Projects at Forest Remote Sensing

Last changed: 06 September 2021

Can spruce bark beetle infestation in forests be detected in time series with radar measurements?

The project objective is to investigate whether it is possible to detect spruce bark beetles infestations in forests with time series of measurements from a radar tower at Remningstorp.

Contact: Johan Fransson
Financier: Hildur & Sven Wingquist's Foundation

Collection of data and further development of database at Remningstorp as "super test site" for the benefit of future forest remote sensing research

The project objectives are to collect remote sensing and field data and further develop the existing database at Remningstorp as a "super test site" for the benefit of future forest remote sensing research.

Contact: Johan Fransson
Financier: Hildur & Sven Wingquist's Foundation

Detection of spruce bark beetle attacks from new remotely sensed data and continuity in data from Remningstorp

How early in the summer can spruce bark beetle attacks be detected from time series of satellite images and radar data?

Contact: Eva Lindberg
Financier: Hildur and Sven Wingquist's Foundation

Estimating forest resources and quality-related attributes using automated methods and technologies , ForestQuality

Forest inventory, which records not only the basic attributes of trees, but also the forest state and the yields of the forest, provides the fundamental reference data for all decision-making that are relevant to human interventions in forest ecosystems, ranging from management decisions at the landscape scale to harvest planning in forest stands. High benefits can be obtained if quality of individual trees , indicated by attributes such as stem curve, size distribution, height of the

lowest dead branch, crown base height and maximum branch diameter can be characterized, and if accuracy and spatial coverage of volume estimations can be improved. In this project, we digitalize forests, automate forest inventory methodologies using mobile laser scanning and harvester-collected data, and calibrate the plot level wood quality and volume estimates. This is a project within the research programme “Tandem Forest Values” (

Contact: Johan Holmgren
Financier: Kempestiftelserna

Forest inventory using low altitude airborne laser scanning

Kontakt: Henrik Persson
Finacier: Bo Rydin Foundation

Improved understanding of the influence of reference data errors to remote sensing based estimates

The project intends to develop a framework for quantifying different error sources in the field references, and furthermore correct for these, such that correct remote sensing accuracies can be reported.

Conact: Henrik Persson
Financier: Bo Rydin Foundation and Kempe

Improving berry yield prediction and mapping

Adding value of non-wood forest product as part of ecosystem services.

The aim of the project is to develop methods for predicting forest berry yield for large areas applying auxiliary information and seasonal data and create models to forest planning system.

Contact: Inka Bohlin
Financier: Formas

Mistra digital forest

Contact: Håkan Olsson

National forest data lab

The National Forest Data Lab is an open platform for the entire forest sector. Businesses and public authorities are the intended main users and collaborators, however, the platform can also be used by, for example, academia, research institutes, interest groups and other interested parties. The National Forest Data Lab provides an infrastructure of digital programmable interfaces for accessing satellite data, forest related geodata, AI-methods and wall-to-wall maps. To facilitate data-driven innovation, new models, features and tools that enable analysis of changes, new wall-to-wall maps and AI analysis are being developed.

Contact: Johan Fransson
Financier: Vinnova through Swedish Forest Agency

New forest maps with tree species information from time series of satellite data

Development of methods to create tree species maps from time series of satellite images and radar data in combination with multispectral laser scanning data.

Contact: Eva Lindberg
Financier: Skogssällskapet

New space digital economy innovation center

The main objective of the “KvarkenSpaceEco” project is to establish Kvarken Space Center, a long-lasting innovation center to boost space-based business and innovation in the Kvarken region.

Contact: Johan Fransson
Financier: EU through Vasa University

Webpage KvarkenSpaceEco

Tree species classification from remote sensing - next generation forest maps for ecology and management

Development of methods to create tree species maps from different types of remotely sensed data: satellite images, radar data, laser scanning data, matched aerial images.

Contact: Eva Lindberg
Financier: Formas

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