Climate change is changing our attitude to the need for forest data. Few years ago it was published in Nature how many trees there are in the world. The estimate was based on 425 000 manually measured field sample plots and satellite data, and they concluded that the global number of trees is approximately 3.04 trillion. Obviously, it would be scientifically important to have a technology in which all trees could be automatically counted, their growth would be automatically measured and their CO2 intake and carbon sequestration would be automatically measured in real-time, even hourly - with a minimum amount of manual measurements. According to present knowledge, this has been considered as quite impossible to implement due to lack of accurate data, lack of technology to perform this and lack of adequate field reference techniques. 

The objective of project HPC Carbon is to develop the missing mapping technology in which all individual trees (IT) could be automatically counted, characterised and mastered in time using HPC and by merging different-scale, award-winning laser scanning technologies. The project will demonstrate the concept feasibility in Finnish boreal forests; the long-term impact of the project is in setting an example framework after which similar large-scale references can be established all over the world in different biomes. We are using various laser scanning techniques, since they cover country-level coverage for IT detection (data amount 50TB) and provide change information that could be calibrated with field reference (data amount 200+ TB). Finally we have knowledge at tree level, from stand characteristics to growth and quality and to hourly intaked carbon. All of these are beyond the feasible scope of processing by existing workstations, and, thus, the research activities would greatly benefit from HPC for these tasks.