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Large-area virtual forests from terrestrial laser scanning data

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Number of pages3
ISBN (Electronic)978-1-5090-3332-4
Publication statusPublished - 3 Nov 2016
Publication typeA4 Article in a conference publication
EventIEEE International Geoscience and Remote Sensing Symposium -
Duration: 1 Jan 1900 → …

Publication series

NameIEEE International Geoscience and Remote Sensing Symposium Proceedings
ISSN (Electronic)2153-7003


ConferenceIEEE International Geoscience and Remote Sensing Symposium
Period1/01/00 → …


Combining virtual forests with radiative transfer is a powerful tool to calibrate and validate ground-based, airborne and spaceborne sensors. In this set-up, we can control and calculate all aspects of the forest structure and the simulated signal, which would not be possible using measured data only. Terrestrial laser scanning (TLS) enables us to measure forest structure directly with high detail. We present a processing chain that uses TLS data as input data to assess the end-to-end traceability of various in situ LAI and fAPAR products via radiative transfer modelling. Tree reconstruction from TLS data is used to represent the explicit 3D forest structure in radiative transfer models.


  • forestry, geophysical image processing, image reconstruction, remote sensing by laser beam, 3D forest structure, TLS data, absorbed photosynthetically active radiation, airborne sensor, fAPAR product, ground-based sensor, in situ LAI, large-area virtual forest, leaf area index, radiative transfer model, spaceborne sensor, terrestrial laser scanning, tree reconstruction, Biological system modeling, Data models, Laser modes, Sensors, Solid modeling, Three-dimensional displays, Vegetation, 3D modelling, Calibration and Validation, Forestry, Terrestrial LiDAR, radiative transfer

Publication forum classification

Field of science, Statistics Finland