Nationwide spatial distribution of aquaculture ponds in China: Inland surpassing coastal areas revealed by Satellite remote sensing

• A novel OS-APM workflow was developed to map aquaculture ponds (APs). • First national-scale annual 10-m AP datasets (2016–2023) in China were made. • Inland dominated China’s contemporary aquaculture landscape (56% vs. coastal 44%) • AP area exhibited an inverted-U trend (peak 2019) with 14% contraction by 2023. • The reversal was strongly correlated with China’s ecological civilization initiatives. Rapid expansion of China’s aquaculture ponds (APs) has significantly contributed to food security and economic development, yet simultaneously triggering ecological degradation. However, the absence of high-resolution national datasets has constrained systematic analyses of APs’ spatiotemporal dynamics and their transboundary environmental footprints. To fill this gap, we developed a robust approach for accurately monitoring APs across China and elucidating the spatiotemporal dynamics and underlying mechanisms driving their changes. The Optical-SAR Aquaculture Pond Mapper (OS-APM) was developed, a novel framework integrating spatiotemporal-spectral signatures to synergistically leverage multi-sensor time series for precision AP mapping. The OS-APM comprised a hierarchical segmentation strategy for large-scale AP delineation, multi-modal feature fusion to distinguish spectrally ambiguous classes, and an ensemble classifier integrating optical, SAR, geometric, and topographic features. The framework achieved individual-pond-scale extraction accuracy (OA > 90 %) and generated China’s first 10-m resolution annual AP dataset (China_AP), derived from 119,882 Sentinel-1 and 579,436 Sentinel-2 scenes (2016–2023). This dataset revealed previously undocumented spatiotemporal patterns, indicating a 2023 AP inventory of 19,919.52 km 2 , with inland systems (55.56 %) now surpassing coastal ones (44.44 %) to dominate China’s aquaculture landscape. Spatially, four provinces (Jiangsu, Hubei, Shandong, Guangdong) collectively host 56 % of national APs, with 58 % clustered in the Yangtze-Huaihe River corridors. Temporally, the AP area exhibited an inverted-U trajectory, increasing from 20,685.20 km 2 (2016) to a peak of 23,256.84 km 2 (2019), then contracting below initial levels to 19,919.52 km 2 by 2023. This reversal strongly correlates with China’s ecological civilization initiatives, notably the 2017 Aquaculture Water and Tidal Flat Plan. This study establishes multi-sensor data for national AP monitoring, quantifies inland AP expansion patterns under policy regulation, and delivers a scientific foundation for reconciling aquaculture intensification with wetland conservation.

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Publication Details

Journal
International Journal of Applied Earth Observation and Geoinformation
Published
2025-11-15
DOI
https://doi.org/10.1016/j.jag.2025.104958
Citations
1
Primary Topic
Marine Bivalve and Aquaculture Studies
Type
article
Field-Weighted Citation Impact
1.11
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article

Nationwide spatial distribution of aquaculture ponds in China: Inland surpassing coastal areas revealed by Satellite remote sensing

Hongtao Duan, Tianci Qi, Zhe Sun, Xiaohong Gu et al.
1 citations
International Journal of Applied Earth Observation and Geoinformation
Marine Bivalve and Aquaculture Studies
1.11
article

Nationwide spatial distribution of aquaculture ponds in China: Inland surpassing coastal areas revealed by Satellite remote sensing

Hongtao Duan, Tianci Qi, Zhe Sun, Xiaohong Gu, Wenping Yuan, Zhigang Cao, Juhua Luo, Ming Shen
article en
1 citations

Abstract

• A novel OS-APM workflow was developed to map aquaculture ponds (APs). • First national-scale annual 10-m AP datasets (2016–2023) in China were made. • Inland dominated China’s contemporary aquaculture landscape (56% vs. coastal 44%) • AP area exhibited an inverted-U trend (peak 2019) with 14% contraction by 2023. • The reversal was strongly correlated with China’s ecological civilization initiatives. Rapid expansion of China’s aquaculture ponds (APs) has significantly contributed to food security and economic development, yet simultaneously triggering ecological degradation. However, the absence of high-resolution national datasets has constrained systematic analyses of APs’ spatiotemporal dynamics and their transboundary environmental footprints. To fill this gap, we developed a robust approach for accurately monitoring APs across China and elucidating the spatiotemporal dynamics and underlying mechanisms driving their changes. The Optical-SAR Aquaculture Pond Mapper (OS-APM) was developed, a novel framework integrating spatiotemporal-spectral signatures to synergistically leverage multi-sensor time series for precision AP mapping. The OS-APM comprised a hierarchical segmentation strategy for large-scale AP delineation, multi-modal feature fusion to distinguish spectrally ambiguous classes, and an ensemble classifier integrating optical, SAR, geometric, and topographic features. The framework achieved individual-pond-scale extraction accuracy (OA > 90 %) and generated China’s first 10-m resolution annual AP dataset (China_AP), derived from 119,882 Sentinel-1 and 579,436 Sentinel-2 scenes (2016–2023). This dataset revealed previously undocumented spatiotemporal patterns, indicating a 2023 AP inventory of 19,919.52 km 2 , with inland systems (55.56 %) now surpassing coastal ones (44.44 %) to dominate China’s aquaculture landscape. Spatially, four provinces (Jiangsu, Hubei, Shandong, Guangdong) collectively host 56 % of national APs, with 58 % clustered in the Yangtze-Huaihe River corridors. Temporally, the AP area exhibited an inverted-U trajectory, increasing from 20,685.20 km 2 (2016) to a peak of 23,256.84 km 2 (2019), then contracting below initial levels to 19,919.52 km 2 by 2023. This reversal strongly correlates with China’s ecological civilization initiatives, notably the 2017 Aquaculture Water and Tidal Flat Plan. This study establishes multi-sensor data for national AP monitoring, quantifies inland AP expansion patterns under policy regulation, and delivers a scientific foundation for reconciling aquaculture intensification with wetland conservation.

International Journal of Applied Earth Observation and GeoinformationVol. 145
Chinese Academy of Sciences (CN), Peking University (CN), Nanjing Institute of Geography and Limnology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 18%
Marine Bivalve and Aquaculture Studies
1.11
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