Forest height is a key parameter in forestry. SAR interferometry (InSAR) techniques have been extensively adopted to retrieve digital elevation models (DEM) to give a representation of the continuous variation of the Earth’s topography, including forests. Unfortunately, InSAR has been proven to fail over vegetation due to low coherence values; therefore, all phase unwrapping algorithms tend to avoid these areas, making InSAR-derived DEM over vegetation unreliable. In this work, a sensitivity analysis was performed with the aim of properly initializing the relevant operational parameters (baseline and multilooking factor) to maximize the theoretical accuracy of the height difference between the forest and reference point. Some scenarios were proposed to test the resulting “optimal values”, as estimated at the previous step. A simple model was additionally proposed and calibrated, aimed at predicting the optimal baseline value (and therefore image pair selection) for height uncertainty minimization. All our analyses were conducted using free available data from the Copernicus Sentinel-1 mission to support the operational transfer into the forest sector. Finally, the potential uncertainty affecting resulting height measures was quantified, showing that a value lower than 5 m can be expected once all user-dependent parameters (i.e., baseline, multilooking factor, temporal baseline) are properly tuned.

Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry

Samuele De Petris
First
;
Filippo Sarvia;Enrico Borgogno-Mondino
Last
2022-01-01

Abstract

Forest height is a key parameter in forestry. SAR interferometry (InSAR) techniques have been extensively adopted to retrieve digital elevation models (DEM) to give a representation of the continuous variation of the Earth’s topography, including forests. Unfortunately, InSAR has been proven to fail over vegetation due to low coherence values; therefore, all phase unwrapping algorithms tend to avoid these areas, making InSAR-derived DEM over vegetation unreliable. In this work, a sensitivity analysis was performed with the aim of properly initializing the relevant operational parameters (baseline and multilooking factor) to maximize the theoretical accuracy of the height difference between the forest and reference point. Some scenarios were proposed to test the resulting “optimal values”, as estimated at the previous step. A simple model was additionally proposed and calibrated, aimed at predicting the optimal baseline value (and therefore image pair selection) for height uncertainty minimization. All our analyses were conducted using free available data from the Copernicus Sentinel-1 mission to support the operational transfer into the forest sector. Finally, the potential uncertainty affecting resulting height measures was quantified, showing that a value lower than 5 m can be expected once all user-dependent parameters (i.e., baseline, multilooking factor, temporal baseline) are properly tuned.
2022
3
1
479
492
https://www.mdpi.com/2673-4834/3/1/29
Sentinel-1; SAR; interferometry; phase unwrapping avoiding; forest height; uncertainty assessment; topographic levelling approach
Samuele De Petris ,Filippo Sarvia, Enrico Borgogno-Mondino
File in questo prodotto:
File Dimensione Formato  
earth-03-00029.pdf

Accesso aperto

Descrizione: Articolo principale
Tipo di file: PDF EDITORIALE
Dimensione 5.18 MB
Formato Adobe PDF
5.18 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1851016
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact