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September 23, 2025Kastamonu University Journal of Forestry FacultyOpen Access

Estimation of Aboveground Carbon Using Different Remote Sensing Data and Modelling Techniquesa

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Authors

HAHasan AksoyAGAlkan Günlü

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Overview

This analysis demonstrates successful AGC prediction using remote sensing and modeling techniques, highlighting ANN and MLR effectiveness.

Key Points

  • Estimating aboveground carbon can be effectively achieved using various remote sensing data.
  • The study revealed texture variables from Sentinel-2 produced the highest accuracy for AGC with R2=0.86.
  • Artificial neural networks and multiple linear regression modeling techniques significantly enhanced AGC predictions.
  • Field measurements from 184 sample plots provided a robust dataset for model fitting and testing.

Cite This Study

Aksoy et al. (2025) studied this question.

synapsesocial.com/papers/68d4726431b076d99fa6b930https://doi.org/10.17475/kastorman.1787120
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