Abstract: Coastal aquaculture is an important part of marine economic development and plays a vital role in food security. However, the disorderly expansion and development of coastal aquaculture has hindered maritime traffic and also caused marine environmental problems. In order to obtain coastal aquaculture data timely and accurately for the coastal zone survey and for the standardization and reasonable coastal aquaculture, this paper proposes a method based on Google Earth Engine (GEE) platform for a rapid information extraction of coastal aquaculture area in long time series. We used Sentinel-1 and Sentinel-2 satellite image data to construct an extraction model based on random forest classification, determined and extracted the coastal culture area of Pingtan county from 2017 to 2021. Experimental results show that in Pingtan County, where the aquaculture density is low and the aquaculture characteristics are not prominent, the extraction method based on GEE platform utilized in this study exhibits an accuracy rate exceeding 90%. This indicates that rapid identification of aquaculture areas amidst complex water bodies has yielded favorable outcomes, thereby offering valuable insights for scientific planning and standardized management of coastal aquaculture.