Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees

Price, B.; Gomez, A.; Mathys, L.; Gardi, Oliver; Schellenberger, A.; Ginzler, C.; Thürig, E. (2017). Tree biomass in the Swiss landscape: nationwide modelling for improved accounting for forest and non-forest trees Environmental Monitoring and Assessment, 189(3), pp. 1-14. Springer Netherlands 10.1007/s10661-017-5816-7

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Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Agricultural, Forest and Food Sciences > Abteilung Masterstudien

Name:

Price, B.; Gomez, A.; Mathys, L.; Gardi, Oliver; Schellenberger, A.; Ginzler, C. and Thürig, E.

Subjects:

S Agriculture > SD Forestry

ISSN:

0167-6369

Publisher:

Springer Netherlands

Language:

English

Submitter:

Simon Lutz

Date Deposited:

10 Dec 2019 09:50

Last Modified:

10 Dec 2019 09:50

Publisher DOI:

10.1007/s10661-017-5816-7

ARBOR DOI:

10.24451/arbor.8389

URI:

https://arbor.bfh.ch/id/eprint/8389

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