Abstract
For a long time, Geography did not hold a specific mathematical approach for any interpretation of space and this was the key reason why Geography degrees covered a wide variety of subjects such as demography, geology or topography to fulfill its curriculum. Yet from the 90’s, Geography finally created its own research agenda to meet four vital questions of any true geographer: “Where is …?”, “Is there a general spatial pattern?”, “What are the anomalies?” and “Why do these phenomena pursue certain spatial distribution?” The present review article addresses ten different spatial (point, regression and event) issues for learning and teaching aim where statistics play a major background role on the outcomes of myGeoffice© free Web GIS platform. These include cluster analysis, geographically weighted regression (GWR), ordinary least squares (OLS) regression, path analysis, minimum spanning tree, linear regression, space-time clustering and point patterns, for instance. Although the technical viewpoint of the algorithms is not explained at fully, this review paper makes a rather strong emphasis on the result’s interpretation, their respective meaning and when these techniques should be applied in a learning/teaching context.
Highlights
Several classical statements concerning the definition of Geographical Information Systems (GIS) can be found in specialized literature expressing the idea that spatial analysis can somehow be useful
GIS can be seen as a spatial analysis engine and its main end relies on the ability to predict outcomes and, above all, to understand those [23]
GIS is a specific class of information systems designed to capture, storage, manipulate, retrieve, analyse and display all forms of geographically referenced data and information [25]
Summary
According to [1], it had been estimated that 80% of the informational needs of local government policymakers are related to geographic location. Under the current Internet age, Geographical Information Systems (GIS) is seldom included in any Geography syllabus to foster inferential analysis of spatial data. Nowadays, many GIS applications can be found in the real world such as tourism, aviation, archaeology, agriculture, water and air pollution, crowed simulation, parking availability, overfishing, telecom and network services, accident analysis, urban and transportation planning, environmental issues, navigation and flooding damage estimation, banking and general business sector, geology and coal mines, volcanic hazard identification, desertification and deforestation, public health applications, crime analysis, locating underground pipes and cables. Quoting [5], if GIS connects what with the where, geographic information science discovers how
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