Quantitative Revolution: Major Methodological and philosophical developments in Geography

The quantitative revolution in geography brought about a number of methodological developments that changed the way geographers approached their research. These developments allowed geographers to analyse and understand spatial phenomena in new ways, and helped to establish geography as a more quantitative and scientific discipline. 

Some of the major methodological developments in geography due to the quantitative revolution are:

Statistical analysis:

One of the most important methodological developments in geography due to the quantitative revolution was the use of statistical analysis. Geographers began using statistical methods to analyse and interpret data, such as regression analysis, correlation analysis, and spatial analysis. These methods allowed geographers to identify patterns and relationships in data, and to make predictions about spatial phenomena based on statistical models which are called spatial statistics. 

In Network analysis matrices are used. 

For example, geographers used statistical analysis to study the relationship between crime rates and various social and economic factors, such as poverty, unemployment, and education levels. By analysing these relationships, geographers were able to identify factors that contributed to higher crime rates in certain areas, and to make predictions about the likelihood of crime in different neighbourhoods.

Sampling techniques:

The use of sampling techniques was another important methodological development in geography due to the quantitative revolution. Sampling techniques involve selecting a representative subset of a larger population for study, and using the results of the study to draw conclusions about the larger population. This allowed geographers to collect data more efficiently and cost-effectively, and to generalize their findings to larger spatial areas.

For example, geographers used sampling techniques to study public opinion on environmental issues in different regions of the United States. By selecting a representative sample of the population in each region, geographers were able to estimate the attitudes of the entire population, without having to conduct surveys on a larger scale.

Multivariate analysis:

The use of multivariate analysis was another important methodological development in geography due to the quantitative revolution. Multivariate analysis involves the study of the relationships between multiple variables, and includes techniques such as principal component analysis and factor analysis. These techniques allowed geographers to identify the underlying factors that contributed to spatial phenomena, and to develop more complex models of spatial behaviour.

For example, geographers used multivariate analysis to study the relationship between climate and vegetation in different regions of the world. By analyzing multiple variables, such as temperature, precipitation, and soil type, geographers were able to identify the factors that contributed to the growth of different types of vegetation.

Spatial analysis techniques:

The use of spatial analysis techniques was another important methodological development in geography due to the quantitative revolution. Spatial analysis involves the study of spatial patterns and relationships, and includes techniques such as spatial autocorrelation, spatial interpolation, and spatial clustering. These techniques allowed geographers to identify spatial patterns and relationships that were not immediately visible, and to analyse spatial phenomena in new ways.

For example, geographers used spatial analysis techniques to study the spatial patterns of land use in urban areas. By analysing the spatial distribution of different types of land use, geographers were able to identify areas of urban sprawl and to develop strategies for managing growth and preserving green space.

New theories and models

The quantitative revolution led to the development of new theories and models in geography. These theories and models helped to explain various spatial phenomena.

Gravity model, which explains the spatial interaction between places, was developed during this period. The gravity model assumes that the interaction between two places is proportional to their population size and inversely proportional to the distance between them. It has been used to explain a wide range of spatial phenomena, such as trade flows, migration patterns, and communication networks. Based on the gravity model Social physics has been developed which seek to explain the social relationships using gravity model. Concept of retail gravitation, population potential all are examples of social physics. 

Locational analysis

Locational analysis is a process of evaluating the geographic location of a particular entity or activity. It involves examining factors such as accessibility, proximity to resources, market demand, competition, and infrastructure availability. 

The goal of locational analysis is to identify the most optimal location that maximizes efficiency and profitability. This analysis is commonly used in various fields, including retail businesses, logistics, real estate development, and manufacturing. By considering relevant factors and utilizing spatial data analysis techniques, locational analysis helps businesses and organizations make informed decisions about where to establish operations or expand their presence, ultimately contributing to their success and competitiveness.

Location Theory: 

It focuses on understanding and explaining the spatial patterns of economic activities and human settlement. It seeks to analyze the factors influencing the choice of location for various activities and the resulting spatial distribution.

One prominent concept in location theory is the "central place theory" developed by Walter Christaller in the 1930s. The theory explains the size and spacing of cities and towns in a hierarchical manner. According to Christaller, settlements function as central places providing goods and services to surrounding areas. Larger settlements are fewer and serve larger regions, while smaller settlements are more numerous and cater to smaller catchment areas.

For example, consider a city with a regional shopping mall. The mall serves as a central place, attracting consumers from nearby towns and villages. Smaller towns might have convenience stores or smaller retail outlets catering to their local population. This hierarchy of settlements is based on the principle of "range" (maximum distance consumers are willing to travel) and "threshold" (minimum number of customers required to sustain a business).

Another example is industrial location theory, which explains the factors influencing the siting of industries. Factors such as availability of raw materials, labor supply, transportation networks, market demand, and government policies influence the location decisions of industries. For instance, a manufacturing plant might be located near a port for efficient import and export of goods or near a particular region to capitalize on the availability of skilled labor.

Rank size rule, 

Social area analysis, 

Network analysis, 

System analysis, 

Regional science

all are the results of increasing awareness on spatial analysis as a result of quantitative revolution. 

Development of Mathematical modelling

The use of mathematical modelling was another major methodological development in geography due to the quantitative revolution. Geographers began using mathematical models to simulate and predict the behaviour of spatial phenomena, such as the flow of water through a river system or the movement of air masses in the atmosphere. These models allowed geographers to test different scenarios and to make predictions about the future behaviour of spatial phenomena.

For example, geographers used mathematical models to study the spread of infectious diseases, such as HIV/AIDS and malaria. By simulating the spread of the disease under different scenarios, geographers were able to identify strategies for controlling the disease and reducing its impact.

Mathematical models can be deterministic or stochastic. Deterministic models have wider implications in physical geography. 

New Cartography: Remote Sensing and Geographic Information Systems (GIS):

The use of remote sensing was another major methodological development in geography due to the quantitative revolution. Remote sensing involves the use of satellite imagery, aerial photography, and other forms of remote sensing technology to study spatial phenomena from a distance. Remote sensing allowed geographers to study large areas of the earth's surface in a short amount of time, and to observe spatial patterns and relationships that were not visible from the ground.

For example, remote sensing was used to study deforestation in the Amazon rainforest. By analysing satellite imagery, geographers were able to identify areas of deforestation and to study the impact of deforestation on the local environment.

The development of computer technology and geographic information systems (GIS) was another major methodological development in geography due to the quantitative revolution. GIS allowed geographers to store and manipulate large amounts of spatial data, such as maps, satellite imagery, and demographic data, in digital form. This made it possible to create more accurate and detailed maps, and to analyse spatial patterns and relationships more easily.

For example, GIS allowed geographers to create detailed maps of land use and land cover, which were used to study changes in land use patterns over time. GIS also allowed geographers to analyse the spatial patterns of population density, and to identify areas of high population growth or decline.

Philosophical Development due to Quantitative Revolution

The philosophical development in Geography due to the quantitative revolution was a response to the limitations of traditional approaches that relied on descriptive and qualitative methods to understand spatial phenomena. The adoption of positivism, determinism, reductionism, and objectivity represented a shift towards a more scientific and objective approach to Geography that emphasised empirical data and quantitative analysis. In this section, we will discuss each of these philosophical developments in more detail.

Positivism:

Positivism emphasises the use of empirical observation and scientific methods to understand the world. In Geography, positivists argued that the discipline should be more scientific and rigorous, and that geographic research should be based on empirical data and quantitative analysis. They believed that this approach would lead to more objective and reliable results, and would allow for greater generalisation and prediction.

One of the key strengths of positivism is that it allows for the testing of hypotheses and the development of theories that can be used to explain phenomena. By using rigorous methods and systematic observation, geographers can identify patterns and regularities in spatial phenomena. For example, positivist approaches have been used to understand the relationship between urbanisation and economic development, or the impact of climate change on natural systems.

However, one of the criticisms of positivism is that it can be reductionist and mechanistic, ignoring the complexity and nuance of spatial phenomena. Positivist approaches may also be limited by the quality and availability of data, as well as the assumptions and biases of the researcher.

Reductionism:

Reductionism is the belief that complex phenomena can be explained by reducing them to their constituent parts. In Geography, reductionists argued that complex spatial phenomena could be understood by breaking them down into smaller components. They believed that by studying the relationships between these components, geographers could develop a more comprehensive understanding of spatial phenomena.

One of the key strengths of reductionism is that it allows for a systematic and analytical approach to spatial phenomena. By breaking down complex systems into smaller parts, researchers can better understand the behaviour of the system as a whole. For example, reductionist approaches have been used to understand the dynamics of urban systems or the drivers of environmental change.

However, reductionism has been criticised for oversimplifying the complexity of spatial phenomena. It may also be limited by the quality and availability of data, as well as the assumptions and biases of the researcher.

Objectivity:

Objectivity is the belief that scientific inquiry should be free from bias and personal values. In Geography, objectivists argued that geographic research should be free from subjective interpretation or personal bias. They believed that by using objective methods and rigorous analysis, geographers could produce more reliable and valid results.

One of the key strengths of objectivity is that it allows for the development of rigorous and reliable methods for understanding spatial phenomena. By minimizing the role of personal bias and subjective interpretation, researchers can develop more objective and systematic approaches to geographic inquiry. For example, objective approaches have been used to develop reliable methods for mapping and monitoring land cover change, or quantitative and philosophical developments in Geography due to the quantitative revolution.

Systems Approach:

Systems theory is the belief that complex systems can be understood by examining the relationships between their constituent parts. In Geography, systems theorists argued that spatial phenomena can be understood as complex systems, and that by studying the relationships between different components, geographers can develop a more comprehensive understanding of spatial phenomena.

One of the key strengths of systems theory is that it allows for a holistic and integrated approach to understanding spatial phenomena. By examining the relationships between different components of a system, researchers can better understand how the system behaves as a whole. For example, systems theory has been used to understand the dynamics of urban systems or the drivers of environmental change.

However, systems theory has been criticised for oversimplifying the complexity of spatial phenomena, and for ignoring the role of human agency in shaping spatial systems.