PELAGIX: An Intelligent Decentralized Framework for Verified Quantification and Transparent Trading of Blue Carbon Assets

Abstract

Mangrove carbon assessments require spatially explicit methods whose assumptions, data support, and verification status remain traceable. This study presents an integrated workflow for operational mangrove mapping, modeled above-ground carbon (AGC) estimation, complementary carbon accounting, parameter sensitivity, and a prototype digital measurement, reporting, and verification (MRV) provenance layer for a Sundarbans area bounded by approximately 88.10–89.10°E and 21.50–22.35°N. Sentinel-2 surface-reflectance observations from 1 January to 30 April 2023 were cloud-screened, median composited, and used to calculate NDVI; NDVI > 0.4 defined the operational mangrove mask. The supplied Google Earth Engine workflow quality-screened GEDI monthly rh100, median-composited it, applied its original rh100/100 transformation, and filled unobserved structural values using 15× NDVI. Biomass and carbon were modeled as AGB = H× NDVI× 10.5 and AGC = 0.47× AGB. The retained raster footprint contains 15,793,243 mangrove cells (157,932.43 ha under the nominal 0.01 ha-per-cell convention). Mean AGC density was 2.8060 t C ha?1 (median 2.7935; standard deviation 0.6325), with total modeled AGC of 443,164.99 t C and derived AGB of 942,904.24 t. A separate InVEST baseline reports 409,383 t C. Combined variation of the project-specific AGB coefficient and carbon fraction produced 343,486.54–550,027.47 t C (-22.49% to +24.11%); this is parameter sensitivity, not a confidence interval. GEE and InVEST outputs are complementary, non-equivalent model results. The prototype demonstrates evidence handling and digital provenance workflows, not carbon-credit certification or independent verification. No independent field validation was available, and reported values represent modeled above-ground carbon rather than total ecosystem carbon.

Introduction

This study presents an integrated remote-sensing and digital monitoring workflow to estimate above-ground carbon (AGC) in the Sundarbans mangrove ecosystem. Mangroves play a crucial role in protecting coastal areas, supporting fisheries, maintaining biodiversity, and storing carbon that helps mitigate climate change. Accurate carbon assessment is important for understanding their environmental value and potential contribution to climate action.

The study combines Sentinel-2 satellite imagery, GEDI lidar data, Geographic Information Systems (GIS), and the InVEST carbon model to analyze mangrove vegetation and estimate above-ground carbon. Sentinel-2 imagery is processed to calculate the Normalized Difference Vegetation Index (NDVI), while GEDI data provide canopy-structure information. These variables are integrated using project-specific equations to estimate above-ground biomass and carbon density. QGIS and Google Earth Engine support data processing, visualization, and quality control.

The methodology also includes a separate InVEST-based carbon estimate, sensitivity analysis, geospatial quality checks, and a proposed digital Measurement, Reporting, and Verification (MRV) framework for tracking environmental data and carbon-asset provenance. The digital framework aims to improve the traceability and transparency of carbon estimates.

However, the study acknowledges several limitations. The available raster data cover only part of the analytical area, the biomass estimation equation lacks independent field calibration, and some missing GEDI canopy-height values are filled using NDVI-based estimates. Furthermore, the analysis considers only above-ground carbon rather than the complete ecosystem carbon stock, which also includes below-ground biomass, dead organic matter, and soil carbon.

Conclusion

This study documents a spatially explicit workflow combining 2023 Sentinel-2 vegetation information, quality-screened GEDI rh100, project-defined height processing and gap filling, modeled AGB and AGC, a separate InVEST baseline, parameter sensitivity, and a proposed evidence-centric digital-MRV layer. For the retained raster footprint, mapped mangrove extent is 157,932.43 ha and total modeled AGC is 443,164.99 t C; InVEST separately reports 409,383 t C under its supplied LULC and pool parameters. Combined parameter scenarios span 343,486.54–550,027.47 t C, demonstrating sensitivity rather than statistical uncertainty. These values represent modeled above-ground carbon and are not independently field-validated or equivalent to total ecosystem carbon. The prototype demonstrates evidence handling and provenance, not certified credits or independently verified environmental quantities. Field validation, stronger support and uncertainty records, and external verification remain necessary before any application to credit issuance or trade.

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Copyright

Copyright © 2026 Sanket Jaiswal, Satish Patel, Soham Nimje, Prachi Jain, Spandan Karandikar, Srujan Barshe. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.