Abstract
Vegetation phenology dynamics have attracted worldwide attention due to its direct response to global climate change and the great influence on terrestrial carbon budgets and ecosystem productivity in the past several decades. However, most studies have focused on phenology investigation on natural vegetation, and only a few have explored phenology variation of cropland. In this study, taking the typical cropland in the Shandong province of China as the target, we analyzed the temporal pattern of the Normalized Difference Vegetation Index (NDVI) and phenology metrics (growing season start (SOS) and end (EOS)) derived from the Global Inventory Monitoring and Modeling System (GIMMS) 3-generation version 1 (1982–2015) and the Vegetation Index and Phenology (VIP) version 4 (1981–2016), and then investigated the influence of climate factors and Net Primary Production (NPP, only for EOS) on SOS/EOS. Results show a consistent seasonal profile and interannual variation trend of NDVI for the two products. Annual average NDVI has significantly increased since 1980s, and hugely augmentations of NDVI were detected from March to June for both NDVI products (p < 0.01), which indicates a consistent greening tendency of the study region. SOSs from both products are correlated well with the ground-observed wheat elongation and spike date and have significantly advanced since the 1980s, with almost the same changing rate (0.65/0.64 days yr-1, p < 0.01). EOS also exhibits an earlier but weak advancing trend. Due to the significant advance of SOS, the growing season duration has significantly lengthened. Spring precipitation has a relatively stronger influence on SOS than temperature and shortwave radiation, while a greater correlation coefficient was diagnosed between EOS and autumn temperature/shortwave radiation than precipitation/NDVI. Autumn NPP exhibits a nonlinear effect on EOS, which is first earlier and then later with the increase of autumn NPP. Overall, we highlight the similar capacity of the two NDVI products in characterizing the temporal patterns of cropland phenology.
Highlights
Plant phenology, the study of annually recurring plant growth and reproductive events timing, and their endogenous and exogenous drivers [1], is influenced by changes in environmental factors, such as temperature, precipitation, sunlight [2,3]
We highlight the similar capacity of the two Normalized Difference Vegetation Index (NDVI) products in characterizing the temporal patterns of cropland phenology
When compared season start (SOS)/EOS between Vegetation Index and Phenology (VIP) and Global Inventory Monitoring and Modeling System (GIMMS), we identified that both SOS and EOS from VIP were averagely overestimated by about
Summary
The study of annually recurring plant growth and reproductive events timing, and their endogenous and exogenous drivers [1], is influenced by changes in environmental factors, such as temperature, precipitation, sunlight [2,3]. Oceanic and Atmospheric Administration (NOAA) satellites to monitor the earth surface since 1979 For this reason, the Normalized Differential Vegetation Index (NDVI) time series (over 30 years) derived from reflectance observed by channels 1 and 2 of AVHRR as part of the Global Inventory Modeling and Mapping Studies (GIMMS) project is often employed to investigate land surface dynamics at global and regional scales [3,13,14]. The Normalized Differential Vegetation Index (NDVI) time series (over 30 years) derived from reflectance observed by channels 1 and 2 of AVHRR as part of the Global Inventory Modeling and Mapping Studies (GIMMS) project is often employed to investigate land surface dynamics at global and regional scales [3,13,14] This dataset contributed to important findings on global land surface changes, especially prior to 2000 when other remote sensing data sources were relatively scarce. We investigated the climate and biotic factors influencing the land surface phenology dynamics of cropland by means of gridded climate datasets
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