# Remote Sensing Technologies for Monitoring Argane Forest Stands: A Comprehensive Review
## 4 Remote Sensing Applications
### Land Use and Land Cover Assessment and Density Assessment  
Remote sensing, particularly satellite imagery, plays a crucial role in both land use and land cover assessment (LULCA) and change detection within Argane stand habitats. It allows researchers to categorize and map different land cover types, such as forest-coverchanges, global environmental changes [34], agricultural areas, urban development, and natural vegetation. Cameras mounted on satellite imagery, aircraft and radar provide a unique aerial perspective that serves mapping, land-use planning [35; 36; 37; 38], and environmental monitoring purposes exceptionally well [3; 39; 40; 41]; disaster response [42; 43; 44]; and sea ice monitoring [45; 46; 47; 48]. These technologies provide invaluable insights into land cover, vegetation, and dynamic changes over time, making them indispensable tools for researchers. By delineating the extent and distribution of land cover categories, scientists can assess the impact of land use changes on Agrane stand populations. LULC data help identify areas at risk due to factors like deforestation, urban expansion, or agricultural encroachment, providing essential insights for conservation planning. For example, [PERSON] et al. [49], focused on using a CNN-based model for change detection to map deforestation of Agrane forest stands, an UNESCO Biosphere Reserve located in the Souss-Massa region of Morocco from 2015 to 2020. [PERSON] et al. [50] analyzed the tree-cover changes between 1967 and 2019 in Agrane woodlands exhibiting different levels degrees of degradation across the provinces Chtouka-Ait Baha, Taroudant, and Agadir Ida-Outanane. [PERSON] et al. [51] conducted a study on the current state of forest species, specifically the Agrane stands (_Argania spinosa_), in Essaouira Province to analyze forest changes (degradation) and create innovative approaches for preserving this native tree species. [PERSON] et al. [52] assessed and analyzed the degradation of vegetation cover over the past three decades, spanning from 1984 to 2018, in regions of the Agraneiae Biosphere Reserve in Morocco. Tree density assessment involves specifically measuring the number of trees per unit area within a defined forested or vegetated area. It is a metric used to understand the density of tree populations within a particular region, forest, or ecosystem, and it is particularly valuable for vegetation analysis. The assessment of Agrane stand density has been conducted by various authors, including [PERSON] et al. [53] and [PERSON] et al. [54]. In the eastern region of Morocco, the area occupied by the Agrane forest stands covers 7.2 km\({}^{2}\), which is considerably lower compared to the southern region of Morocco, where it spans an area of 8300 km\({}^{2}\)[55]. Additionally, [PERSON] et al. [50] reported that Agrane stand densities can reach up to 300 trees and shrubs per hectare, with the average tree density increased from 58 trees per hectare in 1967 to 86 trees per hectare in 2019. This increase is primarily attributed to the proliferation of small trees with a diameter of less than 3 meters, often resulting from stump re-sprouting after the telling of larger trees in the provinces of Chtouka-Ait Baha, Taroudant, and Agadir Ida-Outanane. To enhance the monitoring and conservation of Agrane stands and other species, researchers should adopt advanced machine learning models for their high accuracy in detecting deforestation events from satellite imagery data. Integrating these models with multi-source data, including satellite imagery, on-ground observations, and historical records, can significantly improve the accuracy and comprehensiveness of land use and land cover assessment (LULCA) and change detection. This integration will allow for more precise identification of areas at risk due to deforestation, urban expansion, and agricultural encroachment. Policymakers should leverage these findings to develop and enforce targeted conservation strategies, focusing on high-risk regions identified through remote sensing studies.