ESTIMATION AND MAPPING OF ABOVE GROUND BIOMASS OF MANGROVE FOREST USING ALOS-2 PALSAR-2 IN BENOA BAY, BALI, INDONESIA

Abstract

Mangrove forests are distributed in limited areas around along costlines, but they play important role in carbon fixation and carbon storafe in the tropic areas. Mangrove forests are a transitional ecosystem between land-based oceans, most of which are well-known along the tropic and subtropical coastlines. Mangrove ecosystems have an ecological function as an absorber and storage of carbon in the form of biomass. Remote sensing technology can include data spatially and temporally. This makes it easy to predict the overall extent and carbon stock. So that in the context of sustainable management of mangrove ecosystems it can be utilized to monitor mangrove carbon balance and become the basis for policy development. The objective of this study was to determine the potential above ground biomass model from ALOS-2 PALSAR-2 data in mangrove forests of Benoa Bay, Bali. In this research, the filter used is frost filtering. AGB model was constructesd by using dual-polarization L-band SAR of ALOS-2 PALSAR-2 data and field inventory plots. 40 plots were collected in the field and the allometric equation. The prediction model for aboveground biomass potential based on the ALOS-2 PALSAR-2 image on HV polarization in the mangrove Benoa Bay area, the correlation value (r) of 0.82, the coefficient of determination (R2) of 0.68. Validation model aboveground biomass-based, correlation value (r) of 0.90, the coefficient of determination (R2) of 0.82, and RMSE of ± 39.85. The potential of aboveground biomass and carbon stock in the mangrove Benoa Bay area is 364,241.87 Mg and 171,193.67 Mg C with the ability to absorb carbon dioxide (CO2) of 628,280.81 Mg CO2 Sequestration same with 3 bottles in 2020.
Keywords: Mangrove; Aboveground biomass (AGB); HV Polarization; ALOS-2 PALSAR-2.