Presentation done at Plantation Management 4.0 | 24th-25th February 2021 | Virtual Conference. Organized by Trueventus.

1. How precision/digital
technologies are impacting the
forestry sector
Marcos Wichert, MSc
Vice President,
Plantation Forest Management, Stora Enso

2. Forest is our
foundation
for value creation
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3. Marcos Wichert – Plantation Management 4.0.
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
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1. Introduction to the forestry sector
2. Concepts of precision/digital forestry
3. Cases of precision forestry technologies
1. Eco-RFID for packaging
2. Harvester sensors data capture and usage
3. Drone and LiDAR for forest inventory
4. Remote sensing for forest monitoring
5. Eucalyptus nursery automation
6. Mechanical planters with on-board technologies
4. Challenges and future needs

4. Introduction
Forestry sector overview - definitions
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
7% planted forests Native species are 56% of planted forests
Some definitions:
• Forestry is related with the planted forests sector, to provide wood as raw material for several industries
• Silviculture is related with the operations done to establish and plant a new forest crop (e.g. agriculture)
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5. 5
Introduction
Forestry sector overview – planted forest area
Source: Pöyry 2018
Source: FAO 2009. Planted forests: uses, impacts and sustainability
Source: FAO 2009. Planted forests: uses, impacts and sustainability
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

6. Introduction
Forestry sector overview – Eucalyptus plantations
Asia/Oceania
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
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Source: Chris Harwood, CAETS congress in Uruguay 2018

7. Introduction
View of Eucalyptus plantation for pulpwood in Brazil
(Veracel)
• Mosaic plantations in the landscape
• 100% planted forest certified by the Forest
Stewardship Council (FSC)
• Sustainable wood production using only 49% of
total area for Eucalyptus plantations (51% as natural
forests conservation areas, non-productive)
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
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8. Introduction
Stora Enso’s productive forest land areas at end 2020
Source: Stora Enso 2020 annual report
One of the biggest private forest owner in the world, with 2,34 M ha of productive
forest land. Annual harvested volume of 9,3 M m3. Total land and biological asset
value in balance sheet EUR 7.3 billion.
Marcos Wichert – Plantation Management
4.0. Kuala Lumpur 25/Feb/2021
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9. Biocomposites
Paper
3.1 million tonnes
Market pulp1
2.6 million tonnes
Corrugated packaging
and other packaging
solutions3
0.5 million tonnes
Containerboard
1.3 million tonnes
Consumer board
2.7 million tonnes
Other products4
Externally
delivered residuals
1.6 million tonnes
Lignin
Bark and
harvesting
residuals for
energy
Wood products
5.3 million m3
Production in 2020
Wood1
35.9 million m3
Fossil fuels
7.2 TWh
External
biomass energy
5.2 TWh
Water
561 million m3,
of which 97%
was returned
back to
the local
environment
Purchased
electricity2
6.5 TWh
Purchased pulp
and paper for
recycling
2.2 million tonnes
Pigments, fillers,
starch, and other
chemicals
2.1 million tonnes
Efficient use of materials in circular bioeconomy
Externally delivered
electricity/heat/
steam
1.0 TWh
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
Total
Source: Stora Enso 2020 annual report

10. 10
Introduction
Planted forests roundwood main uses

11. Introduction
Planted forests roundwood global production estimates
2030
Interconnected global wood and fiber flows
Source: Pöyry 2018
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

12. Introduction
Forest sector serving various industries’ current and
future needs
Source: Pöyry 2018
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
New bio-materials can replace plastic
Replacing plastic
in food packaging
Replacing plastic
in food packaging
DuraSense® biocomposites

13. Concepts of Precision Forestry
Planted forests main value chain
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
Land acquis. &
management
Nursery
Plantation and
maintenance
Harvesting
and roading
Logistics
Wood
sales/purch.
Plantation continuous
supporting processes
Monitoring Planning
Main operational/production processes

14. Concepts of Precision Forestry
Planted forests data flow in the value chain
We want to plan and control better
the operations to maximize value
and minimize costs!
We need data for precision forestry!
Standardized data!
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

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Concepts of Precision Forestry
Forestry 4.0 vision and main aspects
https://www.youtube.com/watch?v=r4vhLQ8OEP0
Source: FPInnovations, Canada, 2017
Collecting data digitally from different sources
All data collected is
sent remotely to a
database in the cloud

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Concepts of Precision Forestry
Forestry 4.0 vision and main aspects
Source: FPInnovations, Canada, 2017
Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

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Concepts of Precision Forestry
Forestry 4.0 vision and main aspects
UNMANNED TRUCKS
Source: FPInnovations, Canada, 2017

18. Cases of Precision Forestry
Eco-RFID for packaging tracking (Stora Enso example - Europe)
https://www.youtube.com/watch?v=vSF5oPy6vKE
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19. Cases of Precision Forestry
Data from harvesting machine sensors – operator
performance
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

20. Cases of Precision Forestry
Machines data dashboard – production, maintenance, etc.
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

21. Cases of Precision Forestry
Harvested forest productivity map, data machine sensors
Example productivity map,
individual tree volume data from
Harvester head sensor
Harvested area 6,1 ha
Volume 223,8 m3sub/ha
Basal area 24 m2/ha
Tree volume 0,53 m3sub
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
Source: Marcos Wichert, 2015

22. Cases of Precision Forestry
Drone and LiDAR for Stora Enso forest and log yard inventories
Forest health monitoring
Log piles stocked volume
measurement - update
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23. Cases of Precision Forestry
Autonomous drone forest inventory and terrestrial LiDAR
https://www.youtube.com/watch?v=GL3EnZdEOsE
https://www.youtube.com/watch?v=2zadTtCadeI
Autonomous drone flight and LiDAR data capture
below the forest canopy (under development in NZ)
Use of ground portable LiDAR for forest inventory plot
measurement (operational in New Zealand by Interpine)
Source: Interpine, New Zealand
Source: Interpine, New Zealand
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

24. Cases of Precision Forestry
Monitoring Stora Enso forest changes with satellite
imagery
Windfall damage
Unhealthy forest spots
25 Marcos Wichert – Plantation Management
4.0. Kuala Lumpur 25/Feb/2021

25. Cases of Precision Forestry
Remote sensing mapping forest growth performance
Drone image productivity map using Normalized Difference
Vegetation Index (NDVI) Satellite image productivity map using NDVI
Source: Marcos Wichert, 2015
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

26. Cases of Precision Forestry
Eucalyptus nursery automation (Fibria, now Suzano,
example – Brazil)
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021
https://www.youtube.com/watch?v=vInK8kZ7jog&t=169s
New technologies and
innovations adapted from
other sectors (mainly
flowering sector from the
Netherlands).

27. Cases of Precision Forestry
Mechanical planters available with on-board technologies
J.Hartwhich, simple planter (no
onboard tech.) - Uruguay
Risutec planter - Finland
Bracke planter -
Sweden
Komatsu-Bracke planter - Brazil (development project)
Novelquip planter prototype - S.Africa
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28. Cases of Precision Forestry
Focus to aggregate more operations in one machine
Example 6x1 operations of Risutec spot planter head with on-board guidance system and GPS recording
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

29. Challenges and future needs
Need to increase mechanization level before precision forestry
Annual % change 2015 2016 2017 2018
Inflation (CPI) 3,4% 3,0% 3,6% 4,0%
Min. Wage - Riau 10,5% 11,6% 8,2% 8,7%
Increasing manual labour cost will
stimulate more silviculture mechanization
(example Riau-Indonesia)
Indonesia South Africa
China
Brazil
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

30. Challenges and future needs
How to measure mechanization level in forestry companies-
benchmarking
Example of a Forestry Research Institute (IPEF) survey with some
Brazilian companies, with 8 levels of mechanization.
Example of planting operation mechanization level
Overall mechanization level of the companies
MANUAL
MANUAL
Level 1 Level 2
Level 1 Level 2
COMPANY
COMPANY
Average
Average
SEMI-MECH.
SEMI-MECH.
Level 3 Level 4
Level 3 Level 4
MECHANIZED
MECHANIZED
AUTOMATED
AUTOMATED
Level 5 Level 6
Level 5 Level 6 Level 7 Level 8
Level 7 Level 8
Source: Guerra, S.P.S, IPEF, 2020 https://www.ipef.br/publicacoes/livros/IPEF-PCMAF-LevantamentoMecanizacao.pdf
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

31. Challenges and future needs
The skill shift happening with more digitalization and
automation
Source: McKinsey & Company, May 2018
The table below shows how the labor market skills are expected to shift, under 5 main categories and in different
industries and job sectors, as a result of adoption of artificial intelligence (AI) and various automations.
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

32. Challenges and future needs
New technologies increase exponentially and new skills are
needed
Source: Dominguez, J., Sep 2018. Engineering Education for XXI.
1. Complex problem solving
2. Coordinating with others
3. People management
4. Critical thinking
5. Negotiation
6. Quality control
7. Service orientation
8. Judgement and decision making
9. Active listening
10. Creativity
World Economic Forum (2015) World Economic Forum (2020)
Difficult for Universities to catch up with the
speed that new technologies are introduced.
As the world becomes more complex, new skills and competencies are required from the
workforce for the successful performance of the companies in the future.
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

33. Challenges and future needs
Critical components to successfully implement new
technologies
• Right skills and competencies
• Capability building
• Change management
• Transform more data available into intelligence, improving decision making
• Critical thinking and complex problem solving capacity
• After sales technical support and solutions development (new tech. provider)
20%
30%
50%
Precision technologies (digitalization)
Processes
People
• Integration in current business processes and IT database systems (cloud)
• Data quality, availability and updating schedule
• Data analytics (algorithms, big data, machine learning, AI)
• Data and computation platform (data collection and transmission)
• Connectivity to send data
• Visualization and restitution tools
• Data engineering
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

34. Challenges and future needs
Main topics of publications and articles about precision
forestry in the internet
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

35. Challenges and future needs
Main technology drivers for the future of precision forestry
Robots &
automation
Increased autonomous machine operation in the field and robots in
the nurseries
Cloud systems
Real time communication between operational systems.
Big databases in open systems
Augmented
reality
Support from augmented reality for
machine maintenance, and display of
operational standards/manuals
Cyber-security
Guarantee data safety in open systems
and integrated networks, and also data
transfer from machines
IoT and
connected
sensors
Network of smart forestry sensors with
machines. Multi-directional communication
between networked objects
Optimization &
simulation
Optimization systems utilizing real-time data updates from database.
Simulation of best solution considering the impact in the whole value chain
Big-data &
analytics
Real time decision making support and
optimization based on full evaluation of
available data from all systems (e.g ERP, SCM,
CRM, etc.) and machine data
Source: Adapted from McKinsey & Company, June 2018. Precision forestry a revolution in the woods.
Data
integration
Horizontal and vertical data integration based on
data transfer standards. Needed before a fully
automated value chain implementation is done
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Marcos Wichert – Plantation Management 4.0.
Kuala Lumpur 25/Feb/2021

36. The renewable future
grows in the forest
Thank you!

37. marcos.wichert@storaenso.com
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