Biodiversity, as the foundation of ecosystem services, provides humans with essential living environments and abundant resources.Conducting quantitative biodiversity evaluation is crucial for advancing ecological civilization and achieving high-quality development. Taking dongzhai national nature reserve (Xinyang City, Henan Province) as a case study, we established a remote sensing assessment system for biodiversity by integrating Landsat satellite imagery series and selecting eight representative indicators across three hierarchical dimensions (species, landscape, and ecosystem diversity) based on inter-level ecological correlations, indicator significance, and local characteristics. Specifically, species diversity was quantified using the enhanced vegetation index (EVI), habitat quality index (HQI), and Water Network Density Index (WNDI); ecosystem diversity was characterized by the Percentage of Habitat Area (Sp); while landscape diversity was evaluated through four complementary indices: the Splitting Index (SPLIT), Contagion Index (CONTAG), Simpson's Diversity Index (SIDI), and Shannon's Diversity Index (SHDI). This systematic framework enables comprehensive biodiversity monitoring through synergistic analysis of spectral, spatial and compositional features derived from multi-temporal remote sensing data.Via analytic hierarchy process (AHP), centroid shift modeling, Sen+Mann-Kendall trend analysis, and Hurst index methods. Through remote sensing analysis and modeling approaches, we conducted a comprehensive quantitative assessment of both spatiotemporal evolution patterns and future change trends of biodiversity in the protected area during the 2011-2023 period.Key findings revealed: The biodiversity index (BI) exhibited an overall high level with a "south-high, north-low" spatial pattern, where the northwestern areas are predominantly occupied by residential settlements, construction lands, and scenic spots with frequent human engineering activities, while the southern regions are mainly covered by densely vegetated primitive forest areas. BI showed a trend of gradual increase in high-value areas and stabilization in low—value areas. The BI value ranges for the years 2011, 2015, 2019 and 2023 were 0.0878-0.7916, 0.0879-0.7962, 0.0874-0.7926 and 0.0874-0.7976 respectively,showing a trend of gradual increase in high-value areas and stabilization in low—value areas during 2011–2023.Projections indicate 98% of the reserve will maintain consistent future trends. During the 2011-2023 period, high biodiversity level areas consistently accounted for over 80% of the study area, displaying a trend of initial increase followed by decrease and subsequent stabilization, whereas low biodiversity level areas exhibited a slow annual increase before stabilizing, with degraded areas(23.71%) slightly exceeded improved areas (20.75%), and the distribution centroid shifted from Pengxin Town to Lingshan Town before stabilizing.This study shows that remote sensing assessment system, incorporating eight indicators across three dimensions of species diversity, landscape diversity, and ecosystem diversity, demonstrates strong representativeness, timeliness, operational feasibility and data accessibility, enabling efficient evaluation of spatiotemporal biodiversity evolution in protected areas.