Landscape Inventory and Analysis -...

CHAPTER 5

Landscape Inventory and Analysis

tendency to collect only that information requiredto address a specific problem. That information,because it is specialized, is often disconnectedfrom the larger concerns of the planning area andfails to satisfy more generic information needs.This results in a one-dimensional view of the land-scape that does not support the ecological premisethat everything is connected to everything else(Steiner, 1991). Yet, without providing a more systematic view of the landscape, “seeing” theconnections between the natural elements of thelandscape and gaining insight regarding their interaction is difficult to achieve. Furthermore, because environmental planning is based on anintegrated view of the landscape, synoptic-scaledata concerning the biophysical processes charac-terizing the region must be collected and analyzedto provide the baseline knowledge from whichplans can be developed (Steiner, 1991). With theseelements in place, the data gathered through inventory and monitoring activities helps to sub-stantiate environmental planning and improvesthe credibility of the environmental plan. Deriv-ing the information needed to reach this point,however, depends on the implementation andtiming of programs developed to inventory andmonitor the regional landscape.

An inventory, as its name suggests, is an item-ized listing of current assets. If we consider the geographic area of a watershed, it would be necessary to have information pertaining to thatarea’s geology, climate, land use, land cover, and

Information is a critical component of any decision-making process, and environmentalplanning is no exception to this rule. As demon-strated by Lein (1997), every decision-makingbody relies on information to exist, and the acqui-sition, processing, and dissemination of infor-mation are fundamental activities undertaken byplanning agencies. Information can be considereda form of planning intelligence, and planning in-telligence is a type of strategic decision support in-formation that enables the environmental plannerand the community to identify, understand, andmanage the problems characterizing the planningarea. This intelligence is derived from organizeddata and facts about the regional setting and thosefeatures that are of specific concern to planning. Inthis chapter the methods used to collect and orga-nize this information, and the evaluation proce-dures employed to provide the “intelligence”needed to direct the environmental planningprocess, are examined.

Regional landscape inventoryand monitoring

Inventory and monitoring are among the mostbasic tools that enable environmental planners to establish critical baseline information and measure change. Unfortunately, information per-taining to the natural environment has often beenused in an ad hoc manner (Steiner, 1991). There is a

Integrated Environmental PlanningJames K. Lein

Copyright © 2003 by Blackwell Publishing

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vegetation, as well as a range of other factors, sothat effect plans to manage the watershed can bedrafted. Thus, whether in the context of environ-mental planning or with reference to the local retail department store, the inventory represents abasic accounting of the presence or status of important and valuable resources whose presentdisposition is unknown. Through the inventoryprocess an understanding of these assets is ac-quired and their quality, quantity, condition, andlocation become known. As a preplanning mecha-nism, the inventory plays a vital role by providingthe detailed overview of the region necessary before specific programs or policies can be draft-ed. In this role, the inventory describes the salientenvironmental variables that characterize theplanning area, identifies their geographic extent,and carefully documents their important proper-ties. Once completed, the inventory forms a base-line information source against which plans andprograms can be evaluated, and provides a mech-anism whereby the opportunities and constraintsof the environment can be disclosed and recom-mendations can be offered to guide future devel-opment within the region.

For an inventory to be effective several organi-zation questions need to be addressed. Takingeach question in turn, they help to refine the meth-ods used to develop the inventory and ensure itsadequacy.

What to inventory?

Unlike our department store analogy with items arranged on stockroom shelves, the naturalresource inventory is complicated by the multidimensional nature of the environment. Therelevant factors to include in an inventory may be predetermined by local, state, or federal man-dates. In other instances selection of the naturalfactors to inventory may require careful delibera-tion by the planner. Selecting the appropriate factors to inventory depends largely on purpose.In the majority of cases an inventory is conductedto give decision-makers a comprehensive and detailed understanding of the physical andhuman characteristics of the planning area. Usingthis information-base, environmental data can be

employed directly in setting development optionsand priorities, identifying problems, and increas-ing general knowledge about the region that canbe used by decision-makers.

Typically the dominating or prominent fea-tures of the landscape are chosen and described ina manner such that a decision-maker unfamiliarwith the planning area can learn enough about itsimportant qualities to ensure that plan develop-ment and implementation remains focused. Natural Factors given consideration in a resourceinventory may include the follow items:

1 Habitats found within or adjacent to theplanning area.

2 Major cultural resources found within or adjacent to the planning area.

3 Major land uses and related land-use activi-ties found within or adjacent to the planningarea.

4 Major land and resource ownership patternsand management responsibilities.

5 Major historic, prehistoric, and archaeologi-cal resources.

A comprehensive outline of the natural, cultural,and amenity resources that can typically be exam-ined and subject to inventory are presented inTable 5.1. Describing each of the factors presentedin the table may involve the production of statisti-cal summaries, detailed maps documenting location and geographic arrangement, narrativesummaries reviewing and explaining importantfeatures or relationships, photographs and othersupporting graphic displays to enhance visualiza-tion of the planning area. Because the overridinggoal of the inventory is to present data and infor-mation to improve understanding, anything notrelated to improving communication and thetransfer of critical environmental knowledgeshould be avoided.

How to inventory

An inventory can be derived from a mix of prim-ary, secondary, and tertiary sources. Consequently,data collection and data evaluation become criti-cal phases in the inventory process. Perhaps themost important step in data collection involvesidentifying the boundaries that will delineate the

LANDSCAPE INVENTORY AND ANALYSIS 95

planning area and delimit the geographic extentof the biophysical and sociocultural factors thatwill be mapped and described. Although bound-aries may be set by legislative goals, there is a hierarchical quality to an inventory that directsdescription and mapping through different levelsof geographic scale and resolution. Generally, aninventory proceeds from a regional scale to a locallevel of detail. This hierarchical structure is usedto place the planning area into its larger environ-mental context and to enhance the decision-maker’s ability to see relationships that may existbetween the planning area and the larger regionallandscape. The drainage basin at the regional leveland the watershed (or sub-basin) at the local levelserves as the ideal natural delimiting feature forecological planning and analysis (Steiner, 1991;McHarg, 1969). Recall that a drainage basin isidentified by locating the drainage divides be-tween channels of a particular order through theuse of contour (elevation) data and runoff pat-terns. Since the drainage basin is delineated on thebasis of physiographic and hydrologic criteria, itcreates a practical reference for connecting naturaland cultural attributes that facilitates system representations. The drainage perimeter has also

been used to approximate ecosystem boundaries.By applying the drainage basin as the primary organizing spatial unit, data characterizing thenatural, cultural, and amenity resources pres-ented in Table 5.1 can be collected and mapped.

Cartographic treatment of inventory data is animportant method of communication, visualiza-tion, and analysis by which the quality of the inventory can be determined in large part by thequality and accuracy of the maps created for dis-play. Therefore, one of the more critical decisionsthat must be made early in the inventory processhas to do with the selection of a base map and scaleof representation. The base map will be used to anchor all the spatial information collected for the inventory. Factors that will influence the appropriateness of the base map include: (1) scale,(2) projection, (3) locational reference, and (4)medium.

1 Map scale – a map is a scaled representationof a portion of the earth’s surface. The scale of a map is simply the ratio between map distance and earth distance. However, scalegreatly influences the level of generalizationrequired in order to represent geographic ob-jects and directly controls the degree of detailthat can be seen on a map. It is therefore es-sential that an appropriate scale is selected tothat the representation of the surface can beas accurate as possible and the features andpatterns of natural factors shown withoutunnecessary abstraction or generalization.Although the increased use of digital geo-graphic information systems (GIS) has reduced some of the concerns regardingscale, every map product, whether stored ina machine environment or printed on paper,will posses a level of resolution (the smallestground area that will be treated as an objectthat can be represented on the map) as a func-tion of its scale that will direct how objectscan be represented and symbolized.

2 Projection – the characteristics of a particu-lar map are determined by the projection onwhich it is plotted. The retention of shape,equivalence, direction, or distance are im-portant considerations when deciding uponthe purpose of a map. Retaining one charac-

Table 5.1 Landscape factors subject to inventory.

Natural elementsPhysiography: slope, drainage, unique featuresGeology: bedrock formations, faults, fractures, slumps, slipsSoils: type, composition, permeability, erosion potentialHydrology: drainage systems, springs, seeps, wetlandsVegetation: plant associations, unique communitiesWildlife: habitatsClimate: temperature, precipitation, wind flow, humidity,

evaporation

Cultural elementsTransportation: roads, rail lines, airportsUtilities: oil, gas, water networksStructures & excavations: buildings, mines, dumpsOwnership: name, assessed valueHistorical/archaeological: significant features and sites

Visual and aesthetic elementsMajor viewshedsMinor viewshedsScenic areasUnique featuresPoints of interest

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teristic generally results in the distortion ofother potentially important characteristics.For mid-latitude regions, conic projectionssuch as the Lambert or Alber’s projection arecommonly used on base maps, althoughother options are possible.

3 Locational reference – Before maps can beprepared that actually portray the locationsof surface objects, a means of determining location must be selected. Locational sys-tems can include latitude and longitude aswell as more specific reference grids such asthe Universal Transverse Mercator (UTM)grid system, or the State Plane CoordinateSystem.

4 Medium – traditionally mapped data werecompiled and printed on paper or polyesterfilm. While maps placed on these media arestill very common and useful, the emergenceof digital cartography and GIS together withthe advent of the worldwide web (www),has introduced new source material for mapcompilation and display. Selection of mapmedia must be taken into consideration sincethis simple decision will influence the ease ofdata storage, stability, accessibility, perma-nence, and ease of update and error correc-tion. While inventory data may be collectedfrom a variety of sources including field surveys and sampling, data are likely to beassembled and compiled into a digital formfor computer storage and processing. Forthis reason, digital formats are preferred andprovide greater flexibility when compared totraditional map media.

With a base map selected, the inventory canproceed as an exercise in data collection, data compilation, and geographic description andmapping. Since the inventory explains the firsttechnical phase in the sequence on which planning depends, the compilation of inventoryelements is directed by the information content of each data item. To be useful, it is essential thatthe information presented in the inventory meetsthree fundamental requirements (Gonzalez-Alonso, 1995). First, it must be comprehensive and gaps in the information should be avoidedwherever possible. Secondly, the inventory must

be systematic so that it can be applied easily. Lastly, the inventory must be multidimensionaland give reasonable consideration to the totalityof the significant environment.

The key decisions affecting how an inventorymay be compiled relate to the choice of elementsand the appropriate level of detail that will effectively communicate their importance. Theimportant factors to consider when planning theinventory include: (1) the general characteristics ofthe planning area, (2) the objectives and socioeco-nomic implications of the inventory, (3) the size of the planning area, and (4) the availabilityand quality of data. With reference to informationcontent, processing, and purpose, a resource in-ventory can be targeted at three interrelated levels:

• A reconnaissance level appropriate for describing regional patterns or elementsthat characterize large-scale regional trends.

• A semi-detailed meso-scale level orientedtoward general planning questions withmore specific data needs.

• A detailed site-specific level required for localized analysis involving siting decisionsand the assessment of environmental impact.

Although exhaustive collection of informationmay not be required in all cases, concentrating onthose elements that supply information that de-fine the planning area makes it possible to map elements into homogeneous regions, and defineelements in a clear and simple manner (Gonzalez-Alonso, 1995).

Documenting the inventory

The data selected and collected in the inventorymust be assembled into a format that will give decision-makers a clear indication of the land-scape’s significance and outline the main implica-tions that should direct future use. Therefore, theinventory and the recommendations that growfrom it provide a basis for subsequent analysisand for raising questions concerning specific fea-tures of the landscape, such as:

• its susceptibility to modification• its stability• its aesthetic qualities


• its conservation value• its opportunities and constraints.

Based on these points, it can be seen that an inven-tory represents more than simply an exercise indata collection. It provides an initial assessment ofsite characteristics that allows the potential of anarea to be critically examined. Therefore, to be useful, a detailed evaluation of each factor to-gether with a series of planning recommendationsshould accompany the discussion. This form ofcursory evaluation identifies the issues, concerns,possibilities, and limitations that are associatedwith each natural factor, and allows options to beentertained without specific goals or objectives inmind that might otherwise limit thinking.

With respect to documentation, the ultimategoal of an inventory is to produce an organizedand concise review of the pertinent material thatclearly describes the planning area in both a narra-tive and graphic form. An inventory is typicallydivided into five major sections beginning with an introduction and proceeding systematicallythrough each thematic factor. A generic outlinepresenting the basic structure and contents of anatural resource inventory is given in Table 5.2.Each section in this document has a specific pur-pose and establishes the background needed toproceed to the sections that follow. The logic be-hind this design is simple. Beginning with the introduction, an overview of the planning area isoffered and the purpose and scope of the inven-tory is explained. Information presented in the introduction establishes the site and situationalcontext of the planning area and helps communi-cate a sense of place. With the general charac-teristics of the regional setting described, thedecision-maker has a reconnaissance-level per-spective of the planning area. Moving from thisgeneral overview, the section that follows can in-troduce the human and cultural factors that definethe area, along with a brief historical treatment ofthe region to document its origins and suggest itsevolution. In this section emphasis is also given toaesthetic qualities and known management prob-lems that exist within the planning area. The prob-lems identified in this section can include a rangeof social, economic, and environmental issues thatshould be recognized as the information in the

inventory is interpreted. Using this discussion as a backdrop, this section of the inventory mayconclude with a review of general planning recommendations that have been derived fromthe analysis of data inventoried. Although a moredetailed treatment of these recommendations willfollow later in the document, a general summaryis presented here to help frame the material that isintroduced in the sections to follow.

The next major section of the inventory can beconsidered to form the heart of the document. Inthis section the detailed information pertaining tothe natural site conditions selected for examina-tion are presented. While the sequence or ordermay vary, generally a “ground-up” approach isused. This approach allows the environmentalfactors that define the planning area to unfold in amanner that facilitates an understanding of factorinteractions and interrelationships.

The final substantive section of the inventorycontains recommendations regarding the presentstate and the potential concerns surrounding eachfactor. This section is critical to the success of theinventory, particularly if it is to have value as abasis for goal-setting and plan-making. Recom-

Table 5.2 General resource inventory contents.

I. Introductiona) site descriptionb) purpose of inventoryc) table of contents

II. History of Site and General Informationa) land ownership patternsb) existing land usec) aesthetic qualities and special featuresd) general planning recommendations

III. Natural Site Conditionsa) geologyb) vegetationc) soilsd) hydrologye) climatef) wildlife habitat

IV. Summary of Planning Recommendationsa) review of planning considerationsb) recommended usesc) development constraintsd) other limitations

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mendations address the particular types of use,pattern of development, design concerns, and locational constraints that where identified dur-ing the inventory and analysis process. The con-cept of a constraint is particularly important tothis purpose. Constraints can explain environ-mental limitations evident with respect to a givenfactor, from expansive soils, flood risk, slope insta-bility, and sensitive habitats, to historic sites, cul-tural amenities, and areas of scenic value. Eachconstraint is documented and the overall devel-opmental suitability of the planning area for fu-ture use is described in relation to how each factorimparts its influence. Although recommendationsare merely suggestions, they often identify impor-tant alternatives that can be better accommodatedby the site given its biophysical and socioeconom-ic characteristics. Moving the inventory into amore coherent expression of opportunity or con-straint directs our attention to the methods of landevaluation and analysis.

Land evaluation and analysis

A large tract of land is being considered for some form of use. The question is what use is bestsuited for that area. This is the general questionthat guides the land evaluation process and the methods that have been developed to assess the “fitness” of land for development. However,numerous environmental factors influence the development process and require careful evalua-tion. From topography, surface drainage, climate,and soil, to the incidence of natural hazard, anddisease, a range of environmental characteristicsaffect the current as well as the future state of thelandscape system and impart some direct influ-ence on the land use placed at a given location.Consequently, there are considerable benefits tobe realized from a simultaneous assessment of thelandscape factors critical to the sustainable use ofthe planning area. The regional landscape inven-tory is the first phase in this more comprehensiveprocess of landscape evaluation.

Drawing from the fundamental principles that(1) land should be used for the purposes for whichit is best suited and that (2) land of high value for

an existing use should be protected againstchanges that are difficult to reserve, the natural environmental factors that define the regionallandscape are subjected to six interpretativestages that when completed yield an expression ofthe optimum configuration of land use within theplanning area (McRae & Burnham, 1981). Thestages defining this evaluative process are illus-trated in Fig. 5.1. By definition land evaluation isthe process of estimating the potential of land foralternative uses (Dent & Young, 1981). Throughthis evaluation process a comparison is made be-tween the requirements of specific types of useand the resources offered by the environment tosupport them. Fundamental to the evaluation pro-cedure is the widely understood fact that differingland uses will define differing requirements. Sincenearly all human activities use land to some de-gree, the opportunities and limitations of this in-creasingly scarce resource must be translated intoa form that can aid decision-making (McRae &

Technicaland

socialfactors

Politicaland

economicfactors

Optimumland use

Landvalue

Landcapability

Landsuitability

Natural environmentalfactors

Landcharacteristics

Landqualities

Fig. 5.1 The general method of land evaluation.


Burnham, 1981). Land evaluation is the methodol-ogy designed to achieve this objective.

As a general methodology, land evaluation canbe conducted directly by trial and error, or indi-rectly through the application of an analytical approach that attempts to explain or predict landperformance under specific categories of use. Thelogic that makes land evaluation possible relatesto the fact that land varies in its physical andhuman-geographic properties. Therefore, this inherent variation should affect land use, sug-gesting that given a proposed use, some land areasare more appropriate in physical and/or econom-ic terms. This observable variation is in part sys-tematic with definite and knowable causes.Because causal influences can be known, the vari-ation, whether expressed in physical, political,economic, or social terms, can be mapped. Fur-thermore, the behavior of the land when subjectedto a given use can be predicted with some degreeof certainty, depending on the quality of data andthe depth of knowledge relating land to land use.Hence land suitability for various actual and pro-posed uses can be systematically described so thatdecision-makers can apply these predictions toguide their decisions.

Providing this specialized information is thefunction of land evaluation and information be-comes a key ingredient in this process. Typicallythree sources of information are required: (1) land,(2) land use, and (3) economics. Land data is obtained directly from the natural resource inventory. Information regarding the ecologicaland technical requirements of various land-usetypes is acquired from the subject areas that havedeveloped applied and theoretical knowledge re-lated to each category. Economic data may not benecessary if the results of an evaluation are neededto address purely physical issues; then only gener-al economic and social patterns are required.However, if the results are required in strict eco-nomic terms, then data on specific costs and pricesis needed (Dent & Young, 1981). These data needscoupled with the observation that direct evalua-tion methods tend to be of limited value unlesslarge amounts of data can be collected, supportthe use of indirect evaluation techniques (McRae& Burnham, 1981).

As an analytic tool, a land evaluation may bepresented in terms that are qualitative, quantita-tive, physical, or economic (Dent & Young, 1981).A qualitative evaluation is one in which the suitability of land for alternative purposes is expressed in qualitative terms only. For example,observation of land areas based on soil, slope, anddistance criteria may suggest that a given landarea, because of its soil type, steepness of slope,and distance from major roads, may be of mar-ginal value for a particular type of crop produc-tion. Therefore, the use of terms such as highly,moderate, or marginally suitable or not suitablewhen considering a specific type of use implyqualitative judgments have been made to placeland into one of these categories. Typically, quali-tative evaluations are employed mainly at a recon-naissance scale, or as a preliminary to moredetailed investigations. While the results of thistype of land evaluation may be highly general-ized, it permits the integration of many environ-mental, social, and economic factors.

Quantitative physical evaluations provide numerical estimates of the benefits to be expectedfrom the use of land. Quantitative evaluation is most frequently carried out as the basis for economic evaluation, where results are expressedin terms of profit and loss. Here, monetary valuesare applied to data from quantitative measures toobtain cost expressions and to derive profit andloss treatments of inputs and outputs. However,Dent and Young (1981) note that an economicevaluation is not strictly confined to profit and lossconsiderations. Other consequences such as theenvironmental or social can be included and combined with economic data as a basis for decision-making.

Regardless of the type of evaluation con-ducted, the goal of evaluation is to predict changeand to provide better insight concerning the con-sequences of a development plan. Thus, as a plan-ning tool, land evaluation becomes a necessitywherever changing the landscape is contem-plated (Dent & Young, 1981). Prediction, in thiscontext, directs attention to the concept of suitabil-ity. Generally, all land evaluation procedures attempt to express this idea and relate it eitherqualitatively or quantitatively to alternative types

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of land uses. Therefore, given different forms ofuse, with varying environmental opportunitiesand constraints, land evaluation methods strive toproduce an expression of suitability that can beused to direct how land should be utilized. Usingthis expression, a comparison is made betweenthe requirements of the contemplated land use(s)and the qualities of the land that are present tosupport it. The suitability of land can be assessedand expressed in several ways. Three of the morecommon include: (1) capability, (2) suitability, and(3) value. A variety of analytic techniques havebeen introduced to perform regional landscapeanalysis and land evaluation that apply theseterms as a control which directs the future use ofland resources (McAllister, 1986; Anderson, 1980;Steiner et al., 1994; Davidson, 1992).

Methods of landscapeassessment

Techniques for regional landscape evaluation andanalysis are general tools that assist with the taskof assembling a large number of important land-scape variables into an expression that can be usedto direct decision-making. Through integration,data from diverse sources can be interpreted, eval-uated, and communicated in a manner that guidesthe process of choosing among alternatives andidentifying optimal patterns that maximize bene-fits and reduce or avoid costs. More importantly,these techniques complement the method of regional landscape analysis applied in environ-mental planning. This method, derived from theprocedures outlined previously by McHarg (1969)and Steinitz (1977), define a combination of proce-dures which form a model that describes the general process. The four main phases of thismodel are as follows:

1 Inventory – describing the compilation ofdata on natural environmental conditions toserve as critical baseline information onwhich further analysis may draw.

2 Data interpretation – explaining the process of categorizing inventory data to define patterns and trends.

3 Data synthesis – defines the combination of

data through the use of specific analytic tech-niques and models to derive expressions ofsuitability or constraint.

4 Plan formulation – explaining the integrationof land evaluation and ecological assessmentresults into the policy-making process.

Connecting data to the plan is accomplishedthrough the application of one or more evaluative(analytic) techniques. With each technique adopted, certain assumptions or conventions areassumed that influence how well a given methodcan be applied and its results interpreted (McAllister, 1986). When one is conducting an assessment of a plan or design, assessment typically implies that a comparison is being made between two states, one of which is the con-dition that will result from implementing the plan.The effect of the proposal can be examined bycomparing:

1 The original state existing before the actionwas taken, referred to as the baseline state.

2 The state that would have evolved in the absence of the action.

3 Agoal or target state.4 The ideal state.

The appropriateness or suitability of a proposal,therefore, relates to how well the various statescompare. Thus, given baseline conditions, oneasks how closely the goal state, ideal state, and the“non-action” state agree.

Not all assessment methods provide the samelevel of comparison. Generally, differences amongmethods are revealed by the way they addressconcerns related to the categorical descriptionsused to estimate and report natural factors and ef-fects, the manner by which magnitude and signifi-cance of change is estimated, and the proceduresused to derive ratings intended to indicate the rel-ative importance of each factor. With reference tothe description of factors included in the selectedmethodology, the fundamental rule for selectingcategories is that they must be mutually exclusiveand exhaustive. Concerning the question of magnitude and significance, mathematical or statistical procedures are considered to be themost reliable means of estimation. However, inboth cases, assessment relies heavily on the use ofexpert judgment. This is particularly the case in


situations where: (1) scientifically valid proce-dures are lacking, (2) data needed to implement aprocedure does not exist, or (3) where cost factorsprohibit the use of certain procedures. The ques-tion of measurement can be addressed in a num-ber of ways. First, the notion of rating implies eithera subjective or quantitative ordering of a variable.Therefore, one distinction considers the source ofthe rating. Ratings can be derived from a variety of sources: measurable physical characteristics,monetary values, or expert judgment (McAllister,1986). Finally, rating type describes the general ap-proach that was used to scale qualities, quantities,or effects. Four scaling methods frequently ap-plied in environmental assessment include (1)simple, (2) constant, (3) scaled value weight, and(4) rescaled weight. The general characteristics ofthese rating schemes are summarized in Table 5.3.A more detailed discussion of these approachescan be found the McAllister (1986).

Recognizing the distinctions that exist amongvarious assessment techniques available helps theplanner identify the approach that will producethe most meaningful results. In general an assess-ment technique should be:

• Systematic – any technique must be system-atic to ensure that the results it provides arereplicable.

• Simple – the techniques selected should notbe overly complex.

• Quick – the techniques must be able to generate useful results within a reasonablelength of time.

• Inexpensive – the techniques should not impose unnecessary costs.

• Legally acceptable – the techniques shouldconform to the various legal and administra-tive requirements to which it is subject.

• Comprehensive – the techniques should becapable of incorporating all of the relevantfactors important to the decision-maker.

While strict adherence to these points may not bepossible in all situations, they focus attention onthe practical aspects of the analysis problem andoffer some insight to help evaluate whether a certain technique is feasible or not. The methodsavailable to the environmental planner fall withinfour broad categories: (1) methods of land capabil-

ity analysis, (2) methods of developmental suit-ability analysis, (3) methods of carrying capacityanalysis, and (4) methods of land evaluation and site assessment. Each of these techniques is reviewed below.

Land capability analysis

Land capability analysis is a technique designedto classify land units based on their ability to sup-port general categories of use. The term capabilityhas specific meaning in this context. When used inreference to land, capability implies that a givenarea, due to its inherent characteristics, may bequalified for a specific type of use (i.e. agriculture,open space, urban). Determining the qualifica-tions land must possess to be considered appro-priate relies on relating the land area to a set ofenvironmental factors that influence how well agiven land use will perform. The environmentalfactors typically employed in capability analysisinclude soil erosion potential, susceptibility toflooding, climate, and slope stability, togetherwith other factors that stand to degrade the utilityand productivity of land. The analysis of land capability, therefore, requires an evaluation of thedegree of limitation posed by permanent or semi-permanent attributes of land to one or more landuses (Davidson, 1992). The logic guiding analysisis comparatively simple. Capability is based on

Table 5.3 Characteristics of land rating schemes.

Scaling method Characteristics

Simple rating method A set of guidelines or standardized procedures are followed in assigning judgmental importance scores

Constant value weight Rating applied to each unit of a given type of impact

Scaled value weight Derived from a mathematical function, they are used to avoid possible inaccuracies of constant weights

Rescaled impact weight Scaled weights adjusted by expert judgment; used to overcome factor dependencies problems

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the premise that as the degree of constraint increases, land should be allocated to lower cate-gories or less intensive forms of use. Although this technique was originally developed to assistwith agricultural planning and designed to helpidentify agricultural land uses that would not con-tribute to environmental degradation, the conceptof capability is flexible enough to permit broaderinterpretations.

There are two principal ways whereby land capability can be assessed. One example isthrough the use of categorical systems. Categori-cal systems are implemented by testing the valuesof appropriate soil and site properties against cri-teria for a set of land-use categories. Site condi-tions are compared against these evaluativecriteria and if the minimum criteria are not met,then the land area in question automatically fallsto the next class and the process repeats until amatch is identified. Land characteristics are thentested against less stringent criteria as the evalua-tion process continues through the classificationsystem until a category is identified where all thecriteria are satisfied. A second means of derivingan estimate of land capability is through the use ofparametric systems. Parametric systems applymathematical formulas to combine site propertiesinto a quantitative expression. Although paramet-ric systems differ in respect to the factors that areincluded for mathematical manipulation, threegeneral approaches are common:

1 Additive systems of the form P =A +B +C2 Multiplicative systems of the form P = A ¥ B

¥C3 Complex systems of the form P = A (B + C)¥D.

In each of the examples listed above, P is the para-metric rating or score and A, B, C, and D representsoil and site properties. The basic features of cate-gorical and parametric approaches are examinedbelow.

Capability classification

A variety of land capability classification tech-niques have been introduced (Davidson, 1992).Perhaps the best known of these is the USDAmethod formalized by Klingebiel and Mont-

gomery (1961). The USDA method employs athree-tier structure in its classification system:

• Tier 1, Capability Class – the top level in theclassification with a total of eight classes de-fined and labeled I to VIII inclusive, indicat-ing the degree of limitation in descendingorder of severity.

• Tier 2, Capability Subclass – indicating thetype of limitation encountered within theclass, these subclass designations identifylimitations such as erosion hazard, climate,fertility, or excess water that restrict the useof land. The limitations recognized at thesubclass level are:Subclass e (erosion), defining soils wheresusceptibility to erosion is the dominant limitation.Subclass w (excess water), explaining conditions of poor soil drainage, wetness,high water table, and overflow as the domi-nant limitation.Subclass s (soil), describing soils that havelimitations associated with shallowness,low moisture-holding capacity, or salinity.Subclass c (climate), identifying land whereclimatic conditions limit land use.

• Tier 3, Capability Unit – a subdivision of thesubclass where the variation in degree ortype of limitation is similar across soil type.Thus within the same narrow range of envi-ronmental conditions, capability units de-fine land areas that share a similar responseto management and improvement practices.

Soil and climate limitations in relation to theuse and management of soils are the basis for dif-ferentiating capability classes. Assigning landareas to capability units, capability subclasses,and capability classes is conducted on an evalua-tion of 8 environmental factors. These are summa-rized in Table 5.4. The assignment process itself is based on a series of assumptions that have been discussed in detail by Klingebiel and Montgomery (1961). When carefully applied to a well-defined problem, land areas falling withinone of the eight classes can be described andmapped accordingly (Davidson, 1992):

• Class I: soils with few limitations that restricttheir use.


• Class II: soils with some limitations that reduce capability.

• Class III: soils with some severe limitationsthat require special management.

• Class IV: soils with very severe limitationsthat restrict certain activities and requirespecial management.

• Class V: soils with little or no erosion hazardbut with other limitations that restrict exten-sive activities.

• Class VI: soils with very severe limitationsand that are unsuitable for cultivation andrestrict use to pasture and range.

• Class VII: soils with very severe limitationsthat make them unsuited to cultivation andrestrict use to woodland or wildlife.

• Class VIII: soils and landforms with limita-tions that preclude their commercial viabili-ty and restrict use to recreation, aesthetic, orwatershed purposes.

Implementing the USDA method is largelysubjective since the criteria for establishing classlimits are not generally specified. Therefore, thetechnique can be considered a formal representa-tion of expert-technical judgment. Although theresults can be useful, the advantages and disad-vantages associated with land capability classifi-cation must be well understood in order to guideits appropriate application. The strengths andlimitations of the USDA method have been examined by McRae and Burnham (1981) and aresummarized in Table 5.5. Problems related to

imprecision and subjectivity must be balanced,however, by the flexibility such categorical sys-tems offer. Flexibility of use has contributed to thedesign of similar measurement frameworks inCanada, Great Britain, and the Netherlands, eachmodeled after the USDA approach (Davidson,1992).

Parametric methods

Dividing land into a small number of categoriesthat are mutually exclusive and supposedly ex-haustive imposes an artificial structure that doesnot correspond well with the variability inher-ent to complex environmental interactions. By relaxing the need for discrete classification and replacing nominal categorization of land withcontinuous scale assessment, more realistic re-sults can be obtained (McRae & Burnham, 1981).Applying parametric techniques in a land capabil-ity analysis involves:

1 Establishing a land unit to assess.2 Obtaining the required data.3 Developing the appropriate measurements

for that data.4 Translating the raw measured data into a

coding or rating scale.

Table 5.4 Criteria used for placing soils into capability classes.

1. Ability of the soil to give plant response to use andmanagement based on organic matter content, ease ofmaintaining nutrients, percentage base saturation,cation-exchange capacity, parent material, water holdingcapacity

2. Texture and structure of the soil to the depth thatinfluences the environment of roots and the movement ofair and water

3. Susceptibility to erosion4. Soil permeability5. Depth of soil material to layers inhibiting root penetration6. Alkalinity7. Physical obstacles8. Climate

Table 5.5 Advantages and disadvantages of the USDAsystem.

Advantages:• Division into small number of ranked categories is easily

understood• Qualitative and suggests realistic approach given

knowledge limitations• Versatility• Easily applied• A general-purpose classification system• Stresses adverse effects of poor management• Useful way of relating environmental information• Results easily displayed on maps

Disadvantages:• Subjective• Interactions between limiting factors difficult to express• Division into too few categories overgeneralizes

conditions• Implied ranking suggests true land value• Fails to include socioeconomic factors• Emphasizes limitations rather than land’s positive potential• Difficult to use where reliable soil information is lacking

104 CHAPTER 5

5 Performing the desired mathematical com-bination of measured properties.

6 Applying the resulting scores to the entireplanning area.

A selection of additive, multiplicative andcomplex schemes has been reviewed in detail byMcRae and Burnham (1981). Perhaps the mostwidely known parametric method is the StorieIndex Rating System (Storie, 1978). This multi-plicative system computes a land-quality ratingindex based on the general relation

(5.1)

Where:A = character of the soil profileB = texture of surface soilC = slopeD=miscellaneous factors (i.e. drainage,

alkalinity).Ratings for each factor are provided and ex-pressed as percentage scores in Storie (1978). Anexample of the scores applied in a hypotheticalcalculation are shown in Table 5.6.

As with the categorical approach, parametricsystems possess important advantages and disad-vantages that should be understood before thesemethods are applied. The main advantages ofthese systems when compared to categoricalmethods include:

SIR A B C D= × × ×

• reduced subjectivity• ease of adaptation• attractive simplicity• amenability to computer manipulation.

The main limitations are related to concerns surrounding

• misleading impressions of accuracy• calibration difficulties• parameter inconsistencies.

An alternative means of evaluating land shifts thefocus from capability to the concept of develop-mental suitability.

Developmental suitabilityanalysis

Developmental suitability may be defined as the“fitness” of a given tract of land for a well-defineduse (Steiner, 1983). When compared to the conceptof capability, suitability explains the conditionwhere a singular use is described that is the mostappropriate use for a site in the landscape. There-fore, while capability narrows the search for alternative land uses that may be “qualified,” suitability refines this search further to identifythe single use that fits with the environmental con-ditions present at a given location. To illustratethis important terminological distinction, con-sider the example of a county that is exploring options for currently undeveloped land areas. The county wishes to identify what uses might beappropriate and seeks workable alternatives.Through the application of land capability analy-sis, broad categories of general land use are iden-tified that suggest where land may be qualified to support urban, agricultural, and recreationaluses. Within each of these categories, develop-mental suitability analysis is performed to deter-mine which specific types of urban, recreational,and agricultural uses are the most appropriate.Thus within the general land-use category ofurban, suitability analysis can suggest whichareas may best support residential, commercial, or industrial forms of development.

Variations in the degree of suitability are deter-mined by the relationship, actual or anticipated,between benefits and the required inputs associ-

Table 5.6 Calculation of the Storie Index Rating System.

Index parameters:Factor A – Rating based on characteristics of physical profileFactor B – Rating based on surface textureFactor C – Rating based on slopeFactor X – Rating based on other site conditions

Index calibration: Percent:Soil type X – brown upland soil with

shale parent material and depth Factor A = 70.0to bedrock at 90cm

clay loam texture Factor B = 85.0

rolling topography Factor C = 90.0

moderate sheet erosion Factor X = 70.0

Index rating:SIR = 0.70 ¥ 0.85 ¥ 0.90 ¥ 0.70 = 0.37 or 37%

Source: Adapted from McRae and Burnham (1981).


ated with the use in question for the tract of landunder consideration (Brinkman & Smyth, 1973).Focused on the concept of suitability, effectiveanalysis depends on the techniques that make systematic use of environmental information and relate the condition of the environment to theactivity it is proposed to accommodate (Ortolano,1986). In this context, suitability analysis can belooked upon as a filter, where land-use require-ments are passed through an environmentalscreen. Land uses passing through this screen canbe considered the most suitable for the site underconsideration (Fig. 5.2).

Identifying the potential opportunities or con-straints of a site requires selection of those land-scape attributes that would support or influencethe functioning and sustainability of the activityunder consideration. Avariety of techniques havebeen proposed to perform a suitability assessment(Hopkins, 1977; Fabos, and Caswell, 1977). Tradi-tionally, selected landscape attributes are depict-

ed in map form and combined cartographically sothat when viewed collectively they provide in-sight into the type of use intrinsically suited to thatlocation. This generalized procedure for conduct-ing a developmental suitability analysis has beendescribed by Lein (1990). In nearly all cases, ob-taining an expression of suitability becomes afunction of the analyst’s associative logic when re-lating landscape qualities as indicators of con-straint to a specific developmental design. Asnoted by Lein (1990), this method of analysis con-tributes to the common practice of compiling a se-ries of data maps each representing a selectedenvironmental theme or variable, interpreting acombined pattern, and drawing conclusions fromtheir composite profile. However, the practicallimitations of complex manual overlaying opera-tions, coupled with the inability to consistentlyconfirm the results obtained through visual in-spection of superimposed map surfaces, gaveway to alternative procedures (Hopkins, 1977;Steiner, 1983; Bailey, 1988).

At present, 7 general approaches to develop-mental suitability analysis have been introduced(Table 5.7). With some variations, an algorithm istypically applied to a set of environmental vari-ables and produces an expression of suitabilitythrough either direct or implied mathematical op-erations. The environmental variables selected forinclusion in the suitability algorithm are assignedsome type of value, rating, score, or weight. Usingthese numerical approximations of fitness, devel-opmental suitability is derived as a function ofcross-factor addition or multiplication of thesenumerical expressions as dictated by the respec-tive algorithm. The cross-factor results are then assembled into an arbitrarily derived classifica-tion scheme to allow a portrait of developmentalsuitability to take form (Lein, 1990).

Several algorithms are available to assist withthe analysis of developmental suitability, andmost have been extended to take advantage of themap-data processing capabilities of a geographicinformation system. Six common methods havebeen reviewed extensively in the environmentalplanning literature: (1) the Gestalt method, (2) themethod or ordinal combination, (3) the linearcombination method, (4) the nonlinear combina-

Landscape attributes

Suitability analysis model

Recommended land usesFig. 5.2 The suitability analysis “filter.”

106 CHAPTER 5

tion method, (5) the Rules of Combinationmethod, and (6) statistical grouping techniques(Hopkins, 1977; Anderson, 1980; Lein, 1990).While the intent of each technique is to provide anobjective measure of suitability, each of the proce-dures introduced tends to be based on a commonset of assumptions. First is the assumption thatlandscape factors are independent. This impliesthat environmental parameters do not share func-tional relationships. We know, however, that land-scape variables are greatly interdependent. Nextis the assumption that mathematical propertieshold when assigned values are compared acrossfactor levels. Here, the implication is that addingor multiplying variables creates mathematicallyvalid results. We understand, however, that three

times soil does not equal slope. Another importantassumption is that rating or scoring schemes canbe applied uniformly across factor levels. Finally,it is generally assumed that subjectively derivedweights are flexible given changing environmen-tal conditions.

These assumptions, however, lack absolute va-lidity. This fact tends to frustrate the “scientific” as-pects of suitability assessment and implies that themajority of combinatorial techniques are invalidwhen viewed critically or insufficient if used as thesole means for expressing developmental con-straint. Of course, if these or similar techniques areinvalid or flawed, then why are they used in prac-tice? There are several responses to this question.First, it is important to recognize that environmen-tal planning is as much an art as it is a science.Therefore, while we may strive to develop analytictools that embrace the rigor and objectivity of purescience, our reality is a blend of imprecise conceptscoupled with environmental relations that defyexact quantification (Lein, 1993b). Consequently,techniques that perform composite landscape as-sessments should not be looked upon as a calculusof certainty, but rather as simplifying tools that re-duce the complexity of the planning problem to amore manageable set of conditions. By keepingthis point in mind, the planner may apply thesetechniques and use technical judgment effectivelywithin its proper context. Suitability analysis,though conducted using addition, multiplication,or some other logical operation on a set of environ-mental conditions, is not an exercise in mathemat-ics. Instead it characterizes an algebra involvingsymbol manipulation whose logic must be clearand explicit to ensure that its results are interpret-ed correctly. For this reason, developmental suit-ability analysis represents an expert judgmentmethod of evaluation (McAllister, 1986). As an ex-ercise in the guided use of expert judgment, thegeneral methods used to express suitability andform a geographic pattern of landscape opportu-nity and constraint can be examined.

Gestalt methods

The Gestalt concept when applied to develop-ment suitability analysis requires consideration of

Table 5.7 General methods for developmental suitability analysis.

Method Description

Gestalt method Determination of suitability classesthrough field observation, airphoto interpretation, ortopographic maps withoutconsideration of individualenvironmental factors

Ordinal combination Mapping the distribution of landtypes, subjectively rating theirsuitability, then physicallyoverlaying each map to describe a composite suitability profile

Linear combination Rating and weightingenvironmental factors, thenapplying an algorithm to produce a mathematical expression of“fitness”

Nonlinear combination Use of a nonlinear function tocombine ratings into a suitabilityscore

Factor combination Modification of the Gestalt methodto accommodate interdependenceamong factors

Clustering Application of statistical clusteringalgorithms to find natural groupingamong environmental variables

Logical combination The use of rule and heuristics toassign suitability scores toenvironmental factors


the landscape as a whole rather than as an assem-blage of elements. Homogeneous regions are de-termined through observation using data sourcesthat characterize the landscape in its entirety, suchas aerial photographs, topographic maps, or fieldobservations. From these sources, an expressionof suitability forms from a three-step process:

1 The study area is partitioned by implicitjudgment into homogeneous land unitsbased on the interpretation of landscape patterns.

2 A table is created that verbally explains theeffects or constraints that will occur in each ofthe regions should the potential land use belocated there. Each land unit is then evalua-ted and a relative score or grade is assigned.

3 A set of maps, one for each land use, is pro-duced to show these regions in terms of theirsuitability. Value judgment is implicit andcan be expressed graphically for each landunit delineated on the map.

The Gestalt technique yields valid or invalid ana-lytic results depending on the skills of the analystand the circumstances surrounding the project.Several problematic issues concerning this ap-proach to suitability assessment have been noted.First is the realization that the process is based onimplicit judgment rather than explicit rules. As aconsequence, the results can be difficult to evalu-ate since the methodology is not well docu-mented. Therefore, the procedure relies on one’smental ability to assimilate many interactive factors, which creates results that can be difficultto communicate to decision-makers.

Combinatorial methods

Generating an expression of suitability usingcombinatorial methods describes the general pro-cedure of applying a mathematical operation di-rectly or implicitly on a set of factor maps thatdepict important landscape qualities. Three prin-cipal methods dominate this approach: (1) ordinalcombination, (2) linear combination, and (3) non-linear combination.

Ordinal combination – The ordination combi-nation method explains a three-step procedurethat creates a composite map detailing the devel-

opmental suitability of the planning region. Theprocedure begins by mapping a set of selected environmental variables according to specific categorical representations (i.e. soil types, slopeclasses, vegetation types). These mapped charac-teristics reflect distinct dimensions along whichvariations between land parcels can be described.Types mapped for each factor define nominal labels used to place variables along a measure-ment dimension. For example, land use might betyped according to well-recognized categoriessuch as residential or industrial, while slope maybe typed as low, moderate, high. The next step inthe process requires creating a cross-tabulationtable comparing factors to proposed or potentialland uses. The elements of this simple two-dimensional matrix are filled by entries definingthe relative suitability rating for each land use ofeach type across all the factors. The ratings explainan ordinal scaling of all the characteristics of thetype. For instance soil type might include consid-eration of its permeability, depth to water table,organic content, and pH, together with the com-parative “costs” of the land use it placed on thetype. These ratings, expressed according to an or-dinal measurement scale, can be derived from anumber of sources such as maps, reports, or expertjudgment. From here, a series of factor maps canbe produced showing the suitability of the land-scape for each land use under review. The finalstep in this process consists of physically overlay-ing the suitability maps of each individual factorfor each land use to create a composite characteri-zation of suitability over the region. If the numberof factors is few, the visual interpretation of thecomposite map is relatively straightforward.However, as the number of factors increases, theassociative logic needed to draw effective inter-pretations and recognize patterns in the data canconfound meaningful interpretations. The great-est limitation of this approach, however, sur-rounds the implied addition of ordinal scalenumbers and the assumed independence of fac-tors. These flaws notwithstanding, the need to express suitability as a composite quality or scorethat will evidence spatial variation and can be dis-played geographically over the planning region isclearly demonstrated by this approach.

108 CHAPTER 5

Linear combination – The logical flaws inher-ent in the ordinal combination method are avoid-ed when the types with each factor are rated onseparate interval scales. The ratings for each typeproduced in this manner are typically multipliedby a weight to reflect the relative importance ofthat factor. The new “weighted” rating for a givenarea is then added to produce a suitability score.According to this approach, suitability becomesthe product of the linear combination of factors.As demonstrated by Hopkins (1977), multiplica-tion by weights can also be used to change the unitof measure of the ratings by the ratio of the multi-plier, so that all ratings fall along the same intervalscale.

Perhaps the most critical aspect of the linearcombination method considers the proceduresused to rate factors. Although there are no formalrules to guide the process, a logic is assumed thataims to produce a rating that can be interpretedmeaningfully. Several schemes for deriving rat-ings are described by Largo (2001) and Hopkins(1977). Afamiliar rating scheme follows the analo-gy of assigning grades to a set of examinations.The first step in this process requires establishing a total possible suitability score. This value is di-vided among various factors and each assumes a given proportion of the total. Each type (class) of each factor is then rated as to its suitability in relation to the proportion of the total score assigned to the factor. Although the linear combi-nation method corrects the measurement prob-lems associated with ordinal approaches, theproblem of factor independence remains. Linearcombination methods are unable to address thesituation where the relative suitability for a spe-cific land use of a type on one factor depends onthe type on any of the other factors. Despite thisdrawback, applying the linear combinationmethod can be justified on the grounds that:

• Factors might be known a priori to be independent.

• The method is cost effective and easy to implement.

• Factors typically used in the model can be deductively determined to be independent.

Grouping techniques

An alternative strategy to suitability classificationthat avoids issues surrounding factor indepen-dence and mathematical invalidity involves theuse of the methods that define homogeneous regions explicitly. These techniques apply multi-variate statistical procedures to group or clusterland units into regions based on measures of similarity (Betters & Rubingh, 1978; Omi et al.,1979; Cifuentes et al., 1995). Three multivariatetechniques have been shown to be particularlyuseful: (1) cluster analysis, (2) discriminant analy-sis, and (3) factor analysis/principal componentsanalysis. When compared to judgment-basedmethods of suitability analysis, multivariate techniques provide a rational framework for analyzing the similarity of units that vary with re-spect to numerous environmental conditions. Inaddition, these techniques rely on a numericaltreatment of data that implies direct measure-ment across several dimensions. This type of ap-proach lends itself to more robust ordination andproduces results that can be easily represented in map form.

As a procedure for determining developmen-tal suitability, multivariate methods require cer-tain information to guide the interpretation ofresults:

1 Criteria to assess suitability – given a set ofpossible uses, the criteria needed to ade-quately express suitability must be specified.These criteria may involve selected environ-mental characteristics as well as other factorsconsidered relevant to the problem.

2 Criteria to determine importance – the crite-ria developed to assess suitability will varyin importance depending on the land useunder consideration. These contrasts andvariations in importance should be exam-ined across all land uses.

3 Conditions that determine favorability for agiven use – given different land uses, the con-ditions of favorability may vary for each cri-terion, therefore each criterion may have asomewhat different set of conditions consid-ered advantageous or adverse to each use.


4 Suitability classification scheme – a classifi-cation system should be developed in accor-dance with the specified criteria. Above all,the method of classification should be objec-tive and provide for a hierarchical character-ization of suitability.

It is with this final point, classification, that multi-variate techniques make their contribution.

Suitability by clustering Cluster analysis defines aset of techniques for accomplishing the task ofpartitioning a set of objects into relatively homo-geneous subsets based on inter-object similarities.There are four strategies employed in a clusteringprocedure:

1 Partitioning methods2 Arbitrary origin methods3 Mutual similarity procedures4 Hierarchical clustering methods.

Although a discussion of each is beyond the scopeof this section, a detailed explanation of clusteranalysis can be found in Davis (1986) and Kachigan (1986).

Typically, clustering begins by measuring eachof a set of n-objects on a set of variables (k). Next, ameasure of similarity, distance, or difference is cal-culated and used to compare objects in the set.Using these calculated similarity measures, an al-gorithm expressing a specific sequence of rules isemployed to cluster the objects into groups basedon the inter-object similarities. The logic underly-ing a given clustering algorithm is based on the as-sumption that objects that are similar belong to thesame group. The ultimate goal of any clusteringmethod is to arrive at a cluster pattern of objectsthat displays small within-cluster variation, butlarge between-cluster variation (Kachigan, 1986).The differences between the resultant clusters(groups) can be interpreted by comparing each totheir mean values on the input variables. The twomain considerations that influence the applica-tion of this technique and the selection of a spe-cific clustering procedure relate to: (1) obtaining ameasure of inter-object similarity, and (2) specify-ing a procedure for forming the clusters based onthe similarity measures.

An expression of suitability develops out of the

formation of the clusters as land units are groupedinto similarity classes. This pattern is refined asthe clusters are examined and the statisticalgroups are assigned to informational categories.The interpretation of the cluster pattern and thenaming of the resulting groups is a critical phase inthis application. In general, interpretation relieson the use of judgment supported by the carefulexamination of the means and variances on the en-vironmental variables used as input. For example,at the conclusion of an analysis it might be ob-served that Cluster 1 displays a high mean on vari-ables x2, x3, and x7, while Cluster 2 shows highmean values on variables x1, x5, x6. If variables x2,x3, and x7 explain soil characteristics, then Cluster1 may reflect soil qualities or conditions. There-fore, from these comparative profiles of the inputvariables the distinguishing qualities of the clus-ters can be identified.

Suitability by discriminant analysis Discriminantanalysis is a procedure for identifying relation-ships between qualitative criterion variables andquantitative predictor variables. The technique isparticularly useful for identifying the boundariesbetween groups of objects, where the boundary isdefined in terms of the characteristics of the crite-rion variables that distinguish (discriminate) theobject in the respective criterion groups.

Discriminant analysis is an adaptation of re-gression analysis and is designed for situationswhere the criterion variable is qualitative. In regression analysis an equation is solved that describes a weighted combination of values onvarious predictor variables. This equation enablesprediction of an object’s value on a quantitativecriterion variable given its measure on each of thepredictor variables. Asimilar concept is employedin discriminant analysis, only here the equation iscalled a discriminant function. The discriminantfunction uses a weighted combination of predic-tor variables to classify an object into one of the cri-terion variable groups. This function is therefore aderived variable defined as the weighted sum ofvalues on the individual predictor measurement.This derived variable is termed a discriminantscore.

110 CHAPTER 5

The general form of the discriminant functioncan be expressed as:

(5.2)

where X1, X2, . . . , Xn represent values on variouspredictor variables, while b1, b2, . . . bn explainweights associated with each variable. The value ldefines an object’s discriminant score. Central tothe application of this technique are the definingcharacteristics or parameters that guide its use.These include: (1) the weights associated witheach predictor variable, and (2) the critical cut-offscore for assigning objects into their criteriongroups. Typically, these parameters are deter-mined in such a way as to minimize the number ofclassification errors.

Applying discriminant analysis involves thefollowing steps:

1 Selecting from a tentative list of variablesthose that contain the most useful classifica-tory information.

2 Constructing the relevant disciminant functions or scores based on the selectedvariables.

3 Interpreting the discriminant functions inorder to identify factors that reflect majorgroup differences.

4 Examining the discriminant functions inorder to study the effects of several variableson an individual’s group identity.

5 Making the final classification and validat-ing the results.

Suitability by factor methods Factor analysis de-scribes a family of procedures for removing the re-dundancy from a set of correlated variables andrepresenting these variables as a smaller set of“derived” variables or factors. Perhaps one of themore applicable derivations of this approach is thetechnique referred to as “principal componentsanalysis.”

Although it is not strictly a method of factoranalysis, principal component analysis (PCA) is amultivariate statistical procedure used to deter-mine the underlying dimensionality of a data set.The main objectives of the PCAtransform are to:

1 Reduce the dimensionality of a data set.2 Determine a linear combination of variables.

λ β β β= + +1 1 2 2X X Xn n. . . ,

3 Direct the choice of meaningful variables inan analysis.

4 Assist visualization of multidimensionaldata.

5 Identify underlying or latent structures indata.

In the majority of applications, PCA is employedto reduce the dimensionality of a data set and pro-duce a set of components that are uncorrelatedand ordered in relation to the variance explainedby the original data. Following this procedure, en-vironmental data describing important landscapequalities can be represented as a matrix of theform:

Where f 1n represent observations 1 . . . m withattributes n . . . p.

The matrix Fn can be linearly transformed tocontain a set of eigen vector components V1. Theresulting new variables, termed principal compo-nents, can be expressed according to the relation:

(5.3)

When the input data explain geographic qualitiesor quantities, the components express compositespatial patterns that are defined in terms of component loadings. These loadings quantify therelationship each component shares with the underlying patterns found within the originaldata. The principal component transform has several characteristics that are of special interestwhen applied to the problem of suitability analy-sis. First, the total variance is preserved in thetransformation. Second, the transform minimizesthe mean square approximation of error. Lastly,this is the only transform that generates uncorre-lated coefficients.

An important issue that influences the useful-ness of PCA relates to the problem of componentstructure and interpretation. After the reductionof observation space has been accomplished,which initial variables contribute the greatestshare in the variance is often difficult to deter-mine. Equally difficult to explain is the overallmeaning of the component patterns. Thus, regard-

V a X a X a Xij ij ij ij n= + +1 2 . . . .

Fn

n

mn

p

mnp

f

f

f

f

=⋅ ⋅ ⋅

⋅ ⋅ ⋅

⎡

⎣

⎢⎢⎢

⎤

⎦

⎥⎥⎥

1 1

M M


less of the application area, it is generally impos-sible to specify beforehand the number or signifi-cance of the components that will emerge fromPCA. Consequently, since PCA may be regardedmore as an exercise in mathematical manipulationthan a pure statistical procedure, its value is bestjudged by performance rather than by theoreticalconsiderations. Therefore, interpretation of the re-sulting components, their structure and meaningrelies on judgment, the use of supporting informa-tion, and careful validation.

Extensions based on artificial intelligence

The suitability analysis problem has attracted interest from a variety of fields beyond environ-mental planning. Several of the more promisingmethodological approaches to assessment haveemerged from the field of artificial intelligence(Lein, 1997). One AI technology in particular hasbeen shown to be a viable alternative to tradition-al methods of suitability analysis (Lein, 1990). Thisalternative identifies a branch of AI research re-ferred to as “expert systems.” An expert system isa computer program designed to mimic the rea-soning process of a human expert in a narrowlydefined subject area. Using this expert knowl-edge, the system can approach problems usingsymbolic forms of data and information process-ing and reach conclusions similar to those ahuman expert would reach. In a paper by Lein(1990), a rule-based expert system was developedand applied to the suitability assessment problem.The system was designed to incorporate the sub-jective-technical judgment common to the proce-dures discussed previously, and treat themexplicitly in the assessment process. The proto-type system functions as a consultative expert sys-tem and uses a backward chaining inferencingstrategy. The demonstration program consists of110 rules, 223 qualifiers, and 45 choices that guidethe planner through an assessment of suitability.

The primary intent of the prototype is to assistthe planner in identifying relevant informationand to direct the interpretation of effects. The userof this system interacts with a knowledge-base

made up of rules and facts describing the suitabil-ity of selected environmental characteristics rela-tive to a set of potential users (Table 5.8). Byresponding to a series of system queries, informa-tion is returned to the user listing the alternativesthat best match the environmental conditions ofthe site (Table 5.9).

When compared to traditional methods of as-sessment and the limitations associated with each,the expert system becomes an attractive alterna-tive that facilitates the synthesis of facts and quali-tative experience into an automated support toolthat can:

• Help clarify knowledge and effective problem-solving strategies.

• Preserve knowledge and encourage its sharing.

• Integrate knowledge and experience fromseveral different fields.

• Apply heuristic knowledge.A related AI technology that has been applied

to the suitability analysis problems is the artificialneural network (Wang, 1994). Based on an abstrac-tion of the human brain, an artificial neural net-work is a mathematical model comprised of aseries of highly interconnected computational ele-ments linked together to form a specific architec-ture. From this structure, information is processed

Table 5.8 Sample rule in knowledge-based suitability system.

IF:Proposed use is single family dwellingAND septic system is YESAND soil_permeability is 2.0 to 0.2 inches/hour

THEN:Soil_limitations are moderate

Table 5.9 Sample conclusion window of suitability limitations.

Values based on 0.0 to 10.0 systemValue

1 flood limitations are. . . . Severe 10.02 groundwater limitations are. . . . Severe 10.03 bedrock limitations are. . . . Moderate 9.04 slope limitations are. . . . Moderate 9.05 drainage limitations are. . . . Slight 8.0

112 CHAPTER 5

according to a set of external inputs (stimuli). To demonstrate the feasibility of this approach,Wang (1994) developed a back-propagation neur-al network that takes as input a series of environ-mental variables then maps the input data to oneof four suitability classes. Because neural networkmodels are powerful pattern classifiers, the are extremely useful in situations that define high-dimensional problem spaces and complex inter-actions between variables. As illustrated by Wang(1994), a neural network can assess land suitabili-ty and provide classification accuracies of 80% orbetter. Therefore, when neural networks are com-pared to existing methods of analysis several advantages can be noted:

1 They can be trained to make decisions basedon a more complex decision rule.

2 They are simple in structure and compara-tively easy to construct.

3 They can be modified to fit other applications.

Carrying-capacity analysis

Carrying capacity has been a central concept inplanning and environmental management forwell over three decades (Mitchell, 1989). The con-cept emerged from the biological sciences, butwhen it is applied in the context of environmentalplanning, carrying capacity can be defined as thedegree of human activity that a region can supportat an acceptable quality of life without engender-ing significant environmental degradation (Bishop et al., 1974). Alternatively, Hayden (1975)and Cook (1972) have defined carrying capacity asthe maximum ability of an environment to con-tinuously provide resources at the level requiredby the population. Both definitions are valid andsuggest that the interaction between population,development, and the local resource base is gov-erned by thresholds or levels of intensity that willinfluence long-term sustainability.

Arriving at an expression of carrying capacityhas traditionally relied on the subjective judgmentof those familiar with the region in question, cou-pled with the measurement of surrogate estima-tors that could be related in a statistical algorithm

(Lein, 1993). Applying this expression, carryingcapacity can be integrated with a range of socialand economic indicators to define an “optimal”level of development. Based on this optimum, theenvironment may remain intact relative to its potential for sustained output. When one is con-sidering the question of measurement, connec-ting the concept of carrying capacity back to its biological origins helps to frame an assessmentmethodology.

In the biological sciences, carrying capacity de-fines the relationship between the resource base,the assimilative and restorative capacity of the en-vironment, and the biotic potential of a species.The biotic potential of a species, defining the max-imum rate of population growth that could beachieved given the number of females that reachand survive through their reproductive years, isthe controlling variable in this relationship. Bioticpotential, given adequate food supplies, livingarea, and the absence of disease and predation,contributes to population increases that must bebalanced by the environmental system. In theecosystem, environmental resistance regulates biotic potential by imposing limits on food sup-ply, space, and other inhibiting factors. Within thisrelationship, carrying capacity emerges as thelimit or level a species population size attainsgiven the environmental resistance indigenous toits location.

Whether it is explained within a biological context or from the perspective of a planner, carrying capacity is influenced by three critical assumptions:

1 There are limits to the amount of growth anddevelopment that the natural environmentcan absorb without threatening environ-mental stability through environmentaldegradation.

2 Critical population thresholds can be iden-tified beyond which continued growth willtrigger the deterioration of important natu-ral resources.

3 The natural capacity of a resource to absorbgrowth is not fixed.

These assumptions have led to numerous attackson the concept and the methodologies used to derive estimates of carrying capacity. Criticism


tends to focus on questions concerning the defini-tion of threshold levels, the representation of envi-ronmental equilibrium, and the manner by whichcarrying capacity estimates are interpreted (Lein,1993a). These concerns have been summarized byHassan (1982), and recognize the fact that (1) it isdifficult to calculate environmental thresholds, (2)external influences can frustrate the “closed-system” perspective and introduce uncertainty,(3) strict concern for environmental potential limits the scope of analysis when applied tohuman systems, and (4) assessment relies heavilyon subjective-professional judgment.

While the practical problems listed above con-spire to frustrate the simple estimation of carryingcapacity, the concept remains a useful appliedmethodology largely for its facility for:

• Raising questions about developmentstrategies.

• Providing insight regarding the relationshipbetween environmental degradation andhuman activities.

• Assisting in setting priorities in response togrowth pressures.

Therefore, as Lein (1993a) maintains, the phil-osophical appeal and heuristic value of the carrying-capacity concept compensates for thepragmatic difficulties encountered with its application.

The majority of methods designed to assesscarrying capacity (C) employ a deterministic solu-tion to the general relation:

Two central conditions are implied by this relationand influence the manner by which carrying ca-pacity estimates are derived: (1) identification of agrowth variable, and (2) identification of a limit-ing factor. A growth variable can represent eitherpopulation or a measure of human activity such asthe number of new dwelling units per year or thenumber of park visits per day (Ortolano, 1984).Limiting factors may include natural resources,physical infrastructure, or other finite elementsthat may restrain growth as a function of availabletechnology. Limiting factors applied in carrying-capacity assessments help define three general ex-pressions of the concept and direct its application

C f= ( )potential resources, technology .

to problems where such measures can providemeaningful information. Three useful expres-sions of carrying capacity are:

1 Environmental carrying capacity – definedby biophysical characteristics (variables) in-cluding measures of air and water quality,ecosystem stability, and soil erosion. Thesevariables define thresholds such as emissionstandards, BOD, and net primary produc-tivity, that can be measured and linked by theory or empirical evidence to specific consequences. Employing these measuresallows careful examination of the assimila-tive capacity of the environment and the ability of environmental “sinks” to accom-modate change.

2 Physical carrying capacity – describing thecapacity of infrastructure such as roads,highways, water supply systems, landfills,etc., to maintain an acceptable level of per-formance under population growth and development pressures. Because physical infrastructure is designed with specific capacity levels in mind, growth forces canexceed the predetermined optima and resultin a degradation of performance and envi-ronmental quality.

3 Psychological carrying capacity – directsfocus to the social environment and explainsthe role perception, attitude, behavior, andculture play in the way people react to theirsurroundings. Embedded in this expressionare cultural and psychological factors thatinfluence individual behavior and responsesto the quality and condition of amenity resources, recreational area, institutional settings, and the aesthetic aspects of the environment.

Making carrying capacity work

Admittedly, carrying capacity, while it is intuitive-ly appealing, is difficult to implement. However, itcan be used to help formulate plausible alterna-tive scenarios for how a region may develop or torefine a basic understanding of possible environ-mental constraints. To operationalize an exercisein carrying capacity analysis it is necessary to:

114 CHAPTER 5

1 Identify the relevant growth variables andlimiting factors.

2 Establish minimum and maximum valuesfor each limiting factor.

3 Derive a quantitative link between limitingfactors and growth variables based on eithermathematical models, empirical relation-ships, or expert judgment.

4 Develop growth scenarios to explain (char-acterize) the dynamics of the processes involved.

5 Estimate the restrictions imposed by eachlimiting factor on the growth variable(s).

6 Review carrying-capacity estimates and refine methods as needed until results com-municate constraint effectively.

Although the procedures for applying the conceptto environmental planning are still evolving, Ortolano (1984), Mitchell (1989), and Westman(1985) have reviewed several useful examples.

Summary

Before decisions can be made regarding the futurestate of the planning area, information pertainingto the region must be collected, assembled, andanalyzed. Because planning is an information-driven activity, methods to manage informationand direct its use are critical to successful plans. In

this chapter the collection and analysis of land-scape information was examined. Drawing on thebasic principles of regional landscape analysisand the formulation of a natural resource inven-tory, this chapter described how land evaluationmethods can be applied by the environmentalplanner and how this information can be used tobalance human development with the large goalof maintaining environmental functioning. Theprincipal methods examined were land capability,developmental suitability, and carrying-capacityanalysis; and the ability of each to provide an ex-pression of landscape opportunity or constraintwas evaluated.

Focusing questions

What does it mean to inventory a site and whatdoes an inventory communicate?

Define the process of land evaluation and dis-cuss the two basic types of land evaluationmethod.

What is the ultimate goal of developmentalsuitability assessment methods and what arethe limitations associated with rating andweighting techniques?

How do the terms suitability and capability dif-fer, and what does this difference mean?

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