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The Laegeren site: an augmented forest laboratory combining 3-D reconstruction and radiative transfer models for trait-based assessment of functional diversity


Morsdorf, Felix; Schneider, Fabian D; Gullien, Carla; Kükenbrink, Daniel; Leiterer, Reik; Schaepman, Michael E (2020). The Laegeren site: an augmented forest laboratory combining 3-D reconstruction and radiative transfer models for trait-based assessment of functional diversity. In: Cavender-Bares, Jeannine; Gamon, John A; Townsend, Philip A. Remote sensing of plant biodiversity. Cham (Switzerland): Springer, 83-104.

Abstract

Given the increased pressure on forests and their diversity in the context of global change, new ways of monitoring diversity are needed. Remote sensing has the potential to inform essential biodiversity variables on the global scale, but validation of data and products, particularly in remote areas, is difficult. We show how radiative transfer (RT) models, parameterized with a detailed 3-D forest reconstruction based on laser scanning, can be used to upscale leaf-level information to canopy scale. The simulation approach is compared with actual remote sensing data, showing very good agreement in both the spectral and spatial domains. In addition, we compute a set of physiological and morphological traits from airborne imaging spectroscopy and laser scanning data and show how these traits can be used to estimate the functional richness of a forest at regional scale. The presented RT modeling framework has the potential to prototype and validate future spaceborne observation concepts aimed at informing variables of biodiversity, while the trait-based mapping of diversity could augment in situ networks of diversity, providing effective spatiotemporal gap filling for a comprehensive assessment of changes to diversity.

Abstract

Given the increased pressure on forests and their diversity in the context of global change, new ways of monitoring diversity are needed. Remote sensing has the potential to inform essential biodiversity variables on the global scale, but validation of data and products, particularly in remote areas, is difficult. We show how radiative transfer (RT) models, parameterized with a detailed 3-D forest reconstruction based on laser scanning, can be used to upscale leaf-level information to canopy scale. The simulation approach is compared with actual remote sensing data, showing very good agreement in both the spectral and spatial domains. In addition, we compute a set of physiological and morphological traits from airborne imaging spectroscopy and laser scanning data and show how these traits can be used to estimate the functional richness of a forest at regional scale. The presented RT modeling framework has the potential to prototype and validate future spaceborne observation concepts aimed at informing variables of biodiversity, while the trait-based mapping of diversity could augment in situ networks of diversity, providing effective spatiotemporal gap filling for a comprehensive assessment of changes to diversity.

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Additional indexing

Item Type:Book Section, not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Life Sciences > General Agricultural and Biological Sciences
Physical Sciences > General Environmental Science
Physical Sciences > General Engineering
Physical Sciences > General Earth and Planetary Sciences
Language:English
Date:2020
Deposited On:02 Oct 2020 12:25
Last Modified:03 Oct 2020 20:00
Publisher:Springer
ISBN:978-3-030-33156-6
OA Status:Hybrid
Publisher DOI:https://doi.org/10.1007/978-3-030-33157-3_4

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