TUT Inverse Problems


TUT Inverse Problems research group is organizing a very informal small-scale workshop for discussing new interdisciplinary possibilities in tree/forest modelling. The idea is to combine advanced instrumentation, mathematical methods and plant models. The participants include experts from the fields of laser scanning, functional-structural plant modelling, forest science and mathematical modelling.


The agenda of the workshop will be built around a list of research interest and open research questions suggested by the participants. The first day of the workshop will consist of gathering such a list, but we encourage participants to send questions in advance with the form below. Suggestions received before the workshop will be listed here:

  1. How can Quantitative Structure Models (QSMs) be utilized in the future, e.g., on large areas?
  2. QSMs enable fully automatic species recognition from TLS data. How can this be utilized?
  3. Should we store QSMs in a public database, and if so, what would be the applications of such a database?
  4. Faster/simpler/non-realistic models of tree growth for more effective calibration/tuning of the algorithms (Bayes Forest) producing Stochastic structure models (SSM).
  5. Genetic clone studies: relation between SSM (computer tree clones generator) and real genetic tree clones. How much structural variability is possible in computer and real clones? Calibration of SSM’s.
  6. Methods for estimating the leaf area density/leaf area index at individual tree scale and forest plot scale from TLS/ALS data.
  7. Issues with LAI and foliage profile estimation with TLS.
  8. Retrieving growth development parameters from crown analysis (rhythm ratio, dormancy, branching distribution laws) with ALS.
  9. How can we estimate tree development status (as defined by architectural botany) within heterogeneous forests from Aerial Lidar range data acquisitions?

More extensive information about the topics can be found below in the Material section. If you are a presenter or you otherwise feel that the participants should read some material before the workshop, please contact the organizers and we will add your material to the list.


There are currently 20+ people confirmed to participate.

Mathematical modelling / Organizers

Mikko Kaasalainen Tampere University of Technology
Ilya Potapov Tampere University of Technology
Pasi Raumonen Tampere University of Technology
Markku Åkerblom Tampere University of Technology

Forest remote sensing

Sanna Kaasalainen National Land Survey of Finland
Alan Strahler Boston University
Kim Calders University College London
Jose Gonzalez de Tanago Menaca Wageningen University
Eric Casella Forest research (UK)
Mark Danson University of Salford
Fadal Sasse University of Salford
Rachel Gaulton Newcastle University

Forest sciences

Raisa Mäkipää Finnish Natural Resources Institute
Timo Pitkänen Finnish Natural Resources Institute
Mikko Peltoniemi Finnish Natural Resources Institute
Kaisa Nieminen Finnish Natural Resources Institute
Aleksi Lehtonen Finnish Natural Resources Institute
Juha Immanen University of Helsinki
Meinrad Abegg University of Zurich / WSL


Risto Sievänen Finnish Natural Resources Institute
Frederic Boudon CIRAD / Inria Virtual Plants
Grégoire Vincent CIRAD / UMR AMAP (FR)
Marc Jaeger CIRAD / UMR AMAP (FR)


When travelling from abroad your flight will most likely take you to Helsinki. From there you'll have the option to travel the remaining 200 km to Tampere either by train, bus or a plane.

The trains are operated by VR and you can buy tickets and see schedules here.
Regular bus
Bus lines are operated by various companies but you can buy tickets to all of them from Matkahuolto. Timetables are available on the same site. Usually, on long-distance buses you can also buy a ticket from the driver.
Economy bus
There is a company that operates a cheaper bus connection between big cities such as Helsinki and Tampere. The company is called OnniBus and you can see the timetables and book tickets here. Tickets need to be booked in advance.
You can probably get the tickets from the same place you got your ticket to Helsinki. The flight distance is really short, so if you would have a long wait between flights, its probably faster to take the train or a bus.


The venue for the workshop is in the centre of Tampere in a building called Pikkupalatsi. This property was originally build as a modest residence for the first superintendent of the Finlayson factory back in 1897. Since then the building has been used an apartment building and even office space.

Nowadays the top floor is used as an apartment, and the first and basement floors can be rented for various types of events. The first floor has been restored to its original appearance and consists of several individual rooms. The basement houses the sauna and pool area and also a pool room (biljards, not swimming) with a table more than a hundred years old.

The street address of the Pikkupalatsi is Hämeenpuisto 7 which is just a walking distance away from the city centre. The bus line 3 drives though the main street, Hämeenkatu, and stops at Pikkupalatsi, and the name of the bus stop is appropriately Pikkupalatsi.


We suggest that every field gives a general introduction and an overview of open questions in a short free-form presentation of < 30 minutes. Proposed introductions include the following:

Topic / Field Presenter(s) Slides Size
Tree modelling: TLS, QSM, applications Pasi PPTX 10.2
Stochastic structural plant models Ilya PPTX 8.4
forest laser scanning instruments Kim & Alan PDF 27.0
multiwavelength scanning Mark & Fadal PPTX 8.5
forest inventory Meinrad PDF 2.3
plant morphogenesis and architecture Frederic PDF 17.9
forest genetics Juha & Kaisa
forest growth models Mikko P. PPTX 2.0
FSPM Risto PDF 2.4
forest ecology, carbon issues Raisa PPTX 7.8

The presentations will not be the main focus of the workshop. They should only offer a compact introduction to the field, and thus we encourage people to collaborate on the presentations to minimize their number. Each presentation should end on a list of open research questions, which will be collected and used as the agenda for Wednesday.

Start Tuesday, 7th June End
09:45Morning coffee at Pikkupalatsi10:00
10:00Opening of the workshop10:30
10:30Introductory presentations12:00
13:30Presentations continue15:30
15:30Question list refining16:30
19:00Self-planned evening program19:00
Wednesday, 8th June
08:45Morning coffee at Pikkupalatsi09:00
09:00Information about the day09:15
09:15Discussions in groups12:00
13:30Group discussions continue14:30
14:30Travel to Viikinsaari15:20
16:00Group discussions continue19:00
19:00Dinner in Ravintola Viikinsaari21:00
21:30Return by ferry to Laukontori21:50
Thursday, 9th June
08:45Morning coffee at Pikkupalatsi09:00
09:00Summary of discussions10:00
10:00Collaboration planning12:00
13:30Planning continues15:30
15:30Ending of the workshop15:45

Material on topics

This section lists background information on topics to be discussed.

QSMs: large areas; applications and prospects

Maple tree QSM

Quantitative Structure Models (QSM) are cylinder based models reconstructed from terrestrial laser scanning data. These models contain the geometric properties of a tree as well as the topological branching structure. For a simple overview of QSMs, please see the 3D Forest Information animation. For interactive examples of the models, visit the online Tree Gallery. For more details, see the paper Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data.

We are interested in how QSMs could be utilized with large areas, and what the future applications could be. For applications where illustration is key, we've developed alternative ways to visualize QSMs not as cylinders but continuous Bézier surfaces. Visualizing reconstructed tree models video demonstrates visualization with these surfaces with textures and leaves sampled from distributions based on the QSM.

Stochastic structure models

Stochastic structure models (SSM) are structure models augmented with stochastic rules. In particular, we've augmented the LIGNUM model with stochastics received from reconstructed quantitative structure models. For details, see the paper Data-based stochastic modeling of tree growth and structure formation.

Stochastic structure model diagram

We've found that SSMs can be used to create realistic plant models based on data and thus accounting for stochastic influences. SSMs allow modelling of plant growth which is one of our open research areas.

Stochastic structure model diagram

Tree model database

QSMs offer a compact representation of the structure of a tree, and thus are ideal to be stored in relational databases. We've been working on a demonstration on such a database. Currently we store information in forest plot, tree, tree model, branch and cylinder tables, and enable the computation of, e.g., volumes, areas, and size distributions.

Is all the relevant information in the database, should something be added? Where would you utilize a tree database? What are the likely use cases?


Below is a list of plans that were made during the workshop. The list only contains the plans that were reported with the provided template. If you would like to add something to the list, please contact the organizers.

Funding proposal

Finding useful traits using models, QSM and clone studies

Basic idea

Better (breeding) features (more wood) by changing genetics.

Find a mutant (lack of apical dominance for an example) phenotype differs from normal. Test that mutation is inherited by mendelian way (genotype is reason for strange phenotype). MAP mutated gene(s). Make marker for gene. Use elite form for breeding to make more valuable/higher biomass forest.

Objectives and timeline

  • Effective search of wrong/bad mutants in the forest (ALS).
  • Models calibration to the known mutants.
  • Existing birch mutants can be already utilized for modelling and proper phenotyping. Modelling normal and mutant can be done in close future. National screening for new apical dominance mutants could be tried much later distant future.
  • Clone plot QSM analysis

Total: 5-10 years

What exists?

  • Clone birches sites
  • Known described mutants


Predicting breeding value of mutants or interesting traits

Basic idea

  • Phenotyping of known mutants - structural characteristics
  • Characterizing physiological traits of mutants
  • Develop v. good predictive model incorporating deep physiology (potentially ensemble of multiple models)
  • Incorporate forest management model to predict stand development
  • Test models on known stand development data, then incorporate mutant/variant traits.
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