This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …

The foundation model has recently garnered significant attention due to its potential to
revolutionize the field of visual representation learning in a self-supervised manner. While …

Enhancing original LiDAR point cloud features with virtual points has gained widespread
attention in multimodal information fusion. However, existing methods struggle to leverage …

Hyperspectral image classification (HSIC) has become a hot research topic. Hyperspectral
imaging (HSI) has been widely used in a wide range of real-world application areas due to …

Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with
the aid of high spatial resolution multispectral (MS) images. Most prior works usually perform …

Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise
information for diverse downstream applications. Recent development of the segment …

Quantitative remote sensing of crop diseases at the field or plot scale is essential for crop
management. Conventional approaches frequently rely solely on single-modal remote …

Earth observation (EO) techniques have undergone rapid development, facilitating
comprehensive measurement and monitoring of the Earth's various facets, including land …

Convolutional neural networks (CNNs) and vision transformers (ViTs) have shown excellent
capability in complex hyperspectral image (HSI) classification. However, these models …

Multimodal Large Language Models (MLLMs) mimic human perception and reasoning
system by integrating powerful Large Language Models (LLMs) with various modality …