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.

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

De Petris, Samuele;Borgogno-Mondino, Enrico
2022-01-01

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.
Geomatics for Green and Digital Transition. ASITA 2022
Springer
Communications in Computer and Information Science
1651
251
262
978-3-031-17438-4
978-3-031-17439-1
https://link.springer.com/chapter/10.1007/978-3-031-17439-1_18
Forest height SAR Interferometry Least squares adjustment
De Petris, Samuele; Cuozzo, Giovanni; Notarnicola, Claudia; Borgogno-Mondino, Enrico
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1877366
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