Mapping large-scale aquaculture ponds in Jiangsu Province, China: An automatic extraction framework based on Sentinel-1 time-series imagery

Chongbin Liu,Jia Xu,Kang Xu,Juanjuan Yu

AQUACULTURE(2024)

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摘要
Aquaculture holds significant importance in supporting food security, economic development, resource conservation, and ecological balance. However, the rapid expansion of aquaculture ponds has caused many environmental problems. Studies on the trends and spatial distribution of aquaculture ponds in Jiangsu province, China, are limited, and there is a lack of aquaculture datasets with a 10-m resolution. This study aimed to develop a novel assessment framework for mapping aquaculture ponds using the Google Earth Engine (GEE) platform and Sentinel-1 time-series images. We integrated multi-threshold segmentation and object-oriented classification to extract spatial data on aquaculture ponds from 2017 to 2021 in Jiangsu Province. Results showed that (1) local adaptive threshold methods could extract data about water bodies more effectively. Based on the time series of each image element, calculating its water frequency could effectively exclude seasonal water. (2) This method could effectively map aquaculture ponds in Jiangsu Province. The overall identification accuracy was higher than 93%, and the Kappa coefficient was higher than 0.87. These results are in accordance with those in the statistical yearbook. (3) The total aquaculture pond area was largest in 2017 (3404.00 km2) and smallest in 2021 (2939.51 km2). The aquaculture pond area in Jiangsu Province showed a slight downward trend over the five-year period. Aquaculture ponds were mainly distributed in central and southern Jiangsu and the coastal areas, with the highest density at the junction of Yangzhou, Taizhou, and Yancheng. (4) From 2017 to 2021, Aquaculture ponds spanning 104.65 km2 (accounting for 55.28% of the total reduced area) were transformed into wetlands. In the coastal zone. Our results substantiate that aquaculture pond removal can accelerate wetland restoration. This study maximised the identification of aquaculture ponds as independent targets. Taken together, these results can provide a reference for aquaculture green development and tail water management in Jiangsu Province.
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Aquaculture ponds,SAR,Time series,Google earth engine (GEE)
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