Dynamics of artificial aquaculture ponds in China from 2015 to 2025

Abstract

Artificial aquaculture ponds (AAPs) play a critical role in ensuring food security, supporting rural economic development, and shaping ecological landscapes. Yet, a nationally consistent, high-resolution, and individual-scale dataset of these ponds has been unavailable, hindering accurate assessments of their spatial distribution and temporal dynamics. In this study, we present CN-AAP10, the first 10-m resolution dataset of AAPs across China, delineating individual ponds from Sentinel-2 imagery. Using an improved ResUNet model applied to annual median composites of Sentinel-2 data for 2015, 2020, and 2025, we generated a dataset that captures pond-level features and their changes over a decade. Validation based on 3,049 randomly selected samples yielded an overall accuracy of 92.46%. Our results reveal a markedly uneven spatial distribution: eastern China accounts for 97.4% of total pond area, forming a continuous belt along coastal zones and major river plains. Temporally, the total pond area expanded from 17,280.59 km2 in 2015 to 18,968.79 km2 in 2020, followed by a modest decline to 18,110.83 km2 in 2025, indicating a shift from rapid expansion towards more regulated development. CN-AAP10 enables robust monitoring of aquaculture dynamics and offers a data foundation for sustainable aquaculture management, wetland conservation, and carbon emission assessments.