A new way to monitor crops for global food security
Food production is under threat across the world from a combination of urban development, shrinking space for arable land, groundwater depletion and other challenges; all which are being exacerbated by climate change Accurate monitoring of agricultural productivity is essential for both global food security and the livelihoods of low-income rural regions, but current monitoring methods aren’t meeting this challenge.
This UK-China research collaboration has pioneered a new approach which has improved accuracy of crop monitoring by ten percent and produced crop yield estimates over large areas at an unprecedented ten metre resolution – compared to the previous one-kilometre resolution estimates. The result is likely to be the most accurate portrait created to date of changing agricultural production in the North China Plain.
Previously, researchers used either field surveys and mathematical models or satellite imagery to monitor crops, but both methods have their limitations. The team combined these previously incompatible data sets using new data assimilation techniques to give significantly improved estimates of agricultural productivity.
The project is among the first to make use of data from the new Sentinel and Chinese GF satellites and has fed directly into agricultural production planning in China, providing more accurate analytics of crop development and responses to different stresses so that more suitable management practices can be deployed.
Besides providing better predictions of crop yield and crop growth, the team is training academics to use the software developed during the project, and the state-of-the-art techniques are already being applied to other countries including Ghana, Argentina and the UK.
This project will lead to critical advances in quantitative remote sensing and data assimilation technology, enabling high resolution, high accuracy crop yield predictions that will benefit people both in and outside of China.
Professor Shunlin Liang, University of Maryland
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Caption: UK-CHINA Research and Innovation Partnership Fund world class research and innovation partnership
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Newton Fund (logo)
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Caption: Regional crop monitoring and assessment with quantitative remote sensing and data assimilation
Professor Philip Lewis, University College London and Professor Zhongxin Chen, Chinese Academy of Agricultural Sciences (CAAS)
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The blue logo of Institute of Digital Agriculture.
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Speaker (Prof Jianqiang Ren)
With the emergence of problems in resources, environment and climate change,
Food security has become an important issue in the world.
China, as a large country with a population of 1.3 billion,
Have always attached great importance to food security.
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Professor Ren Jianqiang is speaking in front of the camera with a computer desk in the back.
Caption: Professor Ren Jianqiang, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences
A corn in front of the camera:
Corn filed appears. Corn leaves are swinging in the wind;
Corns and grains are piled on the ground. Corn leaves are swinging in the wind;
A tractor drives past many corns. In the background a farmer is shoveling corns.
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Meanwhile, the national agricultural management departments have put forward higher requirements
For agricultural remote sensing technology.
For our project,
We have made efforts to improve the accuracy
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Professor Ren Jianqiang is speaking in front of the camera with the computer screen in the back.
The aerial view of a green wheat field.
The aerial view of a large filed of green wheat and many houses with red roofs scattered in between.
Farmers are harvesting wheat and loading wheat on a tricycle.
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And level of regional agricultural monitoring and evaluation and crop yield estimation.
Supported by high-resolution remote sensing images
Such as the Sentinel and the Gaofen satellites,
Our joint UK-China team used the new technologies of remote sensing and data assimilation
To improve the accuracy of crop yield estimation,
And these new technology have been widely applied and verified in the North China Plain.
At present, the accuracy of regional crop yield estimation has increased by about 10% and reached more than 90%.
Supported by the Newton Fund,
The Chinese Academy of Agricultural Sciences has established a good collaboration
With UCL which masters top remote sensing technology,
And we have worked very effectively on our joint research and application.
We will further apply mature technologies to other crops domestically
And to other regions in the world such as South America and Africa
To improve global food security and sustainable agricultural development
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Many researchers are sitting in front of computers watching satellite data on the screen in the office;
Two researchers are watching satellite data on the screen;
A white round remote sensing transmitter base station with leaves in the front;
The white round remote sensing transmitter base station is slowly rotating;
A harvester is driving in the field with the base station in the background;
A high-speed train drives through broad farmland;
Professor Ren Jianqiang is speaking in front of the camera with the computer screen in the back.
A peasant woman sifts grain with a bamboo sifter in the wheat field;
A farmer bends to harvest in the rice field;
An endless green rice field;
A large brown cotton field;
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The Newton Fund is devoted to achieving the
UN’s Sustainable Development Goals.
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Presented by
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Executive Producer
Zhan Zhang
Directed，Filmed，Edited by Manman Yang
Second Cameraman
Wei Wang
Produced by Believing is Seeing Studio Guangzhou
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Special thanks
UK Research and Innovation China
British Council
British Consulate General Guangzhou
Institute of Agricultural Resources and Regional Planning,
Chinese Academy of Agricultural Sciences (CAAS)
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Newton Fund Delivery Partners
UK
Academy of Medical Sciences
British Academy
British Council
Met Office
Royal Academy of Engineering
Royal Society
UK Research and Innovation
Newton Fund Delivery Partners
CHINA
Chinese Academy of Agricultural Sciences
Chinese Academy of Engineering
Chinese Meteorological Administration
Chinese Academy of Medical Sciences
Chinese Academy of Social Sciences
Chinese Academy of Sciences
Institute of Atmospheric Physics, Chinese Academy of Sciences
Ministry of Education
Ministry of Science and Technology
National Natural Science Foundation of China (NSFC)
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Regional crop monitoring and assessment with quantitative remote sensing and data assimilation
Project leads: Professor Philip Lewis, University College London, UK and Professor Zhongxin Chen, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences
Delivery partners: Science and Technology Facilities Council, part of UK Research and Innovation and National Natural Science Foundation of China
