|
Noise in SAR imagery was produced due to different backscatter response from the objects in the earth surface. This resulted in a grainy image, usually known as “salt and pepper” noise, which reducing the capability to identify object from radar imagery. Therefore, speckle filtering was conducted to decrease this noise from SAR imagery. This study aims to assess the performance of different types of speckle filters especially when used to construct forest aboveground biomass (AGB) model from Sentinel-1 data in Barru Regency, South Sulawesi. There were 4 filters used in this study i.e. Frost, Gamma-MAP, Median, and Refined Lee. AGB model was constructed by using dual polarization C-band SAR of Sentinel1 data and ground inventory plots. 23 plots were collected in the field and the allometric equation was used to calculate the biomass value of the field survey data then cross validation models were generated by using biomass value and backscatter data from VV and VH polarization. Quality control was performed by comparing the coefficient of determination (R2 ) of those filters. The result shows that Frost filter especially on VH polarization was chosen as the bestfit model to estimate the AGB based on higher value of R2 (0.3464158) and RMSE (33.5231). The result demonstrated Frost filter as the best filter for retaining and/or enhancing the backscatter signal in Sentinel-1 data to be used in vegetation bio-physical modelling.
|
