Accuracy comparison of remote sensing methods (UAV, LiDAR, Radar) and field allometry in mangrove blue carbon quantification: A systematic literature review - Ludwick Satria Romadoni; H. Husamah; Bello Ganiyu (Universitas Muhammadiyah Malang, 2025)
Background: Mangrove ecosystems are crucial blue carbon reservoirs, yet quantifying their carbon stocks faces methodological challenges. Field allometric methods, while accurate, are destructive and labor-intensive. Non-destructive Remote Sensing (RS) (UAV, LiDAR, Radar) offers an efficient alternative for landscape-scale mapping. However, literature comparing the accuracy and bias of these diverse RS sensors remains fragmented. Objectives: This study aims to (1) synthesize and compare accuracy metrics & RMSE from various RS methods in estimating mangrove biomass and carbon stocks, and (2) identify factors in forest structure and sensor types that most significantly influence estimation bias Methods: This research employs a Systematic Literature Review (SLR) guided by PRISMA. Data were extracted from 10 core empirical articles (2018-2025) covering various platforms from optical satellites to UAV-LiDAR. Results: The SLR results indicate that high-cost technologies like LiDAR do not always guarantee the highest accuracy compared to optical sensors (Sentinel-2) under certain conditions. The primary identified bias factor is signal saturation in dense canopies. Conclusion: These findings provide evidence-based guidance for researchers and biology educators in selecting the most robust methodology for carbon inventory.