Comparison of Boreal Biomass Estimations Using C- and X-Band Polsar

Sammanfattning

This study investigated the potential of using polarimetric synthetic aperture radar (PolSAR) data acquired at C- and X-band to estimate forest aboveground biomass (biomass) at a test site in southern Sweden. The SAR data were acquired with RADARSAT-2 and TerraSAR-X in September 2015, and the biomass estimations were cross-validated with 48 field inventoried plots of 40 m radius (0.5 ha), covering dominantly coniferous hemi-boreal forest. The quad-pol SAR data (HH, HV, VH, VV) were decomposed using the Yamaguchi model and the mean modelled scatter components for the plots were extracted and used as predictors in linear regression models to estimate the biomass.The model performances were quantified using the root mean square error (RMSE) and adjusted coefficient of determination, R-adj(2). The leave-one-out cross-validated RMSEs were 58.1 (37.1%) and 60.6 (38.6%) tons/ha for C- and X-band, respectively, and the R-adj(2) were 0.52 and 0.47, respectively. The regression model for C-band data used the volume and helix scattering components in the Yamaguchi decomposition as predictors, while the corresponding X-band model used the double bounce and surface components. The differences were likely due to the different penetrations at C- and X-band. We noticed a tendency to saturation at about 300 tons/ha in the X-band predictions, while no such tendency was noticed for the C-band model.We conclude that the Yamaguchi polarimetric decomposition technique is a useful approach when estimating biomass in a hemi-boreal forest. The strengths are not comparable to approaches where height information are available (e.g., single-pass interferometry from TanDEM-X), but this polarimetric approach based on single satellite images showed sensitivity to the entire biomass range (0 - 400 tons/ha) in our dataset. The potential of using quad-pol SAR data is, therefore, important to investigate further.

Nyckelord

RADARSAT-2; TerraSAR-X; TanDEM-X; polarimetry; PolSAR; forest; biomass

Publicerad i

IEEE International Geoscience and Remote Sensing Symposium proceedings
2022, sidor: 5555-5558
Titel: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium : proceedings
Utgivare: Institute of Electrical and Electronics Engineers

Konferens

IEEE International Geoscience and Remote Sensing Symposium (IGARSS), JUL 17-22, 2022, Kuala Lumpur, MALAYSIA

SLU författare

• Persson, Henrik

  • Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet
    

• Mukhopadhyay, Ritwika

  • Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet
    

• Huuva, Ivan

  • Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet
    

• Fransson, Johan

  • Institutionen för skoglig resurshushållning, Sveriges lantbruksuniversitet
    
  • Linnéuniversitetet

Associerade SLU-program

SLU Centrum för biologisk mångfald, CBM

UKÄ forskningsämne

Skogsvetenskap
Fjärranalysteknik

Publikationens identifierare

• DOI: https://doi.org/10.1109/IGARSS46834.2022.9884506
• eISBN: 978-1-6654-2792-0

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/122102