Remote Sensing of Land Surface Phenology

Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects

Estimating Frost during Growing Season and Its Impact on the Velocity of Vegetation Greenup and Withering in Northeast China

Vegetation phenology and photosynthetic primary production have changed simultaneously over the past three decades, thus impacting the velocity of vegetation greenup (Vgreenup) and withering (Vwithering). Although climate warming reduces the frequency of frost events, vegetation is exposed more frequently to frost due to the extension of the growing season. Currently, little is known about the effect of frost during the growing season on Vgreenup and Vwithering. This study analyzed spatiotemporal variations in Vgreenup and Vwithering in Northeast China between 1982 to 2015 using Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS 3g NDVI) data. Frost days and frost intensity were selected as indicators to investigate the influence of frost during the growing season on Vgreenup and Vwithering, respectively. Increased frost days during the growing season slowed Vgreenup and Vwithering. The number of frost days had a greater impact on Vwithering compared to Vgreenup. In addition, Vgreenup and Vwithering of forests were more vulnerable to frost days, while frost days had a lesser effect on grasslands. In contrast to frost days, frost intensity, which generally decreased during the growing season, accelerated Vgreenup and Vwithering for all land cover types. Changes in frost intensity had less of an impact on forests, whereas the leaf structure of grasslands is relatively simple and thus more vulnerable to frost intensity. The effects of frost during the growing season on Vgreenup and Vwithering in Northeast China were highlighted in this study, and the results provide a useful reference for understanding local vegetation responses to global climate change