Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests

Oleg Antropov (Corresponding Author), Yrjö Rauste, Tuomas Häme, Jaan Praks

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)

Abstract

Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen). The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha) for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9%, R2 = 0.66) was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8%, R2 = 0.77) compared to 38.8-51.6 m3/ha (40.8-54.3%) from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34%, R2 = 0.79) when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.
Original languageEnglish
Article number999
JournalRemote Sensing
Volume9
Issue number10
DOIs
Publication statusPublished - 1 Oct 2017
MoE publication typeA1 Journal article-refereed

Fingerprint

PALSAR
ALOS
boreal forest
synthetic aperture radar
time series
biomass
backscatter
stem
polarization
forest inventory
mixed forest
parameter
sensor

Keywords

  • forests
  • biomass
  • remote sensing
  • radar
  • polarimetry
  • boreal forest
  • SAR polarimetry
  • time series
  • ALOS PALSAR
  • L-band
  • stem volume
  • synthetic aperture radar

Cite this

@article{64e3217b523c4de0ac1556c60633fdd3,
title = "Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests",
abstract = "Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen). The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha) for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9{\%}, R2 = 0.66) was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8{\%}, R2 = 0.77) compared to 38.8-51.6 m3/ha (40.8-54.3{\%}) from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34{\%}, R2 = 0.79) when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.",
keywords = "forests, biomass, remote sensing, radar, polarimetry, boreal forest, SAR polarimetry, time series, ALOS PALSAR, L-band, stem volume, synthetic aperture radar",
author = "Oleg Antropov and Yrj{\"o} Rauste and Tuomas H{\"a}me and Jaan Praks",
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Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests. / Antropov, Oleg (Corresponding Author); Rauste, Yrjö; Häme, Tuomas; Praks, Jaan.

In: Remote Sensing, Vol. 9, No. 10, 999, 01.10.2017.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Polarimetric ALOS PALSAR Time Series in Mapping Biomass of Boreal Forests

AU - Antropov, Oleg

AU - Rauste, Yrjö

AU - Häme, Tuomas

AU - Praks, Jaan

N1 - Project code: 102343

PY - 2017/10/1

Y1 - 2017/10/1

N2 - Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen). The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha) for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9%, R2 = 0.66) was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8%, R2 = 0.77) compared to 38.8-51.6 m3/ha (40.8-54.3%) from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34%, R2 = 0.79) when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.

AB - Here, we examined multitemporal behavior of fully polarimetric SAR (PolSAR) parameters at L-band in relation to the stem volume of boreal forests. The PolSAR parameters were evaluated in terms of their temporal consistency, inter-dependence and suitability for forest stem volume estimation across several seasonal conditions (frozen, thaw and unfrozen). The satellite SAR data were represented by a time series of PolSAR images acquired during several seasons in the years 2006 to 2009 by the ALOS PALSAR sensor. The study area was in central Finland, and represented a managed area in typical boreal mixed forest land. Utility of different PolSAR parameters, their temporal stability and cross-correlations were studied along with reference stand-level stem volume data from forest inventory. Further, two polarimetric parameters, cross-polarization backscatter and co-polarization coherence, were chosen for further investigation and stem volume retrieval. A relationship between forest stem volume and PolSAR parameters was established using the kNN regression approach. Ways of optimally combining PolSAR images were evaluated as well. For a single scene, best results were observed with polarimetric coherence (RMSE ≈ 38.8 m3/ha) for scene acquired in frozen conditions. An RMSE of 40.8 m3/ha (42.9%, R2 = 0.66) was achieved for cross-polarization backscatter in the best case. Cross-polarization backscatter was a better predictor than polarimetric coherence for few summer scenes. Multitemporal aggregation of selected PolSAR scenes improved estimates for both studied PolSAR parameters. Stronger improvement was observed for coherence with RMSE down to 34 m3/ha (35.8%, R2 = 0.77) compared to 38.8-51.6 m3/ha (40.8-54.3%) from separate scenes. Finally, the accuracy statistics reached RMSE of 32.2 m3/ha (34%, R2 = 0.79) when multitemporal HHVV coherence was combined with multitemporal HV-backscatter.

KW - forests

KW - biomass

KW - remote sensing

KW - radar

KW - polarimetry

KW - boreal forest

KW - SAR polarimetry

KW - time series

KW - ALOS PALSAR

KW - L-band

KW - stem volume

KW - synthetic aperture radar

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U2 - 10.3390/rs9100999

DO - 10.3390/rs9100999

M3 - Article

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JO - Remote Sensing

JF - Remote Sensing

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