GIRAS: A Geographic Information 

Retrieval and Analysis System for 

Handling Land Use and Land Cover Data

GEOLOGICAL SURVEY PROFESSIONAL PAPER 1059
GIRAS: A Geographic Information 

Retrieval and Analysis System for 

Handling Land Use and Land Cover Data

By WILLIAM B. MITCHELL, STEPHEN C. GUPTILL, K. ERIC ANDERSON, 

ROBIN G. FEGEAS, and CHERYL A HALLAM

GEOLOGICAL SURVEY PROFESSIONAL PAPER 1059

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHINGTON : 1977
UNITED STATES DEPARTMENT OF THE INTERIOR 

CECIL D. ANDRUS, Secretary

GEOLOGICAL SURVEY 

H. William Menard, Director

Library of Congress catalog-card No. 77-600047

First printing 1977 

Second printing 1978

For sale by the Superintendent of Documents, U.S. Government Printing Office

Washington, D. C. 20402 

Stock Number 024-001-03007-1
CONTENTS

	Page

Abstract ........................................................................... 1

General system description .......................................................... 1

Source data ........................................................................ 2

Land Use and Land Cover Map .................................................. 2

Political Unit Map .............................................................. 3

Census County Subdivision Map ................................................. 3

Hydrologic Unit Map ........................................................... 3

Federal Land Ownership Map ................................................... 3

State Land Ownership Map ..................................................... 3

Data volumes ...................................................................... 4

Data structure ..................................................................... 5

Data capture ....................................................................... 7

Data retrieval ...................................................................... 11

Data manipulation, analysis, and output ............................................. 11

Data manipulation ............................................................. 11

Data analysis .................................................................. 12

Data output .................................................................... 12

GIRAS II, current system design ..................................................... 13

References ......................................................................... 16

ILLUSTRATIONS

Page

FIGURE 1. General system flow of GIRAS .................................................................................... 3

2. Topological elements of a polygon map ............................................................................ 5

3. GIRAS file structure ............................................................................................ 6

4. Map header control points ....................................................................................... 7

5. Graphic input procedures for GIRAS ............................................................................. 10

6. Arc-to-polygon program sequence ................................................................................. 11

7. Island routines within the arc-to-polygon program ................................................................. 11

8. Final arc-to-polygon error-checking sequence ...................................................................... 12

9. Design features and contrasting capabilities of GIRAS I and GIRAS II .............................................. 14

10. System flow diagram of GIRAS I and GIRAS II .................................................................... 15

TABLES

Page

TABLE 1. U.S. Geological Survey land use and land cover classification system for use with remote sensor data ..................... 2

2. Federal land ownership .......................................................................................... 4

3. Data volumes of a sample of digitized map overlays ................................................................ 4

4. Estimated data volumes, 1975-1981 .............................................................................. 5

ill

GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND 

ANALYSIS SYSTEM FOR HANDLING 

LAND USE AND LAND COVER DATA

By WILLIAM B. MITCHELL, STEPHEN C. GUPTILL, K. ERIC ANDERSON, 

ROBIN G. FEGEAS, and CHERYL A. HALLAM

ABSTRACT

The U.S. Geological Survey is currently producing land use and 

land cover maps and associated overlays (e.g., political units) for the 

United States. These maps are being digitized, edited, and incorporated into a digital data base. The data will be available to the public 

in both graphic and digital form, and statistics derived from the data 

will be published. To accomplish these tasks the Geographic Information Retrieval and Analysis System (GIRAS) has been designed 

and developed. GIRAS is designed to accept digitizer input, provide 

comprehensive editing facilities, produce cartographic and statistical 

output, permit retrieval and analysis of data, and exercise data base 

management tasks. The editing and output procedures are currently 

operational and utilize an arc segment, polygon approach in a production mode. The system incorporates facilities for gridding the 

polygon data to make it compatible with grid-based data sources. 

Current system development is focused upon an interactive data base 

to enable immediate retrieval and display of map information. Users 

will be able to search for either locations or attributes and display 

results in a graphic or tabular form.

GENERAL SYSTEM DESCRIPTION

The accelerating need to facilitate the rational planning, management, and utilization of natural resources 

and the environment in the United States has been 

linked, in recent years, with an accompanying need for 

improved techniques and methods for the storage, 

analysis, and display of large quantities of spatial environmental data. Concomitant with these needs, rapid 

developments in the past decade in computer technology and in the applications of computers to environmental and natural resources data handling have promoted the creation of increasingly sophisticated 

spatially-oriented information systems. Understandably, those agencies of the Federal Government, planning bodies in the regions and States of the United 

States, and the private sector which are concerned with 

the planning and management of the nation's environmental and natural resources are likely to be in the 

vanguard of those system developments. Early in 1976, 

for example, more than 50 system activities in the U.S. 

Geological Survey were specifically concerned with 

gathering and handling spatial information in the

fields of geology, geography, topography, and water 

resources.

The Geographic Information Retrieval and Analysis 

System (GIRAS) is one such system. It has been 

designed to input, manipulate, analyze, and output 

digital spatial data developed for the land use and land 

cover mapping and data compilation program of the 

U.S. Geological Survey. The program is designed to provide systematic and comprehensive collection and 

analysis of land use and land cover data on a nationwide basis. In addition to the land use and land cover 

maps at scales of 1:250,000 and 1:100,000, associated 

maps are compiled showing hydrologic units, political 

units, census county subdivisions, Federal land ownership, and in some instances, State land ownership. 

GIRAS comprises three basic subsystems to handle 

that data: (1) Data input, (2) data retrieval and 

manipulation, and (3) data output. It incorporates a 

data base structure designed specifically for handling 

spatial data and provides comprehensive facilities for 

data editing, data manipulation, and graphic and 

statistical output. The initial development and current 

production mode of GIRAS I uses standardized batch 

computer routines for input and output processing. The 

general system flow of GIRAS I is shown in figure 1.

GIRAS I is a batch-oriented sequential system on 

which development began in 1973. Initial emphasis was 

on the editing and correction of digitized land use and 

associated data bases, the assemblage of simple 

archival data files based upon individual 1:250,000 

topographic quadrangles, and the application of rudimentary data retrieval routines to produce "standardized" statistical listings and plotter graphics. The driving force of that initial emphasis was the clear need to 

provide basic standard statistics to the cooperating 

agencies. These included the Louisiana State Planning 

Office, the Florida State Planning Office and ten 

regional planning councils in the State of Florida, the 

Ozarks Regional Commission, and various Kansas 

State agencies. The recognition of the relevance and apl
GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

plication of up-to-date land use, political, hydrologic, 

census, and Federal and State land ownership data 

which could be stored, manipulated, and retrieved 

through modern computer-aided techniques have 

developed in the direct relation to the sophistication of 

planning organizations, their exposure to geographic 

information systems, and the availability of new planning data. The initial reaction and the initial requirement of cooperative users was for statistics and 

graphics that can be produced by the most basic of 

geographic information systems. Areal data and associated attributes are transformed to a fixed grid system 

which can produce simple composites of graphic data 

and simple tabular listings.

This report describes the facilities and procedures of 

GIRAS I, a batch-oriented operational system. Sections 

of this report that follow describe in more detail the 

source and characteristics of the data being processed 

in GIRAS I, the data structure being used, the procedures for data capture and editing, data retrieval, 

data manipulation, and data output. The final section of 

the report describes the system design features that 

have been established for the interactive GIRAS II 

which has been under development in parallel with 

GIRAS I since 1975.

SOURCE DATA

The basic set of data presently produced in the 

program includes:

1. Land Use and Land Cover Map,

2. Political Unit Map,

3. Hydrologic Unit Map,

4. Census County Subdivision Map,

5. Federal Land Ownership Map, and

6. State Land Ownership Map (optional).

LAND USE AND LAND COVER MAP

The basic purpose of this map is to provide land use 

and land cover data to be used as a data source in itself 

or in combination with the other data sets produced in 

the program. One of the basic sources for land use compilation is the NASA high-altitude U-2/RB-57 aerial 

photocoverage, usually at scales smaller than 1:60,000. 

The l:250,000-scale topographic map series is used as 

the base map for the compilation of the land use and 

land cover and the associated overlays, with the exception that the l:100,000-scale topographic map base is 

used if that base map is available at the time the data 

set is released to the open file by the Geological Survey. 

Although compilation of land use and land cover is performed on a film-positive base enlarged to approximately 1:125,000, digitizing is performed at 1:250,000. 

The associated overlays are both compiled and digitized 

at 1:250,000.

TABLE 1. U.S. Geological Survey Land Use and Land Cover 

Classification System for use with remote sensor data

Level I Level II

1 Urban or built-up land

2 Agricultural land

3 Rangeland

4 Forest land

5 Water

6 Wetland

7 Barren land

11 Residential

12 Commercial and services

13 Industrial

14 Transportation, communications, 

and services

15 Industrial and commercial 

complexes

16 Mixed urban or built-up land

17 Other urban or built-up land

21 Cropland and pasture

22 Orchards, groves, vineyards, 

nurseries, and ornamental 

horticultural areas

23 Confined feeding operations

24 Other agricultural land

31 Herbaceous rangeland

32 Shrub and brush rangeland

33 Mixed rangeland

41 Deciduous forest land

42 Evergreen forest land

43 Mixed forest land

51 Streams and canals

52 Lakes

53 Reservoirs

54 Bays and estuaries

61

62

Forested wetland 

Nonforested wetland

8 Tundra

9 Perennial snow ice

71 Dry salt flats

72 Beaches

73 Sandy areas other than beaches

74 Bare exposed rocks

75 Strip mines, quarries, and gravel 

	pits

76 Transitional areas

77 Mixed barren land

81 Shrub and brush tundra

82 Herbaceous tundra,

83 Bare ground tundra

84 Mixed tundra

91 Perennial snowfields

92 Glaciers

Land use and land cover compilation is based upon 

the classification system and definitions of Level II land 

use and cover as shown in table 1.

All features are delineated by curved or straight lines 

which depict the actual boundaries of the areas 

(polygons) being described. The minimum size of 

polygons depicting all urban and built-up land (categories 11-17), water (51-54), confined feeding (23), 

other agricultural land (24), and strip mine, quarry, 

and gravel pit (75) categories is four hectares. All other 

categories of land use and land cover have a minimum 

polygon size of 16 hectares. Those sizes are also considered the minimum sizes to which polygons are 

digitized. In urban and water categories, the minimum 

width of a feature to be shown is 200 meters; that is, if a 

square with sides 200 meters in length is delineated, 

the area will be 4 hectares. Although this minimumwidth consideration precludes the delineation of very
SOURCE DATA

STATISTICS

77 A

RUDIMENTARY 

DATA RETRIEVAL

USERS

\ /

GRID 

COMPOSITING

GRAPHICS

FIGURE 1. General system flow of GIRAS.

narrow and very long 4-hectare polygons, triangles or 

other polygons are acceptable if the base of the triangle 

or minimum width of the polygon is 200 meters in 

length, and the area of the polygon is 4 hectares. For 

categories other than urban and water, the 16-hectare 

minimum size for delineation requires a minimum 

width polygon of 400 meters. Line weight for delineating land use and land cover polygons and for neat lines 

is 0.10 mm at the production scales of 1:250,000 or 

1:100,000.

POLITICAL UNIT MAP

The Political Unit Map provides a graphic portrayal 

of the county and State boundaries and is compiled 

using base maps at either 1:250,000 or 1:100,000. 

Source material for the Political Unit Maps is from 

Bureau of the Census unpublished maps entitled 

"County Subdivisions Townships and Places" and 

from the "Geographic Identification Code Scheme" and 

the "County and City Data Book," both Bureau of the 

Census publications (U.S. Bureau of the Census, 1972 b 

and c). The "County Subdivisions Townships and 

Places" maps are also used to separate Census County 

Subdivisions into Census Tracts. State and county 

political subdivisions are encoded with a five-digit number in accordance with the Geographic Identification 

Code Scheme with the exception that nontracted "independent cities" in Maryland, Missouri, Nevada, and 

Virginia are given an eight-digit code reflecting the 

State and city codes.

CENSUS COUNTY SUBDIVISION MAP

This map provides a graphic depiction of Census 

Tracts in Standard Metropolitan Statistical counties 

and Minor Civil Division or equivalent boundaries in 

non-Standard Metropolitan Statistical Area (SMSA) 

counties. The overlay is digitized in the same manner as 

the other overlays and is based upon a Bureau of the

Census publication entitled "Census Tracts" for the 

SMSA covered by the sheet being compiled (Bureau of 

the Census, 1972a) and a Bureau of the Census publication entitled "Geographic Identification Code Scheme" 

(Bureau of the Census, 1972c). Census tracts are encoded with a four-digit number which is unique for each 

SMSA and a six-digit number which is unique for each 

census tract. Minor civil divisions are encoded with an 

eight-digit number: the first two digits are the State 

code, the next three are the county code, and the last 

three are the minor civil division identifier.

HYDROLOGIC UNIT MAP

The Hydrologic Unit Map provides a reference for 

statistics published by the U.S. Geological Survey and is 

based upon Hydrologic Unit Maps together with the list 

"Boundary descriptions and name of region, subregion, 

accounting units, and cataloging unit." The hydrologic 

units are encoded with an eight-digit number which indicates the hydrologic region (first two digits), hydrologic subregion (second two digits), accounting unit 

(third two digits), and cataloging unit (fourth two 

digits).

FEDERAL LAND OWNERSHIP MAP

The U.S. Geological Survey has the responsibility to 

research, obtain, and format maps, plots, and other 

descriptive data relating to Federal Land Ownership. 

Minimum size for the delineation is 16 hectares and 

ownership is encoded according to the agencies shown 

in table 2.

STATE LAND OWNERSHIP MAP

In some instances in which the U.S. Geological 

Survey has a cost-sharing cooperative agreement with 

a specific State, a map overlay showing an inventory of 

State-owned land is produced from data furnished by
GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

TABLE 2. Federal land ownership

Code Agency

Department of Agriculture

1 1 Agricultural Research Service 

12 Forest Service (National Forest) 

13 Forest Service (National Grassland)

Department of Commerce

21 National Oceanic and Atmospheric Administration

Department of Defense

31 Air Force 

32 Army 

33 Army (Corps of Engineers-Civil Works) 

34 Navy

Department of the Interior

41 Bonneville Power Administration 

42 Bureau of Indian Affairs (does not include Indian 

lands held in trust) 

43 Bureau of Land Management 

44 Bureau of Mines 

45 Bureau of Reclamation 

46 Fish and Wildlife Service (National Wildlife Refuge) 

47 National Park Service (National Monument, 

Seashore, and Recreational Areas) 

48 National Park Service (National Park)

Department of Justice

51 Bureau of Prisons

Department of State

61 International Boundary and Water Commission, U.S. 

and Mexico

Department of Transportation

71 Federal Aviation Administration 

72 Federal Railroad Administration 

73 U.S. Coast Guard

Other Agencies

81 Energy Research and Development Administration 

82 General Services Administration 

83 National Aeronautics and Space Administration 

84 Tennessee Valley Authority 

85 Veteran's Administration

the State. Although this overlay is compiled to the same 

base map as used for the other overlays, the polygons 

are encoded according to the ownership codes used 

by the particular State.

DATA VOLUMES

The digitizing operation of the GIRAS has been functional since mid-1975. The records of the data-editing 

procedures have been used to estimate the data 

volumes that will be involved in future operations. Table 3 shows some measures of data volumes for the 

categories of Land Use and Land Cover, Political Units, 

Census County Subdivisions, Hydrologic Units, Federal 

Land Ownership, and State Land Ownership for

selected samples of 1:250,000 map quadrangles. The 

statistics show the numbers of arcs and digitizer coordinates input to the system as a result of digitizing as well 

as the numbers of arcs and coordinates output after a 

data reduction process in the editing stage. In addition, 

the number of polygons and the arc line lengths for the 

quadrangles are shown. The high, low, and average 

counts and measurements are also shown for each. 

The most dramatic variations indicated are the 

digitizer coordinates reduced in the editing process 

while not basically affecting the number of arcs. The 

greater complexity of the land use and land cover maps 

is demonstrated by the average number of polygons 

recorded for them as compared to those recorded for 

other overlays. Equally instructive is the wide high and 

low variations in the number of polygons and the arc 

line length for quadrangles sampled. 

Data volumes for the initial 9-year period of the land 

use and land cover mapping program have been estimated by using the average length of arc lines digitized 

for land use and land cover and the associated overlays 

in conjunction with the mapping schedules presently 

planned for the program. Another estimate of the data 

volume is provided by the numbers of input coordinate

TABLE 3. Data volumes of a sample of digitized map overlay 

categories

Sample size Average High

Land Use and Land Cover

Output arcs................... 54 7,340 27,339

Input coordinates ............. 54 877,003 2,170,480

Output coordinates ............ 54 165,384 435,540

Polygons .................... 51 2,986 9.865

Arc length (ml ..... .......... 50 97.91 214.95

Political Units

Polygons ..................... 54 16 37

Arc length (ml .............. 34 13.79 142.60

Census County Subdivisions

Input coordinates ............. 48 106,812 258,456

Arc length (ml ...............

Hydrologic Units

Input arcs .................... 48 34 67

Output arcs .................. 43 36 72

Input coordinates ............. 50 45,205 82,480

Output coordinates ............ 45 4,850 10,966

Polygons .................... 54 12 23

Arc length (ml ............... 34 8.17 12.28

Federal Land Ownership

Input coordinates ............. 35 36,536 181,250

Output coordinates ............ 33 5,492 13,896

Polygons ..................... 37 31 222

Arc length (ml ............... 24 5.65 25.19
DATA STRUCTURE

points by millions of points as they are received from 

the digitizing contractor. The two data volumes are 

shown in table 4 as they are distributed by category 

over the 9-year period. Since the beginning of the 

digitizing contract in early 1975, over 10 million output 

coordinates and over 5,000 meters of arc lines have 

been processed in the editing stage. That volume is the 

equivalent of over 80 million bytes of data.

TABLE 4. Estimated data volumes, 1975 -1981

Category / 

(1975-1981)

Land Use and Land Cover . . .

Census County Subdivisions .

Federal Land Ownership

State Land Ownership ......

Total ...............

\rc lint? length 

imt'tersl

. 37,408 

. 3,002

. 7,708 

. 3,592

. 2,698

. 2,665

. 57,073

Output coordinates

37,000,000 

2,000,000

6,250,000 

3,250,000

2,750,000

3,000,000

104,250,000

DATA STRUCTURE

The handling of spatial data, particularly in large 

quantities, is an area which has not been explored very 

thoroughly. Researchers have typically dealt with 

either small quantities of complex data or large quantities of simple data. Under these circumstances, questions of data organization have not been critical, but as 

large sets of spatial data are compiled, the necessity of 

having an efficient, comprehensive data structure 

becomes apparent.

The problems of data organization that appear minor 

to a researcher working with what he views as a manageable data set become large obstacles to someone who 

is operating in a production mode. The economics of the 

system are such that they are very sensitive to forms of 

data organization. A well-thought-out and optimized 

logical and physical structuring of the data may mean 

the difference between the success and failure of a 

large project.

The GIRAS data structure is the latest in a series of 

evolving structures used to represent digital land use 

data. As such it reflects our (and our users') biases concerning the information to be presented and its format.

Since all maps compiled in the land use and land 

cover mapping and data program are polygon maps, the 

data structure was designed to expedite the handling of 

this data type. The topological elements associated with 

polygon maps are shown in figure 2. In the GIRAS 

structure, the common boundaries, or arcs, are digitized 

only once. The arcs are then linked together to form 

polygons. Arcs are line segments defined by a series of 

x, y coordinate pairs. Topologically the structure is 

similar to the DIME format used by the Bureau of the 

Census, (Cooke and Maxfield, 1967) and to the structure described by Puecker and Chrisman (1975). In

dealing with spatial data, it is often more desirable to 

store certain data rather than to recompute it. Thus, a 

large amount of ancillary data (e.g., polygon area, 

perimeter, etc.) is carried along in the data structure. 

The storage of such information not only eliminates redundant computations, but also facilitates data 

retrieval and analysis tasks. The general structure of a 

map file is shown in figure 3.

The map header contains a substantial amount of inNODE 

ARC

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ISLAND

12 POLYGON LABEL

FIGURE 2. Topological elements of a polygon map.
GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

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DATA CAPTURE

formation, including the amount of data in the map, the 

date of the source material, title, and control point 

information. The details of the contents of the map 

header are shown in figure 3. A map may be segmented 

into sections. This sectioning allows for more economical processing by constraining the amount of data processed at one time. It also facilitates geographic 

retrieval of subsets of the data. The section header is 

described in figure 3.

Within each map section there are four subfiles: arc 

records, coordinate data, polygon records, and a subfile 

assigning arcs to polygons (called FAP). Figure 3 shows 

the contents of the arc and polygon records. The subfiles are highly interrelated to facilitate analysis. The 

polygon record contains a pointer to the FAP subfile 

(PLA), which, in turn, points to those arcs comprising 

the polygon. The arc records point to coordinate strings 

describing that arc. Both the arc and polygon records 

contain information to further simplify analysis. For 

example, an arc record contains the attribute codes left 

and right of the arc. If an analysis requires the extraction of boundaries between two types of land use, then 

that information can be retrieved directly from the arc 

records. In addition, if the areas of the polygons adjacent to the boundary are desired, the arc record points 

to the appropriate polygon records where the areas are 

recorded.

The TEXT file relates to the entire map and contains 

definitions of attribute codes which can be used in 

manipulation procedures. The associated data file is 

provided to enable users to carry with the map additional information for their own purposes.

The design of the data structure was guided to some 

extent by the fact that the program is in a production 

mode for land use and land cover and associated maps. 

At present, map editing operates in a batch mode on sequential files. The editing process necessarily operates 

upon all the data, often employing insertions and deletions to the data. This operation is amenable to sequential processing. However, the data structure has been 

designed so that random access methods could be implemented. This would probably be the desired method 

when the maps are placed in a data base and the 

manipulations are focused upon retrieval and analysis 

rather than modification.

DATA CAPTURE

Once a particular data structure has been determined, a procedure must be established to capture data 

to place in that structure. The data capture procedure 

involves the conversion of line maps into a digital format. As defined here the digitization process includes 

not only the initial conversion to digital form, but also 

the editing process by which "clean" or logically correct 

data files are produced.

A number of alternatives are available in both hardware and methodology to accomplish the initial conversion to digital form. Our experience has highlighted two 

major considerations in the design of a data capture 

system. These are hardware independence and the 

minimization of digitizer-operator induced errors. An 

effective method must not rely heavily on either the 

data capture device or operator judgment. The input 

processing procedures, under development since 1973, 

attempt to accomplish this by limiting the amount of information required from the digitizer and allowing 

transportable software to perform automatic editing, 

error checking, and file creation.

The digital data from any given digitizer must be 

identified by map title, date, and other textual information. The digitizer coordinate frame of reference is 

defined by the map projection and the digitization of 

selected control points with known geographic coordinates. Figure 4 shows map header control points. In addition, the processing procedures require two files; the 

first contains unlabeled lines defined by a series of x, y 

coordinate pairs, and the second, a file of polygon labels, 

each tied to an arbitrary point within the polygon.

In digitizing, lines are not tagged in any way, and all 

that is required while digitizing lines is the ability to 

recognize line intersections (nodes). The lines of the 

map are completely defined when each arc, including 

the arcs which are the boundaries of the map, has been 

digitized at least once. The only points which need be 

digitized more than once are the nodes.

The arcs of the maps can be linked together at their

NW

FIGURE 4. Map header control points.
8 GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

common nodes around each completely closed area. 

These areas, which are assumed to be homogeneous in 

the characteristic being mapped, are called polygons. 

Polygons which cross the boundary of the map are 

assumed to end at the boundary. A single polygon surrounded by one larger polygon is a simple island. A 

group of adjacent polygons surrounded by one larger 

polygon is called a compound island and contains identifiable nodes at arc junctions. For the purposes of 

digitization it is necessary to choose one point on the 

boundaries of simple islands to be the node. This node is 

both the first and last point in the coordinate string 

defining the arc which is the boundary of the simple island. The direction in which an arc is digitized is immaterial.

Every polygon of each map is identified by a not 

necessarily unique integer attribute of from one to ten 

digits. A polygon is completely defined when its attribute has been recorded at least once followed by the 

coordinates of some arbitrary interior point within the 

polygon which is neither on an arc nor within an included island.

The types and sophistication levels of equipment 

which have been used to supply data to the processing 

procedures cover a wide range from simple manual encoding and card punch operations to an automatic 

line-following laser scanner. While any device which 

can translate lines into a series of x, y coordinate pairs 

may be used, until recently the device used has been 

some variety of digitizing table with a manually operated cursor.

Experimental projects involving map digitization 

were conducted in 1973 and involved the use of Bendix 

Datagrid 1 and Wang tables. Production digitizing of 

U.S. Geological Survey land use and land cover maps 

began in the fall of 1974 using a Computer Equipment 

Corporation digitizing station operated by the Johns 

Hopkins Applied Physics Laboratory. To support the 

editing, update, and limited revision of production land 

use and land cover data, and to support continuing 

research projects requiring map digitization, the 

program utilizes INTERMAP, an interactive digitizing 

and editing system. This system has allowed a large 

amount of flexibility in digitizing and editing tasks.

Our experience in processing data digitized on tables 

with manually operated cursors has shown us that the 

number of problems, and therefore the amount of editing necessary, has varied with the machine or digitizing 

station used and with the skill of the operator. Some 

machines, designed for automatic drafting work, have 

proved unsuitable due to the high inertia of the cursor 

or arm when attempting to depart from a straight line.

Many tables create problems merely because they do 

not permit the operator to view his work until after he 

has completed the digitizing operation, if at all. The 

problems caused by using such "blind" tables include 

missing data (either lines or polygon labels), lines 

digitized more than once, incorrect labels, and loss of 

origin resulting in different frames of reference for 

various parts of the same map. Digitizing systems 

which allow viewing of the data while digitizing and 

which include some degree of back-tracking capability 

produce better results.

The experience and skill of the digitizer operator 

play even more important roles in the quality of the 

output from manually operated digitizer tables. Map 

topology must be understood and care must be taken so 

that control points are digitized correctly and lines are 

followed exactly. Constant attention must be paid so 

that line intersections (nodes) are recognized and that 

two arcs are not digitized as one. Labels must be correct, and good bookkeeping kept so that all labels and 

lines are digitized.

In 1975, the next phase of production digitizing of 

U.S. Geological Survey land use and land cover maps 

was undertaken by contract to I/O Metrics Corporation, 

who used a SWEEPNIK laser scanner. That scanner is 

used in a line-following mode rather than a raster-scan 

mode so that no raster-to-vector conversion is necessary. The use of the laser scanner has solved many of 

the problems inherent in manual digitizing, but has 

brought up new problems to replace them. The most 

serious problems have come from the poor quality of the 

line data after scale reduction and photo processing of 

the original inked compilation maps. Weak lines on the 

original drop out and strong lines bleed into neighboring lines and labels. Graphics of this quality cause the 

operator to repeatedly reposition the laser probe 

manually during the course of a digitization run. 

However, our experience has shown that if the source 

maps are scribed, with digitizing by automatic scanner 

in mind, considerable savings may be realized. If the 

high quality graphics input standards are met, the 

digitized data returned by the scanner are far more accurate and error free than the data from a manual 

digitizing operation.

After the necessary data have been captured by the 

digitizing device, the data go through the following 

steps to produce a final clean file:

1. Conversion of data files to standard GIRAS format;

2. Data reduction, i.e., elimination of points not needed 

to define lines within a given spatial tolerance, 

(data reduction program);

3. Splitting of data sets into sections, if necessary;

4. Limited automatic edit and error detection for the 

arc data;
DATA CAPTURE

5. Manual batch or interactive edit of line data, with 

returns to step 4 until data are error free;

6. Merging of labeled polygon points with the arc data 

resulting in either further error detection or clean 

files (ATP program);

7. Manual batch or interactive edit of polygon label 

data with returns to step 5 or 6 if necessary; and

8. Edge match of each map section with neighboring

map sections. 

This process is diagramed in figure 5.

All new digitizer data are first converted to standard 

GIRAS format. Each digitizer requires a special format 

conversion program. This format conversion process 

can be combined with the data reduction step to reduce 

input/output charges.

The data reduction step is important since all further 

editing, manipulation, and retrieval costs are dependent upon the amount of data to be processed. Our consolidation procedure has proven to be computationally 

efficient, and provides an 80 90 percent reduction in 

the amount of data delivered by the SWEEPNIK scanner.

In the next step the digital data may be split into sections, depending on the amount of data involved. As 

part of the splitting process, arcs are added along split 

lines to form a continuous outside boundary for each 

section.

Next, an automatic editing procedure is applied to the 

arc data. The types of editing and error checking are: 

A. Editing:

1. Deletion of one-point arcs,

2. Deletion of arcs shorter than allowed tolerance,

3. Deletion of duplicate arcs,

4. Adjustment of arc end points to meet exactly at 

modes, and

5. Deletion of points within duplicate-point

tolerance of nodes; 

B. Error detection:

1. End point of an arc matches no other end points 

and

2. Less than three arcs meet at node 

(Exception: one-arc islands) 

(Inclusion: "apple in a window").

The map processors use the error listing generated by 

this procedure, a graphic display of the digital data 

(either a hard copy plot, or CRT display), and a copy of 

the compilation manuscript to check the data and to 

decide the necessary edit corrections. The digitizing errors which must be corrected are: 

A. Line errors:

1.Two arcs represented as one (joined),

2. One arc represented as two,

3. Lines digitized more than once, and

4. Lines not digitized at all;

B. Polygon label errors:

1. Digitized point on an arc,

2. Digitized point outside the polygon,

3. Polygon mislabeled, and

4. Polygon left unlabeled.

The compilation errors which must be corrected are: 

A. Line errors:

1. Line or portion of a line omitted,

2. Line drawn to an island, separating a polygon 

from itself ("apple in a window"), and

3. False boundary between polygons of the same

characteristic; 

B. Polygon label errors:

1. Polygon mislabeled and

2. Polygon left unlabeled.

The possible commands to correct these errors are: 

A. Unlabeled arcs:

1. Join two arcs into one,

2. Divide one arc into two,

3. Delete an arc,

4. Delete a segment of an arc,

5. Add a segment of an arc,

6. Add an arc,

7. Translate an arc, and

8. Rotate and (or) stretch/compress an arc; 

B. Labeled polygon points:

1. Change a label,

2. Add a labeled point,

3. Delete a labeled point, and

4. Move a point.

This editing process continues until no further node errors are found.

A major computer program of the input processing is 

the arc-to-polygon (ATP) program. ATP ties the labeled 

polygon interior points to the arc data, creating the 

cross referenced polygon-arc files described in the previous section. The program also serves as the final 

stage of topological checking and verification. The 

program sequence is outlined in figures 6 8. Most of 

the Polygon Label Errors are flagged in ATP as well as 

false arc crossings and duplicate arcs. The errors listed 

may indicate more arc editing and (or) editing of the 

labeled interior points. Since the program deletes duplicate and misplaced labels, the editing of labeled polygon 

points consists of either changing a label or adding a 

labeled point.

The final step in building the GIRAS file involves the 

edge matching of the outside boundary arcs of each 

map section with neighboring map sections either from 

the same map sheet, or other maps previously digitized 

and filed. This edge match process entails not only the 

completion of the map presently processed, but the update of the edge information of maps already stored.
10 GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

Initial Graphic to Digital Conversion 

(Map Digitization)

Conversion to Standard Format

Data Compaction

Spatial Segmentation (SPLIT)

Automatic Edit and Error 

Detection for Arc Data

Merge Polygon Label 

Data with Arc Data (ATP)

Edge Match

Insertion into Data Base

no

no

yes

Manual Batch or

Interactive Editing

of Arc Data

Arc Data 

Correction 

Needed ?

Manual Batch or

Interactive Editing

of Polygon Label Data

FIGURE 5. — Graphic input procedures for GIRAS.
LABELED

POLYGON

POINTS

T

Check for node errors.

Check for location error 

of next polygon point.

Chain polygon perimeter.

> r

Build polygon files 

and label arcs.

> f

DATA MANIPULATION, ANALYSIS, AND OUTPUT 11

1. Rotation, translation, and scaling of coordinates;

2. Conversion from geographic coordinates to specified 

map projections;

3. Restoration of original digitized map sheet from rectangular coordinate projection;

4. Conversion from polygon structure to grid cells of 

any specified size;

5. Production of area summary statistics from polygon 

or gridded data;

6. Geographic interpolation;

7. Filtering of nominal spatial data;

8. Feature generalization; and

9. Accuracy estimation of nominal maps.

DATA MANIPULATION

The first three procedures in the list deal with coordinate conversion. In order to accommodate the needs of 

various users, it is necessary to be able to rotate and 

translate the coordinate system and scale it to desired 

size. Similarly, a facility to change the data to a given 

map projection is also desirable, particularly when a 

supplemental base map exists on a different projection.

A number of existing spatial data systems can utilize 

only data stored by grid cells. Thus a program to convert the polygon structure to a grid cell format has been

FIGURE 6. — Arc-to-polygon program sequence.

DATA RETRIEVAL

Once the source materials have been placed in 

GIRAS form, the data can then be processed by various 

retrieval and manipulation procedures. The manipulation procedures can be applied to the archived data or to 

subsets of that data after retrieval by a data base 

management system.

Until recently, complex, automated retrieval of digital spatial data has not been needed. Most manipulations have been conducted on entire map sheets or on 

sections of maps. The output software contains 

facilities for the selection of subsets of the data for 

manipulation. For example, a program which draws a 

color shaded map of polygons manipulates only the 

polygon with the desired attributes.

DATA MANIPULATION, ANALYSIS, 

AND OUTPUT

Spatial data in the GIRAS structure can be processed 

by a number of manipulation and analysis procedures 

such as:

Array of polygon points

within a given 

polygon perimeter

Delete all other island 

points within this island

Delete any interior 

island arcs from arrays

Build polygon files 

and label arcs

FIGURE 7. — Island routines within the arc-to-polygon program.
12 GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

Polygons chained around 

all input polygon points.

List arcs with same

attribute label on both

sides.

Chain total map 

outside boundary.

List arcs missing polygon 

label on either side.

< Total map area= \ 

Sum of all polygon areas? /

FIGURE 8. — Final arc-to-polygon error-checking sequence.

devised. The latest version of the program takes advantage of the information in the GIRAS data structure 

and greatly reduces computational time as compared to 

earlier techniques. Previous methods were based on a 

point-in-polygon search routine to see if the center of a 

grid cell was within a specified polygon. The technique 

used by the present program polygon-to-grid (PTG), 

uses only the data associated with the arcs, and not the 

polygons. The intersection points between each 

horizontal scan line of the grid system and the arc are 

calculated. The attribute data carried with each arc is 

then used to decide the categories of the cells along that 

scan line. This causes the relationship between grid size 

and the computation time to be linear rather than exponential. This is of importance since a small grid size 

(specifically one half of the smallest feature) is required 

to retain the detail of the map.

For gridded data sets, a method has been developed to 

evaluate that data set on the basis of the probability of 

occurrence of a certain cell state, given the states of the 

neighboring cells. This technique is described in more 

detail by Gup till (1977).

Programs exist which provide summary areal tabulations of the data, whether stored in polygon or grid 

form. State and local planners have expressed a great 

desire and need for such tabulations.

DATA ANALYSIS

When gaps occur in what one assumes to be a continuous field of scalar data, a geographic interpolation 

program is used to predict values for the missing data. 

In the most common case, a weighted average of the six 

nearest data points is used to supply an interpolated 

value. The GIRAS interpolation program uses this 

scheme, but it can accommodate other interpolation 

methods. The program is also capable of handling binary valued nominal data.

Filtering techniques for nominal data are a part of 

the GIRAS software. Several different methods have 

been developed for use with nominal data. These include such techniques as neighbor counting, modified 

neighbor counting, and various propagation processes 

(see Guptill, 1975). Additionally, an "optimal" spatial 

filter should also prove promising in the development of 

land use and land use change maps from Landsat Computer Compatible Tapes data. While data on a lattice 

are usually used in this program, polygonal data can be 

handled by using the results in this program, and 

restoring the polygons from the processed data.

Several procedures exist for feature generalization. 

These include the optimal filter algorithm mentioned 

previously as well as a modified version of the WEED 

program. These procedures indicate that a more suitable technique for feature generalization as required by 

scale changes in mapped data is needed.

DATA OUTPUT

The various display capabilities of the GIRAS software 

are:

1. Color/pattern shading of polygon;

2. Boundary and attribute plotting for polygons and 

arcs;

3. Pattern symbolization of grid cells;

4. Choropleth mapping of polygons;

5. Choropleth mapping of gridded polygons (line 

printer);

6. Isometric bivariate histogram plotting;

7. Perspective view block diagram;

8. Perspective view contour mapping; and

9. Perspective view pins diagram.

Some of the plotting criteria and options are:
GIRAS II, CURRENT SYSTEM DESIGN 13

Selective boundary plotting criteria:

1. Attributes on either side (by polygon),

2. Attributes not on either side,

3. Attributes on one side and another set of attributes on the other side (by boundary type),

4. Attributes on one side and another set of attributes not on the other side, and

5. Attributes not on one side and attributes not on

the other side. 

Polygon plotting options:

1. Boundaries only of given polygon attribute(s),

2. Polygon labels and (or) polygon sequence numbers,

3. Polygons selectively shaded, each selected attribute shaded with a unique user-specified color-pattern combination, and

4. Any scale.

Hard copy graphics output is presently (1977) generated by a Calcomp 763 drum plotter, although other 

output devices include the Gerber plotter and line 

printer. Most of the graphics procedures feature either 

a simultaneous generation of the drawing on the CRT 

screen, or allow for previewing of the drawing before 

actual plotting.

A procedure also exists to create open window press 

plate negatives using scribe coats generated on the Gerber 32 plotter from the GIRAS digital data. Solid colors 

are used to portray Level I land use and land cover and 

two digits carry the Level II land use and land cover 

data.

Eight separate plot files are generated on tape for 

the Gerber plotter, one file for each of seven Level I 

categories, and a file of all Level II land use boundaries. 

For each Level I category, only external boundaries 

(those separating that Level I category polygons from 

other Level I uses) and not internal boundaries (those 

separating different Level II sub-categories of the same 

Level I use) were selected for plotting. A 250 ^m scribing tool is used to cut the set of scribe coat material.

Photosensitive peel coats are exposed from each 

Level I category plate for each set, and open window 

negatives are made for each color. The Level II land use 

boundary scribe coats are used to print the black land 

use boundaries. A screened standard 1:250,000 quadrangle black line base is added for reference.

GIRAS II, 

CURRENT SYSTEM DESIGN

The initial system of GIRAS I, now operating in a 

production mode, was based upon a batch sequential input processing subsystem leading to the storage of data 

in simple digital archives. Further, the manipulation of 

those archival files is accomplished by a grid compositing system to permit the production of rudimentary,

standardized statistical and graphic outputs for the 

early users of the program. Thus far, that system has 

been successfully utilized to input a large amount of 

land use data and associated environmental data. In addition, the system has been supporting an accelerating 

production of tabular and graphic data sets in response 

to requirements of State cooperative users.

The GIRAS I production system, however, was not 

designed to support the capture, editing, and correction 

of very large and complex data sets such as presently 

scheduled for the land use and land cover data and 

analysis program, nor to fulfill the extended and advanced manipulative or analytic desires of the cooperative users. So far, expectations of State cooperative and 

Federal agency users have rapidly exceeded the 

relatively modest capabilities that were originally planned for a batch-oriented production system, and the 

need for a more advanced and sophisticated geographic 

information system was recognized early in GIRAS 

operations.

In mid-1975, the past experiences in the operation of 

GIRAS I were examined, the requirements of State 

cooperative agencies and Federal agencies were considered, and studies by outside consultants on the computer handling of geographical data (Tomlinson, 

Calkins, and Marble, 1976) were reviewed. This reexamination resulted in the development of a radically 

different design philosophy and criteria which have 

guided the development of GIRAS II through 1977.

GIRAS II is characterized by its use of an interactive, 

on-line, time-sharing, random access input processing 

system, a complex data base to be managed by a data 

base management system, interactive manipulation 

and analysis facilities which will permit user intervention through remote terminals, and advanced statistical and graphic outputs which include interactive 

graphic displays for remote terminal users.

The major design features of GIRAS I and II for the 

five essential elements of a geographic information 

system are summarized in figure 9 to contrast the 

capabilities of the two systems in terms of the ways in 

which a user of the system might operate it. The five 

elements are: (1) Data capture, (2) input processing, (3) 

data base management, (4) manipulative and analytic 

operation, and (5) statistical and graphic output. The 

two columns in the center of the diagram indicate the 

increased flexibility and value of the system under 

development as compared with the system now in 

operation.

The general system structure of GIRAS II and the 

transition linkage of GIRAS I with GIRAS II is shown 

in figure 10. Although the two systems differ drastically 

in complexity, explanation of a few differences in their 

design will serve to contrast the capabilities for applica-
14 GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

GIRAS I GIRAS II

Batch-Oriented 

System flow

Possible Modes 

of User Involvement

Interactive-oriented 

Systems Flow

DATA CAPTURE

BATCH INPUT 

PROCESSING

-N

-V

DIGITAL 

ARCHIVES -V

BASIC MANIPULATION AND ANALYSIS 

(Grid Compositing)

Limited capability 

to input data to 

system

Dependent on own 

processing 

resources

Sequential processing off-line 

only, machine 

dependent, application programmer 

dependent

Sheet-by-sheet 

processing, offline, storage 

dependent

Data optimized 

for one user's 

applications

SYMAP-type 

analysis and 

manipulation 

programs

RUDIMENTARY 

STATISTICAL AND 

GRAPHIC OUTPUT

Data listings 

and simple 

graphics only

User can input 

data to system

Value of stored 

data increases

Dependence on programmer decreases

Less dependence on 

own machine resources

Cost per bit of 

data stored 

decreases

A-

\rData regarded as a 

State or region 

wide resource

Data pooled to form 

a multiple-application, independent 

resource

Distributed data 

bases

<=

Generalized search 

capability

Dependence on

application programmer decreases

Access to advanced 

capabilities and 

assistance from 

GIRAS programmer

-

Can produce 

extended statistics and 

graphics through 

query of data 

base

Interactive

graphic displays 

for mental and 

mathematical 

models

DATA CAPTURE

INTERACTIVE 

ON-LINE, 

TIME-SHARING, 

RANDOM ACCESS 

PROCESSING

COMPLEX DATA BASE 

MANAGEMENT SYSTEM

INTERACTIVE 

MANIPULATION AND 

ANALYSIS WITH USER 

INTERVENTION 

(Polygon compositing)

ADVANCED STATISTICAL AND GRAPHIC 

OUTPUT

INTERACTIVE GRAPHIC 

DISPLAYS FOR REMOTE 

TERMINAL USERS

FIGURE 9. Design features and contrasting capabilities of GIRAS I and GIRAS II.
GIRAS II. CURRENT SYSTEM DESIGN 15

GIRAS I •&;

T m

N m 

s|

T m

II

STATISTICS

T \

RUDIMENTARY 

DATA RETRIEVAL

USERS

GRID 

COMPOSITING

\ /

GRAPHICS

POLYGON 

COMPOSITING

TV A T1 A T7F*T rPTXT/^1 STATISTICAL 

CHECK

DATA BASE

MANAGEMENT

SYSTEM

COMPLEX 

DATA

BASE

DATA RETRIEVAL DATA UPDATE

DATA 

Z X

MANIPULATION

DATA 

ANALYSIS

S GIRAS II

STATISTICS

GRAPHICS

INTERACTIVE 

DISPLAY

EXTENDED 

z

MANIPULATION 

AND ANALYSIS

OTHER DATA 

SETS

INTERACTIVE 

PROCEDURES

USERS

FIGURE 10. — System flow diagram of GIRAS I and GIRAS II.
16 GIRAS: A GEOGRAPHIC INFORMATION RETRIEVAL AND ANALYSIS SYSTEM

tions in land use planning and decisionmaking. Probably the most critical change has been from a batch - 

oriented, sequential access computer system to an interactive, time-sharing, random-access computer 

system. A second design change is the shift from grid 

compositing to polygon compositing. Tests of polygon 

compositing have demonstrated that the user can move 

from the manipulation of only entire map sheets or sections of sheets to output software which will provide 

facilities for the selection of subsets of the data for 

manipulation, the query of the data base, or searches 

for particular data subsets through the hierarchical 

data structure. A third aspect of the GIRAS II design is 

the interposition of a "data base management system" 

between the complex data base and data retrieval. The 

need for a data base management system has become 

critical as increasing volumes of spatial digital information are added to the U.S. Geological Survey geographic 

information system.

REFERENCES

Anderson, J. R., Hardy, E. E., Roach, J. T., and Witmer, R. E., J976, A 

land use and land cover classification system for use with remote

sensor data: U.S. Geol. Survey Prof. Paper 964, 28 p.

Cooke, D. F., and Maxfield, W. H., 1968, The development of a 

geographic base file and its uses for mapping, in Papers from the 

fifth annual conference of the Urban and Regional Information 

Systems Association [1967]: Akron, Ohio, Kent State Univ., p. 

207-219.

Guptill, S. C., 1975, Spatial filtering of nominal data — an exploration: Univ. Michigan Ph. D. thesis, 210 p.

____ 1977, An optimal filter for maps showing nominal data: U.S.

Geol. Survey Jour. Research, v. 6. (In press.)

Puecker, T. K., and Chrisman, Nicholas, 1975, Cartographic data 

structures: Am. Cartographer, v. 2, no. 1, p. 55—69.

Tomlinson, R. F., Calkins, H. W., and Marble, D. F., 1976, Computer 

handling of geographical data: Paris, Nat. Resources Research, 

ser. XIII, 214 p.

U.S. Bureau of the Census, 1972a, Census tracts — 1970 census of 

population and housing: U.S. Bur. Census Final Repts. PHCU)-1 

through PHC(1)-241. [1 v. for each Standard Metropolitan 

Statistical Area.]

____1972b, County and city data book, 1972; U.S. Bur. Census, 

1020 p.

____1972c, Geographic identification code scheme— 1970 census 

of population and housing: U.S. Bur. Census Repts. PHC(R)-1 

through PHC(R)-4. [1 v. for each of the 4 U.S. regions, Northeast, North Central, South, and West.]

* U.S. Government Printing Office: 1978-677-026/ 12