Despite their proximity to the coast, few studies have focused on identifying and mapping the vegetation of Algerian islands and islets. To fill this lacuna, our work, using satellite images and machine learning methods, is mainly aimed at identifying and mapping the main vegetation groups on a few islands, while evaluating the effectiveness of the random forest classifier, which is effectively used in the study of the vegetation of large areas. However, despite the high heterogeneity of their vegetation cover, the use of very high-resolution images (Pléaides and SPOT 6/7), through the fusion bands and derived bands (NDVI), has allowed the elaboration of a fairly precise vegetation map that can be used for the preparation of management and protection plans for these habitats. Our methodological approach revealed very satisfactory results, having allowed the identification of the plant communities inventoried in the field, while showing high accuracy values, ranging from 0.642 for the halophilic group of Asteriscus to 1 for the endemic Chasmophyte group of the Habibas archipelago (Pléiades images). The groups identified from SPOT 6/7 images show accuracy values between 0.67 for the Mediterranean cliff formations on Garlic Islet and 1 for the two formations (shrubby and herbaceous) of the Skikda islands. Our methodological approach, and notwithstanding the great heterogeneity and the very small surface areas of our islands and islets, has led to very satisfactory results, reflected with good overall accuracy and kappa index values (for Pléiades: overall accuracy > 92% and kappa index > 0.90; for SPOT 6/7: overall accuracy > 83% and kappa index > 0.80).

尽管它们靠近海岸，但很少有研究专注于识别和绘制阿尔及利亚岛屿和小岛的植被。为了填补这一空白，我们的工作使用卫星图像和机器学习方法，主要旨在识别和绘制少数岛屿上的主要植被群，同时评估随机森林分类器的有效性，该分类器有效地用于研究大面积的植被。然而，尽管它们的植被覆盖高度异质性，但通过融合带和衍生带 (NDVI) 使用非常高分辨率的图像（Pléaides 和 SPOT 6/7），可以绘制出相当精确的植被图，可用于为这些栖息地制定管理和保护计划。我们的方法论方法显示出非常令人满意的结果，Habibas群岛特有的Chasmophyte群的星号到 1 （Pléiades 图像）。从 SPOT 6/7 图像中识别出的组显示，大蒜岛上的地中海悬崖地层的准确度值介于 0.67 和斯基克达岛的两个地层（灌木和草本）的 1 之间。我们的方法论方法，尽管我们的岛屿和小岛的异质性很大且表面积很小，但已经产生了非常令人满意的结果，反映了良好的整体准确度和 kappa 指数值（对于 Pléiades：整体准确度 > 92% 和 kappa 指数 > 0.90；对于 SPOT 6/7：总体准确度 > 83% 和 kappa 指数 > 0.80）。