37 http://dx.doi.org/10.30536/j.ijreses.2018.v15.a2683 @National Institute of Aeronautics and Space of Indonesia (LAPAN) BIOMASS ESTIMATION MODEL FOR MANGROVE FOREST USING MEDIUM-RESOLUTION IMAGERIES IN BSN CO LTD CONCESSION AREA, WEST KALIMANTAN Sendi Yusandi 1 , I Nengah Surati Jaya 2* , and Fairus Mulia 3 1 Directorate of Biodiversity Conservation, Ministry of Environment and Forestry, Manggala Wanabhakti blok 7 lt 7 Jl. Gatot Subroto, Jakarta Pusat, Indonesia 2 Remote Sensing and GIS Laboratory, Faculty of Forestry, Bogor Agricultural University Bogor, Indonesia 3 PT Kandelia Alam. Jalan Supadio Pontianak * e-mail: ins-jaya@apps.ipb.ac.id Received: 13 June 2017; Revised: 15 May 2018; Approved: 22 June 2018 Abstract. Mangrove forest is one of the forest ecosystem types that have the highest carbon stock in the tropics. Mangrove forests have a good assimilation capability with their environmental elements as well as on carbon sequestration. However, the availability of data and information on carbon storage, especially on tree biomass content of mangrove is still limited. Conventionally, an accurate estimation of biomass could be obtained from terrestrial measurements, but those methods are very costly and time-consuming. This study offered an alternative solution to overcome these limitations by using remote sensing technology, i.e. by using Landsat 8 and SPOT 5. The objective of this study is to formulate the biomass estimation model using medium resolution satellite imagery, as well as to develop a biomass distribution map based on the selected model. The study found that the NDVI of Landsat 8 and SPOT 5 have considerably high correlation coefficients with the standing biomass with a value of higher than 0.7071. On the basis of the values of aggregation deviation, mean deviation, bias, RMSE, χ², R², and s, the best model for estimating the mangrove stand biomass for Landsat 8 is B=0.00023404 e (20 NDVI) with the R² value of 77.1% and B=0.36+25.5 NDVI² with the R² value of 49.9% for SPOT 5. In general, the concession area of Bina Silva Nusa (BSN) Group (PT Kandelia Alam and PT Bina Ovivipari Semesta) have the potential of biomass ranging from 45 to 100 ton per ha. Keywords: mangrove forests, biomass, model, score, NDVI 1 INTRODUCTION The increase of carbon dioxide (CO2) concentration in the atmosphere has been a major factor that affects the global warming. Forests are considered to be one of the important components of the mechanism of carbon emission that may reduce GHG when it managed in a sustainable manner. Forest biomass is also often used as one of the basic considerations in sustainable forest management activities, especially those associated with carbon trading. This is due to the ability of the forest to sequester the CO2 in the biomass. The volume of biomass content trapped in the forest depends on stand conditions such as natural regeneration, disturbance conditions and forest allocation (IPCC 2001). Mangrove forests are one of the forests which possibly have the highest carbon storage in the tropics compared to the other forest types in the world (Donato et al. 2012). Although mangroves are known to have good assimilation capabilities with environmental components and have high C absorption rates, data and information on carbon International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 1 June 2018: 37-50