Cross-Scale Consistency and Scale Effects of Vegetation Phenology Across China: Evidence from MODIS Data

Vegetation phenology derived from satellite vegetation indices is sensitive to spatial scale, yet how spatial aggregation affects phenological timing and temporal dynamics across broad geographical extents remains insufficiently understood. In this study, the 250 m MOD13Q1 Enhanced Vegetation Index (EVI) time series from 2000 to 2024 was used as a common data source, and 1 km and 5 km datasets were generated directly through spatial aggregation. By maintaining the same sensor, vegetation index, temporal sampling, and phenology retrieval method across scales, this controlled within-source framework minimizes confounding effects associated with cross-sensor differences. The start of the growing season (SOS) and end of the growing season (EOS) were retrieved using asymmetric Gaussian fitting combined with a dynamic threshold method. Their spatiotemporal patterns, aggregation-induced cross-scale consistency, and bias were systematically analyzed. The broad spatial patterns of multi-year mean SOS and EOS remained generally consistent across the three scales. SOS showed an overall advancing tendency and EOS an overall delaying tendency, while the proportion of pixels with relatively large trend magnitudes decreased at coarser spatial scales. Cross-scale correlations remained high across all scale pairs and generally increased with latitude, with SOS exhibiting higher cross-scale consistency than EOS. Annual SOS correlations declined during 2000–2024, whereas EOS correlations increased during the early part of the record and declined thereafter, with a breakpoint around 2010. The bias showed clear differences in direction and magnitude between SOS and EOS and among vegetation types, and its absolute magnitude generally increased with increasing scale disparity. These results indicate that aggregation-induced phenological responses are not spatially uniform but vary systematically with geographical context, vegetation type, and phenological phase. These findings provide a scientific reference for the cross-scale comparison and scale transformation of multi-source remotely sensed phenology products, as well as for studies of regional ecological processes.