Quantitative revolution

The quantitative revolution was a major paradigm shift in the field of geography. A paradigm shift is a fundamental change in the basic ideas and methods of a science. This revolution sought to make geography a more rigorous and systematic discipline. Before this change, geography was mostly known as regional geography. This older approach focused on describing the unique features of specific areas. Geographers wanted to explain the differences between one place and another. However, many felt this method could not explain general spatial dynamics. The quantitative revolution changed geography from a descriptive subject into a spatial science. This transition moved the field from an idiographic approach to a nomothetic one. An idiographic approach focuses on describing unique individual cases. A nomothetic approach seeks to establish general scientific laws.

This shift occurred during the 1950s and 1960s. It was a response to several problems facing the discipline at the time. In the late 1940s, the regional tradition dominated geography studies. This tradition focused on the areal differentiation of the Earth's surface. However, many people began to argue that geography was unscientific. Critics claimed it was merely descriptive and lacked real explanation. They felt it did not explain why certain processes occurred. This period was also marked by academic struggles. In 1948, the prestigious Harvard University abolished its geography program. This event was seen as an academic war over the field. Geography was even questioned as a true university subject. Many believed it was only useful for education rather than research.

Major debates helped drive the revolution forward. One of the most famous conflicts was the Schaefer vs. Hartshorne debate. In 1953, Fred Schaefer published a work titled "Exceptionalism in Geography: A Methodological Examination." Schaefer rejected the idea that the region should be the central object of study. He argued that geography should establish morphological laws through scientific inquiry. He wanted to use methods from other social sciences to study processes. Richard Hartshorne responded to these criticisms in several publications. Hartshorne believed in the importance of describing and classifying places. He did not believe there should be a hierarchy between description and law-making. He viewed Schaefer's ideas as subjective and contradictory. These debates were central to the movement in the United States.

Several American universities became leaders in this new movement. The University of Iowa was a pioneer in systematic geography. At Iowa, Harold McCarty worked to establish laws of association between patterns. The University of Wisconsin–Madison also played a major role. There, Arthur H. Robinson developed statistical methods for comparing maps. The University of Washington was another critical center for research. Edward Ullman and William Garrison worked on economic and urban geography. They helped develop central place theory. Students at Washington, such as William Bunge, expanded this work significantly. Bunge wrote "Theoretical Geography," which is considered a seminal text of the revolution. These ideas eventually spread to many other schools, including the University of Chicago.

To achieve scientific precision, geographers adopted many new techniques. They began to prefer numerical data over written descriptions. This approach relied heavily on mathematical and statistical tools. Some geographers used descriptive and inferential statistics to analyze data. They also applied basic mathematical equations and models to spatial problems. For example, they used the gravity model of social physics. They also used the Coulomb equation in their research. Some used stochastic models, which involve the concept of probability. These were used to study processes like spatial diffusion. Others used deterministic models, such as the location models of Von Thünen and Weber. These tools allowed for a much more precise study of space.

This new way of thinking changed the philosophy of geography. It led to the development of theories and tested hypotheses. One of the most important books was "Explanation in Geography" by David Harvey in 1969. Harvey provided a theoretical foundation for geography as a spatial science. He described two ways to explain geographical phenomena. The first is the inductive route, where generalizations come from observation. The second is the deductive route, where scientists create models and hypotheses to test. Harvey preferred the deductive method. This approach was linked to positivism, a philosophy of scientific certainty. Some thinkers, like Karl Popper, offered a different view called critical rationalism. Popper argued that hypotheses should be tested for falsification rather than just verification.

Despite its success, the revolution faced some criticism. Some geographers, such as Ian Burton, were dissatisfied with quantification. Others debated if law-making was even possible in geography. Some researchers, like F. Luckermann, argued that these scientific explanations were just guesses. They felt the models lacked a strong empirical basis. They noted that even tested models sometimes failed to match reality. Nevertheless, by the mid-1960s, the revolution had succeeded. It displaced regional geography as the dominant way of thinking. The new paradigm was clearly visible in academic journals and textbooks. It made geography more useful for both the public and private sectors.

Today, the effects of the quantitative revolution are everywhere. It helped create the technical branches of geography we use now. This includes geographic information science and geoinformatics. The rise of computers led to the development of geomatics. This includes tools like Geographic Information Systems (GIS) and remote sensing. These technologies allow geographers to assess complex models across space and time. They can now study the relationships between different spatial entities more easily. These advancements have even helped bridge the gap between physical and human geography. We can now use computable models to study both the natural and human environments together.