Impact of tree cover loss on carbon emission: a learning-based analysis

Butt, A. H., Jamshed, M. A., Ur Rahman, A., Alam, F., Shakya, M., Almadhor, A. S. and Ur-Rehman, M. (2023) Impact of tree cover loss on carbon emission: a learning-based analysis. Computational Intelligence and Neuroscience, 2023, 8585839. (doi: 10.1155/2023/8585839)

Abstract

Describing the processes leading to deforestation is essential for the development and implementation of the forest policies. In this work, two different learning models were developed in order to identify the best possible model for the assessment of the deforestation causes and trends. We developed autoregressive integrated moving average (ARIMA) model and long short-term memory (LSTM) independently in order to see the trend between tree cover loss and carbon dioxide emission. This study includes the twenty-year data of Pakistan on tree cover loss and carbon emission from the Global Forest Watch (GFW) platform, a known platform to get numerical data. Minimum mean absolute error (MAE) for the prediction of tree cover loss and carbon emission obtained through ARIMA model is 0.89 and 0.95, respectively. The minimum MAE given by LSTM model is 0.33 and 0.43, respectively. There is no such kind of study conducted in order to identify the increase in carbon emission due to tree cover loss most specifically in Pakistan. The results endorsed that one of the main causes of increase in the pollution in the environment in terms of carbon emission is due to tree cover loss.

• Item Type: Articles
• Additional Information: Acknowledgments: This study was supported by Innovative and Collaborative Research Grant under Pakistan-UK Education Gateway (ICRG-2020) (project no. 310366) (Deforestation in Pakistan: Combating through Wireless Sensor Networks (DePWiSeN)).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ur Rehman, Dr Masood and Jamshed, Dr Muhammad Ali
• Authors: Butt, A. H., Jamshed, M. A., Ur Rahman, A., Alam, F., Shakya, M., Almadhor, A. S., and Ur-Rehman, M.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Computational Intelligence and Neuroscience
• Publisher: Hindawi
• ISSN: 1687-5265
• ISSN (Online): 1687-5273
• Copyright Holders: Copyright © 2023 Abdul Haleem Butt et al
• First Published: First published in Computational Intelligence and Neuroscience 2023:8585839
• Publisher Policy: Reproduced under a Creative Commons license