How GIS works

Spatial and Non-spatial Data

  • Spatial data refers to geographic areas or features. Features occupies a location.
  • Non-spatial data has no specific location in space. It can however, have a geographic component and be linked to a geographic location
  • Tabular and attribute data are non-spatial but can be linked to location.
  • Example: In the Portland map, a park is a spatial feature and the associated information about the park name, area, administrative code and type code are non-spatial attributes which are linked to the park by its location.



Themes

  • Themes link features with their attributes
  • Themes are linked by geography
  • Collections of themes form a GIS database


Take, for example, the Portland map. It contains many themes. All the interstate freeways could make up one theme, and all railroads, another. City streets might be a separate theme. Parks, buildings, and waterways are examples of other themes.


Geographic databases (themes) can be used to solve problems like:

  • Site Location

Visualizing customer locations is critical to businesses trying to make better marketing decisions.


Analyzing location is key to making decisions about where to set up a business or service.


Presenting information as maps reveals relationships and patterns that may otherwise be hidden.

Other applications include:

  • tracking delivery vehicles
  • recording details of planning applications
  • modelling global atmospheric circulation


Geo-coding and Geo-referencing

How to encode locational information?

How do we reference locations?

Explicit Geographic Reference

  • latitude and longitude
  • national grid coordinate

Implicit Geographic Reference

  • postal code
  • census tract name
  • forest stand identifier
  • road name

Geocoding

Geocoding = deriving implicit from explicit references

These geographic references allow you to locate features (like a business or forest stand) and events (like an earthquake) on the surface of the earth for analysis.



Example of Geocoding

Addresses are actually the most common form of locational information. An address specifies a location in much the same way as a geographic coordinate does. But, addresses are merely text strings containing a house number, street name, direction, and postal code. The GIS needs a mechanism to calculate their geographic location coordinates before you can display them on a map. Address geocoding allows you to display tabular data containing addresses as points on a map. To do so, a GIS associates addresses stored in a tabular file with a spatial data set, usually a street network that also contains addresses. The GIS then uses the coordinates of the street features to calculate and assign coordinates to addresses in the file. The result is a map on which each point represents an address location in your file.


You can match the restaurant addresses in a file to a street network and show them on a map.

There are countless applications for address geocoding. You can map the addresses of customers, facility sites, club members, retail stores, stops on a delivery route, crime locations, and more. The ability to create map features from files of addresses and other geographic locations is a powerful tool for making better use of the data you already have.


Data Models

There are two fundamentally different types of geographic information.

The vector model

  • information about points, lines, and polygons
  • encoded and stored as a collection of x,y coordinates

The location of a point feature, such as a bore hole, can be described by a single x,y coordinate. Linear features, such as roads and rivers, can be stored as a collection of point coordinates. Polygonal features, such as sales territories and river catchments, can be stored as a closed loop of coordinates. The vector model is extremely useful for describing discrete features, but less useful for describing continuously varying features such as soil type or accessibility costs for hospitals.

The raster model

  • models continuous features
  • a collection of grid cells

Both the vector and raster models for storing geographic data have unique advantages and disadvantages and modern GISs are able to handle both types.

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