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intro-geoinfo-2014 [2014/05/07 05:22]
gcamara
intro-geoinfo-2014 [2014/05/07 05:22] (current)
gcamara
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 What we call "​geographical data" includes different kinds of data. We observe the natural world when we get data about topography, landscapes, the oceans and the atmosphere. Sometimes we represent data from nature as a continuous variation, as when we build digital terrain models. In other situations, we give names to natural features, as when we say "Mont Blanc"​. ​ We also create geographical reality, as when we draw boundaries of countries and of land parcels. We also measure facts of the social world, when we take a census and locate crimes. We also build continuous distributions out of social reality, e.g., when we create maps of disease incidence in a country. We also observe and detect change in the geographical world, as when we map new deforested areas. ​ What we call "​geographical data" includes different kinds of data. We observe the natural world when we get data about topography, landscapes, the oceans and the atmosphere. Sometimes we represent data from nature as a continuous variation, as when we build digital terrain models. In other situations, we give names to natural features, as when we say "Mont Blanc"​. ​ We also create geographical reality, as when we draw boundaries of countries and of land parcels. We also measure facts of the social world, when we take a census and locate crimes. We also build continuous distributions out of social reality, e.g., when we create maps of disease incidence in a country. We also observe and detect change in the geographical world, as when we map new deforested areas. ​
  
-The beauty and the challenge of Geoinformatics is that there are a relatively small set of data structures that are able to represent different types of geographical data. This representational power has enabled software engineers to develop the technology of geographical information systems. The challenge is to understand both the data structures and the semantics of the information they represent. This course is then focused on discussing the semantics of geographical data, as well as the links between such semantics and the associated computer representation. When they complete the course, we expect that students should be iable to understand the different types of geographical data and how they are represented in computers.+The beauty and the challenge of Geoinformatics is that there are a relatively small set of data structures that are able to represent different types of geographical data. This representational power has enabled software engineers to develop the technology of geographical information systems. The challenge is to understand both the data structures and the semantics of the information they represent. This course is then focused on discussing the semantics of geographical data, as well as the links between such semantics and the associated computer representation. When they complete the course, we expect that students should be able to understand the different types of geographical data and how they are represented in computers.
  
 === Motivation === === Motivation ===

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