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Deep Learning has recently emerged as a perfect prognosis downscaling technique to compute high-resolution fields from large-scale coarse atmospheric data. Despite their promising results to reproduce the observed local variability, they…

Machine Learning · Computer Science 2023-05-03 Jose González-Abad , Jorge Baño-Medina , Ignacio Heredia Cachá

Effective adaptation and mitigation strategies for climate change require high-resolution projections to inform strategic decision-making. Conventional global climate models, which typically operate at resolutions of 150 to 200 kilometers,…

Accurate and timely crop yield prediction is crucial for global food security and modern agricultural management. Traditional methods often lack the scalability and granularity required for precision farming. This paper introduces FARM:…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Shayan Nejadshamsi , Yuanyuan Zhang , Shadi Zaki , Brock Porth , Lysa Porth , Vahab Khoshdel

Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help farmers, water managers, and others to manage the effects of…

Other Quantitative Biology · Quantitative Biology 2017-05-29 John J. Nay , Emily Burchfield , Jonathan Gilligan

Super-resolving the coarse outputs of global climate simulations, termed downscaling, is crucial in making political and social decisions on systems requiring long-term climate change projections. Existing fast super-resolution techniques,…

Atmospheric and Oceanic Physics · Physics 2023-04-18 Norihiro Oyama , Noriko N. Ishizaki , Satoshi Koide , Hiroaki Yoshida

Rainfall prediction at the kilometre-scale up to a few hours in the future is key for planning and safety. But it is challenging given the complex influence of climate change on cloud processes and the limited skill of weather models at…

Atmospheric and Oceanic Physics · Physics 2023-11-08 S. Moran , B. Demir , F. Serva , B. Le Saux

Accurate soil moisture (SM) estimation is critical for precision agriculture, water resources management and climate monitoring. Yet, existing satellite SM products are too coarse (>1km) for farm-level applications. We present a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Ioannis Kontogiorgakis , Athanasios Askitopoulos , Iason Tsardanidis , Dimitrios Bormpoudakis , Ilias Tsoumas , Fotios Balampanis , Charalampos Kontoes

The current availability of soil moisture data over large areas comes from satellite remote sensing technologies (i.e., radar-based systems), but these data have coarse resolution and often exhibit large spatial information gaps. Where data…

Machine Learning · Computer Science 2019-05-22 Danny Rorabaugh , Mario Guevara , Ricardo Llamas , Joy Kitson , Rodrigo Vargas , Michela Taufer

Short-term (0-24 hours) precipitation forecasting is highly valuable to socioeconomic activities and public safety. However, the highly complex evolution patterns of precipitation events, the extreme imbalance between precipitation and…

Machine Learning · Computer Science 2026-03-30 Shuangliang Li , Siwei Li , Li Li , Weijie Zou , Jie Yang , Maolin Zhang

This paper investigates the impacts of climate change on groundwater droughts making use of regional projections and standardized indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index…

Atmospheric and Oceanic Physics · Physics 2022-02-10 D. Secci , M. G. Tanda , M. D Oria , V. Todaro , C. Fagandini

Flooding is one of the most destructive and costly natural disasters, and climate changes would further increase risks globally. This work presents a novel multimodal machine learning approach for multi-year global flood risk prediction,…

Machine Learning · Computer Science 2023-01-31 Cynthia Zeng , Dimitris Bertsimas

Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source satellite observations, particularly the combination of geostationary infrared and…

Atmospheric and Oceanic Physics · Physics 2026-05-15 Yunfan Yang , Haofei Sun , Xiuyu Sun , Wei Han , Xiaoze Xu , Xingtao Song , Jun Li , Zhiqiu Gao , Wei Huang , Hao Li

Daily rainfall extremes and annual totals have increased in large parts of the global land area over the last decades. These observations are consistent with theoretical considerations of a warming climate. However, until recently these…

Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world. Climate change further aggravates this issue. Data-driven deep learning approaches could widen…

Satellite remote sensing has been widely used in the last decades for agricultural applications, {both for assessing vegetation condition and for subsequent yield prediction.} Existing remote sensing-based methods to estimate gross primary…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Aleksandra Wolanin , Gustau Camps-Valls , Luis Gómez-Chova , Gonzalo Mateo-García , Christiaan van der Tol , Yongguang Zhang , Luis Guanter

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation (also called total generation) is only visible to the utility as aggregated net-load. This work…

Signal Processing · Electrical Eng. & Systems 2024-03-11 Allison M. Campbell , Soumya Kundu , Andrew P. Reiman , Orestis Vasios , Ian Beil , Andy Eiden

In precision agriculture (PA), soil sampling and testing operation is prior to planting any new crop. It is an expensive operation since there are many soil characteristics to take into account. This paper gives an overview of soil…

Machine Learning · Computer Science 2019-12-05 Quoc Hung Ngo , Nhien-An Le-Khac , Tahar Kechadi

Agricultural management, with a particular focus on fertilization strategies, holds a central role in shaping crop yield, economic profitability, and environmental sustainability. While conventional guidelines offer valuable insights, their…

Machine Learning · Computer Science 2026-02-12 Zhaoan Wang , Shaoping Xiao , Junchao Li , Jun Wang

In recent decades, the causes and consequences of climate change have accelerated, affecting our planet on an unprecedented scale. This change is closely tied to the ways in which humans alter their surroundings. As our actions continue to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Burak Ekim , Michael Schmitt

In general. automated farming systems make decisions based on static models built from the properties of the plant. in the contrast, irrigation decisions in our suggested method are dynamically changing environmental conditions. the model"s…

Systems and Control · Electrical Eng. & Systems 2023-04-18 Kawsalyaa Manivannan , Bharathi Sankar