Relating SAR image texture to the biomass of regenerating tropical forests
Relating SAR image texture to the biomass of regenerating tropical forests
An accurate global carbon budget requires information on terrestrial carbon sink strength. Regenerating tropical forests are known to be important terrestrial carbon sinks but information on their location, extent and biomass (from which carbon content can be estimated) is incomplete. The use of remotely sensed data in optical wavelengths has been of limited use due to both the weak relationship between optical radiation and forest biomass and near-constant cloud cover in the tropics. L-band Synthetic Aperture Radar (SAR) backscatter, however, is related positively to biomass (but only up to an asymptote of around 40–90 Tha21) and can be obtained independently of cloud cover. Both canopy structure and biomass change over time as pioneer species are replaced by early and late regenerating species. These structural changes are related to an increase in (i) tree height, (ii) tree species richness and (iii) canopy thickness and influence the roughness of the canopy surface and consequently SAR image texture. Therefore, we investigated the degree to which textural information could be used to increase the correlation between image tone (backscatter) and biomass. Field data were used to estimate the biomass of 37 regenerating forests plots in Brazilian Amazonia. Texture measures derived from local statistics, the grey level co-occurrence matrix (GLCM) and the variogram were evaluated using simulated images on the basis of their ability to identify significant differences in image texture independently of image contrast. Theselected texture measures were applied to L-band JERS-1 (Japanese Earth Resources Satellite) SAR images and the correlation between backscatter and biomass was determined for regenerating tropical forests. A strong correlation was found for the texture measures and biomass. The ra2 (adjusted coefficient of determination), measuring the correlation between backscatter and biomass, increased from 0.74 to 0.82 with the addition of GLCM-derived contrast. The addition of image texture (GLCM-derived contrast) to image tone (backscatter) potentially increases the accuracy with which JERS-1 SAR data can be used to estimate biomass in tropical forests.
4829-4854
Kuplich, T.M.
70046705-bb8a-400b-9517-b28e4cacb569
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
10 November 2005
Kuplich, T.M.
70046705-bb8a-400b-9517-b28e4cacb569
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Kuplich, T.M., Curran, P.J. and Atkinson, P.M.
(2005)
Relating SAR image texture to the biomass of regenerating tropical forests.
International Journal of Remote Sensing, 26 (21), .
(doi:10.1080/01431160500239107).
Abstract
An accurate global carbon budget requires information on terrestrial carbon sink strength. Regenerating tropical forests are known to be important terrestrial carbon sinks but information on their location, extent and biomass (from which carbon content can be estimated) is incomplete. The use of remotely sensed data in optical wavelengths has been of limited use due to both the weak relationship between optical radiation and forest biomass and near-constant cloud cover in the tropics. L-band Synthetic Aperture Radar (SAR) backscatter, however, is related positively to biomass (but only up to an asymptote of around 40–90 Tha21) and can be obtained independently of cloud cover. Both canopy structure and biomass change over time as pioneer species are replaced by early and late regenerating species. These structural changes are related to an increase in (i) tree height, (ii) tree species richness and (iii) canopy thickness and influence the roughness of the canopy surface and consequently SAR image texture. Therefore, we investigated the degree to which textural information could be used to increase the correlation between image tone (backscatter) and biomass. Field data were used to estimate the biomass of 37 regenerating forests plots in Brazilian Amazonia. Texture measures derived from local statistics, the grey level co-occurrence matrix (GLCM) and the variogram were evaluated using simulated images on the basis of their ability to identify significant differences in image texture independently of image contrast. Theselected texture measures were applied to L-band JERS-1 (Japanese Earth Resources Satellite) SAR images and the correlation between backscatter and biomass was determined for regenerating tropical forests. A strong correlation was found for the texture measures and biomass. The ra2 (adjusted coefficient of determination), measuring the correlation between backscatter and biomass, increased from 0.74 to 0.82 with the addition of GLCM-derived contrast. The addition of image texture (GLCM-derived contrast) to image tone (backscatter) potentially increases the accuracy with which JERS-1 SAR data can be used to estimate biomass in tropical forests.
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Submitted date: 19 February 2004
Published date: 10 November 2005
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Local EPrints ID: 54946
URI: http://eprints.soton.ac.uk/id/eprint/54946
ISSN: 0143-1161
PURE UUID: e87e5d44-1065-4108-9cd2-72dae1b206ea
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Date deposited: 01 Aug 2008
Last modified: 16 Mar 2024 02:46
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Author:
T.M. Kuplich
Author:
P.J. Curran
Author:
P.M. Atkinson
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