~11 My fll<,l'llllrlrnllf~d I •fia.M Yt;a!lv I own~ of tllt clllMn&<.. Hlr.~ ~rhd1 t 2H llM1;o dllllfNo Wit: 1100,Q?l) !Dt~so.c-oo ~1f.4012011 12~~~ Vt.i; My flllli-'lll P.lfllmll~ •nd I ••1-'6 Monttv ~Iha.II. ftGk ~l'.-:irilll llllNctlml Unol! Col~ '!lli S{IO S&4.) No Wl1t~ $100,Q;O IO $1l!O,OOO 1211112011 1Ha;02 YM 1 would pcnoncay ""'° 1 ~•« Monthly Min than Dwelt W.ltile iionaund f1Nort11 Ada"" ei:..~11 a1N.y w111w In 1111 INo WHte $30,000 to '10.000 12111i201T 1U2:13 Vet MyfMnd?~mlly amt I 3'1-4 Mtintll~ A '>tW tJltyi Vl1Hlnt tltntilllnd flOttW S.::tlll~001Clll ell 15 &Hill 121~017 13:39:42 Yo:> I W"411d ptlC'ltlt;llly 1111 t31"'4t Ytll.rly I llW ~ ~llllrtl :lltn.Ollort Nollh Adillm 11ulllm4I s:»G $2& No Whlb 1t/M017 12~40:38 ~· Myfll·:~ •nd I •11"42 Monlhl~ I M ~ llllt 91> 10 I !iWJ 11.~rt ~'11 h rrlllQlCollch llll~S31 f'Jd't Wit«» Willi:! 12/lil".011 13 ... IM1 y_,, My "1~~mly !Ind Ma.30 YH~1 111 .. M~, Ulwl~ ,91111~ ll*A·~ Pltltftr.ld Cot.all d i '3ll 3& IO\lnd ~No WWl6 12/l!ii<l17 13't1i11 YA:~ Myfrlond~ and I •W·M Monlhll' 414-w cl• Vtllli!Q t!omtu nd fi!J:llolt Co;.wll c:11 7$ &Cl N1:> WHtl 12!Si201'n:U!l:lll \'~ I W4lild net lll'At lhll tttvif~ but I know~· 11181 WO\Ad. Gu 111'K1 tol1No WWI& 1215t'401713M38Yc• IW<~P!t~lf UMl31""'2 W.0.,1"1y IJ~ h;rn IJV1)~f,!'."1 iJw1h~ Ca.'IOhai 1501Jwll!an! No WHIO 1"81201113;32:43 '\"ltt I WOllld p.;tlOMlly In~ 14-llO WMldy Mero than 1 w.t.k l/l~g Mtsldl Ind fl~ Cosch cit 12() . ~ No ~ 1!/ti®17 1H,S~ Vo. MVflimlr./f!mlly •nd hl3•ll0 t.~11111 I ll'rtl In tht:I BC'Nl!lrlllW:i 1' IM Bt!Mlllr.eNortll Adoma i!lu•il1e\lll t'lO 0 No Wlit't 1211tl011 1) .M;'48V• IW4Uld~iftlyun11e.ao Wtlldy Mtwdl)la Elut l""' Plltsll'*I Bullnt.:M ~$10043al !\l:J VJliUt 121512.017 13-.38'40 YN I wou)'j l*IO!M.'lly U!..t 11&-:SO P.~ A WNk Culllil'lll ellnlelloM Phl*4i.1 IM!noa 40 30 No Alll~t> 12/5'201 713.~"7:37 YliG i wauld ~ly u."014''\.65 ~ 1 llvt horn · I'd bl vt·lllVQ httti WU.~ ColQll d t SO Hf" No WHle 12J5/201714~65Yu twouldp~.nioMll' lfi131""f Wtddy Aflwlm~ >,,t;~:i '11end11nctf1 oattM BuelMM SSGlcl~ No WWW 12Jll2011 1'4:.04:t:J YH I would pnonlllly Ul'!.:' 131-42 ~ Pelmw\Wlt R8'5ktcnU~ In too .,.._~t!l'Mt~ OolCh cl1$120 ( '80 r.;., WNlll! 12/5"l01714~5:1 5Ye-~ Myflllll'd1111Jmtly!SlldH'Ml4 Yffl1V l llw hl:m l!uhoul\lt Nt Buaintlill't'il t,li tQael No WN\!I 1:VSl2.017 14:17:60 Yff t,t; frlenr.!&lllamlly and I •18-30 WJQl1tJly l/'1)At !M,, ;a Vifflt all of II# RM Pltl09al(I Sllflnc. $2G $100+ _N:) WHllt 1?Ja/201714;1$;4e Ylti I would ~Illy 1111> ltfl.30 YM!ly Ul/<1 In8t.dMl!11 CcUve In Berkahlre ColF'ftl9bld Ooecn ell 40 $0

sao.ooo to m.ooo ~.ooo io $100.000 1100,CX>O IO $1G0,000 $10,000 fO $100,000 $30,000 ID $70,(!{)() More lhlMI $200,000 tr(),000 to $100,000 SHl:0,000. to $150,000 St00.000 to S1li0,000 tr0,000 to $'100.000 $150,000 '° $200.000 $t00,00C lo $150,000 $100,000 to $150,000 $10.~ to $100,000 $30,ooo to sro.ooo

1ZW017 14~1 :2!J V• My fllltN.llllfaml[y and I •31-42 lv~ly ~111an I W«llt 111.anQ Mnndf llnCI ,,~ C:O.Cll di $.'IQ i pay ror-.. M:I W'!illl $'(0,00) lo $100,000 12fft21i17 1432:48 Vt~ lwaultl pctMndly u~ 1455 t.'.l:lmhly t.:Ol91hall a wt.all Vialing lllendu nd f1Mlltll'llllQwn Su1I0011 50 'IS tz~1'14~4:00 YM I woulcl p1:r.on~ly UM 118-30 Monlhly A flw dlyt Vlt !l!t!D f111!nd$11ld ftPHte!leld Olloh di 80 2' No Wtlibt 1W2C17 14:35:14 Vt!! My frlend.X.rrMy lllld 1143·S5 ~ly 111"9 heie aM wo•M) 1llirtl \jlllaoitlenS llllllWM.'Own COid\ d i $20 D:lll'l l'tllfr.imNo \'Jlftt 121'1'2C17 14:311~"4 v~ 1 would pereonillty 11'1;! tee.Got Monlllly 111-.. ~ vi:z~ flli lldt 1r.11 flPllU.fltld C:O.ch di eo .o No wti111:1 t21li!?.ll1 T ~il,4;$:W Y11~ l would pcrl!Olllllly u~ 1466 '\'ileltr lft 111 l fAlllWS fiv:'l In Bttkthlr• Wllamatown CO&Gll d 1 $26 O No ~ 12/Sl2017 1~·$8 Yt\! My flfendtilfamlly ~n:$ I -66+ L'.tlltlNy ~ t~n II Wl!t.k >'.lll& ;, stCCnd hamte.c:Ml Coecll d tDorl't JOoll'l lcnow No ~ 1216.-~17 14:t't9:te y.,., t-.iyfM.ndisffllnjly I nd I • 18-30 Y~y 111-.e M1" CUlill'lll llUf*c:tiOn• L.etlOll ~· ~· S<iC so No V·M~ 121'/1?1.IH t.t;:)R W YllS I would ~'llly 11!t'l 131""2 Wf~y t llW> In \tl4i Baillltllr lllve n f'llBerlcthlrePltlelutld ~ dtSS per I tab lt1& t'SINo Wli1a 12i'ai2017 15:12: 1a Ye:: I would ptrlO!lllly u1111143-SS Moolhly Mor.\ th.In a ~k Vl&fthg :~end.and flP!Uftekl ilrtll. d11> » 30 No \Mite 1;>!M()171S:12:2aV~ ~f~l'ldalftlrrily1ndl 143-~ '1'*111\ly lh¥ttMll! fdbe~ IQNVC Plttjflt ld Coe!lllc:lllHmt4'1 No ll'ih~ 12.1\i:roH 1$ 10:3$ Y~• Myftfend1ilfamly and I ·31-42 Y·)llty A law 4a)'ll Vlalttlg lrien<I• ar~ ft~tlll Collchd1 l!O llO 1211!.'2017 1!\'21~ Yes t ·NOUld perr,orolllly u..'1& 143-55 tklnltlly t.'J.lle that!• Mell all einbo1•e Plttslleld ~ \00\.r.il~tu ~· - .tw Wh~.c

12lf.2~17 iS:3e;59Yn M-jfllelldlll!a111Uy1ndl •lt-42 W~ AfW~!lyt Vltllttlg ~endur.4ft0tfe Ccle•:itd• m ~':) N:• Wh:-ti t2'&'£017 1f' ·37:1!; Y~ ...,. friencblflimlly and I •o43·5tl W?,'ll\y A ll\wel'ly;i; 'Jl~i tlcr.lloan:I f1AU~f® l'lt$1 Cllas· "60 :;45 No 12lllSC17 1S..l&.3il Y()f. My fllend;if:!!mily 81\d I •SIH4 ~ly t:or~ lhan ll WllS. Li"IO llo'):ti Mon~ Cc,-ieh dl~$i7 ar1' "$JyND Wl~!l\ 12/S,,'2017 1f-'46:.S1 Yf;J I w~·Jld not Ute tnle t «YicO lll'd : do not l<M# ·:9!\) "<l!",/; IMI wou::i. : 111181\c.ie ~~

L<tSol tmn $30,00() UlalJ lhan $30.000 $100,000 (0$150,000 $100.00011)$150,000 More 1h11r1 s200.ooo $30,000 lo $70.000 $30,000 lo $7(1,000 More lhan $200,000 Mo~ lhsn 5200,-000

M'Jfe lha11 $20!.l 000 Mnre that! $2:00,000 MQm lhim $:10!H'>OO s1c.:>,x-o t:> s·so.tieo

~ "O -= ('D

Cl r:i. -· ~ ~ .. = ~ .., ~ er ~· l'!!l «"' ~ "'t

~ r:i. ~ .., Q!l

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lwoul!ipnoqlyuM!t!&-30 w.on1111y 4~.,..,,c1aya Vltlklg illM!d11nd hlMIOt1 eus1111111 60 aoNi> twoutcl~lyu"'-> 16e-tl4 ~'IQn~ly Molsttlell1Wffk Vl.ai'!grtf"1nCll .:incHiU:-tr C.Cf!Clll $40 $40No My ~i;Jfwrily 811\1 1 •43-55 Monll'lly A fllw dlfYI Olhufal 111!\IOl.lons l\lollh Ad1J11111 CoaClfl di $1lij $200 Hach ell 30 $16 · IO ll)"C No My !Mn:llllftnily 111d 1 <31-42 t.'onll'lly A U!Qta aey VI~ t:tltnound hFillafiflld Cc:adl di$30 ll'Ac'.f)f'::l'lmll8 No My ftlenoll/t.lmllr •M 1 43-~$ M.?nlhly """ h~ Cll~191 attrc;:(lor.:s Gieat Sarllng';Ccaoll 011~11Urf@$20 ~ch •No lwouldpcrr~lyUE!, 118-30 ~~lhly A~d9)1 ~1111~ Plllafi~<XI Coa.chef1 40 t8No My •~no&liatdly and : :4:t-~ M!>Olhly A 'rJW dG¥a Olllul'l!I suract:ona North Adam$ ec,1ct1 di 825 $200 No My 'lfericl~~y and I •~ .. 55 "s:>n'1!y A few d~Y$ Cll1'1A1l l1'!1actio4'hS Nortll AdM\'l Cntll ell 525 $200 M!1 r,ty 1~!llf,tl\lmlly r;na ; •A3·55 Mi>!lltliy A ~w d11ys Qillllf•l l:lltraQlioll• l'lllrttt Ad11ms; Co:il\'.tl c;!1 $25 $200 ~

Jllillln sac.ooo 111 f10.~ ~ $10,000 Iii $\00,CW 'Malit $:}0,000 IC $10,111,,'-0 'M\lb $00,000 10 $70.003 Alli'tn $100,000 10 $160,000 Wlll\tl, 1\$10,l)QO IC $100,0.X Wit~ $30,0(0 ID $70,000 'Mela $:W,OIJJ, II} $10,°'~ Ylli1!<1 $31),.000 t:; $70,ilC"l V'.111~! $00,000 to $10,003

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lwt""1J J"'1:«ttufly~ 44:1·:l~ Mon.111y >lh!lt l•il'Y:! l!IVt~ "~''' Nt.,,u, ht;Jftt!. (:0..1\:tu;l; $\0 1'1111 !!111t1 Nt1 WIWta $70,000 lo $100,000 IWOltld IXJll(lflJll,uool'.13-(iol ""°""''Y 111\>e ht'IC. CultUt'.71 a!.l.radioos Sed<el Coactld;15;00 25 No Wl'ilt> l.t;t:l: 1!11111 $;10,!Jl!C ; Wlllltl ncl ~!Ill this &efllloa bul I knl!W people thfl1 wOIMI. 1~ No Wl1U. $ l\IG.00!! lo$ Hi{,,(1(1(1 V.y filef.ir./family arrd t • 18-30 Mor.lhly I Cl.llTOl'lffy live In llECultural 31ltaclioTls Nolth Mems Coacti d; $75 $100 No Wtfo• le!lf; lhon $30,000 Y.yfrier«l611'1milvatr<ilo.31· '1l! Mon\ttly Afewda~ Vi~lngfrienlsaod f~PiUsll<ikl Co:ictieli tlOO $200No Wl1ift. t1!l0,0001u$200,000 I wo\Jd p!tei!r'Mlily ur.e 13• .. 4?. Mori!.tily lllve hem i llve here Plttsfil'!ld Coaco;u:t< fo Ila~. dr~ In oocN<:> \'Vlt1'! $15('1,(J)!l to $::JlO.tnl t,ly lril>~ill.lmily .'lr.d I •:;{;-&I M1:1•11Hy i live h~"f'C bul wOl.ll~Vie>iio19 lri0f1oo ll,.,ll ••Sltid<\'ftlgtl ~ $10 0 Yes Wl-ite More ltian $200,000

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'fli lllw!n Hlnfala~;~~h cl:ft4#1Hh!r.\\"'.I ff~:NJ'.., Wtilli s100.~tl)s100,flll') My fll~rl'Jtihmil, Md l •"* Moi11Ny ~~ tf' .. 1r1 '.i w~ifl Cllll!.it.tl ;dr~i i..111111 lu-;lnrif.I m wwU •9}:';, ~ ~ co.ooo l!l 110,lXIO iW!M'I 1*t.':f.~l, 11~ l:J~-4! ~ A~o~ All qt .. alllMi. WtFftlifltfd and 'au.I"'""~ $1~ I/Mt;~ lltt!r.t~ S1~CXIO toS150,COO lwo!lkl 1*'~t1lly11~lGIWA ~ I W'i!Wld ~ 'ltlitn~ Nrci 1111 ¥\i:llng flmll'/ •NY~ Ct>;.iell dlDon'UODn't llmw Ni> $10,l)(ll) lo $100,0CO lwOI# ~lyu0..'- 131"'42 W• tl'An '4l-~ ,,_ii l~HW~· I wOIAd l&t; ~~· I 1CcMI ct '211 m No '>-~~ IA•~ lh'111:10.000 ~"**1ftlrll)' OllCl1 •4'Ma MOii~ 11~11~ l 11' ... llC!t a..11~ ~ Olt 100 "".; !IWll ¢tr No ~il!lle ~MOO to f'f0,000 i WOlllCI ~·ly r.ia.i I ~6-;10 'l'tlll1 Pftftt1131\~~ll CllllllNll~ !AnOll CMellolt 10 eo No Wl!lltl ftO,oco (01100,oco '· W0\111 petf~lllll' ll!!e 116® V.llly Aft•Wlilyl \tllllr..a flllllda ind fll.ee. Cle>Oll Clli $90 111 No 'WWle $70,00J t',) fl00,000 ; WOUid pai!Ollllly U!!O 131-42 Mofltllly A ~f.'<1 llqc' Culllll'li ;llll!Ullor~ Nol'lll Adams CoM:tl Cli 1fl 8'• No ~~ t?o,ooo II) itoo,ooo My fllOndlllflrr·llY ar.IJ I • 11 1rd ul!Ckr My fliWtl!smly OM l 131-42 Ytally 10~ tllttJ, a.m.~ ~rtll M11I"~ e;i., r.11 '1111 t3iO $40 YH Whl't wn.oco IO $1!),C® I-~ p!lt1i0nllll)I u~ 143-116 Morllh1y A few iOyl1 C\llllmll llt!r'ldll:IM It~ Co•dl ell f10 ta().7$ NII WW!e Mol1I tfllln Hoo,c;go Myfrtr~ I M I •43-81 Mantl'Jy Hlw M!Hnd Wint Uvlre llr~. vilitrtV t.Nollh Ad•ma Oo111i1 cl1not ~l1il llv Miit. Ni) Wl'll!i $30,C(.'IJ lo IT0,000 1~~'111Ml1e.3v Monll!'1 111~ 1n111ee~rCJu1u.1~~ NorttiM11111i e.ctid1 t.io $1!.i) No Vful!il $30,0CI) lo $70,000 I wovlll pctlOl!sll)l lll0131-4Z Montl>ly A f9w clJ)'S bulln"s Plltllleld flm c11~·su10 st1'10Q.200 PtNo Mole thin $200.000 My frll~~I' lllld l ·43-d& Moillhl:t A tlrif d<Jya CulU.l 1~11 WlllmtliOWn Ccadl Cll$50 RI Ori-. n> 't~ rro.ooo 1o $100,ooo Myflle.Mll/flrr;ly Ind , ..... Wiidiy Mole lt!Jn... 'IJl"lnO f!IWS. C!.1'111 f1Wett StcokbriCoe.oh d 11k\kno $'iO ~ '•'Vhltlll $3G,OOO lo $70,000 Mt friendiltf.an;ijy Ind I '31'"42 Wdy A VMlt Yt'Olll POasf!llld Cinch d 1$IO t«I buy 4 10 peNo Whikl '30,000 11> S10,Cl0 MyfMll'S~filmlly1tr.dl '40& Monflly tl~ln~~lnthOpJ>lng &~;;NYC ~ c:llS15QltS'r~ 10 NYC No 'Mtta rro.ooo 1o J100,ooo ;would IW'IOIMll)'UH l18-llO Mcmltlly t.billl!iini~ l'lllli'l~~Rlltbld Co&ch'lli ..,. eo No WN1ll rro.ooo 111 s100,ooo ~\lflftnlfllftlmltyar.41 •1WC Wlillllly MM l!IJrtlvr.''4111 Cutlu1tll1ll,.*"8 Pllltlllllll eo.Ollch l!O 11 No Wlilo $30,000 Ill $70.t«> Mr lrion®lf11.mUy • nd t ·43-e8 Monllly A rt-..w ~ b<lond H~ Stocllbrfdg& Coach th$75 orQn ~ W!'<lli; Min thllll $200.000 I wauld ~l'liOl'llly UM t 3t.#l Mot>l'.ty Mole Ill~ "WOOi! WW\ at CUllurlll :tlllltl.Cntol Coach C11 $10 ~ ~ \MlyNO Whi~ Lllu lllln $30.000 ' woukj p('tlOP.'llty UUI 14-eS Monllly A WiCl\ w• l.linox ~eh $100 $4~'1'65 $30,000 ID $70,000 ~ftfendti!ilitillytnd t •a1-42 ~ -.1'\iw~ Cultural l1Uneclilll$ Leno. CO«Ch cll!Jdra t $100 N<1 Wliltl '31>,000 ID $70,000 ~ frlt:nd~'f$1111y •lld I •3M2 ~fly 11"'-il IM ~1 llW ~ Ill" lle~:>llil'!' I ll>'t ~ ll1e be1~ Cit $26 It'• No ll'<'hi\e $30.000 ID $70,000 I wou!";I PMOl\'111)' ~ 131-42 Monl'oly ~ lll:tn • 'MICk Qlltural at;lnlClklnl Pll!alli;tj ~";11 "° <Cl .,"!flir~ll' and 11"6+ YM!ly ~tlwl'll~ f~, StoGkbiclg<! MlltlOl 4 IWrtC:.r N.; ~ MOIOtt&1$200,000 tit/ frlrolld!lllamily afld I •3t-42 Mornr~y UYll '1>~1 ~9clty wn01C eo..:hcl1 10Q ~·t No M'ib $311,000 to $11),000 I w11111d n~ Ut:4'. Ilic Wiii~ Diil i l<nO# peopi. tw.t WIQI, $100 Molt lhtll $2C3.000 J wou:.1 ~di)' U$ll t19·30 Y<;'l!y Mon• tMn • W&flk Wbik Fll\1'1\ekl Coachdl 4(1 W No Wilt. IA&t ttien $30,0CO llfJ lr!Mdi:llllmily and I •86+ Mor1t111 Moc. llttfl 1 ~ ~ml alltalltiona Stocktlldge COl)(t' di S20 •ll t..t.dl -~ Mo!'8 ltlSl'I $2t3,000 ~ wou!:J~•utel31-42 w.kt,• A,...,o.y, : own 11119'!\0IO tw:Lflnoll IJ!ieinal! $'l00 VQrief. N(> •tlti19 $1~!>,000 !O $16Ci,000 !would pel1H.!l'l:.ilyu9Cl31~ Wr.·;Jey llM)ll~~end~~llM~.,,amw®l:!Pllldokl Cllllctl ClllA'lllUn~um.. NI:> lwouki ~:tllyueet«WS Mcnttlly A!t:w!lay3 CuHul'll aantclbnt Wlliamstown C:Uadi w 00 ~ l'llte\lld~llr'.;,jly\IMl31-42 ~ A~dllyi Vl.&.a ftl~ ar.-\1 hPi'.lstlelcl Coe.i:tim~pe $1r~ N) <\Iii~ MG."11 1!~'311 ~o.wo

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$5.00 No .:.;()

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\\lil<ot $1();,,000 to$1 50,000 Aston 1_..,,,,. 1!1~•· $.,ll,l•IU

~-It.I $1tl().(lt1il !()$t!it).f(!()

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I W!.ltJk.1 ~~l~'°"fly U\'1' t.13-!>:> 'r""'tiY f\ lf!-11 '1il)i:l

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1 WOOtl per:IQl1dly use:l65• : t.'IQl:l!1ly U.e •11~11:

150 ·~~·~ ~lJ!ig:~•.vl«,11.Mll!) l~•li•:>C'l<_ l''ll'l'I dll~ ~I

Cullll111l 8llnlctions North Ada1rt1 Cou'11! d! ·100 Uvuhere lo:ttQ• (AW.1;d; :&! Cultural allnlctio,..s Wi~amstown Coal)ll di $;«! Cul~111l 3lrllctlor;!> Notti! Adams BusiROSS 10

No ~te S100,000to$150,000 Kll.i ~ 1-ispanj(More lhan $200,000 lti(l "°" Wit~ !!I00,00011>$tfi0,000 w Nu ~ $30,000 to $10,000

! woc1•:1 "'°'"urll'il'.I' 1t!l(< 1~11~12 'r~~y fl.~*'!~" tk'V 11'.T .. J•S J.11Jt>:urlt1'1.Y btllJ I~-&! Mor;~ily I\,,,.... <1<1'(~

i WUOI~ !lt{ II~ ttt~ ~W.ll: but I k!i<1-V\.>e\'lj'llt> ~'411 W\11. .....

$,:; "-~1 V.Wi.. $7!.l,000 IO $100.COO !it> No White $70,000 to $100,000 $0

I "'1AAI r.u; u~ lf•,C;; .-,r\ll<Y. 'll~l I r.k11111l 1'nt1w <lnyt~ltl "'"" W<lt!ld.

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Cooch d1$20 3C No

ll less tttan $30,000

! "'"''•.11"'"'""-ly 11~ 14'.~.SS UorlJ'I~ /\ f~.,, <M~ c;.11-m.11 •tlll•~.:tlc.~"' North Adalll6 OomJ1 '~' 9lel I would not use 11-is seMc& bL~ I kn<Nr people lhat woud.

f(;o No Wlile $150,000 lo $21Xl,000

t6.v' o d;Ei() ~Varies

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l would pcnanlli!1UM150-M .. ~ A few dlV£ Cultui"-1 ll'1nletkln: S!cokh111Qf! ~di c:t1t~ $100 Acund No Wlilt $150,COO IO $200,000 I would pmo1111ity UM 143-65 WMlcly A ft\'t dqs Culblrtl 4111moUDn::o IAlnOll ~ ~l $2$ $30 No Motll tlto.n $200,000 IWQUld~UMl1lh'!O ~ ~!tltn11wttl! ,,..,111 Qlt.it a~O;cldl~l 21) •100i'Olllldlr~onlh•llll•Le•llllll~&O.ODC 1 wouid ~nlMy 11M I~ v..n1 Mew d~ VWli'IO &l•ndund f11.tr.:ox ~ C11~,.~ ciNo Wlitt $100.000 lo $150,000 I would nd ui.e ., .. ~c;e bull"-people 11191 WOIMI. Ori-Mg, IO ITNo WNtlt My Fri~ and I •31-42 Wtltldy I am M 1lme tnmt:' live l'trt WfJ!ll 61cck~&Jlh'lt':!li '61) t1't No AdM My fl($1ldllfllrray ar.~ I •-13-56 Mllnlhly A WOik ~lbll'il '111tcll!lrlt 1,t;nox Ot:adl c:M llOurTratl No WNID My ft!ttdlfflmly Qnd I •l'tS-64 Yl'lllly Al'~ day Oulllm.ll iilftellona <hat Bamng\r.o.cti d1 !O l drMI My f111111Wfll!llil1t Ind I •et$+ ~'<'11!1!1 A~ \lli.llinv lill!'Cl8 and ftPltllfttld aian• liO 90 IOUllOii'P ·~to.i

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s1so,ooo '° saoo.ooo Melo thlln 1200.000 $70,0001D $100,0Q) $100,000 ID $160,000 $1CO,OOO IO $1$0,000 uo.ooo \0 $10,000

sao.ooo 10 110.000 S1C~JIOO 111 S150.000 sao.ooo to 110.000 11 ~~.ooo 10 s:roo.ooo $70,0CO ID $100,000 More Ir.an $2C>l>,OOO tA1>19 et.• n $2<<0,COO t.Wlt ~9n S2(;1).COO $1t.i),(IC~ II) $150,000 $100,0)Q lo$100.000

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Ml! rr;..1d(!!ll.v1~ ~II'•! I' 1!1·~\\l y,...,,., t.l<.wr, \ll::u; '' ""~"' C.11~1~11 ~lllti;;mi; .IK'.Cb'$ !'ill<.nli'l:l<1~1- S'tU $1)(1 Nu Wblo M\f ll1W¥tsihlu"y tu1>.i I ·4'~.:l.'5 lio•ll!1ty Moxt- ii><•",.,,.,~~ l:t1t,1r•ll iti:•>Mi•1n~ IJ!f• (~111f' <~<''?"- l r~ml<>t:.U. l'fo White $1:i0,0Q() l() lu Nt1 Wl'!•I $30,000 ID $70,000 lW011'l l)!ll'i!OIWI~ 111;,, I ~l4-~v.! U.111~J~ A-.•. ~''""1 $.1nt<:t0.ur.. Leno>< Com~l d; Jll$. i:i N<.1 Wl~te $30,000 10 $70.000 : wc.1ukl l>'.'~>1:;i~ly """ 131 .. ,:; Ye..,.1y I l•w ;,, 111~ tlt.1•!<1111111111'! '"'"' Wil~•llll!!klw!I 0,.,.,,, ,~, "'o ;1':> .,,1""~""~' Wt•;~ $11J.\JOO "'$tO,tro twould personaly use t ~ r Md "-Titler I wuo~J f'l!':;l••~jl~ lll'ft 1·1!1 :;i; '-l<.111d~~

My l•i11nd1.<:l\,,.1l!ly m11i 1 • itl-~li.' Momhly M)' lllL'ltk°!k•1>ily ><Ill~ I ·00·6·' Yearly 1 Wt>U~l l~l'<l"-11)' <t~t I it n",'.l 11'11.l<l"

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- - - - .__.. - - - -

49

Appendh. F: Statistical Analysis of Data

Results showed that only household total income has a statistically significant impact on whether a respondent would ride alone or with family (household income was fowid to account for more than 62.4% of original data).

Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 4.002 1 .045

Block 4.002 1 .045

Model 4.002 1 .045

Chi-square test with a significance level of 0.05 for household total income is 4.002 and exceeds critical value 3.84. The p-value in this test is 0.045 which is below 0.05, indicating that our findings were statistically significant.

V«iabJes m the f~ioll

ti I S.f W~1'cl I 41' !.~19 t Yp.(9}

Stem 1-' 0.PTIOfll.t\.1,."•1\!JY<itlSVU!Jl1Wu 222 ! ,·; t ; ~ MO I 1 Jj~.~ ~~JiGH1$tOt~ lt:r.CDtflj: ~

I i C(li"i S~4,f?lt .tn·: .4tH 4307 · 1 .ti:.ll) ~ l •

- - ...

From the result we get, we assume X as household total income and derive the prediction equation I:

sen

l 2S6

Where : X is categorized into six groups, I for below 30,000; 2 for 30,000 to 70,000; 3 for 70,000 to 100,000; 4 for 100,000 to 150,000; 5 for 150,000 to 200,000; 6 for above 200i000.

50

I I 1

I I I I I

I l

I j

Appendix G: Maps of Tax Bill Addresses

Tax BiUs Mailed from Adams

Tax Bills Mailed from Alford

51

Tax Bills Mailed from Becket

/

••

Tax Bills Mailed from Cheshire

t'

52

I l 1

l l I I l J

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j

Tax Bins Mailed from CLARKSBURG

lax Bills Mailed from DALTON

53

Tax BiUs Mailed from Egremont

Tax Bills Mailed from Florida

· uo j L

54

l l I I

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l

Tax Bills. Mailed from Great Barrington

~ \~I'

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· / '°u I / r I

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,..._-.::~~· .

Tax Bins Mailed·from HANCOCK

55

Tax Bills Mailed from Hinsdaile

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Tax Bills Mailed from LANESBORO

~UD I I ,,

56

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)

Tax Bins Mailed from Lee

Tax BiUs Mailed from LENOX

57

Tax Bills Mailed from New Ashford

\ ~UD

•

Tax Bills MaUed from NORTH ADAMS

58

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Tax BiHs Mailed from Peru

I

\ ~- -·-~

I

Tax Bills Mailed from PIITSFIELD

59

Tax Bills Mailed from SAVOY

\ etUD

Tax Bills Mailed from Richmond

60

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Tax Bills Mailed from Sheffield

Tax BiHs Mailed from STOCKBRIDGE

"-....._ \

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YN'i ··..,.....· ~-.4.,._...,_-

61

Tax Bills Mailed from VJashington

Tax Bills Mailed from West Stockbridge

I ~uo·, r · - -=--,,-.-1--

j fHI fPU

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62

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Tax Bins Mailed from WILLIAMSTOWN

Tax Bills MaHed from WlNDSOR

l l (

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~

63

Appendix H: python Script for Generating City Maps Using MassGIS Data

#!/usr/bin/python # # Written by Erin Kiley <[email protected]>, latest revision Dec 18, 2017

from mpl_toolkits.basemap import Basemap # for drawing map import matplotlib.pyplot as plt import numpy as np import re

import zipcodes import 9eopy.distance # for computing distance between coordinates

from scipy.spatial import Voronoi

import glob # for listing .xlsx files

import openpyxl # for reading Excel files from openpyxl.utils import get_column_letter, column_index_from_string

def is_number(s): try:

float(s) return True

except ValueError: pass

try: import unicodedata unicodedata.numeric( s ) return True

except (TypeError, ValueError): pass

return False

def check_dist_to_stations(lat,long,sta_lat,sta_long): #using Vicenty dis tance formu la dists= [] coords_to_check =(long, lat) for i i n range(0 , len(sta_lat}):

station_coords = (sta_long(i),sta_lat[i]) dists.append(geopy.distance.vincenty{station_coords,coords_to_check}.miles )

#print dis ts return (min(dists),dists.index(min(dists)))

def get_zips(wbname): #gets addresses from specified Excel file, saves as array of s tri ng ~ wb = openpyxl. load_workbook(wbname) sheet = wb.active zips=[) unique_addrs = [J for i in range( 2 ,sheet.max_row):

addr = sheet.cell(row=i,column--column_index_from_string("R" }).value if addr and addr not in unique_addrs:

unique_addrs.append(str(addr)) state= sheet.cell(row=i,column=column_index_from_string{ "U" )).value if state:

state = str(state) if state=="NY" or state=="NJ" : II pick just the NY or NJ state addresses

ZIP= sheet.cell(row=i,column=column_index_from_string( "V" )).value if ZIP:

ZIP = str(ZIP}

64

1

l I

J

J

J

ZIP = re. findal 1( '\d+ ' ,ZIP) [0] # gets the r i rst number in the string (avoids any ZIP+4 issues , and gets a too-she rt numhe r f rorn non·-US codes with alphabetic characters )

i f zipcodes.is_valid(ZIP): zipdata = zipcodes.matching (ZIP) [0] zips.append(zipdata.get( "zip_code" ))

return (zips ,sheet.max_row)

de f get_unique_z ips(zips): sk i nny_zips = list(set(zips)) # gets unique values counts = [zips.count(zip) for zip in skinny_zips l #coun t s occurrences return (skinny_zips,counts)

def get_coords(zips): lats = [] longs = [] for zip in zips:

zipdata = zipcodes.matching(str(zip))(0) lats.append(zipdata.get( ulat" )) longs.append(zipdata.get("long" ))

return (lats, longs}

def get_cityname(wbname}:

def

wb = openpyxl.load_workbook(wbname) sheet = wb.active cityname = sheet.cell(row=2,column=column_index_from_st ring( ' P')) .value return cityname

get_data(lats, longs, fcity,fc i tyny30,fny30,fcityny50,fny50,st ation_latitudes,station_longitu des): #gets coord i nates from addresses, saves as coordinates

lat30 = (] long30 = [] lat50 = (] long50 = (] station50=[ 0J*len(station latitudes) station30=[ 0J*len(station-latitudes) for lat,long in zip(lats,longs):

fcity.write(str(lat)+" , "+str(long)+"\n" ) (dis t _to_stations,which_sta) =

check_dist_to_stations(lat,long,station_latitudes,station_longitudes) /i p 1 i n I dis t _to_stations i f dist to stations <= 30. 0 :

lat30.append(lat) long30.append(long} f cityny30.write(str(long)+" , "+str(lat)+"\n" } fny30.write(str(long)+" , "+str(lat)+"\n" ) lat50.append(latl long50.append(long) fcityny50. write( str{ long)+" , "+str( lat) +"\n" ) fny50.write(str(long)+" , "+str(lat)+"\n" ) station30[which_sta]=station30[which_sta] +l station50[which_stal=station50[which_sta] +l

el1f dist to stations <= 50 .0 : fcityny50. write( std long)+" , "+str( lat )+"\n" ) fny50.write( str( long)+" , "+str ( lat}+"\n" ) l at50.append (lat) l ong50.append(long) station50[which_sta]=station50[which_sta] +l

ret urn (lat30,long30, lat50, long50,station30,stat i on50)

def vorono i_f i nite_polygons_2d(vor, radius=None ): .... .. Reconstruct infinite voronoi regions in a 20 di agram to finite regions.

65

Parameters

vor : Voronoi Input diagram radius : float, optional Distance to 'points at infinity'.

Returns

regions : list of tuples Indices of vertices in each revised Voronoi regions. vertices : list of tuples Coordinates for revised Voronoi vertices. Same as coordinates of input vertices, with 'points at infinity ' appended to the end .

if vor.points.shape[l ] != 2 : raise ValueError( "Requires 2D input" )

new_regions = [] new_vertices = vor.vertices.tolist()

center = vor.points.mean(axis=0 ) if radius is None:

radius = vor.points.ptp().max()

# Const ruct a map containing all ridges for a given point a l l_ridges = {} tor (pl, p2l, (vl, v2) in zip(vor.ridge_points, vor.ridge_vertices):

an_ridges. setdefautt(pl, []).append( (p2, vl, v2l) all_ridges. setdefault(p2, (]).append( (pl, vl, v2))

# Reconstruct infinite regions for pl, region in enumerate(vor.point_region):

vertices= vor.regions[region]

if alt(v >= 0 for v in vertices): # finite region new_regions.append(vertices) continue

# reconstruct a non-finite region ridges = all_ridges[pl] new_region = [v for v in vertices if v >= 0 )

for p2, vl, v2 in ridges: if v2 < 0 :

vl, v2 = v2", vl if vl >= 0:

# finite ridge: already in the region continue

# Compute the missing endpoint of an infinite ridge

t = vor.points[p2} - vor.points[pl) #tangent t /= np. linalg.norm(t) n; np.array([-t[l ], t[0])) #normal

midpoint= vor.points[[pl, p2]].mean(axis=0 ) direction = np.sign(np.dot(midpoint - center, n)) * n far_point = vor.vertices[v2] + direction * radius

I I l I

l )

l ]

]

l J

66

new_region.append(len(new_vertices)) new_vertices.append(far_point.tolist())

:if: sort region counterclockv1ise vs= np.asarray([new_vert ices [v] for v in new_region]) c = vs.mean(axis=0) angles= np.arctan2(vs[:, 1] - c[ l ], vs [ :, 0] - c[0)) new_region = np.array(new_region)[np.argsort(angles) ]

# f i nish new_regions.append(new_region.tolist())

return new_regions, np.asarray(new_vertices)

# Define marke r colors colors = [ ' xkcd:purple' , 'xkcd:green ' , 0 xkcd:blue ' , 'xkcd:pink' , 'xkcd: brown ' , 'xkcd:red' , ' xkcd:light blue• , •xkcd:teal' , 'xkcd:orange' , 'xkcd:light green' , ' xkcd:magenta ' , 'xkcd:yellow' , 'xkcd:sky blue' , 'xkcd:grey' , 'xkcd:lime green' , 'xkcd:light purple' , 'xkcd:violet' , 'xkcd:dark green' , 'xkcd:turquoise' , 'xkcd:lavender' , 'xkcd:dark blue' , 'xkcd:tan• , 'xkcd:cyan' , 'xkcd:aqua' , 'xkcd:forest green' , 'xkcd:mauve' , 'xkcd:dark purple' , 'xkcd:bright green' , 'xkcd:maroon' , 'xkcd:olive' , 'xkcd:salmon' , 'xkcd:beige' , 'xkcd:royal blue ' , ' xkcd:navy blue• , 'xkcd:lilac' , 'xkcd:black' , 'xkcd:hot pink' , 'xkcd:light brown' , 'xkcd:pale green' , 'xkcd:peach' , 'xkcd:olive green ' , 'xkcd:dark pink' ]

# De fine c i ty landmarks landmark_names = [ ' Paterson' , 'Edison' , 'Elizabeth' , 'Newark' , 'Yonkers ' , 'White Pl.a ins • , 'Hempstead• , •West Po int •] landmark_longitudes = [-74. 173, - 74.407 , -74.21, -74.171, -73. 9034, -73.762, -73.6216, -73.957449J landmark_latitudes ; [40.923, 40.511, 40.66, 40.73, 40.926, 41.0326 ,40.7027, 41.38992)

# Def i ne s t ations for Vo ronoi diagr am station_names = ["NYP", "YNY" , "HUD" , "CRT" , "POU", "RHI"] station_longitudes = [-73.993292, -73.902465, -73.798168, -73.882433, -73.937663, -73.951372] station_latitudes = [40.750322, 40.935544, 42. 253805,41.189614,41.707077, 41.921154]

# Draw base maps plt.figure( l ) bigmap = Basemap(projection= 'merc ' , lat_0 = 41, lon_0 = -74,

resolution = 'f' , area_thresh = 0.1, llcrnrlon=-74.5789, llcrnrlat=40.557, urcrnrlon=-72.36, urcrnrlat=42.43)

x,y = bigmap(station_longitudes,station_latitudes) x_otfsets = [-22500, -21000, 0, 0, 0, 0] y_offsets = [0, 0, 0, 0, 0, 0) for label, xpt, ypt, x_offset, y_offset in zip(station_names, x, y,x_offsets,y_offsets):

plt.text(xpt+x_offset, ypt+y_offset, label) points; np.column_stack((x,y)) vor = Voronoi(points) regions,vertices ; voronoi_finite_polygons_2d(vor) #print "-·-·" #print 1 e:·gions #print " - " # pri.nt ve rt ices for region in regions:

polygon = vertices{region) plt.fill(*ZiP(*polygon),alpha=0 .4)

plt. plot( points [:, 0], points [:, l ], ' ko' ,markersize=4) plt.xlim(vor.min_bound[0] - 8.1, vor.max_bound[0) + 0.1) plt.ylim(vor.min_bound[ l ] - 0.1, vor.max_bound[ l ) + 0.1)

bigmap.drawcoastlines() bigmap.drawcountries()

67

#bigmap.fillcontinents(color = 'coral') #bigmar.drawmapboundary(fill_color='aqua') bigmap.drawstates() bigmap.drawrivers()

#filenames = ["NewAshford.xlsx"l filenames= glob.glob( '*.xlsx' ) #List all ,xlsx files in an array color_index=0 # Starting index for cycling through marker colo rs

allny30 = open( "All_30mi_Coords.txt" , 'a ' } allny50 = open( "All_50mi_Coords.txt" , 'a' } allreport = open( "Rep•Jr::. t1:" , ' 'V1 1

)

allreport.write( "Report automatically generated by Python on the basis of MassGIS data.\n\n'NY/NJ' refers to the number of tax bills mailed to New York or New Jersey addresses; '30 mile' and '50 mile' headings refer to the number of tax bills mailed to addresses within 30 or 50 miles (respectively) of one of the following stations: NYP, YNY, CRT, POU, RHI, HUD. Headings 'NYP30' and 'NYP50' refer to the number of tax bills mailed to addresses within 30 or 50 miles (respectively) of NYP station; similarly for other stations. \n\nCity name \t Total tax bills \t NY/NJ \t 30 mile \t 50 mile \t NYP30 \t NYP50 \t YNY30 \t YNY50 \t CRT30 \t CRT50 \t POU30 \t POU50 \t RHI30 \t RHI50 \t HU030 \t HUD50 \n\n" )

for file in filenames: # for each c ity cityname = get_cityname(file) # get the city's n;::imc:, print ("Generating data and map fo r "+cityname+" .•• " } cityny30 = open(cityname+"_30mi _Coords. txt ", 'w' ) cityny50 = open(cityname+"_50mi_Coords. txt" , 'w' ) citycoords = open(cityname+"_NYNJ_Coords. txt" , 'w' ) (zips,num_addrs) = get_zips(file) #get the ZIP codes tor city tax bil ls #(zips ,zip_counts) = get_unique_zips(zips) (lats, longs)= get_coords(zips) #get latitudes and longitudes for ZIP codes (lat30,long30,lat50,1ong50,station30,station50) =

get_data(lats, longs,citycoords,cityny30,allny30,cityny50,allny50,station_latitudes,station_ longitudes) # get all the latitudes and longitudes for the city tax bil "ls

al lreport. write( ci tyname+"\ t"+st r( num_addrs )+"\ t"+st r( len( lats))+"\ t"+st r( 1.en ( lat30 l )+" \ t" +st r(len( lat50) )+"\ t"+st r( station30 (0) )+"\ t"+str( station50 (0)) +"\ t"+st r( station30 [1) l +"\ t" +st r( station50 (1 I)+"\ t"+str( station30 [3] )+"\ t"+st r( station50 [3 ]) +"\ t"+st r( station30 [4 ] )+" \ t"+str ( station50 [4 J) +"\ t"+st r( stat ion30 [5 J ) +"\ t" +st r( station50 (5) )+"\ t"+str( station30 (2) l + "\t"+str( station50 [2] )+"\ t" +"\n" )

print ( cityname+"\ t"+st r( num_addrs)+"\ t"+st r{ len(lats) }+"\t"+st r( len ( lat30)) +"\ t"+st r(le n( lat50)) +"\ t"+st r( stat ion30 [0] ) +"\ t"+st r( station50 [0] ) +"\ t"+s tr{ stat ion30 [1 I}+"\ t"+s tr( sta tion50[1))+"\t"+str(station30[3])+"\t"+str(station50[3])+"\t"+str(station30{4))+"\t"+str(st at ion50[41 ) +"\ t"+st r( station30 [5] )+"\ t "+st r( station50[51) +"\ t"+st r (stat ion30 (2) )+"\ t"+str< s tation50[2])+"\t"+"\n" )

dot_color=colors (color _index] ti get the co Lo r for t lie dots

if long30: plt.figure( l ) counts = [long30.count(long) tor long in 1ong30] #counts the number of occurrences

of each ZIP code maxct = max(counts) minct = min(counts) for i in range( l ,len(long30)): #for each coordinate until the l ast one

x,y = bigmap(long30[i),1at30[i]} #get lat/long attributes for overall bigmap if maxct == minct:

themarksize = 1 else :

themarksize = 3. 0*(counts[iJ-minct)/(maxct-minct} + 1.0 bigmap.plot(x,y,color=dot_color,marker= 'o ' ,markersize=themarksize) # add marke r

to overall bigmap, scaled by number of plots

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plt.figure( 3) plt.clf() city_bigmap = Basemap(projection= ' merc ' , lat_0 = 41, lon_0 = -74,

resolution= 't' , area_thresh = 0 . 1, llcrnrlon=-74.5789, llcrnrlat;40.557, urcrnrlon=-72.36, urcrnrlat=42.43)

x,y = city_bigmap(station_longitudes,station_latitudes) x_offsets = [-22500, -210-00, 0, 0, 0, 0) y_offsets = [0, 0, 0, 0, 0, 0) for label, xpt, ypt, x_offset, y_offset in zip(station_names, x,

y,x_offsets,y_offsets): plt.text(xpt+x_offset, ypt+y_offset, label}

points = np.column_stack((x,y)} vor = Voronoi(points) regions,vertices = voronoi_finite_polygons_2d(vor) ''p r i nt 11

--11

i;pr i nt regions 1::pr i nt "--" f;pri.nt vertices for region in regions:

polygon = vertices[regionJ plt.fill(*zip(*polygon),alpha=0.4) plt.plot(points[:, 0],points[:, l ], 'ko' ,markersize=8) plt.xlim{vor.min_bound[0) - 0.1 , vor.max_bound[0) + 0.1} plt.ylim(vor.min_bound( l ] - 0. 1, vor.max_bound[ l ] + 0.1 )

city_bigmap.drawcoastlines() city_bigmap.drawcountries( ) city_bigmap.drawstates() city_bigmap.drawrivers() #ci t y_bi gmap. fillcontinents{color = ' coral') city_bigmap.drawmapboundary() for i in range( 1,len(long30)): #for each coordinate until the last one

x,y = city_bigmap(long30{i], lat30(i]} #get l at/long attributes for ci ty bigmap if maxct == minct:

themarksize = 4 else:

themarksize = 3.0*(counts[i]-minct)/{maxct-minct) + 4.0 city_bigmap.plot(x,y,color=dot_color,marker= 'o' ,markersize=themarksize) # add

marke r to c ily ll.i.qmdp #x, y c i t y biDrnap ( landmark_longitudes, landma rk_latitudes ) #fo r L.i l.h~l . xp t , ypl .i.11 zip(landmark_names, x, y): :;;> ptt.tex L(xµ1., yp1, label) plt.title( 'Tax Bills Mailed from ' +cityname) plt.savefig(cityname+"_bigmap.png" )

color_index=color_index+l # change the color incex for the~ nr:xt c.ity cityny30.close() cityny50.close() citycoords.close()

plt. figure( 1) #plt. legend ( .oc::"upper rigllt" ) plt.title( ''iHl Tex 51lls" ) #x,y ::: bigmap(landmark_longit udes , lan<l111C11-·-< latitudes) #for label, xpt , ypt in zip( landmil rk_namc~s , x, y): # rJl. i . text( xpt, ypt , label) plt.savefig( "al lbills_bigmap. png" )

allny30. close() allny50.close() allreport.close()

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