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Representing Geographic Space; Discrete and Continuous

Geographic data can be broadly classified into two categories - discrete and continuous. Discrete geographic data is information that is specific to particular locations, and can be represented by different types of values like nominal, ordinal, interval, and ratio. This type of data includes features like landownership, soils classification, zoning, and land use.


When represented on a map, discrete data typically has well-defined boundaries and is typically represented in polygon format. For example, the shape of a property boundary or a zoning district can be considered as discrete geographic data. In addition, point and line datasets such as tree locations, rivers, and streets are also considered as discrete data.


On the other hand, continuous data refers to information that does not have a clearly defined boundary and can be measured at every point on a map. Continuous data is often represented as surfaces and includes datasets like elevation, rainfall, pollution concentration, and water tables. When represented on a map, continuous data can be visualized as a continuous gradient or a smooth transition of values from one point to another.


In summary, discrete geographic data pertains to information that is specific to certain locations and has well-defined boundaries, whereas continuous geographic data pertains to information that is present throughout an area and has no clear boundaries. Understanding the difference between these two types of geographic data is essential for effective analysis and visualization of spatial data.


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