Logo GISdevelopment.net

GISdevelopment > Proceedings > ACRS > 2000


1989 | 1990 | 1991 | 1992 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2002
Sessions

Agriculture & Soil

Water Resources

Coastal Zone Monitoring

Digital Photogrammetry

Environment

Forest Resources

GIS & Data Integration

Hazard Mitigation

Image Processing

Educational & Profession

Global Change

Landuse

Mapping from Space & GPS

SAR/InSAR

Oceanography

Hyperspectral & Data Acquisition System

AirSAR/MASTER

Poster Sessions
  • Session 1
  • Session 2
  • Session 3



  • ACRS 2000


    AirSAR/MASTER


    The Use of Airsar Data for Assessing the Potential of Future Spaceborne Sar for Regional Estimation of Woodland Biomass in Australia

    6. Results

    Relationships between biomass components
    Pearson's product moment correlation coefficients (r) indicated significant relationships (at the 0.01 level) between TAGB and all biomass components (branch, trunk and leaf), and between branch and trunk biomass. The leaf biomass was related to branch biomass at the 0.05 level, although the relationship with trunk biomass was insignificant.

    Relationships between biomass and SAR data
    Relationships between both SIR-C SAR and TOPSAR data and component biomass (including TAGB) were investigated initially on the basis of the correlation coefficient between the log of both the backscatter coefficient (so, dB) and estimated biomass. When establishing relationships, data for low biomass pastures were included.

    Correlation coefficients between SIR-C SAR C- and L-band data with leaf, branch, trunk and TAGB were significant at the 0.01 level, with the strongest relationship observed between L-band VV data and TAGB (Table 1). L-band VV backscatter was related more closely to the woody (i.e., branches and trunks) rather than the leaf biomass. The relationships between C-band VV data and all components of the biomass were comparatively weak, with the exception of the relationship with leaf biomass.

    The correlation coefficients between TOPSAR C-, L- and P- band (all polarisations) and all biomass components were also significant at the 0.01 level (Table 2). P band backscatter (all polarisations) was more strongly related to TAGB, and also branch and trunk biomass, compared to L band VV and C band HH backscatter. The weakest relationship with woody (trunk and branch) biomass was observed with C band HH backscatter. The strength of the relationship with leaf biomass was similar for all wavebands.

    Log SIR-C Backscatter (dB)
    C
    VV
    L
    VV
    1.1 TAGB 0.66 0.81
    Branch 0.61 0.74
    Trunk 0.59 0.70
    Leaf 0.54 0.51

    All figures significant at the 0.01 level (two tailed).

    Table 1: Pearson's correlation coefficients (r) between the logarithm of component biomass and SIR-C SAR C- and L-band backscatter.
    Log TOPSAR Backscatter (dB)
    C
    HH
    L
    VV
    P
    HH
    P
    VV
    P
    HV
    P
    TP
    1.2 TAGB 0.61 0.85 0.91 0.85 0.91 0.90
    Branch 0.58 0.79 0.86 0.81 0.86 0.85
    Trunk 0.51 0.77 0.84 0.79 0.82 0.83
    Leaf 0.48 0.54 0.48 0.45 0.45 0.48

    All figures significant at the 0.01 level (two tailed).

    Table 2: Pearson's correlation coefficients (r) between the logarithm of component biomass and TOPSAR C-, L- and P-band backscatter.

    The lowest dynamic range was observed for TOPSAR C band HH (-9.3 to -21.6; range -12.3 dB) and L band VV (-44.8 to -28.2; range -16.6) data and the largest for P band HV data (-18.9 to - 45.9 dB; range 27.0). Saturation of both SIR-C SAR and TOPSAR C- and L-band data occurred at approximately 20-30 Mg ha-1 and 50-60 Mg ha-1 respectively. P-band saturation (all polarisations) occurred at 80-100 Mg ha-1.

    Page 2 of 3
    | Previous | Next |

    Applications | Technology | Policy | History | News | Tenders | Events | Interviews | Career | Companies | Country Pages | Books | Publications | Education | Glossary | Tutorials | Downloads | Site Map | Subscribe | GIS@development Magazine | Updates | Guest Book