AHI LAI: a seamless 500 m, 4-day leaf area index dataset of the Asia-Pacific region (2015–2025) generated from geostationary Himawari-8/9 observations

Vegetation plays a critical role in Earth system processes, making the monitoring of vegetation dynamics a fundamental component of global change research. Leaf area index (LAI) acts as a primary indicator for assessing vegetation canopy structure. Optical observations from polar-orbiting satellites often experience data gaps because relatively infrequent observation opportunities can coincide with regional cloud cover. High-frequency measurements from geostationary sensors, including the Himawari-8/9 Advanced Himawari Imager (AHI), increase the probability of capturing valid surface signals during transient cloud-free windows. In this study, a Himawari-MODIS fusion framework integrating polar-orbiting satellite LAI observations with geostationary satellite reflectance data was developed and applied to produce a long-term, spatially seamless and high-temporal-resolution AHI-based LAI dataset for the Asia-Pacific. Biome-specific Random Forest models were trained using filtered MODIS LAI as benchmarks to estimate LAI from AHI data. A modified singular spectrum analysis (mSSA) algorithm with spatiotemporal neighbor selection was implemented to reconstruct missing values. The resulting data were subsequently downscaled utilizing spatial texture patterns derived from MODIS LAI data. This AHI LAI product features a 500 m spatial resolution and a 4-day temporal resolution, spanning from 2015 to 2025. Validation against in situ LAI measurements showed that AHI LAI achieved lower RMSE and MAE than MODIS LAI, with values of 1.781 and 1.423 compared with 2.087 and 1.647 for MODIS LAI, respectively. In cloud-prone regions and complex terrains, the AHI LAI product exhibits smoother temporal profiles and lower data dispersion compared to the MODIS LAI product. Furthermore, the AHI LAI product captures timely vegetation responses to moisture stress during drought events. The AHI LAI product may provide continuous data support for ecological monitoring and vegetation dynamics research in the Asia-Pacific region.