Integrating Deep Learning Image Classification with Green Fintech Platform for Carbon Credit Validation

Abstract

Carbon credit markets face persistent challenges of credibility, transparency, and costly verification processes—factors that enable greenwashing and erode trust. To address this, we propose a novel framework that integrates state-of-the-art deep learning image classification with blockchain-based green fintech systems, enabling automated, verifiable carbon credit validation. Drawing on cutting-edge methodologies such as efficient machine learning techniques within blockchain solutions, and AI-driven green financing paradigms, our approach fuses remote-sensing based deep learning models with smart-contract issuance of carbon tokens to ensure immutable audit trails and real-time validation.

We construct and curate a labeled dataset consisting of high-resolution satellite and drone imagery from verified carbon offset sites and control regions, preprocessed to enhance vegetation signal (e.g., through NDVI). We train and evaluate multiple image classification architectures—ResNet-50, EfficientNet-B0, DenseNet-121, MobileNet-v2, and a Vision Transformer—adapted and fine-tuned for binary detection of vegetation health and land-cover change. Comparative performance is quantified using accuracy, F1-score, and computational cost metrics, in line with best practices in model benchmarking.

Subsequently, the superior performing model is embedded within a blockchain-enabled fintech platform: verified image outputs trigger smart contracts to mint or retire carbon tokens, with immutable metadata including image hashes, classification outcomes, and timestamps stored on-chain. This leverages fintech’s capacity to enhance corporate carbon emission efficiency and sustainability and aligns with the emerging responsible FinTech paradigms.

Our integrated system addresses the limitations of manual MRV, deters fraudulent claims, and supports scalable, transparent carbon markets. It contributes to both artificial intelligence and green fintech literatures by demonstrating a practical, technically robust pathway for verifiable carbon credit issuance—thereby reinforcing climate finance integrity.