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November 8, 2025Mires and PeatOpen Access

Biomass prediction of Typha latifolia on a paludiculture site by combining structural and spectral features from UAS data

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Authors

CHChristina HellmannBBBernd BobertzFHFabian Hübner

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Overview

Analysis demonstrates effective biomass prediction for Typha latifolia using DSM and multispectral data, suggesting enhanced vegetation monitoring.

Key Points

  • Biomass prediction reached R2 values of 0.65-0.71, showing effective modeling of Typha latifolia growth.
  • Utilizing digital surface model data significantly improved biomass estimates compared to multispectral alternatives.
  • Observational analysis employed in-situ harvests and UAS measurements over an 8.5 ha rewetted site.
  • Highlights the necessity for precise vegetation monitoring in sustainable land-use practices post-rewetting.

Cite This Study

Hellmann et al. (2024) studied this question.

synapsesocial.com/papers/690e8b75a5b062d7a4e739d8https://doi.org/10.19189/map.2023.cm.sc.2455998
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