The World Wonders Project

 

There are a lot of amazing sites around the world, and thanks to Google’s various technologies such as Street View and Google Earth they’re easier to explore than ever. Google has now taken 132 historic sites from around the world and put them together into a single showcase called the World Wonders Project.

 

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The project covers major sites that we all know about, such as Stonehenge and Pompeii, and also covers lesser-known sites that are quite amazing, such as the Historic Villages of Shirakawa-go and Gokayama. This video shows a bit more about how it works:

 

 

The sites all include Street View imagery (much of which was captured using a Street View Trike), photos, videos, and 3D models in Google Earth.

The New Google Earth Imagery – February

Google has just pushed out a fresh batch of new imagery to a variety of places around the world.

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Due to the new “Pretty Earth” imagery, it’s more difficult to spot fresh imagery. Also, the imagery this month arrived in Google Maps before Google Earth, which threw us off a bit. In any case, here are some of the locations that GEB readers have identified as having fresh imagery. Many of them were made aware of the new imagery via the Follow Your World notifications, which we certainly encourage you to sign up for.

Here is the list of updated areas we know about so far:

  • Canada: Villeneuve
  • Italy: Vernazza
  • Romania: Deva
  • Spain: Villacariedo
  • United Arab Emirates: Dubai
  • United States: California (Chino, Eureka), Illinois (Decatur), Louisiana (Alexandria), North Dakota (Minot), Tennessee (Johnson City, Kingsport)

The Value of Spatial Data Services (SDS)

The end of life for MapPoint Web Service and Multimap is quickly approaching (November 18, to be exact), so it’s a good time to start considering migrating to Bing Maps. This blog focuses on why the use of the Bing Maps Spatial Data Services (SDS) should be considered as your migration solution.

With MapPoint Web Service there are customer data sources and FindNearby queries. You may have considered spatial features found in SQL Server (or SQL Azure). SQL Spatial provides a robust spatial database and is a great solution for complex queries, like find near a route, find in a polygon, etc. If you are using MapPoint Web Service polygon features, SQL Spatial is a good way to go. For those of you with simple queries, SQL Spatial can certainly be used, but it comes at an additional cost and solution complexity (for example, you need to create an API to query data).
 


 
The Bing Maps SDS APIs provide the ability to upload and query your point data, like buildings or stores. Here are some significant reasons to migrate from MapPoint Web Service to Bing Maps SDS.

1)    SDS is a RESTful API. It’s easy to understand and use without WSDLs and SOAP parsing. Like other Bing Maps APIs, the REST APIs support JSONP, thus they can easily be used client side without cross-domain issues.

2)    SDS runs on the Bing Maps Content Delivery Network (CDN) (see figure 1.) When you upload your data using the Data Source Management APIs your data gets automatically replicated to the 19 CDN nodes. When using a client-side query, the request gets routed to the nearest CDN node, which reduces latency and significantly increases performance while adding the reliability that comes with such massive data replication.

Figure 1 – Bing Maps Content Delivery Network nodes

3)    SDS Supports Bounding Boxes. In many applications (store locators, for instance), organizations will often use a FindNearby query (“Give me all the locations within a certain radius”). This is fine for initial queries, but what if the user wants to pan around? FindNearby queries typically don’t work well. Does the user really care about what was nearby their initial query? And does the user really care about all the locations within 20 miles if they have zoomed in to a very specific area? In addition to a FindNearby query, the SDS Query API also supports bounding box queries. This means that as the user pans/zooms the map, you can query based on the user’s new view and load data for the precise area they want to see.