The Greenness Effect of Rural Tourism Brand Certification: Overall Masking and Localized Ecological Cost—Quasi-Experimental Evidence Based on “Overall–Local” Dual-Layer Identification Approach (2000–2025)

Rural tourism brand certification is widely regarded as a policy tool for synergistically promoting rural development and ecological protection, yet the theoretical premise that “certification equals protection” has long lacked rigorous empirical testing. Treating the certification of “National Key Rural Tourism Towns (Townships)” as a quasi-natural experiment, this study employs Mahalanobis distance matching and a multi-period difference-in-differences (DID) model. The “overall–local” dual-layer analysis is based on Normalized Difference Vegetation Index (NDVI) remote sensing panel data for 7 key towns (townships) and 13 control towns (townships) in Hubei Province from 2000 to 2025. DID estimates at the township scale show that brand certification did not produce a statistically significant change in NDVI (ATT = 0.0041, p = 0.441 under cluster-robust standard errors), and this conclusion holds after five robustness tests, an event study, and a statistical power analysis. However, when the analytical scale is disaggregated from the township level down to patch-scale degraded patches, brand certification is found to exhibit marginally significant additional degradation at the local scale within patches where forestland conversion has occurred (ATT = −0.0036, p = 0.073); the interaction term test shows that the forest-to-built-up effect is significantly larger than the forest-to-cropland effect (δ = 0.0363, p = 0.001) by a factor of about 12. Landsat 30 m validation shows that the direction of the effect is consistent with the main analysis (forest-to-built-up ATT = −0.0548, p = 0.049). The ΔNDVI difference between the treated and control groups indicates that conversion patches in key towns (townships) are accompanied by more pronounced greenness degradation (difference of −0.0401 for forest-to-built-up and −0.0037 for forest-to-cropland), and this result remains consistent in direction (all negative) after robustness tests including area weighting, exclusion of small patches, double-ended NDVI screening, and the collapse model. This nested pattern of “no significant effect detected overall, identifiable degradation signals locally” points to the governance illusion of “overall masking” conceptualized in this study: certification maintains a statistically “harmless” appearance at the macro scale, yet conceals real localized ecological costs beneath the mean through the structural offsetting of positive and negative ecological effects. Theoretically, this study advances the critique of sustainable tourism certification from macro-level questioning to micro-level causal evidence and mechanistic hypotheses; methodologically, it contributes a generalizable dual-layer framework for evaluating spatial policy effects; practically, it warns that post-certification monitoring urgently needs to shift from township-level means down to dynamic monitoring at the patch scale, and that the inevitable “trade-off” between tourism development and ecological protection must be confronted.