What Data Types are used in GIS?

In episode 18 of IAM News, Iphigenia mentioned that GIS utilises existing spatial data from various sources, including remote sensing data, surveys, and other geospatial datasets. So, what different types of data can be included in Geographic Information Systems, and what can they be used for?

A Geographic Information System (GIS) is a powerful tool that allows users to analyse, visualise, and interpret spatial data. GIS platforms can handle a wide variety of data types, and these can be broadly categorised into two main types: spatial data and attribute data.

Spatial data, in the context of GIS, refers to information that has a geographic or locational component. It is data that is directly tied to a specific location on the Earth’s surface. Spatial data can be categorised into two main types: vector data or raster data.

Vector data represents geographic features using points, lines, and polygons. These features are defined by their geometric characteristics and are typically associated with data that provides additional information about each feature (more on that later). Points represent specific geographic locations and are defined by a pair of coordinates (latitude and longitude, or x and y). Such points could include city locations, landmarks, or specific addresses.

Lines use a sequence of commercial points to represent linear features including roads, rivers, or political boundaries. These lines can be straight or curved.

Conversely, polygons represent areas or regions that are defined by a closed loop of connected points. They have both an outer boundary and, optionally, inner boundaries. Typically, examples of polygons include large units such as countries, land parcels, or administrative boundaries.

As well as vector data, GIS also include raster data which represents information as a grid of cells, where each cell has a value. This type of data is often used to represent continuous phenomena across a surface. Examples of this data include satellite imagery, digital elevation models (DEMs), or land cover maps.

Vector data provides a more accurate representation of real-world features compared to raster data, especially when it comes to representing distinct boundaries and capturing detailed geometry.

In GIS, spatial data is not only about the geometry, but also about the attributes associated with those geographic features. Attribute data, in the context of GIS (Geographic Information System), refers to non-spatial information or characteristics associated with geographic features represented in spatial data.

Attribute data is often organised in tabular form, where each row corresponds to a specific geographic feature, and each column represents a different attribute or characteristic associated with that feature. For a point representing a city, attribute data could include the name and population of the city; for a line representing a road, attribute data may include the speed limit and maintenance history; and for a polygon representing a land parcel, attribute data could feature its soil composition.

By combining spatial and attribute data, GIS users can perform a wide range of analyses, generate thematic maps, and gain insights into the relationships between different geographic features. Attribute data plays a crucial role in supporting decision-making processes, as it provides context and additional details that enhance the understanding of the spatial information within a GIS dataset.

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