Locational Analysis

• Locational analysis is the approach to human geography that studies the spatial arrangement of phenomena: where activities are located, how places are linked and why the resulting patterns take the form they do.
  • Its aim was to build accurate generalisations, models and theories with predictive power, in the phrase of Brian Berry and Duane Marble (1968).
• It became the core of the “new geography” of the quantitative revolution in the 1950s and 1960s. Its philosophy is positivism, its method that of spatial science, and its toolkit statistics, geometry and location theory.
• Its classic statement is Peter Haggett’s Locational Analysis in Human Geography (1965). The book breaks the human landscape into a sequence of geometrical elements that can be measured, modelled and compared.

Origin and Development of the Locational School

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From Regional Description to Spatial Analysis

• Before the 1950s: human geography was dominated by regional geography. Its idiographic method described the unique character of each region.
  • Paul Vidal de la Blache’s genre de vie and Richard Hartshorne’s areal differentiation were its leading ideas. Description and synthesis were valued above theory and law.
• The critique: by mid-century, regional work was judged encyclopaedic and untheoretical.
  • Fred K. Schaefer’s “Exceptionalism in Geography” (1953) defined geography as the science of spatial arrangements, governed by morphological (pattern) laws.
  • The Hartshorne–Schaefer debate opened the way to a nomothetic, law-seeking geography.
• The shift in focus that followed:
  • from areal to spatial studies;
  • from absolute to relative location;
  • from areal integration to spatial interaction, meaning flows of goods, people and messages.
  • J. Wreford Watson (1955) called geography a “discipline in distance”.

Roots in Location Theory

• The locational school borrowed older economic location theories and rebuilt them as geography:
  • Johann Heinrich von Thünen (1826) on agricultural land use;
  • Alfred Weber (1909) on industrial location;
  • Walter Christaller (1933) and August Lösch (1940) on central places and market areas;
  • Walter Isard’s Location and Space-Economy (1956) and the Regional Science Association (1954).
• Social physics added the gravity model and population potential: John Q. Stewart and William Warntz at Princeton.
  • George Kingsley Zipf’s principle of least effort (1949) gave a behavioural rationale for distance minimisation.

Why Economics and Planning Mattered

• Shared questions: economists had long asked where industries, cities and markets should be, the same questions human geographers now wanted to answer with rigour.
• Borrowed tools: location economics supplied cost curves and market areas. Game theory supplied models of strategic choice, and regional planning supplied practical problems of siting and service provision.
• Two-way exchange: regional science gave geographers a home among economists and planners. Geographers in turn added real distributions, maps and fieldwork to abstract economic models.
• Planning demand: post-war reconstruction, new towns, highways and, in India, the Five-Year Plans needed answers about where to put investment. This made locational analysis immediately useful.

Centres and Contributors

• Seattle: William L. Garrison’s “The Spatial Structure of the Economy” (1959–60) urged geographers to use economists’ location theory. His students carried the approach across North America.
  • Students: Brian J. L. Berry (central places, urban systems), William Bunge, Richard Morrill and Waldo Tobler.
• William Bunge’s Theoretical Geography (1962; 2nd edn 1966) called geography the “science of locations” and geometry its language.
• Iowa: Harold H. McCarty studied laws of association between distributions.
• Lund: Torsten Hägerstrand modelled the diffusion of innovations (1953).
• Cambridge: Peter Haggett and Richard Chorley (Models in Geography, 1967) set the approach in a systems and model-building framework.
• Richard Morrill’s The Spatial Organization of Society (1970) argued that people seek maximum interaction at minimum cost. They therefore cluster related activities, which makes the location patterns of different societies surprisingly alike.
• Brian Berry and William Garrison (1958) tested central place theory on the functional hierarchy of towns, and Berry went on to model whole urban systems.
• Institutional base: the Regional Science Association, the Annals of the Association of American Geographers and, from 1969, Geographical Analysis and Environment and Planning carried the new locational work.
• Others who widened the field: Kevin Cox, David Harvey (in his positivist phase), R. J. Johnston, Robert Sack and David M. Smith.
  • David Harvey’s Explanation in Geography (1969) gave the school its full methodology. Fred Lukermann, by contrast, questioned whether its analogies with physics explained anything.

The Locational Approach

Haggett’s Model

• Haggett asked geographers to revive the geometrical tradition and to study the order, locational order and patterns of human geography. Doing this needed three things:
  • a systems approach, which follows patterns and linkages within a whole assemblage;
  • models, as simplified pathways to understanding the man–environment relationship;
  • quantitative techniques, for precise statements about locational order.
• He used the nodal region as the organising frame. Its parts appear in a logical sequence, each building on the one before.

The Six Elements

• 1. Movement: spatial organisation begins with interaction, such as trade, migration, commuting and messages.
  • Movement follows distance decay: interaction falls as distance rises.
  • The gravity model predicts flows between two places in proportion to their sizes and inversely to the distance between them.
  • Edward Ullman (1956) gave three bases of interaction: complementarity, intervening opportunity and transferability.
  • Example: daily commuting into Delhi, Mumbai or Bengaluru from satellite towns.
• 2. Networks: movement is channelled along routes that form networks.
  • Their structure is measured with graph theory: connectivity indices (alpha, beta, gamma) and detour ratios. Karel Kansky (1963) set out these measures for transport networks.
  • Denser, better-connected networks lower the friction of distance and change the pattern of movement.
  • Example: India’s Golden Quadrilateral highway links Delhi, Mumbai, Chennai and Kolkata. The Western and Eastern Dedicated Freight Corridors are newer trunk routes.
• 3. Nodes: where routes meet, settlements and markets grow.
  • Their size and spacing are studied through the rank-size rule, nearest-neighbour analysis and central place theory.
  • Christaller’s range (the farthest distance a buyer will travel) and threshold (the minimum demand to sustain a service) explain why centres are spaced at regular intervals.
• 4. Hierarchies: nodes form an ordered hierarchy, from hamlets and periodic markets to market towns, cities and metropolises.
  • Christaller’s K = 3, 4 and 7 systems describe the market, traffic and administrative principles. Lösch’s flexible system allows more varied arrangements.
  • Example: the chain from weekly haats and mandi towns to district headquarters and state capitals in rural India.
• 5. Surfaces: the spaces between nodes form surfaces of land use, rent and density.
  • Examples include von Thünen’s rings, William Alonso’s bid-rent gradients (1964) and Colin Clark’s urban population-density gradient (1951), which falls with distance from the centre.
  • Surfaces are mapped as isolines, such as lines of equal land value, rent or travel time.
• 6. Diffusion: added in the 1977 second edition (with Andrew Cliff and Allan Frey). It covers change over time as innovations spread through the system.
  • Spread may be contagious (neighbour to neighbour) or hierarchical (city to town to village).
  • Adoption typically follows an S-shaped curve over time and a neighbourhood effect over space, as Hägerstrand showed.
  • Example: high-yielding varieties spread from Punjab, Haryana and western Uttar Pradesh in the late 1960s, and digital payments spread from metros to small towns.

Characteristics

• Positivist: it seeks laws and theories of spatial arrangement through hypothesis testing and verification.
  • Its practitioners assumed that positive theory (what is) would lead naturally to normative insight (what ought to be). Critics later rejected that assumption.
• Empiricist in practice: it gives priority to observational statements over theoretical ones. Measured facts are treated as able to “speak for themselves”, and theoretical statements are judged by their fit to data.
• Geometric: reality is reduced to points, lines, areas and surfaces, measured through direction, distance and connection.
• Model-based and normative: classic models describe the optimal pattern under ideal assumptions:
  • rational economic man;
  • perfect information;
  • an isotropic plain with uniform transport costs and resources.
• Systems-minded: movement, networks, nodes and hierarchies are studied as interdependent parts of one regional system.
• Statistical: it draws on the general linear model (regression, correlation) and, later, on procedures designed for the special problems of spatial data.

Objectives

• Explain spatial patterns: why a city grew at a river crossing, why an area industrialised, why a market serves a given hinterland.
• Build models and theories: abstract representations of land use, industrial location, central places and spatial interaction that generalise locational decisions.
• Measure precisely: statistics, geometry and mapping replace impressionistic description with replicable results.
• Find optimal locations: minimise cost and distance, and maximise profit, access or coverage, for a factory, warehouse, hospital or school.
• Reveal spatial structure: transport networks, flows of goods and people, and settlement hierarchies, including the forces of attraction and repulsion between places.
• Predict: forecast how patterns will respond to a new road, factory or town.
• Serve planning: give rational criteria for zoning, infrastructure and the allocation of public resources.

Applications and Evaluation

Applications

• Urban geography and planning:
  • It is used to analyse urban hierarchies, land-use structure, commuting and access to services.
  • Location-allocation models site schools, hospitals, parks and fire stations to minimise travel to the nearest facility.
• Industrial and economic geography:
  • Least-cost location (Weber) weighs transport, labour and agglomeration.
  • It guides industrial clustering, industrial corridors, logistics parks and the choice between resource-based and market-based locations.
  • Example: India’s early integrated steel plants were sited near the iron-ore and coal fields of the Chota Nagpur plateau and Odisha.
• Transport:
  • Route design, network connectivity, traffic flow and freight planning use the gravity model and network analysis.
  • Logistics firms use the same tools for route optimisation.
• Retail and services:
  • Reilly’s law of retail gravitation (1931) and the Huff model (1963) delimit trade areas.
  • Supermarkets, banks, malls and fuel stations are sited by customer density and accessibility.
• Regional planning:
  • Planners delimit functional regions, city regions and growth centres, and measure regional inequality for balanced development.
  • India’s growth-centre and service-centre strategies drew on central place ideas.
  • Indian Public Health Standards set population norms for siting primary health centres. A PHC serves about 30,000 people in the plains and about 20,000 in hilly and tribal areas.
• Agriculture:
  • Land-use zones follow von Thünen lines around large cities, such as the vegetable, flower and dairy belts around Delhi and Kolkata.
  • Crop-pattern studies in Punjab and the Deccan are other applications.
• Population and settlement: migration flows, settlement spacing, rural service centres and the planning of urban expansion.
• Disasters and environment: hazard-zone mapping, siting of cyclone shelters and relief centres, and siting of renewable-energy plants under environmental constraints.

Criticism

• Unreal assumptions: isotropic plains, perfect knowledge and profit-maximising economic man rarely exist. This is especially true in rural and traditional societies.
  • Herbert Simon’s satisficer accepts a good-enough choice.
  • Allan Pred’s behavioural matrix (1967) showed that location decisions depend on the information a decision-maker has and the ability to use it.
• Poor prediction: models did not reflect how decisions are really made. Their forecasts of location were often weak, because bias, local knowledge, politics and historical inertia count for more than abstract logic.
• Values ignored: cultural values, social norms and politics shape location.
  • The “ideal” site may be unacceptable to a community, as land-acquisition protests over factory and project sites in India show.
• Static and abstract: models freeze a moment in time. They conceal the real world’s complexity, its history and the dynamics of urban growth, migration and technological change.
• Spatial determinism: critics argued that it is logically impossible to define spatial variables apart from the social context in which they operate.
• Global interdependence: in a world of global supply chains and capital flows, locally experienced environmental dependencies lose their rationale, and locally defined location rules lose force.
• Capitalist bias:
  • Radical critics argued that the school treated profit-maximising location as natural and ignored who gains and who loses.
  • It was blamed for helping over-industrialisation, inequality and environmental damage in the name of spatial efficiency.
• Dehumanised: behavioural and humanistic geographers objected that people became dots on a map, data on a graph or numbers in an equation.
  • Critics also noted that behavioural geography remained a creature of locational analysis: it adjusted the models without questioning their philosophy.
• Limited domain: the methods work well in transport, retail and logistics, but poorly where qualitative and subjective variables dominate. O. H. K. Spate’s warning that measurement is a means, not an end, applied here too.
• Haggett’s own second thoughts:
  • In 1978 he could claim only that the spatial economy was better defined than before, with “incomplete and shaky” theoretical bridges.
  • By 1990 he accepted that the order one finds depends on what one looks for.
  • Marvin Mikesell (1984) doubted that locational analysis had ever truly dominated the discipline.
• These objections formed part of the wider criticism of quantification that ended the dominance of spatial science in the 1970s.

Contemporary Relevance

• Behavioural refinement:
  • Bounded rationality, the behavioural matrix and behavioural geography made location models more realistic.
  • Hägerstrand added the time-space constraints on individual movement.
• Political economy:
  • David Harvey and Manuel Castells criticised the capitalist rationality of location models.
  • They still engaged with locational questions: how capital accumulation shapes spatial structure, how uneven development appears on the map, and how conflicts arise over gentrification and displacement.
• New economic geography: Paul Krugman’s “Increasing Returns and Economic Geography” (1991) brought agglomeration and core–periphery models back into economics, and won him the 2008 Nobel Prize in economics.
• GIS and geocomputation:
  • Location-allocation, network analysis, spatial econometrics, agent-based models of individual choices and machine learning for site prediction are the modern descendants of Haggett’s programme.
  • Businesses use location analytics for logistics, supply chains and real estate.
• Refined theory: Weber, Christaller and Lösch remain foundational frameworks. Their assumptions are relaxed to fit real variation, and contextual, regional and hybrid models are preferred to universal abstractions.
• Indian planning:
  • The PM Gati Shakti National Master Plan (2021) integrates infrastructure layers on a GIS platform.
  • The National Logistics Policy (2022) aims to cut logistics costs.
  • Industrial corridors, the Dedicated Freight Corridors and Smart Cities all depend on locational analysis of nodes, networks and flows.
  • The Planning Commission and now NITI Aayog and state planning boards use locational analysis to delimit planning regions and growth centres and to plan utilities.
  • The National Geospatial Policy (2022) and remote-sensing data have made such planning increasingly data-driven.
• Equity and sustainability: modern multi-criteria models weigh access, environmental cost and social justice alongside cost. Examples include universal access to clinics, schools and water, and siting renewables away from fragile ecosystems.

Spatial Analysis and Locational Analysis

• Spatial analysis is the set of quantitative procedures used in locational work. In practice the two terms are often used interchangeably.
  • David Unwin (1981) defined spatial analysis as the study of the arrangement of points, lines, areas and surfaces on a map.
  • The generalisations of both rest on three spatial concepts: direction, distance and connection (relative position).
• The physical view of space shaped the forms of spatial analysis:
  • Absolute (Euclidean) space, a fixed container, gave geometric analysis: point patterns, nearest-neighbour measures, network geometry and shape indices.
  • Relative space, measured in time, cost or interaction, gave distance-decay, gravity and potential models, cost-distance surfaces and maps transformed by travel time.
  • Treating space as pre-social led to charges of spatial fetishism: the model of space and the socio-spatial dialectic holds that space is produced by society, not merely occupied by it.
• Goal: spatial analysis aimed at accurate, predictive generalisation through precise quantitative description of spatial distribution, spatial structure and organisation, and spatial relationships.
• Difference of emphasis: spatial analysis asks what is happening where, and why. Locational analysis also asks where something should happen for efficiency or profit.
• Specific statistical problems arise because spatial data are not independent. Spatial autocorrelation and the modifiable areal unit problem led to purpose-built spatial statistics.
• Shared criticism: both were faulted for positivist bias, neglect of human agency and blindness to social and cultural complexity.
• Today: spatial analysis has been absorbed into GIScience and spatial data science. Locational analysis survives in regional science, planning and business location analytics. Both feed the wider study of spatial organisation.