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THE INFLUENCE OF SAND AND GRAVEL EXTRACTION
0N URBAN DEVELOPMENT

BY

Lisa B. Holzman

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Resource Development

198R

ABSTRACT

THE INFLUENCE OF SAND AND GRAVE]. EXTRACTION
ON URBAN DEVELOPENT

by

Lisa R. Holzman

Land use changes in the vicinity of thirty-nine sand and gravel
extraction sites in Oakland County, Michigan, were examined using the
microcomputer-based Earth Resources Data and Analysis System 800 for the
period 1957-1980 to determine: (1) patterns of urban development in the
vicinity of extractive operations; (2) the sphere of influence of
extraction sites on surrounding development; and (3) the relationship
between site characteristics and the identified development patterns and
spheres of influence.

The general pattern observed was one of increased development with
distance from the site. This pattern existed for an average distance of
686 meters. Beyond this point development trends were similiar to those
in surrounding areas. Due to the fact that most sites were located at
the outer fringes of urban centers, it is wobable that this observed
development pattern resulted from urban sprawl. The increase in
development over time in the vicinity of extractive operations supports
the idea that extraction has a neutral impact on urban development. The
existing generalizations that sand and gravel operations discourage

urban development were not substantiated by this research.

To D. B. for keeping me going!

11

ACKNW LEDGMENTS

I would like to take this opportunity to express my appreciation to
those individuals who have helped me with various aspects of this
project. First, my thanks to Peter Kakela, Department of Resource
Development, for providing guidance, support, and financial assistance
throughout my entire stay at MSU. Also, my other committee members;
Anthony Bauer, Department of Landscape Architecture, who fostered m
interests in sand and gravel extraction, and Milton Steinmueller,
Department of Resource Development, who did much to broaden my horizons.
Special thanks go to Russ Kruska, CRIBS, for helping me with the
analysis section of this project. Also, to the other people at CRIBS
for providing guidance and financial assistance. As well, thanks go to
Jo-ellen Darcy for editing this paper. Last, but not least, my family,

for providing their support through my entire education experience.

LRH
June, 198A

111

TABLE OF CONTENTS

List of Tables.........O0......O...OOOOOOOOOOOOOOOOOOOO0.0...

List Of FinQSOOCOOOO0......O....0.0...OOOOOOOOOOCOOOOOOOOOO

Chapter I. IntrOduction. O O I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
The Rese ”eh Pm blem O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
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The mm” or the studYOOOOO0.00.0.0...0.00.00.00.00...

Chapter II. Literature Review...............................
Introduction............................................
Sand and Gravel Extraction..............................

Location of Operations.............................
Geologic Constraints..........................
Extracting and Processing Techniques..........
Accessibility of Harket.......................
Nature of Economic Market.....................
Government Restrictions.......................

Impacts of Operations..............................
Identification and Mitigation.................
Company Planning to Mitigate Impacts..........

Community Planning to Control Impacts.........

iv

vi

vii

1O
1O
11
11
1h
16

Urban Development.......................................
Suburbanization....................................
Residential Development............................

Chapter III. Method.........................................

menieHOOOOOOO0.000.000.0000.COOCCOCOOOOOOOOOOOOOOO0.0.

Determination of Study Area Boundaries..................
Land Use Interpretation.................................
Analy8180000000000000000.0.0....OOOOOOOOOOOOOOOOOO0.0..O

sources or 818300.00...OOOOOOCOOOOOOOOOOOOOOOOCOOOOOOOOC

smaryOOOOOO0.0000000000000000000000COOOOOOOOOOOOOOO0.0

Chapter IV. Results and Interpretation......................
Introduction............................................
Results.................................................
Interpretation..........................................

Patterns of Urban Development......................
Sphere of Influence

Pit Characterist1CBOOOOOOOOOOOOOOOOOIOOOOOOOOOOO...

Chapter V. Summary, Conclusions, and Recommendations........

serOOOOOO00......00....0.0.0...OOOOCOOOOOOOOOOOOOOCO

concluaions.OOOCOOCOOOOOOOOOOOOOCOOOIOOOOIOOOOOOOOOOOOOC

Recommendations For Future Research.....................

prndixOOOOOOOOOOCOOOOOOOOOOOOOOOOOOOOOOOOOOOCOOOOOOOOOOOOC.

References.O.0.O..0.IO.00.000.00.00...OOCOOOOOOOOOOOOOOOOOOOO

18
18
18
22
22
22
26
32
37

N2

”3
‘33
N3
115
58
69
73

85
85
87
9O

93

95

LIST OF TABLES

Table 1. Extractive Sites--Active Years.................... AN
Table 2. Incomplete Searches............................... ”6
Table 3. Crosstabulation--AV26, 1980....................... 57
Table u. Spatial Development Patterns...................... 60
Table 5. Temporal Development Patterns..................... 6n
Table 6. Rate of Development............................... 68
Table 7. Sphere of Influence............................... 70
Table 8. Pit Characteristics............................... 75
Table 9. Groups Based on Pit Characteristics............... 77
Table 10. Pit Group Statistics.............................. 81

Table 11. Statistical Comparison of Pit Groups.............. 83

vi

Figure
Figure
Figure
Figure

Figure

Figure 6.

Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure

Figure

7.

8.

9.

10.
11.
12.
13.
1h.
15.
16.
17.
18.
19.
20.

21.

LIST OF FIGURES

Location of Study Areas..........................

White Lake
Avon Study
Example of
White Lake
White Lake
White Lake
White Lake
Avon Study
Avon Study
Avon Study
Avon Study
White Lake
Avon Study
Example of

Example of

Study Area, Extraction Sites..........
Area, Extraction Sites................
a Search..............................
Study Area-Land Use, 1957............
Study Area--Land Use, 196N............
Study Area--Land Use, 1972............
Study Area-~Land Use, 1980............
Area-Land Use, 1957..................
Areap-Land Use, 196N..................
Area-u-Land Use, 1972
Area--Land Use, 1980..................
Study Area--Land Use Distribution.....
Area--Land Use Distribution...........
a Distal Pattern-WN..................

a meim1 Pattern--w1200000000000000.

Rate of Development-Wu..........................

Sphere Of Inflmnce.OOOOOOOOOOOOOOOOOO00.0.0.0...

Sphere of Influence--Location Groups.............

Sphere Of Inflmnce-éize Groups. 0 o o o o o o o o o o o o o o o

Sphere of Influence-~Phase of Pit Development....

vii

an
26
27
36
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as
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so
51
52
53
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55
56
61
62
66
71
78
79
so

CHAPTER I

INTRODUCTION

The Research Problem

Public hearings concerning development of new sand and gravel
operations often indicate that there is a widespread public belief that
sand and gravel extraction discourages urban development. The research
project discussed in this paper examined the validity of this belief.
It attempted to answer the question: Does the presence of a sand and
gravel pit influence patterns of urban development?

In general, locational analysis research has examined and
identified factors which influence the siting of a particular type of
development. For example, the location of an industrial plant may be
controlled by the availability of labor and raw materials, the type and
cost of transportation, and the distance to market. In contrast, this
research problem examined whether a specific type of development (i.e. ,
sand and gravel extraction) influenced the location of another type of
development (i.e., urban development). The general conclusions reached
in this study may be applicable to other study areas and to other forms

of urban mining.

Background
In 1982, the value of sand and gravel production in the United

States totaled 2.3 billion dollars (1982 dollars), accounting for 10.71

of total nonpfuel mineral production. Only stone, iron-ore,.and copper
production ranked higher (111.95, 13.93, and 13.11 respectively) (US
Bureau of Mines, 1982). In Michigan, sand and gravel accounted for 72.N
million dollars, or 7.A$ of non-fuel mineral production, ranking as its
fifth most important non-fuel mineral (M-DNR, 1983). Michigan's sand
and gravel production came from between 300 and 350 extraction
operations, most of which were owner-operated and located in the
southern portion of the state, close to the major population centers
(Walden, 1983). This illustrates an important characteristic of the
sand and gravel industry. Due to the material's bulky nature,
transportation accounts for much of the final cost: "In 1978, the value
of sand and gravel at the pit averaged about $2.50 per ton. At haulage
rates of 12 or 13 cents per ton mile, the price is doubled to a customer
20 miles from the pit site" (Worth, 1980).

Sand and gravel is usually the primary sources of aggregate used by
the construction and paving industry. It is used in Portland cement
concrete or asphaltic concrete, as general fill in utility trenches and
storm drains, for bringing houses and building pads up to grade, as a
base course under highways, railroads, runways, and road surfaces, and
as maintenance material for existing structures and roads. The dominant
market is the urban center. Thus, the economic viability of a sand and
gravel deposit depends not only on geologic conditions (nature, grade,
and extent of the deposit), but also on distance to the market.

‘The necessary proximity of sand and gravel operations to the urban
environment creates a conflict: although the community has need for
low-cost sand and gravel, most neighborhoods do not welcome the presence

of a sand and gravel pit. As a result, zoning for mineral extraction is

often difficult, if not impossible, to obtain. Even when necessary
zoning does exist, the extractor is usually operating contrary to the
wishes of his neighbors. The extraction industry is usually seen as a
negative impact on the community, where 'rapacious producers [are]
avariciously violating mother earth and leaving a scarred landscape"
(Malm, 1982). Neighbors must put up with an ever growing, gaping hole
from which noisy equipment rips out dusty material, dumping it into
noisy trucks which then rumble back and forth along community streets,
endangering children, pets, and general peace of mind.

While it is true that in the past sand and gravel operations were
deserving of much criticism, the situation has improved. Modern mining
methods can mitigate, if not eliminate, most of the negative impacts of
extraction. Operations can be visually screened from.neighhors through
the use of earth harms and landscaping techniques. Dust and noise
levels can be reduced significantly by following appropriate extraction
procedures and using quiet, well-maintained equipment. Problems caused
by increased truck traffic can be controlled through the use of speed
limits, specified hours of operation, and even re-routing. Progressive
or phase rehabilitation can produce an appropriate landform by the end
of the operation's lifetime suitable for agricultural use, housing
developments, industrial or office complexes, or even creation of a
*wildlife preserve. Often, the rehabilitated site undergoes such
development even while extraction is continuing in another portion of
the property. The end result of all of this is an unobtrusive
operation, scarcely noticeable to the extractor's neighbors. Such
well-run operations do exist, but they generally receive little public

notice. That, indeed, is their goal. Instead, public opinion is formed

by the traditional sand and gravel pit, highly visible in the past and
regrettably still visible today.

The closeness of sand and gravel operations to urban areas means
that there is generally a ready market for properly reclaimed sites.
, These tracts of land are suitable for housing developments, office
complexes, playgrounds, and parkland and may therefore increase in value
compared to pre-mined land. But, as Hole put it, "the only landowner
who views a sand and gravel...operation in his neighborhood as a
tolerable thing is the one who is selling or leasing his land for that
purpose" (1970). Most likely, his neighbors do not share his opinion.

Many residents do not realize that the property next to such
reclaimed areas also increase in value (Jewett, 1975). Those who do
recognize these future benefits may not be willing to wait the necessary
ten to twenty years before such financial gains can be realized. Local
residents are more concerned with the present, and the fate of property
abutting on the operating sand and gravel pit. Will the presence of the
pit attract other industrial uses to the area? Will unattractive strip
development occur? Will the value of surrounding property decline?
These concerns are often the basis for local opposition to extractive

operations.

The Purpose of the Study

The research discussed in this report was exploratory in nature.
It focused on the influence of sand and gravel extractive operations on
general patterns of urban development. Within this broad context, three
research goals were identified: (1) to identify and describe general

patterns (spatial and temporal) of urban development in the vicinity of

sand and gravel operations; (2) to define the limits (spatial and
temporal) of these identified patterns, and hence delineate the sphere
of influence of extractive operations; and (3) to relate certain site
characteristics (location, size and phase of pit development) to the
results of the first two analyses.

Chapter II of this report examines the relevant literature which
provided the background information for the study. Research methods are
Ioutlined in Chapter III. Chapter IV presents and discusses the results
obtained from the study. Chapter V summarizes the results, details the

conclusions reached, and provides recommendations for future research.

CHAPTER II

LITERATURE REVIEW

Introduction

To appreciate the need for the present research, it is important to
understand the directions related research has taken. Generally,
however, there is a dearth of information examining sand and gravel
extraction as an influencing factor on urban development trends. There
is, though, a great deal of literature pertaining to the individual
topics of urban development and to extraction of sand and gravel. It
was this material which provided the background, and indeed the
catalyst, for the research discussed in this paper. The available
information falls into a number of categories:

Sand and Gravel Extraction

W
i) Geologic Constraints

ii) Extracting and Processing Techniques
iii) Accessibility of Market

iv) Nature of Economic Market

v) Government Restrictions

W
1) Identification and Mitigation
ii) Company Planning to Mitigate Impacts
iii) Community Planning to Control Impacts

Urban Development

Winn
Woman

The remainder of this chapter highlights the key points of each

catagory.

Sand and Gravel Extraction

MW
Any analysis pertaining to the sand and gravel industry must keep

in mind one key fact: the location of sand and gravel deposits are
fixed. Man's control over these deposits is therefore limited to
determining which ones are exploitable, that is, which ones are economic
to produce.

The location of a sand and gravel occurrence was controlled by
nature. Fast-moving water was needed to transport and concentrate the
sand- and gravel-size particles. Most commercial deposits in the United
States were laid down by glacial meltwater or streams during periods of
above-average flow (Gillson, 1960; Bates, 1969). Pleistocene glacial
ice scoured and transported billions of tons of rock and soil. When the
ice retreated much of this material was left behind as unsorted till.
Meltwater flowing from the ice sheets provided sorting action for the
sediment load, leaving behind vast numbers of sand and gravel deposits.
In or adjacent to mountainous areas, sand and gravel deposits are lain
down by streams during peak-flow conditions. Modern-day or past streams
characterized by steep gradients and large water volumes (i.e. during
flood conditions) act to transport and sort great amounts of sand and
gravel. Where speed or flow decrease, these materials are deposited.

In the case of sand and gravel, operators are interested in
occurrences of aggregate material which, when extraction, processing,
transportation, and other associated costs are subtracted, will yield a

profit after selling. Often only a fine line separates an economic sand

and gravel deposit from one which is un-economic. The factors which
define this fine line are:
i) geologic constraints;
ii) extracting and processing techniques;
iii) accessibility of market;
iv) nature of economic market; and
v) government restrictions.

Each of these factors are discussed below.

1) Geologic Constraints

Geologic constraints are those factors that define the physical
nature of a sand and gravel occurrence, including the nature and depth
of overburden material; the thickness andlextent of the sand and gravel
layer; and, the physical properties of the sand and gravel layer
(including particle-size distribution, particle shape, mineralogy,
durability [hardness and soundness], and cleanliness) (Gillson, 1960;
Bates, 1969; Worth, 1980).

Generally, an operator wants to have a minimal thickness of
overburden, somewhat friable (freeable or crumbly) in nature, and
therefore easy to remove. The greater the vertical thickness and the
horizontal extent of the sand and gravel layer, the greater the
possibility for profit. Geologic constrains are fixed. Man's use of
sand and gravel is controlled by the geologic conditions laid down by

nature.

11) Extracting and Processing Techniques
Two types of extraction operations are commonly utilized for sand
and gravel deposits, dry operations and wet operations. The method

chosen depends upon geologic constraints, surrounding environmental

conditions, cost, government regulations, and operator preference. In
dry operations, extraction occurs above the water table. In Michigan,
such operations generally take place in hilly terrain. An increasingly
larger hole (open pit) is created, from which material is removed by
power shovels or front-end loaders. Generally a small amount of
overburden covers a relatively large quantity of extractable material.

Wet operations occur when deposits are situated below the water
table. In Michigan, such operations are generally found in wetland
areas or in flat terrain. Extraction is carried out by dredging or
dragline techniques. In some cases, both techniques are used. Dredging
operations use a suction device to pump aggregate and water from the
bottom of the pit. A dragline scoops up material from below water
level, creating a lake.

A number of post-extraction processes may be required before the
sand and gravel are ready for market. Screening, crushing, washing, and
combining of grade sizes may be necessary. These are usually dome

on-site.

iii)Accessibility of Market

Market accessibility is related to two key factors; the
availability of a transport medium, and, the distance to market.
Generally, sand and gravel is transported by truck. Trucking costs are
variable, depending upon the length of haul, the traffic encountered,
and the size of the truck. Smaller trucks may be more economic to
operate, but more trips are necessary to move a given quantity of
material. The use of trucks also implies the presence of accessible,

heavy-duty roads.

10

Most sand and gravel is used by the construction industry, the
major market being the urban centers. Due to the bulky nature of the
material, extraction sites must be close to the market, to minimize
transportation cost. Unfortunately, this creates a major conflict:

Generally 55 km [311.1 miles] is the maximum economic
distance for hauling sand and gravel. Because of this
constraint, deposits located near urbanizing areas should be
those of the most immediate interest to both the
construction industry and planner. However, the paradox
here is that the wave of building and road construction,
which has escalated the demand for sand and gravel products,
is at the same time causing urban conflicts which make
deposits less extractable....In the Denver, Colorado,

metropolitan area for example, a recent survey estimated 8110

million metric tons of sand and gravel lay within 218 km of

downtown Denver. However, 581 of these deposits were
designated as inaccessible because they had been built upon

or were too close to newly constructed residences to permit
mining (Griggs and Gilchrist, 1983).

iv) Nature of Economic Market

The economic viability of a sand and gravel deposit changes with
variation in supply and demand. With increase in demand, or decrease in
supply, the value of sand and gravel rises. Thus, operators may be
willing to incur greater expense in extractive operations. Smaller
deposits may become feasible to mine. Lower quality deposits, requiring
beneficiation or upgrading prior to selling, may also become cost
effective. Sand and gravel further away, previously too expensive to

transport, may be able to compete in light of increasing market price.

v) Government Restrictions
Government regulations also act as factors affecting sand and
gravel production. Compliance with regulations may increase both the

cost and time required to turn a sand and gravel deposit into an

11

operating extraction site. Zoning and land-use regulations may prevent
mining activities from occurring on a particular piece of land.
Rezoning to permit mining generally results in delay and added expense.
It may also generate adverse public opinion. Regulations requiring mine
and reclamation plans prior to any development also add to the company's
incurred cost in dollars and time. An operator may be hesitant to
develop a sand and gravel operation if he has reason to believe that it

will become a controversial issue with local residents.

W
i) Identification and Mitigation

Much work has been directed towards identifying the negative
impacts of sand and gravel extraction. Impacts include, but are not
limited to,

- noise

- dust/air pollution

truck traffic

water pollution (surface and ground water)
wildlife/plantlife

aesthetics (visual quality, etc.)
attractive nuisance/site safety

economic (property values, etc.)

- postmining landform/land use

(Jewett, 1975; Coates, 1975; COSMAR, 1980; Banks et al., 1981)
Although most are common to all types of surface mining, the proximity
of sand and gravel to the urban environment results in differing
emphasis. Also, the degree of severity of each impact varies from one
site to another. Major concerns often revolve around visual impact,
increased truck traffic, economic impact, and postmining landform/land

use. These impacts are primarily blamed for attracting undesirable types

12

of development. Little work has been done in identifying positive
impacts.

The literature also examines techniques for mitigating the
identified negative impacts. Visual impact can be minimized through the
use of earth berms (both natural and man-made), landscaping, and an
eye-pleasing site layout. General maintenance or grounds-keeping can
also improve site appearance. Buildings and machinery should be kept
clean and painted regularly. Wherever possible, paint color should
blend in with the natural surroundings.

Dust levels can be reduced by paving major haul roads, watering or
chemically controlling on-site dirt roads, washing all truck bodies
before leaving site, and tarping loads of fine grained material.
Progressive rehabilitation will minimize the amount of disturbed land,
thereby aiding in dust control.

Noise levels can be reduced through equipment modifications and
reduction of gradients of on-site haul roads. Full scale operations
should be limited to “normal“ working hours. Some researchers believe
that there is a correlation between noise and visual appearance. As
noise levels increase, so does unsightliness.

The impacts of increased truck traffic can also be minimized.
Specific truck routes should be planned to avoid residential areas
wherever possible. Operating agreements and payment procedures can be
used to control truck speed and driver courtesy.

Impacts on water systems can be minimized by controlling discharge
from the site. Sediment ponds can be used to remove particle loads from

pumping water before it is recycled into ground water. Oil and chemical

13

spills should be contained to prevent contamination of water.
Monitoring for possible water'pollution can also be undertaken.

Wildlife and plantlife should also be protected. Impact
assessment, carried out prior to any site development, can be used to
assist in planning. Once operations begin, efforts should be made to
minimize wildlife and vegetation disturbance. Menitoring can be carried
out to detect any unexpected problems.

Public safety must be provided. All extractive operations should
be identified by signs. Hidden truck intersections should be clearly
marked. Fencing should be used to prevent entry onto the site.

Much work has been directed towards site reclamation. A number of
studies have been carried out which inventory sand and gravel
operations, identify successfully reclaimed sites, and outline the
procedures used to achieve success (Coates and Scott. 1979; McLelland et
al., 1979; Marshall, 1983). Also, a number of conferences have been
held on reclamation (Thames 1977; Schaller and Sutton, 1978; Bauer,
1982) providing mam examples of successful rehabilitation of sand and
gravel pits. In general, the emphasis is on progressive or phase
rehabilitation which minimizes the amount of disturbed land at any given
time. This also reduces the amount of earth moving necessary, which in
turn lowers the cost of rehabilitation. The aim of rehabilitation is to
create a final landform appropriate to the surrounding area, and
suitable for a number of possible land uses. If a final land use has
already been determined, reclamation can be planned to create the
necessary landform. Post-mining landforms and land uses include
farmland, playground, parkland, housing developments, industrial or

office complexes, and wildlife preserves.

111

The impact of sand and gravel operations on property value is
controversial. Research carried out by some realtors show that:
there has not been a significant difference reflected in the
market between the prices of homes which were located immediately
adjacent to and overlooking the mining operation and those that
are subject to similiar influences except for the fact that they
are somewhat remote from the mining operation and they are not
directly overlooking the--the activity (Treadwell, 1983).
A study carried out at Northwestern University (Radnor et. al. , 1981)
indicated that blasting from quarry operations did not have a
significant effect on property values. Any impact on housing costs was
minimal compared to all other influences that affect the desirability of
a home. Most property owners disagree with this conclusion. If,
indeed, such an impact exists, it is probable that an operation which
minimizes negative environmental and aesthetic impacts would also reduce

negative economic impact .

11) Company Planning to Mitigate Impacts

A number of studies have been directed towards guiding companies in
their planning of community-acceptable sand and gravel operations.
Writings in this category usually discuss such topics as government
regulations, community concerns, pollution control, reclamation, and
company-community relations. A number of key ideas are stressed. First,
the company should be aware of community concerns when planning an
extraction operation. As well, they should be willing to deal with
these concerns. Often, the best means of doing this is by working
"with" the community.

To work best, community involvement should be a two-way

street. The operator should explain the need for sand and
gravel, how it is used everyday by everyone, and what the

15

difficulties are in mining it. He should also be prepared
to discuss specific plans aimed at alleviating local
concerns....

Many operators feel that the less the community knows
about the mining plans the better. This approach may have
worked in the past but, in most cases, will not work
today....Enabling citizens to voice their concerns and
suggestions will generally help to avoid conflicts and
problems at a later date (Banks et al., 1981).

The industry has initiated a number of programs aimed at increasing
company understanding of the need and methods available for mine
planning, especially in regards to site beautification and reclamation.

In 1963, a research project was sponsored by the National Sand and
Gravel Association and carried out by the Department of Urban Planning
and Landscape Architecture, University of Illinois. Completed in 1970,
this five part study examined the fundamental techniques and problems
associated with progressive rehabilitation of sand and gravel extraction
sites (Bauer, 1963; Johnson, 1961:; Jensen, 1965; Baxter, 1966; Pickels,
1969). Case studies were used to demonstrate the techniques and
problems discussed.

In 1972 a research study examining on-site beautification programs
was sponsored by the Southern California Rock Products Association and
the Southern California Ready Mix Concrete Association. It studied
beautification of future operations through an examination of prototype
situations and the landscaping of existing sites (Carreiro, 1975). The
sand and gravel industry has also set up an annual competition to
advance work in mine planning and after-use design. Undergraduate and
graduate students in landscape architecture are invited to send in site

designs. Students "use existing or proposed crushed stone and sand and

gravel sites, evaluate the assets and liabilities of the operation, than

16

propose a beautification program that leads to a final reclamation
proposal" (Carter, 1982). Originally co-sponsored by the American
Society of Landscape Architects and the National Crushed Stone
Association, the competition now has a third sponsor, the National Sand

and Gravel Association.

iii) Community Planning to Control Impacts

Information in this category is usually directed towards land use
planners, usually on a local, township, county, or state level.
Emphasis is on three main points: (1) sand and gravel is often a
limited resource and needs to be protected; (2) the public has a right
to minimum nuisance during sand and gravel operations; and (3) once
extraction is complete, the affected site must be restored to an
appropriate landform (Worth, 1980).

The high cost associated with transporting sand and gravel means
that extraction sites must be close to the urban area. But, as urban
developmnt occurs, a number of problems arise. As a community expands,
it may meet or even surround what was once a remote extraction area.
Thus the problem of impacts arises. Housing units may be built over the
top of potential sand and gravel deposits, thereby preventing extraction
of a valuable resource. Local land use boards need to be aware of these
problems, so that planning can protect both limited sand and gravel
resources and the members of the community. Areas which contain
valuable sand and gravel resources can be set aside in special
extraction districts to allow for future extraction. This concept is

the basis for Ohio's Critical Mineral Resource Areas (CMRA) (Leone,

17

1982) and the Sand and Gravel Extraction Districts of Orange County,
California (Evans, 1973). In such areas, mineral extraction is the
preferred use. incompatible land uses (i.e. housing) are directed away
from these regions.

Local planning boards should also be aware of the
'state—of-the-science' in sand and gravel extraction. Planners should
fully understand the potential impacts of such operations. The granting
of an extraction permit, and extensions of such permits, should outline
a set of operational standards which the operator must follow. Such
standards should not only consider public and environmental impacts, but
also reflect what is economically feasible for the operator.

Finally, local planning boards should be aware that sand and gravel
extraction is only a temporary land use. Numerous post-mining land uses
are possible. While it is often difficult to envision, prior to mining,
what the final land use should be, it is possible to envision the final
landform. Reclamatation allows for the creation of a landform which is
compatible with the surrounding landscape and suitable for a number of
different uses. Sand and gravel extraction should be seen as an
opportunity to create a more desirable landform than that which
previously existed. Such a concept was evident in a proposed mining
operation in Elgin, Illinois (Coates, 1982; Malm, 1982). When a large,
high-quality, aggregate deposit was discovered on a site proposed as a
major recreation area, the Elgin City Council worked with a geologic
consulting firm and a landscape architecture firm to identify the
desired final landform. The final landform was to have the variation in

topography necessary for the desired recreation area. A mining plan was

18

created to bring about this desired landform. Included in the plan of

operation was non-extractive excavation and landshaping.

Urban Development
mm

A number of factors are believed to have stimulated suburbanization
in the United States (Butler, 1980). The development of ghettos in
sections of large cities is believed to have increased the movement of
more prosperous families to the suburbs. Federally funded urban renewal
programs have resulted in the conversion of much of the older
residential sections of downtown areas into office and government space,
high-rise apartments, and public housing. The improvement of
transportation facilities and the availability of low-priced utility
services in outlying areas has also increased suburbanization.

One key point should be mentioned concerning the direction of
suburbanization. In general, the character of development remains
constant as one moves away from the city center (NAHB, 1958). If
initial development northwest of the city center was mainly high-value
residential, successive outward extensions are usually.of similar
character. Therefore, this would be a poor direction in which to locate

a low-cost housing project. The reverse situation would also hold true.

W
The suitability of a site for residential development depends on a
number of factors, both natural and man-made. Natural environmental

conditions which should be examined include climate, topography,

19

geology, hydrology, soils, vegetation, and wildlife. Man-made
conditions which should be considered include the availability of public
utilities and services, view, noise, external odors, property
acquisition, and government regulations and restrictions (NAHB, 1981).

Although overall climatic conditions are generally not a planning
issue, variation in localized topoclimatic conditions may be
significant. Solar radiation, prevailing wind conditions, topography,
slope aspect, vegetation, soil moisture, and the location of large water
bodies may all influence heating and cooling costs, determine level of
human comfort, and promote public safety (Fabos and Caswell, 1977). The
physical characteristics of the site, degree of slope, depth to bedrock,
depth to water table, soil drainage, soil bearing capacity, stoniness,
erodability, and topsoil quality influence the cost of development. The
developer is affected as his costs include any expense required to
overcome undesirable natural conditions. The home-owner must bear any
expense resulting from repeated water damage, erosion, frost heave and
other consequences of poor site selection which necessitate
post-construction site improvements (Fabos and Caswell, 1977).

The availability and adequacy of public water supplies, sanitary
and storm sewers, and lines for telephone, electricity, oil, and gas
services all influence site selection. Access to schools, churches,
local shopping centers, and recreation facilities is also important.
The presence of any of the above features increase the suitability of
the site for development. Eigh'noise levels, obnoxious odors, and
unattractive surroundings all decrease site suitability. Property

availability must also be considered. Ownership and price influence

20

suitability, as do zoning restrictions and other government regulations.

Adjacent land use was once included as another man-made condition
which impacted subdivision location. The National Association of Home
Builders (NAHB, 1958) suggested that airports, industrial uses,
railroads, cemeteries, poorly developed subdivisions, and shack
development all lowered the desirability of adjacent land for
residential development. Airports were considered to be extremely
undesirable neighbors for high class residential use, especially within
two miles or under approach zones. This belief was partly based on the
May, 1952, Report of the President's Airport Commission (PAC, 1952)
which recommended zoning near airports to restrict public and
residential development. Not only would this prevent the erection of
tall structures which might hinder air traffic, but it would also
protect homeowners from the nuisance (mainly noise and vibration) and
possible hazards of overflying aircraft.

Later reports, mainly by private organizations (i.e., one by Roy
Wenzlick and Co. and one by Herman O. Walther), showed that the issue
was not clear-cut. As a result, controversy now exists as to whether or
not an airport does create a serious detrimental influence on
residential development (NAHB, 1958).

The similarity between the airport issue and the issue of this
research paper cannot be overlooked. Like the airport issue, this study
questions the influence of a specific type of development (i.e., sand
and gravel extraction) on the location of another type of development
(i.e. , urban development). It is possible that the conclusions of this

study may also be significant to the airport issue. The following

21

chapters detail the method, the results, and the conclusions reached in

this study .

CHAPTER III

METHOD

Overview

This research analyzed thirty-nine sand and gravel sites in Oakland
County, Michigan. The location was chosen because of its high
concentration of extractive operations and because it was highly
accessible to the researcher. Once the study area was defined, land use
in the vicinity of the sand and gravel extraction sites was determined
for four years, 1957, 19611, 1972, and 1980. This information was then
analyzed using the Earth Resources Data and Analysis System 800 (ERDAS
800) to identify possible patterns of development around each extraction
site. Wherever possible, the area of influence of the extractive
operation was defined. Attempts were made to relate a number of site
characteristics (location, size, and phase of pit development) with the

results obtained.

Determination of Study Area Boundaries

The delineation of study area boundaries was based on a 1:11000 mp
drawn up by the Oakland County Planning Division. Entitled W
Sim it detailed the location of all known sand and gravel pits (past
and present) in the county (OCPD, 1982). Each pit was classified as
being active, not-active, or redeveloped based on its status in 1982

Active sites were defined as those in which extractive operations were

22

23

currently taking place. Not-active sites were those where extraction
had occurred but was not occurring as of April, 1982. These areas were
vacant of other land uses. Redeveloped sites were defined as those on
which extraction had occurred but were currently being used for new and
different land uses (OCPD, 1982). In order to carry out a sequential
study over time, it was necessary to examine pits in all three
categories. To enable examination of impacts on urban development, pits
in regions of differing stages of development were included. Thus,
sites in highly developed areas, areas on the fringe of development, and
areas beyond development were required.

Thirty-nine pits were identified which fulfilled the necessary
criteria of this study. These fell into three clusters on the basis of
location. One cluster, consisting of 15 pits (5 active, 7 not-active,
and 3 redeveloped), ran roughly parallel to and along the White Lake
Township and Waterford Township boundary. A second, roughly spherical
cluster of 8 pits (11 active and 11 not-active) occurred near the
Orion-Pontiac Townships boundary. The last group formed a northeast
widening wedge running from the southwest corner to the northeast corner
of Avon Township. It consisted of 15 pits (7 active, 3 not-active, and
5 redeveloped). A distance of 1.5 km (0.9 mile) was marked‘off in all
directions from each pit symbol to delineate individual pit examination
areas. These examination areas were then joined together, creating the
research area.

For convenience, the research area was broken down into two,
distinct study areas. The White Lake Study Area enclosed the first
cluster of pits. The Avon Study Area contained the other two clusters.

The boundaries of the two study areas are shown in Figure 1. Figures 2

2n

me~“'

.
.

 

5.“. @wmm Lake Study Area
We. .Avon Study Area
Figure 1.

Location of Study Areas

25

and 3 provide more detailed information of the White Lake Study Area and
the Avon Study Area respectively. Each pit is numbered (2-110) to allow
for ease of identification. Initially, one active pit (number M1) in
Milford Township was included as a third study area. Situated in the
center of the town of Milford it was believed to represent a site within
a highly developed region. It was later dropped from the research
project because it was too recent (post-1972) to allow for adequate
examination over time.

As no information or previous work could be found to suggest the
magnitude of the region effected by a sand and gravel extraction site,
the investigator examined the area around each site up to a distance of

1.5 km from the border of extraction.

Land Use Interpretation

Once the study area was defined, changes in land usage, between
1957-1980, were determined. In Oakland County this time span is
represented by four series of airphotos: 1957, 19611, 1972, and 1980.
For each of these years, land use within the study areas was determined
and mapped at a scale of 1:21:000 (1"=2000'). The airphotos used are
listed in Appendix A. All regions within the study area were assigned
to one of the following eleven categories of land use; all of these are
discussed later.

Vacant and Agricultural
Residential
Commercial and Industrial
Lakes
Highway
Special Uses:
Golf
Oakland University
Pontiac-Oakland Airport
Pontiac Silverdome

 

 

 

 

 

 

 

0 REDEVELOPED
W4 SITE NUMBER

 

 

I KILOME IERS

Figure 2.

White Lake Study Area, Extraction Sites

 

 

 

92

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

   

. ACTIVE

 

 

 

 

A NOT ACTIVE

 

 

o REDEVELOPED If}? ;;;_E\:’fl @3753
A... SITE NUMBER

 

 

-. W_ _I_A _‘ _LH,_ ~_ 4‘ _.
1 1 J 4 WLI‘
'-"‘*-_ '““‘~._ ' " ’ ‘
i 5 I I MLDMIIERS

Figure 3. Avon Study Area, Extraction Sites

 

28

Extraction

Gravel Pit Lakes

Land use maps are generally drawn on the basis of airphotos, deeds
of ownership, tax records, platting maps, and other government
documents. Land use categories vary, but generally differentiate
vacant, agricultural, residential, commercial, manufacturing,
industrial, recreational, public, and quasi-public property. Some of
these categories may be further subdivided and some may be combined,
depending on the purpose of the resulting land use map.

Often ownership of the land is included as a basis of
classification. This may not accurately reflect actual use. For
example, public land use could include a large public park, a public
golf course, a high school, a filtration plant, an airport, and a
publicly owned housing development. On the other hand, a private school
and a private golf club might be classified as commercial and an
apartment complex as residential. For the purpose of this study it was
believed that such classification schemes would not accurately reflect
true land use and bias the results obtained. Thus, in order to obtain
an accurate picture of land use, data were collected mainly from
airphotos. Random verification was achieved through ground inspection
and land use maps obtained from the Oakland County Planning Division
(OCPD, 19611; OCPD, 1981).

The heavy reliance was placed on airphoto interpretation for a
number of reasons. First, ground inspection (done during the summer of
1983) could not accurately describe land use conditions in 1980, let
alone in 1972, 19611, or 1957. Land use maps were only available for

19611 and 1981, which, although helpful, provided more detailed

29

information for those years than that obtained from the airphotos. When
compared with data obtained for 1957 and 1972 (solely on the basis of
airphotos) consistency over time was not permitted. Also, the land use
categories used in the two maps differed from each other and from those
used in this study. This created further complications. Therefore,
little reliance was placed on the existing land use maps.

The selection of land use categories was based on a number of
criteria. First, the investigator was interested in a classification
scheme which would reflect the research problem. Hence the necessity of
separating sand and gravel extraction from other forms of development.
For similar reasons, urban and commercial development were also
isolated. Vacant land and land used for agricultural and forest
purposes were combined due to the difficulty of accurately
differentiating these from one another solely from airphotos.

A number of special uses were identified: Pontiac-Oakland Airport,
Oakland University, Pontiac Silverdome, and golf courses. These were
isolated because of the investigator's belief that they might attract
distinct development. This is not to suggest that such uses have a
negative impact on development. Rather, the investigator based this
decision on the idea that certain land uses require certain support
facilities which may be reflected in overall development patterns. For
example, the Pontiac Silverdome holds a large number of spectators.
Parking facilities are therefore needed in its vicinity. Often the
perimeter of a college campus is lined with bookstores, photocopy
services, and coffee shops and restaurants. Nearby low-cost student
housing is also found. It was felt that by separating these special

uses such trends could be recognized if, in fact, they did occur.

30

Initial attempts at land use classification indicated that it was
difficult to identify some individual representatives of certain
catagories, especially when surrounded by one major land use area. For
example, it was extremely difficult to isolate one house in the center
of a commercial district. Even when this could be done, there was no
means for determining if the property was still used for residential
purposes, or if it had been converted to an office building or store.
High-rise apartment buildings and office buildings were also difficult
to distinguish between. The presence of a corner store or gas station.
was difficult to isolate in a residential neighborhood. To eliminate
this problem, it was decided to classify land according to a more
general “character" of use. Thus, one corner store in the middle of a
large residential area was not isolated. similarly, individual
residential dwellings in a downtown business area were not identified.
Attempts were made to accurately portray the land use along major roads
and at major intersections.

As was mentioned earlier, eleven land use categories were used.
m included vacant land and land used for agricultural and forest
purposes. Large parks (both recreational and wilderness/wildlife) were
also included. Railroads and roads other than major highways were also
included.

The investigator was concerned with broad classifications of
development, hence only two general types of urban development were
identified. Residential included all land used for residential-type
development. Uses such as single-family houses, multi-family houses,
apartments, neighborhood parks, and schools were included. As mentioned

earlier, individual neighborhood businesses and corner stores also have

31

been included. Inclusion of all of these land uses allows for
preservation of a residential, or neighborhood, character. W
included all business, commercial, manufacturing, and industrial uses.
Once again, the occasional residential dwelling may be included.

Lake included all mappable, permanent bodies of water. These
regions were not available for development, although they may have
attracted development to them. Rivers and streams were not included.
W included only major road systems, specifically Michigan Highways
75, 59, and 2h. Grass medians between lanes and exit ramps were
included. As discussed earlier, four special land uses were identified,
£9.11, courses, the Pontiac-Oakland Am, Oakland mm, and the
Pontiac mm.

m included all land areas under current disturbance due to
sand and gravel extraction. Each pit or group of pits was identified
with a number to ease later analysis. Actual land use was determined
for only four years: 1957. 19611, 1972, and 1980. The periods between
these years were not examined. Therefore, any extractive activity
occurring during these periods would not be noted. As a result, if the
activity for a particular pit was confined to any of these time periods
(i.e., 1965-1971), it would not be represented in the study. Also,
should a pit cease operations during one interval (i.e., 1967), the
actual year of cessation would not be pinpointed. Unless reactivated,
the pit would not be represented in any of the study years which
followed (i.e., 1972 and 1980 for a pit which ceased operations in
1967).

W included all bodies of water accompanying

extraction. These were within, or next to, a site of disturbance. Like

32

Lake, these areas were not available for development, although they may
have attracted development. Only the larger bodies of water were
included. Should a gravel pit lake remain after all other signs of
disturbance were gone, it was thereafter classified as Lake.

The result of this phase of the project was eight land use
maps, four of the Avon Study Area (1957, 19611, 1972, and 1980) and four

of the White Lake Study Area (1957. 19611, 1972, and 1980).

Analysis

The microcomputer-based Earth Resources Data and Analysis System
800 (ERDAS 800) was used to analyze the land use data. This system
allows for input and manipulation of goo-referenced information, in
this case land use data.

Digitizing was used to assign numerical values to the mapped data.
An x-y cartesian coordinate system was superimposed on all maps of the
two study areas. The information contained in the four maps for each
study area could then be described using the same x-y coordinates with
the use of the digitizer. Reference points were chosen and defined in
terms of x or y locations and a test point used to verify the accuracy
of the set up. The reference points set up the right angle geometry for
the digitizer and defines the’ coordinate system. This acts to
"calibrate" the map for digitizing. The test point is located where the
reference points cross, and it checks (1) the accuracy of superimposing
the reference points and test point on the map, and (2) the accuracy of
digitizing both the reference points and the test point. A maximum
error of 12 meters for the Avon Study Area and 10 meters for the White

Lake Study Area was allowed, accounting for human inaccuracy in

33

superimposing the coordinate system on each land use map. Such an error
corresponds to 00.063 of each study area. All efforts were made to
remain within 00.031 error, or 6 meters.

Each land use map was placed on a digitizing board where
information was recorded using a hand-held cursor device. Each specific
land use category was assigned a distinct numerical value. For each
mapped land use area, or polygon, the corresponding numerical value was
entered, and its boundaries outlined by a series of points using the
curser. Every time the cursor was keyed the corresponding x-y
coordinates at that map location were entered into the computer. A
special number on the cursor keypad was used to inform the computer to
close the polygon when the starting point was almost reached. The
region within the digitized boundary was therefore assigned to the
specified land use value, and contained a finite number of x-y
locations.

A special progrml was then used to convert the digitized (x,y) data
into gridded data with the same coordinate system. The grid system
allows all geographical information to be represented by cells of a
defined area or resolution. Therefore, the map can be represented by an
array of x columns by y rows in the computer's memory in the form of a
gridded or Geographic Information System (GIS) file.

In this study, each GIS grid cell corresponded to a 211 by 211 meter
mapped area (0.1423373? acres). Avon Study Area data were entered into
a grid of 780 rows by 780 columns, and White Lake Study Area data into a
grid of 652 rows by 1195 columns. Polygon data were converted in the
order of digitization. If two or more land use categories over-laid one

grid cell, the last to be entered was recorded as the grid cell value.

311

The grid cell size (211 m x 211 m) was chosen to minimize the error
associated with such overlapping occurrences. It was also chosen so as
to be able to record the smallest map areas which needed to be recorded,
i.e. , the presence of an individual building. Each of the eight land
use maps were digitized and converted to separate land use GIS files.
Each GIS file was then checked and edited on a color display monitor to
ensure that all mapped data were accurately recorded. Each land use
category was assigned a specific color to ease verification. All errors
were edited interactively on the color monitor.

From the edited land use GIS files the investigator obtained
values corresponding to the proportion of each land use found in the
vicinity of each gravel pit. Successively greater distances from each
pit were analyzed. In order to obtain this type of data, the SEARCH
program (one of the analysis phases of GIS) was utilized. SEARCH is a
proximity analysis routine that searches out from a specified class
(attributed value, in this case a specific sand and gravel pit),
creating a series of successive bands. These bands were created cell by
cell, starting at the outer boundary of the class specified to search
from, and growing outward. The search ended when a specified number of
cells, in an outward direction, had been examined. New GIS files were
created for each search (called search GIS files), while the original
land use GIS files remain unchanged.

For example, in a search of 6 cells from class of value 111, the
first band would search out all cells one cell out from all values of 111
(i.e., next to a cell of value 111). The second band would contain those
cells two cells away from all cells of value 1'1. The third band would

search cells three cells away from cells of value 1'1. Successive bands

35

would form in a similar manner. The final band, band 6, would contain
all cells 6 cells away from cells of value 1N.

When more than one area, or polygon, of a specified class occurred,
initial bands developed around each polygon. When the search areas
overlapped, the bands were combined. In this study, this situation
occurred when an extractive site had more than one, discrete, active
sand and gravel pit. Figure '1 illustrates a search of 6 cells from two
polygons of value 1'1. For this study it was believed that 1.5 km was a
realistic maximum for the sphere of influence of a gravel pit. The size
of the area which SEARCH examines depends on the number of cells
specified. As mentioned earlier, cells for this study represented 24 m
x 211 m. Thus, the search distance had to be a whole number multiple of
211. The actual search size was therefore 1512 m (63 cells). This
distance was then broken down into nine smaller divisions. The
investigator expected that any influence of the gravel pit on land use
would decrease with increasing distance from the pit. Therefore, the
divisions closest to the pit had the smallest incremental change.
Divisions were obtained by grouping together search bands. The
resulting distance divisions, or "rings” were then called Ring I through
Ring 11. These were as follows: Ring I: 0-72 m (Bands 1-3); Ring II:
72-11111 m (Bands A-6); Ring III: 1411-216 m (Bands 7-9); Ring IV:
216-360 m (Bands 10-15); Ring 5: 360-5011 m (Bands 16-21); Ring VI:
5011-7114 m (Band 22-31); Ring VII: 71111-1008 m (Bands 32-111); Ring VIII:
1008-12u8 m (Band A2-52); and Ring 1!: 12h8-1512 m (Bands 53-63).

The area around every extractive site was searched separately. For
subsequent analysis, some of the gravel pits were grouped together as

one extractive site. The pits within each group were close together,

111111

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

37

and were expected to have a joint influence on urban development.
Within groups, the individual operations were often difficult to
distinguish and sometimes appeared sequential in nature. The following
pits were grouped together: W2 and W3; WA, W5, W6, and W7; W8 and W9;
AV17 and AV19 (AV18 was never active during the years examined); AV23
and AV211; and AV35, AV36, and AV37. For each mapped year, searches were
run on all extractive sites present.

The results of the searches were then crosstabulated with the land
use data. The crosstabulation program compared the search GIS files
with the land use GIS files (CRIES, 19831). Therefore, for each mapped
year, the land use GIS file was crosstabulated with the search GIS files
for every extractive site within that study area. The computer
calculated the land use distribution within each searched distance ring.
A separate printout was then obtained for each mapped year of every
extractive site. Results were given as the number of cells of each land
use category within each distance ring. Percentages for each land use

within each ring were also calculated.

Sources of Bias

The results of the analysis, and thus the conclusions of the study,
may be biased in at least five possible ways. These were categorized
according to their source: the data base, interpretations,
cartographic, ERDAS, and numerical. Each of these is discussed below.
Where ever possible, attempts were made to minimize the known biases.

The data base for the study was airphotos taken between 1957 and
1980. Thus any distortions in the airphotos were included as part of

the data. Airphotos result from projecting converging rays through a

38

camera lens. As a result, any variation in ground surface elevation
would be recOrded with a scale variation and a displaced image position
(Lillesand and Kiefer, 1979). Areas of higher elevation were closer to
the camera and therefore appeared larger than similar areas at a lower
elevation. Also, the tops of objects were displaced relative to their
base. Displacement extremes occurred at the edges of photographs. In
order to minimize such distortions overlapping airphotos were used. By
carefully selecting airphotos, areas of interest were examined when
centered on the image.

The possibility of interpretational bias must be considered. Land
use was determined from airphotos. Any misinterpretation of the
airphotos would directly effect results. Due to the nature of the study
ground verification was difficult. This was the main reason for
defining land use categories based on the "character" of development.
In this way the importance of small, difficult to identify, islands of
development were minimized. This concept, in itself, would bias all
values obtained for land use proportions. Ground inspection was used to
verify that area character, as determined from airphotos, did agree with
ground truth.

As discussed earlier, only four study years were examined. Any pit
which operated solely in the periods between these years would not be
noted in this study. This might bias the results obtained.

In order to prevent memory bias in interpretation, airphoto
examination did not parallel time. The airphotos for 1980 were examined
first, followed by 19611, 1957. and then 1972. For each time period the

White Lake Study Area was examined prior to the Avon Study Area. This

39

was done to prevent back-checking by the investigator, either directly,
from airphotos, or indirectly, through memory recall.

Consistency of interpretation was important and a number of steps
were taken to ensure this. First, all airphotos were of a scale
sufficient for interpretation. Although actual airphoto scales varied
between years, they were close to 1:24000 (1":2000'). Guidelines were
set down to aid interpretation. For example, land use boundaries were
not necessarily based on property borders. Land uses along roads were
bordered by the road. Elsewhere, buildings generally defined land use
boundaries. Large vacant areas behind buildings and parking lots were
considered vacant, as were large areas between buildings. Within
residential subdivisions backyards were classified as residential. In
areas of strip or road development backyards were considered residential
only if easily defined (i.e., by tree borders or fences) and only if
small.

The information obtained from airphoto examination had to be
transcribed onto 1:2000 maps. A number of cartographic biases could
have resulted from this. Any distortions on the airphotos would be
preserved on the land use maps, i.e., scale variation or displaced image
position. As mentioned earlier, efforts were made to minimize
observance of such distortions. The land use areas drawn on the maps
were 'eyeballed' into place. Because airphoto and map scales were
similar it was hoped that placement bias due to 'eyeballing' would be
minimized. Bias due to line width and drawing were difficult to avoid.
Township base maps drawn by the Oakland County Planning Division were

used to aid cartography.

110

Information could also be biased within the ERDAS phase of the
analysis. Within the digitizing component two main sources of bias were
possible. When the x-y coordinate system was superimposed on each land
use map efforts were made to ensure accuracy. But, slight dislocation
could arise. By allowing a maximum error of 00.06%, the amount of the
dislocation was minimized. Digitizing was the sole means of entering
land use data into the computer. A curser was used to trace land use
boundaries, allowing x-y coordinates to be calculated. Although the
digitizer itself is accurate to 0.001 inches, unavoidable imprecision in
tracing land use boundaries was incorporated as part of the data by the
computer. Each boundary was recorded by a finite number of x-y points.
Thus, depending on the complexity of the boundary and the number of
points used to describe it, a degree of estimation was also incorporated
into the data. To minimize the error associated with such estimation,
care was taken to use a sufficient number of points to adequately
describe each boundary. Any other digitizing errors were corrected
through editing of the GIS files.

All of the digitized data were then converted into gridded (GIS)
files. The grid cells were arranged in vertical and horizontal
directions, at right angles to each other. Land use boundaries at any
other angle were therefore approximated. Each cell (representing 211 m
by 211 m) was assigned a single land use value by the computer. When two
or more land uses overlapped one grid cell, the last value entered, not
the value actually dominating the cell, was preserved. Errors resulted
if the last value did not represent the "physically" dominant land use;
however, the grid cell size was chosen so as to minimize occurrence of

such a bias. As a result, small polygons, such as individual buildings,

311

are therefore over-represented, while the larger areas next to them,
i.e. , vacant areas, are under-represented, because the small areas were
digitized last.

The SEARCH program could also generate certain biases. Each search
went out 1512 meters from the outer boundary of the gravel pit.
Therefore, land use data had to be provided for 1512 meters, in any
direction, from the outer boundary of each gravel pit. In other words,
no gravel pit should have been within 1512 meters of any border of the
land use mapped area. This was not always achieved. The eastern edge
of the Avon Study Area corresponded to the eastern edge of Oakland
County. Land use determination did not go beyond this border.
Therefore, searches around gravel pits near this border were not
complete. Thus, the data produced may not have accurately represented
conditions over 1512 m for a full 360 degrees around each pit. As a
result, actual land use proportions would vary to some degree depending
on the land use distribution of the “missing" seglnent or segments. A
similar problem occurred elsewhere. For each pit or pit group, the
actual area of current disturbance shifted over the time span examined.
The boundaries of the study areas were determined using a 1982 map of
extraction sites. If, at any earlier time, a pit was closer to the
study area boundary, the possibility existed that the full 1512 meter
examination area would not be preserved. Therefore, searches around
these pits might also be incomplete, and thus not represent true
conditions. Whenever an incomplete search occurred, the distance rings
concerned were noted.

All numerical data manipulation was based on numbers arising from

crosstabulation of the search GIS files and the land use GIS files. In

112

converting grid cell numbers to percentages, rounding was done. The
crosstabulation program rounded to two decimal places. Further
manipulation of these numbers would result in error propagation. To
prevent this, and also because of the limited resolution of graphing,

further calculations were only carried to once decimal place.

SI-ary
The method used in this study consisted of three phases: (1)

determination of study area boundaries; (2) land use interpretation; and
(3) analysis using the microcomputer-based Earth Resources Data and
Analysis System 800 (ERDAS 800). The results of these three phases are

presented in the following chapter.

CHAPTER IV

RESULTS AND INTERPRETATION

Introduction

The results of the crosstabulation of land use GIS files
(containing the eight land use maps) with search GIS files (containing
the nine distance rings) detailed the land use distribution around all
extractive sites. Graphs were used to facilitate interpretation of this
numerical data. Interpretive analysis, directed at the research goals

identified in Chapter I, was then undertaken.

Results

Of the thirty-nine extractive pits located in the two study areas,
nine were never active during any of the four mapped years. Seventeen
of the pits were active for only a portion of the study period. Only 13
pits were active throughout the study period. Table 1 lists the years
when each extractive pit was active. As discussed in Chapter III,
certain pits were grouped together for analysis. Pit groupings were as
follows: W2 and W3; W11, W5, W6, and W7; W8 and W9; AV17 and AV19 (AV18
was never active during the study period); AV23 and AV2N; and AV35,
AV36, and AV37. Pit groupings are also indicated in Table 1.

As discussed in the previous chapter, complete searches could not
always be achieved. This occurred when an extractive site was within

1512 meters of the border of the mapped area. The distance rings for

”A

Table 1. Extractive Sites -- Active Years

 

 

195? 196A 1972 1980
W1 R e m o v e d f r o m s t u d y
Grouped {W2 x x x x
as W2 W3 x x
WN x x x x
Grouped W5 x x x x
as W” W6 x x x
W7 x
Grouped W8 x x x x
as W8 W9 x x x x
W10 x x x x
W11
W12 x x x
W13 x
W1N
W15 x x x
W16 x x x x
Grouped AV17 x
as AV18
AV 17 AV19 x x
AV20 x x x
AV21
AV22
Grouped {AV23 x x x x
as AV23 AV2N x x x x
AV25
AV26 x x x x
AV27 x x
AV28 x
AV29 x x x
AV3O
AV31 x x x x
AV32
AV33
AV3N x x x x
Grouped AV35 x x x
as AV36 x x
AV35 AV37 x x x x
AV38 x
AV39 x x x x

AVNO x

115

which the search was incomplete depended on the actual distance between
the site and the border. Table 2 identifies which sand and gravel sites
had incomplete searches. The table also details the year and the rings
concerned.

Eight land use maps were generated in this study. The maps for the
White Lake Study Area are seen in Figures 5, 6, 7, and 8 (1957. 19611,
1972, and 1980 respectively). Figures 9, 10, 11, and 12 show the Avon
Study Area (1957, 19611, 1972, and 1980 respectively). These maps are
found in the pocket on the inside of the back cover. The land use
distribution in the White Lake Study Area and the Avon Study Area for
all study years are summarized in Figures 13 and 111 respectively.

The results of the crosstabulation of SEARCH GIS files with land
use GIS files were tabulated. The table for AV26, 1980, is reproduced
in Table 3 as an example. These tables detailed the land use
distribution around each pit or group of pits. They indicated
variations in land use for the nine distance rings surrounding each
extractive site. Separate tables were prepared for each year. For
those pits which ceased operations during the study period the tables
for post-extractive yearsalso identified the land uses which replaced

extraction.

Interpretation

Prior to any interpretation of the study results, one key point
needs to be clarified. As mentioned in previous chapters, thirty-nine
extractive locations were examined for the period 1957 through 1980.
These 39 operations were grouped into 21 pit in,” to facilitate

analysis. Four specific years were examined: 1957. 19611, 1972, and

Table 2.

Incomplete Searches

N6

 

Pit

Year

to
72

II
72
to
1AA

Distance Rings (meters)

III
1AA
to

216

IV
216
to
360

V
360
to
SON

VI
50A
to
7AA

VII

7AA

to
1008

VIII
1008
to
12N8

IX
12N8
to
1512

 

W2

wu
W13

AV17

AV20

AV28
AV34

AV35

AV39

19611
1972
1980
1980
19611
1972
1980
1972
1980
19611
1972
1980
1972
1980
1972
1980
1957
19611
1972
1980
1957
19621
1972
1980

NNNNNRNX

xxxxxxxx

NXNflNKXN

NNNXNXNN

xxxxxxxxxxxxxxxxxxxxxxxx

 

LR

 

 

VACANT
RESIDENTIAL
COMMERIAL
LAKE

   

GOLF
AIRPORT

 

GRAVEL PIT LAKE
EXTRACTION

 

Figure 5. White Lake Study Area—~Land Use, 1957

 

 

Figure 6.

 

8R

        
 

VACANT

RESIDENTIAL
, COMMERCIAL
WVLAKE

GOLF
AIRPORT

 

GRAVEL PIT LAKE
EXTRACTION

 

White Lake Study Area--Land Use, 1964

 

 

   

 

’11.
I IV////;'
,/

”/CI/

   

VACANT
RESIDENTIAL
% COMMERCIAL

,
35;; LAKE

\\«

GOLF
AIRPORT

GRAVEL PIT LAKE
EXTRACTION

 

Figure 7. White Lake Study Area-—Land Use, 1972

 

6T7

 

 

   
  

   

 

 

 

 

 

 

 

 

 

 

 

 

 

RESIDENTIAL
COMMERCIAL
LAKE

GOLF

AIRPORT

GRAVEL PIT LAKE
EXTRACTION

 

or M ”1 2 7 3MILES

 

Figure 8. White Lake Study Area——Land Use, 1980

 

OS

 

U1

-4

\‘GRAVEL PIT
\\\{‘:: LAKE

EXTRACTION

 

     

Figure 9.

Avon Study Area—-Land Use, 1957

 

 

 

Figure 10.

 

HIGHWAY

Avon Study Area-~Land Use,

EECOMMERCIAL

 
 

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1‘

r-mhnfimmnnl

,/,/’/
/

‘1
\\

 

196“

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Figure 11.

 

  
   
  

 

 
      

 
    

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UNIVERSITY

S ‘SlLVERDOME
§E“‘T3GRAVEL PIT 1m» _ ., __
“‘ LAKE 0

1 2 3 MILES

   
 

   

HIGHWAY

EXTRACTION

Avon Study Area—-Land Use, 1972

 

 

 

 

 

 

 

 

 

 

UNIVERSITY

SILVERDOME
GRAVE L PIT ... E
LAKE 1 0

I EXTRACTION

Figure 12. Avon Study Area--Land Use, 1980

 
 
 
 

3MILES

 

 

     

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

  

 

 

 
 
 
 
 
 
 

 

 

 

 

 

 

 

 

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56

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57

mm: mum P110026, 1980
WHIDC

Croast abulatiom-AV26 , 1980

Table 3 .

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W11 “2 u 6 000 000 M3 000 000 00.0 000 03 000
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HIGH?

mummm m7.

58

1980. Twenty-one sites over 14 years generates a maximum of 811
site-years. Due to the fact that some of the sites (6 sites or 8
site-years) did not develop until midway through the study period, only
76 site-years actually existed. Seven sites (or 12 site-years) ceased
operations during the study period and, therefore, only 61! "active"

site-years occurred.

W
The results of the study were used to identify general patterns of

development found in the vicinity of extractive sites. It is important
to clarify what these patterns represent. Patterns were based on the
change in land use proportions around each extractive site over
distance, and over time. The analysis did not examine the cause of the
observed development.

The patterns of urban development observed can be divided into two
categories; spatial and temporal. Three spatial patterns may occur.
The first type is characterized by an increase in development with
increased distance away from the pit. The second type exhibits a
decrease in development with increased distance. The final type shows
no distinguishable change in development with increased distance.

The majority of the sand and gravel pits examined in this study are
characterized by an increase in development with increased distance from
the site. The term "distal" has been used in this report to describe
this pattern. The general characteristics of the distal pattern are
more residential and commercial lands and less vacant land with
increased distance from the extraction site. The amount of residential

land tends to maximize (to peak) within the nine distance rings

59

examined. To some extent, this also holds true for commercial
development. Peaks for commercial and residential development do not
necessarily coincide. The amount of commercial development is generally
much less than residential development. Also, commercial development is
not always present in rings closest to the pit. This makes it more
Idifficult to distinguish patterns in commercial development. Of the 76
site-years examined, 65 (85.51) have distal patterns. These are
indicated in Table h. Figure 15 illustrates a distal pattern, based on
residential development in the vicinity of wu.

Some of the extractive sites examined exhibited a decrease in
development with increased distance. The term "proximal” has been used
to describe this pattern. The general characteristics of this pattern
are less residential and commercial land and more vacant land as the
distance from the sand and gravel pit increases. Residential land use
is greatest next to the extraction site. This may or may not hold true
for commercial development. Of the 76 site-years studied, 8 (10.5!)
fall into the proximal pattern. Table n indicates which sites have this
development pattern. Figure 16 provides an example of a proximal
pattern, based on residential development in the vicinity of H12.

A few of the extractive sites studied do not appear to have any
discernible change in development with increased distance from the site.
The term "continual" has been used to describe this pattern. The
continual pattern generally occurs in the earlier study years, when the
amount of residential and commercial development was small. Of the 76
site-years studied, three (3.9” exhibit these characteristics. These

pits are identified in Table h.

60

 

 

Table u. Spatial Development Patterns

Pit 1957 196A 1972 1980
H2 C C D D

vu D D D D

H8 D D D D

"10 P P D D

H12 D P P (P)
H13 --- D (P) (D)
H15 --- D D D

H16 D D D D

AV17 --- --- D D

AV20 --- D D P

AV23 D C D D

AV26 D D D D

AV27 D D (D) (P)
AV28 --- --- D (D)
AV29 D D D (D)
AV31 D D D D

AV3h D D D D

AV35 D D D D

AV38 D (D) (D) (D)
AV39 D D D D

Avho --- D (D) (D)

 

P - Proximal Pattern

D - Distal Pattern

C - Continual Pattern

() - indicates site no
longer active
-- - indicates year prior
to pit development

61

 

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Example of a Distal Pattern-4m

Figure 15.

 

mm
6.
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5 6 H w W
9 9 9 9 o
1. 1.. 4| 1I _
ZEE§M .
w
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= _ _ 347/1712! fig 1

Example of a Proximal Pattern—~W12

m w m. w w m m o
a

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pa
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dil
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63

Patterns may also be identified on the basis of development trends
over time. Three patterns can be distinguished, resulting from temporal
changes in land use distribution in the vicinity of sand and gravel pits
groups. The first pattern is characterized by an increase in
development over time. It is described as an "increasing" pattern. The
second type of pattern is the "decreasing" pattern. It exhibits a
decrease in development over time. The last pattern is the "variable"
pattern. Here development changes alternate between increasing and
decreasing patterns.

Table 5 shows the development patterns over time for the 21 study
sites. Development increased in 18 (85.71) of the sites. Note that
very few (3, or 111.31) variable patterns occur. Note also that no
decreasing patterns are found.

In all probability, the phenomenon of decreasing development over
time should be relatively uncommon. Very few areas become less
developed over time. When such a pattern does occur it is generally the
result of inner-city abandonment, or the 'bust' of 'boom' activities.
The occurrence of this pattern in this research project (as part of
variable patterns) may therefore be misleading. It is probably a
reflection of the method of analysis used, rather than any true, on
ground, occurrence. The actual location of extractive operations on a
particular site tends to migrate over time. Hence, the extractive sites
for different years do not necessarily coincide. Therefore, the search
areas for a particular sand and gravel pit, for different years, may
differ. Any changes in land use proportions may partially reflect this
shift in search areas. Decreases in development could thus be recorded

if the extractive site, and therefore the search area, had moved

6”

Table 5. Temporal Development Patterns

 

 

 

Type Of
Pit Pattern Development Comment
H2 81 R
wu sI R,C
H8 I R
H1O V drops between 1972-80
H12 31 R,C
H13 I R,C
H15 31 R
H16 sI R,C
AV17 sI R,C
AV20 V R drops between 196u-72
AV23 I R,C
AV26 sI R,C
AV27 sI R,C
AV28 I R,C
AV29 sI R,C
AV31 vsI R
AV3h I R,C
AV35 V R increases 1957-6h, variable 1964-80
AV38 51 R
AV39 31 R
AVhO I R,C
I - Increasing Pattern s - strongly (modifier)
D - Decreasing Pattern vs - very strongly (modifier)
V - Variable Pattern
R - Residential
C - Commercial

65

slightly away from urbanization. As a result, misleading decreasing
and/or variable development patterns over time appear to arise.

Certain sites exhibit increased development over time within full
view of the extractive operation. The pit H2 provides an excellent
example of this. The site showed a strong increase in residential
development, especially to the east of the site. The site itself is
visually screened on all sides except the eastern boundary. Therefore,
houses which developed to the east of the site did so despite the visual
presence of the extractive operation.

Rate of development may be a more accurate measure of change in
land use proportion over time than temporal development patterns. Rate
of development was determined from the change in land use proportion in
the vicinity of each site over time. Three periods of development were
examined: 1957-19611, 19611-1972, and 1972-1980. Hithin each time period
the change in land use proportion, especially residential land use, was
examined for each of the nine distance rings. The general trend of the
nine rings was then compared to the average rate of development for the
study area. Pour patterns emerged. Ring development rates may be
greater than (>), equal to (s), or less than (0 that of the study area
average. Occasionally different rings within a given time period show
variable (V) patterns when compared to the area average. In variable
patterns, the inner rings often show one pattern (i.e., less than the
area average) while the outer rings exhibit the opposite pattern (i.e. ,
greater than the average).

Figure 17 illustrates the different development rate patterns. The
period 1957-19611 is characterized by rates of development less than (0

the study area average. The period 19611-1972 shows development rates

66

 

53:12.1
.=> mscil .......

.5 PE I I I x..

 

 

 

 

azulumoaeoaoaron no mean

 

 

. up 9:8,:

8:
.83
.38

.0
.52...

67

greater than (>) the area average. The last period, 1972-1980, has
variable (V) development rates. The variability evident in the last
time period results from the inner rings (I-III) having rates less than
the study area average and the outer rings (IV-IX) having rates greater
than the area average.

Table 6 shows the rates of development for the extraction sites
examined. Hhere variable patterns were identified, attempts were made
to indicate any patterns relating to inner or outer rings. Many pits
showed variable patterns. Often inner rings had development rates less
than average while outer rings had rates greater than average. Of the
twenty-one extractive sites, only eleven were active during all three
periods of development. Of these, only two had consistent rates of
development for all three periods. AV31 had development rates greater
than the study area average for all three periods. H1O had development
rates less than the study area average. The other nine active sites had
development rates which varied for different time periods.

Based on 21 extractive sites, and three periods of development, a
maximum of 63 site intervals were generated. Six of the operations
began operations sometime after 1957 and, therefore, only 55 site
intervals actually existed. Of these 55 site intervals, 13 (23.65) had
rates of development greater than the study area average. Pour (7.3!)
had rates equal to the average. (Thus, 17 site intervals (30.9” had
rates greater than or equal to the study area average.) Fifteen site
intervals (27.3!) had rates of development less than the study area
average. The remaining 23 (111.81) had variable patterns. (Of these 23,
eight (311.81) resulted from inner rings less than average and outer

rings greater than average, three (13.01) from reverse conditions, and

68

Table 6. Rate of Development

 

 

Pit 1957-196A 1961-1972 1972-1980
H2 < > >
wu < > v 1-3<
u-9>
H8 = v 1-6) v
7-9<
w10 < < <
H12 > < (>)
w13 NA (>) (v)
H15 NA = >
H16 v 1-3< v v 1-2<
u-9> 3-9>
AV17 NA NA v
AV20 NA v v
AV23 < = <
AV26 v v v 1-u<
5-9<
AV27 < (V) (V)
AV28 NA NA (<)
AV29 < v 1-3< (>)
u-9<
AV31 > > >
AV39 < = <
AV35 v v 1-5> <
6-9<
AV38 (y 1-36) (y 1-7) (>)
n-9> 8-9<
AV39 v 1-5< v v 1-2<
6-9> 3-9)
Avuo NA (>) (<)

 

) Greater than study area average
= Equal to study area average

< Less than study area average

V Variable

() indicates pattern when site no longer active
NA indicates period prior to pit development

69

twelve (52.31) showed no distinguishable pattern based on inner and

outer rings.)

.Snness_2£_1nflnenee
The limits of the development patterns occurring in the vicinity of

extractive sites were defined in hopes of delineating the sphere of
influence of extractive Operations on urban development. Residential
development was used as the indicator of the sphere of influence. Both
spatial and temporal patterns of development were addressed.

As mentioned in the previous section spatial patterns of
development are characterized by distinct changes in land use
distribution with increased distance from the site of extraction. Both
distal and proximal patterns exist. For both patterns the sphere of
influence can be defined.

The limit of the sphere of influence was indicated by a change in
direction of the development pattern. The mid-point of the ring
preceding the change defined the boundary of the sphere. For distal
patterns this was where residential development peaked (local maximum).
For proximal patterns it was the valley (local minimum) prior to which
development started increasing. Overall trends in development were
used. Investigator Judgment was used to smooth out erratics on the
graphs.

Spheres of influence were determined for each study year. Table 7
lists these for each site. This same information is graphically
presented in Figure 18. Symbols are used to differentiate between
spheres of influence resulting from proximal and distal patterns. The

majority of the sites examined had distal spheres of influence. This

70

 

 

Table 7. Sphere of Influence
1957 196" 1972 1980

H2 8767C h32?C 288 D 288 D
H8 1128 D 1128 D 1128 D 1128 D
H8 876 D 876 D 876 D 876 D
H10 180 P n32 P 108 D 108 D
w12 108 D A32 P 288 P (1128 P)
H13 --- 62h D (180 P (288 D)
H15 --- 138 D 1380 D 1380 D
H16 876 D 876 D 876 D 876 D
AV17 --- --- 832 D 876 D
AV20 --- 288 D 180 D 628 P
AV23 628 D 832?C 288 D 180 D
AV26 288 D 288 D 108 D 628 D
AV27 628 D 932 D (628 D (288 P)
AV28 --- --- 108 D (108 D)
AV29 1380 D 1128 D 1128 D 1128 D
AV31 832 D 932 D 876 D 180 D
AV38 1380 D 1380 D 1380 D 1380 D
AV35 876 D 1128 D 108 D 180 D
AV38 1128 D (1128 D) (629 D) (108 D)
AV39 628 D 624 D 624 D 1380 D
AVRO --- 180 D (180 D) (288 D)

 

P - Proximal Pattern
D - Distal Pattern
C - Continual Pattern

7 - questionable due to lack
of development
() - indicates site no longer
active
--- - indicates year prior to
pit development

71

ooeesaueH uo enema» .wp oasuum

Ozw
VVV V NVVVMN
mmmmmmammmuummmmmmwmm

 

   

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72

was expected, as most sites exhibited distal patterns. Note that when
both types of spheres were identified for a particular active site the
maximum sphere of influence resulting from a distal pattern was
relatively small (H10=108 m; H12=108 m; AV20=288 m). A number of
patterns emerge for those pits which ceased operations during the study
year. For most sites, the sphere of influence during active years
resulted from distal development patterns (H13, AV27, AV28, AV29, AV38,
and AVllo). For four of these sites, distal spheres of influence
remained after operations ceased (AV28, AV29, AV38, and AVAO). But, the
size of the sphere decreased with time. At one site (AV27) the sphere
after operations initially ceased was due to distal patterns, but
eventually switched to one resulting from a proximal pattern. Only H13
differed greatly.

During its active year, H13 had a distal sphere of influence. The
first study year after operations ceased showed a proximal sphere. The
following study year showed a distal sphere. This may be a result of
the location of H13 and its proximity to Pontiac Lake. In the years up
to and including 1972, a great deal of residential development occurred
north of H13, along the shoreline of Pontiac Lake. The proximal sphere
for H13 in 1972 reflected this. Between 1972 and 1980 there was little
room for increased residential development around Pontiac Lake. At the
same time both residential and commercial development were occurring
further away, to the south of H13. The end result of this was a distal
sphere in 1980. Thus, the change from proximal to distal sphere related
to development elsewhere, not to pit activity.

A similar pattern was observed for H10, situated on the apposite

side (north of) Pontiac Lake. Although H1O was active throughout the

73

study period, it too changed from a proximal sphere to a distal sphere.
In the case of H10 this was the result of a shift in the location of
lakeshore development. The pit is situated on the north side of Gale
Road. To the south, the north shore of Pontiac lake curves away from
the road, allowing residential development to occur between the lake and
Gale Road. This was where earliest development occurred. To the east
of this area, the lake abutts on the road. Development is therefore
restricted to the area north of Gale Road. This area was less desirable
for residential development and hence developed later. This was
reflected in the change from proximal to distal sphere of influence.
Average values for spheres of influence were calculated. For
distal patterns the mean value was 686 m, based on 68 active and
non-active site-years. The mean value for active site-years only (of
which there were 59) was 715 m. The Student's t Distribution Test,
using a 95% confidence level, showed no statistically significant
difference between the two values. For proximal patterns a mean value
of 111111 m was calculated based on eight site-years (both active and
non-active). Using just active site-years (n=5) the mean value was 391
m. There was no statistically significant difference between the two

values.

We

Attempts were made to relate certain site characteristics to the
development patterns and spheres of influence identified. Three
characteristics were examined: location, size, and phase of pit
development. Sites were grouped as being urban or rural (location);

large or small (size); and increasing or decreasing in size (phase of

7n

pit development). For each group the average (mean) sphere of influence
was calculated. The average sphere of influence for the groups
describing each characteristic were then compared.

Site locations were classified as urban or rural, depending on the
relative amounts of development in their surrounding area. Total
acreage of current disturbance was used to define site size for an
individual or group of pits. Small sites were those where total area
was less than 50 acres. Large sites were those where total area was
greater than 50 acres. Size for one site could vary for different
years. Phase of pit development related to changes in pit size for the
periods 1957-196A, 196n-1972, and 1972-1980. Increasing sites exhibited
an increase of more than 151 within the particular time period.
Decreasing sites showed a decrease of more than 151. Those sites which
changed by less than 15% in either direction were considered constant.

Of the 21 sites examined, 11 (52.4!) were urban and 10 (h7.6$)
rural. Ten sites (117.61) were small throughout their operating period,
3 (111.31) were large, and 8 (38.11) varied between small and large. The
eight pits represented 30 individual pit-years. (Of these, 16 (53.3”
were small and 1h (46.7!) were large.) forty-three phases of active pit
development were identified. Twenty-eight (65.1%) were increasing
phases, 12 (27.111) were decreasing phases, and 3 (7.0!) were constant.
Table 8 details the characteristics for each site.

Using the information in Table 8 the sites were categorized
according to characteristics. Only those sites with distal spheres of
influence were included. Proximal spheres of influence were not
included because they result from a different type of development

pattern. These two development patterns are distinct groups. Due to

 

75

Table 8: Pit Characteristics

 

W2 W4 W8 W10 W12 W

_i

3 W15 W16 AV17 AV20 AV23 AV26 AV27 AV28 AV29 AV31 AV34 AV35 AV38 AV39 AVUO

 

 

 

 

Location R R R R U R U U R R R U U U U U R R U U U
Size
1957 S L S S S —— -- S -- —— L S —- S S S S S L --
1964 L L S S S S S S —— S L S S —— S L S L -— S ——
1972 L L S S S —- S S L L L S -— S L S S L ~— S S
1980 L L L S —- —- S S L L L S -- —- —— S L L -— L —-
Phase of
Pit Development
1957-1964 I D D I I -— -— I -- —- I I D -- I I I I -- D --
1964-1972 I D D I I -- I D -- I I I -— -- I D I I -— I ——
1972-1980 C I I C —- -- I I D C I D -— —— —- D I D —- I --
Location Size Phase of Pit Development
R - Rural S - Small I - Increase
U - Urban L — Large D — Decreasing -~ - indicates pit not active

C — Constant

 

76

the low number of proximal spheres of influence, separate statistical
analysis was not possible for sites having proximal development
patterns. The following sites were therefore excluded from all
statistical analysis: H10 (1957 and 19611); H12 (19611, 1972, and 1980);
H13 (1972); AV20 (1980); and AV27 (1980). The sites included in each
group are listed in Table 9. Note that for size and for phase of pit
development, groups were sub-divided by year. Figures 19, 20, and 21
are graphical representations of the sphere of influence for each site
grouped according to location, size, and phase of pit development
respectively.

One useful method of analysis is to determine the central tendency
and variability of a group of data. For the site groups shown in Table
9 the measurements of sphere of influence were used to calculate group
mode, median, mean, and standard deviation (Table 10). These values
were then used to examine the distribution and variability of spheres of
influence within each group of similar sites.

The calculated values generally indicated a wide range of spheres
of influence within each group. The values showed no tendency to
cluster about a central value. Many of the groups were multi-modal
(i.e., more than one value for sphere of influence occurred with equally
high frequency). Hhere groups were uni-modal (i.e., only one value
Occurred with highest frequency), the actual frequency of the value was
relatively low. This was probably due to the small group sizes. No
consistent patterns were noted when group mode, median, and mean were

Compared.

 

77

Table 9. Groups Based on Site Characteristics *

   

 

W2 wu W8 W10 W12 W13 W15 W16 AV17 AV20 AV23 AV26 AV27 AV28 AV29 AV31 AVBH AV35 AV38 AV39 AVUO NUMBER

 

Location
Rural X X X X X X X X X X
Urban X X X X X X X X X X X
Size
Small
1957 X X
196M X
1972 X
1980
Large
1957
196M X
1972 X
1980 X
Phase

><><><><1
><><
><
><><
><><><><
><
><><><><
><
><
><
><

>4><><><
><
><
><><><><
><
><

Increasing

1957-196A X

196u-1972 X X X X X X X X X X X

1972-1980 X X X X X X X
Decreasing

1957-1964

196u-1972 X X X X

1972-1980 X X X X
Constant

1972-1980 X X X

><
><
><
X
N
><
><
><
N

N
N
><
><

 

* All sites with positive spheres are excluded.

78

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79

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Sphere of Influence-Size Groups

Figure 20.

38533.69 3.. no canmiiooegagn uo season .3 one»:

08.... 58960 8!... 058280 3!... 9.33.»...

 

80

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Table 10. Site Group Statistics
Standard
n Mode Median Mean Deviation
Location
Rural-all 32 876 628 678.0 838.0
-active 31 876 750 690.6 839.3
Urban-all 36 628 628 681.3 837.5
-active 28 tri-modal 628 726.8 837.7
Size
Small
1957 11 876 876 808.0 813.6
1968 11 multi-modal 628 738.2 830.2
1972 9 bi-modal 876 708.0 509.3
1980 5 multi-modal 628 633.6 523.9
Large
1957 3 628 628 792.0 291.0
1968 5 832 832 710.8 381.2
1972 7 bi-modal 288 507.8 835.7
1980 8 tri-modal 876 786.0 510.1
Phase
Increasing
1957-1868 8 832 658 762.0 816.5
1968-1972 10 108 288 559.2 535.1
1972-1980 7 1380 1128 1028.6 837.2
Decreasing
1957-1968 8 multi-modal 750 765.0 302.7
1968-1972 8 876 876 939.0 126.0
1972-1980 8 180 803 865.0 388.8
Constant
1957-1968 0 ND ND ND ND.
1975-1972 0 ND ND ND ND
1972-1980 3 multi-modal 288 380.0 261.9

 

ND - No Data

82

The different groups for each characteristic were then compared.
The Student's t Distribution Test was used to compare mean values for
sphere of influence. The hypotheses tested were:

1'10: U1 = 112

i.e., that there is no statistically significant difference
in means.

81‘ “I a! “2

i.e. , that there is a statistically significant difference
in means.
The rejection region used was:
For a probability of<1=0.05 of a type 1 error (i.e., rejecting the
null hypothesis when it is true) and degrees of freedom
df=n1+n2-2, reject no if tc>ta/2.
In other words, no was accepted unless the calculated value for t (to)
'88 SPOEtOP than the value Of t0/2 obtained from the table of percentage
points of the t-distribution using 01:0.05 (95.01 confidence level) and
GOSPGGB or freedom df=h1+n2-2. Eleven comparisons were done. The
results are shown in Table 11.

Only one comparison resulted in rejecting Ho' The category
involved was phase of pit development and the comparison was between
spheres of influence for sites during increasing phases and constant
phases for the period 1972-1980. The group containing sites with
constant phases was the smallest group examined, with only three sites
included. The standard deviation calculated was approximately 771 of
the mean value determined. For this reason, the results of the

comparison are questionable.

83

 

 

Table 11. Statistical Comparison of Pit Groups
Comparison 'df tc ta/z e Results
Location
Rural vs Urban
All Pits 66 .005 1.960 accept H
Active Only 57 .310 1.960 accept Ho
Size
Small vs Large
1957 12 .087 2.179 accept no
1968 18 .106 2.185 accept Ho
1972 18 .818 2.185 accept no
1980 11 .519 2.201 accept Ho
Phase of Pit Development
Increasing vs Decreasing
1957-1968 10 .013 2.228 accept no
1968-1972 12 1.373 2.179 accept no
1972-1980 9 2.200 2.262 accept Ho
Increasing vs Constant
1972-1980 8 2.891 2.306 reject Ho
Decreasing vs Constant
1972-1980 5 .521 2.571 accept Ho

 

'From Ott, Lyman. 1977.

W-

Duxbury Press, North Scituate, Mass. 6599.

Based on a = 0.05

W
Table 2; Percentage points of the t distribution.

88

Grouping of sites on the basis of identifiable characteristics
(location, size, and phase of pit development) did not result in
statistically significant differences in mean value for sphere of
influence. Therefore, sites of similar character do not have similar

impacts on development .

CHAPTER V

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

Su-ary
Thirty-nine sand and gravel extraction pits in Oakland County,

Michigan, were examined in this study. These were grouped into
twenty-one sites for analysis purposes as discussed in Chapter IV. Land
use changes in the vicinity of these sites were determined for the
period 1957 to 1980. The microcomputer based Earth Resources Data and
Analysis System 800 (ERDAS 800) was used to analyze this information.
The results obtained were then interpreted focusing on three points of
interest: (1) patterns of development identified in the vicinity of
extraction sites; (2) sphere of influence of extractive operations on
surrounding development; and (3) relationship between certain pit
characteristics and identified development patterns and spheres of
influence.

Two aspects of development patterns were examined: those resulting
from changes in land use proportions with increased distance from the
extraction site (spatial patterns); and those resulting from changes in
land use proportion over time (temporal patterns).

For spatial patterns of development, three patterns were
identified: (1) proximal patterns, characterized by decreased urban
development with increased distance from the site; (2) distal patterns,

exhibiting increased development with increased distance from the site;

85

86

and (3) continual patterns, showing no discernable change in development
levels with increased distance from the site. The majority of the sites
examined (85.51) had distal patterns.

Temporal patterns were divided into three patterns. The first,
increasing patterns, showed increased amounts of development over time.
Decreasing patterns were characterized by decreased amounts of
development over time. The third pattern, variable, fluctuated between
increasing and decreasing patterns. The majority of the sites (85.71)
had increasing patterns. It is probable that decreasing, and therefore
variable, patterns arose as a result of the method of analysis used, and
are not true patterns.

A more accurate reflection of change in land use proportion over
time (temporal development patterns) was that of rate of development.
For each time period (1957-1968, 1968-1972, 1972-1980) the development
rate for each site was compared to that for the study area average. The
nine distance rings around each site were examined. Each time period
for each site was rated as having a development rate greater than (>) ,
equal to (z), or less than (<) that of the study area. Those sites
which exhibited variable (V) development rates among distance rings were
also noted.

0f the twenty-one sites examined, most did not have consistent
development patterns for all three time periods. Only 27.31 of the site
intervals examined had development rates less than the study area
average. Almost one-third of the sites (30.91) had rates greater than
or equal to the area average, while 81.81 exhibited variable patterns.

Spheres of influence were delineated by identifying the limits of

the development patterns. Residential development was used as the

87

indicator. Two classes of spheres were identified: those based on
spatial patterns of development, and those based on temporal patterns.
Spatial spheres of influence were classified as being proximal or
distal, based on the pattern of development. For each site the limit of
the sphere of influence for each study year was determined. The mean
value for the sphere of influence for proximal spheres was 888 meters,
based on eight site-years. The mean value for distal spheres was 686
meters, based on 68 site-years.

Attempts to relate certain extractive site characteristics
(location, size, and phase of pit development) with the development
patterns and spheres of influence identified were unsuccessful.
Grouping of sites on the basis of these characteristics did not result
in statistically significant differences in mean values for sphere of
influence. Hithin each group, values for sphere of influence showed no

noticeable tendency to cluster around a single value.

Conclusions

The results of this study have definite significance to the sand
and gravel extractive industry and the communities in which it operates.
The validity of the widespread public belief that the presence of a sand
and gravel pit discourages urban development was not supported by this
research. The investigator therefore concluded that this belief is
questionable, if not false.

The general pattern of development observed in the vicinity of
extractive sites was one of increased development with distance from the
site. This pattern existed for an average distance of 686 meters (0.83

miles). Beyond this point development trends tended to be similiar to

88

those of the surrounding area. This does not automatically mean that
the presence of an extractive operation retards urban development.

The majority of the sites examined were located at the outer
fringes of urban development. Initially, most of these extractive
operations were situated some distance from the urban area. But, the
outward spread of urbanization resulted in a transformation of the land
use in the vicinity of extractive sites. Hith time, the area
surrounding most pits shifted from vacant and agricultural land to
residential and commercial land use. The shift in land use over time
was probably reflected in the distal pattern of development. For many
sites, the increased amount of development with distance from the site
(distal pattern) probably resulted from urban growth, rather than any
influence of the extractive operation.

Some of the sites examined in this study exhibited a decreased
amount of development with distance from the site (proximal patterns).
To conclude from this research that these sites actually attracted urban
development would be misleading. Development in these areas was
probably influenced to a greater extent by other factors.

The idea that extractive operations have a neutral impact on
development must therefore be considered. This is certainly supported
by development trends in the vicinity of extractive sites over time. It
is important to note that in most cases development in the vicinity of
the extractive sites increased with time. In certain cases (i.e. , H2)
this occurred within full view of the extractive operation. This would
seem to indicate that the presence of the extractive operation did not
detract from future residential development. As well, less than

one-third of the site intervals examined exhibited development rates

89

less than the average rate for the study area. Such development trends
support the idea that sand and gravel extractive sites exert no
influence, or a neutral influence, on surrounding development.

From this, it can be concluded that the presence of an extractive
operation is not necessarily a dominant factor influencing urban
development. The development patterns observed in the vicinity of
extractive operations result from a number of factors, i.e., natural
physical conditions of the site (soil, hydrology, etc.) and man-made
conditions (availability of public utilities and services, property
acquisition, etc.). Although sand and gravel pits may exert some
influence on patterns of urban development, the amount of influence
varies from site to site. Attempts to relate certain site
characteristics to the observed patterns of development and spheres of
influence were unsuccessful. Sites of similiar location, size, or phase
of pit development did not have similiar impacts on development.

The major conclusion of this study is that, on a generalized basis,
the presence of sand and gravel extraction does not discourage
development. The generalizations held by much of the public pertaining
to the negative influence of sand and gravel operations on urban
development were not substantiated by the present research. As well,
this study found that the presence of an extractive operation is not
necessarily a dominant factor controlling surrounding land use. As a
result, the possibility of extractive sites having a neutral influence
on urban development must be considered.

The conclusions of this study suggests that no generalization can
be drawn about the potential influence of a planned extractive operation

on urban development surrounding it. Each site should be examined

9O

separately. For any proposed extractive operation, the local conditions
must be fully examined prior to determination of potential influence on
urban development. Generalizations based on existing sites in other
localities may not be correct. This concept of site individuality
should be understood by planners of potential extractive operations, and

by the communities in which the proposed site is situated.

Recc-emdatioms for Future Research

Prior to any discussion of potential research, one key fact needs
to be mentioned. This research project concluded that extractive sites
exert variable influences on urban development depending on the site.
As a result, members of the sand and gravel industry have no reason to
fear the results of future research. In fact, future research may
indicate that some of the negative impacts of sand and gravel operations
are over-estimated. This does not mean that further research is not
needed. On the contrary, additional research is necessary to provide
solid data and to improve public opinion concerning the sand and gravel
industry. Ccmunity organizations should also be willing to carry out
research. This is necessary if they are to increase their ability to
provide relevant information regarding planning of extractive
operations.

Future research should examine a number of questions. Hhat
quantitative influences do sand and gravel operations exert on
development patterns? Extraction sites are just one of the many factors
which might influence the siting of development. The relative weights
of each of these factors, including sand and gravel extraction, should

be determined. Also, any shift in significance of factors with changes

91

in distance or time should be examined. Hhat factors overshadow the
presence of a sand and gravel operation? For example, would the
presence of a picturesque lake exert more influence on development than
a nearby extractive operation? Hhat about zoning or property ownership?
How does the character of the post-mined land affect development? If an
extractive operation produces a lake as one of its by-products, does
residential development occur in anticipation of the lake's presence?
An on-site examination of fewer pits might provide insight as to more
specific patterns of development. For example, does development relate
to topography? How does site visibility influence development? Hhat
influence do truck routes exert?

The qualitative influences of sand and gravel operations on urban
development might also be examined. Hhat types of development are found
near extraction sites? Does residential, commercial, industrial, or
some other type of development dominate? Hhat is the quality of that
development? For example, is residential development in the area
dominated by large, high-value homes, by moderate-value homes, or by
trailer parks?

A second area of possible examination involves operational
procedures. How much control does an operator have over development
patterns? Are patterns influenced by certain individual phases of the
extractive operation, or by the entire process? Do surrounding
development patterns vary between wet operations and dry operations?

Finally, what are the economic impacts of sand and gravel pits? A
detailed examination of this is long overdue. Are property values in
the surrounding area effected? Hhat about increased revenue into the

community resulting from direct company spending and indirect spending

92

by company employees. Are new jobs created, and if so, how many? These
types of questions are best examined on a small scale, perhaps looking
at one or two individual sites. A historical approach might be
necessary to detail changes in property values before, during, and after
extractive operations.

These are just a few examples of potential areas for examination.
There is no limit to the amount or scope of future research. Much work

still needs to be done, and should be done.

APPENDIX

APPENDIX

LIST OF AIRPHOTOS

W

1957

1968

1972

1980

XR-1P-178
XR-2P-63 to 73
XR-ZP-116 to 119
XR-ZP-189 to 158

XR-ZEE—115 to 123
XR-ZEE-151 to 159
XR-ZEE-187 to 189
XR-ZEE-223

XR-1MH-69 to 71
XR-IMM-83 to 87
XR-1MM—128

Semcog 80-230-16-8 to 11
Semcog 80-230-17-9 to 15
Semcog 80-230-18-10 to 12
Semcog 80-230-19-11 to 13

W

1957

1968

XR-1P-17 to 25
XR-1P-87 to 99
XR-1P-187 to 195
XR-ZP-IS to 23
XR-ZP-61 to 65
XR-ZP-191 to 199
XR-ZP-ZIS

XR-3EE-18
XR-BEE-81 to 89
XR-3EE—63 to 71
XR-3EE-97 to 99
XR-BEE—IZS to 127
XR-BEE-ISB
XR-BEE-177 to 183
XR-3EE-195 to 201
XR-BEE-ZOS to 211

93

1972

1980

98

XR-1MH-181 to 185
XR-1MM-188 to 190
XR-1MM-205 to 209

Semcog 80-230-21-9 to 11
Semcog 80-230-22-9 to 15
Semcog 80-230-23-9 to 15
Semcog 80-230-28-9 to 15
Semcog 80-230-25-9 to 15

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0.0‘ ' h ‘ a" 0.149 ' ato'vmes'zz'W‘uJLLJJo-
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mm Pontiac, MI.
.......... 1981. W Pontiac, MI.
..........1982. W. Pontiac, MI.

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