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All Journal Green and Tropical Laboratory for Sustainability
Bello Ganiyu
Department of Science Education, Faculty of Education, University of Ilorin, Nigeria
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Decision Sciences, Operations Research & Management Environmental Science Social Sciences

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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
Green and Tropical Laboratory for Sustainability Vol. 2 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/gtlabs.v2i2.43380

Abstract

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.
Co-Authors Husamah Husamah Ludwick Satria Romadoni