Concept
Quantitative geography is a subfield and methodological approach to geography that develops, tests, and uses mathematical and statistical methods to analyze and model geographic phenomena and patterns. It aims to explain and predict the distribution and dynamics of human and physical geography through the collection and analysis of quantifiable data. The approach quantitative geographers take is generally in line with the scientific method, where a falsifiable hypothesis is generated, and then tested through observational studies. This has received criticism, and in recent years, quantitative geography has moved to include systematic model creation and understanding the limits of their models. This approach is used to study a wide range of topics, including population demographics, urbanization, environmental patterns, and the spatial distribution of economic activity. The methods of quantitative geography are often contrasted by those employed by qualitative geography, which is more focused on observing and recording characteristics of geographic place. However, there is increasing interest in using combinations of both qualitative and quantitative methods through mixed-methods research to better understand and contextualize geographic phenomena. History of geography Quantitative geography emerged in the mid-20th century as a response to the increasing demand for more systematic, empirical, and data-driven approaches to studying geographic phenomena. It is a direct product of the quantitative revolution in geography. It was influenced by developments in statistics, mathematics, computer science, and the physical sciences. Quantitative geographers sought to use mathematical and statistical methods to better understand patterns, relationships, and processes in the spatial distribution of human and physical phenomena. Computers perhaps had the most profound impact on quantitative geography, with techniques such as map analysis, regression analysis, and spatial statistics to investigate various geographic questions.