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1 Introduction We live in a spatial world and are accustomed, on a routine basis, to dealing with the complex spatial relationships that govern much of our daily lives. We live at one location, work at another, and interact with commercial establish- ments, friends, and institutions scattered over a wide area. Decisions involving distance, direction, adjacency, relative location, and other more complex spatial concepts are handled by each of us on a regular, but often intuitive, basis. To assist in making these decisions we have developed over a period of many decades an efficient method of storing information about spatial rela- tionships. This device is known as a map. The first map was created before the first alphabet, so it is clear that we have been working on the creation of efficient spatial storage and display devices for many thousands of years. Data elements that may be stored in map form are commonly referred to as spatial data and possess the unique attribute of having a defined location on the surface of the Earth. These locations are commonly defined on the basis of a standard coordinate system (latitude, longitude, and elevation). Through reference to latitude, longitude, and elevation we can define the location of any entity, anywhere on Earth. Over the years a number of in- creasingly precise measurement tools have been developed to determine these coordinates with a high degree of accuracy. The collection of spatial data, the determination of locations in a standard coordinate system, and the subse- quent storage and portrayal on maps are common functions in all modern societies. Spatial data that have been stored in map form are used for a wide variety 5 l

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6 MODERNIZATION OF THE PUBLIC LAND SURVEY SYSTEM of purposes, including pathfinding, management of natural resources, and mil- itary assessments. Spatial data are usually filed in data sets; each set pertains to a particular land attribute. A common question that map users frequently address to spatial data sets relates to possible interrelationships existing be- tween two or more of these data sets. For example, in attempting to assess the recreation potential of a specific study area, a planner may desire to know which water bodies of a size greater than five acres lie within one mile or less of a paved road. This simple measure of accessibility is obtained by compar- ing two spatial data sets, one showing the size and "distribution of water bodies and the other showing the spatial pattern and nature of the road network. Queries of a similar nature include the following: What is the least-cost route for a temporary logging service road between a new cutting area and an existing highway, taking into account such items as slope, ground cover, drainage, and amount of cut and fill needed? Within a western state, which potential coal-producing areas contain deposits of a specified nature (sulfur content, ash level), suitable for surface mining, and which surface and subsurface rights are owned by the federal government? It is clear that many of us must carry out the integration of complex spa- tial data files on a routine, day-to-day basis. Fundamental to the effective integration of spatial data files is the nature and accuracy of the coordinate system on which they are based. We may say, for example, that things exist "in the same place" only to the extent that they possess identical coordinates Reflected in this statement are two problems. One relates to the precision of measurement of the locations, while the other reflects the coordinate system that is being used. Two different coordinate systems for the same region can be related if a number of common points are known in both systems. Given these corresponding points, a set of transformation equations will permit any locations coded in one set of coordinate values to be expressed in the other. This operation is commonly done when moving from latitude and longitude to any of the plane map projections that are used in conventional maps. Obviously, if two spatial data sets pertaining to the same region cannot be related through a common coordinate system, it is exceedingly difficult for the map user to integrate and manipulate their information in a usable way. Related problems arise when comparing two or more spatial patterns. Each spatial entity possesses both locational (coordinate) and nonlocational characteristics. For example, a parcel of land not only possesses a defined location but it also possesses a number of other spatial characteristics such as slope class, land cover, soil type, and ownership. Consistent location of these spatial characteristics is essential to the successful integration of spatial data l

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Introduction and 7 sets. This integration of different spatial data sets may be impaired through the following: 1. Imprecise measurement of the location of entities in the two data sets 2. Inability to express locations in a common coordinate system. Traditionally, integration of spatial data sets is carried out by transforming the two or more spatial data sets to a common map scale, creation of a trans- parent or translucent overlay for each set, registration of these overlays so that the coordinate systems are aligned, and then manually creating a com- posite overlay sheet that shows those areas where the various phenomena classes being studied occur in juxtaposition (Steinitz, 1977~. This procedure is laborious and time-consuming and is being supplanted by automatic pro- cedures. The basis for modern computer processing of spatial data lies in the crea- tion of consistent digital data files. There are two methods for developing these files: Digitization of existing maps that meet national map accuracy standards (Appendix B) and 2. Acquisition of data directly in digital form. Over the past 15 years a number of computerized systems (known as geo- graphic information systems) have grown up to automate the manipulation and integration of spatial data files. These geographic information systems permit the user to bring together information from numerous spatial data sets into a composite for either visual display or analytic modeling purposes. To bring these data sets into correspondence in the digital domain through what is known as the overlay process demands reference to a common coordi- nate system. In the United States today, it is difficult to display property lines correctly on maps. The reason is that cadastral (land-ownership) systems (such as local coordinate system or a parcel-identif~er system) and cartographic systems are in different coordinate systems. As mentioned previously, map data based on latitude-longitude provide the basic mechanism through which different spa- tial data sets can be brought together. Cadastral data, on the other hand, simply record the location of boundaries or points on the ground. To a signif- icant degree these data are textual in nature (e.g., the deed), and, while mea- surements usually form a major portion of these texts, the latitude and longi- tude coordinates are rarely included. In fact, coordinate information is not generally considered legal evidence when boundary matters are taken to court

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8 MODERNIZATION OF THE PUBLIC LAND SURVEY SYSTEM as at this time the corner monument is of prime importance. This means that the cadastral data exist within their own local coordinate systems and that translation between the cadastral coordinate system and the latitude and longitude system is generally difficult or even impossible. For example, a re- source manager working with digital spatial data files can integrate spatial data pertaining to such characteristics as soils, terrain, and mineral resources, but he cannot subsequently relate this composite information to patterns of land ownership. A substantial portion of the lands in the United States and a very large proportion of those in federal ownership were surveyed under a cadastral system known as the Public Land Survey System (PLSS), which established the familiar township and range system. Until recently, there has been mini- mal demand for expressing the positions of the PLSS monuments in the lati- tude and longitude system or in some other coordinate system such as a state plane coordinate system. Not only are the two coordinate systems funda- mentally different, but bridging the differences involves substantial cost and conflicts with traditional attitudes. The growing use of computer-based geo- graphic information systems to process spatial data has been altering this situation radically. The purpose of the present report is to examine the problems that would be involved in creating a digital, coordinate-based rep- resentation of the PLSS. In pursuit of this goal, the remaining chapters exam- ine the history of the PLSS, the current demand for a digital PLSS data base, the technical and economic considerations involved in the creation of such a data base, and the numerous institutional considerations that would need to be confronted if such a system were to be implemented. l