EarthScape: A Multimodal Dataset for Surficial Geologic Mapping and Earth Surface Analysis

Matthew Massey, Nusrat Munia, Abdullah-Al-Zubaer Imran
3/19/2025
cs.CV

Official code: masseygeo/earthscape (20 stars, MIT, last commit 2026-04-15).

Abstract

Surficial geologic (SG) maps are essential for understanding surface processes and supporting infrastructure planning, but current workflows are labor-intensive and difficult to scale. We introduce EarthScape, an AI-ready multimodal dataset for SG mapping that integrates digital elevation models, aerial imagery, multi-scale terrain features, and hydrologic and infrastructure vector data within a unified, reproducible pipeline. We report baseline benchmarks across single-modality, multi-scale, and multimodal configurations. Our experiments show that terrain features provide the most reliable predictive signal, while raw spectral and elevation inputs degrade substantially under cross-region evaluation. EarthScape offers a geographically compact, but modality-rich benchmark for multimodal fusion, domain adaptation, and surface modeling. EarthScape is available for direct download at https://uknowledge.uky.edu/kgs_data/16/, and code is available at https://github.com/masseygeo/earthscape.

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MIT

EarthScape: a multimodal dataset for surficial geologic mapping, Earth surface analysis, and domain shift analysis..

204Shell, PythonJun 4, 20246 months agoMIT

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Cite this paper

@article{massey2025earthscape,
  title  = {EarthScape: A Multimodal Dataset for Surficial Geologic Mapping and Earth Surface Analysis},
  author = {Matthew Massey and Nusrat Munia and Abdullah-Al-Zubaer Imran},
  year   = {2025},
  eprint = {2503.15625},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.15625v2}
}

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