WHEAT BIOMASS ESTIMATION FROM UAV IMAGERY USING AN ENSEMBLE LEARNING APPROACH WITH BAYESIAN OPTIMIZATION

Water moves from land to air in a process called evapotranspiration, which affects weather, crops, and water supply. Using satellites and AI, we created a system that tracks this water movement every five minutes, day and night, even through clouds. This provides continuous insights that can help manage water, predict weather, and better understand the water cycle.

In this paper, we evaluated different types of satellite radar information to locate flooded areas on sea ice. We found that changes between images over time were the most effective for identifying flooded areas, while other measurements provided information about how flooding evolves, including refreezing processes. We tested these results at a broader scale and confirmed that they can support regional monitoring. These results provide information that can support safer travel on the ice.

Ice-jam flooding poses a significant risk in cold regions, particularly for vulnerable communities. This study maps river sections most prone to ice jams based on their physical characteristics. The findings offer a practical tool for improving flood preparedness and risk management by helping decision-makers prioritize high-risk areas, especially as climate change increases the frequency of extreme winter conditions.