Assessing the spatiotemporal consistency of satellite-derived leaf area index products across the Tibetan Plateau

Vegetation dynamics across the Tibetan Plateau are shifting under climate change, yet our understanding remains hindered by uncertainties among satellite products. We assessed the consistency of seven Leaf Area Index (LAI) products (2001–2018) in capturing mean states and spatiotemporal trends: MODIS, GIMMS, GLOBMAP, GLASS-AVHRR, GLASS-MODIS, HIQ, and GEOV2. Results revealed high agreement on climatological means (Pearson's r > 0.75, p < 0.001), whereas agreement was much lower regarding long-term dynamics (r < 0.6). Only GLOBMAP, GLASS-MODIS, and GEOV2 identified significant greening (0.0059, 0.0052, and 0.0093 m2 m−2 yr−1, p < 0.05), while MODIS, GIMMS, GLASS-AVHRR and HIQ showed non-significant trends. Spatial trend heterogeneities peaked in southeastern forest-dominated regions (<2200 m), which may be related to complex canopy structures. In pixel‑scale analysis, 77% of the vegetated areas lacked consistent and significant trends. Only 0.66% showed unanimous greening across all products, mainly in the northeastern Tibetan Plateau. High consistency occurred in a warm-dry core (10–15°C, 50–150 mm) but weakened toward colder or wetter regimes. These patterns likely reflect sensor disparities, retrieval algorithms, and the extreme environments. These findings provide a comprehensive assessment of the consistency among multiple satellite LAI products and have important implications for monitoring vegetation responses to environmental change.