THEMATIC CHARACTERISTICS OF SPATIAL DATA Attributes are the non-spatial data associated with point, line and area entities. Attributes are the characteristics of an entity GIS might tell us that: a point represents a hotel a line represents a ski lift and an area represents a forest For example, every year the managers of Happy Valley must complete a table for a ski resort guide. For this table they need to provide the name of the ski area, its ranking (1st, 2nd, 3rd, 4th largest in the country), its average winter temperature and the size of the ski area. Each item of data uses a different scale of measurement The names given to these scales are nominal, ordinal, interval and ratio

Nominal Scale On a nominal scale numbers are used to establish identity. Example : - telephone numbers or ski pass codes Adding, subtracting or dividing numbers on a nominal scale will not produce a useful result.

Ordinal Scale The numbers in an ordinal scale establish order Example : - top 10 cafés and ski runs based on the number of people using them each week The most popular ski run (ranked 1) is not necessarily twice as popular as the ski run which is ranked second. Arithmetic operations on ordinal data will again give meaningless results.

Interval Scale On an interval scale the difference between numbers is meaningful Example: - Temperatures, in degrees Celsius Negative numbers are also possible on an interval scale.

Ratio Scale On a ratio scale measurements can have an absolute or real zero, and the difference between the numbers is significant Example: - Snow depth a snow pack that is 3 m deep is twice as deep as one that is 1.5 m deep

OTHER SOURCES OF SPATIAL DATA Census and survey data Census and survey data are collections of related information. They may be spatial in character if each item in the collection has a spatial reference that allows its location on the surface of the Earth to be identified. Examples are population census, employment data, agricultural census data or marketing data   Aerial photographs Aerial photography was the first method of terrestrial remote sensing. It is the capturing of images from a position above the Earth’s surface, or without contact with the object of interest

Aerial photographs

Curran (1989) identifies six characteristics of aerial photographs that make them of immense value as a data source for GIS: wide availability low cost (compared with other remotely sensed images) wide area views time-freezing ability high spectral and spatial resolution and three-dimensional perspective

Satellite images Satellite images are collected by sensors on board a satellite and then relayed to Earth as a series of electronic signals, which are processed by computer to produce an image. These data can be processed in a variety of ways, each giving a different digital version of the image Scanned images are stored as a collection of pixels ,which have a value representing the amount of radiation received by the sensor from that portion of the Earth’s surface The size of the pixels gives a measure of the resolution of the image. The smaller the pixels the higher the resolution. The Landsat Thematic Mapper collects data for pixels of size 30 m by 30 m. Much greater resolution is possible ,say 1 m by 1 m, but this has in the past been restricted to military use. 

Examples of satellite imagery

Field data sources: surveying and GPS There are several methods of collecting raw data in the field for direct input into a GIS. These are most often used when the required data do not exist in any other readily available format such as a map or satellite image. Traditional manual surveying techniques using chains, plane tables, levels and theodolites are examples of direct field measurement, but the data collected need to be written down on paper first. Modern digital equivalents of these manual techniques have been adapted so that the data collected are stored in digital format ready for direct input into GIS. 

GPS receiver and satellite configuration