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  • 1.  Product how-to: Hotspot Density Mapping using MapInfo Pro

    Employee
    Posted 11-27-2017 07:46

    Hotspot analysis helps to identify the events of statistical significance in order to define areas of high cluster occurrence high versus low. The designation of an area as being a hotspot/coldspot is therefore expressed in terms of statistical confidence. The analysis uses vectors (not rasters) to identify statistically significant clusters in data.

    Some Statistics Behind Hotspot Density

    Statistical significance are measured through Z scores and P values. Z scores are measures of standard deviation whereas P-values are probabilities. Both these statistics are associated with the standard normal distribution. The higher (or lower) the Z score, the more intense the clustering. A Z score near zero means no spatial clustering. A high Z score and small P value for a feature indicates a significant hot spot whereas a low negative Z score and small P value indicates a significant cold spot.

    Why Hotspot Density Maps are Useful

    Hotspot mapping has advantages over other methods of aggregating point data, such as spatial clustering, choropleth mapping, and quadrat mapping as the process focusses on highlighting areas which have higher than average incidence of events.

    How to create Hotspot Density Map using MapInfo Pro

    Input Parameters

    Three parameters need to be specified for Hotspot Density Map creation. These are the following:

    • Search Radius: Specifies whether spatial parameters are defined in cell units or distance units. The units should be supported by MapInfo Pro, for example, the options for Distance unit include: US Survey feet, yards, rods, chains, miles, nautical miles, millimeters, centimeters, meters, inches, links and kilometers. If you choose Distance, you need to select a distance unit from the Distance Unit drop-down list.
    • Grid Cell Size
    • Shape of the kernel density function: The shape of the search neighborhood will be dictated by the type and distribution of the input data. The following shape of kernel density are available:
      • Spherical - Performs an equidistant radial search within the search neighborhood. For optimum performance, it is advisable to keep the search distance small. A value less than or equal to 5x of the output cell size is usually sufficient. Spherical search is best applied when the variation in the spatial distribution of the input data is considered isotropic.
      • Elliptical - Performs an elliptical search within the specified search neighborhood. An elliptical search is best applied when some directional anisotropy is known to exist in the spatial distribution of the input data.

     



  • 2.  RE: Product how-to: Hotspot Density Mapping using MapInfo Pro

    Employee
    Posted 11-27-2017 02:58

    Process steps for creating Hotspot Density Map

    Click Create Raster in the Interpolate group to display the interpolation methods and select Hotspot Density

    Hotspot_Density_Map1

    The Create Raster dialog displays. 

    Hotspot_Density_Map2

    From the Input File drop-down list select the file or click to browse and select the required input data file. When the input file is open, from the Select Columns drop-down list, select one or more input data columns. It lists all the columns in the input file and allows you to select the column that contains input data points. The selected column will be used in the interpolation process.

    Select Hotspot Density method from the Select Method drop-down list. You can now specify the required parameters (For more information on available parameters, refer to Hotspot Density Method Options). 

    Hotspot_Density_Map3

    In the Method Options, specify whether spatial parameters are defined in cell units or distance units. If you choose Distance, you need to select a distance unit from the Distance Unit drop-down list. Define search mode to provide information on input data points within the search neighborhood. A default search radius is calculated for you.

    In the Raster Geometry section, specify the cell size and raster bounds for the output raster. If required, click More Options to specify category and sub category of the output projection. If the input file is MapInfo .TAB, projection values are read from the input file, which you can override here.

    Hotspot_Density_Map4

    In the Output File box enter the name you want to specify for your output file. Click to browse to the location in your computer to save the output file and select the required output file format. The values in Output Settings are controlled by the Raster Preferences dialog; however, you can override those settings here. Select the Display Output File check-box, if you want to open the output file in the Map window on completion of the operation. Click Process to start the hotspsot density method interpolation process. The task will then be added to the Task Manager where you can monitor the progress. On completion of the operation, the hotspsot density raster displays in the map window.

    Hotspot_Density_Map5

     



  • 3.  RE: Product how-to: Hotspot Density Mapping using MapInfo Pro

    Posted 11-27-2017 09:28

    Do you have any best practices creating a hot spot density map using the thematic mapping option, i.e. for those of us that do not have the MI Pro Advanced license??



  • 4.  RE: Product how-to: Hotspot Density Mapping using MapInfo Pro

    Employee
    Posted 11-27-2017 15:04
      |   view attached

    Hi Chris

    Both thematic maps and density maps are of great help in exploring spatial data and represents important aspects of the data. But it's important to keep in mind the inherent limitations of the different methods.

    The earthquake magnitude image below shows the two map types to see why they produce different views of the same data. [1: Earthquake Magnitude Data; 2: Point Ranged Thematic Map; 3: Hotspot Density Map]

    Thematics_Hotspot_difference

    With MapInfo Pro Advanced you can easily switch back and forth between thematic and density mapping methods in a few steps.

    It would be very narrative to expect concrete and consistent results for detecting and presenting patterns in data using thematics map but certain design considerations can be taken.

    • Thematic mapping is ideal to show change across a geographic landscape within enumeration units such as country, state, county, postcode etc and should not be used to identify data patterns at large scale such as neighborhoods, localities etc.
    • It should be used as a way of geographically visualizing locations so that patterns of higher than average occurrence of things such as crime, traffic accidents, species occurrence or store locations can emerge
    • Should be used for
      • Management/executive audience
      • Fast and easy decision making
      • Convey actionable information
    • Should have
      • Strong visual hierarchy and grammar
      • Follow Standard Mapping Conventions (5-6 colors)

     

    Hope this helps!

    -Thanks