Mapping rapeseed planting areas using an automatic phenology-and pixel-based algorithm(APPA) in Google Earth Engine

The timely and rapid mapping of rapeseed planting areas is desirable for national food security. Most current rapeseed mapping methods depend strongly on images with good observations obtained during the flowering stages. Although vegetation indices have been proposed to identify the rapeseed flowering stage in some areas, automatically mapping rapeseed planting areas in large regions is still challenging.We developed an automatic phenology-and pixel-based algorithm(APPA) by integrating Landsat 8 and Sentinel-1 satellite data. We found that the Normalized Rapeseed Flowering Index shows unique spectral characteristics during the flowering and post-flowering periods, which distinguish rapeseed parcels from other land-use types(urban, water, forest, grass, maize, wheat, barley, and soybean). To verify the robustness of APPA, we applied APPA to seven areas in five rapeseed-producing countries with flowering images unavailable. The rapeseed maps by APPA showed consistently high accuracies with producer accuracies of 0.87–0.93 and F-scores of 0.92–0.95 based on 4503 verification samples. They showed high spatial consistency at the pixel level with the land cover Scientific Expertise Centres(SEC) map in France,Crop Map of England in United Kingdom, national-scale crop-and land-cover map of Germany, and Annual Crop Inventory in Canada at the pixel level. We propose APPA as a highly promising method for automatically and efficiently mapping rapeseed areas.

Weakened maize phenological response to climate warming in China over 1981‒2018 due to cultivar shifts

Assessing climate change impacts on crop phenology is essential for developing adaptation options.To better understand crop response and adaptation to climate change,there is an urgent need to investigate whether the impacts weakens and how crops responds to recent climate warming,as well as the roles of different drivers in crop phenology change.Here,we analyzed the spatiotemporal changes in maize phenology and the underlying mechanisms over 1981–2018 using up-to-date 6106 phenological observations at 327 agro-meteorological stations in China.We found that during 1981–2018 maize sowing and maturity dates were generally delayed by 0.6 and 1.2 d per decade,respectively,whereas heading date was advanced by 0.9 d per decade.Maize phenology was most negatively correlated with rising minimum temperature(night-time warming),followed by maximum(daytime)temperature,and least by mean temperature.The trends in maize phenology and the correlation between growth periods and temperature generally declined from 1981 to 1999 to 2000–2018 for both spring and summer maize,although climate warming during growth period did not slow down.The phenological response to temperature weakened mainly owing to agricultural managements,especially cultivar shifts.Climate change shortened growth period by 3.4 and 1.7 d per decade but cultivar shifts prolonged it by 4.5 and 2.1 d per decade for spring and summer maize,respectively.Our study highlights that maize phenology is more sensitive to night-time warming than daytime warming,and cultivar shifts far outweigh climate change.These findings foster the understanding of spatiotemporal dynamics of maize phenology and its drivers,which can benefit to develop effective climate change adaptation options for different regions.