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影响因子：4.2

DOI码：10.3390/rs17111853

发表刊物：Remote Sensing

关键字：land surface phenology (LSP); kNDVI; phenology; climate change; Northeast China

摘要：Understanding plant phenology dynamics is essential for ecosystem health monitoring and climate change impact assessment. This study generated 4-day, 500 m land surface phenology (LSP) in Northeast China (NEC) from 2001 to 2021 using interpolated and Savitzky–Golay filtered kernel normalized difference vegetation index (kNDVI) derived from MODIS. Spatial patterns, trends, and climate responses of phenology were analyzed across ecoregions and vegetation. Marked spatial heterogeneity was noted: forests showed the earliest start of season (SOS, ~125th day) and longest growing season (LOS, ~130 days), while shrublands had the latest SOS (~150th day) and shortest LOS (~96 days). Grasslands exhibited strong east–west gradients in SOS and EOS. From 2001 to 2021, SOS of natural vegetations in NEC advanced by 0.23 d/a, EOS delayed by 0.12 d/a, and LOS extended by 0.38 d/a. Coniferous forests, especially evergreen needle-leaved forests, exhibited opposite trends due to cold-resistant traits and an earlier EOS to avoid leaf cell freezing. Temperature was the main driver of SOS, with spring and winter temperatures influencing 48.8% and 24.2% of the NEC region, respectively. Precipitation mainly affected EOS, especially in grasslands. Drought strongly influences SOS, while precipitation affects EOS. This study integrates high-resolution phenology utilizing the kNDVI with various seasonal climate drivers, offering novel insights into vegetation-specific and ecoregion-based phenological dynamics in the context of climate change.

合写作者：Xiaochun Wang,Yinghui Zhao,Haifeng Zou

第一作者：Q1, Jiayu Liu

论文类型：期刊论文

通讯作者：Zhen Zhen*

卷号：17

期号：11

页面范围：1853

ISSN号：2072-4292

是否译文：否

发表时间：2025-01-01

收录刊物：SCI