# Mapping Aquaculture Ponds for the Coastal Zone of Asia with Sentinel-1 and Sentinel-2 Time Series
## 5 Discussion
Aquaculture ponds generally have convex (e.g., rectangular) shapes, but sometimes they may be shaped to fit natural features (curves at rivers or terrain), which leads to concave pond shapes. Apart from the challenges of identifying single-pond aquaculture units in radar imagery, it must be made clear that SAR sensors have clear benefits over optical remote sensing instruments for continuous mapping and monitoring of aquaculture in the coastal zone. The Copernicus Sentinel satellite missions offer free access to continuous, timely, and routine Earth observation data and thus offer enormous potential for large-scale and even global assessment of coastal aquaculture. Therefore, on the one hand, our approachfor continental-scale mapping benefits from scalability through the use of the open data archives of the Sentinel-1 and Sentinel-2 satellites. These provide dense and large volumes of radar and optical imagery that can be accessed, for example, via the Google Earth Engine in preprocessed and analysis-ready data format. In our study, we make use of the analysis capabilities of Google's cloud-based computing platform to process a full annual time series of wide-swath, high-spatial-resolution SAR and optical satellite data for coastal Asia. On the other hand, the post-processing, including the statistical analysis in our study, is based on open software, tools (e.g., python packages, QGIS, GDAL libraries), and auxiliary data (e.g., FAO fishstats, Open Street Map). As a result, the workflow presented could also be adopted and integrated into other cloud computing platforms or frameworks. For the first time, satellite remote sensing was used for the comprehensive assessment of coastal pond aquaculture at continental scale for the entire coastal zone of Asia. The method presented in this study has three major advantages:  
1. a key feature of the novel, continental-scale mapping approach is the use of free and open remote sensing data; the launches of Sentinel-1C and 1D will provide data continuity and satellite-based high-resolution SAR data and enable continuous monitoring over the next decade;
2. the application of a simple and fast segmentation algorithm and scalable processing capabilities within the cloud platform provide the capacity and ability to upscale the framework and enable global mapping of coastal pond aquaculture;
3. the use of open source tools and software creates the possibility of integrating other or updated pre- and post-processing toolboxes, image processing, computer vision models, or algorithms into the framework. Information on the spatial distribution of aquaculture is necessary for spatial planners, policy makers, and ecologists in order to enable sustainable development in the coastal zone and ensure food security. Aquaculture is in conflict with other existing or foreseeable land uses, e.g., urban development, tourism, and traffic infrastructure, among others. The coastal zone provides large resources for millions of people, and sustainable management is essential for future development. Operating aquaculture facilities and the construction of new ponds for fish and shrimp farming are closely linked to freshwater management (groundwater withdrawal for pond water), waste water discharge, and other ecological challenges, such as increasing coastal erosion, land subsidence, and salinization. For this reason, there is a fundamental need for further research to investigate and analyze aquaculture and its impact on natural ecosystems at continental and global scale.