Mapping Data

I have been researching map data to display maps inside the desktop application frontend for nomadexplorers.com. I hit pay dirt. I found several NASA data sources. It’s got me thinking about other possibilities for future additions to nomadexplorers.com and other fun projects. Here are some notes one a few of the data sources I have found.

Earth image data can be provided by OnEarth WMS (web mapping service), a global image mosaic of the earth, produced from over 8200 individual Landsat7 scenes. Each scene is about 500mb in size. These images have been collected during 1999-2003. The highest resolution image has a ground relative resolution of 15 meters, or 50 foot. The mosaic contains all nine spectral bands of the Landsat7 ETM+ instrument. OnEarth includes Blue Marble: Next Generation which is beautiful earth image data. One of the neat things about BMNG is that you can request image data by month so you can visualize seasonal changes on the earth. This will definitely come in handy for many projects. I will have more to come on using OnEarth WMS.

For terrain data there are a couple sources I have found so far. From what I have found the most complete data is the SRTM project. The Shuttle Radar Topography Mission obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database of Earth. SRTM consisted of a specially modified radar system that flew onboard the Space Shuttle Endeavour during an 11-day mission in February of 2000. The second terrain data source I have found is GLOBE (The Global Land One-km Base Elevation Project). I have more research to do on the terrain data sources and the benefits of each.

Probably the most immediately useful is the World Wind Java SDK. This open source project makes it easy to write Java applications that use NASA satellite data and the World Wind visualization technology. The Java SDK is relatively new which combines alot of what I was thinking of implementing from scratch from the resources mentioned above. Since it will save so much time, I will start my desktop application with this. However I am excited of the possibilities that all this data provides for experimentation.

As I study more about each one I will post further information and tutorials about using this data for your own applications.