Spectral signatures represent the unique pattern of reflectance or emittance of electromagnetic energy by different surface materials, which allows remote sensing technologies to identify and classify various land use and land cover (LULC) types. These signatures are influenced by multiple factors that affect the accuracy and reliability of LULC mapping using geoinformatics tools. One of the primary factors is the intrinsic properties of the surface material itself. Vegetation type, soil composition, water bodies, and built-up areas each have distinct spectral responses. For example, healthy vegetation shows high reflectance in the near-infrared (NIR) region due to chlorophyll absorption in the visible spectrum, whereas bare soil exhibits higher reflectance in the red and shortwave infrared (SWIR) bands depending on its mineral content. Similarly, water absorbs most visible and NIR radiation, appearing dark in satellite imagery. Another crucial factor is moisture content, which can significantly alter spectral signatures. Soils with high moisture tend to show lower reflectance in visible and NIR regions because water absorbs energy, whereas dry soils reflect more light. In vegetation, water stress or seasonal changes can reduce chlorophyll content, modifying the spectral response, which