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October 15, 20250 citationsOpen Access

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

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FFFangxiang FengCAClement AtzbergerSJSadiq Jaffer

Key Points

  • Satellite time series enhance climate modeling and carbon accounting, but face challenges from noise and gaps.
  • Temporal embeddings provide a solution to analyze complex satellite data, leveraging repeated observations.
  • These embeddings can simplify the use of voluminous satellite recordings in various environmental applications.
  • The methods aim to refine analysis of surface spectra to support conservation and sustainable land use efforts.

Abstract

Satellite remote sensing from repeated observations and multiple sensors enables a wide range of downstream applications, including climate modeling, carbon accounting, and strategies for conservation and sustainable land use. However, satellite time series are voluminous, often corrupted by sensor noise, clouds, and atmospheric conditions, and unevenly spaced in time, making them challenging to use.

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Cite This Study

Feng et al. (2025) studied this question.

synapsesocial.com/papers/68efd921056559ef42877521https://doi.org/10.59350/yhbhs-5v702
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  1. 1TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis2025 · 9 citations
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