TESSERA Webinar Announcement: October 29th 15:00 UTC

Time: 15:00-16:00 (UTC+1)

Date: 29 October 2025

Zoom link: https://zoom.us/meeting/register/8K2gUUogQ3i0wWLyqgbYHg

Meeting ID: 986 7577 5003

Passcode: 070145

Title:

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

Abstract:

Satellite remote sensing enables a wide range of downstream applications, including habitat mapping, carbon accounting, and strategies for conservation and sustainable land use. However, satellite time series are voluminous and often corrupted, making them challenging to use. We present TESSERA, an open, global, land-oriented remote sensing foundation model that uses self-supervised learning to generate “ready-to-use” embeddings at 10~m scale from pixel-level satellite time-series data.

TESSERA uses two encoders to combine optical data with synthetic aperture radar backscatter coefficients at 10~m resolution to create embeddings that are fused with a multilayer perceptron to create annual global embedding maps. We compare our work with state-of-the-art task-specific models and other foundation models in five diverse downstream tasks and find that TESSERA closely matches or outperforms these baselines. We believe that TESSERA’s ease of use, state-of-the-art performance, openness, and computation- and labelled data-efficiency will prove transformative in a wide range of ecological applications.

Speakers:

Srinivasan Keshav, Profesor and Frank (Zhengpeng) Feng, PhD Candidate

Department of Computer Science and Technology

University of Cambridge