A GLOBAL ANNUAL VEGETATION PHENOLOGY DATASET DERIVED FROM GIMMS LAI 3G TIME SERIES FOR 1982-2015

被引：0
|
作者：
Wu, Wei [1 ]
Xin, Qinchuan [1 ]
机构：
[1] Sun Yat Sen Univ, Sch Geog & Planning, Guangdong Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Peoples R China
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金：
国家重点研发计划; 中国国家自然科学基金;
关键词：
Vegetation phenology; remote sensing; satellite product;
D O I：
10.1109/IGARSS46834.2022.9883293
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Vegetation phenology is a key indicator of ecosystem processes and biosphere feedbacks to the climate system. Remote sensing techniques have been widely used for large scale phenology observations. In this study, the first-order derivative (FOD) method was used to extract the start of the growing season (SOS) and the end of the growing season (EOS) based on the GIMMS LAI3g time series from 1982 to 2015. The results showed that the global 34-year mean SOS and EOS exhibited significant latitudinal variation in spatial distribution. In the Northern Hemisphere, SOS and EOS showed insignificant trend (1982-2015). In the Southern Hemisphere, EOS showed significantly delayed trend of 0.1251 days/year. In addition, GIMMS SOS and EOS showed a significant positive correlation on a global scale with MODIS SOS and EOS. Overall, we produced global vegetation phenology data with longer time series (1982-2015) compared to MODIS vegetation dynamics products (MCD12Q2).
引用
收藏
页码：6130 / 6133
页数：4
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