Supercomputers make Bluesky’s National Geographic datasets a reality

May 7, 2015

 

Aerial mapping company Bluesky is exploring the power of supercomputers to process and deliver 3D maps, comprising trillions of data points, for a range of environmental applications.  Working with HPC Midlands and experts from the Karlsruhe Institute of Technology (KIT) in Germany, Bluesky has already been able to devise workflows to create region-wide maps of sun shadow – of particular interest when considering the effectiveness of solar panel installations. Bluesky is also exploring the use of high performance computers to scale up existing workflows to help create and maintain other key datasets such as the National Tree Map, air pollution models and thermal heat loss surveys.

 

“Having invested in the very latest survey equipment, we are now generating more detailed data covering larger areas than at any other time in the history of aerial surveying,” commented James Eddy, Technical Director of Leicestershire based Bluesky International. “Our nationwide annual programme of data capture results in around hundreds of terabytes of raw data every year.”

 

“Processing this amount of data on conventional computers is simply not time or cost effective,” added Simon Schuffert, Research Associate at KIT. “However, by partnering with HPC Midlands and Bluesky we have proven scalable workflows through a ‘divide and conquer’ approach made possible by parallel programming.”

 

“New sensors such as those employed by Bluesky and the analysis techniques devised by KIT are generating larger volumes of data than ever before,” added James Earl-Fraser, Business Development Associate at HPC Midlands. “In order to derive value there is a growing requirement for automatic and efficient processing such as that offered by high performance computers.”

 

The Bluesky partnership initially developed an open source shadow analysis programme that calculated the amount of shade a 3D surface structure is subject to over a day, month or year. With ground sampling distances of 25 square centimetres this level of detail would, for a country the size of Great Britain, mean processing over 3.5 trillion elevation points! The dataset created by the new shadow analysis could theoretically be used to accurately predict effectiveness of solar panels as small as those attached to parking ticket machines, for example, or monthly and annual sun exposure for agricultural areas.   

 

Having proved the power of high performance computing for solar energy mapping projects, the partnership is exploring other applications, including the update and maintenance of Bluesky’s National Tree Map and projects to map air pollution and heat loss from buildings.

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