Mediterranean forests play a crucial role in the well-being of humanity and the health of our planet. This study explores the role of Mediterranean forests in carbon capture and storage, soil protection and biodiversity conservation. Forests absorb CO2 during photosynthesis, stabilize the soil by reducing erosion, and provide essential habitats for many species. Urban planning plays an important role in climate change mitigation through the creation of green spaces and ecological corridors. From a methodological point of view, the analysis and forecasting are based on the use of remote sensing data and historical data to develop land use simulation models. The study uses Artificial Intelligence (AI) technology to obtain predictions of land use changes. An integrated model of Random Forest and Markov Chain applied to the forests of the Calabria Region is proposed. This approach offers substantial scientific support for sustainable land management policies. The model achieved an accuracy of 99.88%, making it a reliable tool for predicting the dynamics of Mediterranean forests. The results highlight the importance of sustainable forest management to mitigate climate change and conserve biodiversity.

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Mediterranean Forests: Climate Change Mitigation and Soil Conservation

  • Vincenzo Barrile,
  • Alessandra Barresi,
  • Luigi Bibbò,
  • Emanuela Genovese,
  • Giuliana Bilotta,
  • Giuseppe M. Meduri,
  • Francesca Moraci

摘要

Mediterranean forests play a crucial role in the well-being of humanity and the health of our planet. This study explores the role of Mediterranean forests in carbon capture and storage, soil protection and biodiversity conservation. Forests absorb CO2 during photosynthesis, stabilize the soil by reducing erosion, and provide essential habitats for many species. Urban planning plays an important role in climate change mitigation through the creation of green spaces and ecological corridors. From a methodological point of view, the analysis and forecasting are based on the use of remote sensing data and historical data to develop land use simulation models. The study uses Artificial Intelligence (AI) technology to obtain predictions of land use changes. An integrated model of Random Forest and Markov Chain applied to the forests of the Calabria Region is proposed. This approach offers substantial scientific support for sustainable land management policies. The model achieved an accuracy of 99.88%, making it a reliable tool for predicting the dynamics of Mediterranean forests. The results highlight the importance of sustainable forest management to mitigate climate change and conserve biodiversity.