Spatial scale effects of grassland phenology on the Qinghai-Tibet Plateau
Accurate high-altitude vegetation phenology remote sensing products are fundamental data for maintaining ecological balance, accurately reflecting surface energy balance, and stabilizing the cryosphere. However, currently used remote sensing data for phenology extraction have diverse spatial resolutions, and phenology extracted based on different spatial scales may ex-hibit scale effects, which have not received widespread attention. In this study, utilizing Sentinel-2 data with a spatial resolu-tion of 10m, MODIS data with spatial resolutions of 500 and 5600m, and employing the NDGI vegetation index, phenology products with corresponding spatial resolutions for the Qinghai-Tibet Plateau in 2022 were extracted on the Google Earth En-gine (GEE) cloud platform. The study explored the differences in phenology at different spatial resolutions, quantitatively ana-lyzed the scale effects of phenology products, and elucidated their variations with terrain complexity. The research revealed that, compared to high spatial resolution remote sensing products (10m), there is a noticeable lag phenomenon in the spring phenology of coarser spatial resolution (500 and 5600m). When detecting grassland phenology using remote sensing products with different spatial resolutions, scale effects are generally present, with the scale effect of autumn phenology being smaller than that of spring phenology. Additionally, the scale effect of vegetation phenology is influenced by terrain and increases with the complexity of terrain.
万方数据
维普
