ESDA: visualization methods in .NET Draw pdf417 in .NET ESDA: visualization methods

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ESDA: visualization methods using barcode printer for .net vs 2010 control to generate, create pdf417 image in .net vs 2010 applications. Microsoft .NET Micro Framework a distribution of value PDF417 for .NET s for each basic spatial unit and the mean or median used to represent the basic spatial unit at the scale speci ed by the choice of K. Different values of K can be chosen to examine patterns at different scales.

This is not a regionalization procedure in the sense of earlier methods but rather a method of developing a spatial lter which uses all possible groupings of the basic spatial units. Choosing random seeds given K does not ensure regions of similar size. There will be some large and some small regions so if the intention is to create randomly generated regions of comparable size to control for scale, strati cation should probably be added to the criteria for selecting seed points.

As a nal point relating to the spatial framework note that several of the specialist graphics tools for ESDA depend on the speci cation of the weights matrix (W). The ability to explore, through graphical or numerical tools, regional data making different assumptions about the underlying graph has been noted as a potentially important aspect of ESDA (Haining et al., 1998).

6.2.3 Special issues in the visualization of spatial data.

The graphical tools dis cussed in section 6.1 still have an important role to play in the visualization of spatial data for ESDA, but in addition new graphical tools are needed to explore for spatial patterns. Some of these will be described in section 6.

3. In addition maps become an essential element in visualization. One of the consequences of this has been summarized by MacEachren and Monmonier (1992, p.

197): For cartography, the single biggest challenge is to redirect our attention from an emphasis on maps that present answers to maps that foster a search for questions. This is the same type of distinction that was drawn between presentation graphics and scienti c visualization. The questions that arise are: how can maps be made to support visualization objectives and what sorts of tools should be provided with them (MacEachren, 1995; Dykes, 1997).

MacEachren and Monmonier (1992) draw attention to the importance of multiple map views, trying out a variety of map measurements, categories, symbolization schemes, scales, scopes, generalizations, azimuths, elevations, times or time periods and juxtapositions (p. 198). Interaction with graphs and graph parameters are as important to ESDA as to EDA.

In addition ESDA requires the ability to be able to quickly draw appropriate maps, the parameters of which can be interactively modi ed to provide different views, and there needs to be dynamic links between cartographic and statistical displays (Haslett et al., 1990, 1991; Dorling, 1992; Dykes, 1997, 1998; MacDougall, 1992; MacEachren and Kraak, 1997). Linking maps and statistical graphics tools through the operation of brushing has been incorporated into ESDA software (see Anselin, 1998 and Wise.

Visualizing spatial data et al., 1999 for select ive reviews). Monmonier (1989) referred to this as geographical brushing.

Graph-to-map linkage enables the user to query where particular cases on a graph (e.g. the outliers on a boxplot) are located on the map of the study area, map-to-graph linkage enables the user to query if a selected area (e.

g. an inner-city area) is distinctive in terms of attributes. Dynamic graph-tomap linkage allows the user to move a polygon over a graph and see the cases highlighted in the map window.

Dynamic map-to-graph linkage allows the user to move a speci ed polygon or line trace over the map surface and highlight cases on the graph, or report statistics computed just for those cases that fall within the boundary of the moving window (Craig et al., 1989). The map is more than just a repository of information on where cases are located.

Majure et al. (1996) compute a spatial cumulative distribution function (SCDF) computed from a forest defoliation index. They overlay population density data in the map window in order to explore links between differences in defoliation picked up by the SCDF computed on different subareas of the map and a possible source of tree stress.

In this way the map holds both locational information and also data of relevance to the analysis that is underway in other graph windows. High city crime rate areas identi ed using a boxplot can be highlighted on a map of city census tracts that contain socio-economic data. Areas near to one another having similar levels of deprivation but markedly different crime rates would be of interest to detect and investigate more closely.

There are circumstances where map-to-map brushing may be helpful. A population cartogram provides a map where areas are proportional to the number of people in each area and may provide a better spatial framework through which to view, for example, the spatial aspects of social structure (Dorling, 1994, 1995). To achieve this, the cartogram transforms the physical area the user may be familiar with.

Contiguous and non-contiguous forms of cartogram have been developed (Schulman et al., 1988; Olson, 1976). However the viewer may lose their orientation and sense of where they are on a cartogram so that in Cleveland s terminology the cartogram, on its own, fails the table look-up test.

However, linkage to a familiar map (where the linkage is switched on and off as requested) will restore that orientation. Section 6.1.

2 noted the importance of dynamic interactive manipulation of graphics parameters to scienti c visualization. The display responds immediately to user-speci ed changes that can be implemented through a slider bar. Dykes (1997) and Andrienko and Andrienko (1999) illustrate the role of dynamic interactive manipulation of the display parameters of maps to support the exploration of spatial data.

Flexibility can be achieved for example in terms of choice of symbols, class intervals for choropleth maps and use of colour. One of the bene ts is being able to make dynamic visual comparisons from which.
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