Winter Wheat Green-up Date Variation and its Diverse Response on the Hydrothermal Conditions over the North China Plain, Using MODIS Time-Series Data
AbstractVegetation phenology plays a critical role in the dynamic response of terrestrial ecosystems to climate change. However, the relationship between the phenology of winter wheat and hydrothermal factors is inadequate, especially in typical agricultural areas. In this study, the possible effects of preseason climate changes on the green-up date (GUD) of winter wheat over the North China Plain (NCP) was investigated, using the MODIS EVI 8-day time-series data from 2000 to 2015, as well as the concurrent monthly mean temperature (Tm), mean maximum (Tmax) and minimum temperature (Tmin) and total precipitation (TP) data. Firstly, we quantitatively identified the time lag effects of winter wheat GUD responses to different climatic factors; then, the major driving factors for winter wheat GUD were further explored by applying multiple linear regression models. The results showed that the time lag effects of winter wheat GUD response to climatic factors were site- and climatic parameters-dependent. Negative temperature effects with about a 3-month time lag dominated in most of the NCP, whereas positive temperature effects with a zero-month lag were most common in some of the southern parts. In comparison, total precipitation had a negative zero-month lag effect in the northern region, but two lagged months occurred in the south. Regarding the time lag effects, the explanation power of climatic factors improved relatively by up to 77%, and the explanation area increased by 41.20%. Additionally, change in winter wheat GUD was primarily determined by temperature rather than by TP, with a marked spatial heterogeneity of the Tmax and Tmin effect. Our results confirmed different time lag effects from different climatic factors on phenological processes in spring, and further suggested that both Tmax and Tmin should be considered to improve the performance of spring phenology models. View Full-Text
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Description: Figure S1. The workflow for winter wheat area identification Figure S2. A sample of winter wheat EVI time series during growth cycle in NCP and its sixth-order polynomial smooth Figure S3. Random points and validation sample transect for winter wheat extraction in this study Figure S4. The true color synthesis map over the sample transect during December 2014 to January 2015 based on Landsat 8 imagery and goolge earth engine platform Figure S5. Spatial distribution of TP trend (a) and its significance (b) for the preseason T2 during 2001–2015
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Guo, L.; Gao, J.; Hao, C.; Zhang, L.; Wu, S.; Xiao, X. Winter Wheat Green-up Date Variation and its Diverse Response on the Hydrothermal Conditions over the North China Plain, Using MODIS Time-Series Data. Remote Sens. 2019, 11, 1593.
Guo L, Gao J, Hao C, Zhang L, Wu S, Xiao X. Winter Wheat Green-up Date Variation and its Diverse Response on the Hydrothermal Conditions over the North China Plain, Using MODIS Time-Series Data. Remote Sensing. 2019; 11(13):1593.Chicago/Turabian Style
Guo, Linghui; Gao, Jiangbo; Hao, Chengyuan; Zhang, Linlin; Wu, Shaohong; Xiao, Xiangming. 2019. "Winter Wheat Green-up Date Variation and its Diverse Response on the Hydrothermal Conditions over the North China Plain, Using MODIS Time-Series Data." Remote Sens. 11, no. 13: 1593.
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