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Retrieval-Augmented Multi-scale Framework for County-Level Crop Yield Prediction Across Large Regions
Yiming Sun, Qi Cheng, Licheng Liu +3
This paper proposes a new method for crop yield prediction, which is essential for developing management strategies, informing insurance assessments, and ensuring long-term food se…
AgroFlux: A Spatial-Temporal Benchmark for Carbon and Nitrogen Flux Prediction in Agricultural Ecosystems
Qi Cheng, Licheng Liu, Yao Zhang +3
Agroecosystem, which heavily influenced by human actions and accounts for a quarter of global greenhouse gas emissions (GHGs), plays a crucial role in mitigating global climate cha…
Towards Fine-Tuning-Based Site Calibration for Knowledge-Guided Machine Learning: A Summary of Results
Ruolei Zeng, Arun Sharma, Shuai An +5
Accurate and cost-effective quantification of the agroecosystem carbon cycle at decision-relevant scales is essential for climate mitigation and sustainable agriculture. However, b…
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling
Qi Cheng, Licheng Liu, Yao Zhang +5
Agricultural monitoring is critical for ensuring food security, maintaining sustainable farming practices, informing policies on mitigating food shortage, and managing greenhouse g…
Hierarchical Conditional Multi-Task Learning for Streamflow Modeling
Shaoming Xu, Arvind Renganathan, Ankush Khandelwal +9
Streamflow, vital for water resource management, is governed by complex hydrological systems involving intermediate processes driven by meteorological forces. While deep learning m…
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems
Shiyuan Luo, Juntong Ni, Shengyu Chen +6
Modeling environmental ecosystems is critical for the sustainability of our planet, but is extremely challenging due to the complex underlying processes driven by interactions amon…
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications
Shaoming Xu, Ankush Khandelwal, Xiang Li +9
In many environmental applications, recurrent neural networks (RNNs) are often used to model physical variables with long temporal dependencies. However, due to mini-batch training…