Assessing spatiotemporal dynamics and drivers of ecological environment quality using RSEI in the Bayannur region of the Three-North Shelter Forest Program, China

Quantitative assessment of ecological environment quality dynamics is fundamental to evaluating large-scale ecological restoration. This study applied the Remote Sensing Ecological Index to the Three-North Shelter Forest Program’s Bayannur section using Landsat and MODIS imagery from 2002 to 2022. Theil-Sen trend analysis, Mann–Kendall testing, transition matrices, and Geodetector were used to characterize spatiotemporal changes and quantify driving factors. Key findings are as follows. The regional mean RSEI increased from 0.46 to 0.48, but the Fair grade consistently covered over 70 percent of the area, indicating limited recovery. The 2013 summer minimum of 0.36 was caused by anomalous hydrometeorological conditions, while the 2018 peak of 0.52 coincided with above-average precipitation and fell within the period of intensive TNSFP implementation, suggesting a potential synergistic effect that warrants further investigation with direct afforestation data. Over 70 percent of pixels showed no statistically significant trend (|Z|< 1.96), with significant improvements concentrated in eastern and central-southern oasis zones; however, non-significant trends should not be interpreted as ecological stability. The Fair grade had 91.90 percent self-retention, while the Moderate grade showed high mobility. During 2018 to 2022, downgrade probabilities from Good to Moderate and Moderate to Fair reached 24.47 percent and 67.57 percent, highlighting ecological fragility. Elevation showed the largest explanatory power for RSEI spatial heterogeneity (q values 0.270 to 0.494), followed by precipitation (0.227 to 0.379), while temperature influence weakened. The interaction of precipitation and elevation produced the strongest pairwise effect (q values 0.578 to 0.750), suggesting that elevational stratification of water availability is the primary spatial association pattern. These results provide robust evidence for assessing TNSFP outcomes and adaptive governance in drylands.