# Multi-Source Satellite Imagery and Machine Learning
## 4 Materials and Methods
### Dataset
#### 4.1.1 Extraction of Geological Parameters  
The optical and radar images were fused using a discrete wavelet transform (TOD). This method provides an Optical Radar (OR) image, preserving the radiometric richness of LANDSAT images while integrating the textural properties of radar images, producing hybrid OR images with an improved resolution of 12.5 m.  
The SRTM DEM provides foundational data for extracting morphometric parameters (Data 1) critical for geological analysis. These parameters help distinguish between various lithological units and structural features. * Altitude: The altitude map highlights the spatial distribution of elevations, distinguishing between plains, plateaus, and mountainous regions. This parameter helps identify lithological boundaries, such as rhyloitic massifs, traclytic formations, and granitoid outcrops. In this study, altitude is a key variable influencing the spatial distribution of geological units, as elevation often correlates with rock type and soil properties. * Slope: Slope data, derived from the DEM, captures the terrain's steepness and helps reveal geomorphological structures, such as fault lines and lithological contacts. The model uses slope variations to classify areas prone to erosion, infiltration, or surface runoff, which are often linked to specific geological formations. * Aspect (Slope Orientation): Aspect data provide information on slopes' directional exposure, which can influence weathering processes and vegetation patterns and indirectly reflect underlying geological structures. In Random Forest classification, the aspect contributes to identifying structural trends and the orientation of geological units. * Hillshade: The hillshade layer enhances the visualization of topographic features by simulating shadow effects, highlighting linear structures, such as faults and fractures. This is particularly valuable for the model, as it improves the differentiation of geological units based on structural discontinuities. * Hydrographic network and drainage density: The hydrographic network, extracted from the DEM, offers insight into the relationship between surface water flow and geological formations. Drainage density is a critical variable in the model, as it reflects substrate permeability and structural controls on surface water movement. Highly drained areas often correspond to impermeable rocks or fault zones, while poorly drained areas indicate permeable substrates conducive to groundwater infiltration. * Soil map as environmental predictors: Soil characteristics are closely linked to underlying geology and are essential for refining geological mapping. The study integrates soil maps that classify regions into ferrallitic, hydromorphic, and poorly developed soils, each corresponding to specific lithological settings. In the model, soil types serve as categorical predictors, improving the accuracy of lithological classification. * Geomorphological map: Understanding the geomorphological framework is critical for geological mapping. The Western Highlands of Cameroon present a highly diverse relief, ranging from lowland plains to mountainous regions exceeding 2700 m. These geomorphological contrasts are integrated into the model as contextual vari  
Principal component analysis (PCA) was applied to reduce spectral redundancy and extract meaningful information from satellite and hybrid images. This statistical technique made it possible to transform LANDSAT image bands and neo-channels resulting from the fusion of radar and optical images into a set of orthogonal principal components, capturing the majority of the variance of the initial data. The first five principal components (PCs) explained more than 90% of the variance, providing valuable information for lithological and structural discrimination. Specific components were correlated explicitly with distinct geological characteristics: CP4 enhanced the signatures of trachytes, while CP5 highlighted enginess.