The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
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Techniques for Wide-Area Mapping of Forest Biomass Using Radar Data

Yrjö Rauste

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Surveying for public examination and debate in Auditorium M1 (Otakaari 1) at Helsinki University of Technology (Espoo, Finland) on the 17th of February, 2006, at 12 noon.

Overview in PDF format (ISBN 951-38-6695-5)   [2021 KB]
VTT Publications 591, ISSN 1455-0849

Dissertation is also available in print (ISBN 951-38-6694-7)
Copyright © 2006 VTT Technical Research Centre of Finland
VTT Publications 591, ISSN 1235-0621
VTT-PUBS-591
TKK-DISS-2104

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.

This thesis consists of an overview and of the following 6 publications:

  1. 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. © 1990 Taylor and Francis Journals UK. By permission.
  2. 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. © 1999 IEEE. By permission.
  3. 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. © 2000 IEEE. By permission.
  4. 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. © 1990 Taylor and Francis Journals UK. By permission.
  5. 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. © 1993 Altarum Institute. By permission.
  6. Rauste, Y. 2005. Multi-temporal JERS SAR data in boreal forest biomass mapping, Remote Sensing of Environment, Vol. 97, p. 263-275. © 2005 Elsevier. By permission.

Keywords: wide-area mapping, remote sensing, Synthetic Aperture Radar, forest biomass, SAR, polarimetry, mosaicking, forests, backscattering

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© 2006 Helsinki University of Technology

Last update 2011-05-26