Monitoring nature's calendar from space: Emerging topics in land surface phenology and associated opportunities for science applications

• Published in: Global change biology Vol. 28; no. 24; pp. 7186 - 7204
• Main Authors: Ma, Xuanlong, Zhu, Xiaolin, Xie, Qiaoyun, Jin, Jiaxin, Zhou, Yuke, Luo, Yunpeng, Liu, Yuxia, Tian, Jiaqi, Zhao, Yuhe
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.12.2022; John Wiley and Sons Inc
• Subjects: Adaptation; Algorithms; Atmospheric models; big data; bioclimatology; biodiversity; Biological Sciences; Biometeorology; Carbon; carbon cycle; Climate Change; Climate models; Data integration; Dynamics; Ecological adaptation; Ecosystem; Ecosystem dynamics; ecosystems; energy; Environmental impact; global change; Global climate; Interdisciplinary subjects; Monitoring; Multisensor fusion; Phenology; public health; Remote sensing; Review; Reviews; Seasonal variations; Seasons; Vegetation; vegetation dynamics; Water; biodiversity; carbon cycle; big data; vegetation dynamics; global change; public health
• ISSN: 1354-1013; 1365-2486; 1365-2486
• DOI: 10.1111/gcb.16436

Vegetation phenology has been viewed as the nature's calendar and an integrative indicator of plant‐climate interactions. The correct representation of vegetation phenology is important for models to accurately simulate the exchange of carbon, water, and energy between the vegetated land surface and the atmosphere. Remote sensing has advanced the monitoring of vegetation phenology by providing spatially and temporally continuous data that together with conventional ground observations offers a unique contribution to our knowledge about the environmental impact on ecosystems as well as the ecological adaptations and feedback to global climate change. Land surface phenology (LSP) is defined as the use of satellites to monitor seasonal dynamics in vegetated land surfaces and to estimate phenological transition dates. LSP, as an interdisciplinary subject among remote sensing, ecology, and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, here we summarize the recent advances in LSP and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of the global LSP research field. Land surface phenology (LSP), as an interdisciplinary subject among remote sensing, ecology, and biometeorology, has undergone rapid development over the past few decades. Recent advances in sensor technologies, as well as data fusion techniques, have enabled novel phenology retrieval algorithms that refine phenology details at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. As such, we summarize the recent advances in LSP and the associated opportunities for science applications. We focus on the remaining challenges, promising techniques, and emerging topics that together we believe will truly form the very frontier of the global LSP research field.