Comparative analysis of dual-form networks for live land monitoring using multi-modal satellite image time series
Iris Dumeur (CB), J\'er\'emy Anger (CB), Gabriele Facciolo (CB)

TL;DR
This paper compares dual-form attention mechanisms for efficient, recurrent multi-modal satellite image time series analysis, enabling large-area live land monitoring with performance comparable to standard Transformers.
Contribution
It introduces temporal adaptations of dual-form mechanisms for irregular, unaligned satellite data, supporting recurrent inference and improving operational land monitoring.
Findings
Dual-form mechanisms match Transformer performance in SITS forecasting.
Multimodal approach outperforms mono-modal methods in land monitoring tasks.
Efficient recurrent inference enables large-area, real-time land monitoring.
Abstract
Multi-modal Satellite Image Time Series (SITS) analysis faces significant computational challenges for live land monitoring applications. While Transformer architectures excel at capturing temporal dependencies and fusing multi-modal data, their quadratic computational complexity and the need to reprocess entire sequences for each new acquisition limit their deployment for regular, large-area monitoring. This paper studies various dual-form attention mechanisms for efficient multi-modal SITS analysis, that enable parallel training while supporting recurrent inference for incremental processing. We compare linear attention and retention mechanisms within a multi-modal spectro-temporal encoder. To address SITS-specific challenges of temporal irregularity and unalignment, we develop temporal adaptations of dual-form mechanisms that compute token distances based on actual acquisition dates…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRemote Sensing in Agriculture · Remote-Sensing Image Classification · Automated Road and Building Extraction
