Projects at Forest Remote Sensing
Last changed: 15 October 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” (https://www.ksla.se/etikettarkiv/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
More information about the project: Adding value of non-wood forest product as part of ecosystem services: Improving berry yield prediction and mapping
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: Anna-Lena Axelsson
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
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
