• DocumentCode
    1334333
  • Title

    Estimation of forest parameters using CARABAS-II VHF SAR data

  • Author

    Fransson, Johan E S ; Walter, Fredrik ; Ulander, Lars M H

  • Author_Institution
    Dept. of Forest Resource Manage. & Geomatic, Swedish Univ. of Agric. Sci., Umea, Sweden
  • Volume
    38
  • Issue
    2
  • fYear
    2000
  • fDate
    3/1/2000 12:00:00 AM
  • Firstpage
    720
  • Lastpage
    727
  • Abstract
    The use of airborne CARABASII VHF (20-90 MHz) SAR data for retrieval of forest parameters has been investigated. The investigation was performed at a test site located in the southwest of Sweden consisting mainly of Norway spruce forests. Regression models predicting forest parameters from radar backscattering amplitude were developed and evaluated. The results showed a linear relationship between backscattering amplitude and forest stem volume, stem diameter, and tree height. The analysis also showed that the radar signal is strongly affected by ground slope conditions. The root mean square errors from the regression analysis, restricted to forest stands on near-horizontal ground, were found to be 66 m3 ha-1, 3.2 cm, and 2.3 m for stem volume, stem diameter, and tree height respectively. No saturation of the backscattered signal was observed up to the maximum stem volume of 625 m3 ha-1, corresponding to a biomass of 375 tons ha-1. The results imply that VHF SAR data have significant potential for operational use in forestry
  • Keywords
    backscatter; forestry; geophysical techniques; radar cross-sections; remote sensing by radar; synthetic aperture radar; vegetation mapping; 20 to 90 MHz; CARABAS-II; HF; Norway spruce; Picea abies; SAR; Sweden; VHF; backscattering; biomass; forest parameters; forestry; geophysical measurement technique; linear relationship; radar remote sensing; radar scattering amplitude; regression model; synthetic aperture radar; vegetation mapping; Backscatter; Information retrieval; Parameter estimation; Performance evaluation; Predictive models; Radar; Regression analysis; Root mean square; Signal analysis; Testing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.842001
  • Filename
    842001