A critical review of exploring the recent trends and technological advancements in forest biomass estimation
2025
Kabinesh, V | Suwethaasri, D | Baranidharan, K | Ravi, R | Tilak, M | Kalpana, M | Ragunath, K.P | Vennila, S | Hemalatha, P | Vijayabhama, M | Bargavi, S | Eniya, A
Biomass estimation is pivotal in understanding and managing global carbon stocks, offering vital insights into climate change and environmental ecology. It serves as a critical tool for evaluating carbon sequestration potential, a natural mechanism for regulating atmospheric carbon dioxide levels. Accurate estimation of forest biomass not only aids in quantifying carbon stocks but also provides a basis for sustainable forest management, conservation efforts, and policymaking to mitigate climate change impacts. This article provides a comprehensive review of various biomass estimation methods, including ground-based measurements, remote sensing technologies, and hybrid approaches. Each method's strengths, limitations, and practical applications are critically examined, highlighting their suitability for different spatial scales and ecological contexts. Traditional methods, while precise at small scales, are often labour-intensive and limited in coverage. In contrast, remote sensing technologies such as LiDAR, RADAR, and hyperspectral imaging have revolutionized biomass estimation by enabling large-scale and high-resolution assessments. Additionally, recent advancements in machine learning, data fusion, and satellite-based monitoring systems are transforming the field, offering unprecedented accuracy and efficiency. By presenting these trends and innovations, this article provides valuable insights for researchers, practitioners, and policymakers, emphasizing the importance of integrating advanced technologies into biomass estimation for sustainable development and climate resilience.
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