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.

Erosion research of CX-2002U carbon composites under low-temperature high-flux hydrogen plasma

The net erosion yield of CX-2002U carbon fiber composites under high-flux low-temperature hydrogen plasma is investigated using a linear plasma device.It is found that the net erosion yield decreases rapidly first,and then tends to saturate with the increase of hydrogen–plasma flux.When the temperature of the sample eroded by hydrogen plasma is above 300°C,the hybridization of electrons outside the carbon atom would change.Then the carbon atoms combine with hydrogen atoms to form massive spherical nanoparticles of hydrocarbon compounds and deposit on the surface at the flux condition of 1.77×10^(22) m^(−2)·s^(−1).Under the irradiation of hydrogen plasma loaded with negative bias,the surface morphology of the matrix carbon is changed dramatically.Moreover,the energy dependence of mass loss does not increase in proportion to the increase of hydrogen–plasma energy,but reaches a peak around 20 V negative bias voltage.Based on the analysis of different samples,it can be concluded that the enhancement of energy could make a contribution to chemical erosion and enlarge the size of pores existing on the surface.

Spatiotemporal patterns of winter wheat phenology and its climatic drivers based on an improved pDSSAT model

Acquiring spatiotemporal patterns of phenological information and its drivers is essential for understanding the response of crops to climate change and implementing adaptation measures.However,current approaches to obtain phenology and analyse its drivers have deficiencies such as sparse observations,excessive dependence of remote sensing inversion on sensors,and inevitable difficulties in upscaling site-based crop models into larger regions.Based on the Wang-Engel temperature response function,we improved the Crop Estimation through Resource and Environment Synthesis-Wheat(CERES-Wheat)model.First,we calibrated the model at the regional scale and evaluated its performance.Furthermore,the spatiotemporal changes in winter wheat phenology in China from 2000 to 2015 were analysed.The results showed that the improved model significantly enhanced the simulation accuracy of the anthesis and maturity dates by averages of 13%and 12%in most planting areas,especially in the Yunnan-Guizhou Plateau(YG)with improvements of 26%and 28%.The simulated phenology of winter wheat grown in a colder environment(e.g.,the average temperatures during the vegetative growth period range from 0 to 5℃ and from 15 to 20°C,and the reproductive growth period ranges from 10 to 15°C)also notably improved.These results confirmed that the original temperature response function indeed had limitations.Further analyses revealed that the key phenological dates and growth periods over the past 16 years were dominantly advanced and shortened.Specifically,the anthesis date,vegetative growth period(VGP),and reproductive growth period(RGP)indicated obviously spatial characteristics.For example,the anthesis date and VGP in the North China Plain(NCP)and the Middle-Lower Yangtze Plain(YZ)and the RGP in northwestern China(NW)showed opposite trends of delay and prolongation as comparing with the dominant patterns.Sensitivity analysis indicated that the key phenological dates and growth periods were advanced and shortened as the minimum(T_(min))and maximum temperatures(T_(max))rose,while they were postponed and prolonged with the increased precipitation.However,their responses to solar radiation did not show spatial consistency.Additionally,we found that the sensitivity of phenology to climatic factors differed across subregions.In particular,phenology in southwestern China and YG was more sensitive to T_(min),T_(max),and solar radiation than in the NCP and NW.Moreover,the sensitivity to precipitation in NW was higher than that in YZ.Totally,the improved crop model could provide more refined spatial characteristics of phenology at a large scale and benefit to explore its drivers more objectively.Furthermore,our results highlight that different planting areas should adopt suitable adaptation measures to cope with climate change impacts.Ultimately,the improved model is promising to enhance the accuracy of yield prediction and provide powerful tools for assessing regional climate change impact and adaptability.