mlsanityData to 7 Oct 2026

Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shift

arXiv 2407.07616 ↗First posted 10 Jul 2024cs.CVcited by 6

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Abstract (arXiv)

Satellite imagery plays a crucial role in monitoring changes happening on Earth's surface and aiding in climate analysis, ecosystem assessment, and disaster response. In this paper, we tackle semantic change detection with satellite image time series (SITS-SCD) which encompasses both change detection and semantic segmentation tasks. We propose a new architecture that improves over the state of the art, scales better with the number of parameters, and leverages long-term temporal information. However, for practical use cases, models need to adapt to spatial and temporal shifts, which remains a challenge. We investigate the impact of temporal and spatial shifts separately on global, multi-year SITS datasets using DynamicEarthNet and MUDS. We show that the spatial domain shift represents the most complex setting and that the impact of temporal shift on performance is more pronounced on change detection than on semantic segmentation, highlighting that it is a specific issue deserving further attention.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 17 of its 55 references that are in the map. First posted on arXiv 10 Jul 2024.

Builds on

17 of 55 references.

References · 17

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  3. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  4. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,154
  5. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  6. 2021Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networkscited by 141
  7. 2022DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentationcited by 78
  8. 2019Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attentioncited by 71
  9. 2021The Multi-Temporal Urban Development SpaceNet Datasetcited by 62
  10. 2020Lightweight Temporal Self-Attention for Classifying Satellite Image Time Seriescited by 55
  11. 2023ViTs for SITS: Vision Transformers for Satellite Image Time Seriescited by 55
  12. 2021Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Imagescited by 43
5 more
  1. 2022Joint Spatio-Temporal Modeling for the Semantic Change Detection in Remote Sensing Imagescited by 43
  2. 2022Generalized Classification of Satellite Image Time Series with Thermal Positional Encodingcited by 14
  3. 2023MapFormer: Boosting Change Detection by Using Pre-change Informationcited by 12
  4. 2020Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite Imagerycited by 10
  5. 2023Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approachcited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 1.

6 papers.

  1. 2024AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalitiescited by 73
  2. 2025DISCO: Disentangled Communication Steering for Large Language Modelscited by 5
  3. 2025CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysiscited by 2
  4. 2025Multi-temporal Calving Front Segmentationcited by 1
  5. 2025Operational Change Detection for Geographical Information: Overview and Challengescited by 0
  6. 2026Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Typescited by 0