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  • Location Analytics: Mapping, Computational Geoanalytics and Spatial Statistics with Spotfire® and Spotfire® Data Science

    An overview page of all Geoanalytics capabilities of Spotfire.


    Sample Spotfire Map Charts visualizations.


    Location Analytics capabilities include visual analytics in Spotfire®, geocoding and itineraries from Spotfire® GeoAnalytics, and calculations are done in Spotfire® Data Science via Spotfire®'s data function and displayed on the Spotfire® map chart.

    Spotfire®'s map charts can display multiple layers of information.  These layers can include points, lines, WKB objects like shapefiles and polylines, and TMS and WMS layers that show e.g. geology, live weather, or customized images, terrain, or other information. The ordering of these layers can be re-arranged to control which features appear in front of others. The transparency of individual layers can also be controlled; also, each layer can be configured to only be visible at certain zoom levels.  For example, a map can be configured so that as you zoom in, new layers become visible and other layers would disappear. Map layers with points, lines, and WKB  objects can be configured to respond to marking.  Points, lines, or WKB objects on a map that are marked and refreshed by a data function provide a convenient round-trip means of interacting with data and calculations using the map interface.  Some examples of templates that include Spotfire® Data Science functionality include interactive contour lines, heatmaps, polygons, territory calculations, and route optimization. These templates are available for download from the Community Exchange.

    Spotfire® Maps - Using Data Science Algorithms with Location Analytics

    Spotfire®'s map visualization capabilities provide spatial visualization and analytics for everyone.  You can visualize multiple types of data (point locations, shapefiles, WMS, TMS) through multiple layers in a single map visualization.   

    You can invoke algorithms written in R, Python, and Spotfire® Data Science under the hood to perform calculations both within and between your map's data layers. These calculations can produce additional map layers to illustrate results such as contours, heatmaps, optimal driving routes, and territories. These layers are dynamically linked to the underlying Data Science algorithm and can respond to marking and filtering of the map, providing powerful interactive location analytics.

    These capabilities are invoked using data functions. Examples of data functions that you can download from our Community Exchange and try yourself are listed below. You can also create your own new data functions in R, Python, and Spotfire® Data Science to drive new map visualization capabilities or general results in Spotfire®.



    Next Steps with Spotfire® Location Analytics

    Webinars, Articles, and Dr. Spotfire®

    Creating custom Shapefiles for Spotfire®

    Create custom Shapefiles for Spotfire®, to overlay any background image. Learn how to use open-source QGIS software to digitize an image, then use the image as a background in a Spotfire® visualization together with the new clickable shapefile that appears on top of the image.

    Optimizing Supply through Location Analytics

    Location Analytics represents a major opportunity to better organize resources and gain a more cost-effective and market-sensitive flow of goods. Applying equally to manufacturers, distributors, and retailers, the combination of user-friendly, map-based data visualization paired with sophisticated statistical techniques has delivered a breakthrough in logistical planning and the ability to quickly react to changing patterns of demand, demography, and even weather.

    Analytics Meetups

    More Topics using Spotfire® Location Analytics

    Using Geocoding

    Spotfire® automatically places markers if your data contains geographic coordinates (latitude and longitude). If your data contains no geographic coordinates, Spotfire® places markers or features based on the recognized administrative boundary where Spotfire® can display most of your data. Spotfire® supports world-level boundaries and country-level boundaries.

    Expanding Spotfire® list of supported boundaries

    In the case your desired administrative boundaries are not supported, you can still expand Spotfire® coverage using public data or your own data.

    Using Coordinate Reference Systems (CRS)

    Spotfire® can display data with geographical coordinates (latitude, longitude) or (x, y) data specified by a projected coordinate reference system (CRS). The CRS dialog is available for each layer within a Map Chart visualization so that layers with different CRS can be mixed and matched.

    The list of available CRS in the CRS dialog is divided into two broad categories:

    • Geographical Coordinate Reference Systems: Data is defined as a 3D surface and measured in latitude and longitude. These specify the underlying reference ellipsoïd that the latitude and longitude values reference. An example would be WGS84 or North American Datum 1983 (NAD83).
    • Projected Coordinate Reference Systems: Data is defined by a flat 2D surface and measured in units of meters and feet. It combines underlying Geographical CRS and a transformation to a flat plane for producing the map. Often data such as a Shapefile uses x,y coordinates specified in meters or feet from some local reference, that has been produced through a projection (e.g. Universal Transverse Mercator, Polar, or a State Plane projection). This combination is referenced with an EPSG code that can be looked up in the Spotfire® CRS dialog. Shapefiles are very commonly used; to use these, you will need both the underlying Geographic Coordinate System (e.g. NAD27) and the specific UTM projection used, usually given through a Zone number.

    Transforming CRS

    Using Image Layer

    Spotfire® enables adding any image to a map visualization and putting markers specified by coordinates on the image. You can map data over zoomable and draggable images to visualize geographical data or non-geographical data such as human body maps, wafer chips, semiconductors schematic maps, process diagram maps, and many more...

    Extending Spotfire® Map Visualizations

    Voronoi Polygons


    Voronoi polygons let you represent point data with polygons that fill (tesselate) an area.  When fewer polygons than data points are used, the polygons represent aggregated values and can provide a reduction in variability.  Two use cases are illustrated: The first use case aggregates measurements at point locations to a static visualization. The second use case calculates Voronoi polygons with an index to the original data. This second case lets the user adjust filters and observe the tile colors adjust in response.



    Download from Community Exchange

    Heatmaps are useful in providing a high-level summary to visualize overall patterns in spatial data. Studying raw point data for patterns can be difficult owing to uneven spatial coverage, and random variability in the values. Heatmaps start by calculating a smoothly varying surface to represent the data. This surface is represented by a colored heatmap and contours.



    Download from Community Exchange

    Density plots are useful in providing a high-level summary to visualize overall patterns in the density of spatial data, much like a two-dimensional histogram density. Studying raw point data for patterns can be difficult owing to uneven spatial coverage. Density plots start with the calculation of a smoothly varying surface to represent the density of the data. This surface is represented by a colored heatmap and contours.



    Download from Community Exchange

    This Data Function generates a contour plot as a feature layer on a map chart.  The download contains a data function you can import into your own .dxp and a template you can bring your own data into.



    Download from Community Exchange

    Two-dimensional binning with hexagonally-arranged bins of (x,y) inputs. Useful in Spotfire® for simplifying an (x,y) scatter plot with a large number of points. Returns the count of the incoming points in these bins. Additionally, if an optional value column is also provided, it also returns the mean value in the bins. The results can be used in a Spotfire® scatter plot visualization that serves as a heat map of the density of points. Also if the optional 3rd value is used, a Spotfire® scatter plot visualization can be constructed for the mean value across cells. This data function serves as a wrapper for the functionality contained in the hexbin R package.

    Points in Polygons


    For each point in a table of locations defined by Latitude and Longitude coordinates, identify its corresponding enclosing polygon contained in a separate table. Returns a column that contains the enclosing polygon identifier to append to the point location table.

    Useful Data Functions

    A collection of useful data functions has been developed that can perform a variety of tasks such as transforming the Coordinate Reference System (CRS) used by point data or a shapefile, either by EPSG code or PROJ.4 string, see the full collection here.

    • Calculate areas of polygons
    • Convert polygon coordinates to polygon geometries
    • Draw circle with a fixed radius on geographic coordinates
    • Draw rectangles with fixed sizes on geographic coordinates
    • Transform Coordinate Reference System collection

    Geo-enable data with Spotfire® GeoAnalytics

    Spotfire® GeoAnalytics is a cloud-based, high-performance, and scalable geospatial technology to geo-enable data and develop location-based applications.

    Geocode data at address-level precision

    Geocoding is the process of translating physical addresses into latitudes and longitudes (forward geocoding) or translating latitudes and longitudes to physical addresses (reverse geocoding) in order to enable your data to be displayed and analyzed in a geographic context (in a Spotfire® map visualization).

    Spotfire® GeoAnalytics enables geocoding large datasets worldwide with address precision using:

    • Geocoder API: Transforms an address to latitude and longitude coordinates
    • Reverse Geocoder API: Transforms latitude and longitude coordinates to addresses
    • Batch Geocoder API: A batch geocoder request where addresses are specified in an array. Both forward and reverse geocoding methods are accepted by the service and can be mixed.

    Compute distances, routes, and optimized routes

    Spotfire® GeoAnalytics enables loading an itinerary or computing distance between two points or between many waypoints. In the case of an itinerary with multiple way points, the service will automatically compute the fastest route to take to go to each way point with a define or non-defined start point.

    Find locations by distance or time to go

    Spotfire® GeoAnalytics enables to calculate and render the maximum area around a location for given time to go or for a given distance. This allows us to find locations by route distance or the amount of time it will take to walk or drive to.

    Embed maps in your own custom applications

    Spotfire® GeoAnalytics offers a free JavaScript Library (GeoAnalytics.js) to publish maps on your own custom applications and visualize spatial data over it.

    Content Manager

    Spotfire® GeoAnalytics Content Manager enables geocoding of data with street-level precision by importing a table containing addresses or by geocoding addresses manually. You load the data to be geocoded and then visualize it on top of the map.

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