6 papers · 1 filter
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Junchao Gong, Kaiyi Xu, Wangxu Wei +22
Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…
OpenEarth-Agent: From Tool Calling to Tool Creation for Open-Environment Earth Observation
Sijie Zhao, Feng Liu, Xueliang Zhang +11
Earth Observation (EO) is essential for perceiving dynamic land surface changes, yet deploying autonomous EO in open environments is hindered by the immense diversity of multi-sour…
Spatial-Temporal-Spectral Unified Modeling for Remote Sensing Dense Prediction
Sijie Zhao, Feng Liu, Enzhuo Zhang +5
The proliferation of multi-source remote sensing data has propelled the development of deep learning for dense prediction, yet significant challenges in data and task unification p…
Transforming Weather Data from Pixel to Latent Space
Sijie Zhao, Feng Liu, Xueliang Zhang +7
The increasing impact of climate change and extreme weather events has spurred growing interest in deep learning for weather research. However, existing studies often rely on weath…
VegeDiff: Latent Diffusion Model for Geospatial Vegetation Forecasting
Sijie Zhao, Hao Chen, Xueliang Zhang +3
In the context of global climate change and frequent extreme weather events, forecasting future geospatial vegetation states under these conditions is of significant importance. Th…
RS-Mamba for Large Remote Sensing Image Dense Prediction
Sijie Zhao, Hao Chen, Xueliang Zhang +3
Context modeling is critical for remote sensing image dense prediction tasks. Nowadays, the growing size of very-high-resolution (VHR) remote sensing images poses challenges in eff…