Potential of texture from SAR tomographic images for forest aboveground biomass estimation
Synthetic Aperture Radar (SAR) texture has been demonstrated to have the potential to improve forest biomass estimation using backscatter. However, forests are 3D objects with a vertical structure. The strong penetration of SAR signals means that each pixel contains the contributions of all the scat...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-06-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0303243418309504 |
| _version_ | 1811229336543428608 |
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| author | Zhanmang Liao Binbin He Xingwen Quan |
| author_facet | Zhanmang Liao Binbin He Xingwen Quan |
| author_sort | Zhanmang Liao |
| collection | DOAJ |
| description | Synthetic Aperture Radar (SAR) texture has been demonstrated to have the potential to improve forest biomass estimation using backscatter. However, forests are 3D objects with a vertical structure. The strong penetration of SAR signals means that each pixel contains the contributions of all the scatterers inside the forest canopy, especially for the P-band. Consequently, the traditional texture derived from SAR images is affected by forest vertical heterogeneity, although the influence on texture-based biomass estimation has not yet been explicitly explored. To separate and explore the influence of forest vertical heterogeneity, we introduced the SAR tomography technique into the traditional texture analysis, aiming to explore whether TomoSAR could improve the performance of texture-based aboveground biomass (AGB) estimation and whether texture plus tomographic backscatter could further improve the TomoSAR-based AGB estimation. Based on the P-band TomoSAR dataset from TropiSAR 2009 at two different sites, the results show that ground backscatter variance dominated the texture features of the original SAR image and reduced the biomass estimation accuracy. The texture from upper vegetation layers presented a stronger correlation with forest biomass. Texture successfully improved tomographic backscatter-based biomass estimation, and the texture from upper vegetation layers made AGB models much more transferable between different sites. In addition, the correlation between texture indices varied greatly among different tomographic heights. The texture from the 10 to 30 m layers was able to provide more independent information than the other layers and the original images, which helped to improve the backscatter-based AGB estimation. |
| first_indexed | 2024-04-12T10:13:12Z |
| format | Article |
| id | doaj.art-1908ac07448d487a8ab555361bf130ff |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-12T10:13:12Z |
| publishDate | 2020-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-1908ac07448d487a8ab555361bf130ff2022-12-22T03:37:15ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322020-06-0188102049Potential of texture from SAR tomographic images for forest aboveground biomass estimationZhanmang Liao0Binbin He1Xingwen Quan2School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, ChinaSchool of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China; Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; Corresponding author at: School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China.School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, ChinaSynthetic Aperture Radar (SAR) texture has been demonstrated to have the potential to improve forest biomass estimation using backscatter. However, forests are 3D objects with a vertical structure. The strong penetration of SAR signals means that each pixel contains the contributions of all the scatterers inside the forest canopy, especially for the P-band. Consequently, the traditional texture derived from SAR images is affected by forest vertical heterogeneity, although the influence on texture-based biomass estimation has not yet been explicitly explored. To separate and explore the influence of forest vertical heterogeneity, we introduced the SAR tomography technique into the traditional texture analysis, aiming to explore whether TomoSAR could improve the performance of texture-based aboveground biomass (AGB) estimation and whether texture plus tomographic backscatter could further improve the TomoSAR-based AGB estimation. Based on the P-band TomoSAR dataset from TropiSAR 2009 at two different sites, the results show that ground backscatter variance dominated the texture features of the original SAR image and reduced the biomass estimation accuracy. The texture from upper vegetation layers presented a stronger correlation with forest biomass. Texture successfully improved tomographic backscatter-based biomass estimation, and the texture from upper vegetation layers made AGB models much more transferable between different sites. In addition, the correlation between texture indices varied greatly among different tomographic heights. The texture from the 10 to 30 m layers was able to provide more independent information than the other layers and the original images, which helped to improve the backscatter-based AGB estimation.http://www.sciencedirect.com/science/article/pii/S0303243418309504TextureForestVertical heterogeneityBiomassSAR tomographyLayered texture |
| spellingShingle | Zhanmang Liao Binbin He Xingwen Quan Potential of texture from SAR tomographic images for forest aboveground biomass estimation International Journal of Applied Earth Observations and Geoinformation Texture Forest Vertical heterogeneity Biomass SAR tomography Layered texture |
| title | Potential of texture from SAR tomographic images for forest aboveground biomass estimation |
| title_full | Potential of texture from SAR tomographic images for forest aboveground biomass estimation |
| title_fullStr | Potential of texture from SAR tomographic images for forest aboveground biomass estimation |
| title_full_unstemmed | Potential of texture from SAR tomographic images for forest aboveground biomass estimation |
| title_short | Potential of texture from SAR tomographic images for forest aboveground biomass estimation |
| title_sort | potential of texture from sar tomographic images for forest aboveground biomass estimation |
| topic | Texture Forest Vertical heterogeneity Biomass SAR tomography Layered texture |
| url | http://www.sciencedirect.com/science/article/pii/S0303243418309504 |
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