Techniques for wide-area mapping of forest biomass using radar data

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Doctoral thesis (article-based)
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Date
2006-02-17
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Degree programme
Language
en
Pages
103, [77]
Series
VTT publications, 500
Abstract
Aspects of forest biomass mapping using SAR (Synthetic Aperture Radar) data were studied in study sites in northern Sweden, Germany, and south-eastern Finland. Terrain topography – via the area of a resolution cell – accounted for 61 percent of the total variation in a Seasat (L-band) SAR scene in a hilly and mountainous study site. A methodology – based on least squares adjustment of tie point and ground control point observations in a multi-temporal SAR mosaic dataset – produced a tie point RMSE (Root Mean Square Error) of 56 m and a GCP RMSE of 240 m in the African mosaic of the GRFM (Global Rain Forest Mapping) project. The mosaic consisted of 3624 JERS SAR scenes. A calibration revision methodology – also based on least squares adjustment and points in overlap areas between scenes – removed a calibration artifact of about 1 dB. A systematic search of the highest correlation between forest stem volume and backscattering amplitude was conducted over all combinations of transmit and receive polarisations in three AIRSAR scenes in a German study site. In the P-band, a high and narrow peak around HV-polarisation was found, where the correlation coefficient was 0.75, 0.59, and 0.71 in scenes acquired in August 1989, June 1991, and July 1991, respectively. In other polarisations of P-band, the correlation coefficient was lower. In L-band, the polarisation response was more flat and correlations lower, between 0.54 and 0.70 for stands with a stem volume 100 m3/ha or less. Three summer-time JERS SAR scenes produced very similar regression models between forest stem volume and backscattering amplitude in a study site in south-eastern Finland. A model was proposed for wide area biomass mapping when biomass accuracy requirements are not high. A multi-date regression model employing three summer scenes and three winter scenes produced a multiple correlation coefficient of 0.85 and a stem volume estimation RMSE of 41.3 m3/ha. JERS SAR scenes that were acquired in cold winter conditions produced very low correlations between stem volume and backscattering amplitude.
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Keywords
wide-area mapping, remote sensing, Synthetic Aperture Radar, forest biomass, SAR, polarimetry, mosaicking, forests, backscattering
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Parts
  • Rauste, Y. 1990. Incidence-angle dependence in forested and non-forested areas in Seasat SAR data, International Journal of Remote Sensing, Vol. 11, No. 7, p. 1267-1276. [article1.pdf] © 1990 Taylor and Francis Journals UK. By permission.
  • Rauste, Y., De Grandi, G., Richards, T., Rosenqvist, Å., Perna, G., Franchino, E., Holecz, F., and Pasquali, P. 1999. Compilation of a bi-temporal JERS SAR mosaic over the African rain forest belt in the GRFM project, Proceedings of IGARSS'99, 28 June-2 July 1999, Hamburg, Germany, p. 750-752. [article2.pdf] © 1999 IEEE. By permission.
  • De Grandi, G., Mayaux, P., Rauste, Y., Rosenqvist, Å., Simard, M., and Saatchi, S. 2000. The global rain forest mapping project JERS-1 radar mosaic of tropical Africa: Development and product characterization aspects, IEEE Transactions on Geoscience and Remote Sensing, Vol. 38, No. 5, September 2000, p. 2218-2233. [article3.pdf] © 2000 IEEE. By permission.
  • Rauste, Y., Häme, T., Pulliainen, J., Heiska, K., and Hallikainen, M. 1994. Radar-based forest biomass estimation, International Journal of Remote Sensing, Vol. 15, No. 14, p. 2797-2808. [article4.pdf] © 1990 Taylor and Francis Journals UK. By permission.
  • Rauste, Y. 1993. Multitemporal analysis of forest biomass using AIR-SAR data, Proceedings of the 25th International Symposium, Remote Sensing and Global Environmental Change, 4-8 April, 1993, Graz, Austria, p. I-328-I-338. [article5.pdf] © 1993 Altarum Institute. By permission.
  • Rauste, Y. 2005. Multi-temporal JERS SAR data in boreal forest biomass mapping, Remote Sensing of Environment, Vol. 97, p. 263-275. [article6.pdf] © 2005 Elsevier. By permission.
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Permanent link to this item
https://urn.fi/urn:nbn:fi:tkk-006371