CCAV-10m: an annual spatiotemporal dataset for eastern coastal China’s wetland vegetation by integrating Sentinel-1/2 observations via deep learning

Li, Yuying; Yuan, Lina; Liu, Ting; Song, Zijiang; Yang, Shuang; Zhu, Zilong; Liu, Min

doi:10.5194/essd-18-2907-2026

Articles | Volume 18, issue 4

https://doi.org/10.5194/essd-18-2907-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-18-2907-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 4

Data description article

|

27 Apr 2026

Data description article |

| 27 Apr 2026

CCAV-10m: an annual spatiotemporal dataset for eastern coastal China’s wetland vegetation by integrating Sentinel-1/2 observations via deep learning

Yuying Li, Lina Yuan, Ting Liu, Zijiang Song, Shuang Yang, Zilong Zhu, and Min Liu

Data sets

CCAV-10m: An Annual Spatiotemporal China Coastal Wetland Vegetation Dataset Integrating Sentinel-1/2 Observations via Deep Learning Yuying Li et al. https://doi.org/10.57760/sciencedb.31077

Short summary

We introduce CCAV-10m, an annual, species-level 10m resolution coastal wetland vegetation dataset for eastern China. It was produced using a novel phenology-guided vegetation classification network that integrates Sentinel-1/2 satellite imagery with field observations. Validation demonstrates strong classification accuracy (overall accuracy: 0.916, Kappa: 0.898). Regular updates will support long-term coastal wetland research, invasive species monitoring, and precision wetland management.