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Forest Height Estimation Using Sentinel-1 Interferometry. A Phase Unwrapping-Free Method Based on Least Squares Adjustment

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Geomatics for Green and Digital Transition (ASITA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1651))

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Abstract

Forest height is a fundamental parameter in forestry. SAR interferometry (InSAR) has been widely used to retrieve digital elevation models (DEM), which are designed to provide a continuous representation of Earth topography, including forests. The ordinary InSAR framework requires a further phase unwrapping step in order to recover unambiguously the actual topography over the entire scene. The latter was proved to fail over vegetation due to low coherence values and therefore all algorithms tend to avoid these areas during the unwrapping, making InSAR-derived DEM over vegetation very unreliable. In this work, an alternate technique was coupled to least squares adjustment (LSA) with the aim of retrieving accurate forest heights avoiding phase unwrapping. It was computed entirely using free available Sentinel-1 data and SNAP ESA software. A mean absolute error equal to 2.6 m was found and it is consistent to the one estimated by LSA theoretical uncertainty. Preliminary outcomes suggest that proposed approach could be a valid alternative to retrieve forest height based on free data/software constituting an example of technological transfer of SAR technology into forest operative sector.

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Author information

Authors and Affiliations

  1. Department of Agriculture, Forestry and Food Sciences, University of Torino, 10095, Grugliasco, TO, Italy

    Samuele De Petris & Enrico Borgogno-Mondino

  2. Institute for Applied Remote Sensing, EURAC Research, Bolzano, BZ, Italy

    Giovanni Cuozzo & Claudia Notarnicola

Authors
  1. Samuele De Petris
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  2. Giovanni Cuozzo
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  3. Claudia Notarnicola
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  4. Enrico Borgogno-Mondino
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Corresponding author

Correspondence to Samuele De Petris .

Editor information

Editors and Affiliations

  1. University of Torino, Grugliasco, Italy

    Enrico Borgogno-Mondino

  2. University of Pisa, Pisa, Italy

    Paola Zamperlin

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De Petris, S., Cuozzo, G., Notarnicola, C., Borgogno-Mondino, E. (2022). Forest Height Estimation Using Sentinel-1 Interferometry. A Phase Unwrapping-Free Method Based on Least Squares Adjustment. In: Borgogno-Mondino, E., Zamperlin, P. (eds) Geomatics for Green and Digital Transition. ASITA 2022. Communications in Computer and Information Science, vol 1651. Springer, Cham. https://doi.org/10.1007/978-3-031-17439-1_18

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  • DOI: https://doi.org/10.1007/978-3-031-17439-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17438-4

  • Online ISBN: 978-3-031-17439-1

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