Wednesday, August 26th, 2015 at 12:04 pm by ba3 — Category: Uncategorized

Altus 2.0 offers more efficient runtime data support which can simplify the code you write for serving up your data to Altus. The new approach is less error prone and more scalable and allows you integrate new kinds of GIS data as standards and formats change. Pictured here:

• Custom wind information
• Custom polygon data
• Custom turbulence data

Altus offers several ways to put custom assets on the map. One way is pre-processing data on a server into an optimized format for Altus using the Altus Server pipeline and sending binary packages to a device. But if putting a server pipeline in place won’t do, there is another way of providing the data at ‘run-time’. In other words, providing the data to Altus on the fly as needed, and pulling it from your own files, other formats, or third parties.

This concept is called a TileProvider in Altus 1.0. You write code that derives from our base METileProvider and your code serves up data as needed by Altus. This approach is powerful but assumes that you will do all the low-level housekeeping with regards to threads. Additionally, the TileProvider system does not apply to clustered marker layers in Altus 1.0, which have their own special API for on-device creation.

In Altus 2.0 we have introduced a simpler approach that narrows the scope of work (and code) for getting a single tile’s worth of data. Now you simply implement a TileWorker (which has a single function). The thread management and queuing are handled by a TileFactory. This natural separation works well and simplifies the concept and code of custom run-time data providers.

TileFactories are, in essence, TileProviders, but you don’t have to create these (unless you want to). They are provided for you. All you have to do is create a TileWorker that implements a single function for you specific custom data.

Additionally, in Altus 2.0 this model is set up to work with all data types:

• Markers
• Terrain
• Raster
• Vector

So, if you can’t leverage the efficiency of the Altus Server pipeline and the cross-platform Altus package format, and you need to use your own data and logic, you can get it into Altus with a minimal amount of code on your part.