Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data

Kiledar Singh Tomar, Shashi Kumar, V.A. Tolpekin

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

3 Citations (Scopus)

Abstract

Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m- alpha and Yamaguchi decomposition modelling were extracted. The R-2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha(-1)) and 73.424 (t ha(-1)) respectively. On the basis of RMSE and R-2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.
Original languageEnglish
Title of host publicationLand Surface and Cryosphere Remote Sensing III; 987729
PublisherSPIE - The International Society for Optical Engineering
Pages9877-9877
Number of pages11
DOIs
Publication statusPublished - 2016
EventConference on Land Surface and Cryosphere Remote Sensing III: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India - New Delhi, India
Duration: 4 Apr 20167 Apr 2016

Publication series

NameSPIE Proceedings series
PublisherSPIE

Conference

ConferenceConference on Land Surface and Cryosphere Remote Sensing III
CountryIndia
CityNew Delhi
Period4/04/167/04/16

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aboveground biomass
scattering
decomposition
modeling
biomass
carbon cycle
cloud water
electromagnetic wave
ellipse
deforestation
symmetry
synthetic aperture radar
polarization
radar
atmosphere
vegetation
carbon
climate

Cite this

Tomar, K. S., Kumar, S., & Tolpekin, V. A. (2016). Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data. In Land Surface and Cryosphere Remote Sensing III; 987729 (pp. 9877-9877). (SPIE Proceedings series). SPIE - The International Society for Optical Engineering. https://doi.org/10.1117/12.2223639
Tomar, Kiledar Singh ; Kumar, Shashi ; Tolpekin, V.A. / Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data. Land Surface and Cryosphere Remote Sensing III; 987729 . SPIE - The International Society for Optical Engineering, 2016. pp. 9877-9877 (SPIE Proceedings series).
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abstract = "Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m- alpha and Yamaguchi decomposition modelling were extracted. The R-2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha(-1)) and 73.424 (t ha(-1)) respectively. On the basis of RMSE and R-2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.",
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Tomar, KS, Kumar, S & Tolpekin, VA 2016, Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data. in Land Surface and Cryosphere Remote Sensing III; 987729 . SPIE Proceedings series, SPIE - The International Society for Optical Engineering, pp. 9877-9877, Conference on Land Surface and Cryosphere Remote Sensing III, New Delhi, India, 4/04/16. https://doi.org/10.1117/12.2223639

Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data. / Tomar, Kiledar Singh; Kumar, Shashi; Tolpekin, V.A.

Land Surface and Cryosphere Remote Sensing III; 987729 . SPIE - The International Society for Optical Engineering, 2016. p. 9877-9877 (SPIE Proceedings series).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

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N2 - Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m- alpha and Yamaguchi decomposition modelling were extracted. The R-2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha(-1)) and 73.424 (t ha(-1)) respectively. On the basis of RMSE and R-2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.

AB - Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m- alpha and Yamaguchi decomposition modelling were extracted. The R-2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha(-1)) and 73.424 (t ha(-1)) respectively. On the basis of RMSE and R-2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.

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Tomar KS, Kumar S, Tolpekin VA. Semi-empirical modelling for forest aboveground biomass estimation using hybrid and fully PolSAR data. In Land Surface and Cryosphere Remote Sensing III; 987729 . SPIE - The International Society for Optical Engineering. 2016. p. 9877-9877. (SPIE Proceedings series). https://doi.org/10.1117/12.2223639