Krishnakali Ghosh | Nit Bhopal (original) (raw)

Krishnakali Ghosh

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Research paper thumbnail of Multi-Baseline Polinsar Inversion and Simulation of Interferometric Wavenumber for Forest Height Retrieval Using Spaceborne Sar Data

Maintenance of a global forest inventory and regular monitoring of forests is necessary to assess... more Maintenance of a global forest inventory and regular monitoring of forests is necessary to assess the global carbon stock. Forests have versatile functionality for the mankind and the demands could be fulfilled only by judicious assessment of forest biophysical parameters. Forest height is a parameter essential for quantitative monitoring of forests. Remote sensing tools can efficiently monitor forests on a global scale. Many studies have attempted to use Synthetic Aperture Radar (SAR) remote sensing to estimate forest parameters. This research explores Polarimetric SAR Interferometry (PolInSAR), a technology well suited for forest height estimation. The focus of this work is the retrieval of tree heights in Barkot and Thano forests of India using multi-baseline X-band data while attempting to optimize the estimation performance by simulation of wavenumber. Coherence amplitude inversion and three-stage inversion are performed to estimate the tree heights. Previous studies have used datasets with baseline information suitable for height estimation. This research attempts to use datasets with inapt baseline information and imitates the ideal wavenumber condition. The wavenumber is calculated based on the prior knowledge of the maximum tree height in the region of study. The tree height estimates obtained from both inversions are validated against field data. The accuracy of tree height estimates increase from 24.91% to 88.28% when the ideal wavenumber is used. The minimum calculated RMSE is 1.46m for three-stage inversion and 1.96m for coherence amplitude inversion. The results suggest that using an optimal wavenumber can improve the tree height estimation process.

Research paper thumbnail of Multi-Baseline Polinsar Inversion and Simulation of Interferometric Wavenumber for Forest Height Retrieval Using Spaceborne Sar Data

Maintenance of a global forest inventory and regular monitoring of forests is necessary to assess... more Maintenance of a global forest inventory and regular monitoring of forests is necessary to assess the global carbon stock. Forests have versatile functionality for the mankind and the demands could be fulfilled only by judicious assessment of forest biophysical parameters. Forest height is a parameter essential for quantitative monitoring of forests. Remote sensing tools can efficiently monitor forests on a global scale. Many studies have attempted to use Synthetic Aperture Radar (SAR) remote sensing to estimate forest parameters. This research explores Polarimetric SAR Interferometry (PolInSAR), a technology well suited for forest height estimation. The focus of this work is the retrieval of tree heights in Barkot and Thano forests of India using multi-baseline X-band data while attempting to optimize the estimation performance by simulation of wavenumber. Coherence amplitude inversion and three-stage inversion are performed to estimate the tree heights. Previous studies have used datasets with baseline information suitable for height estimation. This research attempts to use datasets with inapt baseline information and imitates the ideal wavenumber condition. The wavenumber is calculated based on the prior knowledge of the maximum tree height in the region of study. The tree height estimates obtained from both inversions are validated against field data. The accuracy of tree height estimates increase from 24.91% to 88.28% when the ideal wavenumber is used. The minimum calculated RMSE is 1.46m for three-stage inversion and 1.96m for coherence amplitude inversion. The results suggest that using an optimal wavenumber can improve the tree height estimation process.

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