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Remote Sensing for Natural Resources    2022, Vol. 34 Issue (4) : 33-41     DOI: 10.6046/zrzyyg.2021438
Identification of mariculture areas in Guangdong Province and remote sensing monitoring of their spatial and temporal changes based on the U-Net convolutional neural network
SU Wei1(), LIN Yangyang1, YUE Wen1(), CHEN Yingbiao2
1. Land Investigation and Planning Institute of Guangdong Province, Guangzhou 511453, China
2. School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
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The mariculture industry occupies an important position in the marine economy of Guangdong Province. Timely and accurate knowledge of the spatial distribution and area changing trends of mariculture areas can greatly promote the sustainable development of the mariculture industry. Conventional interpretation methods for remote sensing images have problems of poor repeatability, low applicability, and high subjective arbitrariness. By contrast, the U-Net convolutional neural network, which belongs to the deep learning network model, can better extract the features of the object with higher extraction precision. Therefore, based on the multi-temporal Landsat TM/OLI remote sensing images, this study identified the mariculture areas (enclosed-sea and open-cage aquaculture areas) in Guangdong from 1998 to 2021 using the U-Net model as the interpretation model. The area trend analysis of mariculture areas was made. The changing characteristics of mariculture areas in terms of spatial distribution patterns were studied. The results are as follows. Compared with network models such as K-Means cluster analysis and DBN, the U-Net model with higher interpretation precision is more suitable for the interpretation of mariculture areas in Guangdong. The mariculture areas in Guangdong are mainly distributed in the western portion of Guangdong, such as Zhanjiang, Jiangmen, and Yangjiang. The mariculture areas in Guangdong can be classified into three levels in terms of area. They have small changes and keep a relatively stable state. The mariculture areas in Guangdong showed a spatial trend of outward expansion from 1998 to 2014 and inward contraction from 2014 to 2021. This study will provide data and technical support for the scientific management of the mariculture areas in Guangdong.

Keywords mariculture area      remote sensing      deep learning      U-Net model      Guangdong Province     
ZTFLH:  TP79  
Issue Date: 27 December 2022
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Wei SU
Yangyang LIN
Yingbiao CHEN
Cite this article:   
Wei SU,Yangyang LIN,Wen YUE, et al. Identification of mariculture areas in Guangdong Province and remote sensing monitoring of their spatial and temporal changes based on the U-Net convolutional neural network[J]. Remote Sensing for Natural Resources, 2022, 34(4): 33-41.
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Fig.1  Location map of the study area
Fig.2  Network structure of U-Net
Fig.3  Comparison of three types of models to identify mariculture areas
Tab.1  Distribution of mariculture areas in Guangdong from 1998 to 2021
城市 1998年 2002年 2006年 2010年 2014年 2018年 2021年
潮州 130 87 20 49 43 46 16
汕头 646 495 479 688 1743 547 317
揭阳 64 93 93 160 103 140 92
汕尾 827 797 1 014 1 054 1 076 1 009 836
惠州 1 152 1 569 1 531 1 462 1 399 1 228 1 337
深圳 1 814 2 186 2 557 1 210 887 699 143
东莞 110 150 42 70 144 58 23
广州 19 225 137 99 215 557 597
中山 783 847 956 1 660 1 066 745 242
珠海 3 103 3 282 3 101 4 272 3 535 3 949 3 758
江门 6 050 7 339 8 506 7 588 7 938 7 684 7 567
阳江 5 880 5 567 7 163 6 579 6 658 6 982 6 632
茂名 1 032 1 305 1 378 1 680 1 427 1 114 1 317
湛江 26 344 24 798 28 232 25 317 26 211 26 187 26 626
Tab.2  Area of mariculture areas in coastal cities of Guangdong form 1998 to 2021(hm2)
城市 1998—
潮州 -8.3 -19.3 36.3 -3.1 1.7 -21.7
汕头 -5.8 -0.8 10.9 38.3 -17.2 -14.0
揭阳 11.3 0.0 18.0 -8.9 9.0 -11.4
汕尾 -0.9 6.8 1.0 0.5 -1.6 -5.7
惠州 9.0 -0.6 -1.1 -1.1 -3.1 3.0
深圳 5.1 4.2 -13.2 -6.7 -5.3 -26.5
东莞 9.1 -18.0 16.7 26.4 -14.9 -20.1
广州 271.1 -9.8 -6.9 29.3 39.8 2.4
中山 2.0 3.2 18.4 -8.9 -7.5 -22.5
珠海 1.4 -1.4 9.4 -4.3 2.9 -1.6
江门 5.3 4.0 -2.7 1.2 -0.8 -0.5
阳江 -1.3 7.2 -2.0 0.3 1.2 -1.7
茂名 6.6 1.4 5.5 -3.8 -5.5 6.1
湛江 -1.5 3.5 -2.6 0.9 0.0 0.6
Tab.3  Dynamic of mariculture areas in coastal cities of Guangdong form 1998 to 2021(%)
Fig.4  Spatial pattern of mariculture areas in Guangdong from 1998 to 2021
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