As 80 percent data created by organizations has a spatial component and this can be quick and easily comprehended when a geographical element is added to the problem. Spatial background is being added to the non spatial data (the attribute data in the form of tables as shown above) by selecting the Visualize –> Map option from the menu as shown in the figure below.
All the tabular information is shown on a map by a process called Geocoding. The concept behind Geocoding is Fusion tables understands and associates all the names of the countries (Country column in the table) to the ground co-ordinates on a geo referenced map. On the other hand, if the table contains latitude and longitude instead of the textual information, it understands and map all these points to the correct location on map and this process is called Reverse Geocoding. As evident from the map below, it shows all the other information such as Arrivals, Percent change etc by click on the push pins on the map.
Figure 4. Google Map interface to the Top tourism data.
The map below displays distinctive darker and lighter tone maps based on two parameters: spatial information (in our case, it is the Country column) and numeric information (Arrivals (millions) column). This visual effects gives a very quick insight on the information needed from the data. This option is only available in the Classic version of the FT (This is the reason, why I chose Classic version for the demonstration).
Figure 5: Intensity Map for Top tourism data.
Fusion Tables Functions
Conventional databases work on SQL statements, need to memorize the right syntax to execute the basic operations whereas most of the basic operation can be done graphically especially for novice users. Though FT does not do aid to solve complex problems but FT functionality could be sufficient enough to visualize and understand the common day to day problems.
This option is used when we would like to filter the data based on the objectives. For example, I would like to see the countries whose touristic Arrivals more than 60 millions for economic study or setting for a business etc. Essentially, using the below SQL statement is used to answer my query as France in databases like the MqSQL etc.
SELECT * FROM Top toursium WHERE Arrival(millions)>= 60
The query can be performed as shown in the below figure by simple selection the options in the drop-down menu and the results can be viewed in any form as discussed in the above section. This could be useful for more complex tables and analysis.
Figure 6. Filter function on Top tourism data.
Aggregate functions: Sum, Average, Maximum, Minimum on the columns of a database allows to do various analytical studies and reports.
For example, the data pulled from the Wikipedia page which is shown in the above section has columns like the Rank, Country, UNWTO Regional market etc. If a tourist business firm wants to analysis the tourists flow at different geographic levels (City—province—-country—-continent). SQL statement and SUM followed GROUPBY functions is used in the column Region to aggregate the International tourist arrivals in Europe.
SELECT SUM (International tourist arrivals (2011)) FROM Untitled Spreadsheet GROUPBY UNWTO Region
The view is used for selective choosing of the columns based on the requirements and saving it as a separate database. This functionality can be used on a large table, multiple tables. In FT it is just done by checking on the selected columns that is necessary for the project objective, without any syntax requirement as below:
CREATE VIEW Trail AS
SELECT Name, Length, End point1 , End point 2 FROM Tourism
Wikipedia (http://en.wikipedia.org/wiki/Long distance_trails_in_the_United_States) has the list of long distance trails in the USA. All the data can be pulled onto spreadsheets and can make a table to query and see all the hiking trails of our interest on the map in a very easy and efficient way.
Figure 7. Fusion Tables map interface display of the longest trails in the USA.
A spatial background to the non spatial data can be a visualize treat for the users to comprehend easy and quickly. This GIS tutorial is intended to aim for the novice users to be able to make use of the power of mapping available existing spatial data using Google Fusion Tables in a simple way without much knowledge of Geoinformatics nor database expertise or programming skills. Depending on the data attributes, requirements, data size and so forth, Fusion Tables can be used for basic mapping needs which can be instrumental as a freely available resource.
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