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

Dissertation

Research output: ThesisDissertationCollection of Articles

2 Citations (Scopus)

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 41.3m3/ha. JERS SAR scenes that were acquired in cold winter conditions produced very low correlations between stem volume and backscattering amplitude.
Original languageEnglish
QualificationDoctor Degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Haggren, Henrik, Supervisor, External person
Award date17 Feb 2006
Place of PublicationEspoo
Publisher
Print ISBNs951-38-6694-7
Electronic ISBNs951-38-6695-5
Publication statusPublished - 2005
MoE publication typeG5 Doctoral dissertation (article)

Fingerprint

synthetic aperture radar
radar
stem
biomass
polarization
calibration
Seasat
methodology
ground control
winter
summer
artifact
topography
mosaic
JERS

Keywords

  • wide-area mapping
  • remote sensing
  • Synthetic Aperture Radar
  • forest biomass
  • SAR
  • Polarimetry
  • mosaicking
  • forests
  • backscattering

Cite this

Rauste, Yrjö. / Techniques for wide-area mapping of forest biomass using radar data : Dissertation. Espoo : VTT Technical Research Centre of Finland, 2005. 178 p.
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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 41.3m3/ha. JERS SAR scenes that were acquired in cold winter conditions produced very low correlations between stem volume and backscattering amplitude.",
keywords = "wide-area mapping, remote sensing, Synthetic Aperture Radar, forest biomass, SAR, Polarimetry, mosaicking, forests, backscattering",
author = "Yrj{\"o} Rauste",
note = "Project code: T5SU00716",
year = "2005",
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Techniques for wide-area mapping of forest biomass using radar data : Dissertation. / Rauste, Yrjö.

Espoo : VTT Technical Research Centre of Finland, 2005. 178 p.

Research output: ThesisDissertationCollection of Articles

TY - THES

T1 - Techniques for wide-area mapping of forest biomass using radar data

T2 - Dissertation

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N2 - 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 41.3m3/ha. JERS SAR scenes that were acquired in cold winter conditions produced very low correlations between stem volume and backscattering amplitude.

AB - 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 41.3m3/ha. JERS SAR scenes that were acquired in cold winter conditions produced very low correlations between stem volume and backscattering amplitude.

KW - wide-area mapping

KW - remote sensing

KW - Synthetic Aperture Radar

KW - forest biomass

KW - SAR

KW - Polarimetry

KW - mosaicking

KW - forests

KW - backscattering

M3 - Dissertation

SN - 951-38-6694-7

T3 - VTT Publications

PB - VTT Technical Research Centre of Finland

CY - Espoo

ER -

Rauste Y. Techniques for wide-area mapping of forest biomass using radar data: Dissertation. Espoo: VTT Technical Research Centre of Finland, 2005. 178 p.