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January 1, 2025International Journal of Environment and Waste Management

A Fusion model for the accurate Above-Ground Biomass (AGB) estimation from Satellite Images using GAN-CNN

R. Geetha S. Arumaishiney Shobana R

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Key Points

The central aim is to develop a fusion model combining GAN and CNN for precise estimation of above-ground biomass.
Developed a machine learning model using Generative Adversarial Networks (GAN) and Convolutional Neural Networks (CNN).
Applied the model to satellite images to assess above-ground biomass.
Conducted validation tests to evaluate estimation accuracy.
Achieved significant improvements in biomass estimation accuracy compared to traditional methods, with a reported accuracy of X% (actual figure not specified).
Demonstrated the model's ability to generalize across different ecological settings, enhancing ecological monitoring capabilities.

Implication

Demonstrates accurate biomass estimation from satellite images using GAN-CNN, suggesting improved ecological monitoring.

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Cite This Study

Geetha et al. (2025) studied this question.

synapsesocial.com/papers/6a095ba67880e6d24efe185c https://doi.org/10.1504/ijewm.2025.10078442

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Keep reading

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