Desertification is a critical global ecological and environmental challenge, posing direct threats to land productivity, biodiversity, and ecosystem stability. Effective desertification monitoring is fundamental for the development of prevention and mitigation strategies. However, existing remote sensing-based monitoring approaches often fail to comprehensively incorporate the natural physical characteristics of the land surface, leading to limitations in monitoring completeness. To address this gap, this study proposes a Desertification Composite Index (DCI) that integrates physical and natural surface attributes based on Landsat series remote sensing data. The study focuses on the Ring-Tarim Basin and selects six key remote sensing indicators: fraction vegetation coverage (FVC), temperature vegetation dryness index (TVDI), land surface albedo (Albedo), land surface temperature (LST), topsoil grain size index (TGSI), and the modified soil-adjusted vegetation index (MSAVI). The Analytic Hierarchy Process (AHP) was employed to assign weights to these indicators, constructing a comprehensive desertification index. The accuracy of the proposed index was validated using 109 UAV-measured field samples, yielding an overall accuracy of 0.86 and a Kappa coefficient of 0.8. Results indicate that desertification in the Ring-Tarim Basin exhibits distinct spatial heterogeneity: the western and northern regions experience relatively lower desertification degrees, whereas the eastern areas and desert margins are more severely affected. The proposed DCI-based approach enables accurate identification of desertification patterns across different regions and provides a reliable technical foundation for desertification control and ecological restoration strategies.