Detecting Changes of Wheat Vegetative Growth and Their Response to Climate Change Over the North China Plain

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 11; no. 12; pp. 4630 - 4636
• Main Authors: Liu, Zhengjia, Wang, Sisi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agricultural land; Agriculture; Air pollution; Algorithms; Change detection; Climate change; Crop growth; crop phenology; Crop yield; Crops; Locating; Mapping; Meteorology; Modelling; Normalized difference vegetative index; phenology algorithms; Prediction algorithms; Remote sensing; Satellites; Temperature sensors; the North China Plain (NCP); Triticum aestivum; Vegetation mapping; Wheat; Winter wheat; China
• ISSN: 1939-1404; 2151-1535
• DOI: 10.1109/JSTARS.2018.2870329

Wheat vegetative growth, defined as the stage from green-up date to heading date (STAGE), is a crucial phrase, which largely affects crop yield. Previous some studies mainly focused on site-based changes of STAGE. However, there are few studies concerning large-scale changes of STAGE, which limits our understanding of regional changes of STAGE in response to climate change. Here, we introduced robust satellite-based phenological algorithms as well as third-generation global inventory modeling and mapping studies normalized difference vegetation index for the period of 1982-2015 to spatially derive winter wheat green-up date, heading date, and STAGE over croplands of the North China Plain (NCP). Changes of STAGE and their response to climate change were then investigated. Results showed that a strong predicted ability of introduced heading date algorithm was observed with r of 0.88 ( p < 0.01), bias of −1.0 day and RMSE of 4.9 days. We found that unlike the patterns of winter wheat green-up and heading date, STAGE spatially decreased from southwestern to northeastern NCP with regional averaged stage of 41.2 ± 4.6 days. Advanced green-up date faster than advanced heading date induced lengthened stage of entire NCP with 1 day/decade ( R 2 = 0.11, p = 0.06). Stage of 23.4% cropland pixels performed significantly lengthened trends ( p < 0.05), mainly locating in western NCP. The relationships between STAGE and climatic variables suggested that compared to precipitation, temperature was more responsible for changes of STAGE ( r = 0.59, p < 0.01). This study highlights important roles of remote sensing data and satellite-based phenological algorithms for regional crop growth monitoring and management.