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Coupling multi-sensory earth observation datasets, in-situ measurements, and machine learning algorithms for total blue C stock estimation of an estuarine mangrove forest

[Display omitted] •Novel total blue C accounting by spatially explicit modelling of C stocks.•Integration of multispectral and SAR data increases accuracy of AGB prediction.•Coastal mangrove wetland stores remarkable amounts of blue C (246710.91 Mg).•High spatial variability of blue C density (0.34...

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Published in:Forest ecology and management 2023-10, Vol.546, p.121345, Article 121345
Main Authors: Datta, Debajit, Dey, Mansa, Kumar Ghosh, Proshanta, Neogy, Sohini, Kumar Roy, Asit
Format: Article
Language:English
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Summary:[Display omitted] •Novel total blue C accounting by spatially explicit modelling of C stocks.•Integration of multispectral and SAR data increases accuracy of AGB prediction.•Coastal mangrove wetland stores remarkable amounts of blue C (246710.91 Mg).•High spatial variability of blue C density (0.34 to 881.50 Mg ha−1) in wetland. In recent years, research on blue carbon (C) has garnered substantial attention worldwide. Nevertheless, we observed a lack of holistic approach, in terms of measurement of total blue C (TBC) potentials. This study focuses on developing a novel approach toward blue C accounting by spatially explicit modelling and estimation of TBC stock in a mangrove wetland of eastern India. A hybrid methodology has been adopted incorporating destructive and non-destructive sampling, allometric and predictive modelling, laboratory-based elemental analysis, and multi-sensory remote sensing (RS) based datasets. Predicted TBC density has been mapped within the wetland influence zone (WIZ) of the study site. Point-specific sample data (n = 250) has been used for the determination of the soil organic C (SOC) prediction model. Spline interpolation, displaying highest R2 value (R2 = 0.74) has been chosen for spatially explicit modelling of total SOC stock. Above ground biomass (AGB) was determined using the relationship between remotely sensed data (ALOS PALSAR-2 and Pleiades-1B) and in-situ dendrometric variables (viz. wood density, tree height, and girth at breast height). Here, among the different parametric and nonparametric models to estimate AGB, the BP-ANN models, specifically model number 22 (adjusted R2 = 0.84, MSE = 1.28, AIC = 3.67, BIC = 1.60), has been identified as the best-fit one with higher adjusted R2 and lesser AIC and BIC values. Indirect allometric equations involving modelled AGB values had been used to generate spatially explicit community-specific below ground biomass values at per pixel basis (∼2 m). Above and below ground C were estimated from these raster data. Integrating all these datasets in a GIS platform, the overall TBC stock of the mangrove was recorded at 246710.91 Mg. The TBC density of mangrove WIZ had revealed considerable variations, ranging from 0.34 Mg ha−1 to 881.50 Mg ha−1. Cumulatively, the study attempted to amalgamate all facets of blue C pools with satisfactory accuracy. This holistic methodology may further aid in regional C stock inventorization, management, and policy formulation, thereby strengthening th
ISSN:0378-1127
1872-7042
DOI:10.1016/j.foreco.2023.121345