English

Cropland Mapping using Geospatial Embeddings

Computer Vision and Pattern Recognition 2025-11-06 v1

Abstract

Accurate and up-to-date land cover maps are essential for understanding land use change, a key driver of climate change. Geospatial embeddings offer a more efficient and accessible way to map landscape features, yet their use in real-world mapping applications remains underexplored. In this work, we evaluated the utility of geospatial embeddings for cropland mapping in Togo. We produced cropland maps using embeddings from Presto and AlphaEarth. Our findings show that geospatial embeddings can simplify workflows, achieve high-accuracy cropland classification and ultimately support better assessments of land use change and its climate impacts.

Keywords

Cite

@article{arxiv.2511.02923,
  title  = {Cropland Mapping using Geospatial Embeddings},
  author = {Ivan Zvonkov and Gabriel Tseng and Inbal Becker-Reshef and Hannah Kerner},
  journal= {arXiv preprint arXiv:2511.02923},
  year   = {2025}
}

Comments

8 pages, 11 figures

R2 v1 2026-07-01T07:21:54.250Z