Brazilian researchers have developed a methodology that uses remote sensing to map the impact of frost on corn crops. This reduces exposure to climate risks and uncertainty regarding agricultural losses.
The model allows users to customize a set of variables, making it useful for other crops in different agricultural contexts. Thus, it has the potential to provide more accurate estimates during harvests and contribute to the development of public policies that support production chains and insurance systems.
Global grain production, particularly of rice, corn, wheat, and soybeans, is concentrated in just five countries: China, the United States, India, Brazil, and Argentina. Fluctuations in harvests in these countries can affect both prices and the global supply. These crops have also been affected by climate change, experiencing severe droughts, extreme rainfall, and more frequent frosts. This issue has been brought to negotiation rounds such as COP30, held in Belém.
In the study, the scientists mapped over 700,000 hectares of corn planted for the second harvest in the western mesoregion of Paraná state (in the areas around Toledo and Cascavel) to identify damage caused by severe frosts recorded between May and June of 2021.
The scientists integrated optical remote sensing data (MultiSpectral Instrument sensor with medium spatial resolution aboard the Sentinel-2 mission satellites) with machine learning techniques (Random Forest algorithm). They achieved 96% accuracy in mapping corn crops and revealed that 70% were damaged by frost during that time. They were able to map the affected areas using the method they called GEEadas.
Click here to see more...