Data Sources, Software, and Techniques Documentation

The Association of Bay Area Governments (ABAG), the regional planning agency for the nine counties surrounding San Francisco Bay, biannually releases estimates of demographic and economic conditions for areas ranging from the region down to census tracts. These projections are based on a host of assumptions and inputs described in detail in ABAG's Projections 98 report. These inputs include estimates of "...national economic growth conditions, the relative competitiveness of the region's economy, and the ability of the region's land supply to support managed growth" (ABAG, Projections 98, p. 2).

Extensive information regarding ABAG's latest Projections data is available at the URL http://www.abag/overview/pub/p2000/.

Note that the smaller the area, the lower the probability of the projections actually occurring, with subcounty and especially census tract projections being "...inherently more susceptible to uncertainty." (ABAG, Projections 98, p 3.)

These density maps were prepared by dividing the ABAG census tract data by the census tract area within ESRI's Arc View GIS program. Separate maps were prepared at 5-year intervals for the period 1990 to 2020. For the detailed maps showing the job densities of the San Francisco Bay region in 1990, 1995, and 2000, along with projections for 2005 through 2020, see CD-ROM file sfb_JD9022LR. For information about population densities in the Bay Area in 1990, 1995, and 2000, along with projections for 2005 through 2020, see CD-ROM file SFB_PD9022LR.

Population and Jobs Within a Half Mile of East Bay BART Stations (Project Overview 18)

Characteristics

This view shows the estimated number of residents and jobs within a half mile of East Bay BART stations in 2000, along with census tract population densities.

 

Population, Employed Residents, and Jobs Within 1/2 Mile of East Bay BART Station

The embedded bar charts shown at each BART station site have a scalar bar on the left with a height representing 5,000 residents or jobs. The central bar shows the number of residents and the right bar the number of jobs. If both bars are above the left 5,000 scale, then the sum of more then 10,000 workers or residents indicates likely viable transit support levels for local businesses with at least some pedestrian orientation.

Possible Applications

The year 2020 estimates could be used to determine which areas not above the threshold level in 2000 are expected to reach the transit-viability threshold level by 2020. Then attention can be given to the years in between and consideration given to site-specific developments that would help supply the transit-viable threshold levels and beyond.

One-mile buffers could be used to estimate population and workers within the extended walking and easy bicycling distance range, and quarter-mile buffers could be used to estimate jobs and population within easy walking distance.

Two-mile radii could be used to estimate data for the moderate bicycling distance area. In Tokyo thousands of bicycles are taken daily to many in-town rail stations, a pattern that could be repeated in California, which has a milder climate, better suited for bicycling.

Data Sources, Software, and Techniques Documentation

Using an Arc View Avenue program script written by Professor Richard Taketa for this project, the proportions of census tract areas inside and outside the half-mile buffers constructed around East Bay BART stations were calculated and used to estimate the proportion of the area of each census tract that was within the walking-distance buffer.

ABAG Projections 98 census tract data were used. Assuming that population and jobs were uniformly distributed across the census tracts, estimates of the numbers of residents and jobs in all tract areas within each buffer were calculated and summed, yielding estimates of the number of jobs and residents within a half-mile walking distance of each East Bay BART station in 2000.

A circular area a half mile in radius has an area of about three-fourths of a square mile. As 15,000 residents per square mile is a rough threshold for support of good transit service, the levels of residents alone within the buffer areas to support good transit would be 11,250. Assuming that jobs in an area had at least a similar effect on transit viability as residents, a combination of more than 10,000 residents and jobs within the transit half-mile buffer would indicate transit viability. The initial version of this map was constructed in three hours using the ABAG Projections 98 data, the Arc View GIS mapping program, and the program script by Professor Taketa. The final presentation map was refined with PageMaker software. One difficult task was to enlarge the downtown Oakland area while keeping the chart bars at the same scale as in the main body of the map.

What Project Overview 18 Shows

Most of the BART station areas from Richmond to Hayward are close to the viable-transit threshold, with the Berkeley and downtown Oakland station areas well above the threshold level. However, outside of central Oakland and Berkeley, only the area north of the Fruitvale BART station indicates sufficient residential density to support strong transit.

Project Overview 19

Characteristics

This view presents a table outlining types of criteria, standards, or norms that could be applied to envisioning measurements before undertaking an action. Each criteria, standard, or norm is linked to at least one possible application as an indication of some of the ways in which the Envisioning Neighborhoods outputs of small multiple replicate maps, charts, images, and tables could be effectively used to take action regarding neighborhoods or places.

Possible Applications

Taking action with regard to neighborhoods or places could entail simply deciding that the neighborhood did or did not merit further consideration or study.

Direct actions could include developers deciding to seek a site in the area, governments deciding to declare the area a place with high TOD potential within which special benefits and programs would be available, or prospective tenants (both commercial and residential) deciding to relocate within the area.

The application of criteria, standards, or norms to Envisioning Neighborhoods output can be undertaken in several ways, depending on circumstances. If only a single necessary and sufficient condition were present, such as to whether or not an area has been classified, an indication of whether that condition has been satisfied should be given central prominence in the Envisioning Neighborhoods summary view.

While Envisioning Neighborhoods summary views can be customized for particular applications, in many instances they will be fairly generic. In many cases, however, the criteria, standards, or norms for actions will vary and will be specific to the circumstances and perspectives of the actor. For this reason, this project has emphasized preparation of the generic envisioning views; however, the specific criteria standards can be invaluable in facilitating development when these standards are incorporated into the analysis, in many cases as overlays to the envisioning screens.

Summary OVerview of Study Areas

The transit centers chosen for creating prototype examples are oriented around rail transit stops, with two being at BART heavy rail stops in the East Bay region (Hayward, and the Fruitvale stop in Oakland); two at CalTrain heavy rail stops in the Peninsula region between San Francisco and San Jose (Redwood City and Mountain View); and three at light rail transit (LRT) stops (the Mountain View stop and the future downtown Campbell stop in Santa Clara County, and the 65th Street stop in Sacramento County).

Four of the transit centers include the downtowns of small to medium-large cities. All were farm market centers during their formative years. The Redwood City and Mountain View centers were on the commuter steam rail line built between San Francisco and San Jose in the 1860s. Redwood City and Hayward are the county seats of large urban counties, with from half a million to more than a million residents. See Appendix B, "History of Transit-Oriented Development, for additional details.

Envisioning the Forthcoming Downtown Campbell LRT Station TOD Potential

Campbell is a city of approximately 38,000 people seven miles southwest of downtown San Jose, in Santa Clara County, California. This study, prepared by Scott Plambaeck, concentrates on the future downtown Campbell light rail station (see CD-ROM file C_Sum for a complete PowerPoint presentation). The extension of the VTA light rail line from downtown San Jose to downtown Campbell, known as the Vasona Line, is expected to be completed in 2004.

The three block groups in downtown Campbell are studied and compared to Santa Clara County and the state of California. The future downtown Campbell station will be located in an area with low population density, as downtown Campbell is mainly a commercial center of small shops and restaurants. The ethnic balance of the downtown Campbell block groups is mainly white, contrasting greatly with Santa Clara County and the state of California as a whole.

This study lists seven types of businesses within walking and bicycling distance of downtown Campbell. Block group information also is provided, showing the number of Hispanics in the downtown area and the population density of the downtown Campbell vicinity. Features mapped include flood plains and downtown area restaurants.

This overview only suggests the procedures that could be used for envisioning. A full envisioning would require more data, with the 2000 census undoubtedly offering a wealth of additional information. The Campbell maps included in this publication were created using 1990 data from the U.S. Census Bureau.

Campbell's downtown core is enjoying a revival as coffee shops, restaurants, and small businesses thrive in this unique and charming downtown. New housing has been built within a quarter mile of the station site and more is planned. The downtown station will be close to several well-established neighborhoods.

 

Campbell Summaries 1 and 2

 

Campbell Summaries 3 and 4

The PowerPoint presentation includes the following information:

Campbell Summary 1 (See Campbell Summaries 1 and 2, left side) shows downtown Campbell from a local, city, county, and state view. The local walking view shows the future downtown Campbell LRT station and the half-mile vicinity around the station. This station is the focus of the Campbell study, and the map identifies all the local streets within a half-mile of downtown Campbell as well as the downtown block groups. The city view shows the entire city of Campbell and the planned LRT stations of the Vasona LRT line. The line, expected to be finished by December 2004, will connect Campbell to the Guadalupe LRT line in downtown San Jose and thousands of jobs in north San Jose, Milpitas, Santa Clara, Sunnyvale, and Mountain View. All the streets of Campbell are shown in the city view, but only the major streets are identified.

The county view shows the city of Campbell as it relates to the entire county and shows the county's highways. Campbell, primarily a bedroom community, is a mature suburb, located 7 miles southwest of downtown San Jose. The state view shows the nine Bay Area counties within the state of California. Santa Clara County is shown in green in the digital color version of Campbell Summary 1.

Campbell Summaries 2, 3, and 4 (See Campbell Summaries 1 and 2, right side and See Campbell Summaries 3 and 4) show age , race and ethnic background . They compare ethnic breakdowns in the state of California, Santa Clara County, and the city of Campbell, and compare them to the three downtown Campbell block groups. They also detail the census block groups via a digital ortho photo (DOP) of Campbell obtained from the Web site www.badger.parl.com. Major streets and the location of the future LRT station and VTA Vasona LRT line are included.

Campbell has a larger percentage of whites than Santa Clara County or the state. Block Group 3 in Census Tract 5056.02 is almost 100 percent white, an infrequent situation the Bay Area. Agewise, the three downtown block groups have a lower population than the city, county, or state of those under 19, but a larger percentage of those in the 19-29 range. Block Group 2 in Census Tract 5065.02 has a large population of those aged 30 to 49. Block Group 3 has the most extreme numbers, with a high percentage of those 65 and over and virtually no population under age 19.

Looking at age is important for TOD for several reasons. Seniors tend to ride transit more than other age groups, and it is important to determine the needs of the prime working-age population, ages 18 to 64.

Campbell Summary 5, Downtown Campbell's Future LRT Station Area, shows Campbell within Santa Clara County and the highways within the county (See Campbell Summaries 5 and 6, left side). The map on the top right shows the restaurants within a half mile of the future LRT station. The restaurants are represented by blue dots. The bottom map presents the density per square kilometer measured at the block level. Blocks with the highest densities tend to be further from the station but within walking distance. Sufficient density is essential in supporting TOD.

Campbell Summaries 5 and 6

The lower right map shows the blocks and the local streets of downtown Campbell and the location of the future downtown Campbell station. The half-mile buffer indicates neighborhoods within walking distance of the station.

Campbell Summary 6, Campbell's Restaurants, goes into more detail regarding restaurants in Campbell (See Campbell Summaries 5 and 6, right side). Using the data from Powerfinder Phone Disc 98, Info USA.com, Inc., two maps were created showing restaurants in the entire city of Campbell and restaurants within one-half mile of the future downtown LRT station. These maps show that most of the restaurants in Campbell are clustered near downtown. The city-level map shows that many of the restaurants in Campbell will be served by the Vasona LRT line.

The second, more detailed, map provides the names of the downtown restaurants. Restaurants are a popular destination for people, and locating stations near restaurants and other entertainment facilities is important in attracting people to ride transit.

Campbell Summary 7, Flood Zones, maps the 100-year flood zones in Campbell used to determine building sites (See Campbell Summaries 7 and 8, left side). It includes a citywide map of Campbell, and a map showing flood zones near the downtown station and population block density per square mile in Campbell.

Campbell Summaries 7 and 8

Campbell Summary 8, Businesses Within Walking and Biking Distance, is a series of eight interactive maps broken into seven broad categories (See Campbell Summaries 7 and 8, right side). The digital version of Campbell Summary 8 provides access to 16 full-screen maps at one-half or two-mile levels. The one-half-mile maps show the walking distance from the future downtown Campbell station.

Including the location and types of businesses is essential in studying sites suitable for TOD. In addition to building mass transit near housing, mass transit needs to go places that people want and need to go to. The Pruneyard Shopping Center, a major shopping center in Campbell, is shown on the map. Although the Pruneyard is outside the half-mile circle, it is less that 1 mile from the downtown station site and is a major retail and employment center in Campbell.

Two miles is considered the biking distance from the future downtown station. Since Campbell is geographically small, portions of San Jose are included in the bicycling distance map. Much of the Vasona Line, which will connect Campbell to downtown San Jose, is shown.

The seven business categories shown in Campbell Summary 8 comprise the following types of businesses:

Business and other retail, including book, copy, gift, and photo finishing shops, along with variety and video stores.

Food, including bakeries, candy and nut shops, coffee and tea shops, grocers, restaurants, and health foods.

Health, including dentists, drugstores, hospitals within 2 and 5 miles, nursing homes, and physicians.

Professional services, including accountants, banks, insurance agents, and attorneys.

Personal care and grooming, consisting of barbers, beauty salons, child care, nursery schools, dry cleaners, laundromats, nail salons, and physical fitness facilities.

Special concerns -- businesses that could cause problems -- includes bars, gunsmiths, liquor stores, and pawnbrokers.

Travel, including auto repair, auto rental, bike repair, service stations, motel and hotels, and travel agents.

Additional information on Campbell's TOD potential can be found in the following CD-ROM files:

C_Bus_Maps includes information on Campbell's businesses within walking and bicycling distance of the future downtown Campbell LRT station, and specific information regarding the seven business categories located within one-half and 2 miles from the LRT station.

C_DriveTime includes information on population residing within 5 and 15 minutes driving times of the future Campbell LRT station.

C_Pop_Housing&Hispanics contains information about Campbell's Households, Hispanic Population and Block Group Z-Scores, Hispanic Household Population Density per Sq. Mile and Block Group Proportions, and Hispanics 0.25 and 0.5 Miles From the Future LRT Station, using 1990 data.

C_WalkingTime includes information regarding population residing within 5 to 25 minutes walking time of the Campbell LRT station.

C_Zon&LU includes land use and zoning information for the area around the Campbell LRT station.

Envisioning the Fruitvale BART Station Vicinity

This chapter presents work concerning the neighborhood surrounding the Fruitvale BART station in Oakland, California. The station area is the site of a mixed-use transit village being built on an existing parking lot by The Unity Council, a nonprofit community development corporation. This $50 million multiuse project began construction in 2000.

This overview provides techniques that could be used to provide information to potential developers, who could use it to reach decisions as to whether this area has potential for them. Some of the information presented here might also be used in detailed presentations provided to facilitate choice of specific sites and choice of the scale and nature of possible developments. This presentation, which is oriented toward planners and developers, can be modified and used by persons considering renting or buying a residence or business site in the area. The Fruitvale BART PowerPoint presentation file is f_sum. Tara Kelly was the Fruitvale BART Station area research leader responsible for producing the materials for this area. The information is presented and described below.

Fruitvale Summary 1, Fruitvale BART Locational Contexts, places the Fruitvale BART station within its spatial context, showing the 10-block groups surrounding the station, the city of Oakland, and the five nearest counties in surrounding San Francisco Bay (See Fruitvale Summaries 1 and 2, left side). The digital data files for the areas were provided by ESRI, and the BART transit line shapes were provided by the Association of Bay Area Governments (ABAG).

Fruitvale Summaries 1 and 2

Fruitvale Summary 2, Walking Time to Fruitvale BART, shows the areas within 5, 10, 15, 20, and 25 minutes walking time, at a pace averaging 2 miles an hour following local roads (See Fruitvale Summaries 1 and 2, right side). This digital view also presents the number of residents within these walking times. Walking time maps will be of particular interest to parties concerned with developing or operating businesses relying, at least in part, on customers residing within walking distance.

U.S. Census block data were used for the population estimates, with ESRI's Network Analyst Extension to ArcView GIS used to determine the walking times areas. The digital streets file from ESRI was used to simulate the roads network.

This map, based on 1990 census data, estimates that 554 persons reside within 5 minutes walking distance of the transit center; 1,537 persons live within 10 minutes; and so forth out to 10,763 persons residing within 25 minutes walking distance. This is sufficient density to provide strong support for public transit.

Fruitvale Summary 3, Census Tract Block Groups, is a digital ortho photograph (DOP) that was corrected to represent on-the-ground relationships and can be used interchangeably with maps (See Fruitvale Summaries 3 and 4, left side). DOPs are ideal for site analysis work, but should be used with a higher resolution than those provided for free on the Internet. The U.S. Geological Survey DOP was downloaded from http://bard.wr.usgs./bard/cog/sanfrancisco/oaklandeast/sw.cog.

Fruitvale Summaries 3 and 4

Fruitvale Summary 4, Hispanic/Latino Population in Fruitvale BART Area, is a choropleth map that was created in Arc View using 1990 census data (See Fruitvale Summaries 3 and 4, right side). This map depicts the proportion of each block group's population that is Hispanic (the predominant racial/ethnic group living in this area). The lowest block group was 40 percent Hispanic and the highest was 70-86 percent Hispanic.

Fruitvale Summary 5, Fruitvale Block Group Data, includes data from the 1990 census that compares the block groups within the study area to each other and to increasingly larger-scale areas of which they are a part. Bar charts depicting family income, age of residents, and family types are included in this file (See Fruitvale Summary 5).

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Fruitvale Summary 5

Fruitvale Summary 6, Fruitvale Area Z-Scores, includes further breakdowns of family incomes, median gross rents, single-family home values, and transportation via z-scores (standard deviations from county means) and a stacked bar chart showing proportions of housing structures with certain numbers of units (See Fruitvale Summary 6). In Block Groups 4072-2 and 4072-1, most buildings have 10 or more units. On the other hand, most of the structures in Block Groups 4061-3 and 4072-2 are single-family detached homes.

Fruitvale Summary 6

Several census data categories were chosen and z-scores calculated for the entire 10-block group area to show how it compares to the county. As can be seen, this area is lower income, has lower housing prices and rents, and has a higher percentage of public transit users than the county as a whole.

Fruitvale Summary 7, Area Transit, illustrates the areas of public transportation lines around the vicinity of the Fruitvale BART station (See Fruitvale Summaries 7 and 8, left side). Public transportation plays a major role in this area, with the Fruitvale station acting as a major transit center with a dozen Alameda-Contra Costa County (AC) Transit District buses stopping in front of the station. The 82 and 82L bus lines, which travel along International Boulevard, carry more than 22,000 passengers each day -- almost equal to the number of automobiles that travel on this road (26,000 per day). AC Transit's second-busiest line is the 40/40L, which runs along Foothill Boulevard. In addition, BART attracts riders from all over, including the Oakland Hills and Alameda.

Fruitvale Summaries 7 and 8

Fruitvale Summary 8, BART Vicinity Views, shows city and neighborhood structures near the Fruitvale BART station, including St. Elizabeth's Church, International Boulevard, and Las Bougainvilleas (See Fruitvale Summaries 7 and 8, right side).

Fruitvale Summary 9, Video Menu, in the digital version accesses digital video pan movie clips taken of entire blockfronts of the area (See Fruitvale Summaries 9 and 11, left side). It includes views from the BART platform toward 34th Avenue and International Boulevard, and 35th Avenue toward Fruitvale Avenue. The video pan shows underutilized land of the current surface parking lot, on which a mixed-use transit village will be built.

Fruitvale Summaries 9 and 11

Fruitvale Summary 10, Potential Future Development Sites in Fruitvale BART Vicinity , is not presented here. It can be viewed as screen 16 on CD-ROM file f_sum.ppt.

Fruitvale Summary 11, BART Transit Village, shows the architectural rendering of the exterior appearance of the Fruitvale Transit Village (See Fruitvale Summaries 9 and 11, right side). New development will include public service facilities, including a low-cost health clinic, library, senior center, subsidized child care, and a computer teaching/learning center; ground-floor retail shops and offices; and 47 housing units on upper floors. In the first phase, 20 percent of the housing units will have below-market rents. In the second phase, additional affordable housing will be built on the adjacent parking lot, with existing displaced parking spaces being moved to a new multilevel parking structure.

One major goal of the Fruitvale Transit Village project is to recapture lands underutilized as surface parking lots and redevelop that land to bring a variety of uses within close proximity to public transportation. It is hoped that this redevelopment will provide easy access to the public while encouraging transit use. Other goals of the project are to generate jobs for community residents and to capture sales revenue from the thousands of BART riders who travel from outside the immediate area, often transferring to and from the 12 local bus lines feeding this station. Project sponsors are also attracting resources to rehabilitate existing housing in the area for resale for low-income families, improve the streets and sidewalks, provide additional housing (especially affordable units), create a new center for local artists, and bring in new commercial development that complements existing businesses.

Additional information on the Fruitvale BART area can be found on the following CD-ROM files:

F_3D_access_F8 has information regarding the Fruitvale BART Station area profiles, including maps about street and accessibility profiles and physical terrain.

F_bikeD has demographic information on the Fruitvale area's most common businesses, area services, school maps, public school ratings, number of students, violent crimes statistics, and maps.

F_LU&ZON is a land-use diagram of the city of Oakland and gives zoning information of the walking-distance vicinity of the Fruitvale BART station.

F_Vicin4_videos are shots of the vicinity of the Fruitvale BART station, which were taken in September 1999.

Envisioning the Hayward City BART Station Vicinity

The summary PowerPoint presentation on the Hayward BART Station is available on CD-ROM file H_sum. Earl Bossard and Dali Zheng were joint project leaders responsible for developing the Hayward BART Station vicinity materials.

 

Hayward Summary 1

Hayward Summary 1 (Figure 17) displays four components that provide locational context for the Hayward BART Station vicinity. A digital ortho photograph (DOP) provides context for the area within walking distance of the Hayward BART station, while maps place this area within contexts of scale ranging from 2-mile bicycling distance to the nine-county region. The Major Streets Within Bicycling Distance of the Hayward BART Station map shows major streets, freeways, and BART lines within the 2-mile bicycling distance. The Alameda County in the San Francisco Bay Area map presents the county within the context of the nine Association of Bay Area Government counties. The BART & Hayward in Alameda County map shows rail connections within the context of the city of Hayward and counties of Alameda and San Francisco.

The summary views can help planners, developers, and analysts decide whether a place merits further consideration for TOD or other development. This view helps to establish the spatial context of the study area in the region and may be of most interest to those not familiar with the area.

The DOP was downloaded from the Internet, using a site specific to the SF Bay region. The U.S. Geological Survey provides DOPs on a national basis. Because of advances in technology, several commercial vendors offer satellite-sourced DOPs at prices far lower than for the custom photographs taken from airplanes, which were the norm until recently.

The street map is derived from the commercially available Streets CD-ROM provided by ESRI, Inc. The county boundary maps are derived from the maps available from ESRI or other providers. They are derivatives of the TIGER maps developed for the 1990 U.S. Census. At the scale shown, only the names of the major arterials and highways are displayed.

The DOP with outlines of the block groups within a one-half-mile walking distance of the Hayward BART station indicates that the area is developed with a grid of tree-lined streets, crossed by major streets and rail lines. One problem with the DOP used for this example is that it was taken several years previous and does not show TOD projects constructed during 1998-99 near the Hayward BART station.

The Major Streets Within Bicycling Distance of Hayward BART Station map shows two Interstate Highways passing within 2 miles of the BART station, I-880 (from San Jose to Oakland) and I-580 (from near Stockton to Oakland). Hayward is shown to be just south of a BART junction.

The BART & Hayward in Alameda County map shows that Hayward is on the main BART line running along the eastern side of San Francisco Bay to Oakland and San Francisco. Hayward is the county seat and is fairly central within Alameda County.

The Alameda County in the San Francisco Bay Area map shows Alameda County to occupy much of the East Bay, east of San Francisco and north of Santa Clara. This places Hayward within 30 miles of Oakland, San Jose, and Palo Alto, and less than an hour's BART ride from downtown San Francisco.

Hayward Summary 2, BART Station and Vicinity Scenes, presents photographs of eight scenes from the area referenced to the DOP (See Hayward Summaries 2 and 3, left side). These scenes can provide a quick qualitative feel for the nature of the area, providing a sense of the scale, age, and style of existing and proposed developments.

Hayward Summaries 2 and 3

The photos show that the BART station is elevated, with a busy set of feeder buses stopping between the station and city hall. Most of the existing downtown development consists of buildings one or two stories in height. Existing and planned TOD development in the vicinity of the BART station tend to be two to three stories in height.

Several vacant sites with TOD potential are in the vicinity, shown in the air photo in the bottom left of the view. More details are provided about existing and proposed TOD projects in this area in the detailed views for Hayward.

Hayward Summary 3, Population/Housing Characteristics of Study Area Block Groups, presents seven sets of stacked bar charts showing census data for the five block groups within walking distance of the BART station (See Hayward Summaries 2 and 3, right side). Data for increasingly larger areas are also shown, starting with the average for this area, and proceeding out to the city, county, and state. Each chart presents comparisons across space among the area block groups and across scale between these block groups and their larger city, county, and state entity.

Census data presented include the year the structure was built, gross rent, units in structure, rooms in housing units, family income, journey-to-work modes, and housing values. Analysts can compare block groups in the area and decide which, if any, have characteristics favoring what they wish to develop. Area characteristics can be used to determine what types of TOD might be most suitable for the area.

The comparisons across scale data will facilitate placing the area in context, while helping to understand local characteristics.

A comparison of the seven sets of stacked bar charts for five block groups within walking distance of the Hayward BART station reveals a surprising number of differences. In all block groups, 20 to 60 percent of the housing was built between 1980 and 1990; in three, about 20 percent of the housing was built before 1949. In terms of gross rents, Block Group 3 had far more low-rent housing (70 percent) than any of the others, which had 20 to 40 percent.

In Block Group 3, 60 percent of the buildings have 10 to 50 units, but three other block groups had less than 10 percent of their units in such large structures. The charts for rooms in housing units tell a similar story, with Block Group 3 having far more small (< four rooms) housing units.

As might be expected from its high proportions of low rents, small housing units, and multiple housing unit structures, Block Group 1 has far more lower-income families. The journey-to-work transportation mode data for Block Group 3 is surprising in that it has the highest percentage of workers who drive alone to work.

Comparison of the four right stacked bars in each set of charts reveals how the walking distance area (leftmost of the four right side bars) compares to its city (Hayward), county (Alameda), and the state of California.

Starting with the housing values in the bottom right set of bars, it is clear that this area has a considerably higher share of low-value housing units, and a much smaller share of high-value housing, than the county or state. Both this area and the city of Hayward have an insignificant share of high-value housing (>$500K). This area also has a greater share of the two lower-family-income groups and a lesser share of the higher-income groups than do the county or state. These charts help define the housing markets in this area and in the city of Hayward in context with the larger county market.

Hayward Summary 4, Population Density, Population and Jobs, Businesses, presents three types of figures -- a choropleth population density map of the area in the vicinity of the station; a street map of the area within walking distance with point locations for seven categories of businesses; and a pair of bar charts showing population and employment estimates from 2000 and 2020 for areas from 1 to 5 miles out from the station (See Hayward Summary 4).

 

Hayward Summary 4

Population density is a key determinant of transit viability and the likely success of TOD projects, so population density data will be of great interest to TOD developers. The animated population maps for the period 1990 to 2020 by 5-year intervals, found in the digital version, could be of considerable interest to many developers.

The side-by-side bars of population and employment totals from 1 to 5 miles out from the Hayward BART station could be of interest to commercial developers wishing to appeal to various broader or narrower markets. Potential developers of a grocery store may be interested in the residents within 1 mile, while developers of a specialty store may consider the area within 5 miles. The digital version of Hayward Summary 4 has links to seven full-page screens with estimates of population and jobs in 2000 and 2020.

The Businesses Within Walking Distance maps could be of interest to commercial developers who want to know the business mix of the area and investigate possible market niches. The business maps can also inform potential residents of the services and shopping opportunities within the vicinity. The digital version of Hayward Summary 4 has links to 16 business maps either within walking or bicycling distance.

In terms of population density, the 2010 map reveals some, but not extensive, areas with sufficient density to support viable transit.

The ring data charts indicate only moderate population growth is expected in the next 20 years for the areas within 2 miles of the transit center, but that more than 20 percent employment growth (102,000 to 124,000) can be expected over that period in the area within 5 miles of the transit center.

The business maps show a heavy concentration of activity east of the transit center, which could be expected in this downtown area of a city of 140,000. A and Mission Streets have considerable strip commercial developments.

Additional information regarding the Hayward TOD potential are located on the following CD-ROM files:

H_5MileR shows the 5-mile radius population and job charts, race and ethnic population maps, residents within 5- and 15-minute drives of the transit center, and population density data.

H_Bike has maps of Hayward, showing seven business types within bicycling distance of the Hayward BART station and population percentages of the various ethnic groups residing within bicycling distance of the station.

H_busroutes_www is a map of bus routes near the Hayward BART station, taken from the ABAG/MTC Web site.

H_DOP includes DOPs of the various block groups in the Hayward BART Station vicinity.

H_DOP_5mile_JPG is a DOP of the city of Hayward and vicinity.

H_F_PD9022 gives population density information regarding the Hayward area, using ABAG estimates for 1990, 1995, 2000, 2005, 2010, 2015, and 2020.

H_TOD_specs has additional information regarding the Hayward BART station vicinity, including specifications for redevelopment sites.

H_W_Scene has photographic scenes of the area around the Hayward BART station, including links to video clips, moving panorama views, and still panorama views.

H_Walk includes maps detailing population within various walking times to the Hayward BART station; businesses within walking distance of the BART station; land use and zoning information for the walking-distance vicinity of the BART station; and bar graphs for population and housing characteristics, family incomes, rents, housing values, and population percentages.

H_Zoning_LU contains land use and zoning information for the walking-distance vicinity of the Hayward BART Station.

Envisioning the Mountain View VTA/CalTrain Station Vicinity

Downtown Mountain View has perhaps the strongest TOD potential of any of the six areas examined in this study. The downtown Mountain View Transit Center not only has a station on the busy direct CalTrain line between San Francisco and San Jose, but also is the north terminal station for the Santa Clara County VTA LRT line, which passes many high-tech job sites on its way to downtown San Jose and then on to the Blossom Valley area of southern San Jose.

The Mountain View summary overview digital presentation consists of five screens, four of which were prepared by Tung Tran in the fall of 1999, and a fifth prepared by Pin-Yuan Wang during the summer and fall of 2000. The complete PowerPoint presentation can be found on CD-ROM file m_sum. A brief synopsis of the project follows.

Mountain View Summary 1, Travel Times from Transit Center, contains three maps placing the transit center in spatial context within the San Francisco Bay region and Santa Clara County, and showing the travel times via CalTrain from Mountain View to stations from San Francisco to Gilroy (See Mountain View Summaries 1 and 2, left side). A photo shows the station site before completion of the CalTrain and LRT stations in December 1999.

Mountain View Summaries 1 and 2

Mountain View Summary 2, Transit Center Vicinity Scenes, contains eight photos of downtown Mountain View and a digital ortho photo (DOP) overlaid with block group boundaries and references to locations of photographed areas. (See Mountain View Summaries 1 and 2, right side)

Mountain View Summary 3, Housing Mix and Five-Mile Radius Stats, presents four sets of charts showing the cumulative numbers of residents, households, employed residents, and jobs at distances from 1 to 5 miles from the transit center, along with a DOP showing downtown area block groups and housing statistics for these block groups and larger areas (See Mountain View Summary 3).

 

Mountain View Summary 3

Mountain View Summary 4, Housing and Population Stats for Walk Area, presents six sets of charts of census data for the nine area block groups and the city, county, and state (See Mountain View Summaries 4 and 5, left side).

Mountain View Summaries 4 and 5

Mountain View Summary 5, Businesses Within Walking and Bicycling Distance of Transit Center, presents eight maps showing seven categories of businesses within one-half and two miles of the transit center (See Mountain View Summaries 4 and 5, right side). In the digital version, these maps are linked to 16 full-screen views of these business locations.

Additional information about Mountain View's TOD potential can be found on the following CD-ROM files:

M_bus98W&B show maps detailing businesses within bicycling and walking distances of the Mountain View Transit Center.

MC_PopD20 has maps including the population density of the vicinity of the Campbell and Mountain View areas using estimates by ABAG for 1990 through 2020 at 5-year intervals.

MV_ZonLUDOP is a DOP of the Mountain View area, along with photos of the vicinity of the Mountain View Transit Center and land use and zoning information.

Envisioning the Redwood City CalTrain Station Vicinity

Downtown Redwood City has strong TOD potential. The downtown Redwood City transit center not only has a station on the busy direct CalTrain line between San Francisco and San Jose, but also has bus bays that service nearby high-tech job sites and residential neighborhoods. The Redwood City presentations consist of seven screens prepared by Pin-Yuan Wang, including three screens linked via thumbnail photos to a total of 12 short videos.

The CD-ROM file SM_Setting is a map of the San Francisco Bay that details Redwood City's location in the region.

The complete PowerPoint presentation for Envisioning the Redwood City CalTrain Station Vicinity is located on CD-ROM file R_Sum. The contents of this presentation follow.

Redwood City Summary 1, Transit Center Vicinity Scenes, contains five photos and three digital ortho photos (DOPs) of scenes in the vicinity of the transit center, along with the boundaries of the eight block groups within one-half mile of the CalTrain Station (See Redwood Summaries 1 and 2, left side).

Redwood Summaries 1 and 2

Redwood City Summary 2, Transit Center Vicinity Characteristics, includes four sets of charts showing the number of residents, households, employed residents, and jobs from 1 to 5 miles from the transit center, along with a map showing downtown area block groups and larger areas (See Redwood Summaries 1 and 2, right side). Another chart shows z-scores for 15 census measures for the average of the eight area block groups, allowing comparison of the area to Redwood City, San Mateo County, and the state of California.

Redwood City Summary 3, Travel Time to Other Stations, shows the travel times via CalTrain from Redwood City to stations from San Francisco to Gilroy, using both a map and table (See Redwood City Summaries 3 and 4, left side).

Redwood City Summaries 3 and 4

Redwood City Summary 4, Video Pans of Station Track Area and Shopping Center Parking Lot, presents four thumbnail photos that, in the digital version, are linked to short video pans of the area (See Redwood City Summaries 3 and 4, right side).

Redwood City Summary 5, More Station Area Video Pans, includes a dramatic short video of the approach of a CalTrain, including crossing sounds. (No miniature shown in printed report; this video is included in the digital version.)

Redwood City Summary 6, Video Pans of Bus Facility and Area South of Station, includes two video pans of the Franklin redevelopment site, which will offer residential TOD sites with good access to shopping, downtown businesses and services, and the transit center. (No miniature shown in printed report; videos are available only in the digital version.)

Redwood City Summary 7, Businesses Within Walking and Bicycling Distance of Transit Center, are maps showing seven categories of businesses within 2 miles of the transit center (See Redwood City Summary 7). These maps are linked to 16 full-screen views of those business locations, showing details for areas within one-half or 2 miles.

 

Redwood City Summary 7

Additional information about the TOD potential in Redwood City can be found in the following CD-ROM files:

R_Zon&DOP includes zoning information for the area within walking distance of the Redwood City Transit Center.

R_MV_PD9022 has maps showing population density by census tracts from Redwood City to Mountain View from 1990 through 2020 at 5-year intervals.

Envisioning the Sacramento 65th Street LRT Vicinity

The Sacramento 65th Street LRT station area has good TOD potential. This transit center not only has a station on the busy direct LRT line to downtown Sacramento but also has several bus bays that service the nearby California State University, Sacramento, campus and residential neighborhoods.

This summary presentation consists of three sets of maps and charts prepared by Andrea Subotic, including race and ethnic data from the Census 2000 pretest that was undertaken in Sacramento in 1998. It also includes multiple maps of the area at the census block group level. Maps and overviews are shown in See Sacramento Summaries 1 and 2, and age-related graphs are shown in See Sacramento Summaries 3 and 4.

Sacramento Summaries 1 and 2

Sacramento Summaries 3 and 4

Four pages present photo scenes and maps to overview the 65th Street Station vicinity. In the PowerPoint version, the transit center and vicinity scenes have links to three full-page screens of the summary.

The majority of the summary (pages 10-22) provides census maps and charts for the area within 1.5 miles of the transit center. Six sets of small multiple maps provide details of census data on age, family income, rooms in housing units, race/ethnic percentages, and means of transportation to work for block groups.

Stacked bar charts are provided for many of the 1990 census block group data, also including statistics for the city and county of Sacramento and state of California, to place the study area in context.

To view the PowerPoint presentation, select CD-ROM file S_Sum. The highlights of the file are presented below.

Seven categories of business within 1.5 miles of the 65th Street Transit Center are shown on a full-screen map, Businesses Within 1.5 Miles of the 65 th Street LRT Station in Sacramento.

Area Data for 1.5 Mile Radius of the Sacramento 65 th LRT Station Population and Housing Characteristics Menu provides a menu for block group maps, block group charts, and census block maps, all based on 1990 data.

Maps: State, County, City a nd 65th LRT Station place the 65th Street LRT station location in context of state, county, and city (shown in See Sacramento Summaries 1 and 2).

Transit Center and Vicinity Scenes shows photographs of the immediate area around the 65th Street LRT station (shown in See Sacramento Summaries 1 and 2).

65th Street LRT Station Area Map details the location of the LRT station in relationship to the California state University, Sacramento campus.

65th Street Study Area Block Groups shows the census boundaries created for the 1990 census. The map also shows light rail routes and major highways.

Age Characteristics at the 65th Street LRT Station, Sacramento by Census Block Group breaks down age demographics of the census block groups surrounding the 65th Street LRT Station.

Age 0-18 Block Group Map, 65th Street Station Area shows the percentage of residents under the age of 18.

Family Income in 1989 at the 65th Street LRT Station, Sacramento by Census Block Groups breaks down the income levels of families living near the LRT station.

Rooms in Housing Units at the 65th S treet LRT Station, Sacramento by Census Block Groups indicates the sizes of housing units near the LRT station.

Race/Ethnic Percentages at the 65th Street LRT Station, Sacramento by Census Block Groups shows the race/ethnic breakdown of the neighborhoods surrounding the 65th Street LRT Station.

Means of Transportation to Work at the 65th Street LRT Station, Sacramento by Census Block Group summarizes the modes of transportation used by residents near the LRT station.

Year Structure Built at the 65th Street LRT Station, Sacramento by Census Block Groups indicates the age of structures standing in the neighborhood around the 65th Street LRT Station.

Year Structure Built at the 65th Street LRT Station, Sacramento has bar charts comparing the age of structures near the 65th Street LRT Station to the remainder of Sacramento, Sacramento County, and the state of California.

Population and Age Characteristics at the 65th Street LRT Station, Sacramento has bar charts comparing the population and age characteristics of residents near the 65th Street LRT Station to the remainder of Sacramento, Sacramento County, and the state of California (shown in See Sacramento Summaries 3 and 4).

Family Income and Means of Transportation at the 65th Street LRT Station, Sacramento are bar charts comparing family incomes and means of transportation to and from work between the residents near the 65th Street LRT Station and the remainder of Sacramento, Sacramento County, and the state of California.

Means of Transportation to Work at the 65th LRT Station, Sacramento is a detailed graph that breaks down mode of transportation by census block group, including carpooling, driving alone, motorcycle, public transportation, and rail.

Rooms in Housing Units in Structure at the 65th Street LRT Station, Sacramento is a series of bar charts that break down the number of rooms per structure in the census block groups near the 65th Street LRT Station, and compares the number of rooms to the remainder of Sacramento, Sacramento County, and the state of California.

Race/Ethnic Percentages at the 65th Street LRT Station, Sacramento by Census Bloc, 1998 has graphs detailing the racial percentages of the neighborhood surrounding the 65th Street LRT Station, using 1998 data.

Race/Ethnic Percentages at the 65th Street LRT Station, Sacramento by Census Block, 1990 gives the same data as above but using 1990 data.

Businesses Within 1.5 Miles of the 65th Street LRT Station in Sacramento is a map with local businesses plotted in relationship to their location of the 65th Street LRT Station.

County or Regional Contexts

Envisioning the Regional Setting for Five TOD Study Areas in the San Francisco Bay Region presents a series of maps showing the regional setting for the five TOD study areas in Alameda, San Mateo, and Santa Clara counties. The "regional setting" is both broadly and narrowly construed, with the broad view looking at the nine counties constituting the Association of Bay Area Governments (ABAG) region, and the narrow view looking at the five counties nearest the study areas : San Francisco, San Mateo, Santa Clara, Alameda, and Contra Costa.

Regional Data

The regional data shown include rail transit routes; county boundaries; highways, commercial airports, and ferry terminals; 2000 and 2020 estimates of population, population density, and housing density; and 1990 census data regarding race, ethnicity, and family incomes.

Understanding the regional setting of areas with TOD potential is important because a significant proportion of activities in this region cross multiple counties, with journey-to-work trips often crossing county boundaries. Potential developers of residential TOD projects need to be aware of where the future residents of their projects may be working. TOD developers also need to be aware of how their project fits in with the general demographic patterns of the region.

All the population and housing estimates for 2000 and 2020 are based on ABAG's Projections '98 census tract data. The 1990 race/ethnicity and family income data source is the U.S. Census, as ABAG does not produce census-tract-level statistics for these measures. Highlights of the CD-ROM file TOD_Region are discussed below. Printed miniatures are shown here only for the Regional Settings and 2000/2020 Population slides.

Rail Transit and Five TOD Study Areas (TOD_Region, slide 1) shows that the study areas encircle San Francisco Bay, with Fruitvale, Hayward, Redwood City, and Mountain View having direct rail transit access to San Francisco (see See San Francisco Bay Region for Five TOD Study Areas.)

 

San Francisco Bay Region for Five TOD Study Areas

Highways, International Airports and Ferries (TOD_Region, slide 7) shows that Fruitvale has excellent access to the Oakland Airport. (Hayward has good access to the Oakland Airport.) Redwood City and Mountain View have direct access to the San Francisco Airport; Mountain View also has good access to the San Jose Airport. (The VTA Vasona Line extension to Campbell in 2004 [not shown] will connect to a station within a mile of the San Jose Airport.)

Population 2000 and 2020 (TOD_Region, slide 8) and San Francisco Bay Region Population Density (SFB_PD9022LR) show that in both 2000 and 2020 the densest population areas will be along the rail transit lines circling San Francisco Bay, with the largest concentrations of high population densities found in San Francisco and from Fruitvale north in Alameda County (this is the city of Oakland). (See See Population 2000 and 2020 Rail Transit and TOD Areas.)

 

Population 2000 and 2020 Rail Transit and TOD Areas

San Francisco Bay Region Age Over 64 Population and San Francisco Bay Region Age over 64 Population Density (TOD_Region, slides 11-14) show the increasing share and density of elderly population expected in the region during the next 20 years.

Modal Racial/Ethnic Group (TOD_Region, slides 17 -21) show areas where Blacks, Asians, Hispanics, or Whites are the most prevalent group, while other views show details for each of these groups.

Median Family Income (TOD_Region, slide 22) shows modest family incomes in the immediate vicinity of all TOD study areas; however, areas of very high incomes exist near the Redwood City, Mountain View, and Campbell TOD potential study areas.

County Context View Characteristics

The Alameda County Settings views present a series of maps for this large urban county, with a population of over a million persons, that place the Fruitvale BART and Hayward BART study sites in countywide context.

The county data include maps showing rail transit lines, the regional context of the county in the San Francisco Bay region, highways, subregional study areas (mostly cities), job data for census tracts and around BART stations, population and housing densities, and elderly population data, race/ethnic data, and family income data.

The county setting of TOD potential areas is important, because most of the residents in this county work and shop in this county; therefore, TOD developers should understand the county jobs, housing, and demographic patterns.

Alameda County TOD Study Sites (Al_Setting, slide 1) and Regional Context of the Fruitvale and Hayward BART Station Areas (Al_Setting, slide 5) show that both the Fruitvale and Hayward BART Station areas are located in the western part of Alameda County along the BART rail line running from Fremont to Oakland and San Francisco. (Slide 5 is shown in See Regional Context of the Fruitvale and Hayward BART Station Areas.)

Regional Context of the Fruitvale and Hayward BART Station Areas

Alameda County TOD Study Areas with Highways (Al_Setting, slide 6) shows that both Fruitvale and Hayward are in the I-880 corridor and both are not far from I-580. Hayward also is located on California Highway 92, which crosses the San Francisco Bay to the west going to the job-rich Silicon Valley area (see See Alameda County TOD Study Areas with Highways.)

Alameda County TOD Study Areas with Highways

Alameda County TOD Study Areas with ABAG Subregional Study Areas (Al_Setting, slide 7) shows that Fruitvale is in the west central area of Oakland, directly east of the City of Alameda. Hayward BART is in north central Hayward, with the city reaching from the unincorporated hills on the east to the bay on the west.

Alameda County TOD Study Areas and Jobs in 2000, Job Change 2000-2020 (Al_Setting, slide 8) shows that Fruitvale is located on the southern edge of the concentration of jobs in central Oakland, which is expected to grow considerably by 2020. Hayward has fewer jobs in its immediate vicinity, both in 2000 and 2020, but is directly west of the large concentration of job growth expected between 2000 and 2020 in the tri-valley area of Dublin and Pleasanton.

Population & Jobs Within 1/2 Mile of East Bay BART Stations (Al_Setting, slide 9) has a great deal of information, which is discussed in detail in the project overview section.

Population Density (Al_Setting, slides 10-11) reveal that although the Fruitvale vicinity has extensive areas with densities sufficient to support viable public transit, the Hayward BART vicinity, even in 2020, is expected to exhibit few census tracts with high densities.

Age Over 64 (Al_Setting, slides 12-15) show a considerable increase between 2000 and 2020 in tracts with more than 20 percent elderly population, but few of these increasingly elderly tracts are near the BART transit centers.

Modal Race/Ethnic (Al_Setting, slides 18-22), along with the full-page screens for each of the four race/ethnic categories, show that Fruitvale is a predominately Hispanic area, with a large Asian community to its immediate northwest and an even larger Black community to its north, east, and south.

Family Income (Al_Setting, slide 23) shows that Fruitvale is located within the largest low-income concentration in the county, while the Hayward BART vicinity is predominately low-middle income in character.

appendix a: Envisioning the Quality of Life and Context for Development in Neighborhoods with Transit-Oriented Development Potential

Abstract

The digital information revolution had provided an incredibly rich set of digital tools and data that can be utilized for envisioning quality of life in cities. We argue that quality of life (QOL) is a distinctly personal measure for each person, reflecting his or her values and culture, nested in a set of spatial relationships starting with home-related facilities that help satisfy residential needs, and include a hierarchy of neighborhood communities.

We suggest that QOL studies for persons and development sites should explore the context of their locations, looking at data for blocks, using a variety of neighborhood definitions in a regional setting.

This paper takes a second look at using digital tools and data to understand neighborhood conditions explored in ICQOLOC I by Bossard, this time utilizing data tools and sources not readily available only two years ago.

Digital tools explored include increasingly powerful computer hardware, digital cameras and camcorders, global positioning systems (GPS) and robust software to transform and model urban data. Digital data readily available on the Internet and CD-ROM now includes ortho photos, topographic maps, census data, school data, crime data, real estate listings and public transportation route maps and schedules.

The Envisioning Neighborhoods Technique (Bossard, 1998) is used for a case study evaluating the quality of life and context for development in neighborhoods with transit-oriented development potential. Detailed sets of multiple maps, charts and photos present neighborhood conditions, with quantitative aspects shown by multiple maps and charts, and qualitative aspects highlighted in photos, videos and digital ortho photos.

 

 

Introduction

America is undergoing an urban renaissance, with considerable interest in improving quality of life within its cities. This urban renaissance is accompanied by support within many areas for reconsideration of urban growth patterns and policies, paying increased attention to the diversity of residential lifestyle preferences.

The "new urbanism," "smart growth" and "sustainable communities" are names for movements developing in the USA reflecting one residential lifestyle preference which has been neglected under policies which promoted standardized, automobile-oriented, suburban housing tracts (Katz; Van der Ryn and Calthorpe). A key aspect of the New Urbanism movements is interest in integrating public transportation systems with well-planned, livable community developments having sufficient densities to support public transportation systems. Transit-Oriented Development (TOD) is the expression increasingly used to describe land use development specifically designed to take advantage of close proximity to good public transit.

TODs are distinguished from other urban settings by what Bernick and Cervero call the 3-Ds of density, diversity and design.

Density means "...having enough residents and workers within a reasonable walking distance of transit stations to generate ridership." Diversity implies "...a mixture of land uses, housing types, and ways of circulating...within the TOD area." Design includes "...physical features and site layouts that are conductive to walking, biking, and transit riding" (Bernick and Cervero, p. 73).

Although transit-oriented development has been advocated in the U.S. for years (Bernick and Cervero, Ch.1), it has yet to realize its full potential. The Envisioning Neighborhoods with Transit-Oriented Development project has been undertaken at San José State University under the sponsorship of the Mineta Transportation Institute to develop techniques for regional planning agencies, local governments and developers to screen, analyze, select and promote areas with TOD potential. In order to facilitate TOD site selection, socioeconomic, demographic, land use, transportation, design and other quality of life measures must all be considered in a spatial setting.

 

 

Appropriate Scales for Studying Urban QOL

What is the appropriate scale for studying urban QOL? While the QOLNET International website points out that there is presently no general agreement on the definition of quality of life, it suggest that nascent urban QOL studies have been generally carried out on the personal and city level (http://www.qolnet.nus.edu.sg/what.html).

We suggest that quality of life is ultimately a distinctly personal measure for each person, reflecting his or her values and culture, nested in a set of spatial relationships. These spatial relationships begin with a person's home, reaching out to home-related facilities that help satisfy residential needs, and include a nested hierarchy of neighborhood communities which may encompass school, shopping, recreation and service functions (see S. Brower, chapter 2, "Neighborhood Settings," for an elaboration of these concepts.)

Personal quality of life may also be a function of the way in which different elements of various neighborhood communities are mixed together in space. Kevin Lynch uses a concept called grain to categorize spatial mixes (Lynch, p. 265).

The grain of a mix is fine when like elements, or small clusters of them, such as members of the same economic or ethnic group, are widely dispersed among a variety of different economic or ethnic groups, and coarse when extensive areas of the same group are segregated from extensive areas of other groups. A grain is sharp when the transition from a cluster of like groups to its unlike neighbors is abrupt, and blurred if the transition is gradual. For Lynch, grain is simply a way of making explicit a spatial feature of cities which is often discussed and is variously referred to by such words as segregation, integration, diversity, purity, land-use mix or clustering. "In its many forms, grain is critical to the goodness of a place." (Lynch, p. 266).

Therefore QOL can be a function of the social, ethnic and economic mix in neighborhood areas as compared to their contextual surroundings. As personal QOL preferences for grain coarseness and sharpness may be quite varied, it is desirable to make available grain-related QOL information in a variety of forms, with aggregate census tract and block group data in maps, charts, and tables used to determine coarseness and census block data used to estimate fineness.

If QOL is a personal measure, but depends on a hierarchy of facilities encompassing one's residence, and various definitions of neighborhood, as well as the grain, or spatial mix of groups or elements one interacts with, then to understand QOL we must understand the spatial settings of urban components, starting with the smallest possible components (people, households, blocks, etc.) and moving out to encompass larger units such as clusters of blocks and other various conceptions of neighborhoods. Keith Devlin, in InfoSense--Turning Information into Knowledge, condenses his advice into one golden rule: context matters (Devlin, p. 201). This applies to urban QOL analysis in that spatial context is a very important component, especially in urban settings.

While the digital/communications revolution (W. Mitchell) has created vast amounts of personal and household data, this data is generally not uniformly available to researchers and is scattered among survey research firms, geo-marketers, utilities, real estate assessment officials and a wide variety of semi-autonomous public service providers and websites.

Therefore in the USA we usually start urban QOL analysis with readily accessible decennial census data, which provides more than 2,000 pieces of data for block group areas averaging 1,000 persons, and the same detailed information for census tracts averaging 4,000 persons, as well as for towns, cities, counties and states (Meyers).

While we would like to use as much personal data for individuals or households as possible, in many cases we are forced to use data for larger areal units, either block groups, census tracts or even cities. This may entail serious problems, identified by quantitative geographers as the modifiable areal unit problem (MAUP) (Wrigley, et. al., p. 23; Openshaw, chapter 4).

Social scientists see this as a manifestation of what they call the ecological fallacy. The ecological fallacy involves the inappropriate inference of individual-level relationships from areal-unit-level results. It arises, typically, when areal-unit data are the only source available to the researcher, but the objects of study are individual-level characteristics and relationships. Routine analysis of census area data in the formulation of policy responses to individual household-level sociological/medical problems of deprivation, deviance, morbidity, etc., is fraught with considerable ecological fallacy risks and must be viewed as highly suspect (Wrigley, et. al., p. 30).

To this we may add that QOL analysis based on citywide data has similar problems. While there is no easy, patent solution to the MAUP, often it can be dealt with by judicious selection of zone boundaries, or using the lowest possible level of aggregation. Therefore we suggest where possible, using block group rather than census tract or citywide data, and where citywide measures are desired, building them up from smaller area measures wherever possible. This is, however, a complex topic worthy of a detailed study of its own.

Our conclusion to the question, "What is the appropriate scale for studying urban QOL?" is to strive for a scale that best reflects people's varied preferences and includes substantial analysis at the neighborhood level. We believe that residences and development sites should be studied in their context, which means looking at data for blocks, block groups and combinations of block groups in the setting of the larger urban region. Therefore in studying urban QOL, we recommend that locations be studied in the context of their block, neighborhood, and the location of neighborhood relative to the spatial patterns of the region (Bossard, 1998).

Envisioning Neighborhoods as a Technique for Estimating QOL

An innovative technique, called Envisioning Neighborhoods (EN) is being used in the EN TOD project to determine, analyze and promote potential TOD sites. The EN TOD technique, being developed by Professor Bossard with the help of many others for this project (see acknowledgements), is building on the work done using census data to envision neighborhoods in California (Bossard and Tallam).

The EN technique enables decision-making regarding places by effectively bringing together information as multiple maps, charts and images. Pioneering EN applications, including a revised version of the presentation initially presented at ICQOLC 98, are available at URL http://www/transweb.sjsu.edu/bossard/census.html.

The EN TOD project is designing, documenting and applying techniques to envision the quality of life and contextual nature of potential TOD sites, particularly along light and heavy rail corridors in the San Francisco Bay region. Data screening techniques use 1990 census data, but are designed to facilitate use of year 2000 data. Digital ortho photos are being used to find and estimate available developable land. Geographical information systems (GIS) map analysis techniques are used to estimate population densities in rings around transit stops, as well as densities of potential riders, workers and customers with access to transit lines connected to transit centers with TOD potential. Understanding of TOD site potential is enhanced by multiple digital images of block fronts linked to digital video and to provide contextual relationships of structures, transit facilities and developable sites.

The EN TOD project is developing case studies with guidelines to enable regional planners, local governments and private developers to use the evolving tools of the digital communications revolution to screen, analyze, select, promote and develop sites with transit-oriented development potential. The process for using these tools will be explained in a step-by-step manner in the EN TOD project final report to facilitate adoption and emulation by local practitioners.

Case Study Example Envisioning the Fruitvale BART Station Vicinity

This example focuses on summary page views that envision neighborhoods with TOD potential and detailed neighborhood profiles including sets of maps, charts and digital images. Components of the summary page views and detailed neighborhood profiles are outlined in Figures 1 and 2. The project's summary page views and detailed profiles will be presented in several forms, including hardcopy paper versions, and digital versions distributed via CD-ROM and the Internet.

Reproduction cost constraints result in the paper versions being in black and white, while the digital versions, utilizing advances in digital technology, include color maps, charts, photos, and short video movies.

 

Figure 1-(CD File; Bk_EQOL, Slide 7)

 

Figure 2-(CD file: BK_EQOL, slide 8)

Presented here is preliminary work on the neighborhood surrounding the Fruitvale BART (Bay Area Rapid Transit) station in Oakland, California, USA. The station area is the site of a mixed-use transit village being built on an existing parking lot by a non-profit community development corporation named The Unity Council. This $50 million multi-use project began construction in 1999. New development will include public service facilities (low-cost health clinic, library, senior center, subsidized child care, and a computer/teaching learning center), ground floor retail shops, offices, and 47 housing units on upper floors. In this first phase, 20 percent of the housing units will have below-market rents. In the second phase, additional affordable housing will be built on the adjacent parking lot with existing displaced parking spaces being moved to a new multi-level parking structure.

One major goal of this project is to recapture lands underutilized as surface parking and redevelop that land to bring a variety of uses within close proximity of public transportation. It is hoped that this redevelopment will provide easy access to the public while encouraging transit use. Other goals of the Fruitvale Transit Village project are to generate jobs for community residents and to capture sales revenue from the thousands of BART riders who travel from outside the immediate area, often transferring to and from the 12 local bus lines feeding this station. Project sponsors are also attracting resources to rehabilitate existing housing in the area for resale to low-income families, improve the streets and sidewalks, provide additional housing (especially affordable units), create a new center for local artists, and bring in new commercial development which complements existing businesses. (Bernick and Cervero devote four pages to "Transit Village Redevelopment: The Case of Oakland's Fruitvale District," pp. 207-210.)

The preliminary materials in this paper present a work in progress towards the development of summary materials, which could be used by potential developers to reach decisions as to whether or not this area has potential for them. Some of the materials presented here may also be used in detailed materials provided to facilitate choice of specific sites and choice of the scale and nature of possible developments. These materials, which are oriented toward planners and developers, can eventually be modified and used by persons considering renting or buying a residence or business site in the area.

Summary Page Views Envisioning The Fruitvale BART Station Area

Listed below is a description of the tools and techniques that Tara Kelly used in creating Figures 3 and 4:

Figure 3- Location Maps for Fruitvale BART Station Vicinity (CD file: BK_EQOL, slide 11)

 

Figure 4-Digital Ortho Photos and Photos for Fruitvale BART Station Vicinity (CD file:F_Sum, slide 7)

These maps place the Fruitvale BART Station area within its spatial context, showing the ten block groups surrounding the station, the City of Oakland, and the five nearest counties in the Bay Area region, with a focus on Alameda County, the county the station is within. All of these maps were created in ArcView GIS 3.1 and imported into PowerPoint. Shape files for the areas were provided by ESRI and the BART transit line shape files were provided by the Association of Bay Area Governments (ABAG), the council of governments type organization for the nine-county San Francisco Bay Region. ABAG has a website that provides access to a wide variety of urban QOL data for its region. See URL: http://www.abag.org.

The choropleth map in the lower right hand corner was also created in ArcView using 1990 U.S. Census data. This map depicts the proportion of each block group's population that is Hispanic (the predominant racial/ethnic group living in this area). The lowest was 40 percent Hispanic and the highest was 70-76 percent. Figure 1 does not have room to include detailed maps, schedules, and other information regarding public transportation found on the Internet at: http://www.abag.org/abag/local_gov/transit.html.

Figure 4-Digital Ortho Photos and Photos for Fruitvale BART Station Vicinity (CD file:F_Sum, slide 7). The U.S. Geological Survey digital ortho photo used was downloaded for free from http://bard.wr.usgs./bard/cog/sanfrancisco/oaklandeast/sw.cog.

The ortho photograph was edited in Microsoft Word (using the "picture" toolbar functions) down to a smaller area surrounding BART. It was then modified (block group outlines added, etc.) using the Microsoft Word "drawing" function and imported to Microsoft PowerPoint. Because digital ortho photos have been corrected to represent on-the-ground relationships, they can be used interchangeably with maps. Ideally for site analysis work digital orthos with a higher resolution than those provided for free via the Internet should be used.

The other photos were taken with a standard 35mm camera, scanned into the computer and opened in Microsoft Word where they were edited using the "picture" tools. These were then imported into PowerPoint to create the full-page summary pageview presentation.

A new high-tech option, considered for taking photos for the project, but not adopted because of the current $2,000 cost, would be to use the Kodak DC265 Global Positioning System (GPS) Solution Kit, which enables users to take 1.6 million mega pixel resolution digital pictures, with the latitude and longitude embedded in the digital file to readily identify the location on digital maps and geo-referenced digital ortho photos. (See URL: http://www.kodak.com/IJS/en/store/catalog.)

Digital video pan movie clips were also taken of entire block fronts in the area with a Sony Mavica MVC-FD88 digital camera. The clips, originally stored on a floppy disk in the camera, can be accessed in PowerPoint by clicking on maps or photos in summary pageview presentations that can be accessed from the Internet or via CD-ROM disk. (See CD file: F_Sum, slide 15.)

Information on the camera is available at URL: http://www.sel.sony.com/SEL/ consumer/dimagin/.

Figures 5a and 5b - Stacked Bar Charts and Standard Bar Charts (CD file: BK_EQOL, slides 13-14)

The bar charts in these two figures were created using Microsoft Excel and imported into PowerPoint to create the full-page presentations. The stacked bar charts shown in Figure 5a were created using a template created by Dr. Bossard (Bossard, 1993) that standardized the process for creating charts linked to data tables, which could be changed. This data, from the 1990 U.S. Census, compares the block groups within the study area to each other and to increasingly larger scale areas they are a part of. The standard bar chart shown in Figure 5b was created using Microsoft Excel.

 

Figure 5a-Stacked Bar Charts and Standard Bar Chart (CD file: BK_EQOL, slide 13)

 

Figure5b - Stacked Bar Chart and Standard Bar Chart (CD file: BK_EQOL, slide 14)

These bar charts represent the percentage of students in each school who scored above the national average on standardized math and reading tests. The schools chosen are ones which are regularly attended by local Fruitvale children.

The state of California and Oakland Unified School District scores are also provided for comparison. From review of the bar chart, one can quickly see that most schools have far fewer students scoring above average than students in the state as a whole or even within the city of Oakland. One notable exception is Skyline High School, which is open to all Oakland students via a lottery system.

While these results, which were only available for public schools, depict a less than desirable school system for the local students, there are alternatives. St. Elizabeth's has its own private school system for K-12 which serves a large number of local students. In addition, as many as four new charter schools have been initiated in this neighborhood over the past couple of years.

Data is from the website for California's public schools at http://www.GreatSchools.net.

An immense amount of social, economic and environmental data regarding crime, real estate and the environment is becoming available on the Internet. Much of this data is well suited to QOL analysis and inclusion in the detailed views to be produced by the EN TOD project. For examples regarding environmental information see http://sfbay.wr.usgs.gov/, or http://www. fema.gov. For uniform crime report statistics by city see http: //www. ibi.gov/ucr.htm; for neighborhood and real estate information for the perspective of a person searching for a home see http://www.realtor.com/FindNeig/.

 

Figure 6a-Population by Rings for Fruitvale BART Area (CD file: BK_EQOL. Slide 16)

 

Figure 6b-Block Groups Within 1, 2 and 5 miles of Fruitvale BART Station (CD file: BK_EQOL. Slide 17).

Figures 6a and 6b were created using ArcView software and 1990 U.S. Census data, using a technique for drawing buffer zones at one, two, and five miles from the center point of the station. The rings were then overlaid over the block group maps linked to census data, and data for any block groups within those rings was captured and transferred to Microsoft Excel for editing and creating the bar chart. (See Andy Mitchell, "Chapter 5: Finding What's Inside," for an explanation regarding overlaying areas and features.)

 

Figure 7a-Housing Units in a Stacked Bar Chart; Figure 7b - Z-scores for Fruitvale TOD Areas (CD file: BK_EQOL, slide 18)

 

Figure 8-Fruitvale BART Station Area Year 2000 Profiles (CD file: BK_EQOL, slide 19)

Figure 7a was created in Microsoft Excel using the template created by Dr. Bossard. It provides both comparisons of the ten block groups in the Fruitvale BART area with one another, as well with the entire area, the city, county and the state. Figure 7b was created in Microsoft Excel using data from the 1990 U.S. Census Data. It was then pasted into PowerPoint along with Figure 7a. The column of data showing actual percentage comparisons was inserted as a text box in PowerPoint. These data help place Fruitvale BART area conditions in the context of the million residents of Alameda County.

Figure 7a: Stacked bar chart showing proportions of housing structures with a certain number of units. In Block Groups 4062-2 and 4072-1, most buildings have ten or more units. On the other hand, most of the structures in block groups 4061-3 and 4072-2 are single-family detached homes.

Figure 7b: Several census data categories were chosen and z-scores calculated for the entire ten-block group area to show how it compares to the county. This area is lower-income, has lower housing prices and rents, and has a higher percentage of public transit users than the county as a whole.

Listed below is a description of the innovative tools and techniques that Shyamala Raveendran considered or used in creating Figure 8. Her goal is to demonstrate how a variety of 3-D visualization tools can be used to understand actual and theoretical spatial patterns.

The Accessibility to Jobs Minus Employed Residence 2000 map is based on a gravity spatial interaction model (Bossard, 1998) showing the relative access in the entire county to the difference between the number of workers working and the number of workers living in census tracts. This measure provides an innovative estimate of the relative access to housing demand, where housing demand is based on good access to one's workplace. According to this measure, the darker the areas on the map, the stronger the housing demand. This map was done using ArcView 3. 1.

The "Streets and Accessibility@ Profile Locations..." street map, also done with ArcView, shows the location of the Fruitvale BART Station, the streets in its vicinity, and the location of North-South and East-West profiles which were cut through the "3-D Images of Accessibility" described below.

The 3D "Accessibility to JNER2000" maps were done with ArcView - 3D Analyst Extension. The respective 2D themes were converted to 3D themes by using "Accessibility to JUER2000" attribute values as the z-value (height). The maps were then viewed in the "3D Scene" dialogue. Next, they were positioned to a desired perspective. The perspective was then exported as a JPEG image file-hence the image as seen on the layout. These 3-D images show the high potential strength of housing demand in the downtown Oakland area northwest of the station.

The 3D N-S and E-W profiles of Accessibility to Jobs Minus Employed Residents 2000, shown in the bottom left comer of Figure 8, were also done with ArcView-3D Analyst. First, a line was drawn on the 3D thematic map in a "View." Next, the "Profile Line" tool sketched a "Visibility Profile" line graph of the map in a "Layout." These profiles indicate that housing demand is likely to be stronger going north or east from the station area, rather than south or west.

The Physical Terrain Profiles from the Fruitvale BART station, shown in the upper right corner of Figure 8, present profiles of the actual physical terrain within 10 kilometers of the station. These profiles were done using U.S. Geological Survey topographic maps using the TOPO! Version 1.0, a low-cost software used by hikers and bicyclists to plan trips.

The profile images exported from TOPO! were rotated, mirrored, and scaled using mainly Paint Shop Pro 4.00.

Finally, all images and maps were brought into a "Layout" in ArcView.

Conclusion

Many communities in the USA are grappling with the notion of how best to meet the desires of their residents whose personal quality of life reflects the sustainable communities movement, which seeks to establish areas that are livable and walkable, and accessible to a great many services and conveniences. Given the factors outlined above, often the ideal setting is a location within close proximity of public transit in an urban setting.

As planning officials, developers and others strive to meet the demand for sustainable communities, they need to equip themselves with the tools to select sites that make sense within their spatial context. The Envisioning Neighborhoods-Transit-Oriented Development (EN TOD) technique, with its myriad methods for analyzing and presenting data in a spatial context, is one such tool.

Acknowledgments

Acknowledgment is given for support provided by the Mineta Transportation Institute at San José State University, the California Department of Transportation, and U.S. Department of Transportation for this work.

Appreciation is given for contributions to this project by team members Steven Colman, Dayana Salazar, Richard Taketa, Antony R. Jayaprakash, Erin Mayer, Tran V. Tung, and Pin-Yuan Wang, as well as to SJSU Open University student Shyamala Raveendran.

References

Included in main report's references.

 

appendix b: History of Transit-Oriented Development

Brett Hondorp

For the PowerPoint presentation, see CD-ROM file TOD_History.