Coverage Analysis: 2023-10-07

Sentinel-2 Cloud Mask Overlay Visualization

⚠️ 6.7% Total Contamination ☁️ 5.7% Cloud Cover 🌑 1.0% Shadows 🛰️ S2A 📐 10m/Pixel 📖 Cite Me
Faded True Color Image
Cloud & Shadow Coverage Overlay

☁️ Cloud & Shadow Detection

Cloud and shadow masks are generated using OmniCloudMask, a deep learning ensemble trained on the CloudSEN12 dataset. The model processes three spectral bands (Red, Green, Near-Infrared) from Sentinel-2 imagery to classify pixels as clear, cloud, or shadow, then applies morphological post-processing to remove noise and smooth boundaries.

Coverage Analysis & Color Legend

  • Total pixels: 13761176 (3289×4184 at 10m resolution)
  • Total contaminated: 919475 (6.7%)
  • Clear areas within Gaza: 12841701 (93.3%)
  • Clouds within Gaza: 788537 (5.7%)
  • Shadows within Gaza: 130938 (1.0%)
  • Clouds outside Gaza
  • Shadows outside Gaza

📚 OmniCloudMask Reference

Model OmniCloudMask
Authors Wright, N. J.; Duncan, J. M. A.; Callow, J. N.; Thompson, S. E.; George, R. J.
Publication Remote Sensing of Environment, 322, 114694 (2025)
DOI 10.1016/j.rse.2025.114694
Repository github.com/DPIRD-DMA/OmniCloudMask
License MIT

🛰️ Product Information & Attribution

Product ID S2A_MSIL2A_20231007T081821_N0510_R121_T36RXV_20241108T203220
Sensing Time 2023-10-07 08:18:21 UTC
Orbit 121
Tile ID T36RXV
Processing Baseline N051
Credit Line Contains modified Copernicus Sentinel data 2023
Data Source https://dataspace.copernicus.eu/
Modifications Official L2A TCI raster cropped to Gaza Strip AOI with visualization overlays: hot magenta/neon purple cloud/shadow mask overlay.
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Citation Formats

Chicago Style

European Commission Copernicus Programme. Sentinel-2 Level-2A satellite imagery. Contains modified Copernicus Sentinel data 2023. Processed by Sentinel Bird. Accessed January 10, 2026. https://dataspace.copernicus.eu/ Wright, Nicholas, John M.A. Duncan, J. Nik Callow, Sally E. Thompson, and Richard George. "Training Sensor-Agnostic Deep Learning Models for Remote Sensing: Achieving State-of-the-Art Cloud and Cloud Shadow Identification with OmniCloudMask." Remote Sensing of Environment 322 (2025): 114694. https://doi.org/10.1016/j.rse.2025.114694 Sentinel Bird. "Cloud Coverage Analysis for 2023-10-07." Sentinel Bird Gaza Satellite Analysis. Accessed January 10, 2026. https://sentinelbird.com/dates/2023-10-07/cloud_masks/.

MLA Style

European Commission Copernicus Programme. Sentinel-2 Level-2A satellite imagery. Contains modified Copernicus Sentinel data 2023. Processed by Sentinel Bird. Copernicus Data Space Ecosystem, https://dataspace.copernicus.eu/. Accessed 10 Jan. 2026. Wright, Nicholas, et al. "Training Sensor-Agnostic Deep Learning Models for Remote Sensing: Achieving State-of-the-Art Cloud and Cloud Shadow Identification with OmniCloudMask." Remote Sensing of Environment, vol. 322, 2025, p. 114694, https://doi.org/10.1016/j.rse.2025.114694. Sentinel Bird. "Cloud Coverage Analysis for 2023-10-07." Sentinel Bird Gaza Satellite Analysis, 2026, https://sentinelbird.com/dates/2023-10-07/cloud_masks/. Accessed 10 Jan. 2026.
Note: This visualization is a derived product. All three sources should be cited: Sentinel-2 data, OmniCloudMask methodology, and this visualization.