# Mapping Aquaculture Ponds for the Coastal Zone of Asia with Sentinel-1 and Sentinel-2 Time Series
## 6 Conclusions  
A novel continental-scale mapping approach was developed to detect and assess pond aquaculture for the entire coastal zone of Asia using multi-sensor Earth observation time series. In this study, we used all available satellite data acquired by the high-resolution C-band imaging radar mission Sentinel-1 and the multispectral Sentinel-2 mission, and we calculated time series metrics to detect pond aquaculture objects. We processed more than 25,000 Sentinel-1 dual-polarized IW GRDH images, generated a temporal median image, and applied image segmentation using histogram-based thresholding to automatically detect and extract pond aquaculture on a single-pond-unit basis. The derived object-based pond units were enriched with multispectral time series information (Sentinel-2), topographic terrain information, geometric features information, and supplementary overlap analysis with global surface water data in order to extract aquaculture ponds in potential low-lying coastal areas and separate them from other natural or artificial water bodies. More than 3.4 million aquaculture ponds with a total area of more than 2 million ha were detected and mapped for a 200-km-wide buffer zone along the shoreline of South Asia, Southeast Asia, and East Asia. Spatial analyses show that aquaculture is clearly concentrated near the coast; 45 percent of the mapped ponds are located within a radius of 5 km from the coast. For each country, we summarized the total area of the mapped coastal pond aquaculture at national level and sub-national level. China accounts for the largestshare of coastal pond aquaculture: 41 percent of the total Earth-observation-derived pond aquaculture area is in China, followed by Indonesia (13 percent), India (11 percent), Vietnam (7 percent), and Thailand (7 percent). The study region covers the coastal areas of 22 Asian countries, which altogether contribute more than 87 percent to the total global annual aquaculture production, representing the world's focus in terms of aquaculture relevance. The results show that we mapped coastal aquaculture at single-pond-level with a mean average overall accuracy of 91 percent. For the first time, satellite remote sensing was used for the comprehensive assessment of coastal aquaculture at a continental scale, covering a shoreline of more than 300,000 km.  
Conceptualization, M.O., F.B., J.H., C.K.; methodology, M.O., C.K.; validation, M.O.; data analysis, M.O.; writing--original draft preparation, M.O.; writing--review and editing, M.O., F.B., J.H., C.K.; visualization, M.O. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors would like to thank [PERSON] for her support in the statistical data analysis and accuracy assessment and [PERSON] for his support in the object feature generation and OSM analysis. Special thanks go to the Copernicus Satellite Program for providing free access to the global Sentinel-1 and Sentinel-2 data; the NASA JPL for providing the free SRTM version 3 dataset; the Open Street Map project for providing free data on waterbodies and shorelines; and GADM for providing data on administrative areas. Furthermore, we would like to thank the Google Earth Engine platform for generating and providing the satellite time series, and we would also like to thank [PERSON] for the thresholding script available in GEE. Finally, we would like to thank the FAO for providing updated global aquaculture statistics.  
The authors declare no conflict of interest.