SOCIETAL VALUE OF GEOLOGIC MAPS

By RICHARD L. BERNKNOPF, DAVID S. BROOKSHIRE, 

DAVID R. SOLLER, MICHAEL J. McKEE, JOHN F. SUTTEF, 

JONATHAN C. MATTI, and RUSSELL H. CAMPBELL

An economic analysis by the U.S. Geological Survey's National 

Geologic Mapping Program that describes (1) geologic maps 

and their use as a fundamental data base, (2) a rigorous 

benefit-cost model for valuing geologic map information, and 

(3) the economic issues associated with determining whether 

or not a geologic map is a public good

U.S. GEOLOGICAL SURVEY CIRCULAR 1111
U.S. DEPARTMENT OF THE INTERIOR 

BRUCE BABBITT, Secretary

U.S. GEOLOGICAL SURVEY 

Gordon P. Eaton, Director

Any use of trade, product, or firm names

in this publication is for descriptive purposes only

and does not imply endorsement by the U.S. Government.

First printing 1993 

Second printing 1996

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHINGTON : 1996

Free on application to the 

U.S. Geological Survey 

Information Services 

Box 25425, Federal Center 

Denver, CO 80225

Library of Congress Cataloging in Publication Data

Societal value of geologic maps / by Richard L. Bernknopf. . . [et al.].

p. (U.S. Geological Survey circular ; 1111) 

At head of title: U.S. Geological Survey, National Geologic Mapping

Program.

Includes bibliographical references. 

Supt.ofDocs.no.: I 19.4/2:1111 

1. Geological mapping. I. Bernknopf, Richard L. (Richard Lewis) II. National

Geologic Mapping Program (U.S.) III. Series. 

QE36.S63 1993

550'.22'3-dc20 92-44935

CIP
CONTENTS

Introduction 1

Geologic Maps: The Basics 1

Geologic Maps: Suppliers, Users, Uses, and Distribution 2

Environmental Decisionmaking with Geologic Maps 4

Costs 4

Benefits 4

Benefit Estimation 5 

The Loudoun County Pilot Study 6

Case A: The Siting of a County Landfill 8

Case B: The Washington Bypass 10 

Net Benefits of Geologic Map Information 12

Cost to Produce Geologic Map Information for Loudoun County 12

Net Benefits of Improved Geologic Map Information 12 

Acknowledgments 12

Chapter I. Geologic Maps: Fundamental Data Base for the Earth Sciences 13

Introduction 13

What Is a Geologic Map? 13

Why Are Geologic Maps Needed? 13

What Kinds of Scientific Information Does a Geologic Map Contain? 14

How is a Geologic Map Used? 14 

Environmental Analysis 14

Waste Repository Siting 14

Regional Ground-Water Quality at Risk from Point-Source and Nonpoint-Source 

Contamination 15

Site-Specific Ground-Water Sources 15 

Geologic-Hazard Recognition 16

Earthquake Potential and Earthquake Hazards 16

Landslide Potential and Landslide Hazards 16

Volcanic Potential and Volcano Hazards 16 

Resource Exploration and Extraction 16

Energy Strategy 16

Minerals Strategy 16 

Balanced Land Management 17

Regional Economic Development Decisions 17

How Much Does It Cost To Produce a Geologic Map? 17 

References Cited 17

Chapter II. The Societal Value of Geologic Map Information: Use in a Regulatory 

Application 19

Introduction 19

The Issue 19

Background and Economic Concepts 19

The Empirical Evaluation 21

Contents II
The Role of Geologic Map Information in the Making of a Decision 21

Reducing Information Uncertainty with Geologic Maps 21

The Inclusion of Geologic Map Information in Regulations 22 

Framework for Empirical Analysis 24

Study Area and Background 24

The Land Use Decisions 25

The Regulatory Standards 29

The Method 29 

The Loudoun County, Virginia, Landfill Siting Demonstration Study 30

The Regulatory Standards 30

Empirical Implementation 31 

The Washington, D.C., Bypass Routing Demonstration Study 36

The Regulatory Standards 36

Empirical Implementation 37 

The Net Benefits of Geologic Map Information 40

Cost to Produce an Improved Geologic Map for Loudoun County 40

Net Benefits of Improved Geologic Map Information 41

Potential Lower-Bound Bias on the Net Benefit Measure 41

Implications of the Study Results 41 

References Cited 41

Chapter III. Geologic Maps as a Public Good: Provision of Geologic Maps and the 

Nature of the Demand for Geologic Map Information 43

Introduction 43

Public Provision of Geologic Maps 43

Historical Perspective 44

USGS Responsibility 44

Other Geologic Map Producers 44

The Distribution and Pricing of the Information 44 

Geologic Information as a Public Good 45

Types of Information 45

Public Goods 45

Nonrival in Consumption 45 

Jointness of Supply 46 

"Free-Rider" Problem 46 

Conditions for Natural Monopoly 47

The Natural Monopoly Framework 47

The Cost Function 47 

The Nature of the Good is Determined by the Institution 49

Other Governments and Agencies 49

Monitoring the Producer of Information 49

Vertical Integration 49

Network Externalities 50 

Testable Hypotheses 50

Background on National Geologic Mapping Program 52 

Needs for Geologic Map Information 52 

References Cited 52

IV Contents
FIGURES

1. A comparison of sections of (A) topographic and (B) geologic maps of the 

Salt Lake City area, Utah 2

2. A location map of Loudoun County, Virginia, showing the position of 

various cultural and geographic features 7

3. Geologic maps of eastern Loudoun County, Virginia 8

4. Digital plot of distribution of cells unsuitable for further consideration as 

possible sites for a landfill based on (A) the 1963 Geologic Map of 

Virginia and (B) a preliminary version of the 1992 USGS Geologic Map 

of Loudoun County, Virginia 10

5. Digital plot of distribution of cells requiring mitigation of slope failures 

arising from road construction, as based on (A) the 1963 Geologic Map of 

Virginia and (B) a preliminary version of the 1992 USGS Geologic Map 

of Loudoun County, Virginia 11

I-1. A graphic representation of some of the typical information contained in a 

general purpose geologic map and some of the many applications of that 

information 15 

II-l 3. Graphs showing:

II-l. The probability distributions of a geologic characteristic for two 

geologic maps of different vintages and different scales for the 

same area 22 

II-2. Economic impact of a regulation based on geologic map

information 22

II-3. Comparison of the size of a grid cell for the 1:500,000-scale 1963 

map and the 1:100,000-scale 1992 map and the delineation of a 

geologic attribute at the two geologic map scales 24

II-4. Location map of Loudoun County, Virginia, showing selected geographic

and cultural features 25

II-5. Digitally plotted geologic maps of eastern Loudoun County, Virginia 26 

II-6. Digital plot of dwelling density per 250-m grid cell in eastern Loudoun

County, Virginia, based on 1990 U.S. Census data 27 

II-7. Graph of frequency distributions for average ground-water yields based on

the two different geologic maps 28 

II-8. Graph of frequency distributions for average shear strengths of geologic

materials based on the two different geologic maps 28 

II-9 12. Digital plots of:

II-9. Areas in eastern Loudoun County, Virginia, excluded from

consideration for possible waste disposal facilities on the basis of 

current State regulations 32

11-10. Spatial distribution of cells in eastern Loudoun County, Virginia, 

restricted from further consideration as a possible landfill site on 

the basis of existing (1963) and improved (1992) geologic map 

information 33 

11-11. Conditional probability of contamination of rock materials in

eastern Loudoun County, Virginia, determined on the basis of their 

permeability 34 

11-12. Spatial distribution of property values, eastern Loudoun County,

Virginia 35 

II-l3. Histogram of the expected losses avoided due to landfill contamination for

cells in the study area, eastern Loudoun County, Virginia 35 

H-14-17. Digital plots of:

11-14. Spatial distribution of expected losses avoided per cell from a 

contaminated waste disposal site 35

Contents
11-15. Areas in eastern Loudoun County, Virginia, that would be

restricted when the improved geologic map is used but would not 

be restricted when the existing geologic map is used 36

11-16. Spatial distribution of expected slope failures due to road

construction, eastern Loudoun County, Virginia, that would 

require mitigation on the existing and new geologic maps 38

11-17. Conditional probability of slope failure due to road construction,

eastern Loudoun County, Virginia 39 

11-18. Histogram of the expected losses avoided due to highway slope failure for

cells in the study area, eastern Loudoun County, Virginia 39 

11-19. Digital plot of spatial distribution of expected losses avoided due to

slope failure induced by road construction, eastern Loudoun County,

Virginia 39 

11-20. Digital plot of areas in eastern Loudoun County, Virginia, that would not

require mitigation when the improved geologic map information is used

but that would require mitigation when the existing geologic map

information is used 40

II-21. Histogram of cost distribution by year for creating the improved geologic 

map of Loudoun County, Virginia 40

III-l. Graph of total profit of a multiproduct firm that produces information 49 

HI-2. Isoquants of a multiproduct firm showing the requirements for industry 

entry 49

TABLES

1. Selected Federal users of USGS geologic map information 3

II-l. Hypothetical regulations applied to cells in the study area 29 

II-2. Variables used in empirical demonstration of value of geologic map

information 29

II-3. Number of cells restricted for waste facility siting 32 

II-4. Number of cells for each highway construction mitigation outcome 37

II-5. Net benefits of new geologic map information in Loudoun County, 

Virginia 41

III-l. Payoffs to the provision of a public good 46

III-2. Federal users of USGS geologic map information 52

VI Contents
SALT LAKE CITY AREA, UTAH

Jio »" ;

A. Topographic Map Roads

 Urban areas

 Landforms

B. Geologic Map Rocks and sediments

 Faults

 Geologic history

1 MILE

1 KILOMETER

Figure 1. A comparison of sections of (A) topographic and (6) geologic maps of the Salt Lake City area, Utah. Scale 

1:100,000.

uses a combination of colors, lines, and symbols to depict 

the composition, structure, and history of geologic materials that support the landscape (fig. IB).

Geologic maps contain descriptive information about 

the solid earth. A geologic map commonly identifies the 

spatial distribution of bedrock materials like granite, 

limestone, sandstone, or shale; surface materials, which 

are deposited by wind, water, and ice; deposits such as 

landslide debris and debris flow materials; and geologic 

structures like faults, fractures, and folds. Geologic maps 

also provide an interpretation of how these materials and 

structures are related in space and time.

This combination of description and interpretation 

provides a conceptual framework relating all the geologic 

elements of an area together. For example, geologic maps 

commonly describe the physical properties of geologic 

materials and structures and can help someone determine 

their strength, porosity, and continuity. They can also 

depict the timing and sequence of events that produced the 

geologic materials and structures displayed on the map.

This may help identify, for example, geologically recent 

earthquake or volcano activity, in areas lacking historic 

records of such activity, that may raise safety concerns. The 

geologic map thus forms a fundamental data base for 

environmental decisions, including land use and zoning, 

that require a forecasting capability. A geologic map made 

and published by the U.S. Geological Survey (USGS) is a 

publicly available general purpose document that provides 

all of these types of information.

GEOLOGIC MAPS: SUPPLIERS, USERS, USES, 

AND DISTRIBUTION

The USGS generally produces areal and regional 

geologic maps. Site-specific geologic maps, which are 

more commonly prepared by State geological surveys and 

consulting geologists, generally begin with the information 

contained in one of the USGS geologic maps.

The USGS has been the major supplier of general 

purpose, regional geologic maps since its creation through

Introduction
Introduction

Societal Value of Geologic Maps

By Richard L. Bernknopf,1 David S. Brookshire,2 David R. Soller,1 Michael J. McKee,2 

John F. Sutler,1 Jonathan C. Matti, 1 and Russell H. Campbell 1

People frequently regard the landscape as part of a 

static system. The mountains and rivers that cross the 

landscape, and the bedrock that supports the surface, 

change little during the course of a lifetime. Geologic and 

hydrologic processes are, however, dynamic. Earthquakes, 

landslides, floods, and drought, to name a few examples, 

shape the societies that suffer through them. Society can, in 

turn, alter the geologic history of an area and affect the 

occurrence and impact of such natural hazards. For example, changes in land use can induce changes in erosion, 

sedimentation, and ground-water supply. As the environmental system is changed by both natural processes and 

human activities, the system's capacity to respond to 

additional stresses also changes. Information describing the 

physical world is critical for identifying solutions to land 

use and environmental issues. Geologic maps are known to 

provide useful information for these purposes. This report 

describes a method for estimating the economic value of 

applying geologic map information to land use decisionmaking.

Economic development decisions at all levels from 

local to global are influenced by their potential for causing 

environmental change. Addressing environmental concerns 

presents decisionmakers with choices that have far-reaching 

societal implications. Deciding to preserve certain tracts of 

land, for example, may limit economic opportunities and 

lessen or enhance the value of nearby lands. Conversely, 

inappropriate development may provide short-term benefits 

while creating long-term problems that could present future 

generations with extremely costly consequences.

Detailed, publicly available information concerning 

the nature and origin of the geology of an area is essential 

for informed public-policy decisionmaking and for economic development. Many public-policy decisions and 

commercial enterprises require a specific kind of earth 

science information, which is spatially based information 

that is linked to geologic materials and geologic structures.

Manuscript approved for publication, January 15, 1993.

1 U.S. Geological Survey.

2 University of New Mexico, Albuquerque, N. Mex.

The earth science product that best captures and displays 

this kind of information is the general purpose geologic 

map.

This report describes the purpose, uses, and value of 

geologic maps. It contains an evaluation and quantification 

of the net benefits of different levels of detail and improvements in interpretive models contained on geologic maps. 

The analysis uses a geographic information system (GIS) 

that includes earth science, engineering, and economic 

information to transfer the geologic map information into 

the decisionmaking framework. We develop and apply a 

model of decisionmaking that makes explicit use of geologic maps. In particular, the benefits of using improved 

geologic map information in a regulatory environment are 

compared to existing or dated geologic map data. The report 

includes the results of a pilot study in Loudoun County, 

Virginia, that illustrate how geologic map information can 

be used in siting a waste disposal facility and a transportation corridor. We show that improvement in geologic map 

information has a net positive value to society that can 

enable planners to make superior land use decisions. Principles developed in this pilot study are generally applicable 

to the many other possible uses of geologic map information.

Specific topics are developed in detail in the three 

chapters of the report. Chapter I provides a definition of a 

general purpose geologic map and a discussion of the use of 

a geologic map as a data base. Chapter II details the 

rigorous development of an economic model for valuing 

geologic map information. Chapter III identifies specific 

hypotheses that can be tested to determine whether or not 

general purpose geologic map information is of public 

benefit and also contains a partial documentation of the 

need for geologic maps.

GEOLOGIC MAPS: THE BASICS

Most people are familiar with highway maps or 

topographic maps that depict forms on the surface of the 

Earth (fig. 1A). A geologic map, unlike a topographic map,

Geologic Maps: The Basics 1
the Organic Act of 1879 (43 U.S.C. 31(a)). The Organic 

Act charges the USGS with providing the geologic knowledge base associated with all Federal, State, and private 

lands. The Director of the USGS is assigned responsibility 

for:

classification of the public lands and examination of 

the geological structure, mineral resources and products of the national domain, (p. 6)

The distribution of geologic information also is prescribed 

by the Organic Act as follows:

The Director ... is authorized ... to dispose of the 

. . . geologic maps ... at such prices and under such 

regulations as may from time to time be fixed by him 

. . . and a number of copies of each map . . . shall be 

distributed gratuitously among foreign governments 

and departments of our own Government to literary 

and scientific associations, and to ... educational 

institutions and libraries .... (p. 8)

Further, the Organic Act requires that maps be distributed at 

costs below those of production and distribution:

Three thousand copies of each shall be published for 

scientific exchanges and for sale at the price of publication ... (p. 7) (emphasis added)

Through the Organic Act, Congress dictated that 

earth science information should be widely available and 

clearly recognized that no social benefit accrued from 

restricted access to geologic information. Regional geologic 

information thus becomes a "public good."

Given the growing debate concerning the need to 

privatize goods and services currently provided by the 

government (and thus reduce government expenditures), it 

is necessary to ask whether production of regional geologic 

map information should be reassigned to the private sector. 

Answering this question requires analysis of several related 

issues that are raised and discussed in depth in chapter III.

Many governmental issues require the use of a 

general purpose geologic map. Federal agencies, for example, have diverse use requirements for geologic maps (table 

1). Federal, State, and local governments use USGS geologic map information for policy development and enforcement in all of these areas. For example, the U.S. Environmental Protection Agency (EPA) and most States require 

geologic map information to establish guidelines for selecting safe waste disposal sites. Highway planners also begin 

their site-selection process with regional geologic map 

information. The need for site-specific information for 

highways and landfills arises only when rights-of-ways or 

potential landfill sites have been identified. This more 

detailed information, or even a site map, commonly would 

not be provided by the USGS but by another, more 

specialized source.

The Departments of Interior (DOI) and Agriculture 

(USDA) also use geologic map information to fulfill their 

land and resource management missions. DOI's Bureau of 

Land Management (BLM) and Minerals Management SerTable 1. Selected Federal users of USGS geologic map 

information

USER APPLICATION

Department of Interior (DOI): 

Bureau of Land Management

(BLM)

Bureau of Mines (BOM) 

Bureau of Reclamation

(BOR) 

Office of Surface Mining

(OSM) 

Minerals Management

Service (MMS) 

National Park Service (NFS) 

Fish and Wildlife Service

(FWS)

Department of Defense (DOD): 

Army Corps of Engineers

Department of Energy (DOE)

Environmental Protection 

Agency (EPA)

Nuclear Regulatory Commission

(NRC)

U.S. Department of Agriculture 

(USDA): 

Agricultural Research Service

(ARS)

Forest Service (FS) 

Soil Conservation Service

(SCS)

Department of Transportation 

(DOT)

Housing and Urban Development (HUD)

Federal Emergency Management Agency (FEMA)

Tennessee Valley Authority 

(TVA)

Energy and mineral resource 

assessments of wilderness 

areas and other public lands; 

resource management plans; 

multiple-use plans; dam and 

reservoir development; 

ground-failure stability 

analysis.

Development planning; waste 

repositories; geologichazards analysis; siting of 

water works.

Energy resource assessments; 

waste repository developments and cleanup; seismic 

evaluations; siting of nuclear 

tests.

Assessment of naturally 

occurring toxins; groundwater assessments; multipleuse land use plans; waste 

site evaluations.

Nuclear plant and waste site 

evaluations.

Toxic substance evaluation; 

ground-water resource evaluation; wilderness assessment; Resource Management Plans.

Transportation and utility

corridor evaluations; airport

and facilities siting;

geologic-hazards evaluation. 

Transportation and utility

corridor evaluations;

geologic-hazards evaluation;

urban area zoning. 

Geologic-hazards evaluation.

Geologic-hazards and groundwater resource evaluations.

vice (MMS) use geologic map information to assist in 

managing energy and mineral resources as required by 

provisions of Federal law. The National Park Service (NPS) 

needs geologic map information to manage the mineral 

resources or geothermal resources found in and around the 

national parks, as law requires. The NPS also uses geologic 

map information to communicate the geologic history and 

landforms to national park visitors. Like the BLM, the 

Forest Service utilizes geologic map information to manage

Geologic Maps: Suppliers, Users, Uses, and Distribution
mineral and renewable resources in the national forests. In 

addition, most Bureaus in DOI and many Federal and State 

agencies need geologic map information to help address 

issues related to hazardous materials on public lands.

Beginning in 1988, the National Geologic Mapping 

(NGM) Program of the U.S. Geological Survey asked 

selected Bureaus in the Department of Interior and other 

Federal agencies to prioritize their needs for geologic 

mapping. The Bureaus were surveyed to guide the program 

in its long-term planning and to begin closer coordination 

among the USGS and other Federal agencies to produce and 

utilize geologic maps. The long-term goal of the NGM 

Program is to systematically build an archival geologic-map 

information base for the Nation. Priorities identified by 

Federal agencies are among the factors that help shape 

long-term program continuity.

ENVIRONMENTAL DECISIONMAKING WITH 

GEOLOGIC MAPS

Costs

The costs of producing geologic maps can be grouped 

into five categories: (1) data collection in the field, (2) data 

compilation and interpretation, (3) data presentation such as 

drafting, digitizing, and data-base construction, (4) printing 

and publication, and (5) distribution. This process is labor 

intensive and requires a highly skilled staff. Therefore, 

producing uniform geologic map coverage for the Nation, at 

a scale detailed enough for nearly all perceived uses, will be 

extremely expensive and thus should be a long-term goal 

that is systematically approached by establishing mapping 

priorities that represent shorter term goals (milestones).

A geologic map of the United States exclusive of 

Alaska and Hawaii was published by the USGS in 1974 at 

a scale of 1:2,500,000 and is the most detailed geologicmap information base that uniformly covers the contiguous 

States. Assuming that the geologic information it contains is 

as accurate as the cartographic base map used for compilation, a resolution of only about 5 km (kilometers) is possible 

for any individual geologic datum. Geologic maps at more 

detailed (larger) scales exist for various parts of the Nation, 

and the geologic-map information base of the Nation is 

improved continually as more detailed geologic map data 

are gathered, as new analytical techniques are developed, or 

as new models are proposed and adopted to interpret the 

distribution and structure of geologic materials.

Geologic maps commonly are constructed from both 

new and existing information. Gathering new information is 

the dominant cost and may determine the priority among 

candidate map areas. The cost of acquiring new geologic 

map information for a particular area will depend on the 

quality of the existing geologic map information for that 

area, on the geological complexity of the area, and on the

level of map detail needed for the perceived application. For 

some regions, the available geologic map data consist only 

of reconnaissance-quality information. For these areas, new 

information of greater density and accuracy must be 

acquired at significant cost. For other regions, the available 

data consist of modern, interdisciplinary, detailed-scale 

geologic map information. In these instances, existing 

geologic map information needs only be revised slightly and 

published in a form that compiles this existing information 

in a new format or in the context of new interpretive 

models. Geologic-map production costs will be relatively 

low in such cases.

Benefits

It is commonly accepted that geologic maps provide 

benefits to society. The specific societal benefits considered 

in this study are the savings (defined in terms of economic 

losses avoided) realized when geologic map information is 

considered in a public-domain land use decision. Benefits 

accrue when regulatory decisions are made from geologic 

maps that contain improved information. These benefits are 

realized as a reduction in the level of uncertainty of 

information (geologic map information in this case) that 

serves as the basis for implementing land use regulations. 

This concept is explained in the following paragraphs.

Any economic decision is accompanied by some level 

of uncertainty. Is enough scientific information available to 

make the best decision? This study examines how geologic 

map information might enter the framework of such a 

decision. For the Nation, the available geologic maps vary 

widely in detail and in vintage. Differences in the amount 

and the detail of geologic maps in an area considered for a 

land use decision have an impact on financial decisions, 

because newer, more detailed geologic maps would be 

expected to provide a better data base for decisions than 

older, less detailed maps. Improvements to the quality of 

the geologic information for an area, therefore, should yield 

societal benefits that can be described as economic losses 

avoided. Expected reductions in property values due to 

adverse environmental impacts can be minimized. This 

study addresses this societal issue in a rigorous, quantitative 

fashion and finds that society indeed benefits from decisions 

based on improved geologic data.

Financial decisions that rely in part on geologic map 

information include issues related to environmental preservation, hazard mitigation, and mineral extraction. We 

examine two issues, landfill siting and major highway 

construction, relevant to an area of rapid urban growth, the 

Washington, D.C., metropolitan region. Landfill siting is a 

significant environmental and economic issue because of 

the potential shortage of available sites and the threat to 

water supplies from leakage of hazardous substances from 

landfills. Selection of a transportation corridor is also an 

important long-term decision that has a geologic compoIntroduction
nent: right-of-way, construction, and maintenance costs for 

these corridors are influenced by local variations in nearsurface geology, which affects, for example, cut-and-fill 

requirements that ensure slope stability. The study area was 

selected in part because new geologic mapping by the 

USGS provided the opportunity to compare land use decisions made with the new and improved geologic map 

information to decisions that would have been made without 

the information. The method outlined in this report is not, 

however, specific to these two issues or to this single 

location. The report develops a general model that can be 

applied to other issues and in other parts of the United 

States.

A fundamental consideration in this model is: What 

impact does the application of geologic map information 

have in the process of land use decisionmaking? We 

examine how geologic map information can provide input 

to a financial decision, at what stage of the decisionmaking 

process the information is useful, and if that information 

would be compelling enough to alter a decision. We test the 

relevance of geologic map information in an economic 

framework. This is known as an "ex ante" approach because 

future decisions are evaluated. A contrasting approach 

would utilize an "ex post" analysis: improvements that have 

actually accrued from the use of a geologic map would be 

evaluated and compared to a hypothetical situation that 

predicts economic conditions if that map information had 

not been available. That approach examines the cost effectiveness of using geologic map information in a known 

decision. By contrast, this study examines the more fundamental question, what is the future economic impact of the 

application of geologic map information in land use decisions?

An analytical approach has been developed to evaluate the monetary value (the benefits) of utilizing geologic 

maps in future land use decisions. The net benefit of any 

geologic map can be described as the "expected loss 

avoided" that arises from using the geologic map, minus the 

cost of producing and disseminating the map. However, the 

societal value of improved geologic map information 

(improvement of a geologic map consists of a greater 

density of geologic observations per unit area and (or) the 

use of more up-to-date concepts relating to geologic processes) is the difference between the net benefits associated 

with using improved geologic map information and the net 

benefits associated with using existing geologic map information of the same area.

Benefit Estimation

In the remainder of this section, we briefly discuss 

certain technical prerequisites and assumptions for the 

development of the economic model used to value geologic 

map information. Discussion is expanded later in this 

Introduction and in chapter II. Technical considerations

include the manner in which we treat the geologic map 

information and execute the model. For the land use issues 

to be studied, both improved maps and preexisting maps 

were evaluated for information uncertainty in a computerized GIS. The geologic map information was converted into 

a probability or likelihood map of an environmental hazard 

such as ground-water contamination from a leaking landfill. 

To evaluate the role of this information in a decision and to 

forecast net benefits, we examined the existing regulations 

(in which the decision is framed) by use of geologic maps. 

In addition, we developed hypothetical regulations based on 

geologic criteria to supplement existing regulations. Implementation of these hypothetical regulations for the 

improved and for the preexisting geologic map information, 

when combined with economic data, yields two estimates of 

expected property losses that could be avoided for the 

hazard. Comparison of expected losses avoided for the 

improved and preexisting geologic map information provides a measure of net benefits of the improved geologic 

map information. Discussion of the results of the pilot study 

begins with consideration of public risk and the need for 

regulation.

When individuals perceive a risk in their daily lives, 

one possible response is to require the public sector to 

remove this risk through regulation. Regulatory agencies 

such as the EPA employ geologic map information in 

setting environmental safety standards. The public agency 

chooses to implement the safety standard after evaluating, 

on the basis of the best available information, whether a 

hazard could be present in a specific location. However, 

uncertainty regarding the true geologic conditions at a 

location remains. As such, the required regulatory safety 

standards for a specific land use could be either lower or 

higher than ideal because of a lack of suitable geologic map 

information.

In the case of natural hazards, the prevailing approach 

is for broad-based standards. For instance, the Uniform 

Building Code, which is a minimum standard for residential 

and commercial construction, distinguishes three risk zones 

for earthquakes in California. Buildings are constructed on 

the basis of this standard of information. If more detailed or 

improved geologic map information and seismic data were 

available to improve the determination of site response, 

these restrictions might need to be adjusted, either up or 

down, in order to achieve a desired level of safety at a 

minimum cost.

The presence of geologic uncertainty means that the 

regulatory process is capable of generating errors involving 

either underregulation or overregulation of land uses within 

a geographic region; either case must result in a welfare loss 

to society. From the economic point of view, this is a 

departure from the optimal level of regulation (zero net 

marginal expected loss avoided losses that could be 

avoided with geology-based standards). The benefits of the 

improved geologic map information can be expressed as the

Environmental Decisionmaking with Geologic Maps
change in the expected loss avoided through regulations and 

the costs expressed as the costs associated with acquiring 

the improved information.

An economic model, presented in depth in chapter II, 

was developed to calculate the expected loss avoided that 

results from using improved geologic map information. 

This model was applied in Loudoun County, Virginia, for 

two actual land use decisions involving (1) the potential 

locations for a county waste disposal facility and (2) the 

choice of a route for an interstate-type highway known as 

the Washington Bypass. Use of the model suggests that 

when geologic-map-based regulations are implemented, 

there is an incremental change in expected property loss and 

mitigation cost avoided between using the existing county 

geologic map information and using a new, more detailed 

county geologic map. This incremental change represents 

the value of the improved geologic map information.

The model is designed to consider a land area that 

could be used for many different purposes. In order to frame 

our analysis, a single use of the land is assumed, for 

example, as a waste disposal facility or as a transportation 

corridor. For statistical analysis, the geologic maps of the 

area were divided into even-sized square cells. Subdividing, 

or "gridding," a map into blocks or cells is the commonly 

used approach to derive map information for a statistical 

analysis. For the maps used in this study, grid cell size was 

dictated by map scale (larger cells for the map of less 

detailed scale, and smaller cells for the more detailed map). 

Within each of these cells, the geology can be characterized 

by a variety of criteria. In our example applications, the 

available geologic map information at different vintages and 

scales for the same land area is used to produce derivative 

maps of geologic attributes such as rock permeability (a 

measure of the ease of fluid flow) and shear strength (a 

measure of the internal resistance to shear stress).

The model assumes that regulations have been promulgated that depend on the geologic map information for 

each cell. Depending upon the geologic attributes of materials within the cell, implementation of the regulation can 

eliminate the location from further consideration for a 

particular land use such as a site for a waste disposal 

facility. The regulations, in effect, define a level of safety 

that places restrictions on land use. In the case of the waste 

disposal site, safety increases as the amount of inappropriate land subjected to consideration decreases. Thus, safety 

is linked implicitly to the amount and quality of available 

information.

For some data, such as geologic map information, a 

probability of encountering an unsafe condition can be 

derived; however, this probability includes a random error 

component. Using traditional statistical techniques, we 

estimate the mean and standard deviation for geologic 

attributes that are derived from a geologic map. The 

geologic attributes and their statistical parameters are an 

integral part of applying the hypothetical regulation. The

agency can regulate by accepting those cells that meet the 

regulatory standard within some confidence level (such as 

95 percent, which allows for two-standard deviations from 

the predicted mean for the geologic characteristic covered 

by the regulations). This practice allows the agency to "err" 

on the side of accepting cells that have a mean that exceeds 

the regulatory standard but for which the mean plus or 

minus two standard deviations meets the regulatory standard.

The vintage and scale of a geologic map affect its use 

in the decision process. New regional geologic maps are 

commonly produced at more detailed scales than existing 

maps. At the new map scale, faulting may be more clearly 

delineated and boundaries between different rock units 

better defined than on the older, less detailed maps. This 

enhanced precision is possible because the newer map is 

generally based on more detailed, systematic observations 

of rock units. Access to a more detailed and modern 

geologic map yields better information (a reduction in 

uncertainty), and as a result a different number of cells are 

acceptable according to the regulatory standard.

For this demonstration study, regulations were developed by applying hypothetical (but realistic) rules based on 

geologic attributes. All cells within the study area are 

considered acceptable for a proposed land use unless they 

are determined not to be in conformance solely due to 

geologic conditions. The assessment is based on the hypothesis that the regional geologic setting influences the likelihood of hazard occurrence and that geologic map information can improve regulatory decisions. Other regional and 

site-specific variables such as hydrologic and topographic 

attributes also exert influence on the problem, in addition to 

the geologic attributes.

THE LOUDOUN COUNTY PILOT STUDY

A model was implemented for the siting of a waste 

disposal facility and the siting of a new interstate-type 

highway route in Loudoun County, Virginia (fig. 2). We 

assumed that these projects will go forward. We did not 

consider the benefits and costs of the projects themselves, 

but we restricted consideration to the benefits and costs of 

utilizing geologic map information in the site-selection 

procedure.

The Loudoun County population, commercial base, 

and road network are each divided in a manner that mirrors 

the underlying geologic framework. The western portion of 

the county (west of U.S. 15) is largely an upland region 

underlain by a complex group of igneous and metamorphosed sedimentary rocks of the Blue Ridge province. East 

of U.S. 15, the county plan has delineated large tracts of 

land for intensive regional growth. These tracts are underlain by part of a Mesozoic basin (Culpeper basin) filled with 

a sedimentary sequence of conglomerates, red siltstones,

6 Introduction
\ LOUDOUN COUNTY, VIRGINIA

Figure 2. A location map of Loudoun County, Virginia, showing the position of various 

cultural and geographic features.

clay stones, and sandstones that are faulted and interlayered 

with massive basalt or intruded by diabase dikes and sills. 

This geologic setting provides opportunities for the development of ground-water well fields, the construction of 

public and private waste facilities, and the extraction of 

construction materials. Both the current landfill and the 

proposed routes for a Washington Bypass are located in the 

eastern part of Loudoun County, so this part of the county 

was selected as the study area.

For this analysis, land use choices were based on two 

geologic maps of different scale and vintage (fig. 3), a 

geologic map of Virginia compiled and published at 

1:500,000 scale in 1963,3 and a preliminary version of a

geologic map of Loudoun County prepared by the USGS at 

1:100,000 scale in 1992. 4

The 1963 geologic map of Virginia shows the general 

distribution of three different rock units in eastern Loudoun 

County. The rock units on the map and the boundaries 

(contacts) between them are approximately located and in 

many instances are accurate only to the nearest 1.5-2 km. 

The spatial distribution of rock units on the 1963 map was 

derived by extrapolation from previously published maps 

and reports on the area, not from new, onsite observations.

The preliminary version of the 1992 USGS-prepared 

geologic map of Loudoun County, Virginia, shows the 

specific distribution of 16 separate rock units in the eastern

3 Geologic Map of Virginia, 1963, compiled by R.C. Milici, C.T. 

Spiker, Jr., and J.M. Wilson. Charlottesville, Virginia Division of Mineral 

Resources.

4 Geologic Map of Loudoun County, Virginia, 1992, Burton, W.C., 

Froelich, A.J., Schindler, J.S., and Southworth, C.S., U.S. Geological 

Survey Open-File Report 92-716.

The Loudoun County Pilot Study
- Diilles Airport

i\

Y

/ /- Dulles Airport

Figure 3. Geologic maps of eastern Loudoun County, 

Virginia. A, Part of the 1963 Geologic Map of Virginia 

(Virginia Division of Mineral Resources). Green = sedimentary rocks (sandstone and shale undivided), pink = 

igneous rocks (diabase and gabbro undivided), and blue 

= conglomerate (a coarse-grained sedimentary rock). B, 

Part of a preliminary version of the 1992 USGS Geologic

Map of Loudoun County, Virginia (Open-File Report 

92-716). Greens and blues = sedimentary rocks (sandstones, siltstones, and conglomerates), pinks and orange 

= diabase and basalt rock units, and darkest blue = 

limestone conglomerate of particular importance to this 

study.

part of the county. 5 These 16 separate rock units and the 

boundaries between them are located with an average 

spatial resolution of about 60 m (meters). This map is based 

on at least 16 actual onsite observations per square kilometer for the approximately 500-km2 area of eastern Loudoun 

County.

In our analysis, both geologic maps of eastern 

Loudoun County were first converted to digital format. 

Next, the permeability (as average ground-water yield in 

gallons per minute) and average shear strength were calculated for each rock unit. These geologic-map based 

attributes are only one subset of the earth science data 

needed to conduct comprehensive land use analyses. If the 

approach developed in this study were to be incorporated 

into an actual regulatory process rather than a demonstration, more precise measures would be obtained and used,

5 Some of the rock units are not discernible on this map (fig. 3) 

because the subtle color changes between rock units are difficult to 

reproduce in the printing process.

such as water migration through the rocks. To treat the 

geologic map data quantitatively and to conduct the statistical analysis, we intersected the derivative maps of average 

yield and average shear strength with a grid of 1-km x 

1-km cells for the 1:500,000- scale map and a grid of 250-m 

x 250-m cells for the l:100,000-scale map. Formatting and 

manipulation of all the data layers used for these statistical 

and spatial analyses required geographic information system (CIS) relational data-base techniques.

Case A: The Siting of a County Landfill

Leakage of hazardous materials from waste facilities 

and landfills poses a threat to the Nation's water supply. 

There is a direct correlation between the rate of transport of 

dissolved and suspended contaminants away from a site and 

the permeability, faulting, and fracturing of the surrounding 

geologic materials. Changes in subsurface conditions that 

reflect local variations in the geology near a disposal facility 

can affect both the rate of transport of contaminants and the 

areal extent of contamination.

8 Introduction
Substantial costs are incurred in reducing the risk of 

water contamination. To protect ground-water supplies 

from irreversible or irreplaceable losses and to protect 

surface-water supplies from contamination, Federal and 

State regulations require the use of a variety of engineering 

solutions at waste sites. These solutions range from construction of lined sites with buffer zones to highly sophisticated integrated engineering and monitoring techniques to 

clean up contaminated sites.

In 1989, Loudoun County received results of a 

contracted engineering analysis that evaluated all areas of 

the county for suitable landfill sites. Recommendations to 

the county about suitable sites are based on the size of the 

landfill required for the projected quantity of waste through 

the year 2015; this estimate is based on the population 

growth rate in Loudoun County. According to the report, 

Loudoun County will generate at least 3.3 million tons of 

solid waste for a population of 246,000 in the 20-year 

period from 1995 to 2015. The disposal of this quantity of 

waste requires a landfill with a capacity of over 9 million 

cubic yards. Assuming the need for this capacity in a single 

landfill site, the consultants concluded in their report that 

less than 15 percent of the total land area of the county 

seems capable of surviving the permit process.

In our demonstration study, we assumed the consultant's report had not been prepared, so as not to bias the 

site-selection process. Further, we assumed that the waste 

disposal site must be located in the eastern portion of the 

county to minimize transportation costs and traffic congestion.

In the following discussion, we describe an expanded 

role for geologic map information in the decisionmaking 

process for potential sites for waste disposal facilities. In 

contrast to the general approach of promulgating environmental regulations that use demographic and cultural protocols as well as scientific data, our approach uses physical 

measures derived exclusively from geologic map information as the initial basis for regulatory decisions.

We implement the following procedures to estimate 

the value of the improved geologic map information relative 

to the existing information in siting a landfill. For this 

application, we assume that a regulator will have a tendency 

to underregulate in his approach to this issue. With 

improved geologic map information, better siting decisions 

can be made, meaning that more environmentally sensitive 

areas would be restricted.

Step 1: The suitability of a cell on each geologic map 

for a landfill is determined on the basis of rock 

permeability (average ground-water yield).

A cell is considered unsuitable if any or all of the 

following physical conditions exist:

a. presence in the cell of the limestone conglomerate 

geologic map unit (a highly permeable material 

prone to sinkhole development and currently used

as a restriction under Virginia State Regulations

for siting waste disposal facilities); 

b. presence of other rock units that have high

ground-water yields; 

c. presence of faults and associated intense fracturing

of rock units in the cell (generally increases the

ground-water yield).

The implementation procedure for step 1 is detailed in 

chapter II of this report. The results of step 1 are shown in 

figure 4.

Using the test for suitability in step 1, we estimate the 

potential property losses that could be avoided (steps 2-4).

Step 2: For each cell on each geologic map, a probability of contamination is estimated as a function of the 

average yield.

Step 3: The monetary value of the property in each cell 

is estimated for each map.

In this application, only property value losses are 

estimated. We do not attempt to quantify the expected value 

of health effects or economic disruption that would ensue 

from a contamination incident in the county. On the basis of 

recent real estate transactions, an average residence in the 

eastern part of the county is assigned a value of $150,000.

Step 4: For each cell identified as unsuitable for a 

landfill in step 1, the expected property loss avoided by 

not placing a landfill in or near the cell is estimated as 

the product of the probability of a loss and the 

monetary value of the loss (total property value) in a 

cell.

Step 5: Summing the expected loss avoided from each 

geologic map and then taking the difference between 

the two, we obtain the value (marginal benefit) of the 

improved geologic map information.

Proceeding on the basis that the county will need to 

construct one new waste disposal facility, we use this 

analysis to estimate the value of the improved geologic map 

information for selecting one site in the study area. The site 

is assumed to occupy a 1-km2 area to conform with the 

proposed sites described in the 1989 engineering report.

The average difference in expected property loss 

avoided between the two geologic maps for a 1-km2 area in 

eastern Loudoun County is slightly over $1.50 million, 

which is the societal value of the improved geologic map 

information in this application.6

6 Discounting issues are not explicitly considered. If one assumes a 

discount rate of 10 percent and an inflation rate of 10 percent, a formal 

annualizing and discounting step is not necessary. Because this is a 

demonstration, we have made these assumptions.

The Loudoun County Pilot Study
I I Not restricted 

Restricted

I I Not restricted 

^_j Restricted

B

Figure 4. Distribution of cells unsuitable for further consideration as possible sites for a landfill based on (A) the 1963 

Geologic Map of Virginia (Virginia Division of Mineral Resources) and (B) a preliminary version of the 1992 USGS Geologic 

Map of Loudoun County, Virginia (Open-File Report 92-716).

Case B: The Washington Bypass

In any part of the Nation, the geologic framework 

affects choices for transportation corridors. Right-of-way, 

construction, and maintenance costs for these corridors are 

influenced by local variations in near-surface geology and 

topography. Depending on the selected location of the 

corridor, mitigation costs due to geologic variability can be 

significant. Engineering solutions for mitigation range from 

cut-and-fill requirements for slope stability described in the 

Uniform Building Code, Chapter 70, to alternative engineering construction techniques such as building retaining 

walls.

A draft environmental impact statement (DEIS) for a 

proposed new transportation corridor that would pass 

through Loudoun County, known as the Washington 

Bypass, has been prepared by the U.S. Department of 

Transportation, Federal Highway Administration (FHWA), 

the Maryland State Highway Administration, and the Virginia Department of Transportation. According to the 

FHWA, the Washington Bypass is a proposed interstatetype highway that would bypass the Washington, D.C., 

region, provide additional roadway capacity to the region,

improve truck and traffic safety, and provide improved 

facilities for both through-traffic and local traffic.

All proposed Washington Bypass corridors cross the 

eastern part of Loudoun County. Along the many alternative routes within the bypass corridor in Loudoun County, 

the length of road varies from 13.2 km to 42.1 km over flat 

to rolling terrain. The variation in engineering characteristics of geologic materials along any proposed corridor 

means that the possibility of slope failure induced by 

construction also varies along any proposed corridor. The 

possibility of slope failure induced by construction along a 

corridor route is directly related to the shear strength of 

near-surface geologic materials. In a manner similar to the 

one used in the landfill application, expected mitigation 

costs avoided for slope failure induced by construction are 

estimated for all cells in the study area. For this application 

we assume only that a highway route must be selected in the 

study area. In the following discussion we describe an 

expanded role for geologic map information in the siting of 

such a transportation corridor.

In contrast to the current practice of using construction guidelines based on topographic as well as other 

scientific data, our approach (similar to the landfill siting 

application) uses a physical measure, shear strength,

10 Introduction
I I No mitigation 

|^| Mitigation required

Proposed western 

bypass corridor

I | No mitigation 

H Mitigation required

Proposed western 

bypass corridor

B

Figure 5. Distribution of cells requiring mitigation of slope failures arising from road construction, as based on (A) the 

1963 Geologic Map of Virginia (Virginia Division of Mineral Resources) and (8) a preliminary version of the 1992 USGS 

Geologic Map of Loudoun County, Virginia (Open-File Report 92-716).

derived exclusively from geologic map information as the 

initial basis for regulatory decisions.

We implement the following procedure to estimate 

the value of the improved geologic map information relative 

to the existing information in siting a transportation corridor 

such that expected mitigation costs for slope failures arising 

from construction would be minimized. For this application, we assume that a regulator will have a tendency to 

overregulate in his approach to this issue. With improved 

geologic map information, better siting decisions can be 

made (fewer locations along the transportation corridor 

would be expected to require mitigation for slope failure 

arising from construction).

Step 1: Cells that would require mitigation are identified for each geologic map (based on a procedure 

detailed in chapter II).

A cell is considered to require mitigation if there is 

low shear strength for a given slope angle. The results of 

step 1 are shown in figure 5.

In steps 2-4, we use the test for mitigation of slope 

failure that is due to construction (step 1) to estimate the 

potential mitigation costs that could be avoided.

Step 2: For each cell, on each geologic map, a 

probability of slope failure that is due to construction is 

estimated as a function of the shear strength and 

topographic variables.

Step 3: The cost of the required mitigation in each cell 

is estimated for each geologic map.

For the study area, the savings in road construction 

costs (retaining walls) and repairs is calculated for the cells 

that require mitigation by the implementation of the 

geologic-map-based protocol. The mitigation cost avoided 

is assumed to be a $2,000 per meter cost (this figure is 

based on the assumption that both sides of the road would 

require mitigation) for constructing a retaining wall to 

prevent road damage (estimated cost for retaining wall 

construction similar to that along the 1-66 corridor in 

northern Virginia).

Step 4: For each cell identified as requiring mitigation 

in step 1, the expected mitigation cost avoided is 

estimated as the product of the probability of a slope 

failure due to construction and the cost of mitigation in 

a cell.

The Loudoun County Pilot Study 11
Step 5: Summing the mitigation cost avoided from 

each geologic map and then taking the difference 

between these values, we obtain the value (marginal 

benefit) of the improved geologic map information.

Depending on the final choice for the location of a 

proposed transportation corridor in eastern Loudoun 

County, the difference in expected mitigation cost avoided 

between the two geologic maps for any cell in the study area 

varies considerably but on average is about $11,000 per 

250-m x 250-m cell. Assuming that any corridor selected 

will cross a minimum of 85 cells and a maximum of 287 

cells (number of cells crossed by the shortest and longest 

proposed routes in the DEIS), the societal value of the 

improved geologic map information in locating an 

interstate-type highway corridor in eastern Loudoun County 

ranges between $935,000 and $3,157,000.

NET BENEFITS OF GEOLOGIC MAP 

INFORMATION

The purpose of this analysis has been to develop and 

implement a methodology for estimating the societal value 

of improved geologic map information. We have derived 

the benefits of using the improved geologic map information for two applications. In this section, we estimate the net 

benefits (benefits minus the cost of producing the improved 

information) of this improved geologic map information.

Cost To Produce Geologic Map Information for 

Loudoun County

Loudoun County occupies approximately 1 ,400 km2 , 

an area equivalent to about ten 7.5-minute (l:24,000-scale) 

quadrangles, or about one-third of a 30 x 60 minute 

(1:100,000-scale) quadrangle. A number of areas within the 

county have been mapped geologically for other purposes in 

the past with varying quality and density of observations; 

these areas have been interpreted and reinterpreted over the 

last century as different paradigms for geologic understanding were developed, tested, and refined or abandoned. The 

current USGS geologic mapping project in Loudoun 

County, therefore, requires both new geologic mapping and 

compilation and reinterpretation of existing geologic map 

information. Total costs for the improved geologic map 

information, the 1:100,000-scale USGS geologic map, are 

projected to be about $1,160,000 distributed over 6 years. 

These costs include an opportunity cost of capital compounded semiannually at 10 percent during the production 

period. The project cost is about $968,000, and interest is 

$189,000. For the project, the capital and operating costs 

are $913,000 and $55,000, respectively. Capital costs

include utilization of plant and equipment and personnel, 

while operating costs include daily expenses and supplies.

Net Benefits of Improved Geologic Map 

Information

The expected net benefit of using the improved 

geologic map information (the modern USGS 1: 100,000- 

scale geologic map), derived from just two of the many 

situations that require geologic data in Loudoun County, is 

the gross benefit derived from the use of the improved 

geologic map information ($2.44 to $4.66 million for the 

two case studies described above) minus the cost of producing that geologic map ($1.16 million). Therefore, the 

expected net benefit (societal value) for the two applications 

of the 1: 100,000-scale Loudoun County geologic map 

ranges from about $1.28 million to $3.50 million.

The United States covers an area greater than 17,000 

times the area of eastern Loudoun County, Virginia. Two out 

of many possible applications of improved geologic map 

information in this small area have been shown to be of 

significant value to society. An improved geologic map data 

base for the Nation will result in enormous savings if properly 

applied to balanced land management decisions. The issue of 

whether all applications of improved geologic map information 

will yield positive net benefits is unknown. We do know that in 

regions that exhibit economic growth, improved geologic maps 

will be increasingly important for making decisions that relate 

to the revitalization of the Nation's infrastructure, for avoiding irreversible environmental impacts, and for mitigating 

effects of natural hazards.

ACKNOWLEDGMENTS

The cooperation of the following individuals and 

organizations is acknowledged: Mitchell Reynolds, George 

Ulrich, and Paul Stone (USGS Office of Regional Geology); Wayne Newell, Al Froelich, Ron Parker, Lucy 

McCartan, and Jerry Spears (USGS Branch of Eastern 

Regional Geology); USGS Water Resources Division, especially Keith Robinson and Curtis Price (Trenton) and Donna 

Belville (Richmond); New Jersey Department of Environmental Protection, with special thanks to Michael Winka 

and Fred Bowers; the U.S. Environmental Protection 

Agency, in particular Charles Carpenter and Neal Durante; 

and Richard Weber, Director, the Loudoun County Department of Environmental Resources. This paper benefited 

greatly from review of an early draft by several of our colleagues in the Water Resources Division and from review of 

the final draft by Steve Gillespie, Ozzie Girard, and Carl 

Shapiro. We thank Mitch Snow for his help in making the 

report more "readable." Pattie Lett demonstrated both skill 

and patience in preparing the numerous drafts of this 

manuscript. Finally, a special thanks goes to Joel Kaplan, 

who suggested that a study of this type had merit.

12 Introduction
Chapter

Geologic Maps: Fundamental Data Base for the Earth 

Sciences

INTRODUCTION

This chapter describes what geologic maps are, why 

they are needed, what kinds of information they contain, 

how they are used, and how much it costs to make them.

What Is a Geologic Map?

A geologic map is a graphical information display 

that uses a combination of colors, lines, and symbols to 

depict the composition and structure of geologic materials 

and their distribution across and beneath the landscape. The 

graphical display contains both descriptive information 

about geologic units and structures and an interpretive 

model of how they were formed. This combination of 

descriptive and interpretive geologic map information provides a conceptual framework that relates all the geologic 

elements of an area together so that the position, characteristics, and origin of each element are understood in relation 

to all other elements. Such a unique synthesis of descriptive 

and interpretive information makes the geologic map a 

powerful research tool for understanding the Earth's composition and structure, internal and external processes, and 

history.

The standard geologic map is a general purpose 

product; that is, it conveys essential information about 

many aspects of the geologic setting, not just one or a few 

aspects. For a prescribed area, such a map might identify 

bedrock formations like granite, limestone, sandstone, or 

shale and their altered or mineralized equivalents; surficial 

units like soils, landslides, and sediment deposited by 

streams, wind, glaciers, and hillslope processes; and geologic structures like folds, faults, and fractures. A single 

general purpose geologic map thus provides a comprehensive record of a diverse suite of geologic features, and this 

characteristic makes the map a primary data base for a broad 

range of societal and scientific applications.

Why Are Geologic Maps Needed?

The regional geologic map is universally recognized 

as the instrument of choice for planning and executing 

research and decisions that involve earth science information (National Research Council, 1987, 1988). Its utility 

and value derive from the fact that the unique information 

content of a geologic map can be used to characterize the

geologic setting of a specific site in the context of the 

surrounding region. Scientists, decisionmakers, and managers can extrapolate the results of site-specific investigations outward to adjacent sites or regions where investigations have not been conducted and thereby forecast or 

predict geologic conditions where data are limited. The 

regional geologic map forms a fundamental data ba^e for 

earth science applications that require a predictive capability (geohazards evaluation, resource assessment, enT 'ironmental analysis).

In order to understand why geologic maps are 

needed, we must first understand and appreciate th? role 

that solid-earth materials and structures play in day-to-day 

activities. Consider the following situations:

1. You are a home buyer. You and your family are moving 

to a part of the United States where you have no firsthand information concerning the nature of the land its 

water hazards, atmospheric hazards, and geologic hazards. You probably would not have the time, resources, 

or inclination to pursue such information through your 

own independent research, so you might turn to some 

publicly accessible source such as a municipal, county, 

or State planning or regulatory commission that already 

has incorporated technical information into zoning and 

setback provisions. But where did these surrogates 

acquire their information, and what assurances di you 

have that their information was comprehensive, well 

documented, and up to date?

2. You are on the seismic-safety panel of the planning 

commission for a county undergoing rapid urban expansion. What planning tool do you use to develop countywide hazard-zonation maps that extrapolate regionally 

the results of a small set of site-specific investigations 

that indicate the potential for landslides, liquefaction, 

subsidence, and strong ground shaking?

3. You are a land use planner for a municipal, county, 

State, or Federal commission charged with the balanced 

use of lands that must accommodate multiple derrands, 

which include agricultural, residential, recreat: onal, 

commercial, industrial, and mineral-, energy-, and 

water-resource uses. What planning tools do you tirn to 

in order to evaluate solid-earth factors that contrib'ite to 

multiple-use decisions?

Introduction 13
4. You are a mineral-, energy-, or water-resource exploration manager. What planning tool do you use to identify 

terranes that are likely to host earth resources? Once you 

have identified favorable terranes, what planning tools 

do you use to select exploratory drilling or grid-sampling 

sites, given that your exploration budget does not have 

room for a trial-and-error strategy and given that you 

must project your limited site-specific information 

across areas or regions where information is sparse?

5. You are a research scientist who develops new models 

for how the solid earth is formed. What research tool do 

you turn to that illustrates three-dimensional relations 

among geologic materials and structures so that you can 

examine the position and origin of each geologic element in relation to the others? Without some means of 

displaying spatial and geometric relations among geologic materials, would you be able to formulate a 

complete model for how these materials formed?

Answers to these questions depend to a large degree 

upon spatially based geologic information that is linked to 

geologic materials and geologic structures. The geoscience 

product that captures and displays this kind of information 

is the geologic map.

What Kinds of Scientific Information Does a 

Geologic Map Contain?

Geologic maps display a broad range of information 

attributes.

Physical properties. Geologic maps provide geotechnical information about each geologic unit and structure, including attributes such as mineralogic composition 

and physical properties, weathering or chemical alteration, 

thickness, degree of consolidation or hardness, relative 

density, and the orientation and spacing of fractures, faults, 

and folds. These attributes are important because they 

determine characteristics such as the strength, transmissivity, and continuity of geologic materials and structures.

Three-dimensional geometry. Through information 

attributes that describe the geometric orientation of geologic 

materials and structures at the Earth's surface, a geologic 

map interprets the three-dimensional shape of geologic 

materials in the subsurface, including (1) the lateral distribution of rock bodies and geologic structures and (2) 

changes in orientation that occur between measurement 

stations.

Relative age relations. Geologic maps provide 

information about the timing and sequence of events that 

produced the geologic materials and structures displayed on 

the map. The timing of one geologic event relative to 

another is important because many basic- and appliedresearch applications keyed to a particular geologic unit or 

structure depend on the chronology of the formation of a 

unit or structure relative to other units and structures.

Relation between geologic form and geologic process. A geologic map allows the map use- to understand 

the geologic processes that produced the materials and 

structures portrayed on the map. As the user understands the 

genetic processes that gave rise to the physical properties 

and geometric configuration of geologic map units or 

structures, the scope and usability of a given piece of 

geologic map information increases.

How Is a Geologic Map Used?

Because of its comprehensive information content, a 

geologic map is the primary data base for a broad range of 

societal and scientific applications. A graphic representation of the primary data is shown in figure 1-1. Each 

specialized application extracts one or mc^e information 

attributes from the general purpose geologic map and 

combines these attributes into special purpose derivative 

maps that address specific geologic features, processes, or 

applications. Derivative maps can be genera*ed by distilling 

selected information from the primary dr*a base or by 

developing and expanding a particular part of the primary 

data base through follow-on specialized investigations. The 

geologic map thus should be viewed as a first-order information layer that can be combined with information layers 

from other geologic, geographic, hydrok'nc, or demographic disciplines.

ENVIRONMENTAL ANALYSIS

Waste Repository Siting

Issue: How does geologic map information help select the 

threshold level of acceptable risk in siting a vaste repository 

facility?

Geologic-map-based information bears directly and 

indirectly on factors that are used to site waste repository 

facilities: (1) geologic maps depict the area! distribution of 

geologic hazards likely to threaten a repository site (earthquake faults, slope failures, ground subsidence); (2) they 

depict the surface and subsurface distribution of permeable 

geologic materials whose transmissivity potential would 

exacerbate the effects of leakage from a wrste repository; 

(3) they depict the distribution of geologic materials whose 

geotechnical properties are compatible with the engineering 

specifications of the repository facility; (4) tvey identify the 

potential for co-located geologic resources (clay, sand, and 

gravel resources, energy resources, ground-water resources) whose development might be compromised by siting a 

waste facility in an area for which the multiple-resource 

potential had not been determined; (5) tvey depict the 

distribution of geologic materials and structures that would 

affect the size and spacing of buffer zone"; and (6) they 

depict the distribution of geologic material more or less 

likely to shake strongly in response to eartl -wake energy.

14 Geologic Maps: Fundamental Data Base
petroleum-bearing 

sandstone

A Geologic Map:

1. Facilitates land management

Critical facilities

Hazardous waste repositories

Regional economic development

2. Locates natural resources

Water 

Energy 

Mineral 

Industrial

3. Identifies geologic hazards

Earthquake faults 

Landslides =^ 

Land subsidence 

Radon

u

- EARTH'S SURFACE

- BELOW EARTH'S SURFACE

Figure 1-1. A graphic representation of some of the typical information contained in a general purpose geologic map 

and some of the many applications of that information. A geologic map can be used to identify geologic hazards, 

locate natural resources, and facilitate land use planning.

Regional Ground-Water Quality at Risk from 

Point-Source and Nonpoint-Source 

Contamination

Issue: How does geologic map information help identify the 

threshold level of acceptable risk for ground- and surfacewater contamination?

Geologic-map-based information is essential to the 

estimation of the vulnerability of regional ground-water 

reserves to point-source and nonpoint-source contamination: (1) on a regional basis, geologic maps depict the areal 

distribution and subsurface configuration of geologic materials that store ground water or that recharge the groundwater reservoirs; (2) geologic maps depict the areal distribution and subsurface configuration of geologic materials

whose layering characteristics and geotechnical properties 

are conducive to the transmission of ground-water contaminants and to the trapping and storage of contaminants; and 

(3) geologic maps depict the areal distribution and subsurface configuration of geologic materials that form barriers 

to the flow of ground water, which is the source of 

dissolved mineral constituents, or that lead to perched 

ground-water conditions.

Site-Specific Ground-Water Sources

Issue: How does geologic map information help locate 

site-specific ground-water sources?

Geologic-map-based information forms the basis for 

locating site-specific ground-water sources: (1) geologic

Environmental Analysis 15
map information defines the local distribution and subsurface configuration of geologic materials that contain ground 

water; (2) geologic maps depict the distribution and subsurface configuration of geologic materials that form barriers 

to and conduits for the flow of ground water or that lead to 

perched ground-water conditions; (3) geologic maps portray 

the distribution of geologic materials and structures that 

affect the size and position of buffer zones; and (4) geologic 

maps portray the distribution and types of materials in 

potential ground-water recharge areas and may improve 

estimation of recharge rates or long-term reliability of a 

ground-water source.

GEOLOGIC-HAZARD RECOGNITION

Earthquake Potential and Earthquake Hazards

Issue: How does geologic map information help identify the 

threshold level of acceptable risk for earthquake-induced 

property damage and loss of life?

Geologic maps provide three kinds of information 

essential for the evaluation of earthquake potential: (1) they 

identify faults whose field characteristics indicate geologically recent activity; (2) they demonstrate geometric relations among different faults so that they can be analyzed as 

an integrated system rather than as isolated features, 

because seismic activity in a region is a product of faults 

whose dynamic interaction must be understood before 

meaningful forecasts can be made about earthquake potential; and (3) through geometric relations between faults and 

other geologic units, geologic maps can document the 

long-term geologic history of faults so as to provide a 

context for instrumentally determined estimates for future 

earthquake activity. Geologic maps provide three kinds of 

information essential for evaluating earthquake hazards: (1) 

they identify the areal and subsurface distribution of geologic materials that have different ground-shaking and 

ground-response potential; (2) they identify active fault 

lines that are likely to yield ground rupture; and (3) they 

distinguish different types of faults that are likely to 

generate different kinds and amounts of seismic energy.

Landslide Potential and Landslide Hazards

Issue: How does geologic map information help identify the 

threshold level of acceptable risk from landslide hazards?

Geologic maps provide three kinds of information 

essential for the evaluation of landslide potential and 

landslide hazards: (1) they identify geologic materials that 

are conducive to slope failure because of their intrinsic 

geotechnical properties; (2) they identify geologic terranes 

that have generated landslides in the recent geologic past; 

and (3) they demonstrate geometric relations between 

landslide-prone terranes and other geologic structures

(faults, folds) so that landslide potential can be understood 

as a product of geologic processes other than simply a 

product of parent material and slope conditions.

Volcanic Potential and Volcano Hazards

Issue: How does geologic map information help identify the 

threshold level of acceptable risk from hazards imposed by 

volcanic activity?

Geologic maps provide three kinds of information 

essential for the evaluation of volcanic potential and volcano hazards: (1) they identify the general geologic setting 

of a region that thereby allows volcanologists to forecast 

one of three or four major types of volcanic activity that 

could be expected to occur in the map area; (2) they identify 

geologic terranes that have been produced by volcanic 

activity in the recent geologic past; and (3) they depict the 

kinds of volcanic processes (high-velocity downhill-flowing 

hot ash clouds, lava flows, mud and debris flows, catastrophic slope failures) that have formed the volcanic map 

units and that could be expected to occur during future 

volcanic activity.

RESOURCE EXPLORATION AND EXTRACTION

Energy Strategy

Issue: How does geologic map information help define a 

develop-or-preserve energy strategy in a multiple-use environment?

Geologic maps provide three kinds of information 

essential for evaluating energy-resource policy: (1) they 

identify the distribution of geologic materials that are hosts 

for various energy commodities (coal, oil and gas, uranium); (2) they identify geologic terranes that hold greater 

potential for the occurrence of an energy commodity of a 

particular quality and quantity; and (3) they provide a basis 

for defining exploration and development strategies and for 

projecting operational costs that depend upon the complexity and scale of the geologic setting.

Minerals Strategy

Issue: How does geologic map information help define a 

develop-or-preserve minerals strategy in a multiple-use 

environment?

Geologic maps provide three kinds of information 

essential for evaluating mineral-resource policy: (1) they 

identify the distribution of geologic materials that are hosts 

for various mineral commodities (precious and base metals, 

industrial minerals); (2) they identify geologic terranes that 

hold greater potential for the occurrence of a mineral 

commodity of a particular type and grade; and (3) they 

provide a basis for defining exploration and development

16 Geologic Maps: Fundamental Data Base
strategies and for projecting operational costs that depend 

upon the complexity and scale of the geologic setting.

BALANCED LAND MANAGEMENT

Regional Economic Development Decisions

Issue: How does geologic map information help define a 

develop-or-preserve land strategy in a multiple-use environment?

Geologic, hydrologic, and topographic features and 

processes interact in a generally predictable way in a 

dynamic environmental system. Some of these physical 

variables are static in the time frame of human activities: 

even though the variables play a critical background role in 

guiding cultural, political, and economic development, they 

neither trigger dramatic changes in human activities nor are 

they themselves altered by such activities. However, other 

physical variables are more dynamic in relation to human 

activities: they can induce dramatic responses in cultural, 

political, and economic development (the social and economic impact of earthquakes, ground- and surface-water 

cycles, landscape evolution), and, additionally, the variables themselves can be altered by human activities. For 

example, patterns and rates of land use can induce changes 

in resource availability, rates and patterns of runoff and 

recharge, and rates of landscape erosion, sediment transport, and sediment accumulation. As the environmental 

system is modified by natural processes and human activities, the system's capacity to respond to additional perturbations also changes.

Environmental changes resulting from either natural 

or human causes influence decisions regarding regional 

economic development, environmental preservation, and 

resource allocation. Options proposed for preservation and 

development each have associated opportunity costs (opportunities foreclosed by taking a particular action): (1) a 

decision to preserve an environment may cause delays in 

regional development and thus may alter the value of 

specific parcels of land and (2) alternatively, development 

may provide short-term benefits to the current population 

while causing irreversible effects on the natural environment in the long run. These long-term impacts could impose 

extremely high costs on future generations.

How Much Does it Cost To Produce a Geologic 

Map?

3. Data-base costs (data-base management, publication, 

distribution, and archival costs).

Original investment costs: a multigeneration national 

geologic map data base. Geologic map information at 

some level of accuracy and data density exists for all parts 

of the Nation: for some regions, the available data base 

consists only of reconnaissance-quality information; for 

other regions, the available data base consists of modern, 

interdisciplinary, detailed-scale geologic map information. 

The cost of acquiring new geologic map information for a 

prescribed area will depend upon the technical quality of the 

available data base for that area and upon the demands of 

the perceived application. For some areas, the available 

information need only be revised slightly and releasei in a 

form that compiles the older information in a new format or 

in the context of new interpretive models for the geologic 

materials and structures. In such instances, geologic-map 

production costs will be relatively low. For other are?s, the 

available archival geologic map information is sparse or 

obsolete in terms of modern geologic theory or analytical 

techniques, and new information of greater density and 

accuracy must be acquired to accommodate the perceived 

application. Of importance is the notion that geologic map 

information is not static: as new analytical techniques are 

developed or as new models for how geologic materials and 

structures are formed, the geologic map information in a 

given region must be reexamined for its accuracy and 

precision.

For this analysis, the geologic information base that 

already exists at the time a geologic mapping investigation 

is initiated is an original investment cost, which is a cost 

that has been underwritten by earlier funding initiatives and 

has produced some previous benefit.

Operational costs. These are the costs associated 

with acquiring new geologic map information beyond that 

which already exists in the data base. Operational costs are 

of two kinds: (1) the costs required for the geologic map 

lines and polygons and their associated information 

attributes and (2) interdisciplinary data required fcr age, 

physical properties, and origin of geologic materials and 

structures.

Data-base costs. These are the costs associated 

with managing all aspects of the archival geologic-man data 

base, including cartographic production, data-base management and distribution, publication, and translation to information users.

Several factors contribute to geologic-map production REFERENCES CITED

costs:

1. Original investment costs (costs already assumed in 

order to acquire a certain background level of geologic 

map information for the Nation).

2. Operational costs (costs to acquire interdisciplinary geologic map information of a particular scale and quality).

National Research Council, 1987, Geologic mapping in th? U.S.

Geological Survey: Washington, D.C., National Ac°demy

Press, National Research Council Report, 22 p. 

 1988, Geologic mapping: Future needs: Washington,

D.C., National Academy Press, National Research Council

Report, 84 p.

Balanced Land Management 17

Chapter II

The Societal Value of Geologic Map Information: Use in a 

Regulatory Application

INTRODUCTION

The Issue

The economic value of scientific information is determined within the framework of the decision process: the 

greater the value of the resources to be protected, the greater 

the value of the information. In this chapter we develop and 

apply a model of decisionmaking that makes explicit use of 

modern geologic maps. We compare the benefits of using 

improved geologic information relative to existing map data 

in a regulatory environment. We show that improvements in 

geologic map information have a net positive value to 

society that enables superior land use decisions to be made. 

As a result, greater economic and environmental losses can 

be avoided than if the improved information were not 

available. The value of the information is shown to be the 

net value of the losses avoided.

Geologic maps are applicable to many policy-related 

issues and concerns. We concentrate on the use of geologic 

information for risk assessment. Despite the fact that 

environmental hazards have been a major policy concern, 

their translation into regulatory policies is difficult because 

of the considerable uncertainty surrounding these risks and 

the physical processes that produce them (Lichtenberg and 

Zilberman, 1988). Depending on the accuracy of the risk 

assessment and the stringency of the regulatory actions 

taken to avoid a loss, uncertainties remain that are due to the 

physical attributes not adequately considered in the implementation of generalized regulations governing the planning 

and engineering of a project (Shavell, 1984). To appreciate 

the role of geologic maps in the decisionmaking process 

requires a full description of the decision problem, the 

geologic map information, and the decisionmaking institution, including the preferences of the decisionmaker. We 

consider each of these issues.

Background and Economic Concepts

Land use decisions commonly are made with some 

level of uncertainty regarding actual geologic conditions. 

Errors can be costly. An inappropriate land use may result 

in the failure of a particular investment project or in 

potential adverse environmental impacts.

There have been a few studies of the value of 

information gathered by public agencies for land use decisions. For example, Lind (1973) addresses the optimal 

assignment problem: which land use should be assigned to 

which parcel of land in order to maximize social su-plus. 

The benefits of this information derive from the superior 

land use allocation. We do not consider the optimal assignment problem. Our focus is to evaluate the effect of 

improved geologic map information for permitting a particular land use in terms of threshold geologic conditions.

Roe and Antonovitz (1985) analyze the valie of 

publicly gathered information in agricultural applications. 

The paper demonstrates that this information is a public 

good in the sense that it may be usefully applied in more 

than one decision without the value of the information being 

impaired. Roe and Antonovitz focus on the case in which 

there is uncertainty concerning one attribute, and information is made available for this attribute. They di not 

consider the value of this information in a regulatory 

decisionmaking process.

Lichtenberg and Zilberman (1988) and Lichtenberg 

and others (1989) explicitly incorporate the impact of the 

uncertainty of the information gathered by public agencies 

when policy is being set. In their framework, there is a risk 

associated with an action, and this risk has uncertainty 

associated with it (that is, the hazard has both an expected 

value and a nonzero variance). The uncertainty is an 

important element of the decisionmaking process. A hazard 

is defined by both the risk, which is the expected vahn, and 

the uncertainty, which is the dispersion. The decisionmaker's problem is to set a regulatory safety standard that will 

be violated not more than some given fraction of the time. 

That is,

Prob {R<RQ}> P

where RQ is the regulatory standard, R is the actual level of 

risk exposure, and P is the margin of safety defined as the 

inverse of the frequency with which the standard is violated. 

P functions much like the confidence interval in statistical 

hypothesis testing. The level of safety can be increased by 

raising RQ or by lowering P. In the Lichtenberg and 

Zilberman framework, the level of information is constant. 

Information is useful in this environment because it allows 

the safety standard to increase without necessarily raising 

the regulatory standard. Lichtenberg and others (1S Q9, p. 

31) note, "The mechanism by which a consensus value of 

the margin of safety could or should be established deserves

Introduction 19
further study." In this chapter we explicitly incorporate 

improved geologic map information into the regulatory 

decisionmaking process and show that the value of the 

improved information is determined by its impact on the 

outcome of the process. 1

A regulator is charged with enforcing land use regulations by allowing or disallowing certain uses of parcels of 

land. On the basis of engineering and epidemiological 

information of an adverse land use impact, a regulatory 

standard can be defined, for example, in terms of a 

particular geologic characteristic. The regulation defines the 

level of the safety that can be achieved.

One view of the behavior of regulatory agencies is 

that they attempt to maximize social welfare by imposing an 

optimal level of safety (Scherer and Ross, 1990). The 

optimal level of safety is achieved by permitting a land use 

to occupy a site only when the expected value of the 

regulatory criterion is below (in the case of minimum 

standards) or above (in the case of maximum standards) the 

mandated standard. Behaviorally, regulatory agencies 

choose to ignore the uncertainty (variance) inherent in 

information and focus solely on the risk (expected value) 

when evaluating a parcel of land.

Not all regulatory agencies can be expected to behave 

in this fashion. There is a considerable body of literature 

suggesting that regulatory agencies are "captured" by the 

very groups they regulate and that they produce regulations 

that benefit or, at least, do little harm to the groups being 

regulated (Stigler, 1971; Peltzman, 1976). 2

In the absence of perfect information, the decisionmaker may have a general perspective (a prior) of the 

possible geologic characteristics of an area. This prior is 

formed from existing available geologic map information. 

As the quantity of information increases or the quality 

improves, the uncertainty (variance) of this prior is 

reduced. 3 This new level of information may be used to 

reduce exposure to risk in decisions concerning the allocation of resources. Further, this improved information 

reduces the risk faced by the decisionmaker by decreasing 

the variance around the mean of the geologic characteristic 

being measured. Thus, land use decisions become more 

precise because parcels are rejected as inappropriate on the 

basis of probability distributions that are less diffuse.

If the decisionmaker is risk neutral, he or she allows 

land use types on the basis of expected values, and the 

information that reduces uncertainty (reduces the meanpreserving spread) has no value. If the decisionmaker is

The value of risk reduction is lower for risks that are less well 

understood (have a higher variance). Reducing the variance will also 

increase the return to raising RQ .

It is beyond the scope of this paper to demonstrate all of the forces 

at work in particular settings.

3 Rothschild and Stiglitz (1970) develop a definition of increasing 

risk as a mean-preserving spread in the variable being observed.

averse to risk, then such information does have value (see 

Rothschild and Stiglitz, 1970; Theil, 1971). Finally, if the 

process yields a bias in favor of a certain type of land use, 

the uncertainty regarding the true state of tH geology may 

be exploited to defend an allocation that the decisionmaker 

prefers.

In the case we address, geologic imp information 

contributes to the measurement of several physical and 

environmental attributes of a site. Further, the uncertainty 

about the attributes of a site may be reduced as improved 

geologic map information is acquired. We focus on the use 

of information in the application of an existing set of 

standards rather than in the setting of standards. Geologic 

map information pertaining to the geologic characteristic 

used to determine whether a parcel of land meets the 

regulatory standard is available with some variance. We 

consider the value of improved geologic map information (a 

reduction in the variance) to be derived froir the fact that it 

permits a more accurate application of the existing regulatory standard.

A regulatory agency can base its decis'on on both the 

risk and the uncertainty surrounding this risk. Even though 

the regulatory standard (an acceptable level of risk) is 

defined as some specific value or level for a geologic 

criteria, the true state of the geologic information is known 

only with some certainty (geologic map attributes can be 

represented as a probability distribution). Cn the basis of 

credible scientific information, the regulator would be able 

to accept or reject parcels of land for a given use if the 

standard lies within some interval around th~. mean. Typically, an acceptable interval is defined as berng within the 

95-percent confidence level (or two standard deviations). 

While there is an optimal level of safety based on the 

expected value of the losses avoided, the ac*ual regulatory 

process may lead to a level of regulation that departs from 

this optimal level when the uncertainty is incorporated into 

the decision process. The regulatory agency cannot, however, set a standard arbitrarily low (or high), because the 

oversight committee responsible for the agency's authorization will demand justification for standard that are too 

lax (or too stringent). 4

Specifically, the uncertainty inherent in scientific 

measurement could lead a regulatory agency to make 

implementation errors. For a particular land use issue, 

regulations could be applied to accept parcels of land for 

which the geologic attribute in a specific location plus 

(minus) two standard deviations falls belov (above) the 

regulatory standard. For example, in the case of waste 

facility siting, the potential for contamination can be 

assumed to increase as rock permeability increases. In this 

particular example, the regulation might be that the geologic attribute minus two standard deviations is less than the

4 See Weingast and Moran (1983) for a discussion of the behavior of 

regulatory agencies under oversight.

20 The Societal Value of Geologic Map Information
standard in order for the location to be acceptable. Because 

contamination is an adverse environmental impact, the 

regulation dictates that waste disposal facilities avoid environments in which the rocks near the surface are highly 

permeable. As improved geologic map information 

becomes available, and the variance of the geologic 

attribute likely decreases, we can reduce the number of 

locations that are presumed to be acceptable by using less 

precise geologic maps. Thus, as the geologic map information becomes more specific, we would tend to restrict more 

locations from this land use. We will refer to this situation 

as a case of underregulation. Alternatively, the regulator 

could determine to be acceptable only those parcels for 

which the geologic attribute plus two standard deviations is 

greater than the standard. We will refer to this as a case of 

overregulation. Regardless of whether the agency chooses 

to underregulate or overregulate, improved geologic map 

information will lead to the application of regulatory rules 

that approach an optimal level of safety.

The Empirical Evaluation

We undertake two applications that involve hypothetical land use regulations in which geologic map information 

is applied in the decisionmaking process: the location of a 

landfill and the routing of a highway. In each case the 

regulatory standard is described in terms of particular 

geologic characteristics. This standard is applied as a 

threshold condition for permitting a certain land use. The 

regulatory decision for parcels with existing geologic map 

information and with improved geologic map information 

are compared. From the resulting change in land use 

restrictions, expected losses can be avoided with the 

improved geologic map information. These expected losses 

avoided can be calculated to yield a measure of the benefits 

of the improved geologic map information. The net benefits 

of this improved information are found to be positive for the 

two applications considered. There are many potential 

applications of the information that can be derived from a 

single geologic map. As such, the net benefits reported here 

may be viewed as a conservative estimate.

THE ROLE OF GEOLOGIC MAP INFORMATION 

IN THE MAKING OF A DECISION

Reducing Information Uncertainty with Geologic 

Maps

Chapter I describes geologic map information. For 

purposes of this chapter, we provide a brief description of 

the nature of geologic map information as it applies to 

regulatory decisionmaking. The geologic characteristics of 

a parcel of land are based on the type, structure, and 

engineering characteristics of the rock that are identified

during the geologic mapping. This activity involves observation, sampling, analysis, and interpretation. The resolution of geologic map information generally increases with 

larger scale maps (more detailed) and with newer vintage 

maps.

Geologic maps can be interpreted to provide the basis 

for statistics that infer quantitative attributes about the 

geologic characteristics of a particular parcel of land. More 

detailed (larger scale) maps provide more accurate statistics 

(provide a likely reduction in the variance). In the demonstration of our applications, the available geologic map 

information (at different vintages and scales) for a region is 

used to produce derivative map information showing rock 

permeability and shear strength. A geologic map's vintage 

is an important consideration because it represents the status 

of interpretations, concepts, and models that continue to 

evolve over time. These geologic characteristics are considered important for our applications. Suppose a new 

geologic map of a region is produced at a scale that is more 

detailed than the existing geologic map, as is commonly the 

case. For instance, at the new map scale, perhaps faulting is 

delineated more clearly and boundaries between different 

rock types (contacts) are defined better than on the older, 

less detailed geologic map. Better delineation of the geologic attributes results because the newer and improved 

geologic map is based on more detailed, systematic observations. If this improved geologic map information leads to 

a different number of restricted parcels, then we have a 

measure of the value of the improved geologic map information. The net benefits of this improved information are 

the changes in the expected loss avoided, and the costs are 

the costs associated with acquiring the improved geologic 

map information.

Gathering geologic map information is a challenging 

process because of the scarcity of geologic outcrops, 

scarcity and expense of drill-hole data, and complexity of 

possible geologic interpretations. In general, the density of 

data required for the appropriate level of geologic resolution 

is a function of map scale. At any map scale, geologic 

information has an inherent uncertainty because observations cannot be made everywhere, and extrapolations must 

be made. Thus, the true value of a geologic attribute for a 

location is described by a probability distribution. The 

central point of the probability distribution is the expected 

value of the geologic attribute in a specific location. The 

variance of the attribute corresponds to the variability of the 

geologic attribute over the entire mapped area. This concept 

is illustrated in figure II-1, in which the probability distribution of a geologic attribute is plotted for two different 

levels of information, d\ and d^ corresponding, for example, to existing and improved geologic information. R in 

figure II-l denotes a regulatory standard (threshold), and g^ 

denotes the expected value of the geologic attribute for a 

given locality or parcel of land. The 95-percent confidence 

interval (2a) about the expected value is indicated for the

The Role of Geologic Map Information in the Making of a Decision 21
Figure 11 1. The probability distributions, c/, and d2f of a 

geologic characteristic, gk, for two geologic maps of 

different vintages and different scales, v., and v2 , for the 

same area. R represents a regulatory standard. gk denotes 

the expected value of the geologic attribute for a given 

locality or parcel of land. 2a is the 95-percent confidence 

level about the expected value for the distributions.

distribution d\ as 2crVi . With this information, we fail to 

reject the hypothesis that the allowed standard, R, is met for 

this parcel of land, because it is within two standard 

deviations of the expected value, and HQ: gk 2crv <R.

With improved geologic map information, based on 

larger scale maps or newer field data, we have distribution 

^2- The improved information is more precise and more 

detailed. As such, distribution d*i has less uncertainty (in 

this case, a smaller standard deviation, 2o\,2 than d\. The 

null hypothesis is rejected because the expected value of the 

geologic attribute minus two standard deviations is greater 

than the standard, R.

The rejection of a particular parcel by use of information from ^2 occurs because the information in ^2 is more 

precise, not because there is a bias in the original data, d\. 

Additionally, note that the expected value of the geologic 

attribute has had the effect only of reducing the variance of 

the statistic.

The Inclusion of Geologic Map Information in 

Regulations

Hypothetically, a regulatory agency could employ the 

following procedure to determine the number of parcels 

available for a given land use. 5 Each parcel is tested for

There are additional issues related to each parcel that go beyond 

the question of optimal information and the value of the information. For 

instance, there is the question of the optimal scale of the geologic map 

information for a specific land use application. In this study we are limited 

by the availability of the existing geologic maps. One could easily envision

EXPLANATION 

| | Case of underregulation 

| [ Case of overregulation

1C \K* \K+ \K++ SAFETY

Figure II-2. Economic impact of a regulation based on 

geologic map information. E(La) is the marginal expected 

loss avoided; K* is the optimal level of safety. See text for 

in-depth discussion.

whether the average value of the geologic attribute 

minus two standard deviations, is greater than or less than 

the regulatory standard. The rule in equation II-1 is applied 

to each parcel.

gk -2av >R (II-D

where gk is the average value of the geologic attribute in k, 

where k= 1, . . ., K, CTV is the standard deviation of g over 

the mapped area for a given vintage geologic map, v, and R 

is the regulatory standard.

The economic impact of a regulation based on the 

improved geologic map information can be seen in figure 

II-2. This figure is a representation of the changes in the 

number of parcels restricted or mitigated when new, more 

detailed information becomes available. Safety (horizontal 

axis) is denoted as the fraction of land (parcels or cells) in 

the region that is rejected (require mitigation) for a partica study to address the question of the optimal scale for resolving a land use 

issue. In addition, there is the question, in a regional geologic mapping 

program, of prioritizing the schedule for creating geologic map information. Which geologic maps should be produced first? Again, this is beyond 

the scope of the study but is an important question in the overall issue 

regarding the "best" geologic mapping program.

22 The Societal Value of Geologic Map Information
ular land use type. Losses avoided through implementation 

of regulations are measured in terms of a money metric 

(dollars) on the vertical axis. As the vulnerable, or "at risk," 

cells are eliminated, society's exposure to that risk is 

reduced. As the level of safety increases, there is an 

increase in expected losses avoided. The change in expected 

losses avoided is shown in the figure as the marginal 

expected loss avoided, E(La), for restricting each additional 

cell. The E(La) curve represents the net marginal expected 

loss avoided (the cost of avoiding losses is constant), which 

is normalized on the figure by representing the E(La) as 

deviations from zero. Therefore, an optimal level of safety 

is shown as the intersection of the E(La) curve and the 

horizontal axis (net marginal expected loss avoided is zero) 

at the point labeled K* in the figure.

There is uncertainty regarding the actual losses to be 

avoided by restricting cells, because there is uncertainty 

concerning the true state of the geology underlying a cell. 

We have indicated this uncertainty in figure II-2 by the 

dashed lines above and below E(La). We have indicated two 

levels of uncertainty, each of which is consistent with a 

different level of geologic map information (d^ and d^ in 

terms of fig. II-l). In each case, the dashed lines enclose 

the 95-percent confidence interval.

The presence of information uncertainty leads to a 

tendency in the regulatory process to generate errors involving either underregulation or overregulation of land uses. 

Since the optimal level of safety is that which results in net 

marginal expected loss avoided being zero, either underregulation or overregulation must result in a welfare loss to 

society.

These losses may be shown by reference to figure 

II-2. Consider the case in which the regulator sets the 

standards to restrict K cells. With K~~ cells restricted, 

the social loss is given by the area bcOK*. This area is the 

amount of the potential consumer surplus that is foregone 

when the regulatory standard is set at K rather than the 

optimal level of K*. Improved geologic map information 

results in the level of regulation being increased so that K~ 

cells are now restricted (this is the 95-percent confidence 

level with this improved information, d-i). The welfare loss 

is now given by the area deOK*. The value of the improved 

geologic map information is the gain in consumer surplus 

(the reduction in the welfare loss) shown as the area cbde in 

figure II-2.

Consider now the case in which the regulator sets the 

standards at K++ (this is overregulation compared with the 

social optimal level of K*). The welfare loss associated with

this amount of overregulation is the area ifOK . With the 

improved information, the regulator reduces the number of 

cells restricted to K+ . The gain from this information is the 

area fihg.

The role of the improved geologic map information in 

a regulatory decision process can be shown explicitly. At 

any geologic map scale, there is a lower limit to the 

resolution of geologic attributes and hence a minimum cell 

size in a rectangular grid. In this demonstration, we assume 

that geologic maps at 1:500,000 and 1:100,000 scales have 

minimum cell sizes of 1 km x 1 km and 250 m x 250 m, 

respectively. 7 In the case of the l:500,000-scale geologic 

map, it is assumed that the geologic attribute has one 

measurement per 1-km x 1-km cell, while at the 1:100,000 

scale, the attribute is assumed to have 16 measurements 

covering the same area. Figure II-3 illustrates the difference 

between the size of a cell and the delineation of a geologic 

attribute at the two map scales. In figure II-3A, the attribute 

takes on one value (an average of the attribute over the area) 

while in figure II-3B, the attribute has 16 discrete observations for the 1-km x 1-km cell. The implication of applying 

a regulatory standard can be explained using an example.

Suppose a regulator is inclined to permit a land use 

unless geologic information in cell k suggests that an 

unacceptable adverse environmental change could occur. 

Figure II-3 depicts possible combinations of acceptable and 

unacceptable cells under two distinct levels of information. 

In comparing the possible outcomes for the two grids, we 

will make the assumption that if any part of a 1-km x 1-km 

cell is considered unacceptable and, therefore, is restricted, 

then the whole 1-km X 1-km area is restricted. 8 There are 

four possible outcomes:

Outcome 1: The cell is restricted if the earlier geologic map 

is used and is restricted if the improved geologic map is 

used.

Henceforth, we shall refer to parcels of land as "k" rectangular 

cells in an equal-area grid to conform with the empirical work to be 

presented in this chapter.

7 Grid sizes are selected by considering limitations in geologic map 

data accuracy and in digital data-base size; too small a grid size results in 

unmanageable file sizes, whereas larger grid sizes result in excessive 

averaging, or smoothing, of the geologic data. For the improved geologic 

map (1:100,000 scale), the minimum grid size is dictated by the 60-m 

spatial resolution of the geologic contacts for this map. However, a grid of 

this dimension would yield nearly 146,000 cells, which was considered an 

unworkable number of cells for this application. Therefore, a somewhat 

larger cell size (250 m) has been selected; in most cells only one geologic 

unit is represented, with a file containing 8,671 cells. To project a grid cell 

size for the existing geologic map (1:500,000 scale) would, based on map 

scales alone, increase the cell size by a factor of five, to 1.25 km. An even 

larger cell size might be warranted on the basis of the fact that geologic 

information on this geologic map was not gathered with the same level of 

detail as on the improved geologic map. However, we have chosen a more 

conservative approach for the existing geologic map by selecting a cell size 

of 1 km.

This is a simplifying assumption only. Relaxation of the assumption would not affect our argument or the resulting empirical estimation.

The Role of Geologic Map Information in the Making of a Decision 23
1 KILOMETER 

CELL 2

CELL 4

CELLS

A 1963 MAP

Figure 11-3. Comparison of the size of a grid cell for the 

1:500,000-scale 1963 map (Milici and others, 1963) and the 

1:100,000-scale 1992 map (Burton and others, 1992) and 

the delineation of a geologic attribute at the two geologic

a 1992 MAP

map scales. In A, the attribute takes one value for the 1-km 

x 1-km cell. In B, the attribute has 16 observations for the 

same 1-km x 1-km cell. In both A and B, a cell with an X 

in it is deemed unacceptable.

Outcome 2: The cell is not restricted if the earlier geologic 

map is used and is restricted if the improved geologic map 

is used.

Outcome 3: The cell is restricted if the earlier geologic map 

is used and the cell is not restricted if the improved geologic 

map is used.

Outcome 4: The cell is not restricted if the earlier geologic 

map is used and is not restricted if the improved geologic 

map is used.

Of specific interest is outcome 2. Cells would not be 

restricted if the earlier, l:500,000-scale geologic map 

(1-km x 1-km grid) is used but would be restricted if the 

improved l:100,000-scale geologic map (250-m x 250-m 

grid) is used. The higher resolution of the l:100,000-scale 

geologic map information prevents a certain land use 

where, given the additional detail of the geologic map 

information, it should not be allowed. If only the earlier, 

less-detailed information were available, this would represent the case of underregulation and a level of safety below 

the optimal level as depicted in figure II-2. Outcome 3 

represents the case of overregulation in figure II-2. On the 

basis of the earlier map information, a land use is not 

allowed; with the addition of improved geologic map 

information, the land use would be allowed.

FRAMEWORK FOR EMPIRICAL ANALYSIS

Study Area and Background

The model is implemented in a demonstration study 

in Loudoun County, Virginia (fig. II-4). To show the 

diverse nature, use, and value of geologic map information, 

we apply the model in two different ways: in locating a 

waste disposal facility and in locating a new interstate-type 

highway route. 9 In considering these two case studies, we 

begin with the perspective that the value of geologic map 

information is the sole issue to be evaluated. We do not 

address the net benefits of the projects themselves. In order 

to estimate the benefits of an improved geologic map 

relative to existing geologic map information, we use a 

benefit-cost framework to evaluate the information content 

on both the old and the new geologic maps.

The Loudoun County population, commercial base, 

and road network are distributed in a manner that reflects 

the underlying geologic framework. The western portion of

The 1963 geologic map has been used in a number of ways in 

Loudoun County and elsewhere in Virginia. Geologic map information 

contained in the 1963 Geologic Map of Virginia has limited application in 

a decisionmaking environment. Two documented applications of this 

geologic map have been as a teaching tool for the geologic framework of 

Virginia and for the general distribution of rock units that are potential 

sources for building stone, aggregate, or road metal.

24 The Societal Value of Geologic Map Information
1

i LOUDOUN COUNTY, VIRGINIA

rc River ^

10 KILOMETERS

Figure 11-4. Location map of Loudoun County, Virginia, showing selected geographic and cultural features.

the county (west of U.S. 15) is underlain by a complex 

group of igneous and metasedimentary rocks of the Blue 

Ridge province. East of the U.S. 15 corridor, the county 

plan has delineated large tracts of land for intensive regional 

growth. These cells are underlain by part of a Mesozoic 

basin filled with a sedimentary sequence of conglomerates, 

red siltstones, clay stones, and sandstones that are faulted 

and interlayered with massive basalt or intruded by diabase 

dikes and sills. This geologic setting provides opportunities 

for the development of ground-water well fields, construction of public and private waste facilities, and extraction of 

construction materials. Given the location of the current

landfill and the proposal for a Washington Bypass in the 

same (eastern) part of Loudoun County, the part of the 

county underlain by rocks of the Mesozoic basin was 

selected as the study area.

The Land Use Decisions

The net benefits of improved geologic map information are determined by comparing the land use decisions 

that would be made when using two geologic maps of the 

same area that are different in scale and vintage (fig. II-5). 

The existing geologic map information is from the 1963

Framework for Empirical Analysis 25
7

Figure 11-5. Geologic maps of eastern Loudoun County, 

Virginia. A, Part of the 1963 Geologic Map of Virginia 

(Milici and others, 1963). Green = sedimentary rocks 

(sandstone and shale undivided), pink = igneous rocks 

(diabase and gabbro undivided), and blue = conglomerate (a coarse-grained sedimentary rock). B, Part of the

preliminary version of the new USGS Geologic Map of 

Loudoun County, Virginia (Burton and others, 1992). 

Greens and blues = sedimentary rocks (sandstones, siltstones, and conglomerates), pinks and orange = diabase 

and basalt rock units, and darkest blue = limestone 

conglomerate of particular importance to this study.

Geologic Map of Virginia compiled and published at 

1:500,000 scale (Milici and others, 1963). The improved 

geologic map information is a preliminary version of the 

USGS Geologic Map of Loudoun County, Virginia, which 

was compiled at 1:100,000 scale (Burton and others, 1992). 

For purposes of demonstration and analysis, the eastern 

Loudoun County portion of each geologic map was converted to digital format in a geographic information system 

(GIS). GIS relational data-base techniques were required 

for handling and formatting the data for statistical and 

spatial analyses.

The 1963 geologic map of Virginia shows the general 

distribution of three lithologic units in eastern Loudoun 

County (fig. II-5A). These lithologic units and the boundaries (contacts) between them are generally located in many 

instances only to the nearest 1.5 to 2 km. The spatial 

distribution of rock units was derived by extrapolation from 

previously published maps and reports. Because there are 

no onsite observations, we assume a uniform distribution 

for describing the geologic attributes of a cell when regulatory standards are applied.

The preliminary version of the new USGS Geologic 

Map of Loudoun County, Virginia, shows the specific 

distribution of sixteen lithologic units in the eastern part of 

the county (fig. II-5B). (As stated in the Introduction, some 

of the new map's rock units are not discernible here (fig. 

5E) because the subtle color changes between rock units are 

difficult to reproduce.) The sixteen lithologic units and the 

contacts between them are located with an average spatial 

resolution of about 60 m. The observational data base for 

the map contains, on average, at least one actual onsite 

observation per cell. As such, given the existence of on-site 

observations and systematic sampling, we assume a normal 

distribution for describing the geologic attributes in a cell 

when regulatory standards are applied.

We used the information on the two geologic maps to 

derive some basic geologic attributes that bear on our 

applications. The ground-water yield (in gallons per 

minute), a measure based in part on rock permeability, is 

estimated for each rock unit on the geologic map. Information on yield for the rock types came from Albert Froelich 

and Ronald Parker (USGS, personal commun., 1991) and

26 The Societal Value of Geologic Map Information
was supplemented by information in Laczniak and Zenone 

(1985). For faulted and intensely fractured areas, the value 

of the ground-water yield is doubled on the basis that these 

features serve to markedly increase the rate of water flow. 

Also, the shear strength of each rock unit on the geologic 

map, a measure of resistance to slope failure, is calculated; 

standard values and information in Froelich (1985) and 

Leavy and others (1983) were used. These two geologicmap-based attributes are only a subset of the information that would be necessary to actually conduct these 

two land use analyses. However, these data are pertinent to 

the analyses and can be applied when using both geologic 

maps. If the approach developed in this study were to be 

incorporated into an actual regulatory process rather than a 

demonstration, more precise measures of, for example, 

water migration through the various rock units would be 

obtained and used.

To treat the geologic map data statistically, the 

geologic maps of eastern Loudoun County were intersected 

in the computer with a grid of 1-km x 1-km cells for the 

1:500,000-scale (existing) map and a grid of 250-m x 

250-m cells for the l:100,000-scale improved map. For the 

l:500,000-scale map, there are 605 1-km x 1-km cells, 

while for the l:100,000-scale map, there are 8,671 250-m 

x 250-m cells. For each cell, an area-weighted average 

yield was computed from the average yields of geologic 

map units intersected by the cell. In the same manner, 

area-weighted average shear strengths were computed. 

Census block data of the number of dwelling units from the 

TIGER files of the 1990 U.S. Census were intersected with 

the cells. A 1990 census block commonly is larger than one 

250-m cell. The proportion of each census block in a cell 

forms the basis for the calculation of the number of dwelling 

units per cell. Figure II-6 shows the dwelling density per 

cell. In addition, for each cell, the average and maximum 

topographic slope also was computed, and the presence of 

faulting, flood plains, municipal wells, airport-exclusion 

areas, and geologic map units prone to sinkhole development was recorded.

Central to our analysis of the net benefits of geologic 

map information is the demonstration that the two geologic 

maps of the same area represent distinct information that is 

statistically different. From the previous discussion, we 

know that the probability of the value of a particular 

geologic attribute in cell k is randomly distributed with a 

mean and a variance. Figures II-7 and II-8 contain the 

uniform and normal distributions for average ground-water 

yield and shear strength, respectively. We argue that when 

a newer vintage and larger scale (more detailed) geologic 

map is available, the geologic condition in any map location 

is more precisely known. This is fundamental to our 

analysis and is a testable hypothesis:

H0 : The geologic information content of both geologic maps is the same.

Dwelling Units per Cell 

| | 0-0.99 

| | 1.0-9.99 

iH 10.0-49.99 

JBU 50.0 or greater

Figure 11 6. Dwelling density per 250-m grid cell in eastern 

Loudoun County, Virginia, based on 1990 U.S. Census 

data.

If the information in the geologic maps is statistically 

identical, then the value of the new geologic map information is zero, by definition. This hypothesis can be tested by 

using non-parametric statistical tests such as the MannWhitney test for the difference between means and the 

squared ranks test for equal variances (Conover, 1980). 

These non-parametric statistical tests are conducted to 

determine whether the two geologic maps come from the 

same statistical population. 10

We tested for a statistical difference between the 

geologic maps, using the Mann-Whitney test (comparison 

of the means, JJL'S, of the geologic attributes for all cells on 

both maps; in other words, does JJL IOO = 1^500?) The test is

It is not hard to imagine geologic maps that are fundamentally the 

same. For example, if a geologic map is updated to a minor extent, a 

statistical comparison of the original and the updated version might show 

that the maps are essentially the same and thus would be inappropriate for 

a demonstration such as we have undertaken here.

Framework for Empirical Analysis 27
3,000

2,500

2,000

EXPLANATION

| | Histogram of average yields

based on improved geologic map

 Normal distribution of

average yields based on the 

improved geologic map

Uniform distribution of 

average yields based on the 

existing geologic map

10 20 30 

ROCK YIELD (GALLONS PER MINUTE)

40

Figure 11 7. Frequency distributions for average ground-water yields based on the two 

different geologic maps.

4,000

3,000

CJ

cc

LLJ 

00

2,000

1,000

0.350 0.375

EXPLANATION

Histogram of shear strengths based 

on the improved geologic map

Bimodal normal distribution of 

average shear strengths based 

on the improved geologic map

Uniform distribution of average 

shear strengths based on the 

existing geologic map

0.400 0.425 

ROCK SHEAR STRENGTH

0.450 0.475

Figure 11 8. Frequency distributions for average shear strengths of geologic materials 

based on the two different geologic maps.

significant at greater than the 99-percent confidence level (T 

= 67.22 for a two-tailed test) (see Conover, 1980); this 

means that JJL IOO ^ jx50o and that the rock units on the two

geologic maps are statistically different. We also conducted 

a non-parametric test for equal variances, comparing the 

variances (<T2's) of the geologic attributes for all cells on

28 The Societal Value of Geologic Map Information
Each implementation protocol is applied to determine 

the acceptability or unacceptability of a cell in the economic 

evaluation. This is referred to as a zero/one decision setting; 

the cell either passes or fails the standard. In other words, 

the threshold screen states that there is a geologic characteristic of a cell that exceeds the regulated standard and that 

we are 95 percent confident of the value of that characteristic.

Step 2: For each cell in the study area, a probability of 

loss, P(Lk), is estimated as a function of the geologic 

attribute of the cell. 12 For the cells identified in step 1, 

these probability values become the basis for estimating expected losses avoided in step 4.

The probability of loss is estimated in equation II-2 for each 

land use.

P(Lk) = P(Hk\ 8k) = ftgk , Vk) (II-2)

This conditional probability is a qualitative choice regression where the estimate of the hazard is based on geologicmap-based attributes such as average yield (a surrogate for 

rock permeability) or shear strength (a resistant force to 

slope failure).

Step 3: The appropriate monetary value in each cell for 

each map is estimated. This value, Lkj represents the 

property at risk.

Monetary measures for property values are developed 

from 1990 Census data in the demonstration for the waste 

facility siting, and measures for mitigation costs are developed from an engineering cost estimate in the highway 

slope-failure application.

Step 4: For each cell identified in step 1, the expected 

loss avoided (the savings), E(L^^ is estimated in 

equation II-3 as the product of the probability of a loss 

(eq. II-2, step 2) and the monetary value of the loss 

(step 3) in cell k:

E(La)k = P(Lk}Lk (H-3)

Step 5: The benefit of the improved geologic map 

information is calculated as the difference in expected 

loss avoided between the two geologic maps.

This is the benefit of the new geologic map information as defined by the regulatory standards. If more geologic 

characteristics were included and (or) the standards were 

changed, variations in the benefits would be likely.

Varnes (1974) argues that a given geologic map is not necessarily 

suitable for all purposes. Thus, we include the type of land use subscript 

in the recognition that different maps will be required for different land 

uses.

Step 6: The marginal cost of the improved geologic 

map is determined. 13 The marginal cos* of the geologic 

map information is the total cost (capital and labor) of 

producing a new geologic map, including the time 

value of money (an opportunity cost cf capital), C.

Step 7: The net benefits of the new geologic map 

information are calculated as the difference between 

the benefits of the new geologic map information and 

the marginal cost of producing the new geologic map.

We apply equation II-4 to estimate th? net benefits of 

improved geologic map information for each land use 

application of the geologic map.

NBV2=^[E(La)Jv -E(La}Jv }-CV2 7=1, . . . , / (11^)

where NBV, is the marginal net benefits (expected loss 

avoided) derived by using the new, more detailed 

(1:100,000 scale) versus the 1963 vintage geologic map (vj) 

(1:500,000 scale), j is the land use, and CV2 is the cost of 

producing the new geologic map. As discussed earlier, we 

assume the new geologic map "builds" upor the knowledge 

base of the existing geologic map. 14

The Regulatory Standards

Leakage of hazardous materials from waste facilities 

and landfills potentially poses a threat to the Nation's water 

supply. Substantial costs are incurred in reducing the risk of 

water contamination (Raucher, 1986). Th^re is a direct 

correlation between the rate of transport o^ dissolved and 

suspended contaminants away from a site and the permeability, faulting, and fracturing of the surrounding geologic 

materials. Changes in subsurface conditions that reflect 

local variations in the geology near a disposal facility can 

affect the rate of transport of contaminants and the extent of 

contamination. Avoidance of irreversible or irreplaceable 

losses of ground water and contamination cf surface-water 

supplies requires engineering solutions for mitigation ranging from construction of lined sites with buffer zones to 

highly sophisticated integrated engineering and monitoring 

techniques for remedial action.

An engineering analysis prepared by HDR Engineering (1989) evaluated all areas of LoudoM n County for 

suitable landfill sites. Recommendations to the county

Because we are interested in the value of the new geologic 

information, we do not need the cost of the old map.

14 Discounting issues are not explicitly considered. If one assumes a 

discount rate of 10 percent and an inflation rate of 1C percent, a formal 

annualizing and discounting step is not necessary. Because this is a 

demonstration, we have made these assumptions.

30 The Societal Value of Geologic Map Information
Table 11-1. Hypothetical regulations applied to cells in the study area

Land use Impact Protocol Screen (threshold standard)

Waste disposal facility ... Contamination .......... Rock permeability

Sink holes......

Highly permeable rock units

Faulting and associated intense 

fracturing...................

Transportation corridor... Slope failure due to

construction............ Rock shear strength.

Restrict when limestone conglomerate

is present. 

Restrict when average yield is s:15

gal/min.

Restrict when faulting and associated 

intense fracturing are present.

Mitigate when rock shear strength 

<0.49.

Protocols are defined as geologic attributes used in implementing regulations.

each map. For the newer map, variance should be reduced 

compared to the older map (o-2 10o < o-25oo)- Using the 

distributions in figure 11-7 for the average yield attribute, 

the test finds a significant variance at the 99-percent 

confidence level (T = 2.63 for a one-tailed test), and using 

the distributions in figure II-8 for the bimodal shear 

strength attribute, the test finds there is also a significant 

difference in the variances at the 99-percent confidence 

level (T = 4.23 and T = 2.65 for one-tailed tests 11 ). These 

tests suggest that the geologic characteristics represented in 

the two maps are statistically different and do not come 

from the same population. Thus, we are able to derive 

estimates of the value of the improved geologic map relative 

to the existing geologic map of the same area.

The Regulatory Standards

Current regulatory standards regarding waste site 

location typically are represented in terms of demographic 

and cultural characteristics, and there are no current highway construction regulations that incorporate geologic criteria. Leakage from waste facilities and landfills threatens 

the Nation's water supply. Variations in regional geology 

near such a facility affect the rate of transport of contaminants and the extent of contamination. Also, the costs of 

constructing and operating transportation corridors are 

influenced by regional variations in near-surface geology 

and topography. In addition, a transportation corridor can 

have an impact on the regional geology by contributing to 

slope failure, excessive runoff, and altered drainage patterns.

The shear strength distribution for the eastern portion of the 

recent, l:lOO,000-scale Geologic Map of Loudoun County, Virginia, is 

bimodal. Two normal distributions for the shear strength variable are, by 

definition, independent of each other (Agterberg, 1974). The test for 

variances was run for both samples and compared to the uniform 

distribution for the eastern Loudoun County portion of the earlier, 

l:500,000-scale Geologic Map of Virginia. The sample is split at a shear 

strength of 0.415.

Table 11-2. Variables used in empirical demonstratic n of 

value of geologic map information

Variable Definition

Geologic attribute of rock materials in cell k sucl as 

faulting, permeability, and shear strength of rocv 

materials.

Monetary loss in cell k.

Probability of a loss Z^ in cell k.

Safety standard for land use j, defined as restrict] ons 

on allowed land uses or requirements for a give"1 

land use, for example, building codes.

Expected loss avoided for cell k.

Expected value of a geologic attribute in cell k; 1~ = 

1, . . .,k.

Expected loss avoided for land use j.

Hazard in cell k.

Additional physical attributes in cell k.

E(Laa)j

An example of hypothetical regulations that are Hsed 

solely on geologic characteristics is presented in table II-l 

for these two land uses. The regulations consist of one or 

more implementation protocols relating to geologic 

attributes (for example, for the waste disposal facility's 

regulation, we apply three rock permeability protocols as 

shown in table II-l). For each protocol, a specific action, or 

threshold standard, is given; this is referred to as a screen. 

Our protocols are not meant to be exhaustive in the existing 

regulatory environment, only illustrative.

The Method

In table II-2 we provide definitions of the variables 

used in this analysis. Implementation of our demonstration 

studies requires seven steps that are outlined below:

Step 1: For each cell on each map, the value cf the 

geologic attribute, g^, at the 95-percent confidence 

level (2o-) must have a finite value (greater than zero). 

If the cell meets or exceeds this condition, the value of 

g£ is compared to the regulatory standard.

Framework for Empirical Analysis 29
about suitable sites are based on the size of the landfill 

required for the projected quantity of waste through the year 

2015, which is based on the population growth rate in 

Loudoun County. According to the HDR Engineering 

report, in the 20-year period from 1995 to 2015, Loudoun 

County will generate at least 3.3 million tons of solid waste 

for a population of 246,000 (HDR Engineering, 1989, p. 

2-5). 15 The disposal of this quantity of waste would require 

a landfill having a capacity of over 9 million cubic yards. 16 

Depending on the actual parcel attributes, the total size of a 

landfill to accommodate the disposal needs of the county for 

a 20-year period starting around 1995 probably would have 

to be at least 600 acres (about 2.5 km2) to adequately buffer 

the site and to mitigate community impacts.

According to conventional practice, the HDR study 

used current regulations based on demographic, cultural, 

and scientific criteria to identify potential landfill sites. To 

more completely illustrate the effects of these regulations, 

we applied the following parts of the Virginia standards to 

identify areas that could be restricted from landfill development:

1. Landfills shall not be sited in geologically unstable areas 

where inadequate foundation support for structural components of the landfill exists. Factors to be considered 

when determining unstable areas shall include: 

a. Presence of sinkholes within the disposal area. 17

2. No sanitary landfill disposal area shall extend closer

than: 18

a. 10,000 feet of any airport runway used for turbojet 

aircraft or 5,000 feet of any airport runway used by 

only piston type aircraft, unless the facility operation 

does not pose a bird hazard to aircraft;

15 Population projections based on Metropolitan Council of Governments Round 4 Cooperative Forecast, November 4, 1987, using the 

Intermediate Level of Anticipated Growth. Annual waste quantity projections are based on a per capita waste generation rate of 5 Ib per person per 

day. This figure is consistent with actual data for 1989.

16 The entire county was screened by HDR; they used 21 criteria 

pertaining to the landfill regulations and to technical issues that usually are 

addressed in permit hearings. One of the criteria used in the decisionmaking process is the "Constraints imposed by physical characteristics pertaining to permitting" (HDR, 1989, p. 3-2). This specific criterion is the only 

geologic input in the engineering study. As a result of this analysis, less 

than 15 percent of the total land area of the county appears to be capable 

of surviving the permit process. Within the reduced land area, three 

potential sites were selected for further examination. The sites were 

selected because of their physical setting and size, potential community 

impacts, traffic impacts, and other waste transportation issues. These three 

locations were designated "Primary Search Areas" and all other areas of 

the county were excluded from further consideration.

17 We used the occurrence of the limestone conglomerate map unit 

as a surrogate for this protocol because sinkhole (karst)-forming processes 

affect this unit.

18 The following rule was applied to show the extent of the current 

restrictions. This specific screen is for demonstration purposes and was not 

used in the estimation of the benefits of geologic map information.

b. 100 feet of any regularly flowing surface water body

or river; 

c. 500 feet of any well, spring, or other ground-water

source of drinking water.

These regulatory screens are implemented and intersected with a 1-km x 1-km grid as shown in figure II-9A 

for the eastern Loudoun County study area as background 

information to indicate the extent of the restrictions of the 

current regulatory standard. Application of the current 

Virginia regulations to the area leaves 162 1-km x 1-km 

cells still available for a waste disposal facility (fig. 11-95). 

Although commonly used, this approach to code enforcement considers geologic map information in but a cursory 

manner.

However, in the following discussion, we describe an 

expanded role for geologic map information in the decisionmaking process. In contrast to the current approach of 

promulgating environmental regulations that use demographic and cultural protocols (alternative policies for code 

enforcement) and scientific data, our approach uses physical measures derived from geologic map information as the 

initial basis for regulatory decisions.

Because this analysis is a demonstration that estimates the value of geologic maps, we do not consider all of 

the possible protocols. For this study, threshold standards 

based upon the application of rule 1 above (rule 2d of the 

current Virginia regulations), and additional hypothetical 

rules based on geologic attributes, are implemented. Thus, 

all cells within the Loudoun study area are considered 

acceptable unless they are determined not to satisfy the 

threshold standard for a particular geologic attribute.

Empirical Implementation

In what follows, we implement the model described 

above. For the landfill siting application, we assume a 

tendency to underregulate.

Step 1: For each cell on each geologic map, the value 

of a geologic attribute related to rock permeability (for 

example, average yield19) is compared to the regulatory screens in table II-1 to identify those cells 

potentially suitable for siting a waste disposal facility.

The suitability test for a cell as a potential landfill site 

based on geologic attributes is a two-part procedure:

1. For any cell to be considered unsuitable, the value of the 

average yield, g^, at the 95-percent confidence level

19 The definition of average yield has two parts: (1) we calculate a 

ground-water yield in gallons per minute for a specific rock unit on each 

map and (2) for each grid cell, an area-weighted average yield is calculated 

from the rock units contained in the cell.

The Loudoun County, Virginia, Landfill Siting Demonstration Study 31
Duties Airport Duties Airport

B

Figure 11-9. Areas in eastern Loudoun County, Virginia, 

excluded from consideration for possible waste disposal 

facilities on the basis of current State regulations (1-km 

grids). A, Regulatory screens. Cray = area susceptible to

presence of sinkholes, brown = airport exclusion areas, 

red dots = municipal water wells, and blue = streams. 8, 

Excluded (red) and nonexcluded (yellow) cells.

(2o-) must be a finite value (greater than zero). For the

cells that meet this condition, the regulatory standard is

applied. 

2. The regulatory standard consists of three screens:

a. the cell is unsuitable if it contains the limestone 

conglomerate geologic map unit (a highly permeable 

material prone to sinkhole development and currently 

used as a restriction under Virginia State regulations 

for siting waste disposal facilities);

b. the cell is unsuitable if it has an average yield equal 

to or greater than 15 gallons per minute (a relatively 

high value for rock units in the study area); and

c. the cell is unsuitable if faults and associated intense 

fracturing of rock units are present (generally 

increases the ground-water yield).

A simple example using equation II-l (gk represents 

the average yield in cell k) illustrates how our model works. 

Consider the values: gk = 20 gal/min; the regulatory 

standard for average yield, Rj^ =15 gal/min; for the earlier 

geologic map, vlt 2crVl = 10 gal/min; and for the improved 

geologic map, v2, 2crV2 = 4 gal/min. For the earlier geologic 

map, vi\ 20 - 10 = 10 < 15, the standard for Rjt so the cell

Table 11-3. Number of cells restricted for waste facility 

siting

[Outcomes are detailed in the section "The Inclusion of Geologic Map 

Information in Regulations"]

Outcome 1 . . 

Outcome 2 . . 

Outcome 3 . . 

Outcome 4 . .

1:500,000-scale 

map (old map)

. Restriction ..... 

. No restriction . . 

. Restriction ..... 

. No restriction . .

1:100,000-scale J? 

map (new map)

Restriction ..... 

Restriction ..... 

No restriction . . 

No restriction . .

jmber of 

m x 1-km

61 

321 

0

223

cannot be restricted for locating a waste disposal facility. 

For the improved geologic map, v2: 20 4 = 16 > 15, the 

standard for Rj, so the cell should be restricted from 

development as a waste disposal site.

The results of applying the standards for siting a 

waste disposal facility for the two geologic maps are listed 

in table II-3; we assume that a landfill will occupy a 1-km 

x 1-km cell that, as mentioned earlier, is the lower limit of 

the geologic resolution of the earlier geologic map. Listed 

in the left-hand column are the possible outcomes of the

32 The Societal Value of Geologic Map Information
I I Not restricted 

^ 1 Restricted

I I Not restricted 

^H Restricted

1963 Information Used 1992 Information Used

Figure 11 10. Spatial distribution of cells in eastern Loudoun County, Virginia, restricted from further consideration as a 

possible landfill site on the basis of existing (1963) and improved (1992) geologic map information.

process. For instance, outcome 2 represents the case where 

no cells were restricted when we use the earlier geologic 

map information but 321 1-km x 1-km areas were restricted 

when we use the new, more detailed information. Figure 

11-10 illustrates the spatial distribution of the restricted cells 

when we use the earlier and the improved geologic map 

information. This represents the case of underregulation. 

The improved geologic map information identified areas to 

be excluded that were not identified with the earlier information. Of note is outcome 3. In this case cells would be 

restricted when the older information is used but would not 

be restricted when the improved geologic map information 

is used. This outcome represents overregulation. Note that 

no cells fell into this category. As such, it becomes apparent 

that using the old data results in underregulation, not 

overregulation. 20

20 As indicated in the footnote regarding the HDR study, three 

primary search areas were identified. One of these is the proposed 

southward extension of the existing waste site and is within our limited 

study area. Thus, we ask "are there any cells restricted on the earlier 

geologic map or the improved geologic map for a 1-km x I-km area for 

the landfill extension south of the existing site?" Our investigation 

indicates that there are no restrictions when the earlier geologic map is

Step 2: For each cell, a probability of loss P(Lk) is 

estimated as a function of the geologic attribute of the 

cell.

For each 250-m x 250-m cell, a conditional probability (log odds) of contamination P(Lk) is estimated by 

applying equation 11-2 as a function of the rock types. The 

conditional probability of contamination, in equation II-5, 

is a binary choice logit regression based on the average 

yield (a surrogate for permeability) of rock materials in 

locations surrounding sites regulated by the EPA according 

to the Resource Conservation and Recovery Act and solid 

waste landfills located in the Mesozoic basin. The estimation of the spatial probability of contamination is:21

used. Of interest, however, is that there are 7 250-m x 250-m cells 

restricted when the improved geologic map is used. All are based on the 

implementation protocol of average yield of ground water and the 

associated screening value. This result supports the conclusion that, in the 

waste site demonstration, the use of the earlier geologic map leads to 

underregulation.

21 Because Loudoun County has only one existing landfill, the 

probability of contamination is estimated for an analogous geologic terrain, 

the Mesozoic basin in central New Jersey, where water monitoring data 

and waste sites are more plentiful. The coefficients from the New Jersey 

equation are extrapolated to the study area in eastern Loudoun County.

The Loudoun County, Virginia, Landfill Siting Demonstration Study 33
Probability of Contamination 

I I 0.35-0.39

0.40-0.44

0.45-0.49

0.50-0.54

Figure 11-11. Conditional probability of contamination of 

rock materials in eastern Loudoun County, Virginia, determined on the basis of their permeability. Cell size is 250 m 

x 250 m.

. = -1.23 +0.37(AVGYLDk) (II-5) tJ(Lk)

where P(L]<) comprises contamination incidence Hk ("yes" 

or "no") given an average yield (gk) = 1 if ground water at 

the waste disposal site exceeds the state primary drinking 

water standard for any constituent, and P(Lk) = 0, otherwise. AVGYLD is equal to the area- weighted average yield 

of rock units. The r-statistic is 1.41 for the constant and 

1.95 for the average yield coefficient, R2 = 0.1, and the 

number of observations («) = 83.

The conditional probability of contamination ranges 

from 0.37 to 0.53, has a mean of 0.42, and a standard 

deviation of 0.03 for the 8,671 250-m x 250-m cells on the 

1 : 100 ,000-scale geologic map (fig . II-l 1 ) .

Step 3: The monetary value of the property (Lk) in each 

cell for each map is estimated.

In this study, only property value losses are estimated. We do not attempt to quantify the expected value of 

health effects or economic disruption that would ensue from 

a contamination incident in the county. In pursuing this 

approach, the private benefits associated with residences in 

the case of the waste site example are captured. However, 

other private benefits are ignored as well as the public 

benefits. We acknowledge that this procedure contributes to 

a bias. However, we know of no practical method for a 

study of this scale and effort that would allow an alternative 

assumption. Further, given that we are only considering 

some of the uses of geologic maps for a region and hence 

only some of the private benefits, the overall benefit bias of 

the study is downward, that is, conservative. This issue is 

developed further in the concluding section of the chapter 

where the overall net benefits are considered.

The number of residences by census block were taken 

from the 1990 U.S. Census to estimate the property-value 

effects in each cell. A census block commonly includes all 

or part of several grid cells. To estimate the number of 

dwellings in a cell, the areal proportion of a census block in 

that cell was multiplied by the total number of dwelling 

units in the census block. For cells containing more than 

one block, these products were summed (see fig. II-6 for a 

spatial representation). On the basis of recent real estate 

transactions, an average residence in the eastern part of the 

county is assigned a value of $150,000. Figure 11-12 

presents a spatial representation of property value per cell.

Step 4: For each cell identified in step 1, the expected 

loss avoided E(La)k (fig. 11-13) is estimated by using 

equation II-3 as the product of the probability of a loss 

(eq. II-5) and the monetary value of the loss (total 

property value) in cell k (step 3).

For each 250-m x 250-m cell, the expected loss 

avoided from a contaminated waste disposal site is estimated as the product of the probability of contamination 

(eq. II-2) and the property value in cell k. Combining the 

spatial distribution of the E(La) (fig. 11-14) with those cells 

identified in step 1 (fig. 11-10) yields the expected loss 

avoided for each geologic map.

Step 5: Calculation of the benefit of the improved 

geologic map information is accomplished by taking 

the difference in expected loss avoided between the 

two geologic maps.

On the basis of the assumption that the county will 

need to proceed with constructing one new waste disposal 

facility, this analysis is used to estimate the benefits of the 

improved geologic map information for selecting one site in 

the study area. The site is assumed to occupy a 1-km2 area 

(about 250 acres), which roughly conforms to the proposed 

sites described in the HDR study (sites selected for future 

landfills ranged from 302 to 978 acres).

34 The Societal Value of Geologic Map Information
1990 Property Values 

| j $0-$99,999 

m $100,000-3499,999 

^| $500,000-3999,999 

m $1,000,000-34,999,999 

 1 $5,000,000 or greater

Figure 11-12. Spatial distribution of property values, eastern Loudoun County, Virginia.

Depending on the location of the proposed waste 

disposal facility, the difference in expected loss avoided, 

E(La), between the two geologic maps ranges from $39,241 

per 250-m x 250-m cell to $124,791 per 250-m x 250-m 

cell. The difference in average expected loss avoided, 

E(La)k, for any cell in the study area is $94,027 per 250-m 

x 250-m cell.

For a landfill site that requires a 1-km X 1-km area, 

the average E(La)k is multiplied by 16 (there are 16 250-m 

x 250-m cells in a 1-km x 1-km area) to estimate the 

societal value of the improved geologic map in this 

land use. 22 The 1-km x 1-km areas that would be restricted

22 In the study area, there are 321 1-km x 1-km areas that are 

acceptable for development as a landfill based on applying to the earlier 

geologic map the implementation protocols that contain at least 1 250-m x 

250-m cell that would be restricted when applying the same protocols to 

the improved geologic map. The existing waste site occupies 147 acres 

(about 0.6 km2), or approximately 10 250-m x 250-m cells.

100 1,000 

NUMBER OF CELLS

Figure 11-13. The expected losses avoided due to landfill 

contamination for cells in the study area, eastern Loudoun 

County, Virginia.

Expected Losses Avoided 

per Cell

g I $0-$9,999 

|H $10,000-$49,999 

^B $50,000-3249,999 

H $250,000-$999,999 

 $1,000,000 or more

Figure 11-14. Spatial distribution of expected losses 

avoided per cell from a contaminated waste disposal site. 

Cell size is 250 m x 250 m.

The Loudoun County, Virginia, Landfill Siting Demonstration Study 35
I I Not restricted 

^ 1 Restricted

Figure 11-15. Areas in eastern Loudoun County, Virginia, 

that would be restricted when the improved geologic map 

is used but would not be restricted when the existing 

geologic map is used. Cell size is 1 km.

by use of the improved geologic map while not being 

restricted using the existing map (outcome 2) are shown in 

figure 11-15. The benefit of the improved geologic map in 

locating a new waste disposal in Loudoun County is 

approximately $ 1,500,000.

These geologically based hypothetical regulations, or 

other regulations more suited to a particular region's geologic setting, could contribute to a comprehensive set of 

regulations for the siting of waste disposal facilities. We 

have outlined a method for evaluating geologic risk, including both the probability of a change in physical state and the 

expected loss avoided from an adverse environmental 

impact, and for restricting individual cells in the process of 

selecting landfill sites in a study area. Decisions for the 

remaining cells can be made on the basis of demographic 

and cultural screens in conjunction with considerations such 

as transportation costs.

THE WASHINGTON, D.C, BYPASS ROUTING 

DEMONSTRATION STUDY

The Regulatory Standards

We consider the development of a new transportation 

corridor in Loudoun County for a Washington Bypass. 23 

According to the Federal Highway Administration, the 

Washington Bypass is a proposed interstate-type highway 

that would bypass the Washington, D.C., region, provide 

additional roadway capacity to the region, improve truck 

and traffic safety, and provide improved facilities for both 

through-traffic and local traffic. The action proposed in a 

published Draft Environmental Impact Statement (DEIS) 

consists of an Eastern Bypass, a Western Bypass, or both. 

The jurisdictions affected by the planned bypass are the 

States of Maryland and Virginia and the cities of Washington, D.C., and Baltimore, Md. Twenty-three counties (or 

portions of counties) would be affected, including Loudoun 

County, Virginia. The assumed right-of-way used for the 

DEIS analysis was located in the center of a corridor 1.3 km 

wide. The right-of-way assumed for all of the alternatives is 

137 m in a new location and 91m where the facility would 

be constructed on an existing roadway. The number of lanes 

and costs will vary by alternative, based on land use and 

traffic projections and on engineering. All proposed Western Bypass corridors cross the eastern part of Loudoun 

County. Along the many alternative routes within the 

bypass corridor in Loudoun County, the length of road 

varies from 13.2 km to 42.1 km over flat to rolling terrain.

Right-of-way, construction, and maintenance costs 

for highways are influenced by local variations in nearsurface geology and the topography. Engineering practices 

(the ease of excavating the near-surface geologic materials) 

along the routes will vary considerably from easy (siltstone) 

to difficult (diabase and metamorphosed conglomerate). As 

such, construction costs due to geologic variability are 

potentially significant. Regardless of the bypass route 

selected, construction and operation of a Washington 

Bypass will have short- and long-term impacts on the 

geology of Loudoun County (U.S. Department of Transportation and others, 1990). Construction activities, which 

include blasting, land clearing, and soil stockpiling, are 

short-term effects that include increases in stream siltation 

and losses of productive soils. Operation of the bypass may 

cause such potential long-term impacts as slope failure, 

excessive runoff, and altered drainage patterns.

The specific protocol that we utilized to form the

23 A Draft Environmental Impact Statement of the Washington 

Bypass has been prepared by the U.S. Department of Transportation, the 

Federal Highway Administration (FHWA), the Maryland State Highway 

Administration, and the Virginia Department of Transportation (U.S. 

Department of Transportation and others, 1990) as part of an evaluation of 

a new highway designed to alleviate traffic congestion in the BaltimoreWashington transportation corridor.

36 The Societal Value of Geologic Map Information
basis of a threshold screen is based upon the geologic 

attribute of rock shear strength. 24 Although slope is also an 

important consideration, we did not use it to screen cells 

from further consideration, because slope is independent of 

the geologic map information. Engineering considerations 

provide the foundation for the screen. This approach is 

based on the cut-and-fill requirements for slope stability as 

described in UBC Chapter 70 (International Conference of 

Building Officials, 1979) and the construction of retaining 

walls on both sides of the right-of-way.

Empirical Implementation

We implement the following procedure to estimate 

the value of the improved geologic map information relative 

to the existing information in siting a transportation corridor 

such that expected mitigation costs for slope failures due to 

construction would be minimized. For this application, we 

assume that a regulator will be conservative (will have a 

tendency to overregulate) in his approach to this issue.

With improved geologic map information, better 

siting decisions can be made (that is, fewer locations along 

the transportation corridor would be expected to require 

mitigation for slope failure that has resulted from construction).

Step 1: For each cell on each geologic map, the value 

of the geologic attribute, rock shear strength, is compared to the regulatory screen (table H-l) to identify 

those cells that potentially would require mitigation for 

slope failures due to construction along a transportation corridor.

The identification of cells potentially requiring mitigation based on geologic attributes is a two-part procedure:

1. For any cell to be considered for mitigation, the value of 

the average shear strength, gfc , at the 95-percent confidence level (2cr) must be a finite value (greater than 

zero). For the cells that meet this condition, the regulatory standard is applied.

2. The regulatory standard consists of one screen: cells that 

would be expected to require mitigation are those with 

an average shear strength of less than 0.49 at the 

95-percent confidence level (2cr). 25

A simple example using equation H-l for the average 

shear strength attribute, gk, illustrates how the model

Table 11-4. Number of cells for each highway construction 

mitigation outcome

[Outcomes are detailed in the section "The Inclusion of Geologic Map 

Information in Regulations"]

We calculate a shear strength for each specific rock unit on each 

map. Then for each grid cell, an area-weighted shear strength is calculated 

from the rock units contained in the cell.

This rule was found to be optimal for a hypothetical evaluation of 

hillside regulations in Cincinnati, Ohio, to avoid landslides that were 

construction triggered (see Bernknopf and others, 1988). When geologic 

map information was added to the hypothetical regulations, there was a 

significant reduction in the area requiring hillslope mitigation.

Outcome 1 . .

Outcome 2..

Outcome 3 . .

Outcome 4. .

1:500,000-scale 

map (old map)

Mitigation .....

No mitigation . .

1:100,000-scale 

map (new map)

No mitigation . .

No mitigation . .

Number of 

250-m x 250-m 

cells

3,889

1,041

2,237

1,504

works. Consider the following values: gk = 0.54; Rj = 0.49; 

2crV Vl = 0.06; and 2erV V2 = 0.04. For v^. 0.54-0.06 = 0.48

< 0.49, the standard for Rj, so the cell is expected to require 

mitigation along this section of road. For v2: 0.54 0.04 = 

0.50 > 0.49, the standard for Rj, so the cell might not 

require mitigation along this section of road.

The results for the application of step 1 for the two 

geologic maps are listed in table II-4. Listed in the left 

column are the possible outcomes of this application. Of 

particular importance is outcome 3. This is the case where 

cells would be expected to require mitigation when the 

earlier geologic map is used but would not be expected to 

require mitigation when the improved geologic map is used. 

This outcome represents the situation of overregulation. 

Note that over 2,000 250-m x 250-m cells are identified in 

this outcome category, while about 1,000 of these cells are 

identified in outcome category 2. As such, the case is made 

for the tendency for overregulation when the earlier (existing) geologic map information is used. Based upon the 

results in table H-4, figure 11-16 is a map of the spatial 

distribution of the cells that would be expected to require 

mitigation when using the earlier and the improved geologic 

map information. By applying improved geologic-mapbased information, we can reduce the tendency to overregulate.

Step 2: For each cell, a probability of loss, P(Lfc), is 

estimated as a function of the geologic attribute for the 

cell.

The probability of a slope failure as based on equation 

II-2 is assumed to be a physical process similar to a 

construction-induced landslide: P(Lk) = P(Hk \ gjt,VJt), 

where the hazard in this case, Hk, is slope failure due to a 

roadcut. P(Hk \ gk,Vk) IS estimated as a function of a 

factor-of-safety variable for failures triggered by new road 

construction. The probability of a slope failure is based on 

a binary choice logit regression, wherein the stability of a 

location changes from a stable to an unstable condition. 

This equation was estimated for landslides in similar types 

of terrain in Cincinnati, Ohio (Bernknopf and others, 1988).

The Washington, D.C., Bypass Routing Demonstration Study 37
I I No mitigation 

H Mitigation required

Proposed western 

bypass corridor

1963 Information Used

I I No mitigation

Mitigation required

Proposed western 

bypass corridor

1992 Information Used

Figure 11-16. Spatial distribution of expected slope failures due to road construction, eastern Loudoun County, Virginia, 

that would require mitigation on the existing and new geologic maps.

The estimate of P(Lk) is: 

~ In/ ~dj^} = -°- 

k

.77 (NRj 

(11-6)

where P(Lk) comprises landslide incidence Hk ("yes" or 

"no") given the observed physical characteristics: average 

slope angle (6), tan 6, residual of shear strength (tan <J>') of

near-surface materials, ^*=(^-eL maximum slope angle 

(MS), tan (MS), and new road corridor excavation (NR). 

The f-statistic is 1.21 for the constant, 13. 18 for the natural 

log of Fk, 4.0 for the natural log of MSk, and 4.28 for NR; 

R2 = 0.26, and the number of observations («) = 14,255. 

The conditional probability estimate, />(£*), includes 

bedrock units and surficial geologic materials. These surficial geologic materials can include transported sediment 

such as alluvium or landslide debris, as well as weathered, 

residual bedrock known as saprolite. In equation II-6, the 

shear strength of the surficial geologic materials is included 

in places where they are at least 6 m thick. The conditional 

probability of slope failure (fig. 11-17) ranges from 0.013 to 

0.838 and has a mean of 0. 143 and variance of 0.024 for the 

new, more detailed geologic map.

Step 3: The cost of the required mitigation in each cell, 

Lfc, for each geologic map is estimated.

For the study area, the expected loss avoided (savings) in road construction costs and repairs (mitigation in 

the form of retaining walls) is calculated for the cells that 

require mitigation. The loss avoided is assumed to be a 

$1,000 per meter cost of repairing a damaged slope by 

constructing a retaining wall to prevent further road damage.26 Because we assume both sides of the road would 

require mitigation, we used a $2,000 per-meter cost.

Step 4: For each cell identified in step 1, the expected 

loss avoided (fig. 11-18), E(L^ is estimated by using 

equation II-3 as the product of the probability of a loss 

(eq. II-6) and the monetary value of the loss (cost of 

mitigation) in cell k (step 3).

We use $2,000 per meter per cell, assuming both 

sides of the road are affected by a slope failure, to estimate 

the expected damages along a route corridor. The expected

26,' This cost estimate is based on a Consulting Engineering Firm's 

cost for retaining wall construction along 1-66 in northern Virginia (Robert 

Gladstone, personal commun., 1990).

38 The Societal Value of Geologic Map Information
Probability of Slope Failure 

| | 0.00-0.09 

£ ] 0.10-0.19 

^H 0.20-0.39

0.40-0.59

0.60-0.84

Figure 11-17. Conditional probability of slope failure due 

to road construction, eastern Loudoun County, Virginia. 

Cell size is 250 m x 250 m.

value and standard deviation of the costs are $75,760 per 

cell and $38,878 per cell, respectively, for the improved 

geologic map.

Combining the spatial distribution of the E(La) (fig. 

11-19) with those cells identified in step 1 (fig. 11-16) yields 

the expected loss avoided for each geologic map.

Step 5: Calculation of the benefit of the improved 

geologic map information is accomplished by taking 

the difference in expected loss avoided between the 

two geologic maps.

Depending on the final choice for the location of the 

three proposed transportation corridors, the difference in 

expected loss avoided, E(La)k, between the two geologic 

maps for any cell in the study area varies considerably but 

averages about $1 1,000 per 250-m x 250-m cell. The cells 

that would not require mitigation when the improved 

geologic map is used but would require mitigation when the

0-40

40-80

80-120

120-160

160-200

200-240

240-280

280-320

320-360

>360

10 100 

NUMBER OF CELLS

1,000

Figure 11-18. The expected losses avoided due to highway 

slope failure for cells in the study area, eastern Loudoun 

County, Virginia. Cell size is 250 m x 250 m.

Expected Losses Avoided 

per Cell

| | $0-$9,999

$10.000-$49.999 

$50,000-$99,999 

$100,000 or more

Figure 11-19. Spatial distribution of expected losses 

avoided due to slope failure induced by road construction, eastern Loudoun County, Virginia. Cell size is 250 m 

x 250 m.

The Washington, D.C., Bypass Routing Demonstration Study 39
I I No mitigation 

Hi Mitigation required

200

Figure 11-20. Areas in eastern Loudoun County, Virginia, 

that would not require mitigation when the improved 

geologic map information is used but that would require 

mitigation when the existing geologic map information is 

used.

existing geologic map (outcome 3) is used are shown in 

figure 11-20. If it is assumed that any corridor selected will 

cross a minimum of 85 cells and a maximum of 287 cells 

(number of cells crossed by the easternmost and westernmost proposed routes in the DEIS), the benefit of the 

improved geologic map information in locating an 

interstate-type highway corridor in eastern Loudoun County 

ranges between $935,000 and $3,157 ,000 . ,

THE NET BENEFITS OF GEOLOGIC MAP 

INFORMATION

The purpose of this analysis has been to develop and 

implement a methodology for estimating the societal value 

of improved geologic map information. Second, we have 

derived the benefits of improved geologic map information

150

100

o

31 h-

<r

LU

o_

50

EXPLANATION

I| Field 

| | Compilation 

Printing

1988 1989 1990 1991 1992 1993

Figure 11-21. Cost distribution by year for creating the 

improved geologic map of Loudoun County, Virginia.

for two applications. In this section, we apply equation II-4 

to estimate the net benefits of the improved geologic map 

information.

Cost To Produce an Improved Geologic Map for 

Loudoun County

Loudoun County occupies approximately 1,425 km2 , 

an area equivalent to about ten 7.5-minute (1:24,000 scale) 

quadrangles, or about one-third of a 30 x 60 minute 

(1: 100,000-scale) quadrangle. A number of areas within the 

county have been mapped for other purposes in the past 

with varying quality and density of observations and have 

been interpreted and reinterpreted geologically over the last 

century as different paradigms for geologic understanding 

were developed, tested, and refined or abandoned. The 

current USGS geologic mapping project in Loudoun 

County, therefore, requires both new geologic mapping and 

compilation and reinterpretation of existing geologic map 

information. Total costs for the improved geologic map 

information, the 1: 100,000-scale USGS map, are projected 

to be about $1,160,000 distributed over 6 years, as shown 

in figure 11-21. These costs include an opportunity cost of 

capital compounded semiannually at 10 percent during the 

production period. The project cost is about $968,000 and 

interest is $189,000. The capital and operating costs for the 

project are $913,000 and $55,000, respectively. Capital 

costs include utilization of plant and equipment and personnel, while operating costs include daily expenses and 

supplies.

40 The Societal Value of Geologic Map Information
Table 11-5. Net benefits of new geologic map information 

in Loudoun County, Virginia (in millions of dollars)

Benefits for new geologic map information ....... $2.44-$4.66

Cost of 1:100,000 scale geologic map of Loudoun 

County ....................................... 1.16

Net benefits.................................... $1.28-$3.50

Net Benefits of Improved Geologic Map 

Information

The net benefits from the use of more detailed 

geologic map information (the USGS l:100,000-scale map) 

are the benefits for the new geologic map information 

($2.44-$4.66 million) minus the cost of producing that map 

($1.16 million). Therefore, the expected net benefit for the 

l:100,000-scale Loudoun County geologic map ranges 

from about $1.28 million to $3.50 million, as shown in 

table n-5.

Potential Lower-Bound Bias on the Net Benefit 

Measure

These results should be considered a lower-bound 

estimate of benefits. Whether the net benefits reflect potential benefits in geologically dissimilar areas is problematic 

until additional case studies are completed. On the basis of 

the proportion of the county actually evaluated in this study, 

this estimate of expected net benefits may be somewhat 

conservative. Our study area covers about 39 percent of the 

total area of Loudoun County and represents the benefits of 

only two applications. The improved geologic map of 

Loudoun County is anticipated to be used for such activities 

as airport expansion and siting, land use planning including 

mountainside and flood-plain development, design and 

construction of surface water impoundments, and siting of 

quarrying operations, borrow pits, and municipal well 

fields.

Implications of the Study Results

The new and more detailed geologic map of Loudoun 

County, Virginia, will be used in a significant number of 

additional applications. When used, the newly identified 

benefits accruable to the improved geologic map information will increase from the results listed in table n-5. The 

issue of whether all applications of improved geologic map 

information will yield a positive net benefit is unknown. 

Geologic maps tend to be more important to society in 

regions that exhibit economic growth. We chose the 

Loudoun County study area because it is a high growth area 

and, as such, will need a significant amount of planning in 

the foreseeable future. This is, of course, speculation on our 

part. However, the application of spatial information (geologic maps) for planning can be evaluated more completely 

after a number of case studies have been undertaken.

REFERENCES CITED

Agterberg, P.P., 1974, Geomathematics: Mathematical lackground and geo-science applications: Amsterdam, Els?vier 

Scientific Publishing Co., 596 p.

Bernknopf, R.L., Brookshire, D.S., Campbell, R.H., and Shapiro, C.D., 1988, An economic and geographic apprairal of 

a spatial natural hazard risk: A study of landslide mitigation 

rules: Environment and Planning A, v. 20, p. 621-631.

Bernknopf, R.L., Brookshire, D.S., and Thayer, M.A., 1990, 

Earthquake and volcano hazard notices: An economic evaluation of changes for risk perception: Journal of Environmental Economics and Management, v. 17, p. 1-15.

Burton, W.C., Froelich, A.J., Schindler, J.S., and Southworth, 

C.S., 1992, Geologic map of Loudoun County, Virginia: 

U.S. Geological Survey Open-File Report 92-716, scale 

1:100,000, 3 sheets, 16 pages of text. [A preliminary version 

of this map was used for this report.]

Commonwealth of Virginia, Department of Waste Management, 

1988, Solid waste management regulations (VR 672-20-10): 

Commonwealth of Virginia, 9 chapters and appendixes.

Conover, W.J., 1980, Practical non-parametric statistics, 2d ed.: 

New York, Wiley, 493 p.

Froelich, A.J., 1985, Map and geotechnical properties of sr'face 

materials of the Culpeper basin and vicinity, Virginia and 

Maryland: U.S. Geological Survey Miscellaneous Investigations Series Map I-1313-E, scale 1:125,000.

HDR Engineering, Inc., 1989, Summary report, Solid waste 

landfill site selection study identification of candidate kndfill 

sites for Loudoun County, Virginia: Alexandria, Va., HDR 

Engineering, Inc.

International Conference of Building Officials, 1979, Uniform 

Building Code, 1979 ed.: Whittier, Calif., 780 p.

Laczniak, R.J., andZenone, Chester, 1985, Ground-water resources of the Culpeper basin, Virginia and Maryland: U.S. 

Geological Survey Miscellaneous Investigations Serier Map 

I-1313-F, scale 1:125,000.

Leavy, B.D., Froelich, A.J., and Abram, B.C., 1983, Bedrock 

map and geotechnical properties of rocks of the Cu'neper 

basin and Vicinity, Virginia and Maryland: U.S. Geological 

Survey Miscellaneous Investigations Series Map I-1313-C, 

scale 1:125,000.

Lichtenberg, E., and Zilberman, D., 1988, Efficient regulation of 

environmental health risks: Quarterly Journal of Economics, 

v. 103, p. 167-178.

Lichtenberg, E., Zilberman, D., andBogen, K., 1989, Regv'ating 

environmental health risks under uncertainty: Groundwater 

contamination in California: Journal of Environmenta1 Economics and Management, v. 17, p. 22-34.

Lind, R.C., 1973, Spatial equilibrium, the theory of rents, aM the 

measurement of benefits from public programs: Quarterly 

Journal of Economics, v. 87, p. 188-207.

Milici, R.C., Spiker, C.T., and Wilson, J.M., compilers, 1963, 

Geologic map of Virginia: Virginia Division of Mineral 

Resources, scale 1:500,000, 1 sheet.

References Cited 41
Peltzman, S., 1976, Toward a more general theory of regulation:

Journal of Law and Economics, v. 19, p. 211-240. 

Raucher, R.L., 1986, The benefits and costs of policies related to

groundwater contamination: Land Economics, v. 62, p.

33^5. 

Roe, T., and Antonovitz, F., 1985, A producer's willingness

to pay for information under price uncertainty: Theory

and application: Southern Economics Journal, v. 52, p.

382-391. 

Rothschild, M., and Stiglitz, J., 1970, Increasing risk, I: A

definition: Journal of Economic Theory, v. 2, p. 225-243. 

Scherer, P.M., and Ross, D., 1990, Industrial market structure

and economic performance: Boston, Houghton Mifflin Co. 

Shavell, Steven, 1984, A model of the optimal use of liability and

safety regulation: Rand Journal of Economics, v. 15, p.

271-280. 

Stigler, G.J., 1971, The theory of economic regulation: Bell

Journal of Economics and Management Science, v. 2, p.

3-21.

Theil, H., 1971, Principles of econometrics: New York, Wiley, 

736 p.

U.S. Department of Transportation, Federal H^hway Administration, Maryland State Highway Administration, and Virginia Department of Transportation, 1990, Washington 

bypass from 1-95 in Virginia to 1-70 and U.S. 50 in 

Maryland, draft first tier Environmental Impact Statement 

and technical memoranda: Report NumHr FHWA-MDVA-EIS-90-01-D Region III, Baltimore, Md.

Varnes, D.J., 1974, The logic of geological maps, with reference 

to their interpretation and use for engineering purposes: U.S. 

Geological Survey Professional Paper 837, 48 p.

Weingast, B., and Moran, M., 1983, Bureaucratic discretion or 

congressional control? Regulatory policymaking by the Federal Trade Commission: Journal of Political Economy, v. 91, 

p. 765-800.

42 The Societal Value of Geologic Map Information
Chapter III

Geologic Maps as a Public Good: Provision of Geologic 

Maps and the Nature of the Demand for Geologic Map 

Information

INTRODUCTION

This chapter introduces technical issues related to the 

provision of regional geologic map information as a public 

good. Two important topics bear on these issues: (1) 

discussion of testable hypotheses concerning the public or 

private provision of regional geologic map information and 

(2) identification of the demand for derivative products 

based on geologic map products. We pose a variety of 

questions relative to who should provide geologic map 

information and discuss how these questions might be 

answered by use of rigorous economic methods. We present 

the initial documentation regarding the identification of the 

demand for regional geologic map information in the 

remaining sections.

PUBLIC PROVISION OF GEOLOGIC MAPS

In the following sections of the chapter, we identify 

and summarize a set of economics issues concerned with 

choosing the public or the private sector to provide regional 

geologic map information.

In the Organic Act, geologic mapping information is 

implicitly assumed to be a public good. This is a testable 

hypothesis. Given the debate about the need to privatize 

goods and services that now are provided by the government (a reduction in government expenditures), asserting 

that geologic mapping is a public good is no longer 

sufficient to resolve the issue. In the privatization debate, 

determining who should provide geologic map information 

requires two steps: deriving a conceptual model and conducting an empirical investigation. The unavailability of 

data at this time limits our investigation to the first of these 

steps.

What is the appropriate institutional choice for the 

production of information, the public sector or the private 

sector? Institutions may best be regarded as systems of 

constraints on individual behavior. The question becomes, 

what system of constraints is most likely to result in the 

lowest cost production of the desired product? This chapter 

contains an examination of a specific case regarding privatization the production of regional geologic map information by the USGS and the constraints surrounding such

information. Assuming that the USGS is the sole producer 

of regional geologic maps, we can narrow this analysis to 

whether production of regional geologic map information 

should be reassigned to the private sector. l

The debate on privatization has focused on two 

general classes of arguments:

1. The examination of the comparative efficiency of public 

sector versus private sector enterprise (Sappington and 

Stiglitz, 1987; Chamberlin and Jackson, 1987). Sappington and Stiglitz note that the recent interest in 

privatization may reflect the view that previous alignments of responsibility (to the public sector) were 

incorrect.

2. Whether or not the production constitutes a natural 

monopoly. In particular, the arguments have focured on 

whether public sector intervention is necessary, because 

a natural monopoly may not be sustainable (Baumol and 

others, 1982).

Apparently overlooked in the privatization deHte is 

the specific role that the nature of the good (product) may 

play in determining institutional choice. 2 This issue has two 

aspects: whether the good is a public good that would be 

underproduced by the private sector and whether the nature 

of the good that is produced is affected by the institution 

producing the good. The importance of both of these issues 

lies in making the choice between relying on public production or on regulation of licensed private producers.

To begin, we summarize whether or not regional 

geologic map information constitutes a public good. First, 

do regional geologic maps generate significant positive 

economic externalities? An affirmative finding suggests that 

the private sector will underproduce the information and

1 Several forms of privatization are possible. Vickers and Yarrow 

(1991) discuss privatization involving competitive firms, privatization of 

monopolies with accompanying regulation, and contracting out of publicly 

financed services. Our concerns have mainly to do with the latter two 

categories.

2 An exception is Wintrobe (1987), who criticizes the general 

precept of those studies purporting to show the inefficiencies of public 

sector production for omitting to recognize that the products prodiced by 

private sector firms may not be the same as those produced by public sector 

firms.

Public Provision of Geologic Maps 43
thereby provide justification for government/wance of the 

production of geologic information. However, by itself, this 

answer is not sufficient to justify public sector production. 

Because of the nature of the good that would be produced 

under different institutional settings, there is a need to 

further sort out the financing problem associated with the 

production decision. Second, is the production process 

subject to economies of scope and scale (that is, a multiproduct natural monopoly)? A finding that there are economies of scope and scale provides an argument for public 

sector production, although it also offers just as valid an 

argument for government regulation of a private sector 

producer. Again, the nature of the good produced under 

different institutional frameworks is a pivotal argument. 

Finally, the proposition that choice of institution affects the 

characteristics of the good could argue for a change in the 

choice of institution.

HISTORICAL PERSPECTIVE

USGS Responsibility

The existence of the Organic Act supports the view 

that Congress intended there to be a Federal role in the 

evaluation of the Nation's lands, environment, and resources. The USGS has the responsibility for classifying the 

resources on the public lands. The wording of the act 

suggests that the Congress wanted the role of the USGS to 

be one of creating and distributing geologic information as 

a public good. Further, Congress recognized, issues of 

public goods aside, that the production of the information is 

best served by a central Federal role. The purpose of this 

section is to highlight those portions of the Organic Act 

which support these interpretations.

The USGS is responsible for providing the geologic 

knowledge base associated with all Federal, State, and 

private lands. The Director is charged with the "classification of the public lands and examination of the geological 

structure, mineral resources and products of the national 

domain." (43 U.S.C. 31(a), p. 6.) The USGS also is 

responsible for earth science information collection beyond 

that of the national domain: "The authority ... to examine 

the geologic structure ... is expanded to authorize such 

examinations outside the national domain where determined 

by the Secretary to be in the national interest." (43 U.S.C. 

31(a), p. 6.)

From these excerpts of the Organic Act, Congress 

established the USGS as the appropriate institution to 

produce regional geologic information. Thus, the USGS, 

under the direction of the Director, was chosen as the 

primary agent for gathering earth science information. 

Further, we believe that the intent of Congress was to 

designate the USGS as the central organization for developing a national geologic information base. Specifically,

the types of information that are provided by the USGS 

"shall consist of geologic and economic mns, illustrating 

the resources and classification of the lands, and reports 

upon general and economic geology and paleontology." (43 

U.S.C. 31(a), p. 7.) Further, the USGS is directed to 

provide general (regional) information: ". . . shall execute 

no surveys or examinations for private partis or corporations." (43 U.S.C. 31(a), p. 6.)

Other Geologic Map Producers

The role of State geological surveys i« different:

State geological surveys have mandate? for collecting 

and compiling geologic information within their 

States and thus possess detailed knowledge of their 

regions and resources. This mandate contrasts with 

the USGS mandate to collect and synthesize geologic 

data from all parts of the Nation, a task that includes 

identifying and analyzing regional geologic problems 

that cross State boundaries. (USGS, 19"7, p. 14.)

There is a distinct difference in the mapping responsibilities of the USGS and the State Geological Surveys. 

The USGS does not systematically produce site-specific 

earth science information. For instance, when a local 

authority determines the right-of-way for a highway, it 

begins the process with a regional geologic map, while the 

necessity for detailed site-specific geological information 

arises only after the actual right-of-way has been chosen. A 

more detailed map or even a site map logically would be 

provided by another institution. As such, the USGS provides map information that is regional or base information 

(occasionally the USGS will conduct site-specific analyses). This distinction between Federal anc1 State roles is 

relevant to our discussion because different types of institutions will generate different types of geologic information. This contrast is addressed in "Conditions for Natural 

Monopoly."

The Distribution and Pricing of the Information

The distribution of geologic informal on also is dictated by the Organic Act as follows:

The Director... is authorized ... to dispose of the 

. . . geologic maps ... at such prices z nd under such 

regulations as may from time to time be fixed by him 

. . . and a number of copies of each m=»p . . . shall be 

distributed gratuitously among foreign governments 

and departments of our own Government to literary 

and scientific associations, and to ... educational 

institutions and libraries ... (43 U.S.C. 31 (a), p. 8.)

Further, the maps are to be distributed at a price that is 

below the average cost of production ard distribution: 

"Three thousand copies of each shall be published for 

scientific exchanges and for sale at the price of publication 

. . ." (43 U.S.C. 31(a), p. 7, emphasis added.) Through the

44 Geologic Maps as a Public Good
Organic Act, Congress dictated that earth science information should be widely available and clearly recognized that 

there was no social benefit to restricting access to geologic 

information. Thus, Congress reaffirmed its position that 

geologic information is a public good.

As part of the privatization debate, Chamberlin and 

Jackson (1987) provide an interesting perspective that 

suggests the debate could end at this point. They posit 

several conditions that, if fulfilled, would lead to the 

conclusion that privatization is warranted.

Where purchases are frequent, information is abundant, costs of a bad decision are small, externalities 

are minimal, and competition is the norm, privatization ought to be pursued. At the other extreme, in 

situations where externalities and collective interests 

abound, natural monopolies are dominant, distributional goals are important. . . public provision should 

continue, (abstract)

Clearly, all of the conditions for a private good are 

not fulfilled in the case of regional geologic map information. Purchases are infrequent, information is limited, and 

potential external costs are high. Thus, there is support for 

the argument that the production of geologic information 

should be carried out in the public sector.

Recently, a revision of OMB Circular No. A-130 

was published in the Federal Register that stated that 

information products should be sold at a price no greater 

than their marginal cost of production and distribution 

(Federal Register, April 29, 1992). Draft legislation has 

been introduced into Congress that effectively stipulates the 

same requirement (H.R. 3459, 1991).

GEOLOGIC INFORMATION AS A PUBLIC 

GOOD

Types of Information

Discussion of the public-good attributes of information begins with the distinction between general and specific 

information. A frequently made argument (see Musgrave, 

1959; Becker, 1975; Conn, 1979) is that general information is a public good, while specific information is a private 

good. There is the presumption that general information 

possesses more of the characteristics of a public good, 

having a lack of exclusion possibilities (anyone can use the 

information) and a lack of congestion costs (there is no cost 

of competition in the use of the information).

As applied to geologic maps, general information is 

collected at a scale that would be valuable for a variety of 

regional planning decisions encompassing a set of choices 

for land uses such as highway route selection, waste 

repository siting, energy exploration, and development

impacts. 3 Such information also would be available for a 

long period of time, given the slow rate of decay of its 

usefulness.

Specific information, on the other hand, is much 

more localized (for example, specific siting characteristics 

of interchanges along a single road right-of-way) and of 

much less use for further application. In essence, the 

collection of site-specific geologic information for determining the economic and environmental feasibility of siting 

a waste repository would be of little use in road planning 

unless the road is to be constructed in the same location as 

the proposed waste facility. As the information becomes 

more specific, the number of users becomes smaller. "Tius, 

geologic information can be both general and specific 

information. Our concern is with geologic maps in the 

general information category. We note, however, that in 

compiling specific information, general information is often 

necessary to provide background data. In what follow:, we 

discuss the economic concepts associated with the production of a public good in order to gain insight into the nature 

of regional geologic information. From this discussion we 

propose a series of testable hypotheses that can be examined 

empirically.

Public Goods

Pure public goods have two key characteristics. First, 

it is impossible, or inefficient, to exclude anyone (nonrival 

in consumption) from consuming the good once it is 

produced. 4 The availability to other users is not diminished. 

Second, the production of the good is characterized by 

jointness of supply (Musgrave, 1959). 5 The extreme case of 

jointness of supply arises when the cost of the good is made 

up entirely of fixed costs. The key characteristics of a public 

good are discussed in more detail in this section, including 

a brief introduction to the "free-rider" problem.

Nonrival in Consumption

Public goods are nonrival in consumption; that if, any 

one individual's consumption of the output does not reduce 

the consumption by others. Maps are available free to 

certain groups, readily available in certain repositories and 

reproducible, so there is little reason to believe tha* any

We are aware that a map cannot be all things to all users. We 

generalize, despite Varnes' (1974) caution, because it is highly likely that 

a regional geologic map will have at least two users.

For many types of public goods it may be technically impossible to 

exclude individuals from consumption of the good once it is produced. 

National defense is one such good, and, at a local level, police a"d fire 

protection also have this characteristic.

Economic efficiency is achieved when the cost of production is 

equal to the market valuation of the good for the last unit produced. If the 

marginal cost is zero (all costs are fixed and would be incurred whether one 

unit or one hundred units were produced), economic efficiency requires 

that the good be "sold" at zero price be made freely available.

Geologic Information as a Public Good 45
individual could be restricted from use. There is an obvious 

case of nonrival consumption for regional geologic maps.

A second aspect of the nonrival consumption argument is the ability to legally exclude others from making 

full use of information through the use of patents and 

copyrights. Such rules for exclusion are necessary for the 

private sector to have the appropriate incentive to produce 

map information that would be otherwise publicly provided 

information. Since individuals are able to obtain map 

information by not paying (a "free ride"), a private sector 

producer would not be able to recover the cost of production 

and would not provide the good.

Implementation of an exclusion scheme is difficult in 

the case of regional geologic map information because the 

range of potential users is large and dispersed. Effectively 

there is no way to implement a payment scheme. As a 

general rule, as information becomes more general, there is 

a larger group of potential beneficiaries and there is less 

likelihood that exclusion is feasible. This point can be seen 

by comparing the possibilities of exclusion from use of a 

general theoretical development in seismology and earthquake prediction in California, relative to an engineering 

rehabilitation job on a building in Berkeley, Calif., which is 

used in a particular application. In the case of the general 

information, there may be a role for the government to 

produce such information.

Jointness of Supply

The jointness of supply condition is fulfilled; that is, 

the per-unit production and distribution costs of regional 

geologic map information are near zero, while the per-unit 

costs of the information collection make up almost 100 

percent of total per-unit cost. Regional geologic maps 

possess this characteristic, because the bulk of the costs of 

producing such maps are borne "up front,"6 while the actual 

printing and distribution costs are relatively small. Because 

the printing costs are relatively low, the cost of serving an 

additional consumer also is small. 7 For example, the 

expected per-unit cost of information collection and synthesis for a l:100,000-scale map covering Loudoun County, 

Virginia, is about $1.16 million, while the cost of production and distribution are about $8.44 per unit. 8 Therefore, 

excluding consumers once the good has been produced is 

inefficient.

Table 111-1. Payoffs to the provision of a public good

[C, contribution; NC, no contribution]

Person B

These costs comprise the data collection, organization, interpretation, coding, and other functions that precede the actual publication of the 

USGS geologic maps.

7 See Matti and others (1988) for a presentation of relative cost 

figures.

8 See Matti and others (1988, table 1) for the costs of producing a 

regional geologic map. Total costs of map compilation and publication are 

$21,100. The normal production run is 2,500 copies.

Person A C

NC

C

4,4

5, 1

NC

1, 5

2, 2

"Free-Rider" Problem

When the above two characteristics for a public good 

occur, in most cases, the private supply of this type of good 

such as a regional geologic map will yield inefficient 

market outcomes. Too little geologic information is produced, and a market failure ensues. This type of market 

failure is known as the "free-rider" problerr. Free riders are 

individuals or groups who attempt to enjoy a good while not 

paying for it; it is impossible or inefficient to exclude them 

from the activity. The nature of the free-rider problem may 

be illustrated as an application of the prisoner's dilemma 

(see Mueller, 1989, p. 8-17), summarized as follows:

Consider a simple economy with two persons. Each 

person begins with an endowment of two dollar's and 

each has two choices (strategies): to contribute to the 

provision of a public good or not to contribute. The 

public good is generated by summing the total contributions and multiplying this by 1.5 to reflect the 

consumer surplus (total area under th*. demand curve 

or total willingness to pay for a commodity) generated 

by the public good. The public good is enjoyed equally 

by both persons, and their payoffs are given by the 

value of the public good minus their contributions. The 

payoffs to these strategies are shown ir table III-l. For 

example, if both choose C (contribution), the total 

contribution is 4, the value of the public good is 6, and 

each person receives 4 as his net payoF. If both choose 

NC (no contribution), then they keep tl Mr endowment, 

so the payoff is $2 to each. If one contributes and the 

other does not, then the contributor receives $1 (his 

share of the public good is $3, and hr contribution is 

$2), while the noncontributor receives $5 (share of the 

public good is 3 and he keeps his endowment). The 

equilibrium outcome in this game is (NC, NC) with no 

public good being produced. This result is unfortunate, 

since the total payoff is clearly greater in the (C, C) 

outcome. The (NC, NC) outcome arises because NC is 

a dominant strategy for both of the persons in this 

economy. That is to say, it is not in either individual's 

interest to separately contribute to the public good 

since the payoff from this strategy is lower than from 

the strategy of not contributing.

The outcome for the general case of the pure public 

good is that private (voluntary) production will lead to

46 Geologic Maps as a Public Good
suboptimal levels of production. 9 As a result of this type of 

individual behavior, economics research has argued that the 

government should intervene to ensure proper provision of 

the good. 10

CONDITIONS FOR NATURAL MONOPOLY

The Natural Monopoly Framework

A natural monopoly is said to exist when the least 

cost means of producing a given quantity of a good (or 

group of goods) is achieved only when the production is 

carried out by a single firm. The technical condition for an 

industry to be a natural monopoly is that the cost function be 

subadditive (see Sharkey, 1982; Baumol and others, 1982). 

For a single-product firm, the cost function (C) is subadditive if:

C(q)< C(aq) (III-D

where 0<«< 1 and aq represents the fraction of the total 

quantity (q) produced by each firm. Equation III-l states 

that production costs are lower if the entire output is 

produced by one firm rather than two (or more) firms.

Geographic regions of the United States are unique; 

therefore, the production of regional geologic map information is a multiproduct industry. In the case of multiproduct industries, subadditivity of the cost function requires 

that

i) + C(q2) > (IH-2)

When we see some voluntary contributions in the "real world" it is 

usually the case that the good generates some private benefits (including 

the utility from donating) or that the good is not a pure public good. Some 

classes of public goods may be provided via the private sector, although 

not necessarily at efficient quantities. Cornes and Sandier (1986) and 

Bergstrom and others (1986) demonstrate these findings. In their setting, 

some individual is willing to privately provide an initial quantity of the 

public good because his marginal utility exceeds the cost of the good. For 

other individuals in the economy, the public good is viewed as an income 

transfer, and, where the public good is normal, the result is an increase in 

the willingness to pay for the good by these persons. The resulting 

response is analogous to a Cournot reaction and can be shown to lead to 

positive provision. The key initial assumption of this analysis is that at 

least one person's demand exceeds the cost of providing the first unit of the 

good. For most public goods this is not the case, and the outcome is that 

private provision will be at zero levels.

Where the cost of the public good is such that no one person is 

willing to supply any amount on his own, there is some debate as to 

whether the private market will supply a positive amount. Where use of the 

good may be prevented after it is made available (a club good), Bagnoli 

and McKee (199la) have shown that a "focal equilibrium" exists in which 

the good is supplied at efficient levels. Where the good is subject to ex post 

consumption by noncontributors, Isaac and others (1985) have shown that 

the good is generally undersupplied.

The free rider problem must be overcome by compelling payments for public goods through a tax system with penalties for noncompliance.

To argue that the production of regional geologic information is a natural monopoly, the cost function must be 

subadditive over different geographic regions. The sources 

of such cost subadditivity are a useful starting point for an 

investigation. Specifically, we begin by deternrning 

whether the production of regional geologic information is 

characterized by the following:

1. Substantial "up front," or setup, costs associated with 

the production of regional geologic information for a 

particular region.

2. A decrease in per-unit cost for a given map of a region 

(this is a corollary of 1).

3. Cost complementarities across map types within a £iven 

region (the cost function is subadditive within a region).

4. Cost complementarities across regions (the cost function 

is subadditive across regions).

If all of these conditions are found to exist, there is support 

for a natural monopoly. 11

The Cost Function

For a given region, the cost function can be characterized in equation III-3 (adapted from Alchian, 1959) as:

C = f(V, x, T, m) (HI-3)

where C is total cost;

V is the planned volume of maps (of all types) of a 

region to be produced over a foreseeable time 

frame;

jc is the rate of output (total number of all typ?s of 

maps of a region to be produced over a given 

time span);

T is the time at which the production is to start; and 

m is the length of time the production is expected to

last (production will end at T + m). 

If any three of the terms in this cost function are fixed, the 

other is determined. For multiple geographic regions, this 

function is redefined as follows: the planned volume, V, 

refers to the planned total volume of maps produced across 

all regions, and jc refers to the total rate of output across all 

regions.

A number of propositions arise when this cost function is used. The empirical question of whether the production of regional geologic map information satisfies the 

conditions of a natural monopoly can be investigated with 

data from the USGS production of regional geologic map 

information.

Additionally, there is the question of whether the industry is 

vulnerable to a class of "cream-skimming," in which other producers enter 

to produce a subset of the regional information bases. The result is 1 'gher 

total costs overall.

Conditions for Natural Monopoly 47
Proposition 1:

-V Y=v -Xn , v=v V V n o (HI-4)

In equation III-4, the cost declines (in constant 

dollars) as the production start time, T, is moved back. This 

proposition allows the producer some lead time to acquire 

inputs and to plan the production process more carefully. If 

proposition 1 is true for regional geologic map production, 

the implication is that there is an optimal program for the 

production of maps which matches willingness to pay for 

timely information to the cost of production. Each geographic region represents a different map, and the demand 

for these maps is not uniform. Where the demand is low 

(willingness to pay is low), delaying production to achieve 

cost savings may be appropriate policy. This point will be 

elaborated in connection with proposition 3.

When proposition 1 is coupled with subadditivity of 

costs over regions, there is a clear case for natural monopoly. The cost savings arise from an optimal schedule of 

production over regions.

Proposition 2:

dC/dV = 0, 82C/dV2 ,=,, T=T 0

In equation III-5, the marginal cost declines as the 

planned volume (number of different types of maps produced within a region) increases. With higher planned 

volume, the producer can take advantage of production 

technologies that may have higher setup (basic information 

gathering) costs but have reduced per-unit production costs 

sufficiently enough to recover the setup costs. In the 

multiple region setting, proposition 2 introduces the possibility of significant cost savings as the number of areas to be 

mapped increases.

Proposition 3:

1 . The cost of production of future map types declines as 

more types are produced within a given region or at a 

given time.

2. The cost of production of maps in new regions is lower, 

on average, than that in the current region.

This proposition states that the production process is subject 

to considerable learning effects. If the production of 

regional geologic maps obeys the above conditions, then 

production should be carried out by a single "firm" in order 

to capture the gains from learning. Further, the production 

of maps should be ordered in such a way that the maps 

demonstrating the highest willingness to pay should be 

produced first.

To demonstrate the existence of a natural monopoly 

in the single product case, it is sufficient to demonstrate the 

existence of decreasing costs of production and distribution 

of the output for the single product. More generally, one

must test whether the cost function is sub additive over a 

relevant range of the quantity produced (Paumol, 1977). 

This is fairly simple to demonstrate by determining whether 

average and marginal cost decrease with increase in output. 

However, as the discussion indicates, the problem is 

slightly more complicated when dealing with a good that is 

complex and that is subject to a high fixed cost of 

production.

For the multiple task or multiple product case, the 

situation is more complicated. We must determine whether 

the cost function is subadditive over several products. 12 If 

subadditivity exists, then there are "economies of scope": 

the costs of producing the component parts of the regional 

geologic information may be greater than the costs of 

producing the whole. Such a situation may arise from cost 

complementarities, shared fixed assets, or learning on the 

part of workers.

Subadditive cost functions are a necessary condition 

for the efficient industry structure to be a monopoly. 

However, such a structure may not be sustainable through 

only private market forces. In a multiproduc* setting there is 

the potential for firm entry to occur in which the new firm 

produces only a subset of the entire product line. While 

production costs will be higher, the entrant could earn a 

profit. However, society will lose because the total cost of 

the entire line of products will be greater with the two 

producers (the economies of scope will be foregone). This 

condition for sustainability may be discussed with the aid of 

figures III-l and III-2, which demonstrate the situation for 

a two-product operation. The axes denote the prices of 

goods 1 and 2.

In figure III-l, the locus through A ard B denotes the 

set of zero profit price vectors. Inside this locus the profits 

are positive, while outside the locus profits are negative. 

Only the portion of the locus from A to B is relevant, 

because all other points require higher price^ of at least one 

of the goods. Sustainability requires that prices on AB be 

such as to not permit profitable entry into one of the two 

product markets.

Figure III-2 depicts the case for which the demand 

for the products is independent (neither substitutes nor 

complements). This case appears to be the most relevant to 

the issue, because, for example, a regional geologic map 

produced for Nebraska is not a substitute fcr a map of New 

Jersey. The shaded areas denote ranges for the prices of 

goods 1 and 2 for which profits are positive, and the locus 

AB is the same as in figure III-l. The crosshatched area 

shows the region in which two single-product firms could 

simultaneously operate. The locus CD denotes prices that 

will yield zero profit and not attract entry, because there are 

no lower prices for good 1 or 2 that will yield a positive

For a detailed discussion of subadditivity of cost functions and 

their implications for the natural monopoly argumen*. see Baumol and 

others (1982).

48 Geologic Maps as a Public Good
Price of Good? 71 = 0

0 Price of Good

Figure 111-1. Total profit of a multiproduct firm that 

produces information. The locus through A and B 

represents the isoprofit locus for IT = 0; inside this 

locus IT > 0; outside, IT < 0; relevant range of IT = 0 is 

AB, since all other points require higher price of goods 

1 and 2.

Price?

Price!

Figure 111-2. Isoquants of a multiproduct firm showing 

the requirements for industry entry. Goods 1 and 2 are 

independent. The crosshatched area denotes price 

ranges where two single-product firms could simultaneously operate. CD denotes prices on AB (zero profit 

locus) for which the natural monopoly A'B' denotes a 

two-product analog to the nonsustainable case.

profit. The natural monopoly here is sustainable without 

government intervention; the firm can prevent entry through 

its own pricing strategy. This demonstrates that in a natural

monopoly in which the products have independent 

demands, sustainable prices always exist. The locus CD is 

not empty.

THE NATURE OF THE GOOD IS DETERMINED 

BY THE INSTITUTION

Other Governments and Agencies

A clear case for natural monopoly is not sufficier* for 

public sector production to be the institutional choice. In 

fact, it is not strictly necessary. We consider the impact of 

the choice of institution on the characteristics of the good 

that is produced and argue that the institution will mrke a 

difference in the good.

First, a great deal of USGS information is used by 

Federal, State, and local governments (as well as users in 

the private sector). If the USGS did not produce this 

information, would these agencies receive the types of 

information necessary for land use planning (zoning) and 

economic development from a private sector firm? Second, 

there is the question of who should pay for and regulate the 

quality of this information, given that the Federal Government frequently mandates its use (as under EPA regulations, for example) by State and local governments. For 

instance, contracting out the information is not costless.

Monitoring the Producer of Information

The production of information cannot be monitored 

costlessly by the party that will be using the information. 

The key point is that the production of regional geologic 

map information is a science. The design of the sampling 

procedure (how dense, how deep, how repeated, and how it 

should be done) and the interpretation of the data are 

essentially the tasks of the geologist. In such situations there 

is the potential to produce biased output. It may be that a 

public sector agency would not always have the resources to 

produce the most reliable data, but it is likely not to ha^e an 

incentive to produce biased results. The same result may not 

be true of private sector firms. Given the consequences of 

incorrect information (impact on such things as waste site 

location, oil exploration, zoning, and construction) and the 

irreversible nature of many of the decisions made with this 

information, the information must be unbiased and as close 

to correct as possible.

Vertical Integration

Another argument that may be made is that it will be 

costly to specify all the important attributes of the regional 

geologic information. In the case of private sector production, the response to this problem is vertical integration 

(Klein and others, 1978; Grossman and Hart, 1986). This

The Nature of the Good is Determined by the Institution 49
response implies increasing concentration in the energy 

exploration industry, for example. In this case, the small 

exploration firms will not be in a position to provide 

information for themselves and consequently will be 

required to rely on the larger firms to provide timely data.

Network Externalities

Finally, there are many goods for which the utility 

derived from use increases as the number of others using 

them increases. Good examples are word processing software, fax machines, and telephone answering machines. 

The greater the number of people using a particular word 

processor program, the easier it is to exchange information. 

The same is true of fax machines and answering machines. 

Katz and Shapiro (1986) discuss some general conditions 

for such network externalities to be relevant.

Regional geologic information satisfies these conditions. Consider the siting of hazardous waste dumps. The 

greater the number of parties using the same regional 

geologic information, the more likely there will be some 

agreement on the choice of sites. Using maps with the same 

information will significantly reduce administrative procedural costs associated with siting such facilities.

TESTABLE HYPOTHESES

The issue of privatization of government activities is 

multifaceted. We have explored the issue of privatization in 

the case of the production of regional geologic map information: Should the production of regional geologic map 

information be undertaken by the federal (public) sector, 

contracted out to the private sector, or should all responsibility be assigned to the private sector? The Congress has 

mandated through the National Geologic Mapping Act 

(P.L. 102-285) that regional geologic information is a 

public good, and it follows that socially efficient production 

should be carried out by the Federal Government.

Moving beyond just accepting the Congressional 

mandate, we have explored the technical requirements that 

must be met for the Federal Government to be the appropriate institution for the production of regional geologic 

information. In doing so, we distinguished between two 

broad classes of geologic information: specific (larger than 

1:24,000 scale) and general (1:24,000 scale or smaller). It is 

the latter that is of specific interest in our discussion.

We considered three different technical requirements. 

First, does the good regional geologic map informationfulfill the conditions for being a public good? The second 

technical requirement for public sector production is that the 

least cost means of production is a single producer. We 

explored the conditions for a natural monopoly. Finally, the 

choice of institutions is shown to depend on the interaction 

between institutional setting and the characteristics of the

good that is produced. We considered the role of the 

institutional setting for the characteristics of the good. It 

appears that the characteristics of the good will vary under 

alternative institutional settings. We argu? that this is a 

critical consideration for determining the appropriate institutional framework for the production of regional geologic 

information.

The following hypotheses can be tested to suggest 

answers to the economic issues that have Hen posed. For 

the section "Geologic Information as a Public Good," the 

question is whether it is socially optimal to exclude individuals from using general information such as regional 

geologic map information. Do we want the patent or 

copyright system to cover truly general knowledge about 

our environment? A great deal of the information produced 

by the USGS may be classified as general knowledge, as 

opposed to specific knowledge. In light of Federally 

imposed requirements for the use of regional geologic map 

information, Federal regulatory requirements would be 

difficult to satisfy if regional geologic trap information 

were copyrighted. Further, the public good argument is a 

necessary condition in supporting continued public sector 

provision (and possibly production) of the information 

product.

H! (Nonrival in Consumption): The marginal cost of 

an additional user of regional geologic information is 

zero.

Once regional geologic map information has been produced, it is essentially costless to provide to additional 

users. In addition, the valuation of the previous users is not 

affected when additional users are added.

H2 (Jointness in Supply): A priori, the*-e is effectively 

zero private provision of general regional geologic 

map information. 13

The approach that would need to be taken to test the 

hypothesis could be in two parts. First, we could attempt to 

observe the provision of regional geologic information by 

the private sector. Second, we could utilize survey techniques to attempt to observe the marginal wi'lingness to pay 

for regional geologic information relative to the cost.

H3 (Free Rider): Ex post, if the good is being 

provided, then exclusion is problematic.

The essential point is that regional geologic map 

information is different from road maps, books, tapes, and 

other physical manifestations of information. Behind each 

of these examples are the ideas embodied in the product,

We should be clear that we are not hypothesizing that no private 

maps exist. However, those that do exist will consist of more specific 

information than would be produced by the public sector. Private-sectorproduced maps will be considered proprietary information. The energy 

industry is a good example of a private organization that produces such 

maps.

50 Geologic Maps as a Public Good
and these ideas are protected by patent or copyright laws. 

An important characteristic of the private production of 

such ideas is that the cost of the road map or tape is small, 

and the good is priced to reduce the incentives to illegally 

reproduce the good. Such goods depend on a large market 

if they are to be produced efficiently. The question here is 

whether regional geologic map information shares the 

characteristics of road maps, musical tapes, and such. 

Initial observation suggests there may be important differences.

In order to test hypothesis H3 , we would have to turn 

to the development of an availability index. This would 

involve ascertaining the general availability of the good and 

demonstrating that, unlike the situation with private goods, 

exclusion is difficult.

There are several additional testable hypotheses from 

the section "Conditions for Natural Monopoly" that concern 

different aspects of the costs of producing regional geologic 

maps. Propositions 1,2, and 3 represent testable hypotheses 

concerning the cost behavior of the production of regional 

geologic maps. Proposition 1 implies that cost will be lower 

for the production of maps that have longer lead times. 

Specifically:

H4: The per-unit cost of regional geologic information is a decreasing function of the length of the 

planning horizon for the production of the information.

Proposition 2 implies that per-unit costs will be a 

decreasing function of the planned volume of the particular 

map output. If the USGS is assumed to be able to forecast 

the demand for the product (the actual output is the planned 

output), then:

H5 : The average per-unit costs of the actual maps 

produced will be inversely related to the level of 

output.

Proposition 3 states that the production of maps is 

subject to the effects of learning by doing. Thus:

H6: The cost per set of map information falls as the 

variety of maps produced increases.

This hypothesis would be supported when there are cost 

advantages to having a centralized group of geologists 

producing information for the entire Nation rather than 

state-level production. Such cost savings may arise from 

sharing of information or from the accumulation of human 

capital in the production of a specialized task (Becker, 

1975).

Each of these hypotheses has a corresponding multiregion version. As noted above, the production of maps 

within the USGS is a multiproduct operation. Economies 

may be realized through the production of a single map, as 

suggested by the preceding discussion. Economies also may 

be realized through joint production sometimes referred to

as economies of scope. Where these economies exist, the 

cost function will be subadditive.

H7 : The cost function for the production of regional 

geologic information is subadditive.

Subadditivity may arise from several sources. The learning 

effects referred to in proposition 3 will provide economies 

of scope where the skills required in the production of one 

product are used in the production of other products. There 

may be common costs associated with the production 

process. The cost function may be of the form:

C(q) = C0 

and C(ft) = C0

C2(q2) cn-6)

where i is an output.

A further empirical question is whether the USGS is 

a sustainable natural monopoly or whether there is some 

potential for the private sector to enter part of the market for 

regional geologic maps (and information) with the result 

that the total cost of the information is increased.

The cost function for the production of the various 

regional geologic map information products produce-i by 

the USGS is written as equation HI-7:

C(q) = F(S) (in-7)

where 5 is the set of outputs with positive output, F(S) is the 

fixed cost associated with the set 5, and q is the constant 

marginal cost of producing the output, i. An output (i) may 

be regional geologic mapping information for a given 

region or it may be mapping information produced at 

different scales.

Sharkey (1982) has shown that a sufficient condition 

for the existence of sustainable prices is that costs satisfy 

weak complementarity and demands are independent. ""Tius:

H8 : Costs of producing regional geologic mapping 

information for different regions (and scales) are 

(weakly) complementary.

Hg: The demands for the various regional geologic 

information outputs are independent (neither substitutes nor complements).

The section "Conditions for Natural Mononoly" 

yields testable hypotheses less readily than the other sections. However, we can investigate and compare the type of 

specific geologic information produced by private factor 

firms and public sector agencies. We would hypothesize 

that the information produced will be different:

H10 : Private sector production of geologic information will focus on less general types of infonration 

(that is, be more specific), smaller geographic areas, 

and will be in less accessible forms of infonration 

provision.

Testable Hypotheses 51
Table 111-2. Federal users of USGS geologic map 

information

USER APPLICATION

Department of Interior (DOI): 

Bureau of Land Management

(BLM)

Bureau of Mines (BOM) 

Bureau of Reclamation

(BOR) 

Office of Surface Mining

(OSM) 

Minerals Management

Service (MMS) 

National Parks Service (NFS) 

Fish and Wildlife Service

(FWS)

Department of Defense (DOD): 

Army Corps of Engineers

Department of Energy (DOE)

Environmental Protection 

Agency (EPA)

Nuclear Regulatory Commission 

(NRC)

U.S. Department of Agriculture 

(USDA): 

Agricultural Research Service

(ARS)

Forest Service (FS) 

Soil Conservation Service 

(SCS)

Department of Transportation 

(DOT)

Housing and Urban Development (HUD)

Federal Emergency Management Agency (FEMA)

Tennessee Valley Authority 

(TVA)

Energy and mineral resource 

assessments; resource management plans; multiple-use 

plans; dam and reservoir 

development; wilderness 

assessments; ground-failure 

stability analysis.

Development planning; waste 

repositories; geologichazards analysis; siting of 

water works.

Energy resource assessments; 

waste repository developments and cleanup; seismic 

evaluations; siting of nuclear 

tests.

Assessment of naturally 

occurring toxins; groundwater assessments, multipleuse plans, waste site evaluations.

Nuclear plant and waste site 

evaluations.

Toxic substance evaluation; 

ground-water resource evaluation; wilderness assessment; Resource Management Plans.

Transportation and utility 

corridor evaluations; airport 

and facilities siting; 

geologic-hazards evaluation.

Transportation and utility 

corridor evaluations; 

geologic-hazards evaluation; urban area zoning.

Geologic-hazards evaluation.

Geologic-hazards and groundwater evaluations.

It would seem likely that the regional geologic 

information available will differ across regions according to 

the relative shares produced by public and private sector 

firms:

Hn: Where there is greater private production of 

geologic information, there will be less information 

in total, the information will be more specific, and it 

will be more costly to use.

In order to test these hypotheses, ve possibly will 

have to assemble a survey. This survey wH investigate the 

nature of the information produced by the private sector.

BACKGROUND ON NATIONAL GEOLOGIC 

MAPPING PROGRAM

Beginning in 1988, the National Geologic Mapping 

(NGM) Program of the U.S. Geological f'lrvey began an 

outreach to selected Bureaus in the Department of Interior 

and other Federal agencies to identify th^ir priorities for 

geologic mapping. This was undertaken to help the program 

in its long-term planning and to begin closer coordination 

between the USGS and other Federal agencies in the area of 

geologic mapping.

NEEDS FOR GEOLOGIC MAP INFORMATION

In addition to prioritized requirements for geologic 

map information already submitted to the USGS National 

Geologic Mapping Program, a derived demand can be 

identified by looking at past cooperative projects with a 

variety of Federal agencies. Table HI-2 lists the past and 

present Federal users of USGS geologic map information 

and the societal application.

REFERENCES CITED

Alchian, A., 1959, Costs and outputs, in Abramovitz, M., ed., 

The allocation of economic resources: Falo Alto, Calif., 

Stanford University Press.

Bagnoli, M., and McKee, M., 1991, Voluntary contribution 

games: Efficient private provision of public goods: Economic 

Inquiry, v. 29, no. 2, p. 351-366.

Baumol, W.J., 1977, On the proper cost tests for natural monopoly in a multiproduct industry: American Economic Review, 

v. 67, p. 809-822.

Baumol, W.J., Panzar, J., and Willig, R., 1982, Contestable 

markets and the theory of industry structure: New York, 

Harcourt Brace and Jovanovich, 510 p.

Becker, G., 1975, Human capital, 2d ed.: Chicago, HI., University of Chicago Press, 268 p.

Bergstrom, T., Blume, L., and Varian, H., 19f 6, On the private 

provision of public goods: Journal of Public Economics, v. 

29, no. 1, p. 25-39.

Chamberlin, J.R., and Jackson, J.E., 1987, Privatization as 

institutional choice: Journal of Policy Analysis and Management, v. 6, no. 4, p. 586-611.

Cornes, R., and Sandier, T., 1986, The theor' of externalities, 

public goods and club goods: New York, Cambridge University Press, 451 p.

Federal Register, 1992, OMB management of Federal information 

resources: Proposed revision of OMB Circular No. A-130, 

April 29, 1992, p. 1-10.

52 Geologic Maps as a Public Good
Grossman, S., and Hart, O., 1986, An analysis of the principalagent problem: Econometrica, v. 51, no. 1, p. 7 45.

Isaac, R.M., McCue, K., and Plott, C.R., 1985, Public good 

provision in an experimental environment: Journal of Public 

Economics, v. 26, no. 2, p. 51-74.

Katz, M., and Shapiro, C., 1986, Technology adoption in the 

presence of network externalities: Journal of Political Economy, v. 94, no. 4, p. 822-841.

Klein, B., Crawford, R., and Alchian, A., 1978, Vertical integration, appropriable rents, and the competitive contracting 

process: Journal of Law and Economics, v. 21, no. 2, p. 

297-326.

Matti, J.C., Bernknopf, R.L., Van Driel, J.N., Ulrich, G.E., and 

Schindler, J.S., 1988, Photomechanical versus computerbased methods of preparing and disseminating geologic-map 

information: A comparison of costs and savings: U.S. Geological Survey administrative report, April 1988, 25 p.

Mueller, D.C., 1989, Public choice II: New York, Cambridge 

University Press, p. 8-17.

Musgrave, R.A., 1959, The theory of public finance: New York, 

Macmillan, 628 p.

Pauly, M.V., 1968, The economics of moral hazard: Ame-ican 

Economic Review v. 58, no. 3, p. 531-537.

Sappington, David, and Stiglitz, Joseph, 1987, Privatization, 

information, and incentives: Journal of Policy Analysis and 

Management, v. 6, no. 4, p. 567-582.

Sharkey, W., 1982, The theory of natural monopoly: New York, 

Cambridge University Press, 229 p.

U.S. Geological Survey, 1987, National Geologic Mapping Program: Goals, objectives, and long range plans: U.S. Geological Survey Circular 1020, 29 p.

Varnes, D.J., 1974, The logic of geological maps, with reference 

to their interpretation and use for engineering purposes: U.S. 

Geological Survey Professional Paper 837, 48 p.

Vickers, J., and Yarrow, G., 1991, Economic perspectives on 

privatization: Economic Perspective, v. 5, no. 2, p. 111-132.

Wintrobe, R., 1987, The market for corporate control and the 

market for political control: Journal of Law, Economics, and 

Organizations, v. 3, no. 2, p. 435-448.

References Cited 53