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Forest cover change is an important aspect of global environmental change because of rapid deforestation in tropical areas. Anthropogenic activities and natural phenomena can cause deforestation and forest degradation that adversely impacts biodiversity and ecosystem services. In 2008, the United Nations Convention on Climate Change (UNFCCC) programme on Reducing Emissions from Deforestation and forest Degradation (REDD+) was launched to curb deforestation and forest degradation in tropical countries. The UNFCCC COP21 Paris Agreement highlighted “encouragement for Parties to implement existing frameworks for a REDD+ mechanism”. For effectively implementing a REDD+ mechanism, a robust cost-effective Measurement, Reporting and Verification (MRV) system should be developed. Geospatial data has been key for the implementation of REDD+ MRV system. In this research, aboveground biomass (AGB) of forests in Cambodia was estimated using a bottom-up approach based on field estimated biomass and PALSAR backscattering (σo) properties. The relationship between the PALSAR σo HV and HH/HV with field-based biomass was strong with adjusted R squared (Radj) = 0.66 and 0.54, respectively as compared with HH polarization. PALSAR estimated biomass shows better results in deciduous forests as compared with evergreen forests of Cambodia because of less saturation of L-band SAR data in deciduous forests. Deforestation, Forest biomass, Geospatial data, Mitigation, SAR backscattering

Integrating ALOS-PALSAR and ground based observations for forest biomass estimation for REDD+ in Cambodia