THESIS ’
m ‘
MICHlGAN STATE unmasm
mum: ALLEN mm

1972

 

 

WHWLHIMIHWHUWWW

3 123 300802 3925

This is to certify that the
thesis entitled

A Computer Method
for Interpretation of Natural Resource Data

for Four Types of Land Uses
presented by

Kenneth Allen Wenner

has been accepted towards fulfillment
of the requirements for

Doctor of BhilQSQDhLdegree in Wevelopment

4/ 22% fl///( //

Major proféo

DateflgufiLll- 1972

0-7639

 

 

 

 

 

 

 

 

 

 

ABSTRACT

A COMPUTER METHOD FOR INTERPRETATION OF
NATURAL RESOURCE DATA FOR FOUR TYPES OF LAND-USES

BY

Kenneth Allen Wenner

To help establish a public policy and a decision making
framework for land use changes there is a need for broad
kinda of land resource inventories and a method of analyzing
the data to determine the relative suitability of different
land areas for.various types of land uses. Inventories and
anIIYeee-of this magnitude and scope require the collection,
storage, and retrieval of Vast amounts of data. Using
~eurrent methods of interpreting data from tables and map
overlays to determine.the physical suitability of an area
for.different land uses are very difficult and time con-
suming. For these reasons there is a need for an automatic
data processing system that will facilitate analysis of our
land resourcesgthet;is expedient, efficient, and spatially
oriented.

The major objectives of this study were to develop a
rapid, efficient method of analyzing large volumes of
natural resource data relating to site suitability for four
different land uses and to develop an index rating system
capable of comparing a given site for several alternative

land uses.

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In the formulation of the implicit model, the basic
assumption was that the physical site suitability for a spec-
ified land use is a function of the natural resource features
relating to or possessed by the site or geographic location
under consideration. The land uses considered in this study
were: 1) sanitary landfills-trench type; 2) residential
homes on sanitary sewers-no basements; 3) residential homes
on septic filter fields-no basements; and 4) continuous
corn. The range of values for each of the natural resource
features considered in this study was divided into classes
and each class was assigned a class number. A point system
of 0 through 2 was then used to measure the degree of in-
fluence each of these classes had on a particular land use.
The feature class well suited to the particular land use was
irated as 0 points and the feature class presenting very
serious problems to the use was rated as 9 points. Points 1
through 8 were used to designate the varying degrees of suit-
ability. The numerical class designators were transformed
into indicator or dummy variables of the -l, 0, +1 type.
Natural features relevant to the land use being evaluated
were designated as independent variables and the total
points represented by the various classes were designated as
the dependent variables. A regression coefficient for each
independent variable for each land use and a constant were
then obtained by regression analysis using a set of theo-
retical observations as sample data. The test data for the

study consisted of 2 sections of land in Grand Traverse

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Kenneth Allen Wenner

County, Michigan. Each section was divided by a row -
column grid system into 2% acre parcels. The selected
natural resource data for each parcel was entered onto a
punch card. The computer program LANDUSE was written and
utilized to read the data cards for each parcel, transform
the data into respective indicator variables, calculate a
physical site suitability index for each land use, and print
these index values in table form using.the row — column
locations. These values can be utilized to compare the
relative suitability of a site for the four land uses or
they can be used to compare several sites for a given land
use. An index value of 100% would be the most desirable

site from a physical feasibility standpoint.

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‘14 J. I

A COMPUTER.METHOD FOR-INTERPRETATION OF

NATURAL RESOURCE DATA FOR FOUR TYPES OF LAND USES

BY

Kenneth Allen Wenner

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the reduirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Resource Development

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LA ACKNOWLEDGMENTS

The author wishes to express his appreciation to his
thesis advisor, Dr. D. Chappe.lle, and to the members of the
guidance committee, Dr. C. Humphrys, chairman, Dr. M.  Chubb,
and Dr. J. Harman, for their guidance and support in this
study. Appreciation is also extended to Professor H.
Galloway, Mr. G. Earle, Dr. J. Yahner, and Dr. L. :Perkinson,
for their comments and suggestions during various phases of
the research project.~ ' 1

Appreciation is extended to the Cooperative State
Research Servi ce, U. S. Department of Agriculture, as-ad-
ministrative agency of the WMcIntire-Stennis funds, and to
Johnson and Anderson, Ino., Consulting Engineers, Pontiac,
Michigan, for their financial assistance during the formu-
lation of the research proposal for this study, and to the
Department of Agronomy, Purdue University, for their as-
sistance in the completion of this study.

* Special thanks is extended to my wife, Mrs. N. Wenner,
and to Kevin and Cheryl, our two teenagers, for their

patience and understanding throughout this study period.

ii

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M ACKNOWLEDGMENTS

The author wishes to express his appreciation to his
thesis advisor, Dr. D. Chappelle, and to the members of the
guidance committee, Dr. C. Humphrys, chairman, Dr. M. Chubb,
and Dr. J. Harman, for their guidance and support in this
study. Appreciation is also extended to Professor H.
Galloway, Mr. G. Earle, Dr. J. Yahner, and Dr. L. Perkinson,
for their comments and suggestions during various phases of
the research project.

Appreciation is extended to the Cooperative State
Research Service, U. S. Department of Agriculture, as ad-
ministrative agency of the McIntire-Stennis funds, and to
Johnson and Anderson, Inc., Consulting Engineers, Pontiac,
Michigan, for their financial assistance during the formu-
lation of the research proposal for this study, and to the
Department of Agronomy, Purdue University, for their as-
sistance in the completion of this study.

Special thanks is extended to my wife, Mrs. N. Wenner,
and to Kevin and Cheryl, our two teenagers, for their

patience and understanding throughout this study period.

ii

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ii

CHAPTER

1.
2.

3.

TABLE OF CONTENTS

PROBLEM STATEMENT . . . .

PROBLEM ANALYSIS. . . . .

STUDY OBJECTIVES. . . . .

' METHODS AND PROCEDURES. .

General Introduction . . . . .
Formulation of Implicit Model.
Land Use and Natural Features.
~Formulation of EXplicit Model.

Sample Data. . . . . . .

Determination of Parameters fo

Explicit Equation. . . .
Test Data. . . . . . . .
.Data Input . . . . . . .

Data Processing and Computation.

computer Program . . . .
‘Data Output. . . . . . .

Each

5. RESULTS MD DISCUSSION. 0 O O O O O C 0

Advantages of the Index.

.Potential Use of the Index .
New Technology and Techniques.

LIST OF REFERENCES . . . . . . .

APPENDICES

DATA WORK SHEET . . . . .

SOIL CODING SHEET . . . .

COMPUTER PROGRAM "LAND USE"

DATA FOR ROW 3, COLUMN 3, AND SOILS

PSSI VALUES FOR FOUR LAND USES.

iii

. Interpretation of the Suitability Index.

Page

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Table

1.

LIST OF TABLES

Natural Resource Features, Measurement Units,
and Their Respective Class Separations and
Numeric Designations. . . . . . . . . . . . . . .

The Natural Feature, The Class, Variable
Designation, And The Class Roints For Sanitary
Larldfi 113 O O O O O O O O O O O O O O O O O O O O

The Natural Features, The Class, Variable
Designation, And The Class Points For Residential
Homes With sanitary Sewers-No Basements . . . . .

The Natural Features, The Class, Variable
Designation, And The Class Points For Residential
Homes Requiring Septic Filter Fields—No Basements

The Natural Features, The Class, Variable
Designation, And The Class Points For Continuous
Corn. 0 O O O O O O I O O I O O O O O O O O O O O

The Natural Features, Variables, Regression
Coefficients And Constant For Sanitary Landfills.

The Natural Features, Variables, Regression
Coefficients And Constant For Residential Homes
With Sanitary Sewers-No Basements . . . . . . . .

The Natural Features, Variables, Regression
Coefficients And Constant For Residential Homes
Requiring Septic Filter Fields-No Basements . . .

The Natural Features, Variables, Regression
Coefficients, And Constant For Continuous Corn. .

iv

Page

30

35

36

38

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46

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48

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Figure Page

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The Grid Coordinate System of Each Section
of Land Showing the Row-Column Locatins
of Each'Zk Acre Parcel of Land . . . . . . . . . . 52

Schematic Flow Chart of Data Input and Processing. 56'

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v

CHAPTER 1

PROBLEM STATEMENT

The desire for an automatic data processing system for
analyzing information relating to the location, availability,
development, and management of natural resources increases
as the demand for these resources becomes greater.  This
demand is related to the population, and the consumption
needs and habits of the various cultures of the world.

In 1970 the world population was estimated at 3632
million people with a projected increase to 4933 million
people by the year 1985. The Northern America (United States
and Canada) population is projected to increase from 225
million people in 1970 (Golenpaul 1972) to 280 million people
in l985.(murdoch 1971)

With population increases of this magnitude the great

IL.

question facing the world and every nation concerns the
"adequacy of natural resources to provide the kind of living
its peOple want, or in some countries merely to keep the
Population*alive." (Landsberg 32 1963) Most countries
Of the world rely on the land resource as the basic unit for
Providing the food, fiber and space needs of its people. In
théiUnitedEStates‘ "we have used this land resource rather

lavishly and there is not an overall land scarcity now, nor

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is.there likely.to be one for-some-generation, although
some adjustments in land uses will.be needed." (Murdoch
1971) These adjustments-will require-varying degrees of
public control over private lands that-ate fair to the
individual. ;To help establish a.pubiic policy and a land
usetdecision-makiag framework-there.is'a need for broad’
kinds of natural resource inventories»: (Callison 1967)
There is also a need for.a careful examination of the
natural physical characteristics of a land unit and a need
to determine the relative.importance of each characteristic
for different land uses. (Clawson:g§_gl. 1960)

Natural resource inventories.and.analysis of this magni-
tude and scope require the collection,.storage, retrieval,
and interpretation of-vast amounts of data. Therefore there
is aflgreat need to deviSe an automatic data-processing
sydtem.for analyzing our.land resources that is expedient,
efficient, and useful.

The land resource planner or user could utilize such a
data system as an aid in benefit-cost analysis and in prepa-
ration of environmental impact statements. This could be
accomplished by comparing the most desired set of natural
physical characteristics of a specified area. The most
desired set of ratural characteristics for a given land use
‘would be that set requiring the least cost of site prepa-
ration to accomplish the desired objective without gener-
ating harmful side effects within the natural environment.

For example, the desired objective may be to locate areas

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for high agricultural crop.production without.excessive soil
erosion or chemical pollution to water runoff, or to locate
areas for sanitary landfills whore leachate would not enter
the ground water or contaminate surface runoff. Other
examples would be to locate areas for residential develop-
ment where soils are capable of supporting homes without
deep or expensive foundations-and-where soils.are.capable of
absorbing septic tank effluent without ground water contami-
nation.

‘The emamples cited in the previous paragraph represent
a few of the types of objectives or land uses that could be
considered in an automatic data.processing system. All of
these same objectives can be accomplished.without the aid of
a computer system, but the large amounts of data and the
great number of alternative land uses create very tedious

and time consuming tasksi

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CHAPTER 2

PROBLEM ANALYSIS

Evaluation of the land resource generally includes use
of topographic maps prepared by the Geological Survey, U.S.
Department of Interior, geological maps published by the
Division of State Geological Survey, Soil Surveys published
by the Soil Conservation Service, U.S. Department of Agri-
culture, and information from other state and federal
agencies such as the Forest Service, U.S. Department of
Agriculture, and Bureau of Land Management, U.S. Department
of Interior.

Soil surveys consist of maps showing the location of
the various kinds of soil and a report describing each soil
and its properties. This type of survey is useful in land
use planning and management for both agricultural and non-
agricultural uses and for this reason they are currently in
great demand. But the large quantity and complexity of the
data in survey reports make them relatively difficult and
time consuming to use. The soil survey is made by a soil
scientist walking over the land examining the soil to at
least a five foot depth with the aid of a spade or soil
auger.‘ He records selected soil data (Soil Survey Manual
lQSll on an aerial photograph base and after examining
several acres he delineates areas of soils that have similar

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CHAPTER 2

PROBLEM ANALYSIS

Evaluation of the land resource generally includes use

of topographic maps prepared by the Geological Survey, U.S.
Department of Interior, geological maps published by the
Division of State Geological Survey, Soil Surveys published
by the Soil Conservation Service, U.S. Department of Agri-
culture, and information from other state and federal
agencies such as the Forest Service, U.S. Department of
Agriculture, and Bureau of Land Management, U.S. Department
of'Interior.

~:SOil surveys consist of maps showing the location of
the various kinds of soil and a report describing each soil
and its properties. This type of survey is useful in land
use planning and management for both agricultural and non-
agridultural uses and for this reason they are currently in
great-demand. But the large quantity and complexity of the
data in survey reports make them relatively difficult and
time consuming to use. The soil survey is made by a soil
scientist walking over the land examining the soil to at
least a five foot depth with the aid of a spade or soil
auger.1 He records selected soil data (Soil Survey Manual
1951l.on an aerial photograph base and after examining
several acres he delineates areas of soils that have similar

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characteristics from other areas by drawing lines on the
photograph separating one area from another. The soil in-
formation.is recorded on the aerial photograph by use of
numeric or alphabetic codes to denote the soil type, slope
and erosion. A code of this type is called a mapping unit
by soil.scientists. Each mapping unit represents a set of
natural physical characteristics and is listed in a table
with interpretations for different land uses. These inter-
pretations may be in the form of short narratives or they
may be in the form of "suitability ratings." Wenner gt 2;.
1968). The suitability ratings relate the degree of hazard
a particular soil character or slope presents to a given
land use and is generally expressed as slight, moderate, or
severe. The degree of hazard may be related to: the cost
of physically preparing the site for the desired use such
as land grading; the need of expensive internal soil drain—
age; the inability of the soil to support a specified load;
the potential of a given use to cause pollution through
surface sedimentation or contamination; or the ability of
theLsoil to perform a desired function such as serving as an
effluent discharge area where the effluent is to be filtered
through the soil. Another method of expressing the suit-
ability_rating is to examine several soil characteristics
and.give a general rating for the mapping unit. This
general.rating may be expressed.as A, B, C, D, E (Wenner
gE_gl. 1964) or they may be expressed as good, fair, poor,

or very poor. The A or good rating would indicate the soil

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is well suited to that particular land use whereas the E or
very poor rating would indicate the soil is not Suited to a
particular land use.

The user of soil survey information must determine from
the aerial photographs the mapping unit or units covering
'hiS'area of interest, then refer to the interpretation
'tables for a suitability rating for the specified land use.
He must then associate the suitability ratings or different
soil characteristics for a given land use with the location
of the mapping unit. If the user wishes to make comparisons
‘of the general suitability of a given site or area for alter-
native land uses he must make separate interpretations for
each use.' Vbry often the user constructs a table of his own
wherein he lists the mapping unit for the area of interest
'and the reSpective suitability ratings for the different
uses he wishes to consider. But the user must still attempt
to visually associate these ratings with their respective‘
locations. If the area is very large, then the user has
difficulty and generally resorts to making land use suit—
ability maps by preparing several copies of the map covering
his-area of interest and properly locating the appropriate
mapping unit delineations. He then constructs a suitability
table for the different land uses he wishes to consider,
prepares a color code for his suitability ratings, and
prepares a color map for each land use. He then examines
leach map by looking at the colors. From his color code he

identifies areas that are suitable for a particular land use

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and-notes this on a master land use suitability map.
Gertain areas of the map may be well suited for several
types of land uses while other areas may be very restricted.
(Montgomery and Edminister, 1966) The land use suitability
map is then used in conjunction with other planning factors,
such as social, economic or political, to develop a compre-
hensive.plan for the area.

Another method commonly employed in preparing land use
suitability maps is the preparation of soil characteristic
roverlaysF.‘ This consists of using the soil maps and pre—
paring a transparent overlay for several of the different
physical characteristics and rating them as to their suit:
ability for a given land use. These overlays are generally
golor coded with green representing the most suitable condi—
tion, red representing the unsuitable condition, and yellow
representing the intermediate situation. (Quay 1966)

_ Two of the difficulties in using the table method are
the problems of location and the inability to make a quanti—
tative evaluation between several alternative land uses.

The degree and extent to which a site is listed as moder—
ately.suitable or not suitable depends upon the number of
factors.considered. As an example: if a site were evalu-
ated on the basis of four or five physical properties and
any one of these pr0perties presented a severe limitation
to the specified use then the site is listed as having a

"severe limitation" or "not suited." But if another site

was evaluated for the same land use using the same type of

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physical properties and all of the properties considered
presented a severe limitation then this site would carry
the same "not suited” rating as the previous site. However,
there is obviously a degree of severity that is not being
taken into consideration. Other problems with the table
method are the mechanical difficulties of construction and
the inability of integrating a large number of physical
properties into a final rating without mentally combining
the influence of several physical properties into a com-
posite rating. 'This is.often accomplished by professional
people kgenerally quite accurately) but the user loses thel
benefit of knowing or-understanding the reasoning behind a
given rating and is often at‘a loss as to h6w he might
proceed to overcome the problem presented by the land unit.

‘ Knowing the exact areal location of the various soils
is beneficial to the user in planning the use of an area.
Very often one mapping unit present within an area may be
more expensive to develop for a given use than another
mapping unit.’ The development or management costs can often
be lowered if the user can select the type of use or locate
different uses-within the area to more nearly coincide with
the suitability ratings; ‘The final decision on land use'
generallyfmust be based on natural features, and on social,
political, and écbnémié considerations.

The difficulties in using the "overlay" system are

chiefly in the mechanical work involved and the inability

to evaluate a large number of physical properties into the

 

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suitability rating process. The user must make a set

of overlays for each property as it relates to a given
land use. As soon as several overlays (representing the
different physcial properties) are superimposed on the land
unit map the color coding creates a degree of opaqueness
and-the user has difficulty deciphering the information and
properly locating the area of interest on the map.

More sophisticated methods of combining the table
method and the overlay method have been proposed for land
use planning. Belknap and Furtado (1968) compared the
Lewis, McHarg, and Hills approaches to utilizing the natural
land unit as a planning base. They concluded from these
comparisons that there are ways to identify, evaluate and
incorporate ecological values into the normal planning and
design process. The mechanical difficulty and complexity
of utilizing natural resource information in the basic
planning has prompted the use of automatic data processing.

I The University of Illinois and The Northeast Illinois
Natural Resource Service Center proposed a Natural Resource
Information System (NARIS 1970) to provide a wide range of
natural resource data for an eight county area in northeast
lllinois. The system would contain information on soils,
geology, hydrology, forestry, climatology, water impound-
ment, topography and land use. The data would be recorded
for areas of forty acres in size. A library file would
store information on each resource concerning various inter-

pretations for a wide range of purposes.

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Swanson (1969) in the Land Use and.Natural Resource
Inventory of New York State utilized a combination.of aerial
photography, steroptical.interpretation of the-photos and
computer display-of data in preparing a comprehensive inven-
tory of land uses and natura1-resources in all 62 counties
of New-!ork State..

The State Planning Agency of Minnesota is developing a
Minnesota Land.Infornation:8ystem.. (MLIS 1970) Data for
this.system.are.collected-for-40 acre parcels and contain
basiclpareel-location,:ownership, dominant:soil.type-and
current land.tse-fer thetentire.state, plus,various land'\
acquisition methods, stataa,-and management recommendation
fericertaiantate:and-county owned lands. The first.large-
scale use of- this system will be to produce land-use maps
for eachtof-uinnesotals eleven planning regions. ‘In the
futuretmapswill hn'praduand which willpermit the evaluation
of each parcel-for best-land use and form the basis for
recommendations-regarding.disposition of state and taxa
forfeit land in the cooperating counties.

'Natural resource-features form an integral part of both
MARIE and.the MLIS'systensibut no stress is given to the
integration-ofnseveral;natural resource features or factors
into axeomposite.land;use.suitability rating system. The
MARIE system utilizes a library data file for storing soils
information-and-the-oatput from this file is in the form of
slight, moderate or severe ratings denoting the degree of

physical hazards for a given land use. The user is unable

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to retrieve the basic soil prOperty data if he wishes to
make further study of a site. [Another difficulty with both
of the systems is the size of the basic parcel. By limiting
the data collection to a 40 acre parcel there is the
assumption that the entire parcel is uniform in character
and this may represent a large spatial aggregation error.
The Iowa Land Use Analysis Laboratory (Sinatra gt Ei°
1972) is currently participating in a natural resources
study of the state of Iowa. The state has been divided
into 10 resource regions and data on topography, super-
ficial water, roads, degree of urbanization, forest cover,
primary soils, secondary soils, tertiary soils, buried
valleys, bedrock topography, shallow bedrock aquifer, pizeo-
metric surface and special land use are entered on a grid
coordinate location matrix. To map these features the
laboratory has purchased the GRID III computer program from
the Computer Graphics Laboratory of Harvard University.
Three mapping scales are being examined--64O acres, 169
acres and 40 acres, with supplementary projects investi-
gating grids of 2.5 acres and squares of 100 feet. The
researchers on this project indicate that it may be possible
‘to assign weights to each of the data variables and their
separate characteristics in order to select cells with
optimal physical conditions for certain land uses. One of
the major difficulties with the data system arises from the

type of soils data input. The soils listed as occurring

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in a major land resource area represent the three to five
soils that occur most often within the area. This type
of spatial aggregation may cause serious error if the user

is interested in smaller parcels of land within the region.

CHAPTER 3

STUDYVOBJECTIVES

'The major objectives of this study were to: 1) de—
velop a rapid, efficient method of analyzing large volumes
of natural reSource data relating to site suitability for
different land uses; 2) spatially orient large volumes of
natural resource data for automatic processing; 3) deve10p
a site suitability index rating system capable of inte-
grating different types of natural resource data into one
index value for a specified land use; and 4) develop an
index rating system capable of rapidly comparing a given
site for several alternative land uses.

In selecting a method of analyzing large volumes of
data the objective was not merely to synthesize the data
into information for the sole purpose of demonstrating
storage and retrieval methods, but rather to analyze rele-
vant data and produce useful and meaningful interpretations.
Therefore serious consideration was first given to the types
of interpretations that were to be considered or that could
be considered. Then several methods of analysis were con-
sidered that might possibly meet the requirements of the
system. 'Another consideration was the selection of a method
that would be flexible enough to identify sets of properties
with one identifier label. This permits the identifier to

13

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he.in primary storage.and.the set.of.corresponding ideas
tifier propertiessto be located.in a supplementary storage
system.; Thissrequirea-the.introduction of a detailed set
of prepertiasionly once but.the identifier may be present

in the primary-aystem numerous times. This_somewhat-raduces
thebaize-ofspriMary storage.neaded.

In.attempting.to spatially orient data, careful con-
sideratien was-given toethe size or areal extent of the unit
te.ba.identified...The.type of use to be made of the output
determinealto-a greatsextent tha.size of the unit to be con-
sidered.«,In the casezof.general or broad land use suit-
ability ratings, the units can be,larger than those that are
to bezutilized forrmone detailedninvestigation. Therefore,
the decision was_made to utilize a small basic unit with-the
capability of Aggregating the.smaller units into whatever
larger size.waa desired.” It:wouldrbe.impoasibla to attempt
to split a large input unit for more detailed analysis.

While developing the index rating system consideration
was given to the fact that information on soils, geology,
topography, and climatology were to be integrated into a
composite value for a specified land use. This necessitated
determining the use to be made of the rating and identifying
the type of person that might utilize this rating. If the
users represented a professional homogeneous group then a
complex system could be developed along with an intensive
training program explaining the derivation and use of the

rating system. However, the potential users may represent

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a group of individuals with a broad range of educational
training and interests. Therefore the rating expression
had to be relatively simple and easily understood.

The framework for deriving the index rating system had
to be broad enough to permit different types of information
to be considered but specific enough to allow consistency
and quantification.

Attempting to compare a given site for several alter—
native land uses utilizing an overlay or colored map pro-
cedure requires a considerable amount of time and effort.
Therefore, some type of rating system was desired that
could permit the analysis of a large group of natural
physical properties.for several alternative land uses.
Again the type of audience or potential user of the index
rating had to be considered in its formulation. The rating

system not only had to be usful, but also simple, relatively

understandable and easily computed.

 

.
_..

CHAPTER 4

METHODS AND PROCEDURES

‘-

General Introduction

 

The procedures to accomplish the objectives of this
study consisted of seven basic phases. In each phase there
were generally several alternative methods that could be
employed to meet the objective and in some phases several
alternative methods were employed before a satisfactory
method was obtained. -There is no intent in this report to
analyze all of the possible alternatives, but merely to
relate the work that was performed and the results obtained.
There-were several assumptions made during the course of

the study and these will be indicated where appropriate.

I

Formulation of the Implicit Model

In the formulation of the implicit model the basic
assumptien was made that the physical site suitability (PSS)
for a specified land use is-a function of the natural
resource features relating to or possessed by the site or
geographic location under.oonsideration. Also, it was
assumed.that each land use has a unique.set of desired
natural physical characteristics and one element or feature
within a set may be more important than other elements.

Therefore, each element or feature must be evaluated

16

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separately for each land use. This assumption was further
expanded to infer that the variables within the function
are additive.

_The implication here is that an initial cost would be
associated with overcoming or correcting a single natural
feature presenting a problem for a given land use and the
cost of correcting another feature of equal hazard on the
same site would be relatively equal to the initial cost.
Butithis may not always be the true situation. For example,
if a site being evaluated for sanitary landfill was a very
permeable sand with a flooding potential, the cost of pro-
tecting the ground water from possible contamination may or
may not be equal to the cost of protecting the area from
flooding: ”Both situations would be considered as pre-
senting severe limitations to the use in question and would
be considered as equal in the physical site suitability
rating. Also, in the additive index rating system the
relative cost of overcoming one hazard is considered as
completely independent of overcoming another hazard. This
may not always be true. However, the cost of overcoming
two severe hazards is greater than the cost of overcoming
just one severe hazard. Therefore, there is a need for some
type of additive model. 'To determine the exact cost of
Overcoming each hazard under actual field conditions would
require extensive investigations of each site. This would

4.;

be very expensive.

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The alternative then is to devise a point system
based on judgment and field experience to evaluate the
relative difficulty of overcoming each feature that may
present a problem for a given land use and add these

points to get an overall quantative rating for a site.

Land Uses and Natural Features

Utilizing the above assumption the first task was to
define the land uses to be considered in the study. They
are: _l) sanitary landfill sites, trench type; 2) resi-
dential home sites with sanitary sewers and no basements;
3) residential home sites requiring septic filter fields
and no basements; and 4) continuous corn sites.1 In
selecting these land uses the intention was to illustrate
two urban classifications with slightly different physical
properties being considered, one agricultural classi-
fication, and one special land classification.

‘The next step in the formulation of the implicit
model was to determine the natural resource features that
were to be considered. There were two alternative methods
to consider at this point. One method considered was to
devise a list of all natural resource features and catalog
as much data as possible. The other approach was to care-
fully analyze the land uses to be considered and select

natural resource features considered to be the most

 

1The continuous corn land use is defined as the
growing of one crop of corn on the same site year after
year.

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19

relevant, thereby limiting data collection to these
features. The latter procedure was selected, while fully
realizing that there are-additional features to be con?
sidened. :Of course, the.researcher mmst weigh the cost
of collecting extra data against'the information to be
gained and the objectives of.the.study.

~In attempting;to,determine the resource features to
comider foreach land use, investigations'werefmade‘ as to
What features:the different land use planning agencies were
.currently.utilizingvsndwwhat.types of interpretations-were
currently available fromrnatural resource agencies. It was
found that most land use planning agencies utilize infor-
nation relating tonaturzal resources that state and federal
agencies are capable of supplying. The agencies supplying
etherbulk of-this information in the midrwestern states are:
Soil Conservation Service (SCS), U.S. Department as Agri~
culture; Geological Survey, U.S. Department of Interior;
State Agricultural Codleges; State Agricultural Experiment
Stations; and State Natural Resource Departments. These‘
'agencies-generally work very closely on the land use suit-
ability interpretations*and.often publish jointly sponsored
tablestfor different uses._ Therefore, most of the inter-
pretations relating the natural resource data to the spar
cific land.uses included in this study were obtained from
these sourceBLand.are documented as to the resource person,

pub 1i cation , or memorandum.

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Sanitary Landfills - Trench Type

The overall purposes of a trench type sanitary land
fill are to bury solid wastes in the soil without pollution
to the ground water. with a minimum of odor, with a minimum
of unsightlinesa, and at minimal cost of burying? digging,
and hauling. To meet these objectives the site should have
a total soil (topaoil..aubsoil and underlying material)
depth to allow for the excavation of a trench of at least
7 to 10 feet deep with an'additional 10 to 30 feet of soil
material under the trench. The slope of the land surface
Should not be over 25 per-cant to allow the safe operation
of large mechanical equipment. The permeability rate of-
the-subsoil and underlying material should not be greater
than two minutes per inch. This creates an underlying seal
preventing leacheate from entering the ground water. Suf-
ficient soil material should be readily available to permit
covering of the wastes with six inches of soil on a daily
basis to prevent the blowing of paper and to help control
odors and with 2 feet of material when the fill is completed.
The seasonal ground water table should be low enough that
water never enters the trench and the area should not be
subject to flooding. The relative number and size of stones
is also a factor conSidered to be important to the ease of
digging and movement of material.

The natural resource features considered to be most

important to the achievement of the objectives for trench

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type sanitary land fills are; slope, texture of the under-
lying material, natural soil drainage, permeability of under-
lying material, flooding potential, and depth to bedrock.
(Kellogg, 1971, page 30)

Information on these variables is readily available
from soil survey maps produced by the SCS. However, soils
naps are limited to interpretations of the upper five feet
of material. Therefore, the value obtained from such
information is somewhat limited but has the advantage of
readily permitting the disqualification of potentially
”unsuited! sites from further consideration. For this
reason the soil survey map is considered a vital informa-
tional tool in the initial selection of land fill sites and
a special interpretation table has been set up for this

purpose.

Residential Homes With Sanitary Sewers

Residential home site evaluations in this study are
defined as being appropriate to single family dwellings of
not more than three stories high, located on k to % acre lot
sizes and without basements. The emphasis for rating soils
is on stability or ability of the soil to support a foun-
dation, and wetness potential. Other natural features in—
fluencing the cost of development are slope, depth to bed-
rock and stoniness. Soil permeability is an additional

natural feature considered very important if the home site

requires a septic tank effluent filter field. In order to

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22

illustrate the importance of this one additional natural
feature, the ratings in this study were-determined for those
homes requiring an on-site.septic filter field as well as
for those homes having access to a sanitary sewer.

In considering the-natural features for homes having
access to sanitary sewers, slope classes 1 and 2 were not
considered as causing a problem to development. Slopes in
class 3 would require a certain amount of cutting and
filling and were.therefore rated as having a.moderats
limitation. Slope class 4.may require considerable cutting
and filling operation but the aesthetics of the rolling
topography would somewhat off set this additional cost-
Therefore, these.slopes.were rated as having moderate to
severe limitation.. 0n slope classes 5 and 6 the cost of
cutting and filling would be considerable and were rated
as presenting severe limitations.

Surface soil texture was not considered as a dominating.
force in the evaluations. However, if the site consisted
of texture classes 1 or 2 (clayey) or texture class 5 (sandy)
for surface soil then there would be an additional difficulty
in-establishing a lawn or shrubs. Sites having these surface
soil textures were rated as presenting moderate limitation.
Soils with a subsoil texture class 1 were rated as moderate
because there would be an additional hazard to foundation
development due to the greater shrink-swell potential of the

clay, but the hazard would not be severe.

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Natural drainage class 1, or those soils having a
water table 0 to 1 foot from the surface at least part of
the year, were considered as presenting a severe limitation
to use. Soils in natural drainage class 2 would require
special water management and were considered as presenting
a moderate limitation. Moderately well drained and well
drained soils (natural drainage classes 3 and 4) do not
present any major problems for residential development.

”Soils high in organic matter are very unstable when
wet and provide a serious problem for foundations. When
these same soils are dried the organic matter will oxidize
and cause subsidence of the soil mass which presents an
additional problem to foundation or road construction.
Utilization of soil areas classified as muck or peat for
roads or permanent buildings present special problems. The
entire depth of organic material must be either removed,
bridged, or Special floating foundations must be constructed.
These corrective measures are very expensive, thus the
degree of hazard is considered very severe and an index value
was not calculated for soils classified as muck or peat.
Soils having no organic matter (class 4) would be considered
as presenting a problem to landscaping and were considered
as presenting a moderate limitation. Soils having 5 to 8
per cent (class 2) organic matter would require that the
surface soil be removed under driveways, sidewalks and

roads-end were therefore rated as presenting a moderate

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24

limdtation. Soils containing 3 to 4 per cent (class 3)
organic matter are desirable for landscaping and are.easy
to remove from construction areas so were rated as pre-
senting slight limitations.

The number and size of.stones are directly related to
the ease of excavating and grading. Stoniness classes 1
and.2 were not considered to.be a problem for small ex-
cavating equipment and were rated as presenting a slight
limitation. Stoniness class 3-would require larger equip-
ment to_remove the stones but their frequency would not -
present an impossible situation and was rated as presenting
a moderate limitation. Stoniness class 4 would require
constant removal with large equipment during excavation
and their frequency would make avoiding them nearly im-
possible. Soils with this problem were rated as presenting
a severe limitation. -

Potential flooding is a severe situation for residen-
tialdevelopment. If an area was considered to be subject
to flooding once in 25 years (class 3) this was considered
to be a severe limitation. For certain types of land uses
there is reason to include an intermediate class 2 but
these were not included in this study. If the area did not
flood then it was considered as class 1 and rated as not
presenting a limitation.

The depth to bedrock is directly related to the ease

of excavating for utility lines to maintain a desired depth,

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25

and to the ease of constructing foundations for homes.

If the bedrock was listed as being deeper than 60 inches
(class 1) then the soil was rated as having_a slight
limitation. If the bedrock was at a depth of 40 to 60
inches (class.2) then there probably would be areas where
minor blasting or drilling would be required and the soil
was rated as presenting a_moderate limitation. But if the
area had bedrock-within 40 inches (classes 3,4 and 5) of
the surface then the amount of drilling and blasting re-
quired would be increased and the soil was rated as pre-

senting a severe limitation.

Residential Homes With Septic Filter Fields

The natural features and their limitations that were
discussed for residential homes having access to sanitary
sewers.are similar to the natural features influencing the
ratings for residential homes requiring septic tank effluent
filter fields.‘ The exceptions are (l) the addition of sub-
soil permeability, and (i) changing the limitation rating
of natural drainage class 2. In the development of a
filter field the objective is to filter the effluent from
the septic tank into the soil. For the septic tank to
function properly the soils in the immediate area must be
permeable enough to transmit the volume of water used in
the household through the soil. Soils in permeability
class 3 are generally considered too impervious for septic

filter fields but with installation of extra large fields

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26

they are being utilized on a limited basis. The cost of
these large systems is high and the soils are rated as
moderate to severe hazard. Soils in permeability class 2
require relatively large systems and are rated as presenting
moderate limitations. The change in natural drainage class
2 is from a moderate limitation for residential homes with
access to sewers to moderate to severe rating for resi—
dential homes requiring a septic filter field. This change
is necessitated by the presence of excess water in the soil
during part of the year, but with subsurface drainage this
problem may be overcome. if

The SCS in cooperation with other state and federal
agencies has developed an interpretation table whereby the
factors discussed for residential development are the
basic units considered in this study. (Kellogg, 197l,
page 28) ' .

The interpretation table as prepared by the SCS [for
each of the above three land use classifications are based
on individual natural feature values and each feature is
rated as having slight, moderate or severe hazard for the
land usejin‘question.1 In these tables if any one of these
variables is rated as presenting a severe hazard to deve-
lopment for the specified land use, then the site is listed

3

as having a severe rating. But if all the properties have

 

1In this study the additional rating of moderate to
severe has been added as discussed on pages 22 and 24;

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27

a severe rating the site is still rated as being severe.
There is no allowance for degrees of severity and all the
variables are essentially rated as having equal weight in

the final rating.

.Continuous Corn

Ideally the best.sites for continuous corn are those
capable of producing the highest yields with the least
production cost and without detrimental effects to the.soil.

The natural resource features considered for con-
tinuous corn were not as clearly delineated in published
tables. However, a composite yield rating has been deve-
10ped for each soil. LThese composite ratings are based on
experimental data and field experience on representative
sdils and interpolation of this information for other soils.
The list of natural features and the point system actually
considered in these composite ratings were obtained through
a personal interview'with Harry Galloway.1 'They are:'
slope, surface soil texture, subsoil texture, topsoil
depth, organic matter, soil depth favorable to root deve-
lopment, available water, flooding, topographic position,
and freeze free period. Currently Ray Dideriksen2 is pre-

paring a yield productivity table for the major agricultural

 

1Professor in the Department of Agronomy, Purdue
university, West Lafayette, Indiana.

2State Soil Scientist, Soil Conservation Service,
U.S. Department of Agriculture, Indianapolis, Indiana.

 

 
 

 

 

 
 

 

 

 

 
 
 
 

 
 
 
 

 

 

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28

crops of Indiana. This table evaluates the potential con-
tribution of different soil properties to yield for certain
bench mark soils. Using criteria developed in this study
and as well as criteria utilized by Dideriksen, the impor-
tance-of natural soil drainage was a difficult issue to
evaluate. Therefore, the basic assumption for this study
was*that.all soils were adequately drained so that time-
liness of operation would not be deterred due to poor drain-
age. Dideriksen projected his tables to include both im-

proved natural soil drainage and unimproved drainage.

Natural Features

- All Of the natural resource features considered in this
study arei” surface soil texture, subsoil texture, texture
of the underlying material, natural soil drainage, topsoil
depth, organic matter, stoniness, soil depth generally
favorable to root growth, relative permeability of the sub-
soil, available water, slope, flooding, topographic posi-
tion, and length of freeze-free period. Soil erosion was
also included in the list of variables but was not considered
in the suitability calculations.

The next step was to determine the units of measure-
menta'of each of these natural features and the range of
these measurement values. Eight of the variables were
measured in interval and ratio scale, 5 in the nominal scale,

and the remainder of the variables were measured in ordinal

scale.“Bxisting tables (Kellogg 1968), (IN-sost-1-1970),

 

 

 

 

 

 

 

 

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(Soil Survey Manual) and personal consultations with Guy
Earlel and Harry Galloway were utilized in dividing each
natural feature into classes or categories and all the
measurements were converted to the nominal scale.2 In this
conversion process there is a loss of data which indicated
that variables previously measured in ordinal and interval
scales (actual values) now merely are within a specified
range and this range is designated by a number. Also,
Blalock (1960 - page 13) points out that using numbers
arbitrarily associated with each category does not justify
the use of the usual arithmetic operations on these numbers.
This negates the validity of including standard errors in
this study. I

Table 1 lists the naturalfeatures, the measurement
unit, the class separations, the respective numerical class
designations, and a reference for the definition of each

class.

Formulation of Explicit Model

In the formulation of the explicit model a method had
to be devised to quantitatively evaluate each variable that
was considered relevant to each land use. The first attempt
in the quantification process consisted of using the class

designators for the variables measured in ordinal and nominal

scale and actual values for variables measured in ratio scale.

k

1Assistant State Soil Scientist, Soil Conservation Service,
U.S. Department of Agriculture, East Lansing, Michigan.

2The reasons for this conversion are explained on page 33.

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30

TABLE.l

Natural Resource Features+-Measurement Units, Their
Respective Class Separation, and Numerical Designation.

Measure- *fi" Elass
Natural . ment Desig-
Features Unit Class Separation nation

 

Soil Erosion1 slight 1.
moderate 2
severe 3

Surface Soil2 fine

Texture moderately fine

medium.
moderately coarse
coarse

UlahWNH

Subsoil Texture2 fine
moderately fine
medium
moderately coarse.
coarse

WBUNH

Underlying Material2 fine
Texture moderately fine
medium
moderately coarse
coarse
Natural Soill poorly
Drainage somewhat poorly
moderately well
well
somewhat well to
excessively well

wal-J WIFUNH

Topsoil Depth2 inches greater than 16

11-16
7-10
3-6
0-2

Organic Matter2 per cent greater than 9
568
3-4
0-2

thNi-i U'ltwaH U!

Stoninessl class 0
class 1
class 2
classes 3,4,5

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31

TABLE 1 (Cont'd)

 

Natural.
Features-

’ Soil Depthz

Permeability2

Available Water2

Slope

Flooding

Topography3

Depth to Bedrock2

Freeze free period4

Measure-
ment
Unit”

inches

inches.
per hour

total

inches
of effec-
tive soil

depth

per cent

1 year
in 25
years

position

inches

days

Class Separation

greater than 60

‘40-60

20-39

-10-19 -

Lass than 10

less than .2
.Z-ufi

.7-2.0

2.1—6.0

greater than 6.0

more than 12
9-12
6-8
3-5

0—2

3-6

7-12

13-18

19-25

greater than 25

no
yes

upland high ground
depressional high
ground

terrace high ground
terrace depressional
bottomland or alluvial

more than 60
40-60

20-39

10-19

0-9

less than 90
91-120
121-150

more than 150

Class
Desig-

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32

TABLE 1 (Cont'd)

 

1Class measurement units and class qualitative
.terms are as described in SOIL SURVEY MANUAL (1951).

2Class measurement units and.class qualitative
terms are described in IN-SOILS-l-l970.

3Class measurement units and class qualitative
~terms are described by.Galloway 35 51. (1968).

4Class measurements and.class.qualitativs terms
are described by Van Den Brink, gt 31, (1971).

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33

The predictive quality of this attempt was very poor. The
second attempt was to utilize the numerical class designator
for each variable in some type of additive point system.
However, a class designator of 1 may be ideal for one feature
whereas a designator of 3 may be ideal for another feature.
An attempt was then made to arrange the classes for a given
feature into an order of desirability. But the order was

not consistent for different land uses which would then re-
quire a rearrangement of the classes for every land use. The
concept of utilizing the actual numerical class designators
or actual measurement values in further computation was dis-
continued in favor of using indicator variables of the -1,

0, +1 type. -(Ruble 1967) The number of variables needed

for each feature is N—l where N = the number of classes or
class groups to be evaluated. The following example illus-
trates the structure of these variables in evaluating slope

for sanitary landfills.

If Slope Class = 1,2,3 If Slope Class = 4,5
X5 = 1 X5 = 0
X6 = 0 X6 = 1
If Slope Class = 6
X5 = -1
X6 3 -1

Note that in the above example slope classes 1,2, and
3 present slight limitations for development of sanitary
landfills and have been considered as 1 group. Slope classes
4 and 5 present moderate limitations and have been grouped
tOgether.“ Slope class 6 presents a severe limitation and

is considered by itself, thus making a total of 3 slope class

1V

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34

groups to be considered for sanitary landfills. Applying
the N—l formula there is a need for 2 variables.

The first step to determine the relative weight or
value of each variable was to devise a point system to quan-
tify each class or class group according to its degree of
suitability for the land use under consideration. A point
spread of 0-9 (inclusive) was utilized, 0 points designates
the most suitable class and.lf9¢points represents the degree
of suitability, with 9 points representing a very restrictive
situation. I

The second step consisted of setting up a series of
observations as sample data (page 44). In these samples the
dependent variable consisted of the summation of points for
the occurring classes of natural features influencing a
given land use (page 44). Dnce the total points for each
observation was determined,:the classes or class group were
then transformed into the indicator variables as explained
on page 33. The sample data were then submitted for regres-
sion analysis'to determine the regression coefficient of
(each variable and the constant for each land use. In the
final analysis of the test data (page 50) the natural feature
classes were transformed.into the indicator variables, and
the constant and regression coefficients for the independent
variables were utilized to calculate the dependent variable.

Tables 2, 3, 4, and 5 list the natural features, the
class or classes, the variable identification, and the class

points for sanitary landfills, residential homes with

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35

TABLE 2

The Natural Feature, the Class, Variable Designation, and
the Respective Class Points for Trench Type Sanitary
Landfills.1

AA . A

 

 

Naturali 33 2
Feature Class ‘ Variable Points'
Slope 1,2,3 X5 0
4,5 X6 3
6~ 9
Subsoil Texture 3 X7 0
1,2,4 X8 3
5 9
Natural Drainage 3,4,5 X2 0
1,2 9
Stoniness 1,2 x10 0
3 X11 3
4 9
Permeability 1,2,3 X4 0
4,5 9
Flooding 1 X3 0
3 9
Depth to Bedrock 1 X9 0
' 2(3,4,5 9

 

1The basic information for this table was taken from
Kellogg(13714 Table 7, page 30). The major change being
the use of points in lieu of the slight, mederate or severe
limitations as defined by Kellogg.

20 points denote the feature class or classes that
present a slight limitation, 3 points denote the feature
class.er classeSTthat present a moderate limitation, and
9 points denote the feature class or classes that present
a severe limitation.

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36

TABLE 3

The‘Natural Featuresw-the Class, Variable Designation and
the Class Points for Residential Homes with Sanitary
Sewers — No Basements.1

 

 

Natural Feathres Class Variable Points2
Slope 1,2 X2 0
3 X3 3
4 X4 6
5,6 9
Surface Texture 3,4 X5 0
1,2,5 3
Subsoil Texture 2,3,4,5 X6 0
1 3
Natural Drainage 3,4,5 X7 0
2 X8 3
l 9
Organic Matter3 3 X9
2,4 X10
1
Stoniness 1,2 X11 0
3 X12 3
4 9
Flooding3 1 x13 0
3 9
Depth to Bedrock 1 X14 0
2 X15 3
3,4,5 9

 

1Basic information taken from Kellogg (1971,, table 6,
page 28) and unpublished SCORECARD FOR HOMESITE EVALUATIONS
prepared by the Department of Agronomy, Purdue University,
West Lafayette, Indiana. The major difference being the use
of points in lieu of the slight, moderate, moderate to
severe, and severe rating.

20 points denote the feature class or classes that
present slight limitations, 3 points denote the feature
class or classes that present moderate limitations, 6 points
denote the feature class or classes that present moderate
to severe limitation, and 9 points denote the feature class
or classes that present severe limitations.

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37

TABLE 3 (Cont'd)

A
" v fiv v

*3Organic matter class 1 and flooding class 3 were
considered as very severe limitations and too difficult
to overcome for residential use and no index values were
calculated for sites having these values.

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38

TABLE 4

The Natural Features, Their Class, Variable Designation, and
the Class Points for.Residential.Homes Requiring Septic
Filter Fields - No Basements.1

A k 4. -

L

 

 

Natural Features Class Variables Pointszv
Slope 1,2 X2 0
.3 X3 3
4 X4 6
5,6 9
Surface Texture 3,4 X5 0
1,2,5 3
Subsoil Texture 2,3,4,5 X6 0
l 3
Natural Drainage 3,4,5 X7 0
2 X8 6
l 9
Organic Matter3 3 X9 0
2.4 X10 3
l 9
Stoniness 1,2 X11 0
3 X12 3
4 9
Flooding3 l X13
3
Depth to Bedrock l X14 0
2 X15 3
Subsoil Permeability 4,5 X16 0
3 X17 3
2 X18 6
l 9

 

1Basic information taken from Kellogg(197l, Table 6,

page 28) and unpublished SCORECARD FOR HOMESITE EVALUATION

prepared by the Department of Agronomy, Purdue University,
The major difference is the use
of the point system in this study in lieu of the slight,

West Lafayette, Indiana.

moderate, moderate to severe and severe ratings.

 

 

 

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_ ..._ _ _ s
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— . .
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r. . . n _ ~ rl. pit . if p T.
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T . . . . . .
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.. .1 1 _. 1;
l . . ‘ , T. . . . I, TO. .. Tl . T I. .J. T) . ‘i . . t l . If . .. T
\s ..a — rile CV .\...J .8 “is r.ly «Trix. nl.¢V fl‘y \MK I.\ .IU 1,)» 04 PI. F.\ O\_ AL 0;» FL Pf» (PM \.\ Kirk. NWT”. .1. \ . rlJ . _ ._r ‘
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39

TABLE 4 (Cont'd)

.L __.J

fl f Ff v

fl

20 points denote the feature classes that present
slight limitations, 3 points denote the feature classes
that present moderate limitations, 6 points denote the
feature classes~that present moderate to severe limitations,
and 9 points denote the classes that present severe
limitations.

3Organic matter class.l and flooding class 3 were
considered to be severe limitations and too difficult to
overcome for residential use and no index values were
calculated for sites having these values.

Put.
.1 .

 

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103

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L- .

40

TABLE 5

The Natural Features, Their Class, Variable Designation, and
the Class Points for Continuous Corn.1

 

 

Natural Features Class Variable Points3
Slope 1 4X2 0
' - 2 X3 '2
3 X4 6
4,5 9
Surface Texture 3 X5 0
2,4 X6 3
1,5 6
Subsoil Texture 3 X7 0
2,4 X8 2
1,5 4
Topsoil Depth 1,2 X9 0
3 X10 2
4 X11 4
5 6
Organic Matter 1,2,3 X12 0
4 X13 2
5 6
Stoniness 1,2 X14 0
3 X15 3
4 6
Soil Depth Favorable 1,2 X16 0
to Root Development 3 X17 3
4 X18 6
5 9
Available Water 1,2 X19 0
3 X20 2
4 X21 6
5 9
Flooding 1 X22 0
3 6
Topographic Position 2,4,5 X23 0
1,3 3
Freeze Free Days 3,4 X24 0
2 x25 3
1 9

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41
TABLE 5.(Cont'd)

 

1Basic information derived through consultation with
Harry Galloway, professor, Department of Agronomy, Purdue
University, West Lafayette, Indiana.

2Slope groups 4,5, or 6 were considered as a very
:severe limitation and too difficult to overcome and no
suitability index was calculated for sites having slopes
in these classes. — .

, 30 points.denote the most suitable classes, 1 to 8
points indicate the degree of suitability and 9 points
,represent the most.restrictive situations.

 

 

\.
pp

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or. o.-

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3 hr.

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42

sanitary sewers, residential homes requiring septic filter
fields, and continuous corn respectively.

The dependent variable was.then considered to be the
summatian of the points that a particular site would have
for a given land use.

.A summation value for the dependent variable from this
type of.ealculatipnewns.menely a total of the points re-
presented.by:the variable.c1asses for a given land use.
This was satisfactory for comparison of a single type of
land use fer*several sites,.but the value was not.adequate
to compare a.given site for.alternative uses. The point
value could be.a~reflection-of the number of variables con-
sidered and not entirely due to the land use suitability.
To illustrate the above situation assume two sites, site A
andsite 3,. are being evaluated for residential homes with
sanitary sewers. A total.of 8 natural physical features:
are considered relevant for this land use. Assume all of
the natural features.of.site A have a moderate rating (3
points each), and site~B has one feature having a severe
rating (9 points) and the remaining features have a moderate
rating. ‘The total number.of points for site A is 24 and
for site B,is:30 points- Therefore, site A is considered
more.physically.suited for residential homes with sewers
than site B. As indicated earlier in the text, this method
of.analysis is satisfactory for comparing several sites for
a given land use. But assume the planner wishes to deter-

mine if site A is more physically suitable for continuous»

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43

corn or residential homes on sewers. The number of natural
physical features.considerednnelevant.for.continuoua corn is
11 and.assume.a11;of.these features have a.moderate rating
(3 paintsueachl. .This wbuld.make.antota1 of 33.points for
“continuous.corn.versue a total o£.24 for.residential homes.
.But, this:comparison-istnetlreally.validebecause.the sites
“are about equallyzwell'adaptednfor bsmhzuses according to
the slight, moderateinandgseweredratingwaystem. The differ-
“ence in.the number.of points is.dnemmbre to the nuMDer‘of
naturalzfieatures.cnnsideredrthanltelthe suitability of each
feature;. This makes the concept of.developrmg an index
value.more justifiednwhennone wants to compare a single site
‘fur.several.alternativennses..KThe-index.in.this.stndy.con-
'sists.of'dividing-the numberzof actual'points for.a site for
a-ginen land use by.the tbtal number of pointsIPOssibLe—for
”thELsamexlandflusea..(assuningatheaworst.possible natural
conditiqn)‘FThis;va1ue.isnthen.converted:to a percentage.
which. is. a- masureaof the per. cent of ”goodness" ‘of a, site.
for a given land use and is referred to as the Physical

Site Suitability Index (PSSI) in this study. The PSSI of a
site for one land use can be compared to the PSSI for other
land uses, or the PSSI of a site for a given land use can

be compared to the PSSI of another site for the same land
use. This procedure. permits the type of flexibility needed

1'

in evaluating the physical features of a site.

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Sample Data

 

One hundred and forty four observations depicting
'different types of natural conditions were utilized for a
multiple regression mode1.for sanitary landfills. The obser-
vations did not represent;actua1 field observations, but
rather theoretical combinations.of differeht'natural condi-
tions that could occur in the real world; All classes
within each natural feature.were represented but not all of
the possible naturally occurring combinations-were included.

one hundred and ninety six observations were utilized
in the multiple regression model for residential homes with
sanitary‘sewers,‘residential homes requiring septic filter
fields, and continuouslcora. The method of formulating
these observations.was very similar to the method utilized
for sanitary landfills.'.The additional number of obser-
vations was necessary to include more possible combinations
caused by evaluating a greater number of natural features

for the latter three land uses than for sanitary landfills.

Determination of Parameters for Each Land Use

the dependent variable for each theoretical observation
was calculated by converting the observation data into their
appropriate classes and determining the respective points of
each occurring class. The points were then summed and the‘
summation entered as the dependent variable for that obser-
vation.' Each of the class‘designations were then trans-

formed into indicator variables of the -l,0,+1 type. This

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45

procedure was adhered to for each observation and for each
land use. These data were.then entered onto computer cards
with a card for each observation which resulted in a deck
of 144 data cards representing 144 observations to be eval-
uated.for sanitary landfills and 3 decks of 196 data cards
representing.196 observations to be evaluated for each of
the other land uses considered in this study.

_ Data were then submitted for computer analysis.using
the least squares technique. (Stepwise Regression 1969)

The general form of the equation submitted for each

land use was as follows:

Y = f(xik“+

k " xnk)

Y = total point summation for land use k
k = specified land use
X = variable for land use k

i = variable identification

n = last variable

Explicit Equation

The regression coefficients obtained from the computer
analysis for each land use represent the approximate weighted
values of each designated independent variable for the
different land tses.

Tables 6, 7, 8, and 9 list the natural features, vari-
ables, the regression coefficients and the constants for
Sanitary landfills, residential homes with sanitary sewers,
residential homes requiring septic filter fields, and con-

tinuous corn respectively.

 

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46

TABLEMG

The Natural Features, Variables, Regression Coefficients,
and Constant for Sanitary Landfills.

 

 

 

Regression
Natural Features Variable Coefficient
Constant 26.64
Natural Soil Drainage X2 -4.47
Flooding x3 -4.47 r?
5—1
Permeability X4 -3.21
slope ' x5 -4.03
X6 ~0.96 .4
Texture of Subsoil x7 -l.90 5!
X8 +1.09
Depth to Bedrock X9 -4.54
Stoniness X10 -4.01

x11 -a.93

 

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47

TABLE 7

The Natural Features, Variables, Regression Coefficients,
and Constant for Residential Homes with Sanitary Sewer -
No Basements.

 

 

'ifiegression

Natural Features Variable Coefficients
Constant 28.07
Slope X2 24.40

X3 -1.51

X4 +1.48
Surface Soil Texture X5 -1.‘4
Subsoil Texture X6 -l.$7
Natural Soil Drainage X7 -3.97

x8 -0.98
Organic Matter X9 -4,03

X10 -Q.93
Stoniness X11 -4.02

812 r1.04
Flooding X13 —4.46
Depth to Bedrock X14 -4.10

x15 -o,31

 

 

 

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48

TABLE 8

The Natural Features, Variables, Regression Coefficients,
and Constant for Residential Homes Requiring Septic Filter
Fields - Ne Basements.

 

 

Regression

NaturalWFeatures Variable Coefficients
Constant 33.83
Slope X2 -4L39
X3 -1;Sl
Surface Soil Texture X5 -l.42
Subsoil Texture X6 -2.10
Natural Soil Drainage X7 f4.93
- X8 +0.96
Organic Matter X9 ;4.04
, X10 -O.90
Stoniness Xll -4.02
X12 71.04
Flooding X13 -4L46
Depth to Bedrock X14 :4.10
X15 -0.81
Subsoil Permeability X16 -4.27
X17 -1.33

X18 +1.89

 

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49

TABLE 9

The Natural.Features, Variables, Regression Coefficients,
and Constant for Continuous Corn.

 

 

Regression

Natural Features variable Coefficients
Constant a i . 35.00
Slope X2 -4.12
X3 -2.14
‘X4 +1.77
Surface Soil Texture X5 -3408
X6 -0.03
Subsoil Texture X7 -1.92
X8 +0.07
Topsoil Depth ' x9 -3.14
Xll +1.09
Organic Matter X12 -2.52
: X13 ‘ ’ -0.57
Stoniness ‘ X14 +3.15
X15 -0.19
Soil Depth x15 44.39
X18 +1.50
Available Water X19 -4.22
X21 +1.84
Flooding x22 -2.98
Topographic Position X23 —1.45

Freeze Free Days X24 -3.94
- . * - X25 -l.01

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50

These tables can be related to equation form simply
by summing the constant and the product of each variable
and its respective regression coefficient. This summation
value is then converted into an index value as explained
on page 43. 'For example, the equation for determining the
PSSI for'sanitary landfills is:

'pSs1-='Ioo-((26.64- 4.4722e4.47X3-3.21x4-4.0335-0.9GXG-
l.90X7+l.09X8-4.54X9-4.0leO-0.93Xll)/45)100

Test Data

 

Test data were collected in Grand Traverse County,
Michigan. -Criteria for selecting the county consisted
merely of choosing a county in Michigan where information
on soils and topography was readily available and where
contrasting differences in soils and topography existed
within relatively short distances. The size of the test
area consisted of two sections of land (1280 acres).
Several of the soil survey maps in the Grand Traverse Soil
Survey Report (Weber st 31. 1960) were visually examined .
and a section of land was selected that contained differf
end types of land uses and contained contrasting soil condi-
tions in terms of soil texture and natural soil drainage.
A second section of land was selected from the same county
but in an area where part of the section was inundated by
the East hrm of Grand Traverse Bay. The purpose of selecting
the second section was to permit the entering of special land

use characteristics into the system and later testing the

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51

system for possible existence oflthese special.character-
istics. A grid coordinate system.was then superimposed
over the soil survey map for each of the sections of land
selected. The grfissisiei_EE§B&JETE£EBCEEE€ZSSjo£ land
(640 acres) into 2% acre units 03156 gsieefs par section
for a total of 512 parcels.l Each grid unit;hasithen iden-
tified by row - column designations as indicated in Figure
l. 1

Data were then collected and recorded opfia data sheet
(appendix A) for each 25 acre unit. :Collectiomjwas re-
stricted to the type of natural resourCe‘data‘listed in
Table l and certain bread,classificatiens of current land
use as determined from the.aerial photographs in the Grand
Traverse County Soil-Survey.Report.. (Weber gt 21. 1966)
The current land use classification used included urban,
recreation, transportation, agriculture, timber, and water.
An estimate was made of the approximate percentage that
each land use constitutes:of.each designated*2k acre unit.
These percentage values'were then grouped into the following
five classes for numerical identification: class 1 = 100

(91-1008), class 2 = 75 (65~90%), class 3 3 50 (35-64%),

class 4 = 25 (10-34%), and class 5 = 0 (0-9%). The primary
purpose for including current land uses was to recognize

dominant landscape;characteristics.such as bodies of water
and to recognize the:importance of current land uses. For

example a site index.value would be meaningless for a

sanitary landfill if 75% of the 2% acre unit was currently

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Township 29 North, Range 10 West, Section 34,
Grand Traverse County, Michigan

Column
1 l6

 

I

Township 27 North, Range 11 West, Section 36,
Grand Traverse County, Michigan

Column
1 16

17

2090

32

 

FIGURE 1. The Grid Coordinate System of Each Section of
Land Showing the Row - Column Locations of
Each 2% Acre Parcel of Land.

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53

in an urban classification. Likewise an agricultural
rating would be meaningless if 100% of the 2% acre unit
was classified as water or urban.

Natural resource data were obtained by determining
from the soil survey map (aerial photograph background)
the dominant mapping unit (soil type, slope, and erosion)
for each of the 512 land parcels (2% acres each). In some
instances several different mapping units were present
within a single parcel. In these cases the mapping unit
that had the steepest slope, or had greatest erosion, or
had poorest natural drainage was determined to be the
critical mapping unit.

A composite list of all existing soil types, slopes
and erosion combinations was made from the data sheets.
Each of thse existing combinations is referenced by soil
scientists as a soil mapping unit and usually designated
by three letters and a number. The first two letters indi-
cated the soil type, the third letter indicated the slope,
and the number indicated the erosion class. Occasionally
there were only two letters and the third letter was inter-
preted as an A. In several instances the number was missing
and this was interpreted as a l.1 The text of the Grand
Traverse Soil Survey Report (Weber et 31. 1966) was then
utilized to determine the soil characteristics represented

by each mapping unit. Values listed for these features were

 

1The letter and number are occasionally omitted for
soils that occur only in flat areas or where the erosion
is always class 1.

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54

then coded with the aid of a soil worksheet (appendix B)
into the various classes as listed earlier in this chapter.
The data for each soil was then entered onto an individual
computer card using the soil type and slope letters, and
the erosion class as the mapping unit identifiers and the
numerical class designators to identifythe class value
represented for each feature. -

Information on each data sheet was then entered on an
individual computer card using gridcoordinates to identify
each 2% acre unit along with numerical class indicators
representing the percentages of the different current land

uses, and the freeze free period. The soil mapping unit

was identified with three letters and a number.

Data Input

 

-"The soil card data Was entered into a single dimension
array identified as SC(M).' The SC indicated the datanas
from the soil-card and the M denoted the 13 elements in the
array.‘ The first element of the SC array consisted of'3
alpha characters identifying the soil mapping unit. The
remainder of the elements were numerical and are identified
on the soil work sheets. (appendix B)

The basic data on each parcel were entered into a three
dimensional array which was designated DSl(I,J,N). The
first two dimensions were utilized to denote the row and
column locations.“ The third dimension denoted the basic
site data and consisted of 27 elements. The first 11 ele—

ments consisted of the numerical information entered from

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55

the data card while element number 12 was entered as three
alpha characters identifying the soil type and slope with

element number 13 designating the numerical erosion class.

Elements 7, 8, 9, and 10 are blank in this study. These

spaces were reserved for possible additional features but

were not utilized. Elements 14 through 27 were reserved

for the soil features that were entered into the system

from the soils array SC(M) .
All 512 of the site data cards were read into central

storage of the computing system at the beginning of a run.
Then a soils card was read and each site was checked to

determine if the mapping unit identified on the soil card
matched the mapping unit on the data card. If there was

not a match on any of the 512 parcels between the soil
type, slope and erosion then the information contained on

that particular soil card was not retained and another soil

card was read. However, if the soil card mapping unit
matched the data card mapping unit then the data contained

in elements 3 through 16 of the SC array was entered into

elements 14 through 27 of the D81 array and another soil

The procedure of reading one soil card at

card was read.
a time and checking each site for the matching mapping unit

was continued until soils information was entered for all

512 sites. An error message was incorporated into the com-
puter program to indicate the occurrence of a missing soil

card. Figure 2 is a schematic flow chart showing the basic
steps of the data input system.

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56

FIGURE 2

Schematic Flow Chart of Data Input and Processing

Legend

Entrance or Exit

Data Input or Output

 

Computations

 

 

 

Decision

Begin Loop

End Loop

“7.10 .0

57

     
      
   
      
    

Read Data Card
For Each Site
DSl(I,J,N)

Read Soil
Card
SC

  

Check For
timate

Figure 2

 

 

 

 

 

 

 

 

 

 

 

 

 

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, Determine If
“manil;Card Labelray
34$},- Mapeing _ Unit
On Data Card

 

   
   

 
 
  

 

 

 

  
  

Enter S '
Into Si e Data

 

 

Figure 2 (Cont'd)

 

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1 Determine If4 A
Each Data Site Array
Contains Soil Data

  
    
 

DSl(I'J'y . yes.

no

 

 

 

 

K=l,4 1i

Transform Data
. Into Indicator

Variables

 

 

 

 

if PSSI: i k
/ f(xik+ ..xnk) ‘
1 _ .
Write :ES

Results

 

 

 

 

 

 

 

End

Figure 2 (Cont'd)

 

 

 

 

 

 

 

 

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60

Data Processing and Computation

‘The data processing consisted mainly of transforming
number class data designators into indicator variables of
the -l, 0, +1 type as explained earlier in this chapter.
A series of transformation statements were written for each
land use covering all of the independent variables for that
land use. The Physical Site Suitability Index equation
‘for a given land use immediately follows the set of trans-
formation statements for that land use. Each land use is
denoted by a K value and the possibility was built into
the system of evaluating all four land uses or any one parti-
cular land use by designating the appropriate K value. This
value would direct the computer to the corresponding set of
transformation statements.

 The computed PSSI is stored in a three dimensional

array designated as DS2(I, J, K). The first two dimensions
of this array denote the row ~ column location and the
third di mension denotes the land use K. The primary reason
for not incorporating this value into the D81 array is due

to the variable type. The DSl arrays are integer type and

the DSZ arrays are stored as real type.

Computer Program

The'computer.program was written in Fortran IV (CDC
1969) andprocessed on the CDC 6500 computing system at
"Michigan State Uhiversity,-East Lansing, Michigan, and on
-the CDC 6500 cemputing system at Purdue University, West

Lafayette, Indiana.

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The entire computer.programis included in Appendix C
and apprOpriate comment cards-have been inserted for aid

and assistance in following the logic and procedure.

Data Output

 

Output from the program is in the form of 9 tables
(Appendices D and E). Appendix D consists of one table and
is a partial listing of the data entered and also illustrates
the ability to recall information on a particular land
parcel.' The first line of output is a listing of the data
to be entered for location coordinate row 3, column 3.’ This
unit was selected to illustrate the type-of data input and
also as a check to make sure that data were propertly
entered into the program. The remainder of the output in
Appendix D represents the 43 soil cards that were repre-
sented in the two sections of land. The last “soil" card
represents a water area. The program was written to check-
for a value of zero in the 14th element of the 3rd dimen-
Sion of the D81 array. If this value was zero then the'
computer looked for another soil card and if none could be
found the program would abort. Therefore, a method had to
be divised to read a "soil” card for every coordinate re-
gardless of whether the area was water or land and the only
way of entering a positive number greater than zero into
this element was through the soil array. Therefore, the
three letters "000" represent a water area and the value

h

of one can be entered into the l4t element and values for

elements 15 thru 27 are listed as zero.

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Output in Appendix E is in the form of eight tables
denoting the Physical Site Suitability Index for each land
use and for each section. Each‘value in the tables re-
presents a 23 acre unit‘and_is geographically located ac-
cording to its row - column designation. The size of each
table has been spaced into an eight inch square which is a
fairly common. scale for aerial.photography (eight inch682
on the map equaling one.mile)c Tho.value of 666 in Appendix
E. page: 93; 97. 101. and 105 illustrate the value of the
special land use.character. This is the East Arn;of Grand«
Traverse Bay and a calculated index for any type of land use
VGULd be meaningless. .The.spooial character 555 in appendix
E. pages 105 and 107;i11uatratos the value of allowingjor
ioverriding" featurea.: Theso.aro topographically steep areas
and to consider using them.£or continuous corn -vould be a
hazardous and difflult undertaking. Footnotes on the output
pages denote potential existence of "overriding" features

for different land uses that were built into the system.

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CHAPTER 5

RESULTS AND DISCUSSION

Interpretation Of the PhysiCal Site Suitability Index

The Index is a-degree of suitability represented by a
set of physical featurestor a given land use; iThesei
features represent real world situations and thé'size of
the area evaluated is 2% acres. This measurement of suit-
ability is'derived by comparing the set of physical features

of‘& given area to be'evaluated to a suitable set cf physi-

1

cal features used as-a standard for a given land use. The

index may be interpreted as representing the per cent of
"goodness“ Of a site or area for a given land use in

physical terms.

Advantages of the Index

The index and the method of calculating the index es-
tablishes a framework for integrating and analyzing various
types of natural resource data into a single rating. This
framework permits addition of variables to include many
types of land uses. It also allows for a change in the

weighted value of each variable as its relative importance

to a given land use may change.

 

‘ 1The’standards‘used in the Study are referenced for the
respective land uses as explained in chapter 4.

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64

Several alternative land uses-may be-compared for a
given site utilizing the index as azcriterion.1 Current
methods of comparison relate.the set of properties for-a
given land use as presenting slight,-moderate or-severe
hazards (as defined on page 5) to the use.in question but
there is no quantitative method of evaluating_degnees of
suitability within a given—clase‘ The index prevides a
numeric rating ranging from a possible high of 100% to a
possible.low of 0%. To compare several alternative land
uses.for-a site the user askswfor.the.calculated value for
a_given land use covering therarea in which he is inter?
sated. The land use having the.higheat index value is the
use most physically adaptable-to the site. If the index
value is less than.nearmperfect.(lOO%) on if the.user
wishes he may want to examinepthe.cause of the lower values
for tha.other.uses. .To.accompliah.thia the user asks for.
a listing ef the natural feature values thatswere seasidered
for-each land use. .(Illuttrated.in Appendix D) This pro-
vides the flexibility of being able to knew the physical
features of the site and know which land use is the more
adaptable.

:For example,the parcel cf land located in row 6, column
l,_section.34 has an index rating of 67 for sanitary land:

fills, a rating of 85 for homes on~sanitary sewers. a rating

 

1Only the four land uses specified in this study can
be compared unless the program is expanded.

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of 76 for homes requiring septic-filter fields. and a

rating of 78 for continuous corn. .This would indicate to
the planner that of the 4 land uses considered, the site

is most physically suitable for homes on sanitary sewers;
and least suitable for‘a sanitary landfill.. The-planner also
kncws that the parcel is nearly equal in its rating for con-
tinueus corn and residential homes requiring septic filter
fields. Since the parcel did net have a 1000 rating for any
of the land uses tested the-planner will probably want to=~
examine‘the natural features to determine why the ratings
were-low; He can then analyze the site in conjunction with
additiOnal data to recommend a land use;or management
practice.

Comparing several sites for a single‘land use is rela-
tively simple utilizing the‘index. The userucompares the
calculated.index;value for each.site in which he is.interv
ented. The site having the highest rating is the site most
adaptable to the use in question.

For example the parcels of land located in row 3 column
3, and row 3 column 5 have ratings for residential homes on
sanitary sewers of 92 and 79 respectively. The planner or
deVelopeerould immediately know that the natural physical
characteristics of the land parcel located in row 3 column
3 is better suited for this land use than the other parcel.
He would then evaluate other factors such as location. ac—

cessibility, availability and.other planning factors before

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reaching a final decision regarding the development or
purchase of the site. Very often in these types of compari-
sons the user may wish to look at the adaptability of the
surrounding area as well as the immediate location. This
would enable the user to know whether he has an isolated
area or if the entire region around the site is nearly
similar. After examining the index values for each site
the user.may wish to know why the variation existed between
the values. This can be accomplished by asking for a list-
ing of the natural feature values listed for each site.
(Appendix D)

In comparing several sites for a single land use or
several land uses for a single site the user not only has
ths_flexibility of knowing the relative rating of each site
for the land tse considered, but he also has the option of
determining the physical characteristic of each site. This
flexibility can be utilized to great advantage in conjunction
with other planning and decision-making factors. For
example, if a user is looking for a homesite requiring septic
filter.fields the best alternative site based on the natural
physical features may be less accessible than another site
with a slightly lower rating. By examining site features
having the lower rating the user may decide that he can
economically overcome the less desirable features and be in
a much better location. The user must make this decision.

. In making land use decisions the land planner may be

confronted with the situation of having a limited land area

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67

for several projected land uses. The planner needs to know
critical limitations that may exist in each land parcel.

He may also want to know the degree of land use adaptability
of each parcel. Very often one parcel of land is well
adapted to many different types of uses while ether parcels
are very limited as to their suitability for different uses.
For example, a well drained upland soil may be rated high
for several types of uses but a soil high in organic matter
may have a high rating only for agriculture.“ Therefore, if
the planner had to make a decision between zoning units, the
more logical agricultural zone would be the higher organic
soils.’ To aid in this decision process the planner may
desire a location map of areas having natural features
presenting a critical situation to specific land uses such
as flood plain areas or organic soil areas.

To obtain this type of information the planner or a
computer programmer would have to write a few statements
requesting the computer to scan each parcel of land for a
specified natural feature. .Once a given value were found
the parcel location would be noted and a value or symbol
would be printed on a row - column location to denote the
Special condition. For example if the planner wished to
obtain a print of all bottom land soils (areas subject to
stream overflow) he would write program statements to look
at each parcel of land for a value of 5 in the 26th entry .
of the data array., (DSl (I,J,26) I= row number and J= column

number). If this value was found then a number 5 could be

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68

printed for that location. This would be a.single objective
map and all locations having a value of 5 would be bottom-
land and the planner could then utilize this type of
information in his planning process.

The greatest single advantage of the index is the
capability of analyzing a set of physical features for a
number of sites very easily and efficiently through an
automatic data proceSsing procedure. The cost and time of
coding and in putting.the initial data for the automatic
system is nearly equal to the cost of analyzing the same
set of data for one land use by conventional overlays and
tables. Once data are initially entered into the computing
system they can be recalled for multiple uses, which reduces
the cost per use. But if data are to be used only once,
then there does not appear to be a great cost advantage

in using the computer program.

Potential Uses of the Index

 

The site index represents the relative suitability of
each site for given types of land use, and can be combined
with location, economic, and transportation data to serve
as an additional tool in local, area, state, and regional
planning.

State agencies can utilize this type of information
system and analysis in promoting state-wide recreation or
land use planning or in preparing state wide greenbelt areas

or highway corridor maps. Agencies such as the Soil and

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Water Conservation-Districts:and the Cooperative Extension
Service can utilize the information.in encouraging and w
promoting more local land use planning and conservation.
Federal agencies.such as,the U.S. Forest Service and U.S.
Soil Conservation Service can utilize the.available infor-
mation to quickly analyze data that would be_of value in
assisting local communities.in formulating-community goals
and action plans.- All agencies-can utilize.and expand the
physical information system to.help-in evaluating their own
goals and assistance plans-for-serving the general public.

Natural rescurce planners-and managers can utilize the
site index to help locate areas where certain types of de-
velopment may be injurious-to-the environment without certain
precautionary measures.' The site-index can also be of
assistance in managing land-resourceseto obtain maximum
benefit or:return from:an individual site.

This can be accomplished by the resource planner
comparing-the index ratings of-a site for the desired
potential-uses...If the indexnratings are near 100 per cent
for each of the uses than-the.manager would know that he
would not have to invest in expensive site preparation
costs, but if the index ratings are less than perfect he
can determine from a listing of the physical properties
the cause of low rating. He can then consult a land
contractor-to determine the;cost of overcoming the problem
or problems. The costs of site preparation can then be

added to the cost of purchase and management and compared

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70

to the potential gross return of the site to-determine the
net return. For example, a land resource manager or de~
veloper may have a site where he wishes to deve10p a‘:
residential development and-the index rating for homes on
sanitary sewers may be 109 per cent but the same site may
have a lower rating for residential homes‘requiring septic
filter fields.‘ The developer can determine the Cost—of
overcoming the problem of installing the septic filter field
and weigh this cost against the cost of alternativersewage
treatment methods.‘ The costs of installing a treatment
plant or overcoming the problem~of"installing a septic
filter field may make the cost-of lots higher than-the
developer feels he can realize from their sale. The de-
Veloper or land resource manager would then want to'consider
alternative uses-of the land. This same type of procedure
Can be performed for each proposed use and the manager oan
determine which use will give'the'greatest net return
without causing injurious effects to the environment.-

'Agricultural planners can utilize the site index in
making yield predictions and in evaluating areas for future
agricultural production. .This information can then be
correlated to local zoning- to help preserve certain soil
areas for production of food and fiber.

Realtors and land develOpers-can benefit from the site
index~by13eleeting-areas that have a favorable rating for

their needs or interests.

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71

_ The uses suggested.above.rapresent but.a few of the
applications that can be made.of the site index. The index
can-also be used in teaching natural resource planning_
through the use of-game-simulation.models as well as in
research and extension work.

. A primary potential use ofnthe_data.handling method is
in the field of watershed;planningrand.managemant. The-
current method.of.estimating.runoff from a watershed area
or reach is to determine thespredominate soil areas, type
9f;vegetative cover and general slope.of the land for a
broad area or entire reach.. A.watershed characteristic
value is then.determined.by approximating the various.cate-
series of.sach.unit.. This value is then utilized in pro-
jecting runoff and calculating the hydrological character-
istics of the watershed. With the use of automatic data
processing and the coordinate location of small segments
covering the entire watershed, the planner or engineer
can determine the percentage of each area that is in differ-
ent types of vegetative cover and determine the portion that
is urban. This current land use information can then be
combined with data on slope} surface soil texture, depth of
topsoil, and texture of the subsoil to estimate the infil-
tration rate. The potential runoff can then be calculated
for a specified rainfall intensity. Using smaller segments
and locational.orientation of resources.will give a more
accurate estimateof potential runoff than does the current

I

method of using a value.for a large area. The planner could

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72

then utilize the suitability index to determine patential
uses of the watershed area, combine these with economic pro-
jections for the area, adjust zoning and planning of the
area to.match the suitability index as near as economidally
P0381b18;. The.watershad engineer could.then.utilise then
planning projections-for the area and the locations of these
projections in recalculating.the hydrological:charactere
istics of the watershed. The hydrologist would know exactly
which land areas ara;affected and the change.that.this will
lake in overall watershed-characteristics. These calcu-
lations and projections-can be accomplished.very“rapidly

and easily with automatic data processing using the suit-

ability index computer program.

1

New Technologyfiand Techniques

 

The SCS (Swanson 1970) is currently engaged in the task
of coding soils information for automatic processing to be
used primarily for soil classification. They (SCS) are in
the discussion stage of setting up a system of utilizing
coded information for land use interpretations1 and are
experimenting with the use and formulation of a method to
publish a digitized soil survey map. If this procedure can
.be accomPlished, then soils information could be read

directly from the map and the task of coding and reading

soil maps would be greatly simplified. The SCS projection

V— Y

1National Cooperative Soil Survey Technical Work-
Planning Conference, Charleston, South Carolina, January
25- 28, 1971.

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73

is to have the digitized.mapping procedure operational by
1974.1

EJohannSen (1968) emphasised the need for establishing
an economical information processing system that has the
capability of making resource information available to the
user within a week and that remote sensing with automatic
data processing capability may possibly meet these require-
ments.

The National Aeronautics and Space Administration will
soon orbit an Earth Resources Technology Satellite to trans-
mit imagery back to earth on urban and rural land uses,
geologic features, and other natural features of the earth's
surface. (Sattinger 1971) Other natural resource infor-
mation and hopefully the information from the satellite can
be utilized as input for computing the index. Philip Le
Blanc,2 at the Laboratory for Application of Remote Sensing
in West Lafayette, Indiana, is currently investigating the
capability of remote sensing techniques to consistently
identify different types of ground cover and land use
patterns. This information can become a direct input in

calculating the Physical Site Suitability Index.

 

1Personal conversation with Ray Dideriksen, State
Soil Scientist, Soil Conservation Service, U.S. Department
of Agriculture, Indianapolis, Indiana.

2Philip N. LeBlanc, Remote Multispectral Sensing of
Land Use Features, (unpublished) M.S. Thesis, Department
Of Agronomy, Purdue University, West Lafayette, Indiana.
June 1972.

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74

The Site Suitability Index has.many potential uses
and has the capability of becoming a valuable tool in land
use planning decisions. These capabilities become even
greater when data inputs become more refined and are more

efficiently obtained.

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LI ST OF REFERENCES

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LIST OF REFERENCES

Belknap, Raymond K., and'John G. Furtado. 1968. The

Natural Land .Unit as a Planning Base. Landsca 0
Architecture. Volume 58. Number 2, pp. IKE-IE7.

Blalock, Hubert M. 1960. Social Statistics. McGraw-Hill
Book Company. New York, and London.

 

Callison, Charles H. 1967. Americas Natural Resources.
. National Audubon Society. The Ronald Press Company,
New York.

 

I

CDC. 1969. Qntrol Data, 6400/6500/6600 Computer System
Fortran Extended Reference Manual. Control Data‘
Corporation.. Palo Alto, California.

Clawson, Marion, R. Burnell Held, and Charles H. Stoddard.
1960. Land For the Future. Resources For the Future,
fInc. Johns Hopkins Press, Baltimore, Maryland.

Galloway, H. M.,.0. Hopkins, Jr., J. L. Ahlrichs, and T. C.
Bass. 1968. Soil Judging In Indiana. ID-72.
Cooperative Extension Service, Purdue University,
West Lafayette, Indiana.

Golenpaul; Dan.: '1972. Information Please, Almanac, Atlas
and Yearbook; 1972. 26th edition. Simon and
Sauuster, New York City, New York.

In-Soils-l. November 1970. Standard Terminology To Be
Used In Indiana Soil Surveys. Soil Conservation
Service, U.S. Department of Agriculture, Lincoln,
Nebraska.'

 

Johannsen, Christian J., and M. F. Raumgardner. 1968.
Remgte Sensin For Planning Resource Conservation. _
Proceedings 0 the 23rd Annual Meeting Soil Conser-
vation Society of America. Athens, Georgia. Published
by Soil Conservation Society of America, Ankeny, Iowa.

Kellogg, Charles E. 1971. Guide For Interpreting Engineer-
ing Uses of Soils. (Advanced unedited copy February
T9717. SoiTConservation Service, U.S. Department of
Agriculture, Washington, D.C.

75

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76

Landsberg, Hans. H., Leonard L; Fischman, and Joseph.L.
Fisher. 1963. Resources in America's Future-
Patterns of RequiiementswgndAvailabilities 1960-
2000. Resources For the Future, Inc. The Johns-
fiopkins Press, Baltimore, Maryland.

MLIS. March 1971. (Minnesota Land Information System).
Department of Administration, State of Minnesota,
St. Paul, Minnesota. ' '

Montgomery, P. H., and Frank C. Edminister. 1966. "Use
of Soil Surveys in Planning for Recreation." Soil
Surveys and.Land Use Planning. Edited by L. J...
fiartelli, A. A. Klingebiel, J. v. Baird, and M. n.
Heddleson. Soil Science Society of America and
American Society of.Agronomy, Madison, Wisconsin.

 

Murdoch, William W. 1971. Environment, Resourceg,
Pollution and Society. Sinauer Associates, Inc.,
Stamford, Connecticut. -

 

NARIS. 1970. (Natural Resources Information System);.
University,of Illinois, and the Northeast Ill1nois
Natural Resource Service Center. ILLIAC IV Project.

‘Urbana, Illinois. "“' -~,

Quay, John R. “1966.' "Use of Soil Surveys in Subdivision
Design." Soil Surveys and Land Use Planning. Edited
by L. J. BarteIIi, A. A. KlingebeiI, 3. V. Baird, and
M. R. Heddleson. Soil Science Society of America and
American Society of Agronomy, Madison, Wisconsin.

 

Ruble, William L. 1967. Analysis of Covariance and
Analysis of Variance With Unequal Frequencies Per-
mitted In The Cells. Stat Series Number 18.
Agricultural Experiment Station, Michigan State
University, East Lansing, Michigan.

 

Sattinger, Irvin. J. 1971. Satellites To Monitor Earth
Resources. Parks and Recreation. Vol. VI. No. 12.

 

Sinatra, James B., Lyle Sendlein, Gary 1. Hightshoe,
Robert C. Palmquist, and Thomas E. Fenton. 1972.
Iowa Awareness. Volume 1, Number 3. The Iowa Land
Use Analysis Laboratory, College of Agriculture,
Iowa State University, Ames, Iowa.

 

Soil Survey Manual. 1951. U.S. Department of Agriculture
Handbook Number 18. Agricultural Research Adminis-
tration. U.S. Department of Agriculture,

Washington, D.C.

,
““71

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77

Stepwise Regression. 1969. BMDZR. Computer Center,
Purdue University, West Lafayette, Indiana.

Swanson, Dwight W. 1970. Use Of Automatic Data Processing
In The Soil Survey. Soil Survey TechnicaI'Notes.
Soil Conservation Service, U.S. Department of
Agriculture, Washington, D.C.

Swanson, Roger A. 1969. Land Use and Naggral Resource
Inventory. New York State Office of'Planfiing
Coordination, Albany, New York.

 

Van Den Brink C., N. D. Strommen, and A. L. Kenworthy.
1971. Growing Degree Days In Michigan. Michigan
State University Agricultural Experiment Station.
East Lansing, Michigan.

Weber, Herman L., Robert Hall, Nels R. Benson, and G.
Van Winter. January 1966. Grand Traverse County,
Michigan, 8911 Survey Report. Michigan Agricultural
Expefiment Station. East Lansing, Michigan and Soil
Conservation Service, U.S. Department of Agriculture,

Washington, D.C.

Wenner, Kenneth A., C. J. Johannsen, H. M. Galloway, L.
Hoyle and R. Montgomery. 1964. Munster Soil Survey

Report. Munster, Indiana.

Wenner, Kenneth A., H. M. Galloway, J. E. Yahner, Irving
Dow, L. Hoyle, and Ival Persinger. 1968. Crown Point
Soil Survey Report. Crown Point, Indiana.

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APPENDICES

APPENDIX A

DATA WORK SHEET

Location

Row Cqumn

Current Land Use

 

1. Urban
__ 100% ‘__ 25%
75% ___ 0%
50%

2. Transportation

__ 100% __ 25%
___ 75% .__ 0%
_.. 50%
3. Recreation
__ 100% __ 25%
__ 75% _ 0%
_ 50%
4. Agriculture
__ 100% __ 25%
___ 75% __. 0%
__ 50%
5. Timber
__100% _25%
75% __ 0%
50%
6. Water
__ 100% ___25%
.__ 75% __ 0%
50%

78

APPENDIX A

DATA WORK SHEET

Climatology

 

11. Freeze Free Period
1. __ 60-90 days

2. __ 91-120 days
3. __ 121-150 days
4°.__ More than
150 days
Soils

12. Mapping Unit

 

soil type slope

13. Soil Erosion

cIass

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APPENDIX B

SOIL CODING SHEET

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SOIL CODING SHEET

 

 

Soil Label 2.
. _ soil type Slope soil erosion
Slope ’
1 ‘ 0-2% A 4 13—18% D
2 396% ‘ B 5 19-25% E
3 7-12% C 6 More than 25% F or G
5, 6 Texture 4. 5. 6.
Surface Subsoil Underlying
Material
c1ay_ .,
silty clay I l l
dandy clay.

silty clay loam
clay loam 2 2 2
sandy clay loam

silt'

silt loam 3 3 3
loam” “
Sandy loam| 4 4 4
loamy Band 5 5 5
sand_ ;.
Drainage
1. Poorly and very poorly
2 Somewhat poorly
3 Moderately well
4 Well

5 Somewhat to excessively well
Topsoil Depth'

More than 16 inches
11-16 inches

7~lO inches

3-6 inches
0—2‘inohes

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1 More than 9%

2 5-9%

3 3-4%

4 0-2%

Stoniness (classes)

1 0

2 1

3 2

4 3, 4, or 5

Soil Depth

1 More than 60 inches
2 40-60 inches

3 20-39 inches

4 10-19 inches

5 Less than 10 inches
Permeability

1 Less than .2 inches/hr.
2 .2-.6 inches/hr.

3 .7-2.0 inches/hr.

4 2.1-6.0 inches/hr.
5 More than 6.0 inches/hr.

Available Water

More than 12 inches
9-12 inches
6-8 inches
3-5 inches
0-2 inches

thNH

Flooding (1 year in 25)

1 no
3 yes

Topographic Position

1 ___ Upland high ground

2 ____Up1and depressional
3 ____Terrace high ground
4 ___ Terrace depressional
5 ___ Bottomland or alluvial
Depth to Bedrock

1 ___ More than 60 inches
2 ___ 40-60 inches

3 ___ 20-39 inches

4 ___ 10-19 inches

5 ___ Less than 10 inches

 

 

 

 

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COMPUTER PROGRAM "LAND USE"

 

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APPENDIX D

DATA FOR ROW 3,.COLUMN 3, AND SOIL DATA -

 

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APPENDIX D

DATA RETRIEVAL

The material included in this appendix illustrates the

i

type and form of data retrieval that is possible with this

In 1

computer program for any of the parcels of land evaluated;

and identifies all of the Soil mapping units, with their

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respective characteristics asllisted in Appendii B, that

 

were included in this study. - . ,
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"As an erample, the first row of values pn the following
page'is a print of the data suhmitted to the computer program
from the data work sheet (Appendix A) for the land parcel ‘
located in row 3 column 3, section 34. The soil mapping

4

unit occurring on this parcel is identified in the last two
columns as EYB 1. Each remaining row of values represehts
a different soil mapping unit and its reSpective set of
characteristics.. The soil characteristics for row 3 column
3 can be?determined‘by locating the row beginning with FYB‘
in the left Column and a l in the second column.: (The:

characteristics are identified consecutively in Appendix 8,)

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APPENDIX E

PSSI VALUES FOR FOUR LAND USES

 

 

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APPENDIX E

PSSI VALUES

Two sections of land (640 acres each) and 4 land uses
were evaluated in this study and the tables in this Appendix
represent the PSSI values calculated for a section and for
a specified land use. (The section location and land use

I.

are identified at the top of each table.)

 

Each section was divided into a 16 x 16 row-column grid
system making a total of 256 cells of 21 acres in size.. A
PSSI value was calculated for every cell in the system and
this value was printed in table form according to its:row-
column location. Lines were drawn around contiguous cells
having equal value to illustrate a method of associating

larger areas of similar suitability. The lines were placed

midway between the values to represent the cell boundaries.

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