In this study, we used radar data from the ALOS-2 PALSAR-2 satellite to build biomass estimation models and then create a biomass map in Can Gio Mangrove Biosphere Reserve. We used the single variable regression and multivariate regression method, in which 30 sample plots for training model and 15 sample plots for validation model, the coefficient of determination (R 2 ) and root mean square error (RMSE) were used as metrics for evaluating the biomass estimates. The regression analyses showed that the HV polarization was highly related to the biomass, linear model (R 2 = 0.74; RMSE = 28.16), exponential model (R 2 = 0.69; RMSE = 28.73), and polynomial model (R 2 = 0.76; RMSE = 28.03). However, the HH polarization did not show a high relationship with the above-ground biomass, linear model (R 2 = 0.42), exponential model (R 2 = 0.46), or polynomial model (R 2 = 0.42). We also tried multiple linear regression between the parameters extracted from radar image (HH, HV, and textures) and field biomass. The coefficient of determination (R 2 ) between the biomass and two independent variables (HH and HV) was 0.79, and RMSE was 29.78. However, the model with the combination of HV variable and eight texture variables provided a better result (R 2 = 0.81; RMSE = 27.76), in other word the model could explain 81% variation of forest biomass. This model was used to produce the aboveground biomass map in Can Gio Biosphere Reserve in South of Vietnam.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.