CARBON STOCKS ESTIMATION USING POLARIMETRIC INTERFEROMETRIC RADAR (POLINSAR) IN THE PERSPECTIVE OF CLIMATE CHANGE MITIGATION (STUDY AREA: SOUTH EAST SULAWESI) - ODE MUHAMMAD GOLOK JAYA , LA
Mapping carbon stocks is a strategic step to study the climate change impact caused by increasing carbon emissions and greenhouse gases in the Earth's atmosphere. The availability of geospatial information of carbon stocks with good accuracy will support mitigation efforts pursued by climate change, for example through conservation of carbon stocks, expansion of carbon stocks, mapping and monitoring of high carbon value areas. To obtain geospatial information of carbon stocks, the application of remote sensing techniques has become one of the tools suggested and used by researchers widely over the past decades. However, the cloud cover, fog and smoke that often occur, particularly in parts of Indonesia, causing the importance of selecting remote sensing systems in accordance with these conditions. Remote sensing radar has the ability to penetrate cloud cover, fog or smoke and can operate day and night. Therefore, remote radar sensing system is believed to be the best solution in the context of this problem. However, radar remote sensing systems have limitations in mapping carbon stocks, especially when only utilizing information from radar polarization through its backscatter analysis (Polarimetric Synthetic Aperture Radar / PolSAR technique). The occurrence of saturation leads to inaccurate information on the resulting carbon stock. Such inaccuracies will cause losses in the calculation of carbon values when associated with the economic value of carbon stocks. On the other hand, in the radar sensor system there is an interferometric technique that can overcome the saturation problem. Therefore, polarimetric and interferometry synthetic aperture radars (PolInSAR) are believed to be able to overcome the problem of inaccuracies in the estimation of carbon stocks. However, polarimetric and inteferometry combination techniques still need to be evaluated for their ability to estimate carbon stocks, particularly in Indonesia. This study aims to evaluate the performance of PolInSAR techniques for the estimation of carbon stocks in Indonesian territory according to the haracteristics of the region by taking into account the constraints of saturation, temporal decoration, the limited SAR image polarization and the topographic conditions to obtain carbon estimates that have the minimum uncertainty in perspective climate change mitigation. Three locations have been selected for the evaluation of the dry tropical forests of Wolasi region, mangrove forests in coastal areas of South Konawe Regency and wet tropical forest in the protected forest area of Moramo. Satellite images used in this study were ALOS PALSAR full-polarimetric (polarization HH + HV + VH + VV) and dual-polarization (HH + HV) in repeatpass interferometric and single baseline modes. ALOS PALSAR image with 23 cm wavelength and 1.25 GHz center frequency has several advantages, one of which is the HV backscatter coefficient is closely related to carbon vegetation reserve. The method used in this research is the comparability of Polsar and PolInSAR technique to the result of field survey. The carbon estimation by PolSAR is based on the value of backscatter coefficient with and without Radiometric Terrain Flattening (RTF) topographic correction. While carbon estimation with PolInSAR is done by developing Random Volume over Ground model (RVoG) as a representation of vegetation biophysical model through integration of polarimetric and interferometry component (PolInSAR) of ALOS PALSAR image. Next, comparing to PolSAR technique with and without RTF. To obtain vegetation height as an input in carbon estimation, the RVoG model is inversed through the forest height inverse-process method and the results are compared with field measurements. The results of the proper vegetation height analysis of coherence polarimetric interferometry and RTF optimization resulted in a model of high estimation of vegetation and tropical carbon stocks with good accuracy. It is expected to become a reference (standard) in mapping carbon stocks in Indonesia. The results of this study indicate that the PolSAR technique can be used in dry tropical forest cover with up to 155 tons/ha (R2 = 0.9384) carbon stock, while in wet tropics with higher vegetation density is 225 tons/ha (R2 = 0.961) and in mangrove area with carbon stock value up to 45 tons/ha (R2 = 0.9068). While with PolInSAR technique, the carbon value of 200 tons/ha in dry tropical forest (R2 = 0.7525), 300 tons/ha in wet tropical forest (R2 = 0.6672) and 60 ton/hectare for mangrove (R2 = 0.6606). The value is about 30% higher than the carbon value generated through the PolSAR technique. The results of this study provide an important contribution in the development of carbon stock determination strategy in Indonesia in the perspective of climate change mitigation.