Abstract
This paper focuses on the quantitative modeling of desertification in Morocco’s Middle Atlas regions, Ain Nokra Forest. In order to map the degree of desertification in the forest in 2021, this study used Sentinel-2A images. More precisely, the spectral indices, such as the NDVI, albedo, and TCT indices, have first been calculated. After putting different combinations through a linear regression analysis, the feature space was created using the correlation ratio that is the most negative of these indices (NDVI–albedo, TCG–TCB, and TCW–TCB). With a correlation ratio of − 0.80, the TCG–TCB combination is the best, followed by the NDVI–albedo ratio, which has a correlation ratio of − 0.63. A desertification map for the entire forest has been created as a result of the first combination being used to propose the Desertification Degree Index (DDI). There are currently five categories of desertification (extreme, severe, moderate, low, and non-desertification). according to our model, the forest is progressively desertifying. Typically, 40% of the forest area is classified as having severe to intense desertification, while 51% is classified as having weak to moderate desertification. However, only 8.52% of the region is deemed to be “non-desertified”. Finally, due to its incredibly high overall accuracy of 88.32%, the model is almost optimal for quantitative analysis and monitoring of desertification in the Moroccan Middle Atlas.
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El Hairchi, K., Ben Brahim, Y., Ouiaboub, L. et al. Desertification modeling in the Moroccan Middle Atlas using Sentinel-2A images and TCT indexes (case of the Ain Nokra Forest). Model. Earth Syst. Environ. 9, 4279–4293 (2023). https://doi.org/10.1007/s40808-023-01752-z
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DOI: https://doi.org/10.1007/s40808-023-01752-z