5 papers
SPECTRA: Band-Routed Embedding and Stage-Wise LoRA for Cross-Sensor Fine-Tuning of Geospatial Foundation Models
Xingyan Li, Jordan A. Caraballo-Vega, Jie Gong +2
Geospatial foundation models (GeoFMs), pretrained on large-scale geospatial data such as Earth observation (EO), climate, and weather data, have shown promising performance when fi…
Learning Subglacial Bed Topography from Sparse Radar with Physics-Guided Residuals
Bayu Adhi Tama, Jianwu Wang, Vandana Janeja +1
Accurate subglacial bed topography is essential for ice sheet modeling, yet radar observations are sparse and uneven. We propose a physics-guided residual learning framework that p…
Improving Greenland Bed Topography Mapping with Uncertainty-Aware Graph Learning on Sparse Radar Data
Bayu Adhi Tama, Homayra Alam, Mostafa Cham +3
Accurate maps of Greenland's subglacial bed are essential for sea-level projections, but radar observations are sparse and uneven. We introduce GraphTopoNet, a graph-learning frame…
DeepTopoNet: A Framework for Subglacial Topography Estimation on the Greenland Ice Sheets
Bayu Adhi Tama, Mansa Krishna, Homayra Alam +6
Understanding Greenland's subglacial topography is critical for projecting the future mass loss of the ice sheet and its contribution to global sea-level rise. However, the complex…
Integrating Fourier Transform and Residual Learning for Arctic Sea Ice Forecasting
Louis Lapp, Sahara Ali, Jianwu Wang
Arctic sea ice plays integral roles in both polar and global environmental systems, notably ecosystems, communities, and economies. As sea ice continues to decline due to climate c…