most citedOn the Foundations of Earth and Climate Foundation Models

16 citations · 16 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2025

GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification

Yang Mu, Zhitong Xiong, Yi Wang +5

Global tree species mapping using remote sensing data is vital for biodiversity monitoring, forest management, and ecological research. However, progress in this field has been con…

cs.CV2025

Towards a Unified Copernicus Foundation Model for Earth Vision

Yi Wang, Zhitong Xiong, Chenying Liu +8

Advances in Earth observation (EO) foundation models have unlocked the potential of big satellite data to learn generic representations from space, benefiting a wide range of downs…

cs.LG2025

Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation

Leonard Waldmann, Ando Shah, Yi Wang +6

Earth observation (EO) data features diverse sensing platforms with varying spectral bands, spatial resolutions, and sensing modalities. While most prior work has constrained input…

cs.CV2025

DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation

Zhitong Xiong, Yi Wang, Weikang Yu +7

Earth observation (EO) spans a broad spectrum of modalities, including optical, radar, multispectral, and hyperspectral data, each capturing distinct environmental signals. However…

cs.AI202416 cited

On the Foundations of Earth and Climate Foundation Models

Xiao Xiang Zhu, Zhitong Xiong, Yi Wang +7

Foundation models have enormous potential in advancing Earth and climate sciences, however, current approaches may not be optimal as they focus on a few basic features of a desirab…