Hybrid Machine Learning Approach to Model Cedar Forest Cover Changes in Morocco’s Middle Atlas
DOI:
https://doi.org/10.54386/jam.v28i2.3284Keywords:
Atlas Cedar, Forest dynamics, Climate change, Random forest, Cellular automata, Sentinel, LandsatAbstract
The Atlas cedar forests in the Moroccan Middle Atlas, particularly the Sidi M'Guild region, are undergoing rapid degradation due to increasing climatic stress and anthropogenic pressure. This study introduces a hybrid modelling approach integrating random forest (RF), cellular automata (CA) and Markov chains to simulate forest cover dynamics from 1990 to 2032. The model integrates remote sensing data from Landsat 4, 8 and Sentinel-2, bioclimatic variables (temperature, seasonality, rainfall of the driest quarter) and indicators of human influence (density of occupancy, proximity to forest edges). The results project a 91% decline in Cedrus atlantica and a 74% decline in juniper, contrasted with a 1,290% expansion of holm oak, indicating a major ecological shift to drought-tolerant hardwoods. The RF–AdaBoost classifier achieved 98% accuracy, and the RF–CA–Markov framework demonstrated strong predictive power (Kappa = 0.72). These results offer a solid tool to anticipate forest transitions and guide adaptive forest management strategies, aligned with Morocco's national reforestation efforts.
References
Alba-Sánchez, F., Abel-Schaad, D., López-Sáez, J. A., Romera-Romera, D., Pérez-Díaz, S., & González-Hernández, A. (2025). Seven Millennia of Cedrus atlantica Forest Dynamics in the Western Rif Mountains (Morocco). Forests, 16(9), 1441. https://doi.org/10.3390/f16091441
Asif, M., Kazmi, J. H., Tariq, A., Zhao, N., Guluzade, R., Soufan, W., Almutairi, K. F., Sabagh, A. E., & Aslam, M. (2023). Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest. Geocarto International, 38(1), 2210532. https://doi.org/10.1080/10106049.2023.2210532
Beroho, M., Briak, H., Cherif, E. K., Boulahfa, I., Ouallali, A., Mrabet, R., Kebede, F., Bernardino, A., & Aboumaria, K. (2023). Future Scenarios of Land Use/Land Cover (LULC) Based on a CA-Markov Simulation Model : Case of a Mediterranean Watershed in Morocco. Remote Sensing, 15(4), 1162. https://doi.org/10.3390/rs15041162
Chafik, H., Berrada, M., Legdou, A., Amine, A., & Lahssini, S. (2020). Exploitation of spectral indices NDVI, NDWI & SAVI in Random Forest classifier model for mapping weak rosemary cover : Application on Gourrama region, Morocco. 2020 IEEE International conference of Moroccan Geomatics (Morgeo), 1‑6. https://doi.org/10.1109/Morgeo49228.2020.9121895
El Mhamdı, A., Aarab, M., & El Fariati, A. (2023). Evaluation of the Accuracy of Open-Source DEMs using GPS Data. International Journal of Environment and Geoinformatics, 10(1), 41‑50. https://doi.org/10.30897/ijegeo.1119695
El Moussaoui, E., Moumni, A., & Lahrouni, A. (2024). Assessing the influence of different Synthetic Aperture Radar parameters and Digital Elevation Model layers combined with optical data on the identification of argan forest in Essaouira region, Morocco. iForest - Biogeosciences and Forestry, 17(2), 100‑108. https://doi.org/10.3832/ifor4183-016
Grinand, C., Vieilledent, G., Razafimbelo, T., Rakotoarijaona, J., Nourtier, M., & Bernoux, M. (2020). Landscape‐scale spatial modelling of deforestation, land degradation, and regeneration using machine learning tools. Land Degradation & Development, 31(13), 1699‑1712. https://doi.org/10.1002/ldr.3526
Kamusoko, C., Wada, Y., Furuya, T., Tomimura, S., Nasu, M., & Homsysavath, K. (2013). Simulating Future Forest Cover Changes in Pakxeng District, Lao People’s Democratic Republic (PDR) : Implications for Sustainable Forest Management. Land, 2(1), 1‑19. https://doi.org/10.3390/land2010001
Laaribya, S., Alaoui, A., Ayan, S., & Dindaroglu, T. (2024). Changes in the potential distribution of atlas cedar in morocco in the twenty-rst century according to the emission scenarios of RCP 4,5 and RCP 8,5. Forestist, 74(1), 16-25. https://doi.org/10.5152/forestist.2023.0004
Legdou, A., Chafik, H., Amine, A., Lahssini, S., & Berrada, M. (2020). A Random Forest-Cellular Automata Modeling Approach to Predict Future Forest Cover Change in Middle Atlas Morocco, Under Anthropic, Biotic and Abiotic Parameters. In A. El Moataz, D. Mammass, A. Mansouri, & F. Nouboud (Éds.), Image and Signal Processing (Vol. 12119, p. 91‑100). Springer International Publishing. https://doi.org/10.1007/978-3-030-51935-3_10
Legdou, A., Amine, A., Lahssini, S., Chafik, H., & Berrada, M. (2022). Predicting Forest Cover Change in Middle Atlas Morocco : A Logistic–CA–Markov Approach. In J. C. Bansal, A. Engelbrecht, & P. K. Shukla (Éds.), Computer Vision and Robotics (p. 229‑239). Springer Singapore. https://doi.org/10.1007/978-981-16-8225-4_18
Linares, J. C., Taïqui, L., & Camarero, J. J. (2011). Increasing Drought Sensitivity and Decline of Atlas Cedar (Cedrus atlantica) in the Moroccan Middle Atlas Forests. Forests, 2(3), 777‑796. https://doi.org/10.3390/f2030777
Mei, K., Tan, M., Yang, Z., & Shi, S. (2022). Modeling of Feature Selection Based on Random Forest Algorithm and Pearson Correlation Coefficient. Journal of Physics: Conference Series, 2219(1), 012046. https://doi.org/10.1088/1742-6596/2219/1/012046
Merhej, O., Ali, M., & Thabeet, A. (2025). Using CA-Markov Model to Predict Land Use/Land Cover Changes in Bayer and al-Bassit region, Latakia, Syria. Journal of Agricultural and Marine Sciences, 27(2), 50‑58. https://doi.org/10.53541/jams.vol27iss2pp50-58
Mokhtari, N., Mrabet, R., Lebailly, P., & Bock, L. (2014). Spatialisation des bioclimats, de l’aridité et des étages de végétation.
Mounir, S., Saoud, N., Charroud, M., Mounir, K., & Choukrad, J. (2019). The Middle Atlas Geological karsts forms : Towards Geosites characterization. Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles, 74, 17. https://doi.org/10.2516/ogst/2018089
Rhanem, M. (2011). Aridification du climat régional et remontée de la limite inférieure du cèdre de l’Atlas (Cedrus atlantica Manetti) aux confins de la plaine de Midelt (Maroc). Physio-Géo, Volume 5, 143‑165. https://doi.org/10.4000/physio-geo.1983
Simou, M. R., Houran, N., Benayad, M., Maanan, M., Loulad, S., & Rhinane, H. (2024). MONITORING FOREST DEGRADATION OVER FOUR DECADES USING REMOTE SENSING AND MACHINE LEARNING CLASSIFICATION ALGORITHMS IN BOUSKOURA, MOROCCO. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-4/W9-2024, 337‑342. https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-337-2024
Sharma, L. K., Sinha, S. K., & Saha, B. (2018). Agrometeorological indices for growth and yield of major forest species in semi-arid region of India. Journal of Agrometeorology, 20(4), 306–311. https://doi.org/10.54386/jam.v20i4.720
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 ANASS LEGDOU, AYOUB SOUILEH, BOUCHRA NASSIH, SAID LAHSSINI, AOUATIF AMINE
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is a human-readable summary of (and not a substitute for) the license. Disclaimer.
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
