The contribution of remote sensing and machine learning in the mapping, climate and environmental study of the Ouled Abdoun basin

Abstract

The phosphatic basin of Ouled Abdoun, located in the northwest of Morocco, is widely recognized as one of the most important phosphate basins globally. It holds considerable economic significance, both for Morocco and for global phosphate supply. The use of satellite imagery facilitates mapping in the Ouled Abdoun basin. Analysis of band reports demonstrates that the Ouled Abdoun basin is rich in clayey, carbonated, and marly terrains. Mapping of the Ouled Abdoun basin using machine learning with the help of Google Earth Engine, through the creation of NDVI and NDWI maps, helps to specify vegetation densities and the amount of water present in the Ouled Abdoun basin. Additionally, the extraction of graphs and maps of precipitation, temperature, and air quality provides visualization of the climate in the Ouled Abdoun basin. The analysis of our study area using machine learning (Google Earth Engine) has revealed several important environmental trends. We observed that vegetation is concentrated in the Tadla plain and the northern part of the basin, and it is closely related to precipitation, while the temperature of the basin has risen significantly during this period, with a temperature increase of 4°C in just 17 years, regarding air quality, we found that the concentration of CO was moderate, with a decrease in 2020.