Rice is one of the most strategic commodities in the world. It is closely connected with food security, economic growth, employment, culture and regional peace. Although the world has made significant progress to improve rice production, countries where rice is a staple food still have no accurate way of knowing how much rice has been grown and how much harvest can be achieved.
Google Earth, the Group on Earth Observations, the University of Sydney, and the University Malaya Trengganu have been working together to develop a groundbreaking new technology that will help to develop the first real-time monitoring platform for rice fields. The platform, named Paddy Watch, will use Google Earth Engine (GEE) to detect how much rice is grown, predict rice yield, inform water use and make decisions that will help countries reach the Zero Hunger target of the United Nations 2030 Agenda.
Paddy Watch is one of the 32 projects selected as part of the GEO - Google Earth Engine program that provides funding to tackle environmental and social challenges using open Earth data.
We spoke with the project leader, Professor Budiman Minasny from the Sydney Institute of Agriculture, to learn more about the project and how his team will be using GEE to provide accurate and up-to-date spatial information on rice yield prediction globally.
Budiman, can you describe the challenge you want to tackle with this project?
Rice is the staple crop for more than half the world’s population and 10 percent of all arable land is dedicated to rice farming.
Currently, there is no global standard for monitoring where rice is grown. The current process for rice field estimation relies on field surveys that are time-consuming and inefficient.
Another tried survey method is using MODIS satellite data to estimate rice-growing areas at a regional and national scale. The MODIS Satellite provides coarse resolution imagery and is affected by cloud cover in many regions of the world. While this method does save time, it’s inaccurate and in some regions, unusable for monitoring rice fields.
How will your project address these problems?
Our team aims to build the first high resolution near-real-time global rice field monitoring platform - Paddy Watch. Using GEE and radar imageries, we aim to provide accurate and up-to-date information to farmers and agricultural extension officers on how much rice has been planted and how much harvest can be achieved. This information is crucial to achieving global food and water security.
How will Paddy Watch impact the agricultural community?
This information is expected to help farmers and agricultural extension officers better manage their land in the face of climate change.
Scientists can use these data to develop research strategies to build healthy soils and increase yield in different environments. Further, teachers and lecturers can use these online resources to educate future generations about food production and the environment, and policymakers can use the maps to formulate data-driven policies and decisions around food security to boost local economic growth.
How does Google Earth Engine help you achieve your project-related goals?
We will use GEE to build the first real-time mobile application that will allow farmers, agricultural scientists, non-government organisations and government planners to manage land use to ensure food security in the world’s rice bowls.
The real-time land-use data generated using Google Earth will be verified by field operators in Malaysia, Indonesia, China, and Vietnam. This will allow the agricultural scientists to calibrate their monitoring methods to ensure its accuracy worldwide.
The GEO-GEE program funding will provide us with computing resources crucial in delivering these large datasets of monthly data.
What does success look like to you?
Success for us will be creating an application that can provide spatial information on rice area, and rice yields globally. The proposed novel method will produce high-resolution monthly maps of rice-growing regions, as well as it’s growth stages and estimated yield every month.
EO Data Science’s role in the GEO - GEE Program
EO Data Science partnered with Google Earth Engine and the Group on Earth Observations to launch the GEO-GEE Program, which supports GEO member countries to operationalise their science as they strive to tackle the world’s biggest sustainable development challenges.
In July 2020, 32 projects across 22 countries were selected into the program which offers $3 million USD towards product licenses and $1 million USD in technical support from EO Data Science. This funding and support will help these projects tackle global challenges using open Earth data. Read the announcement and list of winners here.
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