The evolving Interstate Highway System and the changing geography of the United States

Journal of Transport Geography 25 (2012) 70–86

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The evolving Interstate Highway System and the changing geography of the United States Joe Weber ⇑ Department of Geography, Box 870322, University of Alabama, Tuscaloosa, AL 35487, United States

a r t i c l e

i n f o

Keywords: Interstate Highway System Accessibility Network analysis Sunbelt

a b s t r a c t The Interstate Highway System is a product of the 1930s and 1940s, yet remains essential to U.S. transportation in 2012 and for the foreseeable future. This analysis examines how the Interstate Highway System has changed since its inception in 1938, first map in 1947, and the beginning of construction in 1956. The mileage has grown considerably, allowing for many new routes, and the spatial coverage of the network has been extended to allow many new metropolitan areas to be connected. This has lowered connectivity but increased the metropolitan population served. A GIS dataset was created for the 1947 network, allowing it to be compared to the current network using standard accessibility measurement techniques. This research shows that the Interstate System has not kept up with population shifts in the South and West, and there is no correlation between accessibility change and population change. The greatest improvements have in fact taken place in the densest part of the network, not where population or traffic growth has been greatest. It has therefore reinforced advantages held by places already well placed on the original 1947 network. The old American Manufacturing Belt continues to provide an effective regionalization for capturing variations in the Interstate network, though it has become the Rustbelt and is of declining importance within the country. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction The Interstate Highway System (or IHS, Fig. 1) makes up the majority of the mileage of the American freeway system and is an essential component of U.S. transportation, carrying 24% of daily vehicle miles traveled despite making up only 1.15% of national road mileage (Federal Highway Administration, 2008a). It is also the product of a long ago era in the country’s transportation geography. Planning for this system began in 1938, which was only 28 years after the country reached its peak level of horse powered transportation and 6 years before American railroads reached their highest ever passenger counts (Vance, 1990). Only 14 years had passed since every state had created a highway department (Weber, 2005), and bus service over the country’s highways would remain racially segregated for another 23 years (Arsenault, 2006). Route 66 was only 12 years old, had only been completely paved for 1 year, and would not become famous in The Grapes of Wrath for another year or for the song until 1946 (Wallis, 2001). Only a year had passed since the destruction of the Hindenburg ended transatlantic dirigible service, and there would be no domestic

⇑ Tel.: +1 205 348 0086; fax: +1 205 348 2278. E-mail address: [email protected] 0966-6923/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jtrangeo.2012.07.012

jet airliner service for another 21 years (Vance, 1990), National highway vehicle miles traveled (VMT) in 1938 were about 1/10th the 2000 value, while the total road and street mileage of the country (2,639,324 km or 1,640,000 miles) was only 37% of the mileage existing in 2000 (Federal Highway Administration, 1995). The geography of the United States was also quite different in 1938. The population recorded in the 1940 census was only 150 million, about half that of 2010. New York City (with 11,690,520 people, 63% of the 2000 value) was the world’s largest city (Harris, 1942). Of the 140 metropolitan districts of 50,000 or more people the Census Bureau identified for the 1940 census, only 11 contained over 1 million people, compared to 261 metropolitan areas in 2000, 49 of them having a population greater than 1 million people. Several of the 50 largest metropolitan areas of 2010, such as Las Vegas or Orlando, were insignificant towns in the 30s and 40s. The distribution of these metropolitan districts showed that the largest cities were concentrated within the American Manufacturing Belt (AMB). This area, roughly bounded by the East coast, Ohio and Mississippi rivers, and the Great Lakes (Hartshorne, 1936; Wright, 1945), contained the vast majority of the nation’s population and industrial capacity. Since that time the country’s population has not only doubled but also shifted increasingly towards the southern and western states (the Sunbelt). Manufacturing has also decentralized widely, causing many Midwestern cities to lose their economic base and much of their population.

J. Weber / Journal of Transport Geography 25 (2012) 70–86

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Fig. 1. The Interstate Highway System, 2000. Data source: Bureau of Transportation Statistics, 2007.

The Interstate System is a product of the 1930s and 1940s, yet remains essential to the U.S. in the 21st century and will continue to serve as the primary intercity highway network for the foreseeable future. Given how much the country has changed since 1938, how has the Interstate System changed as well? It can be hypothesized that the intercity component of the Interstate System will have adapted to changing conditions by adding new links in areas of the country that have seen substantial population and economic growth since the 1940s. Rapidly growing Sunbelt cities should see their connectivity within the national system, and accessibility to other places, greatly increased. Given the decline of the AMB and growth of the Sunbelt it can also be expected that the IHS will provide a more even level of service throughout the country than originally designed, with a lower level of accessibility variations. This study examines how the size, connectivity and accessibility of this intercity transport network has evolved as the country has changed since the late 1930s, whether it reflects the changing population geography of the country, and how it may continue to evolve in the next half century. Changes in the Interstate Highway System between 1950, the first year for which metropolitan areas were defined, and 2000, the last year for which consistent metropolitan area definitions are available, are examined in relation to changing population patterns. While considerable attention has been devoted to the creation of freeway networks within urban areas and consequent impacts at this scale (Moon, 1994), this research is directed at the national scale.

2. Origins of the Interstate Highway System Initial planning for the Interstate system began when a provision was inserted into the Federal Aid Act of 1938 directing the Bureau of Public Roads to investigate ‘‘the feasibility of building, and cost of, superhighways not exceeding three in number, running in a general direction from the eastern to the western portion of the United States, and not exceeding three in number, running in a general direction from the northern to the southern portion of the United States, including the feasibility of a toll system on such

roads’’ (U.S. Congress, 1938, p. 636).1 This report, Toll Roads and Free Roads, was completed in 1939 and showed that a set of national toll roads was not feasible (Bureau of Public Roads, 1939). However, interest led to a second report (National Interregional Highway Committee, 1944, p. 20), which outlined a 54,589 km (33,920 mile) ‘‘National System of Interregional Highways’’ for which ‘‘the primary purpose was to select routes forming an integrated system of reasonably limited total extent which would join the principal centers of population and industry in each geographic region with centers of similar relative importance in other geographic regions, by lines as direct as practicable.’’. The goal was therefore ‘‘the interconnection of the larger cities in all regions, accommodation of short-run traffic in and about lesser centers insofar as practicable, and creation of a system of optimum extent and maximum utilization’’ (1944, p. 20). This network would connect all cities with more than 300,000 people, and 130 out of the 140 metropolitan districts. The largest cities not on this proposed network were Akron, Canton, and Youngstown, Ohio. Additional criteria for the network were discussed, including serving manufacturing, agriculture, war industry and areas where postwar employment would be greatest. In each of these cases the recommended network provided a high level of service, as each of these coincided with the location of the largest cities in the country (though less so for agriculture). Similar outcomes were present for car registrations and traffic. Terrain was mentioned as a minor locational factor, as ‘‘the location of the recommended routes has been influenced in remarkably few places solely by consideration of topography’’ (1944, p. 19), though it did provide an explanation for apparent route indirectness and ‘‘the varying sizes of interstices between the meshes of the system in different parts of the country’’ (1944, p. 19).

1 Fishman (2007) traces the Interstate System further back into the New Deal programs of the 1930s, perhaps even to Theodore Roosevelt’s National Conservation plan of 1908, itself a modernized national master plan in the spirit of the 1808 Gallatin plan for internal improvements that led to the National Road through the Midwest (Goodrich, 1958).

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J. Weber / Journal of Transport Geography 25 (2012) 70–86

This study led to the creation of a new national highway system. The Federal-Aid Highway Act of 1944 included a section of about 150 words that specified a National System of Interstate Highways to comprise no more than 64,374 km (40,000 miles), and ‘‘so located as to connect by routes, as direct as practicable, the principal metropolitan areas, cities, and industrial centers, to serve the national defense, and to connect at all suitable border points with routes of continental importance in the Dominion of Canada and the Republic of Mexico’’ (U.S. Congress, 1944, p. 842). The routes were to be jointly selected by the states and federal government. In 1946 the states proposed routes for the Interstate system, totaling 45,070 miles, well beyond the 40,000 mile limit (Bureau of Public Roads, 1946). This mileage was trimmed, and on March 14, 1946, a map of 60,067 km (37,324 miles) was sent out to all states for their approval. Nebraska was the first to agree, and a tentative map of the Interstate system was distributed August 2, 1947 (Fig. 2) (Bureau of Public Roads, 1947). This 60,642 km (37,681 mile) system (urban routes were added later) was described as having ‘‘north–south, east–west, and diagonal routes that will make it possible to travel from any section of the country to any other section by a direct route’’ (Bureau of Public Roads, 1947, p. 5). It would serve 182 of the 199 cities of 50,000 or more people. Not every city in the AMB was on the network, as some medium sized or small cities were passed by in favor of nearby larger cities, but most were quite close to it. This is similar to a pattern observed several decades later for air transport, in which

medium-sized cities within the AMB often had much more limited airline service than their populations would indicate due to their proximity to larger cities with more important airports (Taaffe, 1956). However, no funding for the system existed, and no construction took place. That problem was not resolved until the Federal Aid Highway Act of 1956 (U.S. Congress, 1956) was passed and created the Highway Trust Fund, to be filled with gas tax money for construction. The Act also increased the mileage limit to 65,983 km (41,000 miles) and changed the name of the system to the National System of Interstate and Defense Highways. Construction finally began (although some existing freeways were incorporated into the system) and was to be completed by June 30, 1972 (Moon, 1994; Lewis, 1997; Weber, 2011). In 1992 the Interstate System was officially declared complete (McNichol, 2006), but over 1500 miles have been added since then and construction will continue into the foreseeable future. The Interstate Highway System has had enormous impacts on American travel patterns, urban geography, economic patterns, rural geography, and culture (Moon, 1994; Nadiri and Mamuneas, 1996; Lewis, 1997; McNichol, 2006; Weber, 2004, 2011; Warf, 2008; Swift, 2011). In addition to transforming American life, the system has also adapted to changing American geography. The mileage of the system has been expanded, and many new routes added; new metropolitan areas have been connected to the system and the accessibility patterns of the system have changed.

Fig. 2. Interstate Highway System map of 1947. Source: Bureau of Public Roads, 1947.

J. Weber / Journal of Transport Geography 25 (2012) 70–86

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Fig. 3. Route additions and new MSAs since 1950. Data source: Bureau of Transportation Statistics, 2007.

2.1. Enlarging the Interstate System As soon as the system was funded in 1956 it began to be altered. Congress expanded the mileage limit in 1957, 1968, and 1973, though requests for new mileage by states always exceeded that available (Federal Highway Administration, 2009). Much of this mileage went to urban routes (not discussed in this research), but the intercity system grew as well. The official mileage limit is currently 68,869 km (42,793 miles), but beginning in 1968 additional routes could be added to the IHS if they were useful additions, though they would not be funded at the regular rate of 90% federal to 10% state funds. These ‘non-chargeable’ routes have allowed the total IHS mileage to exceed the official mileage limit, reaching 75,198 km (46,726 miles) as of 2002 (Fig. 3). The IHS was extended to Hawaii (82 km or 51 miles), Alaska (1741 km or 1082 miles), and Puerto Rico (402 km or 250 miles) in 1960, though roads in the latter two areas need not be built to freeway standards (Weingroff, 2009). Once mileage was added, it could be allocated to lengthening existing routes (such as I-70 west of Denver2) or adding entirely new routes (such as I-77), either of which required a collaborative process between states and the federal government, with local interests also strongly involved in attempting to influence the results (Ripple, 1975). Additionally, the urban freeway revolt of the 1960s led to the possibility of allowing a new route to be substituted for another (Schwartz, 1976). This was an outgrowth of successful freeway protests in San Francisco between 1959 and 1965, when the planned Embarcadero freeway was abandoned and the Century freeway in Los Angeles substituted (Mohl, 2004). The Federal Aid Highway Act of 1973 formalized the process whereby routes may be transferred within a state (Schwartz, 1976), allowing the original 1947 map to be altered to fit local needs.

2 Colorado was the only state to oppose the creation of the IHS in 1944, apparently due to opposition over the lack of a route west of Denver that was added in 1956 (Weingroff, 2008). The highway was extended to allow greater access between Southern California and Colorado and points east.

Although the Interstate System was officially considered to be complete in 1992 and the focus of national transportation policy shifted away from the system, construction has not stopped. The addition of non-chargeable routes continues, though as of 2002, all but 9 km (5.6 miles) of the 68,869 km (42,793 mile) chargeable system were completed (Federal Highway Administration, 2009). New Interstate highways may still be added, either by action of the Federal Highway Administration or through laws passed by Congress (Federal Highway Administration, 2008b). Many new routes have been authorized and may be constructed when funding becomes available (Fig. 4). The new U.S. 78 freeway (Appalachian Regional Corridor X) between Memphis, Tennessee, and Birmingham, Alabama, will become I-22 when the last freeway section is complete in Birmingham in 2012. Other authorized routes include I-49 between Shreveport, Louisiana, and Kansas City, Missouri; I69 from Indianapolis, Indiana, to Mexico; I-73 and I-74 from Ohio to Myrtle Beach, South Carolina; and I-86 in New York. Many other routes have been or are being discussed and it can be expected that additional routes will be added in the future, and in that sense the Interstate System will never be completed. Many additional freeways that are not part of the IHS but are constructed to the same standard have been built in many states, leading to a total of 95,857 freeway kilometers (59,563 miles) in the U.S. (Federal Highway Administration, 2006). A number of non-chargeable Interstate routes have been designated on existing non-IHS freeways, while several routes have lost their Interstate status. The boundary between the IHS and functionally identical freeways is therefore quite flexible. Rather than arbitrarily limit this discussion to only those routes carrying an official Interstate number, the Interstates and all additional connected freeway routes are treated here as part of a single American freeway system. 2.2. Changing metropolitan population on the Interstate Highway System As the goal of the Interstate System was to connect large cities, the network can be evaluated as to how well it continues to serve

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J. Weber / Journal of Transport Geography 25 (2012) 70–86

Fig. 4. Future Interstate routes. Source: Federal Highway Administration, 2008b.

this goal. In 1950 the Census Bureau began presenting statistics for large cities in the form of metropolitan areas based on county populations (Adams et al., 1999). In that census there were 168 Standard Metropolitan Areas (SMAs) in the contiguous states (Table 1). The number of metropolitan areas has increased from the 168 SMAs of 1950 to 274 Metropolitan Statistical Areas (MSAs) in 2000, though the 2000 metro areas often combine several cities treated separately in 1950. By 2010 this number had grown to 366 MSAs, but because of significant changes in how these MSAs are defined for 2010 the 2000 MSA definitions and populations are used here. To allow for comparability those 1950 SMAs contained within a single 2000 MSA were combined for this research, resulting in 135 metro areas for 1950. Of these, 121 were on the 1947 network, and 14 were left off.3 Those cities on the system contained 97% of the nation’s metropolitan population and 57% of the total U.S. population (Table 2). The importance of the American Manufacturing Belt at this time can be seen by the fact that those MSAs within it and on the 1947 network account for 65% of total metropolitan population. While many of the new MSAs added by 2000, such as Las Vegas, Nevada, were located along routes of the Interstate system, the 3 An SMA or MSA was counted as being on the network if the freeway route passed through the central county of the metropolitan area. Garrison (1960) counted 143 SMAs on the network in 1960, and 23 off the network. It was not possible to identify which SMAs were off the network and why his count differs from the one presented here.

freeway mileage added to the American freeway system also allowed many new metropolitan areas to be connected to the system, increasing from the 121 of 1950 to 241 in 2000 (Table 2). These metro areas now include 97.47% of total metropolitan population, a percentage slightly lower than in 1950. While new routes serve to connect many new MSAs, these are predominantly smaller metro areas, such as Lubbock, Texas, or Columbus, Georgia. The great majority of MSAs and metro population (92.68%) on the IHS is actually on the routes first specified in 1947. The declining importance of the AMB can be seen by the fact that cities in that area now account for only 41.6% of total metropolitan population. Thirty-three metro areas remained off the American freeway system in 2000,4 though only San Angelo, Texas, was left off the network in both 1950 and 2000. The McAllen–Edinburg–Mission, Texas, MSA is the largest of these (with a 2000 population of 569,463), though it is connected by freeway to the nearby Brownsville–Harlingen–San Benito MSA (the fourth largest not on a freeway). Some cities, such as the declining steel town of Johnstown, Pennsylvania, attribute much of the economic misfortunes to their lack of Interstate highways (Mellott, 2007), yet the city is connected to I-76 and the rest of the IHS by a non-Interstate freeway (US 219) and is therefore considered here to be on the system. The goal of serving

4 PB Consult, Inc. (2007) mentioned 70 MSAs located off the network, but did not mention which ones, for what year, or what criteria may have been used to define this set.

Table 1 Comparison of metropolitan area rankings in 1950 and 2000. 2000 MSA

2000 Population

New York–Northern New Jersey–Long Island, NY–NJ–CT–PA CMSA

21,199,865

Los Angeles–Riverside–Orange County, CA CMSA

Rank

On IHS

New route

Acc rank

In AMB

1950 SMA equivalent to 2000 MSA/ CMSA

1950 Population

Rank

On IHS

Acc rank

1

Y

No

158

Yes Yes Yes Yes Yes Yes

2

Y

No

222

Chicago–Gary–Kenosha, IL–IN–WI CMSA

9,157,540

3

Y

No

15

Washington–Baltimore, DC–MD–VA–WV CMSA

7,608,070

4

Y

No

110

12,911,994 545,784 504,342 258,137 229,781 154,656 4,367,911 281,642 5,495,364 75,238 1,464,089 1,337,373 2,240,767 290,547 3,671,048 268,387 132,399 2,483,568 581,776 546,401 156,987 137,469 133,028 125,935 3,016,197 270,963 614,799 361,253 806,701 113,066 671,797 495,084 732,992 275,876 331,770 1,116,509 1,465,511 410,032 148,162 556,808 1,681,281 563,832 409,143 2,213,236 704,829 904,402 147,203 277,140 814,357 871,047 109,585 114,950 551,777 500,460

1 32 35 74 85 112 3 67 2 164 11 12 7 63 4 73 131 6 25 31 111 125 129 135 5 72 24 49 19 157 23 38 20 70 54 13 10 44 116 29 9 27 45 8 21 16 117 68 18 17 141 138 30 37

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y

79

16,373,645

New York–Northeastern NJ New Haven, CT Stamford–Norwalk, CT Bridgeport, CT Trenton, NJ Waterbury, CT Los Angeles, CA San Bernardino, CA Chicago, IL–IN Kenosha, WI Washington, DC–MD–VA Baltimore, MD San Francisco–Oakland, CA San Jose, CA Philadelphia, PA–NJ Wilmington, DE–NJ Atlantic City, NJ Boston, MA Brockton, MA Worcester, MA Manchester, NH New Bedford, MA Lowell, MA Lawrence, MA Detroit, MI Flint, MI Dallas, TX Fort Worth, TX Houston, TX Galveston, TX Atlanta, GA Miami, FL Seattle, WA Tacoma, WA Phoenix, AZ Minneapolis–St. Paul, MN Cleveland, OH Akron, OH Lorain-Elyria, OH San Diego, CA St. Louis, MO–IL Denver, CO Tampa–St. Petersburg, FL Pittsburgh, PA Portland, OR–WA Cincinnati, OH–KY Hamilton–Middletown, OH Sacramento, CA Kansas City, MO–KS Milwaukee, WI Racine, WI Orlando, FL Indianapolis, IN San Antonio, TX

Yes Yes Yes

7,039,362

5

Y

No

234

Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD CMSA

6,188,463

6

Y

No

139

Boston–Worcester–Lawrence, MA–NH–ME–CT CMSA

5,819,100

7

Y

No

191

Detroit–Ann Arbor–Flint, MI CMSA

5,456,428

8

Y

No

64

Dallas–Fort Worth, TX CMSA

5,221,801

9

Y

No

113

Houston–Galveston–Brazoria, TX CMSA

4,669,571

10

Y

No

155

Atlanta, GA MSA Miami–Fort Lauderdale, FL CMSA Seattle–Tacoma–Bremerton, WA CMSA

4,112,198 3,876,380 3,554,760

11 12 13

Y Y Y

No No No

60 205 238

Phoenix–Mesa, AZ MSA Minneapolis–St. Paul, MN–WI MSA Cleveland–Akron, OH CMSA

3,251,876 2,968,806 2,945,831

14 15 16

Y Y Y

No No No

215 118 42

San Diego, CA MSA St. Louis, MO–IL MSA Denver–Boulder–Greeley, CO CMSA Tampa–St. Petersburg–Clearwater, FL MSA Pittsburgh, PA MSA Portland–Salem, OR–WA CMSA Cincinnati–Hamilton, OH–KY–IN CMSA

2,813,833 2,603,607 2,581,506 2,395,997 2,358,695 2,265,223 1,979,202

17 18 19 20 21 22 23

Y Y Y Y Y Y Y

No No No No No No No

223 1 165 175 66 236 5

Sacramento–Yolo, CA CMSA Kansas City, MO–KS MSA Milwaukee–Racine, WI CMSA

1,796,857 1,776,062 1,689,572

24 25 26

Y Y Y

No No No

229 33 44

Orlando, FL MSA Indianapolis, IN MSA San Antonio, TX MSA

1,644,561 1,607,486 1,592,383

27 28 29

Y Y Y

No No No

172 2 168

Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Yes Yes Yes Yes

Yes Yes Yes

Yes Yes Yes

Y

10 48 119 67

98

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y

24 86 99 37 109 121 113 81 18

J. Weber / Journal of Transport Geography 25 (2012) 70–86

San Francisco–Oakland–San Jose, CA CMSA

114

115 11 105 103 30 120 3 117 41 34 102 2 106 75

(continued on next page)

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Table 1 (continued) 2000 MSA

2000 Population

Rank

On IHS

New route

Acc rank

Norfolk–Virginia Beach–Newport News, VA–NC MSA Las Vegas, NV–AZ MSA Columbus, OH MSA Charlotte–Gastonia–Rock Hill, NC–SC MSA New Orleans, LA MSA Salt Lake City–Ogden, UT MSA

1,569,541 1,563,282 1,540,157 1,499,293 1,337,726 1,333,914

30 31 32 33 34 35

Y Y Y Y Y Y

No No No No No No

151 217 20 84 126 210

Greensboro–Winston-Salem–High Point, NC MSA

1,251,509

36

Y

No

89

Austin–San Marcos, TX MSA Nashville, TN MSA Providence–Fall River–Warwick, RI–MA MSA

1,249,763 1,231,311 1,188,613

37 38 39

Y Y Y

No No No

163 6 186

Raleigh–Durham–Chapel Hill, NC MSA

1,187,941

40

Y

No

108

1,183,110

41

Y

No

173

Buffalo–Niagara Falls, NY MSA Memphis, TN–AR–MS MSA West Palm Beach–Boca Raton, FL MSA Jacksonville, FL MSA Rochester, NY MSA Grand Rapids–Muskegon–Holland, MI MSA Oklahoma City, OK MSA Louisville, KY–IN MSA Richmond–Petersburg, VA MSA Greenville–Spartanburg–Anderson, SC MSA Dayton–Springfield, OH MSA

1,170,111 1,135,614 1,131,184 1,100,491 1,098,201 1,088,514 1,083,346 1,025,598 996,512 962,441 950,558

42 43 44 45 46 47 48 49 50 51 52

Y Y Y Y Y Y Y Y Y Y Y

No No No No No No No No No No No

120 26 197 150 140 68 80 3 116 76 11

Fresno, CA MSA Birmingham, AL MSA Albany–Schenectady–Troy, NY MSA Tucson, AZ MSA Tulsa, OK MSA Syracuse, NY MSA Omaha, NE–IA MSA Albuquerque, NM MSA Knoxville, TN MSA El Paso, TX MSA Bakersfield, CA MSA Allentown–Bethlehem–Easton, PA MSA Harrisburg–Lebanon–Carlisle, PA MSA Scranton–Wilkes-Barre–Hazleton, PA MSA

922,516 921,106 875,583 843,746 803,235 732,117 716,998 712,738 687,249 679,622 661,645 637,958 629,401 624,776

53 54 55 56 57 58 59 60 61 62 63 64 65 66

Other Y Y Y Y Y Y Y Y Y Other Y Y Y

Yes No No No No No No No No No Yes No No No

231 47 169 214 72 152 71 189 22 204 225 138 109 137

Toledo, OH MSA Baton Rouge, LA MSA Youngstown–Warren, OH MSA Springfield, MA MSA Sarasota–Bradenton, FL MSA Little Rock–North Little Rock, AR MSA McAllen–Edinburg–Mission, TX MSA Stockton–Lodi, CA MSA Charleston–North Charleston, SC MSA Wichita, KS MSA Mobile, AL MSA

618,203 602,894 594,746 591,932 589,959 583,845 569,463 563,598 549,033 545,220 540,258

67 68 69 70 71 72 73 74 75 76 77

Y Y Y Y Y Y

No No No No Yes No

32 123 62 180 187 57

Y Y Y Y

No No No No

230 135 82 121

Yes

Yes Yes

Yes Yes Yes

Yes Yes Yes

Yes Yes

Yes

Yes

Yes Yes Yes Yes Yes Yes Yes

1950 SMA equivalent to 2000 MSA/ CMSA

1950 Population

Rank

On IHS

Acc rank

Norfolk–Portsmouth, VA

293,552

60

Y

77

Columbus, OH Charlotte, NC New Orleans, LA Salt Lake City, UT Ogden, UT Greensboro-High Point, NC Winston-Salem, NC Austin, TX Nashville, TN Providence, RI Fall River, MA–RI Raleigh, NC Durham, NC Hartford, CT New Britain–Bristol, CT Buffalo, NY Memphis, TN

503,410 197,052 685,405 274,895 83,319 191,057 146,135 160,980 321,758 1,111,926 61,539 136,450 101,639 358,081 146,983 1,089,230 482,393

36 93 22 71 163 96 119 108 58 14 166 126 148 50 118 15 40

Y Y Y Y Y Y Y Y Y Y

7 46 83 112

Jacksonville, FL Rochester, NY Grand Rapids, MI Oklahoma City, OK Louisville, KY–IN Richmond, VA Greenville, SC Dayton, OH Springfield, OH Fresno, CA Birmingham, AL Albany–Schenectady–Troy, NY

304,029 487,632 288,292 325,352 576,900 328,050 168,152 457,333 111,661 276,515 558,928 514,490

59 39 64 56 26 55 104 41 140 69 28 34

Y Y Y Y Y Y Y Y Y

91 68 69 71 1 52 39 4

Y Y

35 88

Tulsa, OK Syracuse, NY Omaha, NE–IA Albuquerque, NM Knoxville, TN El Paso, TX

251,686 341,719 366,395 145,673 337,105 194,968

78 52 48 120 53 95

Y Y Y Y Y Y

70 72 65 108 13 111

Allentown–Bethlehem–Easton, PA Harrisburg, PA Scranton, PA Wilkes-Barre–Hazleton, PA Toledo, OH–MI Baton Rouge, LA Youngstown, OH–PA Springfield–Holyoke, MA–CT

437,824 292,241 257,396 392,241 395,551 158,236 528,498 455,565

43 61 75 47 46 110 33 42

Y Y Y Y Y Y Y Y

66 43 61

Little Rock–North Little Rock, AR

96,685

156

Y

49

Stockton, CA Charleston, SC Wichita, KS Mobile, AL

200,750 164,856 222,290 231,105

92 106 87 84

Y Y Y Y

118 75 74 80

51 101 12 97 60

Y Y Y Y Y

90 58 29

15 87 25 93

J. Weber / Journal of Transport Geography 25 (2012) 70–86

Hartford, CT MSA

In AMB

536,691 516,929 502,141 493,175 483,924 480,091 479,198 477,441 476,230 470,658 465,161 456,022 452,851 447,728 446,997 440,888 440,801 432,345 426,526 417,939 412,153 406,934 403,070

78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100

Salinas, CA MSA Santa Barbara–Santa Maria–Lompoc, CA MSA Shreveport–Bossier City, LA MSA Lafayette, LA MSA Beaumont–Port Arthur, TX MSA York, PA MSA Corpus Christi, TX MSA Reading, PA MSA Rockford, IL MSA Provo–Orem, UT MSA Visalia–Tulare–Porterville, CA MSA Biloxi–Gulfport–Pascagoula, MS MSA Davenport–Moline–Rock Island, IA–IL MSA Appleton–Oshkosh–Neenah, WI MSA Peoria–Pekin, IL MSA Huntsville, AL MSA Hickory–Morganton–Lenoir, NC MSA Reno, NV MSA Brownsville–Harlingen–San Benito, TX MSA Montgomery, AL MSA Springfield, MO MSA Eugene–Springfield, OR MSA Macon, GA MSA Fort Pierce–Port St. Lucie, FL MSA Huntington–Ashland, WV–KY–OH MSA Killeen–Temple, TX MSA Fayetteville–Springdale–Rogers, AR MSA Fayetteville, NC MSA Utica–Rome, NY MSA Evansville–Henderson, IN–KY MSA New London–Norwich, CT–RI MSA Savannah, GA MSA Tallahassee, FL MSA Erie, PA MSA Columbus, GA–AL MSA

401,762 399,347 392,302 385,647 385,090 381,751 380,783 373,638 371,236 368,536 368,021 363,988 359,062 358,365 347,387 342,376 341,851 339,486 335,227 333,055 325,721 322,959 322,549 319,426 315,538 312,952 311,121 302,963 299,896 296,195 293,566 293,000 284,539 280,843 274,624

101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135

Y Y Y Y Y Y Y Y Y Other Y Y Y Y Other Y Y Y Y Y Y Y Y

No No No No No No No No No Yes No No No No Yes Yes No No No No No No No

96 177 27 167 178 50 8 95 184 125 24 53 39 61 233 198 78 220 59 226 141 48 92

Other Y Y Y Y Y Y Y Y Other Y Y

Yes No No No No Yes No No No Yes No No

224 111 130 149 115 194 133 25 213 228 127 28

Y Y Y Y

No Yes No No

16 49 73 227

Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y

No No No No No No No Yes No No Yes No No No No Yes

83 58 239 91 190 34 153 105 131 161 18 176 128 157 81 101

Columbia, SC

142,565

121

Y

53

Fort Wayne, IN

183,722

98

Y

14

Lexington, KY Augusta, GA–SC

100,746 162,013

150 107

Y Y

5 63

Lancaster, PA Chattanooga, TN–GA Des Moines, IA Kalamazoo, MI Lansing, MI

234,717 246,453 226,010 126,707 172,941

82 80 86 134 100

Y Y Y Y

21 44 20 45

Jackson, MS

142,164

122

Y

57

Madison, WI Spokane, WA

169,357 221,561

102 88

Y Y

42 116

Canton, OH Saginaw, MI Bay City, MI

283,194 153,515 88,461

66 113 160

Y Y Y

22 56

Shreveport, LA

176,547

99

Y

85

195,083 202,737 165,471 255,740 152,385

94 91 105 76 114

Y Y

95 47

Yes Yes

Beaumont–Port Arthur, TX York, PA Corpus Christi, TX Reading, PA Rockford, IL

Y Y

64 32

Yes

Davenport–Rock Island–Moline, IA–IL

234,256

83

Y

28

Yes

Peoria, IL

250,512

79

Y

17

Montgomery, AL Springfield, MO

138,965 104,823

124 145

Y Y

54 50

Macon, GA

135,043

127

Y

59

Yes

Huntington–Ashland, WV–KY

245,795

81

Y

23

Yes Yes Yes

Utica–Rome, NY Evansville, IN

284,262 160,422

65 109

Y

82

Savannah, GA

151,481

115

Y

78

Erie, PA Columbus, GA–AL

219,388 170,541

89 101

Y

38

Yes

Yes

Yes Yes

Yes Yes Yes

Yes

Yes

77

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J. Weber / Journal of Transport Geography 25 (2012) 70–86

Columbia, SC MSA Colorado Springs, CO MSA Fort Wayne, IN MSA Daytona Beach, FL MSA Lakeland–Winter Haven, FL MSA Johnson City–Kingsport–Bristol, TN–VA MSA Lexington, KY MSA Augusta–Aiken, GA–SC MSA Melbourne–Titusville–Palm Bay, FL MSA Lancaster, PA MSA Chattanooga, TN–GA MSA Des Moines, IA MSA Kalamazoo–Battle Creek, MI MSA Lansing–East Lansing, MI MSA Modesto, CA MSA Fort Myers–Cape Coral, FL MSA Jackson, MS MSA Boise City, ID MSA Madison, WI MSA Spokane, WA MSA Pensacola, FL MSA Canton–Massillon, OH MSA Saginaw–Bay City–Midland, MI MSA

78

Table 1 (continued) 2000 MSA

265,559 258,916 252,320 251,662 251,494 251,377 250,291 246,681 243,815 243,537 242,628 237,132 235,932 233,450 232,621 226,778 225,965 222,581 217,955 217,858 214,911 213,517 210,554 208,780 207,290 207,033 203,171 201,437 196,629 194,477 193,117 191,822 191,701 183,577 182,821 182,791 181,269 179,669 175,818 174,706 174,682 174,367 172,412 170,498 169,871 169,391 167,392 166,814 164,875 163,256 162,582 162,453 160,026 159,576 158,422 157,322

Rank

On IHS

New route

Acc rank

In AMB

1950 SMA equivalent to 2000 MSA/ CMSA

1950 Population

Rank

On IHS

Acc rank

136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191

Y Y Y Y Y Y Y

No No Yes No No Yes No

21 162 148 40 171 202 87

Yes

South Bend, IN

205,058

90

Y

16

Yes

Binghamton, NY Charleston, WV

184,698 322,072

97 57

Y Y

76 33

Lincoln, NE

119,742

137

Y

73

Y Y Y Y Y Y Other Y Y Y Y Y

No No Yes No No Yes Yes Yes No Yes No No

164 203 182 181 85 154 94 104 63 235 156 159

Duluth–Superior, MN–WI Portland, ME Lubbock, TX

252,777 169,201 101,048

77 103 149

Y Y

96 104

Roanoke, VA

133,407

128

Y

40

Johnstown, PA Green Bay, WI Asheville, NC

291,354 98,314 124,403

62 154 136

Y

31

Amarillo, TX

87,140

162

Y

100

Y

No

145

Waco, TX

130,194

133

Y

94

Y Y Y

No No Yes

117 86 13

Y

No

9

Springfield, IL

131,484

132

Y

19

Y Y Y Y Y Y Y Y Other Y Y Y Y

No Yes Yes No No No No No Yes No No No No

195 232 46 147 12 35 241 4 41 122 206 166 132

Laredo, TX

56,141

168

Y

110

Cedar Rapids, IA

104,274

146

Sioux Falls, SD

70,910

165

Y

89

Y Y Y Y Y Y Other Y Y Y Y Y

No No No No No No Yes No No No No No

52 207 142 240 67 237 201 31 219 107 45 70

Topeka, KS

105,418

143

Y

62

Jackson, MI

107,925

142

Y

26

Yes

Yes

Yes

Yes Yes Yes Yes

Yes Yes

Yes

J. Weber / Journal of Transport Geography 25 (2012) 70–86

South Bend, IN MSA Ocala, FL MSA Binghamton, NY MSA Charleston, WV MSA Fort Collins–Loveland, CO MSA Naples, FL MSA Lincoln, NE MSA San Luis Obispo–Atascadero–Paso Robles, CA MSA Duluth–Superior, MN–WI MSA Portland, ME MSA Lubbock, TX MSA Odessa–Midland, TX MSA Roanoke, VA MSA Wilmington, NC MSA Johnstown, PA MSA Green Bay, WI MSA Asheville, NC MSA Yakima, WA MSA Gainesville, FL MSA Amarillo, TX MSA Lynchburg, VA MSA Waco, TX MSA Merced, CA MSA Longview–Marshall, TX MSA Fort Smith, AR–OK MSA Clarksville–Hopkinsville, TN–KY MSA Chico–Paradise, CA MSA Springfield, IL MSA Myrtle Beach, SC MSA Houma, LA MSA Laredo, TX MSA Richland–Kennewick–Pasco, WA MSA Cedar Rapids, IA MSA Lake Charles, LA MSA Lafayette, IN MSA Elkhart–Goshen, IN MSA Medford–Ashland, OR MSA Champaign–Urbana, IL MSA Mansfield, OH MSA Tyler, TX MSA Las Cruces, NM MSA Fargo–Moorhead, ND–MN MSA Sioux Falls, SD MSA Fort Walton Beach, FL MSA Topeka, KS MSA Burlington, VT MSA St. Cloud, MN MSA Bellingham, WA MSA Tuscaloosa, AL MSA Redding, CA MSA Barnstable–Yarmouth, MA MSA Benton Harbor, MI MSA Yuma, AZ MSA Charlottesville, VA MSA Jackson, MI MSA Joplin, MO MSA

2000 Population

155,084 153,444 153,172 152,415 152,307 151,237 150,433 150,355 149,192 148,337 148,217 147,635 147,250 145,867 143,026 142,950 141,627 141,472 140,518 139,750 139,149 137,916 135,758 135,454 133,798 132,008 129,749 129,352 129,144 128,012 126,838 126,697 126,555 126,337 125,834 125,761 124,345 124,277 124,130 122,366 120,822 120,563 120,293 120,044 118,769 116,255 115,092 114,996 114,706 113,329 112,646 112,249 111,674 111,006 110,595 110,156 107,377 104,646 104,010

192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250

Y

No

29

Yes

Lima, OH

88,183

161

Y

9

Y

No

55

Yes

Wheeling–Steubenville, WV–OH

354,092

51

Y

27

Y Y Y

No Yes No

37 51 10

Yes Yes

Y Y

No No

7 106

Terre Haute, IN

105,160

144

Y

6

Y Y Y Y

No No No No

196 98 38 129

Y Y Y Y

Yes No Yes Yes

193 185 143 100

Pueblo, CO Wichita Falls, TX

90,188 98,493

159 153

Y

107

Y

No

19

Other Y Y Y Y Y

Yes No No Yes Yes No

74 102 209 99 77 88

Altoona, PA Waterloo, IA

139,514 100,448

123 151

Y Y Y Y Y Y Y Y

No Yes Yes No No No No No

160 144 124 114 179 97 103 212

Sioux City, IA

103,917

147

Y

84

Y Y Y Y Y Y Y

No Yes No Yes No Yes Yes

65 136 17 200 90 119 14

Yes Yes Yes Yes

Muncie, IN

90,252

158

Y

8

Yes

Decatur, IL

98,853

152

Y Y Y Y Other

Yes No No No Yes

75 69 112 36 134

Y

No

30 San Angelo, TX

58,929

167

Yes

Yes

Yes

Yes

Yes

Yes

79

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J. Weber / Journal of Transport Geography 25 (2012) 70–86

Lima, OH MSA Athens, GA MSA Wheeling, WV–OH MSA Bryan–College Station, TX MSA Janesville–Beloit, WI MSA Parkersburg–Marietta, WV–OH MSA Bloomington–Normal, IL MSA Jacksonville, NC MSA Terre Haute, IN MSA Eau Claire, WI MSA Panama City, FL MSA Santa Fe, NM MSA Monroe, LA MSA Decatur, AL MSA Rocky Mount, NC MSA Florence, AL MSA Punta Gorda, FL MSA Pueblo, CO MSA Wichita Falls, TX MSA Jamestown, NY MSA Yuba City, CA MSA Dothan, AL MSA State College, PA MSA Columbia, MO MSA Greenville, NC MSA Steubenville–Weirton, OH–WV MSA Texarkana, TX–Texarkana, AR MSA Billings, MT MSA Altoona, PA MSA Waterloo–Cedar Falls, IA MSA La Crosse, WI–MN MSA Dover, DE MSA Abilene, TX MSA Alexandria, LA MSA Wausau, WI MSA Florence, SC MSA Glens Falls, NY MSA Rochester, MN MSA Sioux City, IA–NE MSA Flagstaff, AZ–UT MSA Albany, GA MSA Bloomington, IN MSA Sharon, PA MSA Williamsport, PA MSA Muncie, IN MSA Grand Junction, CO MSA Auburn–Opelika, AL MSA Lawton, OK MSA Decatur, IL MSA Goldsboro, NC MSA Sheboygan, WI MSA Anniston, AL MSA Hattiesburg, MS MSA Iowa City, IA MSA Sherman–Denison, TX MSA Danville, VA MSA Jackson, TN MSA Sumter, SC MSA San Angelo, TX MSA

large cities has generally been met, though it seems likely that continued route additions will be necessary to maintain current coverage levels.

92

36 55

J. Weber / Journal of Transport Geography 25 (2012) 70–86

Acc rank

80

Y

Y Y

132,966

130

157 155 93,892 96,826

No No Y Y

216 199

No No Y Y

170 221

Yes No No Yes Y Y Y

188 174 79

Yes Yes

Yes

No No No No Yes Yes No No Y Y Y Y Other Other Y Y

43 183 218 192 23 146 211 208

Yes

Pittsfield, MA

Gadsden, AL St. Joseph, MO 54 56 93 No No Yes Y Y Y

251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 103,459 102,490 102,008 101,541 99,962 97,478 95,802 94,719 91,545 91,070 90,864 90,830 89,143 88,565 84,699 84,278 84,088 82,148 81,607 80,357 78,153 75,565 66,533 57,813 Gadsden, AL MSA St. Joseph, MO MSA Cumberland, MD–WV MSA Kokomo, IN MSA Lawrence, KS MSA Grand Forks, ND–MN MSA Missoula, MT MSA Bismarck, ND MSA Owensboro, KY MSA Elmira, NY MSA Bangor, ME MSA Lewiston–Auburn, ME MSA Dubuque, IA MSA Rapid City, SD MSA Pittsfield, MA MSA Pine Bluff, AR MSA Victoria, TX MSA Jonesboro, AR MSA Cheyenne, WY MSA Great Falls, MT MSA Corvallis, OR MSA Pocatello, ID MSA Casper, WY MSA Enid, OK MSA

2000 MSA

Table 1 (continued)

2000 Population

Rank

On IHS

New route

Acc rank

In AMB

1950 SMA equivalent to 2000 MSA/ CMSA

1950 Population

Rank

On IHS

2.3. Changing connectivity on the Interstate System The growth of the network and the addition of additional MSAs can be expected to have altered the structure of the network. This can be examined with graph theory by treating the network as a set of nodes (MSAs) and links (routes between them). A simple measure of connectivity is the degree of a node, or the number of links connecting it to adjacent nodes (Garrison, 1960). A higher degree means more direct connections to other cities, and will increase as new routes are added to the network. If new MSAs appear along existing routes this will however likely reduce the average degree of the network, as will cities located at the ends of spurs. The degree of each MSA was counted, with freeway links leaving the urbanized area of the primary city and connecting directly to another MSA or international boundary crossing outside the MSA representing links. Chicago had the highest degree (eight), followed by Indianapolis with seven radiating routes in 1947. The average degree in 1950 was 3.06, falling to 2.84 in 2000 due to the addition of many spurs and MSAs appearing along existing routes (Table 3). The effects of these changes were not distributed evenly, however. The average degree of cities within the old AMB was and remains higher than those outside it, and actually increased for AMB cities between 1950 and 2000, while it fell for those outside the AMB. While coastal cities and those near border crossings (both predominantly outside the AMB) will, however, likely receive a lower score due to their peripheral location, it is clear that cities within the core were more likely to receive new routes than those outside. While many new routes have been added to serve new MSAs outside the core, these have tended to be spurs or cities added along single routes and so lowered the degree value. Degree values show a moderate correlation with population for both years (0.352 in 1950 and 0.533 in 2000) (Table 4), reflecting the greater size of cities located in the well-connected AMB. The range and standard deviation slightly increased during this period, showing that unevenness in connectivity within the network increased. Bigger cities became better connected over time, but smaller metro areas were more likely to be located along single routes or spurs. 2.4. Network accessibility A simple means of measuring changes to a network is by examining the changing accessibility of places on it. Accessibility is a fundamental concept in geography that has been developed into a range of meanings (Kwan and Weber, 2003). While space-time measures focus on individual mobility, aggregate or proximity measures evaluate the location of a place or set of places to another set of places. The closer a location is to more destinations the higher its accessibility. A range of proximity-based measures has been developed, including the population potential or field based notions. Many studies have used this or related accessibility measures to examine accessibility or accessibility change within European highway or railroad networks (Linneker and Spence, 1992; Gutiérrez and Gómez, 1999; Holl, 2007). However, this measure is not appropriate here because it is better suited to a continuous accessibility surface rather than for a relatively small number of discrete nodes. Also, since the focus here is on network change, any change in population potential would almost entirely reflect population change rather than that of the network structure. The Shimbel or topological accessibility shows the sum of shortest network distances from each location to all other locations on

81

J. Weber / Journal of Transport Geography 25 (2012) 70–86 Table 2 Metropolitan population on IHS in 1950 and 2000. Total MSA population

MSAs

Located on IHS

All MSAs

MSAs

Percent of MSAs

MSA population

Percent of total MSA population

MSAs

Percent of MSAs

MSA population

Percent of total US population

1950

86,204,157

in AMB not in AMB Total

56 79 135

51 70 121

91.07 56,234,298 88.61 27,870,966 89.63 84,105,264 Percent of US population

65.23 32.33 97.57 55.81

56 79 135

41.48 58.52 100.00

57,159,158 29,044,999 86,204,157

37.93 19.27 57.20

2000

224,845,240

in AMB not in AMB Total

76 198 274

72 169 241

94.74 93,590,737 85.35 125,565,654 87.96 219,156,391 Percent of US population

41.62 55.85 97.47 77.87

76 198 274

27.74 72.26 100.00

94,037,742 130,807,498 224,845,240

33.42 46.48 79.90

Table 3 Accessibility in 1950 and 2000.

1950

2000

Total MSA population

Region

Total MSAs

MSAs on IHS

Average Shimbel

Average degree

86,204,157

West South Midwest Northeast Total in AMB not in AMB

14 54 43 24 135 56 80

13 49 38 21 121 51 70

231793.00 119121.91 103202.31 121528.64 126645.22 106598.75 141250.51

3.08 2.98 3.11 3.14 3.06 3.22 2.94

Total MSA population

Region

Total MSAs

MSAs on IHS

Average Shimbel

Average degree

Percent population change

Percent accessibility change

Percent degree change

224,845,240

West South Midwest Northeast Total in AMB not in AMB

48 122 69 35 274 76 198

42 100 65 34 241 72 169

432300.37 259558.76 230492.58 285134.93 1184.37 1014.11 1256.90

2.52 2.70 3.08 3.21 2.84 3.44 2.59

314.12 256.9 97.42 47.4 176.61 71.23 253.38

87.71 113.08 118.18 130.94 115.05 127.78 105.78

11.54 21.43 25.9 28.65 23.02 29.46 18.33

Table 4 Correlations results. 1950 Population 1950 Accessibility 2000 Accessibility Accessibility change

0.057 0.094 0.124

2000 Population 0.24 0.099 0.062

Change in population 0.314 0.278 0.39

1950 Degree 0.16 0.151 0.204

2000 Degree 0.172 0.21 0.2

Bold indicates significant at .01 level. Italics indicates significant at .05 level.

the network (Kwan and Weber, 2003). Places with a lower aggregate distance to all other places are more accessible (the other locations can be reached with less total travel). This measure was first used in geography to examine the topological structure of a portion of the early Interstate system (Garrison, 1960) and is appropriate for this network because it focuses on discrete network locations. Metropolitan areas were a focus of the original network and are appropriate origins and destinations for travel (Garrison, 1960). It is common to examine the accessibility of a transport system at different points in time using this measure (for example, Gauthier, 1968; Murayama, 1994; Wang et al., 2009). In such studies accessibility will change under a variety of conditions, including new (or fewer) links offering shortcuts, a reduction in mileage or travel time over one or more links, and if MSAs are added or removed. If improvements are added evenly throughout the network then percent accessibility change will be evenly distributed among all nodes. If not, then areas with the greatest percent change will show where the network has been most improved. However, the use of topological accessibility is relatively limited in these

circumstances, and there are only a few questions that can be asked: what places are most/least accessible at each point in time; what places have gained the most or least accessibility; and has overall variation increased or decreased? These questions have been addressed for large networks by a number of studies. Murayama (1994) examined topological accessibility change for the Japanese railroad system for up to 59 cities at six periods between 1898 and 1990. Because of scheduled services, travel times were available for each year. Accessibility changes were the result of new lines opened and changes in travel times along existing lines. Not surprisingly, centrally located cities possessed higher accessibility than peripheral cities at all periods. However, the opening of high-speed lines to the west of Tokyo meant that cities in that direction increased in accessibility more than others. The variation in accessibility between Tokyo and peripheral cities also decreased over time due to increased highspeed service throughout the country (though there are increased differences between cities on and off the high-speed lines). Wang et al. (2009) carried out a similar analysis for the Chinese railroad system for 330 cities at four time periods between 1911 and 2000.

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J. Weber / Journal of Transport Geography 25 (2012) 70–86

Accessibility changes were the result of new lines opened and changes in travel times along existing lines. The most accessible cities shifted southwards over time, with the result that ‘‘The network center had shifted from Tianjin to Zhengzhou by 1957 and has stayed there ever since’’ (Wang et al., 2009, p. 775). Li and Shum (2001) measured accessibility for 31 cities for the Chinese National Expressway Network Plan of China for 1990, 2000, and 2020. This will be a 85,000 km (52,817 mile) freeway system, and is the Chinese equivalent of the Interstate System, though it has been under construction only since the 1990s (Weber, 2011). They find that Zhengzhou is the most accessible place in each time period, which is to be expected as it is near the center of cities used in the study. Because they have three time periods they can compare accessibility change before and after 2000. The first period produced the greatest accessibility improvement but also aggravated regional disparities, particularly the east–west divide in the country. By the end of the second period accessibility scores have become more uniform as routes spread throughout the country. Because of this spread of route coverage, the large cities of eastern China were not always the ones with the greatest accessibility change. The far west and northeast show high improvements in the first period, reflecting the low level of access to this area before the freeways were built. To determine how the American freeway system has changed between the initial plan of 1947 and today’s network, accessibility was calculated in GIS for metropolitan areas on the original planned 1947 IHS network and for all connected freeways in 2000. The 2007 National Transportation Atlas Database (NTAD) highway network (Bureau of Transportation Statistics, 2007), which contains all major highways, was used as the basis for the 2000 freeway network. 2000 was used as the most recent time period as the definition of MSAs, and therefore their number and boundaries, changed considerably after that time. A network of Interstate and connected non-Interstate freeways in 2000 was extracted from this database. Very little GIS data are available to represent transport highway networks for time periods before the early 1990s, a severe limitation for understanding historical

change as networks have developed (Healey and Stamp, 2000). While the National Historical GIS database contains many boundaries for time periods as far back as 1790, there are no road themes available (National Historical Geographic Information System, 2010). The planned 1947 Interstate network was therefore created from the 2000 network by removing all Interstate routes not present in 1947. The 1947 routes are approximated by the location and mileage of current routes. Distance in kilometers was used for network length due to the difficulty of estimating travel times for 1947.

3. Accessibility change Despite the addition of routes and cities, accessibility patterns for 1947 and 2000 are very similar, with the lowest values (greatest accessibility) in the Midwest. Louisville had the highest accessibility in 1950, while St. Louis did in 2000. This is somewhat similar to the movement of the weighted center of U.S. population during the same time period (Fig. 3), which matches the expectation that the freeway network has adjusted to national population changes. However, neither the 1950 nor the 2000 MSA populations have a significant correlation with that year’s accessibility score, which is not surprising. Topological accessibility will show a positive correlation with population only if population is concentrated in the central part of the country, which does not describe the U.S. population distribution. Neither does it match that of Europe, where the most accessible cities are those located near the center of the distribution of cities, and the least accessible are located in peripheral areas such as Scotland, Spain, and Italy (Dupuy and Stransky, 1996). Patterns of accessibility change were mapped to see if the fastest growing areas of the country have seen the greatest improvement in accessibility (Fig. 5). In this study accessibility can only change if the network mileage between MSAs decreases due to the construction of new links. If these new links are added evenly throughout the network then accessibility change will be distributed

Fig. 5. Accessibility change by MSA, 1950–2000. Data source: Bureau of Transportation Statistics, 2007.

J. Weber / Journal of Transport Geography 25 (2012) 70–86

evenly. If they are concentrated in certain areas, MSAs adjacent to new routes will show the greatest improvement. In the case of the American freeway system it can be expected that rapidly growing areas would have the greatest improvements. However, the Midwest and Great Plains have had the greatest improvements in accessibility, though other cities have also had notable improvements. Many new Interstate connections were added in Illinois, Michigan, and in the Appalachians (particularly I-77 from Cleveland to South Carolina). In contrast, peripheral areas, such as the coasts and Southwest, often had the greatest population increase, despite the lowest accessibility change (Fig. 6). Similarly, although I-70 was extended westwards from Denver the benefits of this new highway are not reflected in Fig. 5 as the majority of cities in the accessibility analysis are located to the east of Denver. These patterns, however, are the opposite of those found for the National Trunk Highway System in China, where accessibility changes were often greatest in peripheral areas, though areas of greatest accessibility were found in the central part of the country (Li and Shum, 2001). Accessibility change has a weak negative correlation ( 0.390) with population change, indicating that cities with population increases did experience decreases in accessibility scores, meaning an improvement in accessibility (Table 4). However, as most cities had population increases, and network additions created some accessibility improvements everywhere, this is not surprising. Interestingly, the range and standard deviation of accessibility values increased from 1947 to 2000, indicating that the new routes have not helped reduce accessibility variations in the network, as was observed for Japanese and Chinese railroad networks. The accessibility results match the degree values for MSAs in showing that the additional routes added to the freeway network have favored the Northeast and Midwest. Degree values show a weak negative correlation with accessibility in 2000 (Table 4), indicating that cities with improvement in accessibility tend to have more routes serving them as well (though degree has no significant correlation with accessibility change). Changes to the Interstate System since it was first mapped in 1947 have increased

83

differences between the old AMB and the former periphery rather than reducing them. Network changes were also tested separately using the four Census regions (West, South, Midwest, and Northeast) (Table 3). While the Midwest region will show the best accessibility due to its location, it is interesting that the Northeast shows the greatest accessibility and degree improvement, with the West showing the least. The South has the lowest degree in 1950 but the West is lowest in 2000 (the Northeast is highest in both periods). If the West is represented by all states west of Missouri then western MSAs clearly have lower degree, change in degree, and accessibility change than eastern cities. However, the contrasts are not as extreme as that found between AMB and non-AMB cities. This latter division appears more fundamentally to describe spatial variations in network characteristics than do Census or other regional divisions, both for 1950 and 2000. It should be noted that these results do not take into account the large spatial scale of many of the Sunbelt MSAs. Larger MSAs such as Los Angeles cover a larger area than many eastern states, but their freeway system is ignored in this analysis because they are urban rather than intercity. Additional routes that were counted as interurban in the Midwest or Northeast would here likely be ignored as intraurban in this region. The results also reflect the spatial distribution of MSAs and underlying population patterns, as where there are more metro areas close together there are more possibilities for shortcuts that will improve accessibility.

4. Conclusions The Interstate Highway System has clearly changed since its inception in 1938, the first map in 1947, or the beginning of construction in 1956. The mileage of the IHS has grown by about 10% and the construction of many thousands more miles of identical freeways has resulted in a larger American freeway system. This growth has allowed for many new urban and rural routes,

Fig. 6. Population change by MSA, 1950–2000. Data source: Bureau of Transportation Statistics, 2007. Population data source: U.S. Census, 2012.

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and the spatial coverage of the network has been extended to allow many new MSAs to be connected. This has lowered connectivity but increased the MSA population served. The Interstate program has also changed tremendously in its goals, funding, environmental policies and administrative oversight over the decades, with the result that it can be said that there have been at least six different Interstate programs (Weiss, 2008). The first generation (‘Interstate 1.0’) was designed to build as many miles of basic freeway as quickly as possible (soon modified into a 1.1 version with better landscaping). This first generation of freeways provided the greatest economic return on the financial investment of the system (Nadiri and Mamuneas, 1996). A second generation IHS began to be implemented around 1970 with added safety and environmental features, while a 2.1 version allowed for transfer of Interstate funds to other routes and programs. In the 1980s and 1990s later generations included a focus on using Interstates as economic development tools and new rules on toll roads. These generations 3.0 and 4.0 have included many new routes and will likely be associated with considerable future expansion. It can certainly be expected that there will be additional Interstate programs (and geographies) in the future, as funding sources change and new issues arise. However, this research has shown that the IHS and the larger freeway network have not kept up with population shifts, and there is no correlation between accessibility change and population change. The hypothesis and expectation that the system has adapted to the enormous demographic and economic shifts of the past half century have not been supported. The greatest improvements have taken place in the densest part of the network, not where population or traffic growth has been greatest (and if changes in lane miles could be examined it is likely that this trend would be even more pronounced). It has therefore reinforced advantages held by places already well placed on the original 1947 network. While there are no available data on capacity, flows, or congestion going back to the 1940s, it may be that these areas had a greater need for an improved highway system than did more sparsely populated areas, at least in the early decades of the Interstate system. The use of the old AMB continues to provide an effective means for capturing regional variations in the national freeway network, though it has become the Rustbelt and is of declining importance within the country. The question of why the American freeway network has not kept pace with population change surely has its roots in the Interstate system having been created as a political compromise in Congress with a delicate balance of urban (largely Northeastern) and rural interests (Schwartz, 1976; Lewis, 1997). The distribution of federal funds for road building (not just for the Interstates, though with Interstates taking up a large share of the total) is also an inherently political process, and was until recently based on a formula that allocated money to states on the basis of their population, land area, and the mileage of postal routes (General Accounting Office, 1995). The use of postal route mileage to determine funds dates to 1916, when it was necessary to justify federal support for road building, and was outdated by legal changes in 1919. Population and area were included to balance between the needs of small densely populated states and large rural states. Road building has become an increasingly urban activity, making the use of land area less important. Nonetheless, during most of the Interstate era funds were allocated based on an antiquated compromise formula dating back almost a half century before Interstate construction even began. Considerable change has taken place on the Interstate and larger American freeway network since the conclusion of the study period in 2000. Seven MSAs have been connected to the system since then, and many others will likely be added in the next decade. The connectivity and accessibility of numerous cities currently

on the network will be greatly affected by planned routes such as I22, I-49, I-69, I-73, and I-74 (assuming these routes are actually built). I-69 could connect the McAllen and Brownsville MSAs, with over 1.1 million people, to the Interstate system. These routes would increase the connectivity and accessibility of eastern cities, reinforcing patterns already observed, but would have little impact on western cities. Interestingly, there is evidence that these new routes may be of greater interest to rural and small-town populations than metropolitan areas, which may be more interested in adding capacity, reducing congestion, or constructing transit or other rail projects than building new highways (Dellinger, 2010). And, while the early Interstate era was steeped in the language of national defense, recent projects are more likely to draw on NAFTA and its promise of economic transformations for justification (Dellinger, 2010). The actual relationship of the system to either goal was and remains vague. Other future intercity freeway routes are possible and likely, and could have greater impacts on the network. The lack of a direct freeway link between Phoenix and Las Vegas has been blamed on the dated planning for the Interstate system (Brookings Institution, 2008a). These two metro areas had 4,364,094 and 2,141,893 people in 2009, respectively, and are only 462 highway kilometers (287 miles) apart. In 1950 the Phoenix metro area had only 331,770 people, Las Vegas was not an MSA but a city of only 24,624, and the current main road between them had not yet been built. This main road is now being upgraded to a freeway, and officials in both cities have called for it to become an Interstate highway (settling unofficially on I-11) (Velotta, 2010). In contrast, Pittsburgh and Philadelphia are about the same distance apart but together contained 5,885,700 people in 1950 and were connected by freeway in 1940 even before the IHS was created. Kansas City and St. Louis are about 64 km (40 miles) closer together and had 2,495,800 people in 1950. I-70 between them was the ‘‘first interstate project to be awarded and to start construction after the signing of the 1956 act’’ (Weingroff, 2010). There will likely be many such situations in coming decades as population growth creates demand for better highway connections. Many of these will likely be excellent corridors for high speed rail projects, providing competition for new Interstate routes (Hagler and Todorovich, 2009). Several recent reports have called for significant changes to U.S. transportation policy and planning, with a new national vision for transportation. Future transport policy should acknowledge metropolitan areas as the location for the majority of the country’s population and economic activity. Sustainable mobility within metropolitan areas is now the predominant challenge, rather than that of movement across the country, as was the case in the 1940s and 1950s. A one-size-fits-all approach to the nation’s transport needs (as the IHS represented) is no longer workable, and standards and solutions should be geographically tailored to the needs of different areas. A seamless multimodal transport system is necessary, allowing more options for movement between and within cities. The American freeway system is a crucial part of these plans, though its role in a future nationwide multimodal transport system remains to be decided. One report calls for a near doubling of capacity of the American freeway system to meet the needs of the next 50 years, including 16,093 km (10,000) miles of new freeway, 32,187 km (20,000 miles) of upgrades from existing primary road to freeway, and 32,187 added lane-kilometers (20,000 lane-miles) on existing routes (American Association of State Highway and Transportation Officials, 2007). Another report calls for 24,140 new route kilometers (15,000 route miles) and 142,588 new lane kilometers (88,600 lane-miles) to be added to existing routes (PB Consult, Inc., 2007). Both emphasize how the country has changed since the inception of the freeway era and the importance of

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continuing to adapt to the current geography and future transformations. This includes the need to ‘‘extend the existing Interstate System to regions and resources currently not served at Interstate standards, including a range of significant urban areas and destinations that have emerged since the Interstate was designated over fifty years ago’’ (PB Consult, Inc., 2007, p. v). This report calls for places to have the same freeway access as older metropolitan areas, but this research has shown that more recently connected areas are likely to be on spurs and not serve as junctions for several routes. Northeastern cities would likely receive the greatest accessibility improvements if these expansions were to take place. However, another report (Brookings Institution, 2008b, p. 58) suggests the identification ‘‘of those portions of the interstate system that, because of employment and residential decentralization, no longer serve central transportation goals and are capable of being decommissioned or downsized.’’ I-81 in central Syracuse was identified as an example. In this case, accessibility or connectivity of cities on the American freeway network may go down, but it appears likely that most impacts would be within cities rather than among them. In 1938 American passenger railroads were near their peak, aviation was still of limited use, and highway construction appeared to have no limits. Today a new national transportation vision is needed to address the ‘‘triple crises of our congested highways, the outmoded aviation system, and the inadequate passenger rail network’’ (Brookings Institution, 2008a, p. 61). Other issues the Interstates and the American freeway system will have to respond to include a lack of funds, as money available from the Highway Trust Fund has not kept pace with construction costs. This problem has its roots as far back as the 1960s (Taylor, 1995) but has become acute in recent years. Many states have begun to seek alternative funding for their freeways, including tolls, bonds, sales tax, and property taxes (Weber, 2011). These arrangements will likely lead to considerable variation among states in future freeway construction. Maintenance costs are a growing concern, as evidence continues to mount that roads and bridges are not being adequately maintained (LePatner, 2010). A longer term challenge to Interstates and connected routes is that of climate change (Koetse and Rietveld, 2009). While there are tremendous uncertainties in this, it has already been found that freeways will be vulnerable to sea level increases at numerous locations along the East coast (ICF, 2008). The system has already proven vulnerable to storms along the Gulf Coast, and these problems point to another source of increasing geographic variation in the American freeway system.

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