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Pitch

its all about the data: GPS the logging, Satellite imagery of forests, Government reports of the actors, and math to put it all together.


Description

Summary

Uniquely modified gps units deployed to harvesting equipment in the field (anything from axes to excavators) combined with an exhaustive forestry database and proprietary GIS platform enable Catenaut to verify and measure almost anything related to forest harvests. Landowner information, real-time harvest profitability, stand stocking level, harvest legality, restricted party screening, forest type, canopy species, wildlife impact, sustainable harvest rates, - whatever metrics are important to you, we can measure them, in real time, for less than the cost of a cell phone.

 


What actions do you propose?

it's easy - if some of the major companies would just buy a satellite gps tag and stick it on the loggers in their supply chain then our platform can do the rest. They dont even have to use our gps tags - anything will do - even a bluetooth Tile.  The social action that has to occur is more pressure on the major forest product consumers; P&G, Nestle, Wal-Mart, McDonalds, etc to demonstrate verifiable sustainability in their forest product supply chains. Right now most of them say something along the lines of, "we purchase certified fiber" but there are dozens of high quality studies that suggest fiber certification does not ensure sustainable harvesting practices. Fiber certification is a good and necessary first step but it is not the answer. Data is the answer.  


Who will take these actions?

Any number of people could implement this change; procurement managers, government officials who determine concession area boundaries, brokers and dealers. IF there was a compelling reason to actually eliminate illegal logging form their supply chains then people from all walks of life could take appropriate action, but as one major multinational VP of sourcing told me, "that's a nice idea, and I can see how it would work, but you see, if we have proof that forest products from illegal logging were entering our supply chain then we would be legally obligated to stop buying from that supplier and isolate those products in our inventory. You can see how that would cause an unacceptable disruption to our operations and potentially expose us to legal liability as well." 


Where will these actions be taken?

The system could be used to monitor deforestation and prevent concession area over harvest in Indonesia, Brazil, parts of Africa - anywhere in the world where illegal logging and deforestation is a concern.


How much will emissions be reduced or sequestered vs. business as usual levels?

I know that creating data in the forest and combining it with all the other data available can prevent illegal logging. I have no way of knowing the value of that. How much is the Sumatran elephant worth? Who's to say. However, judging from the response I've received from nearly every major multinational, it's something less than the price of a cell phone. 


What are other key benefits?

We invested so heavily in this system and created such a large partner network because we strongly believe that science and engineering could save the Orangutans. That was the mission, and it's since grown somewhat, but undoubtedly, preventing a 200 year old tree from becoming toilet paper has value. 


What are the proposal’s costs?

Each satellite GPS unit costs about $150, and the data costs are about $30 a month. The database of all the laws, concession areas, shape files etc is about $20 a month and any reports are just the cost of our time. About $200 each. All in cost for a typical paper mill would be $4,500 for the equipment and $920 a month for the information. 


Time line

The timeline is now. Anyone can go buy a satellite gps unit and link it into our database. it's easy.

 


Related proposals

I dont know of anything like what we've created. There are a lot of companies that offer pieces of it, satellite imagery monitoring, logger tracking, harvest auditing, etc. but I dont know of anyone else who has stitched all patchwork pieces together into a complete quilt like we have. 


References

Geoghegan, J., Villar, S. C., Klepeis, P., Mendoza, P. M., Ogneva-Himmelberger, Y., Chowdhury, R. R., ... & Vance, C. (2001). Modeling tropical deforestation in the southern Yucatan peninsular region: comparing survey and satellite data. Agriculture, Ecosystems & Environment85(1), 25-46.

McCracken, S. D., Brondizio, E. S., Nelson, D., Moran, E. F., Siqueira, A. D., & Rodriguez-Pedraza, C. (1999). Remote sensing and GIS at farm property level: Demography and deforestation in the Brazilian Amazon.Photogrammetric engineering and remote sensing65, 1311-1320.

Harper, G. J., Steininger, M. K., Tucker, C. J., Juhn, D., & Hawkins, F. (2007). Fifty years of deforestation and forest fragmentation in Madagascar.Environmental Conservation34(4), 325.

Vance, C., & Geoghegan, J. (2002). Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data. Agricultural Economics27(3), 317-332.

Rahman, M. M. (2004). Estimating Carbon Pool and Carbon Release due to Tropical Deforestation Using High-resolution Satellite Data.

Mayfield, H. (2015). Making the most of machine learning and freely available datasets: a deforestation case study.