Remote Sensing of Land Surface Phenology

Dear Colleagues,

Land surface phenology (LSP) involves the use of remote sensing to monitor seasonal dynamics in vegetated land surfaces and to retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP, as an important field in environmental and climate remote sensing science, has undergone rapid development over the last few decades. Both regional and global LSP products have been routinely generated and played prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing global change 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 LSP retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals are undergoing, and efforts in seeking ways to reduce these uncertainties are also forming an active research field. In addition, open source software and hardware are being developed and have greatly facilitated the use of LSP metrics by scientists beyond the remote sensing community. As such, we organized this Special Issue to cover the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. In doing so, we hope to not only summarize the ongoing diverse LSP developments but also boost discussions on future prospects in LSP research. We welcome contributions that fall within, but are not limited to, the following topics:

• Advances in LSP retrieval algorithms
• Assessing and reducing the uncertainties in LSP retrievals
• Retrieving LSP using optical, microwave, LiDAR, and SIF
• Ensuring long-term continuity of LSP across sensors and satellite missions
• Applying multisensor data fusion techniques for LSP
• Proposing improved satellite LSP validation strategies using ground observations
• Near-real-time monitoring and short-term forecasting of LSP
• Retrieving LSP from nanosat constellation and geostationary satellites
• Developing LSP products using cloud platforms such as GEE and PIE-Engine
• Developing phenocams (phenology cameras) for LSP applications
• Developing open source computer code, software, and hardware for LSP
• Prototyping and upgrading regional, national, and global LSP products
• Applying LSP in agriculture, ecology, LULC, and global change
• Tracking the long-term trends and IAV of LSP and its interaction with regional climate
• Exploring the interactions between LSP and climate/human activities factors

Thank you and we look forward to receiving your contributions!

Dr. Xuanlong Ma
Dr. Jiaxin Jin
Dr. Xiaolin Zhu
Dr. Yuke Zhou
Dr. Qiaoyun Xie
Guest Editors

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