Toward a Standardized Land-Use Coding Standard

March 30, 1994

Prepared by the Research Department, American Planning Association, for the Federal Highway Administration, U.S. Department of Transportation. © 1994 American Planning Association


The Research Department of the American Planning Association assisted the Federal Highway Administration in determining the interest of federal agencies in updating the 1965 Standard Land Use Coding Manual (SLCUM). This scoping project results are summarized below.

Working Paper

In 1965, the Federal Highway Administration and the Department of Housing (then the Bureau of Public Roads and the Urban Renewal Administration, respectively) published the SLUCM. The manual provided a detailed listing of land-use categories with numeric codes assigned to them. The categories were based on the Standard Industrial Classification (SIC) system. This coding procedure became the typical method for land-use coding in urban areas throughout the country. The manual was reprinted in 1972. Beginning in the late 1970s, the manual was used less frequently because land-use planning emphasized short-term, small-scale projects and the long-term horizon for planning was de-emphasized.

The 1965 SLUCM provided a general numeric coding scheme that used two, three, four, or more digits to identify land-use activities and an additional two to eight digits to identify ownership, type of structure the activity is housed in, auxiliary use codes for secondary land uses, etc. The primary emphasis of the SLUCM coding was to provide an exhaustive set of land uses derived from the SIC codes and a limited set of attribute data to further define some of the land-use categories. The manual provided illustrations of three attributes: ownership types; type of structures for residential uses; and crop types for farm uses.

The coding system as developed in 1965 was a recommended system; participating agencies or programs were not required to use it.

In brief discussions with several federal agencies, the following primary purposes surfaced. The contents of a SLUCM update could potentially include all of them. However, the manual will be limited to addressing, either through the main update of the SLUCM or an addendum, only those aspects in which a specific agency expresses interest. The purposes of revision are:

Case Studies

Included here is a summary of 21 case studies of successful coding schemes currently in use for land-use and land-cover information. A wide range of coding schemes representing a broad spectrum of applications and sources of land-use/land-cover data was collected and reviewed during the research. The schemes included in this report are currently in use in both the public and private sectors for land-use/land-cover applications.

For the purposes of this study and to better understand the differences between systems, the coding schemes are classified based on their current use and suitability for use as a standard. This classification scheme and a table that summarize all of the major coding schemes are presented below. Additionally, each of the major coding schemes has been more fully explained in a narrative. Those narratives are followed by a listing of each of the coding schemes. All the examples are cited, and, where available, the source or contact name, address, and other details are also provided. The coding schemes used in the survey came from the following agencies:

Fairfax County, Virginia

County of Los Angeles, California

Department of Natural Resources, North Carolina

City of St. Louis, Missouri

Orange County, California

Washoe County, Nevada

Clark County, Nevada

U.S. Geological Survey

Institute of Transportation Engineers

Maryland Water Resources Administration, Department of Natural Resources

Atlanta Regional Commission, Atlanta, Georgia

Southern California Association of Governments

Army Corps of Engineers

Executive Office of Environmental Affairs, Massachusetts

Ohio Remote Sensing Program

Department of Natural Resources, Michigan


Note: All of the above examples are available in a downloadable Excel file.

Classification of Coding Schemes

Land-use/land-cover coding schemes are generally used to categorize land uses to study specific phenomena, such as commercial activity, transportation impacts, or environmental impacts. In the study of such phenomena, land-use/land-cover data is ascribed to spatial or geographic entities, such as parcels, census tracts, or one-acre grids. The choice of a specific coding scheme is based on the types of phenomena and the geographic entity that is being analyzed.

While it is relatively easy to determine the geographic extent of a coding scheme, and thereby its adaptability as a standard, the purposes for which land-use/land-cover information is to be used are not always clear. Some coding schemes can become quite complex when they seek to describe a large variety of attributes. For example, a coding scheme may further differentiate between public and private ownership (public and private parks, office buildings housing government offices and private offices, public and private schools). The complexity of a coding scheme also generally tends to increase as resolution levels increase. For instance, land-cover data acquired through remote-sensing has a significantly lower resolution than parcel-based land-use data. Some coding schemes counter this complexity by using a hierarchical coding scheme that makes it easier to aggregate various data.

In sum, the type of coding scheme that an agency chooses is typically based on two factors — the scale (geographic extent) at which the land-use/land-cover data is used and the source (data acquisition methods) of land-use/land-cover information. The other factor in making a choice, and one that is becoming increasingly critical due to advances in use of computer-based technologies, is the ease of manipulation of the various land-use/land-cover classes. This manipulation makes it possible to share digital information. Some classification methods, such as hierarchal methods, are easier to use when aggregating data than are non-hierarchal methods.


The four common scales for coding schemes are:

Source of Data

The primary source of land-use/land-cover data (or the data acquisition method) also affects the type of coding scheme used. The resolution (or the minimum mapping/coding unit) and accuracy of the data are dependent on the type of source. The three common methods are: site survey, aerial photography, and satellite-based remote sensing.

Classification Methods

Coding schemes generally group together similar or related land-uses and sometimes land-cover types. The two common methods of classification are a simple exhaustive listing and a hierarchy of land uses.

Summary of Coding Schemes

The Summary of Coding Schemes table compares the schemes. The schemes listed in the table are grouped by scale (or geographic extent) namely, Neighborhood/Area Plan Scale, Citywide or Countywide Scale, Regional Scale, and Statewide Scale.

Each of the coding schemes is identified by its location of use, the name of agency or jurisdiction, and the following:

Descriptions of Coding Schemes Surveyed

Fairfax County, Virginia


Fairfax County uses four different coding schemes for land-use applications. Each coding scheme evolved over several years and was customized as needs changed. The primary source of land-use data for the entire 400-square-mile area of the county is the Land Master File, which is a parcel/land-records database. The Land Master File contains land-use data for more than 70 million square feet of built commercial space and 400,000 dwelling units spread over several urban cores, towns, and rural areas of the county. For assessments, zoning, and other routine county parcel-based land-use needs, the Existing Land Uses Coding Scheme is used. This is a three-level coding scheme that consists of about 150 three-digit codes. Every record in the Land Master File is a tax parcel and contains a list of all existing land uses for each parcel. Applications that require existing land-use information primarily use this coding scheme.

For projections and land-use-based impact analyses, the Planned Land Uses Coding Scheme is used. In this scheme, planned land-use designations, obtained from the Comprehensive Plan, are grouped differently. While the Existing Land Uses Coding Scheme is an exhaustive list of all different types of land uses loosely based on the Standard Industrial Classification, the Planned Land Uses Coding Scheme groups similar types of uses together. Applications that study impacts of growth and project demand for public services, such as schools, safety, transportation, etc., use this coding scheme. Because data requirements for such studies typically emphasize the magnitude of impact rather than precise land uses, each of the major land-use types is classified according to the intensity or density of development. For example, residential uses are grouped by the number of dwelling units per acre. In the Existing Land Uses Coding Scheme, they are grouped by the dwelling unit type (single-family, town houses, apartments, condominiums, etc.). The Planned Land Uses Coding Scheme also uses a three-digit code and contains more than 200 distinct codes. Depending on specific application needs, this coding scheme is frequently modified.

For thematic land-use mapping, such as the Comprehensive Plan Maps, simplified versions of the above two coding schemes are used. A coding scheme that contains 25 character-based codes is used for aggregating existing land uses. For planned uses, the Conceptual and Area Plan Land Uses coding scheme is used. This coding scheme contains 12 three-digit land-use codes and is generally aggregated from the Planned Land Uses Coding Scheme.

County of Los Angeles, California


The County of Los Angeles, like many large jurisdictions in the country, uses several land-use coding schemes to meet a diverse range of applications. Since the county consists of distinct geographic and development patterns, coding schemes for each planning area were customized to address specific planning needs. Three coding schemes included for comparisons from the survey are from: Malibu/Santa Monica Mountains Area Plan; Santa Clarita Valley Area Plan; and Hacienda Heights and Rowland Heights Area Plans.

Each of the coding schemes is very specific to its area and contains no more than 26 land-use codes. All of them use unique mixed numeric and character codes. As part of the county's General Plan/Zoning Consistency Program begun in 1986, the land-use information was incorporated in a land-use layer of a countywide GIS system. Each area's unique land-use codes were maintained in the system. The land-use layer of the GIS system, which also includes 31 other similar areas throughout the county, was used to identify areas where the zoning was not consistent with the General Plan land-use designation. Because of the complexity of the system and lack of funds to maintain and update the land-use portion of the database with information from each of the small area plans, the program is no longer used actively.

Department of Natural Resources, North Carolina


Superconductor/Supercollider Project (pdf)

This coding scheme was adopted for use in the feasibility analysis of a superconductor/supercollider facility in an area roughly equal to 16 quad (7.5' USGS) maps. The seven land-use categories represent the rural nature of the study area. Some categories, such as Urban Land, contain further delineation of land uses in an hierarchal system. The primary source of land-use data was aerial photography with a mapping unit of three acres. Although the source data was grid based, the 28 land-use codes were used to map typical overlays through a GIS system.

The coding scheme as used is being modified for other statewide applications in cooperation with counties developing such an information base.

City of St. Louis, Missouri



St. Louis Land Records Management System (pdf)

The coding scheme used by the City of St. Louis Land Records Management System is the closest to a full implementation of the 1965 SLUCM and is typical of systems used in several cities across the country. The City of St. Louis is approximately 61 square miles in area with a population of about 400,000 and 195,000 dwelling units. The city is losing population. Most commercial uses are concentrated in the downtown area of the city. Although several new land uses were added or existing definitions modified, the coding scheme retains the four-digit numeric coding scheme of the 1965 SLUCM. Currently there are over 800 codes the city uses to designate all land uses in a parcel-based database. To accommodate secondary land uses, a new database field was added to the Land Record Management System. The secondary land uses information provides the city with more accurate land-use data.

The primary source of data collection is the Assessor's Office. Because of the sheer number of codes, there is a move by the Assessor's Office to use a simplified one- or two-digit coding system at the expense of losing land-use detail. In commercial areas, the License Collector's office uses a modified and simplified four-digit coding system. The primary challenge is to maintain a consistent land-use coding scheme across all city agencies.

Orange County, California


The 1990 Land Use Inventory program adopted a modified Level II Anderson coding scheme with about 26 land-use codes. The Anderson coding system was originally developed at the USGS and is 4-level hierarchial system. Because the primary source of data was aerial photography, the entire 800 square miles (22 USGS quads) were divided into 15,000 cells, and each cell was given one of the land-use codes. The cells were aggregated to census tracts, community planning areas, and cities to meet specific program needs. This coding scheme is a combination of a three-digit system mixed with a character code.

Principal applications of this system are to obtain a countywide inventory of land uses that could identify undeveloped land in relation to other developed land uses.

Washoe County, Nevada


The county's integrated terrain unit mapping project used a simplified Level II Anderson coding scheme to map the entire 6,600-square-mile county area for a vegetation layer of the GIS system. This layer is to be used in conjunction with a land-use layer that consists of both existing and planned land uses. The primary source of land-cover data is aerial photography with a mapping unit of two acres. The primary application of this information is the monitoring of water resources and the relationship of irrigated to nonirrigated land uses. Other applications were developed to assist in forest fire control and water-quality studies.

The coding scheme consists of two levels with a total of 29 codes. The county is currently trying to update the coding scheme to identify dedicated and nondedicated open space and forest lands.

Digital Line Graph — Enhanced, U.S. Geological Survey


Digital Line Graph — Enhanced (pdf)

DLG-E Model Overview from USGS (pdf)

Complete DLG Standards

The U.S. Geological Survey enhanced the Digital Line Graph model to a feature-based model. This model, DLG-E, uses a comprehensive approach to represent all types of features. The model uses five basic groups or views for all features — Cover, Division, Ecosystem, Geoposition, and Morphology. The views are based on some common defining characteristics. Cover reflects physical or material features; Division reflects cultural/political boundaries; Ecosystem reflects environmental features; Geoposition reflects locational characteristics relative to know or established points; and Morphology reflects the form (beach, basin, dune, island, valley, etc.) of land. Within each view there are subviews that clarify the distinctions between the various features. There are a total of 202 features in all five views. Most land-use/land-cover features are in the view Cover. Cover consists of 122 features grouped in five subviews — Barren Land, Built-up Land, Cultivated Cropland, Vegetation and Water.

The DLG-E model is used to generate the digital cartographic productions based on the National Digital Cartographic Data Base. This effort, which is part of the National Mapping Program, will be periodically reviewed by the USGS. A significant effort is being made to ensure that information based on the DLG-E data model can be exchanged with other federal, state and local agencies.

Institute of Transportation Engineers


ITE Manual, 5th Edition (pdf)

The ITE Manual provides trip generation statistics for various land uses based on data obtained by the ITE. The ITE Manual is a standard guide for estimating the number of trips that may be generated by a specific land use. Land uses are identified by a one-level coding scheme. Some of the uses have multiple codes to account for diversity in traffic impacts based on their size or density of development. There are 10 major land-use types with a total of about 127 land-use codes. With each new edition of the ITE Manual, the land-use codes are altered or expanded.

This coding scheme is entirely based on a single characteristic of land uses — trip generation. Typically, such coding schemes based on a single characteristic or attribute of a land-use/land-cover type are very application specific and not conducive to land-use data sharing.

Passaic, New Jersey


Passaic River Basin (pdf)

The Passaic River Basin is a 132 square-mile area of ten counties, 132 municipalities and a population of 2.4 million. The U.S. Army Corps of Engineers maintains a GIS containing hydrologic and land-use information for environmental analyses of the basin. The primary source of data is aerial photography although some land-use information for urbanized counties is provided or cross-checked by local planning agencies. The minimum mapping unit is a 10.33 acre grid unit. The coding scheme uses 13 basic land-cover classes for the GIS layer. The land-use information for urbanized areas is aggregated to these classes. The Corps provides hydrologic information to local agencies in addition to using this for its own programs.



The Massachusetts GIS Program (pdf)

The MassGIS program uses a statewide land-cover database to support various state and local program needs. The land-use data layer of the GIS was developed using 1:25,000 scale color infrared aerial photos with a minimum mapping unit of one acre. The coding scheme used for the land-use data layer has 21 land-use classifications and several additional classes were added for parts of Massachusetts. The coding scheme evolved from the MacConnel Coding Scheme, an earlier coding scheme developed by Prof. MacConnel and was widely used throughout the state of Massachusetts. The MacConnel coding system was a simple list of land uses that contained 104 classes. In the MassGIS adaptation, there are an estimated 70,000 polygons in the land-use data layer using the 21 classes (and additional classes for some parts of the state). The land-cover classes in use closely meet the environmental program needs around the state. Typical applications of this scheme are regional and statewide scale such as watershed protection buffer zones, air quality monitoring applications, pesticide regulation, solid waste sites, and monitoring coastal ecosystems. The MassGIS program also distributes its GIS data through computer files or published maps to other local and state agencies.

Note: Complete references for contacts and sources appear in the printed report.

Disclaimer: This material is based upon work supported by the Federal Highway Administration under AGREEMENT No. DTFH61-92-P-01590. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the Federal Highway Administration.

© 1994 American Planning Association