Axional Geospatial

Most data have a component that can be tied to a place: an address, postal code, global positioning system (GPS) location, census block, city, region, country, etc. Geographic mapping lets you visualize, analyze, create and manage data with a geographic component. And you can build compelling maps that help you visualize patterns, trends and exceptions in your data.

Using a spatial database to store objects like points, lines and polygons using geometry data types offers a significant advantages in front of classic mapping solutions where the view is oriented to analyze transactional or statistical data. The new geographic tools can reveal trends and patterns that are otherwise hidden in the alphanumerical data.

Axional Geospatial allows organizations to easily implement spatial extensions and simplifies the process of building geoespatial applications.

Key points

• A WEB form designer allows users write database querys and represent it on maps.
• A geospatial SQL grammar allows users write database independent geospatial SQL statements.
• Location tracking capabilities integrated in the client software.

Data analisys

Multi Layers

Axional Geospatial can show multiple layers of independent data sources in a map. For instance, a company might be interested in crossing distinct data in the map, such as the location of its customers and sociogeographical data (average income, age…) of the area (state, district, postal code…).

With Axional Geospatial, each layer is defined as a SELECT statement written int the XSQL-GEO syntax. Below there’s an example of a geospatial query of a layer:

<select>
    <columns>
        countries.name,
        <nvl>deficit2009,0</nvl>        colref,
        abs(<nvl>deficit1998,0</nvl>)   deficit2008, abs(<nvl>deficit1999,0</nvl>)   deficit2009,
        abs(<nvl>deficit1998,0</nvl>)   deficit2010, abs(<nvl>deficit1999,0</nvl>)   deficit2011
        <geo.transform srid='4326'>
                <geo.buffer>
                    <geom1>
                        <geo.transform srid='utmzone(countries.the_geom_city)'>
                            countries.the_geom_city
                        </geo.transform>
                    </geom1>
                    <dist>100000*sqrt(abs(eu_gdp.deficit2009))</dist>
                </geo.buffer>
        </geo.transform>    gdp_shape
    </columns>
    <from table='eu_gdp' >
        <join table='countries'>
            <on>eu_gdp.gid =  countries.gid</on>
        </join>
    </from>
    <where>
       countries.region = 150 AND
        <geo.intersects>
            <geom1>the_geom</geom1>
            <geom2>
                <geo.polygon>
                   <coords>
                          #lng_min #lat_min, #lng_min #lat_max,  #lng_max #lat_max, #lng_max #lat_min, #lng_min #lat_min
                   </coords>
                   <srid><geo.getSRID>the_geom</geo.getSRID></srid>
                </geo.polygon>
            </geom2>
        </geo.intersects>
    </where>
</select>

For each data layer certain attributtes can be set:

• Label: A label identifying the layer that will appear in the legend.
• Visibility zoom range: A minimum and a maximum zoom ranges in which the layer is visible. Outside the range the layer becomes invisible.
• Initial visibility: A layer, although being in the visible range, can be set to be initially hidden. It can be made visible dynamically by the user.
• Category: Layers can be groupped into categories.
• Render types for geometries: Usually, spatial databases have 3 kinsds of geometric types: point, line and polygon. But sometimes, due to the nature of the data it can be more useful to draw the geometries in a specialformat. Axional Geospatial provides special renderers such as:
  • Heatmap: Suitable for drawing densities.
  • Clustering: Useful when having a large number of markers
  • Gps track: The choice for drawing GPS points as a pth.
• Symbology: Allows the definition of symbols of the map. That is, the colors applied to the geometries, opacity, borders, image markers (when geometries are points) etc..
• Info window: The text that will appear in a box when clicking a geometry. The text can be a static string, or a template with references to columns in the row clicked or can be a call to a XSQL-Script in the server returning HTML code.
• Tracking cursor: A tracking cursor is another SQL query used to iterate the layers. When a tracking cursor is defined, the layer SELECT statement is supposed to have variables in the SQL condition. For each row returned by the tracking cursor, the layers sql is executed with thr variables passed by the cursor. That means that for every row in the cursor a new layer is generated.

Thematic mapping

A choropleth map is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income. Choropleth mapping shows statistical data aggregated over predefined regions, such as counties or states, by coloring or shading these regions.

Colored maps are not always the best way to display values, since large regions are emphasized much more than small ones. To address this issue, instead of drawing complex country shapes, circles can be easily drawn The area of each circle is proportional to the absolute value of the data.

The success of many thematic maps, especially choropleth maps, depends upon understanding how we manipulate colors to systematically encode our geographic data using the three dimensions of color: hue, lightness, and saturation

Axional Geospatial comes with 3 predefined categories of set of color palettes to suit the different nature of the data being represented:

• Qualitative color scheme: contains different hues that keep lightness and saturation constant, should be used for nominal data. (ie: un-ordenable categories, not numerical data
• Sequential color scheme: Any sequence that is dominated by changes in lightness can be used with orderable (rankable) categories (low/medium/high) or with numerical data
• Diverging color scheme: should only be used when your data has a natural mid point such as a zero (e.g., positive and negative change/growth) or if you want to compare places to something like the national average (e.g., county data showing places that are above and below the national average for a variable like per capita income)

In addition to the predefined color palettes shipped with Axional Geospatial, developers also can define their own palettes to suit their map requirements. Moreover, even end users can dynamically change the color palette being used in the map by easily clicking the palette in the legend.

Special renderers

Heat Maps

The heatmap is one of the most useful and powerful data-analysis tools available in business intelligence. It is a visualization feature that presents multiple rows of data in a way that makes immediate sense by assigning different size and color to cells each representing a row.

If the data points are valued, that is, each point is associated with a value, the graphical representation consists of regions known as areas of same value which can be filled with different colors or just be delineated by contour lines or both.

Heat Maps illustrate the density and distribution of point data, generated in real-time over pan and zoom maps. Point influence (radius) and colour swatches can be configured to give the most appropriate overlays for your data

Clustering

Some applications are required to display a large number of locations or markers. Google Maps mash-ups can suffer performance problems when trying to display a large number of markers at any one time.

To overcome this poor performance, the information displayed on the map needs to be simplified, for example, by using some kind of clustering.

Clustering is the process of grouping closely positioned locations together and representing them with a single pushpin. When you zoom in those locations will become further apart and will separate into their own pushpins. The client side part of “Client Side Clustering” is clustering the data on the fly in JavaScript rather than going back to the server to request more data. When you have a few thousand or less location to display on the map client side clustering can be significantly faster than server side clustering and also cuts down on request to your server thus making your application more scalable. The following images are an example of the same approx 6000 pushpins before and after being clustered.

GPS tracking

Gps tracking is a special layer renderer aimed at drawing GPS tracks. The data input must be gps point coordinates. The renderer takes care of connecting the coordinates with lines and also draws a circle representing the accuracy of the gps measurement

Location tracking

As many of the data stored in a database can be georeferenced it becomes posible to analize any related information projected on a map. For example. If you have customers you can see your sales by area in a map joining the geometry locations associated with a customer with the sales stored in sales tables. Instead of see a classic report of sales by region you can see those sales in a map. Even more. You can zoom in the map to see more detailed information and even go to a concrete customer and see their invoices.

You can easily implement Location Based Services (LBS) for Android mobile devices. The LBS services use geographic information to serve a mobile user and enable service organizations to improve their service operations by allowing them to make decisions and take actions based on real-time location information:

• Improved customer service
• Increased field workforce utilization
• Reduced scheduling & dispatcher labor

Axional mobile LBS enables services, such as:

• Maps and navigation for mobile users/employees.
• Resource tracking with dynamic distribution: Vehicles, service people, rental equipment, fleet scheduling.
• Information services: Locating the nearest business or service, such as the nearest banking cash machine, User generated content.
• Proximity-based notification: Targeted advertising, Favorite list.

Using Axional mobile location tracker services, your database will receive tracking position of your users or vehicles that can be easily be used to report things such as distances, time spent in a delivery, advice customers about the location of a purchase, optimize routes, etc.

Mobile devices

Android mobile devices can be used either to query and view information stored in our databases or to capture location information and push them into our systems.

Databases

Axional Geospatial works with

• Informix Spatial datablade
• DB2 Spatial Extender
• Oracle Spatial
• Postgres PostGIS

Key features

• Form designer to query and represent alphanumeric + geospatial data
• Data capture from Android devices
• Native SQL spatial queries
• Independent XML/SQL PostGIS grammar
• Geoespatial database migration tool from any to any supported databases

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