High-resolution Unmanned Aerial Vehicles (UAV) imagery for estimating above and below-ground biomass in mangroves of Rembang, Central Java, Indonesia

Abstract. Iryanthony SB, Wirasatriya A, Pribadi R, Purnomo PW, Muchtar E, Basyuni M, Wijayanto D. 2025. High-resolution Unmanned Aerial Vehicles (UAV) imagery for estimating above and below-ground biomass in mangroves of Rembang, Central Java, Indonesia. Biodiversitas 26: 2065-2078. Mangrove ecosystems are essential for climate change mitigation. The blue-carbon ecosystems in Pasar Banggi, Rembang, Central Java, Indonesia, sequester carbon and reduce emissions. The Essential Ecosystem Area in Pasar Banggi, Rembang, encompasses 36 hectares along a 2.7 km stretch and can support two flights at an altitude of 120 meters Above Ground Level (AGL). This site assesses Unmanned Aerial Vehicles (UAV) methodologies for Above-Ground Biomass (AGB) using a Phantom 4 Pro Obsidian true color sensor with a resolution of 20 MP. UAV offer remarkable accuracy and resolution of 4.1 cm per pixel. This study evaluates the volume of AGB and the carbon sequestered in mangroves utilizing aerial footage obtained from UAV and accurate Global Navigation Satellite System (GNSS) data. The study creates precise digital surface models and digital terrain models to determine the mangrove canopy elevations. The horizontal accuracy (CE90) is approximately 0.0201 m, whereas the vertical accuracy (LE90) is around 0.0249 m. The canopy heights are 1-6 m along the beach and 1-14 m further inland. Applying an allometric equation specified for Southeast and East Asia region yields an AGB ranges from 6 to 317 mg/ha. AGB is then converted into Below-Ground Biomass (BGB) through a ratio, producing total biomass as the aggregate of AGB and BGB. BGB ranges from 2 to 123 mg/ha with total biomass can attain levels of up to 440 mg/ha. In this site, Rhizophora mucronata, R. apiculata, and R. stylosa constitute most of the total area covering biomass, 38%, 27%, and 9%, respectively, demonstrating their significance in carbon sequestration. The high accuracy of AGB estimation with root mean square error of 8.95 mg/ha demonstrates the considerable efficiency of combining UAV and GNSS technologies in improving the precision of biomass estimation for carbon stock assessments.