Startups and the emerging market for data science in forestry

 Today, we’ll wrap up our look at how data science, machine learning and AI are transforming the forestry sector by exploring the market and startups in the field.


Forest products like timber, pulp, herbs and others contribute at least half a trillion dollars to the global economy each year. Now, while the word “forest” typically conjures up an image of a place that’s remote, hard to access and undisturbed - the truth is that a lot of forest products come from agro-forests. These are forests that are planted, harvested and maintained similar to crop fields - and thus, have similar issues to those seen in the agricultural sector. However, while there’s been a lot of interest in the agricultural sector on using data science, machine learning and artificial intelligence to solve problems, the forestry sector has been slower to catch on. But that’s been changing in the last couple of years - with Scandinavian countries and Canada leading the way. And the major developments have been in agro-forests or commercial forests or plantations. 


The term that’s used for data science and digital technologies in forestry is “precision forestry”- and it covers a number of different aspects of forests and forest operations. It includes developing machines, sensors and algorithms to more precisely harvest trees and timber, building models and monitoring forest health through remote sensing data, flying drones to identify fires, better breeding programs through genetics, and developing models of soil, ecosystem and tree health at a very granular scale.

(Source: McKinsey and Company, 2018)


The precision forestry market was estimated at close to $4 billion in 2019 and is forecast to grow to $6 billion by 2024 at an annualized growth rate of 9%. While much of the growth to date has been in North America and Europe, it is expected that Asia and Africa will be the major drivers over the next couple of decades as countries in the region adopt and develop novel technologies and practices.



Another sector where data science is being used in forestry is in monitoring the extent of forest loss, reforestation and forest degradation for untouched, old-growth forests like the Amazon rainforests or the forests in the Congo Basin. However, these applications are usually developed by non-profit organizations and government agencies rather than commercial entities - so the algorithms and data are usually free, easy to access and display. 


It’s still an extremely young field, so there are comparatively fewer startups as opposed to the energy or agricultural sectors. Many of them are located in European countries and are heavily focused on harvesting timber more efficiently, and using satellite imagery to monitor forest health. The best known among them are Xylene and Timberter in the smart harvesting business,SilviaTerra,  Satelligence and Dendra Systems in the climate change, reforestation and data science business, and , Tesselo and Terramonitor in the disaster and satellite data segments of the market. Of course, large forestry companies like Weyerhaeuser in the US and Scion in New Zealand are hiring aggressively and building data science teams for agro-forestry applications. Similarly, Google and Microsoft are also using cloud computing, their large remote sensing datasets and partnerships with universities and non-profits around the world to develop interesting applications of AI-based forestry for public good. 


Of course, with the pandemic impacting construction activities around the world, there’s been a slight slowdown in funding for forestry startups and activity in the space. However, it’s an extremely young and vibrant sector that’s expected to grow rapidly over the next decade - so keep an eye on what’s happening in the space!

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