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The result looks much like a treemap diagram, although the latter is generally sorted by size rather than geography. These are often contiguous, although the contiguity may be illusory because many of the districts that are adjacent in the map may not be the same as those that are adjacent in reality.
The most common purpose of a thematic map is to portray the geographic distribution of one or more phenomena. Sometimes this distribution is already familiar to the cartographer, who wants to communicate it to an audience, while at other times the map is created to discover previously unknown patterns (as a form of Geovisualization). [17]
There are also many different types of geodata, including vector files, raster files, geographic databases, web files, and multi-temporal data. Spatial data or spatial information is broader class of data whose geometry is relevant but it is not necessarily georeferenced, such as in computer-aided design (CAD), see geometric modeling.
Attribution studies generally proceed in four steps: (1) measuring the magnitude and frequency of a given event based on observed data, (2) running computer models to compare with and verify observation data, (3) running the same models on a baseline "Earth" with no climate change, and (4) using statistics to analyze the differences between the ...
As the volume of geographic data has exploded over the last century, thematic cartography has become increasingly useful and necessary to interpret spatial, cultural and social data. A third type of map is known as an "orienteering," or special purpose map. This type of map falls somewhere between thematic and general maps.
However, they can make the map overly complex, especially if there is not a meaningful geographic pattern in the variable (i.e., the map looks like randomly scattered colors). Although representing specific data in large regions can be misleading, the familiar district shapes can make the map clearer and easier to interpret and remember. [15]
That is, a larger symbol looks like more of something and thus more important, and it is very difficult to interpret it any other way (e.g., as qualitatively different nominal categories). A second tendency is for users to interpret relative sizes: a symbol that is twice as large (in area or length) will be interpreted as representing twice the ...
where d ij is the Euclidean distance between the i th and j th points in a data set of n points, t is the search radius, λ is the average density of points (generally estimated as n/A, where A is the area of the region containing all points) and I is the indicator function (i.e. 1 if its operand is true, 0 otherwise). [3]