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20242026
most citedTESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis

40 citations · 49 across the 6 of their papers we have counts for

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cs.LG2026

Exploring the potential of AlphaEarth and TESSERA embeddings for Fine-scale Local Climate Zone Mapping: A case study across five cities in Switzerland

Htet Yamin Ko Ko, Clement Atzberger

Understanding urban spatial morphology is critical for climate modeling, risk assessment, and sustainable urban design, and Local Climate Zone (LCZ) mapping provides the basic fram…

cs.LG2026★ 1 cited

Embedding -based Crop Type Classification in the Groundnut Basin of Senegal

Madeline C. Lisaius, Srinivasan Keshav, Andrew Blake +1

Crop type maps from satellite remote sensing are important tools for food security, local livelihood support and climate change mitigation in smallholder regions of the world, but…

cs.LG2025★ 40 cited

TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis

Zhengpeng Feng, Clement Atzberger, Sadiq Jaffer +11

Satellite Earth-observation (EO) time series in the optical and microwave ranges of the electromagnetic spectrum are often irregular due to orbital patterns and cloud obstruction.…

cs.LG2024★ 1 cited

PILA: Physics-Informed Low Rank Augmentation for Interpretable Earth Observation

Yihang She, Andrew Blake, Clement Atzberger +2

Physically meaningful representations are essential for Earth Observation (EO), yet existing physical models are often simplified and incomplete. This leads to discrepancies betwee…

cs.LG2024★ 1 cited

From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model

Yihang She, Clement Atzberger, Andrew Blake +1

Advances in machine learning have boosted the use of Earth observation data for climate change research. Yet, the interpretability of machine-learned representations remains a chal…