Mangrove environments have garnered attention in recent years as a result of their substantial contribution to the earth's dynamic. Its function in carbon sequestration within coastal sediments helps alleviate climate change. Mangrove ecosystems, characterized by various tree species, face numerous threats and require continuous monitoring for conservation efforts, which can be facilitated by remote sensing. Biodiversity monitoring and the detection of different species demand highly specific techniques. This study introduces a comprehensive analysis of in situ spectral signatures for two mangrove species found in Egypt. We assessed these spectral signatures and organized them into a spectral library to classify high-resolution Pleiades Neo satellite images using linear unmixing techniques to differentiate the mangrove species. The results were significant, allowing us to distinguish five halophyte coastal species and accurately identify the two mangrove species, Avicennia marina and Rhizophora mucronata, with an accuracy assessment of 89.83%.