Assessment of Sentinel-2A images for estimating rosemary land cover through an object-based image analysis approach

Rosemary is a medicinal plant widely used in the food and pharmaceutical industry. In Morocco, rosemary harvesting generates significant benefits for the local economy. Even though, decision makers are short of accurate information about its geographical distribution area. The aim of this study is to delineate the rosemary shrubs in the Oriental region in Morocco in order to provide guidance for the sustainable use of these natural resources. We therefore used the freely available images of Sentinel-2A for binary classification (rosemary shrubs and the other lands) through an object-based image-analysis approach. The random forest classifier was deployed and trained with different object features likewise spectral values and vegetation indices. As a result, the distribution area of rosemary is 240,747 ha, which represents 18% of the studied area. Besides, an encouraging overall accuracy of 94.24% was attained; the user's accuracy for the class of "rosemary" and "Others" is 93.3% and 95.0%, respectively; meanwhile, the producer's accuracy for "rosemary" and "Others" is 93.72% and 94.65%.