arXiv Machine Learning August 4, 2026 By Zhixing Ruan, Lixin Lu

A Sequence-to-Sequence ConvLSTM Approach for Leaf Area Index Forecasting over the South-Central United States

Read the original on arXiv Machine Learning →

arXiv:2608. 00879v1 Announce Type: cross Abstract: Leaf Area Index (LAI) is a fundamental biophysical variable governing land-atmosphere interactions; however, LAI forecasting at high spatial resolution remains an unsolved challenge.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Jun 26

Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariates

arXiv:2602. 17683v3 Announce Type: replace Abstract: Short-term forecasting of vegetation dynamics is a key enabler for data-driven decision support in precision agriculture.

By Irene Iele, Giulia Romoli, Daniele Molino, Elena Mulero Ayll\'on, Filippo Ruffini, Paolo Soda, Matteo Tortora

multimodal benchmarks

arXiv Machine Learning

Jun 18

Spatiotemporal downscaling and nowcasting of urban land surface temperatures with deep neural networks

arXiv:2605. 13566v2 Announce Type: replace Abstract: Land Surface Temperature (LST) is a key variable for various applications, such as urban climate and ecology studies.

By Solomiia Kurchaba, Angela Meyer

benchmarks safety

arXiv AI

Jun 18

A Hybrid LSTM--Vision Transformer Architecture for Predicting HRRR Forecast Errors

arXiv:2606. 19026v1 Announce Type: cross Abstract: Forecast errors in high-resolution numerical weather prediction (NWP) systems are often linked to unresolved planetary boundary layer (PBL) processes, convection, terrain-induced circulations, and other vertically structured atmospheric phenomena.

By David Aaron Evans, Jay C. Rothenberger, Kara J. Sulia, Nick P. Bassill, Chris D. Thorncroft

llms computer-vision safety

arXiv Machine Learning

Jul 7

GlacierCastAI: Predicting Glacier Retreat from Multi-Modal Satellite Imagery and Climate Signals

arXiv:2607. 04117v1 Announce Type: new Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing deep learning methods focus on mapping current boundaries rather than forecasting future ones.

By Arunkumar Ramachandran

multimodal benchmarks

arXiv Machine Learning

Jun 15

Can Machine Learning Forecast Rice Yields in Data-Constrained Settings? Satellite Climate Data, National Crop Statistics, and Lessons from Sierra Leone

arXiv:2606. 13959v1 Announce Type: new Abstract: Sierra Leone's agriculture operates with almost no data-driven decision support, and no published machine learning study has examined the country's crop yields.

By Ibrahim Denis Fofanah

arXiv AI

Jul 14

Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector

arXiv:2607. 10208v1 Announce Type: cross Abstract: Accurate meteorological forecasting is essential for agricultural planning, irrigation management, and environmental decision support.

By Piotr Sikora, Sotirios Kontogiannis

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Probabilistic NDVI Forecasting from Sparse Satellite Time Series and Weather Covariates

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A Hybrid LSTM--Vision Transformer Architecture for Predicting HRRR Forecast Errors

GlacierCastAI: Predicting Glacier Retreat from Multi-Modal Satellite Imagery and Climate Signals

Can Machine Learning Forecast Rice Yields in Data-Constrained Settings? Satellite Climate Data, National Crop Statistics, and Lessons from Sierra Leone

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