52 APN Science Bulletin 8 (1) www.apn-gcr.org/bulletin Integrating ALOS-PALSAR and ground based observations for forest biomass estimation for REDD+ in Cambodia 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 Reduc- ing 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 (σ o ) properties. The relationship between the PALSAR σ o HV and HH/HV with field-based biomass was strong with adjusted R squared (R 2 adj ) = 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 https://doi.org/10.30852/sb.2018.414 Received: 11 January 2017 Published (online): 18 December 2018 Published (PDF): 26 December 2018 ABSTRACT KEYWORDS DOI DATES HIGHLIGHTS » PALSAR is effective in monitoring biomass and its changes without limitations of clouds » National level biomass information is useful in implementing sustainable forest management practices required for REDD+ » Empirical, remote sensing and modelling studies can be useful for generating biomass information for REDD+ MRV implementation Ram Avtar a * , Saumitra Mukherjee b , S.B.S. Abayakoon c , Chann Sophal, and Rajesh Thapa d a Graduate School of Environmental Science, Hokkaido University, Sapporo, Japan b United Nations University, Institute for the Advanced Study of Sustainability (UNU-IAS), Tokyo, Japan c School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, India d International Centre for Integrated Mountain Development (ICIMOD), Nepal * Corresponding author. Email: ram.envjnu@gmail.com. 1. INTRODUCTION Forests play an important role in global carbon cycling as they are potential carbon sinks and sources to the atmosphere CO 2 (Muukkonen & Heiskanen, 2007; Pachauri et al., 2014). Tropical forests store about 40% of terrestrial carbon (Page et al., 2009). According to the FAO (2015), total forest area declined by 3% from 4128 M ha to 3999 M ha in 1990 and 2015, respectively. Natural forest area declined from 3961 M ha to 3721 M ha between 1990 and 2015, while planted forest increased from 168 M ha to 278 M ha. The Intergovernmental Panel on Climate Change (IPCC) has pointed out that reducing or pre- venting deforestation is a mitigation option for climate change (Angelsen A., 2010; Pachauri et al., 2014). The Clean Development Mechanism (CDM) under the Kyoto Protocol is not sufficient to mitigate climate change by adopting afforestation and reforestation because deforestation releases more greenhouse gases (GHGs) than afforestation and reforestation (Schoene, 2005). Forest conservation is only one of many possible options by which permanent land-use change may be avoided (Skutsch et al., 2007). REDD+ prevents carbon emissions being released into the atmosphere by conserving exist- ing carbon stocks. The basic idea of REDD+ is to reward