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https://doi.org/10.5194/essd-2020-122
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2020-122
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  22 Sep 2020

22 Sep 2020

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This preprint is currently under review for the journal ESSD.

A new satellite-derived dataset for marine aquaculture areas in the China's coastal region

Yongyong Fu1, Jinsong Deng1, Hongquan Wang1, Alexis Comber2, Wu Yang1, Wenqiang Wu1, Shixue You1, Yi Lin3, and Ke Wang1 Yongyong Fu et al.
  • 1College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, 310058, China
  • 2School of Geography, University of Leeds, Leeds LS1 9JT, UK
  • 3Department of Geography, University of Hong Kong, Hong Kong SAR 999077, China

Abstract. China has witnessed extensive development of the marine aquaculture industry over recent years. However, such rapid and disordered expansion posed risks to coastal environment, economic development, and biodiversity protection. This study aimed to produce an accurate national-scale marine aquaculture map at a spatial resolution of 16 m, using a proposed deep convolution neural networks (CNNs) based model and applied it to satellite data from China's GF-1 sensor in an end-to-end way. The analyses used homogeneous CNNs to extract high-dimensional features from the input imagery and preserve information at full resolution. Then, a hierarchical cascade architecture was followed to capture multi-scale features and contextual information. This hierarchical cascade homogeneous neural network (HCHNet) was found to achieve better classification performance than current state-of-the-art models (FCN-32s, Deeplab V2, U-Net, and HCNet). The resulting marine aquaculture area map has an overall classification accuracy > 95 % (95.2 %–96.4, 95 % confidence interval). And marine aquaculture was found to cover a total area of ~1100 km2 (1096.8 km2–1110.6 km2, 95 % confidence interval) in China, of which more than 85 % are marine plant culture areas, with 87 % found in the Fujian, Shandong, Liaoning, and Jiangsu provinces. The results confirm the applicability and effectiveness of HCHNet when applied to GF-1 data, identifying notable spatial distributions of different marine aquaculture areas and supporting the sustainable management and ecological assessments of coastal resources at a national scale. The national-scale marine aquaculture map at 16 m spatial resolution is published in the Google Maps kmz File Format with georeferencing information at https://doi.org/10.5281/zenodo.3881612 (Fu et al., 2020).

Yongyong Fu et al.

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A new satellite-derived dataset for marine aquaculture in the China's coastal region Yongyong Fu, Jinsong Deng, Hongquan Wang, Alexis Comber, Wu Yang, Wenqiang Wu, Shixue You, Yi Lin, and Ke Wang https://doi.org/10.5281/zenodo.3881612

Yongyong Fu et al.

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Short summary
Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the first time. It was found to cover a total area of ~1100 km2, of which more than 85 % are marine plant culture areas, with 87 % found in four coastal provinces. The results confirm the applicability and effectiveness of deep learning when applied to GF-1 data at the national scale, identifying the detailed spatial distributions and supporting the sustainable management of coastal resources in China.
Marine aquaculture areas in a region up to 30 km from the coast in China were mapped for the...
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