Employment Capacity in Transit Station Areas in Maryland Prepared by: The National Center for Smart Growth Research and Education at the University of Maryland* Gerrit Knaap, PhD, Director Terry Moore, Senior Research Scholar Rebecca Lewis, Research Assistant Research assistance provided by Chis Dorney, Cathy Dowd, Steve Gehrke, Ray Hayhurst, & Doug Kampe March 2010 *The views expressed do not necessarily represent those of the University of Maryland, the Maryland Department of Transportation, or the State of Maryland.
Employment Capacity in Transit Station Areas in Maryland March 2010 EXECUTIVE SUMMARY The Transportation Policy Research Group of the National Center for Smart Growth (NCSG) at the University of Maryland conducted an exploration of existing employment and the capacity of undeveloped developable land to accommodate new employment in 110 transit stations in the State of Maryland. NSCG based its estimates on parcel-level data about (1) land use from the Maryland Department of Planning, and (2) employment (Quarterly Census of Employment and Wages) from the Maryland Department of Labor Licensing and Regulation. The analysis demonstrated that even if there was no redevelopment and no increase in employment densities, there exists within Maryland s 110 transit station areas enough capacity to accommodate approximately 30 percent of all anticipated employment growth in the region that includes Baltimore City, and Anne Arundel, Baltimore, Cecil, Frederick, Harford, Howard, Montgomery, and Prince George s counties, and 24 percent of all anticipated employment in the state from now until the year 2030. It shows that existing employment densities in Maryland's transit station areas vary from over 95 jobs per acre on average at stations on the Baltimore Metro line to under 30 jobs per acre on average at stations on the MARC line. The greatest unutilized job capacity exists in Montgomery County (a result more of its high existing employment densities than of its large amount of undeveloped developable land), but the largest amount of undeveloped but developable land exists in Prince George's County. Of the four transit lines, the Baltimore Metro has the least unutilized job capacity; the MARC line has the most. The analysis also raised several questions and suggestions for additional work, including: further testing of the accuracy and reliability of the estimates; sensitivity analysis on the extent to which redevelopment and increases in development intensity could add to job capacity, and more system-level analyses of how to get the most out of Maryland s statewide transit system.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 2 1 BACKGROUND The National Center for Smart Growth Research and Education (NSCG) at the University of Maryland signed with the Maryland Department of Transportation (MDOT) a memorandum of understanding to engage in joint research related to transportation in Maryland. The work plan for 2009, the first year under the amended agreement, contained six distinct research tasks. This report is NCSG s submission for Task C1. Task C1 was originally to analyze residential, commercial, and office property markets in station areas. NCSG and MDOT amended the task to be one of making estimates of the capacity of undeveloped but developable land in rail-station areas in Maryland to accommodate employment growth. Such estimates should be useful to MDOT in several of its planning efforts related to transportation facilities and development in those station areas. The estimates in this report and accompanying spreadsheets are preliminary. They must be interpreted in the context of the data and methods used to create them (described in some detail in Section 2 and appendices). The project did not start with a request to get some specific type of estimates of employment capacity by station area. Rather, it evolved as a spin-off of other work NCSG was doing statewide to estimate employment capacity using state employment and parcel data. The estimates of employment capacity we provide are useful for comparing relative employment capacity across different station areas, but cannot be used without additional analysis as firm estimates of the absolute employment capacity in any particular station area. 1 Our scope did not attempt a more typical analysis for station area evaluation: a site-specific analysis of existing development and development potential. Rather, we are working with statewide data that is quite accurate in aggregate, but could easily be off for any parcel or grouping of parcels, which makes its application in any specific station area questionable. Its advantage and unique contribution is that it describes 110 station areas with consistent data and methods, which allows for relative comparisons. 1 One big reason for that caveat is inherent in the method: the estimates here are for the employment capacity of undeveloped developable land; they do not address jobs that will be created by the redevelopment and intensification of use on developed parcels, which typically plays a big role in heavily urbanized areas, which is where most rail stations are located.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 3 Though NCSG spent a lot of time proofing the data that are the basis for the estimates presented in this memorandum, there are some inherent limitations with the underlying data that introduce imprecision into the estimates. There are ways to reduce that imprecision, but they take time and were not part of the scope for this project: we discuss them in this report. In addition to this report, NCSG is delivering to MDOT spreadsheets that include information about parcels, acres, employment, employment densities, and unutilized capacity within each station area. We include similar spreadsheets by county with information aggregated to the zoning classification level. We also include maps that convey results for the four transit lines with stations in Maryland. The rest of this report has three sections: Section 2, Framework for the evaluation. Concepts, methods, data, and caveats. Section 3, Summary of results. Detailed results by station area are in accompanying spreadsheets. Section 4, Conclusions. 2 FRAMEWORK FOR THE EVALUATION Though it is always the case in planning analysis that the proper use of information depends on an understanding of the data and analytical techniques used to develop that information, that point is particularly true in this project. Thus, we spend some time at the beginning of this report describing the data, our methods, and the limitations of both. 2.1 THE ROLE OF UNDEVELOPED, DEVELOPABLE LAND IN ESTIMATING JOB CAPACITY Fundamental to our evaluation are several reasonable but rebuttable assumptions that are typical of all evaluations of this type: If employment growth is to be significant in some area over the long run, buildings will have to be constructed to accommodate that employment
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 4 growth. In the short run it is possible that excess building supply and increased employment densities in existing buildings can accommodate employment growth. Over the long run, however, significant growth will require new built space. Buildings require sites. For many reasons it is typically easier and less expensive to build on undeveloped but developable sites than on sites that already have buildings on them. Thus, it is typical for land-use and transportation planners to consider the supply of undeveloped but developable land in planning. For example, it is common practice for standard four-step transportation models to require as inputs an estimate of employment growth by transportation analysis zone (TAZ), and for those estimates to be based in part and sometimes primarily on the amount of undevelopable developable land in the TAZ. These points suggest not only the importance of land supply to transportation modeling and planning, but also some of its limitations. In particular, real estate development does not happen wherever undeveloped developable land is in ample supply there has to be demand for real estate products as well, and that demand is a result of many factors. One must be careful with growth forecasts based only on the supply of land. It is not that supply-side forecasts of development ignore demand rather, they assume that demand will be there if the land under evaluation is close to land that has already been developed. For example, the Maryland Department of Planning has a state growth model that forecasts residential development primarily as a function of residential developable land, its zoning, and assumptions about the percentage of the maximum allowed density that will develop on the undeveloped developable land. It conditions its estimates to some degree by proximity to developed land, in large part because urban levels of residential zoning are generally in urban places, and thus close to places where residential demand has manifest itself as residential development.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 5 2.2 OVERVIEW OF METHODS USED BY NCSG TO ESTIMATE EMPLOYMENT CAPACITY AROUND RAIL STATIONS Our method attempts to go beyond the assumption that if you zone it they will build. We have added some demand-side reality into the evaluation by looking not just at undeveloped developable land and imputing to it some amount of development and employment capacity based on what is allowed by underlying zoning, but also by looking statewide at the amount of employment on similar types of land. In summary, our method was to: Identify station areas and define ½-mile buffers (using GIS) around those station areas as our analysis areas. Create a statewide GIS layers of developed, undeveloped but developable and undeveloped undevelopable land using various attributes from the state s Property View database to classify land into these three categories. Use statewide, site-specific employment data from the Department of Labor, Licensing, and Regulation (DLLR) to make estimates of the density of employment by zoning classification within each county. This method allows us to create an empirically based estimate of existing employment density for developed lands. Apply the employment density estimates to the land base to create estimates of unutilized employment capacity in each station area. Following sections describe each of those steps in more detail. 2.3 METHODS BY TASK 2.3.1 Definition of station areas The task of the NCSG was to make estimates of the capacity of undeveloped but developable land in rail-station areas in Maryland to accommodate employment growth. These estimates will be useful for MDOT in several of its planning efforts related to transportation facilities and development in those station areas. Transit Stations Maryland Area Regional Commuter (MARC) Train Service 38 Transit Stations
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 6 9 Counties Washington Metropolitan Area Transit Authority (WMATA) Metrorail 26 Transit Stations 2 Counties Baltimore Light Rail 33 Transit Stations 3 Counties Baltimore Metro Subway 14 Transit Stations 2 Counties All Transit Systems 110 Transit Stations 9 Counties Station Areas The NCSG defined the stations area as all land within one half-mile of that transit station. One half-mile represents the typical distance a person will walk to access transit from either their origin or destination. This distance is represented by a half-mile radius buffer surrounding each of the 110 transit stations in Maryland. Within this buffer the NCSG could estimate, using Property View parcel data, the capacity of the undeveloped developable land to accommodate employment growth. Property View is a parcel point database, however, which introduced other limitations and caveats. Caveats Station areas overlap other station areas. This occurred with 44 transit stations in Maryland. This simply means these stations are located within at least one half-mile of at least one other station. Stations serving the same transit system could be within proximity of one another or stations could be within proximity of stations serving other transit systems. See Appendix C1-C3 for this example at the Silver Spring MARC and Metrorail stations and Westport Light Rail station area. Station areas overlap into other states. This occurred with six stations in Maryland. Five of these station areas overlapped into Washington, D.C. and one station overlapped into Virginia. This accounts for the lower number of total acres within the parcels at these stations. See Appendix C1-C3 for this example at the Silver Spring MARC and Metrorail stations.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 7 Station areas overlap into multiple counties. This occurred with 11 stations in Maryland. In most instances a station area overlapped into only one other adjacent county, but one station overlapped into two other counties. These stations have had their employment capacity broken down by each county they and then totaled for the station. Parcel centroids do not fall in the station areas. This was a frequent occurrence. In some cases large parcels would lie within one half-mile of the station but because their centroid did not fall within this area, the parcel was not included in the station area. See Appendix C1-C3 for this example at the Martin State Airport MARC station and Perryville MARC station. Larger parcels may skew the average employment density of station areas. This is something to consider but it cannot be corrected. These parcels may have the majority of the acreage within the station area but have considerably lower employment capacity. See Appendix C1-C3 for this example at the Monocacy MARC station. Station areas contain a large amount of right of way. This was an issue that occurred in many station areas, resulting in lower acreage for the station area buffer. Parcel point data does not include acreage for right of way. Station areas overlap bodies of water. This was an issue that only occurred in a handful of stations. The bodies of water are not accounted for in total acreage, thus these stations have significantly lower amount of total acreage. See Appendix C1-C3 for an example at the Perryville MARC and Westport Light Rail station. Figure 1: Transit Stations in Maryland. To identify stations by number, please see Appendix C1-C1.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 8 To identify stations by number, please see Appendix C1-C1. 2.3.2 Definition of undeveloped developable land To obtain an estimate of employment capacity, we must know what land is available for development. We call this land undeveloped but developable. Property parcel information (as points) was used to classify parcels as developed, undeveloped developable, and undeveloped undevelopable, and the acreage of each parcel. Briefly, these three categories are defined as: Developed: parcels with structure assessed over $10,000; Undeveloped (and) Undevelopable: parcels without a structure assessed over $10,000 that are not developable because of environmental constraints or protected status; Undeveloped (but) Developable: parcels without a structure assessed over $10,000 and are not environmentally or legally constrained from development;
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 9 To classify parcels and calculate areas, we used the Master Parcel Database (based on Maryland PropertyView) which is maintained by Maryland Department of Planning and used in MDP s Residential Growth Model. See Appendix C1-B for further information about the assumptions used to divide land into developed, undeveloped undevelopable, and undeveloped undevelopable. Developed land was used to calculate employment per acre ratios, and undeveloped developable acres were used to calculate unutilized capacity. Because employment falls on both residential and non-residential land, we classified all parcels in the county into these three categories. We discuss below how we treated unutilized capacity on residential land. Limitations Area: In the Property View database, parcel data are represented as points rather than polygons, the acreage field for the parcels is sometimes inaccurate. Because we used the Maryland Department of Planning Master Parcel Database, these errors are less egregious than using raw Property View data. 2.3.3 Estimation of employment by location A number of state and federal agencies collect and/or disseminate employment data. These data are supplied at a variety of geographic scales from points representing individual employers to county totals. We sought employment data at the finest geographic scale available, so that we could derive employment density estimates for (relatively small) geographic areas. The only source of data at the workplace level for the entire state of Maryland is the Quarterly Census of Employment and Wages (QCEW, formerly known as the ES-202 data) compiled by the Maryland Department of Labor Licensing and Regulation (DLLR). This dataset provides monthly employment estimates by establishment for each quarter. The QCEW data used in this analysis date from the second quarter of 2007 -- the most recent data available at the time of processing. QCEW data were obtained from DLLR as a database (.dbf) file which staff at NCSG geocoded into a GIS shapefile. Each point in the GIS shapefile shows the location of a particular employer and provides the number of employees working at that site, in addition to other information such as North American Industry Classification (NAICS)
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 10 code. Adjustment factors were applied to each QCEW employment count to compensate for points that could not be geocoded and for employees that the QCEW dataset does not count. Appendix C1-A describes the entire adjustment process in more detail. 2.3.4 Estimation of employment density by zoning classification Employment densities can be calculated several different ways. Often, when Floor Area Ratios (FARs) are used to calculate employment capacity, industry standard employment densities are employed. In this analysis, we considered using three different types of employment densities based on different scales, and ultimately chose to compute employment density using zoning classifications at the county level. See Appendix C1-B for more information. Employment density was obtained by dividing total employment in a given zoning category (using QCEW data) by total developed acres (from Property View data) for each zoning category in each the county. 2.3.5 Estimation of unutilized employment capacity by county With knowledge of existing employment densities and undeveloped but developable parcels, we are able to compute unutilized employment capacity for the entire county. We computed three estimates of unutilized employment capacity. Here s why: While residential zones are not intended for employment, many employment sites exist in areas zoned residential. This could occur for several reasons: Employment sites may have existed when zoning boundaries were drawn (grandfathering) Jurisdictions do not zone for institutional uses like churches and schools, and these often fall in residential zones Geocoding errors result in misclassification of employment location. (See Appendix C1-A)
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 11 For these reasons, we estimate three different types of employment capacity, all of which treat employment capacity in residential zones differently. Estimate #1 (Full Residential). We assume that the future will be like the past, regardless of zoning classification. Employment densities in the future in residential zones will continue at the same levels as the present. Estimate #2 (Limited Residential): Assuming that employment on residential lands occurs primarily on exempt uses like education, churches, and nonprofits, we calculate a ratio of exempt developed acres in each zone to predict exempt acres in the future. In residential zones, employment is assigned to predicted exempt acres. Estimate #3 (No Residential): we do not assign employment to residential zones, assuming that all existing employment on residential zones was grandfathered. To calculate unutilized employment capacity we: Apply the zoning classification specific employment per developed acre ratios to each individual zoning polygon and calculate three separate estimates, discussed above. We provide detailed data by zoning classification for each county in Appendix C1-C5. Apply the employment per developed acre ratio to each individual undeveloped but developable parcel. Each parcel in a particular zoning classification receives the same employment per acre ratio. This ratio is multiplied by the acreage of each undeveloped developable parcel to obtain Estimate #1. Residential and Mixed Use parcels are treated differently under Estimate #2 and #3. See Appendix C1-B. This attributes unutilized capacity to individual undeveloped but developable parcels and permits aggregation at several scales from the parcel to the zoning classification to the county. It is extremely important to be clear about what this method represents. In this method employment capacity is computed by assuming that all future employment will occur in each zone at the same densities that currently exist in
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 12 the developed parcels of that zone. It does not represent the maximum employment density allowed by zoning; it does not represent the maximum employment density that is feasible if zoning was changed. It is probably best interpreted as the amount of employment that would occur if in the future all undeveloped land in station areas developed at the same employment densities as in the past. Further, it does not consider the possibility of redevelopment. 2.3.6 Estimation of employment capacity by station area For each station area, we calculated the number parcels and acres in all three classifications of land, jobs and job sites, employment density, and unutilized and total capacity. Computing this data for each station area permits aggregation by transit line or county. For details, see Appendix C1-B. Generally, this entailed: Overlaying a station buffer layer over parcels and employment sites for each county, counting the number of parcels and jobs that fell within these half-mile buffers for each station. Obtaining total capacity by summing existing employment in the station area and three estimates (see above) of unutilized employment capacity on undeveloped developable parcels. Aggregating data to transit line and county. See appendix C1 for results. Limitations Overlapping buffers: some parcels, jobs, and unutilized capacity falls within two station areas. How we handled this: We summed data for each station area individually, so parcels and employment sites falling within more than one buffer are essentially double counted in the station area table (Appendix C1-C1). It is important to note that summing up employment capacity for all station areas would lead to inaccurate totals at the statewide level. When summing by county, data were not double-counted (Table 1) Buffers extending into multiple counties: some station area buffers extend into two or three counties.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 13 How we handled this: We summed data for these stations by county, and totaled the sums to obtain a station area total. (see Appendix C1-C1) Parcel centroids falling outside the buffer: because parcel data are centroids not polygons, points with land area inside the buffer fall outside the buffer. How we handled this: We only summed parcel points that fell inside the buffer, which explains variation in station buffer acreage. Acreage also does not include right of way, water, or land in other jurisdictions. 3 SUMMARY OF THE RESULTS A summary of our results are presented in Tables 1-3. Before discussing the results it is important to note again what the results represent: preliminary estimates, with limited data, under a specific set of assumptions. Most importantly, the estimates were generated using Property View (a parcel point dataset), QCEW data (an incomplete compilation of employment in the state), and under the assumption that undeveloped land in station areas will be developed at existing employment densities. Table 1: Jobs and Job Capacity in the State, 9-County, Region and Station Areas State 9 Counties with Transit Stations Station Areas Existing Jobs (BEA/ QCEW Adjusted - 2007) 3,437,502 2,850,054 685,934 New Jobs Projected by 2030 (MDP-BEA) 630,898 521,346 Total Projected Jobs by 2030 (MDP-BEA) 4,068,400 3,371,400 Total Job Capacity 3,862,279 842,637 Unutilized Job Capacity 1,012,225 156,703 Percent of County Projections Accommodated by Unutilized Capacity 194% 30% Percent of State Projections Accommodated by Unutilized Capacity 160% 25%
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 14 As shown in Table 1, total jobs in the state currently equal 3,437,502. The Maryland Department of Planning projects that employment in the state will grow by 640,098 jobs by 2030 for a total of 4,077,600 jobs. Total employment in the 9- County region currently equal 2,850,054. The Maryland Department of Planning projects that employment in the 9-County region will grow by 521,346 jobs by 2030 for a total of 3,371,400 jobs. Total employment capacity in the 9-County region equals 3,862,279. Thus capacity to accommodate new jobs in the 9-County region equals 1,012,225 jobs. Thus there is ample capacity to accommodate new jobs in the 9-County region if future development occurs at the same employment densities as in the past. At present, 685,934 jobs in the 9-county region are located within a half mile of Maryland s 110 transit station areas. Those 110 station areas have the capacity to accommodate a total of 842,637 jobs. Thus Maryland s transit station areas have the capacity to accommodate an additional 156,703 jobs. This means that the 110 transit station areas in the state have the capacity to accommodate 30 percent of total estimated employment growth in the 9-county region or 24 percent of all expected employment growth in the state between now and the year 2030. As shown in Table 2, 42 percent of all jobs in station areas are located in stations on the Baltimore light rail line. As expected, existing employment densities are highest in the station areas on the Baltimore Metro system and lowest on the MARC line. As a result, 41 percent of the unutilized employment capacity is in station areas of the MARC line even though 39 percent of the total employment capacity is in station areas of the Baltimore light rail line. In the maps by station line in Appendix C1-C4 we show the ratio of unutilized capacity to existing jobs for the Baltimore Light Rail line. As expected, stations closer to the center of Baltimore have high levels of existing jobs, while peripheral stations contain higher levels of unutilized capacity. For the Baltimore Metro system, we show the ratio of undeveloped developable acres to total acres. Owings Mills and Old Court have high percentages of undeveloped but developable acres while Rogers Avenue has the lowest percentage. For the MARC commuter rail, we show employment per acres ratios for each station. As expected, stations near downtowns, like Frederick and Baltimore Penn Station have the highest employment per acre ratios. For WMATA, we show bar graphs that illustrate the ratio of unutilized employment to existing jobs and convey total
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 15 capacity for each station. Stations in Montgomery County (especially Bethesda and Silver Spring) have much higher total capacity than Prince George s County. Rockville, Wheaton and Silver Spring have high total amounts of unutilized capacity. These maps are for illustration only; many additional maps would be needed for comprehensive analysis. Table 2 Transit Stations, Undeveloped Parcels, Jobs, and Job Capacity in Maryland s Transit Systems ID ACRES IN PARCELS EXISTING JOBS Transit Line Number of Transit Stations Percent of Transit Stations Number of Acres In Parcels Undeveloped Developable in station areas Percent of Total Acres In Parcels Undeveloped Developable in station areas Number of Jobs Percent of Total Jobs in station areas Employment Density (employees per developed acre) EMPLOYMENT CAPACITY Percent of Total Unutilized Capacity Percent of Total Employment Capacity Baltimore Metro 14 13% 1,114 14% 331,493 22% 95.34 15% 21% Baltimore Light Rail 32 29% 1,605 21% 648,982 43% 77.32 16% 39% MARC 38 35% 3,214 41% 268,879 18% 29.48 43% 21% WMATA 26 24% 1,854 24% 274,782 18% 41.79 27% 19% Total 110 100% 7,786 100% 1,524,136 100% 55.29 100% 100% As shown in table 3, most of the undeveloped developable acres are located in Baltimore City, Anne Arundel, Baltimore, Montgomery, and Prince George s Counties. As shown in Table 3, Prince Georges County has the most undeveloped but developable acres and Baltimore city has the highest existing employment densities in station areas. Most of the unutilized employment capacity, however, is in Montgomery County. This is because Montgomery County has the highest combination of undeveloped but developable acres and the highest employment densities in commercial and industrial zones.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 16 4 CONCLUSIONS AND NEXT STEPS The Transportation Policy Research Group of the National Center for Smart Growth (NCSG) at the University of Maryland conducted an exploration of existing employment and the capacity of vacant land to accommodate new employment in 110 transit stations in the State of Maryland. NSCG based its estimates on parcel-level data about (1) land use from the Maryland Department of Planning, and (2) employment (Quarterly Census of Employment and Wages) from the Maryland Department of Labor Licensing and Regulation. The estimates in this report and accompanying spreadsheets are preliminary. Estimates of employment capacity are more useful for comparing the relative employment capacity across different station areas than as firm estimates of the absolute employment capacity in any particular station area. One reason for this is that the estimates are based only on the amount of land that is developable but undeveloped (which is roughly equivalent to vacant). The capacity estimates do not include jobs that will be created by the redevelopment and intensification of use on developed parcels. Many jobs typically locate on already developed land in heavily urbanized areas, which is where most rail stations are located. Another reason is that the estimates are based on existing employment densities and do not include the likelihood that future employment densities on vacant land in transit station areas will be higher than they have been in the past. Nonetheless, the analysis provides considerable information and a solid foundation for additional analysis. It shows that even if there were no redevelopment and no increase in employment densities, there exists within Maryland s 110 transit station areas enough capacity to accommodate approximately 154 percent of all anticipated employment growth in the region that includes Baltimore City, and Anne Arundel, Baltimore, Cecil, Frederick, Harford, Howard, Montgomery, and Prince Georges counties and 24 percent of all anticipated employment in the state from now until the year 2030. It shows that existing employment densities in Maryland's transit station areas vary considerably: from over 95 jobs per acre on average at stations on the Baltimore Metro line to under 30 jobs per acre on average at stations on the MARC line. The greatest unutilized job capacity exists in Montgomery County (a result more of its high existing job densities than of its large amount of undeveloped developable land), but the largest amount of undeveloped but developable land exists in Prince
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 17 George's County. Of the four transit lines, the Baltimore Metro has the least unutilized job capacity; the MARC line has the most. The analysis raises several questions. Most importantly: is the analysis sufficiently complete and detailed to serve as a basis for policy decisions? The accuracy and reliability of the estimates could be tested by studying a few station areas more closely, perhaps using parcel boundary data and more carefully verified employment data. Sensitivity analysis could also provide additional insights into the extent to which redevelopment and increases in development intensity could add to job capacity. More and better charts, graphs, and maps could help explanation and interpretation. Further analysis of station area typologies and system-level analysis of transit submarkets could be especially useful. What types of jobs are concentrated around which transit stations, where do the people live who work in those jobs, and how strategic investment and regulatory decisions can lead to more efficient use of Maryland's transit network. Answering those questions would involve further analysis of employment and demographic information, further analysis of transit rider surveys, and better integration of existing information about each transit station and the access to services provided by each station.
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 18 Table 3 Parcels, Acres, Employment and Employment Capacity by County ID ACRES IN PARCELS PARCELS County Acres In Parcels Total Acres In Parcels Developed Acres In Parcels Undeveloped Acres In Parcels Undeveloped - Developable Acres In Parcels Undeveloped - Undevelopable Parcels Total Parcels Developed Parcels Undeveloped Parcels Undeveloped - Developable Parcels Undeveloped - Undevelopable Anne Arundel 242,783 168,185 74,598 38,229 36,369 195,434 170,878 24,556 16,432 8,124 Station 3,366 2,324 1,042 777 265 6,159 5,256 903 735 168 Non-Station 239,417 165,861 73,556 37,452 36,104 189,275 165,622 23,653 15,697 7,956 Baltimore City 37,247 28,621 8,626 4,993 3,633 340,913 240,214 100,699 88,423 12,276 Station 5,358 3,944 1,414 966 448 61,991 36,308 25,683 23,341 2,342 Non-Station 31,889 24,677 7,212 4,027 3,185 278,922 203,906 75,016 65,082 9,934 Baltimore Co 345,466 244,160 101,306 52,568 48,738 279,873 241,791 38,082 29,718 8,364 Station 6,336 4,764 1,572 1,142 430 10,744 7,765 2,979 2,652 327 Non-Station 339,130 239,396 99,734 51,426 48,308 269,129 234,026 35,103 27,066 8,037 Cecil 64,922 4,238 60,684 45,578 15,106 44,780 34,151 10,629 9,580 1,049 Station 134 104 30 26 4 513 451 62 53 9 Non-Station 64,788 4,134 60,654 45,552 15,102 44,267 33,700 10,567 9,527 1,040 Frederick 380,931 284,143 96,788 77,964 18,824 85,667 75,167 10,500 9,471 1,029 Station 1,646 1,073 573 299 274 2,913 2,538 375 316 59 Non-Station 379,285 283,070 96,215 77,665 18,550 82,754 72,629 10,125 9,155 970 Harford 310,503 249,313 61,190 41,611 19,579 89,779 78,950 10,829 8,437 2,392 Station 571 434 137 95 42 1,294 1,079 215 197 18 Non-Station 309,932 248,879 61,053 41,516 19,537 88,485 77,871 10,614 8,240 2,374 Howard 151,005 110,736 40,269 14,317 25,952 96,140 86,569 9,571 5,223 4,348 Station 1,103 781 322 268 54 586 388 198 161 37 Non-Station 149,902 109,955 39,947 14,049 25,898 95,554 86,181 9,373 5,062 4,311 Montgomery 284,835 182,923 101,912 43,384 58,528 315,548 286,239 29,309 18,833 10,476 Station 8,640 6,163 2,477 1,226 1,251 27,446 23,483 3,963 3,670 293 Non-Station 276,195 176,760 99,435 42,158 57,277 288,102 262,756 25,346 15,163 10,183 Prince George's 271,940 153,003 118,937 83,865 35,072 236,164 202,895 33,269 27,443 5,826 Station 7,134 4,142 2,992 1,900 1,092 14,562 12,513 2,049 1,795 254 Non-Station 264,806 148,861 115,945 81,965 33,980 221,602 190,382 31,220 25,648 5,572 TOTAL 2,089,632 1,425,322 664,310 402,509 261,801 1,684,298 1,416,854 267,444 213,560 53,884 Station 34,288 23,729 10,559 6,699 3,860 126,208 89,781 36,427 32,920 3,507 Non-Station 2,055,344 1,401,593 653,751 395,810 257,941 1,558,090 1,327,073 231,017 180,640 50,377
Task C1, Employment Capacity in Transit Station Areas in Maryland NCSGRE March 2010 Page 19 ID JOBS EXISTING JOB CAPACITY County Job Sites Number of Jobs Job Density Unutilized Capacity - Estimate 1 Total Job Capacity - Estimate 1 Unutilized Capacity - Estimate 2 Total Job Capacity - Estimate 2 Unutilized Capacity - Estimate 3 Total Job Capacity - Estimate 3 Anne Arundel 13,713 362,500 2.16 119,692 482,192 100,407 462,907 93,639 456,139 Station 387 14,208 6 6,080 20,288 5,737 19,945 5,681 19,889 Non-Station 13,326 348,292 2 113,612 461,904 94,670 442,962 87,958 436,250 Baltimore City 12,396 402,855 14.08 77,943 480,798 62,389 465,244 54,529 457,384 Station 4,751 224,642 57 20,757 245,399 18,134 242,776 15,895 240,537 Non-Station 7,645 178,213 7 57,186 235,399 44,255 222,468 38,634 216,847 Baltimore Co 21,023 515,509 2.11 141,675 657,184 118,549 634,058 107,388 622,897 Station 2,513 102,680 22 18,530 121,210 17,595 120,275 16,799 119,479 Non-Station 18,510 412,829 2 123,145 535,974 100,954 513,783 90,589 503,418 Cecil 2,000 40,355 9.52 22,764 63,119 18,297 58,652 17,555 57,910 Station 14 348 3 96 444 96 444 96 444 Non-Station 1,986 40,007 10 22,668 62,675 18,201 58,208 17,459 57,466 Frederick 6,167 130,761 0.46 53,232 183,993 38,995 169,756 33,645 164,406 Station 578 9,362 9 8,374 17,736 2,763 12,125 308 9,670 Non-Station 5,589 121,399 0 44,858 166,257 36,232 157,631 33,337 154,736 Harford 5,821 118,062 0.47 121,028 239,090 112,727 230,789 107,767 225,829 Station 168 4,285 10 2,004 6,289 953 5,238 876 5,161 Non-Station 5,653 113,777 0 119,024 232,801 111,774 225,551 106,891 220,668 Howard 8,869 189,477 1.71 44,990 234,467 38,647 228,124 38,202 227,679 Station 225 7,984 10 3,015 10,999 2,989 10,973 2,989 10,973 Non-Station 8,644 181,493 2 41,975 223,468 35,658 217,151 35,213 216,706 Montgomery 30,446 652,310 3.57 194,108 846,418 153,380 805,690 133,519 785,829 Station 7,563 260,019 42 77,909 337,928 66,485 326,504 62,556 322,575 Non-Station 22,883 392,291 2 116,199 508,490 86,895 479,186 70,963 463,254 Prince George's 15,273 438,225 2.86 236,793 675,018 192,258 630,483 138,766 576,991 Station 1,660 62,406 15 19,938 82,344 15,844 78,250 13,298 75,704 Non-Station 13,613 375,819 3 216,855 592,674 176,414 552,233 125,468 501,287 TOTAL 115,708 2,850,054 2 1,012,225 3,862,279 835,649 3,685,703 725,011 3,575,065 Station 17,859 685,934 29 156,703 842,637 130,596 816,530 118,498 804,432 Non-Station 97,849 2,164,120 1.54 855,522 3,019,642 705,053 2,869,173 606,513 2,770,633