High-resolution mapping of water photovoltaic development in China through satellite imagery

•A random forest model is developed to map Water Photovoltaic from satellite data.•Annual 10-m resolution WPV maps during 2016–2019 are generated for China.•The area of WPV in China is increasing rapidly, especially Stationary Photovoltaics.•The WPV mapping can help promote the sustainability of solar energy development. Renewable energy is crucial to address climate change and achieve carbon neutrality. Within the existing technologies, photovoltaics is one of the most promising renewable energies. However, large-scale development of photovoltaics always needs a large amount of space, competing for land with other usages. Installing photovoltaics on water surfaces such as lakes and reservoirs is one of the major solutions to solve the contradiction between photovoltaic development and land shortage. In recent years, many countries have been actively promoting the development of water photovoltaic (WPV) to reduce carbon emission and meet increased energy demand, of which China is far ahead. Mapping the spatial distribution of WPV with satellite image time series will help reveal the spatial distribution, assess the scale and future potential of national WPV development, and understand its environmental impact. However, studies and reliable spatial data on the extent and distribution of WPV are still lacking. To address this gap, we proposed a classification algorithm based on Random Forest to extract WPV features and determine the types of the WPV from the Sentinel time series. The results show that the area of WPV in China reached 165 km2 in 2019, with an average annual growth of 43.8 km2 from 2016 to 2019. Among them, Stationary Photovoltaic (SPV) accounts for 95% of the total WPV, while Floating Photovoltaic (FPV) only accounts for 5%. Based on our WPV mapping results, we estimated the installed capacity and power generation of WPV would be approximately 6911 MW and 7.8 TWh yr−1, accounting for 3.4% and 3.5% of the total cumulative installed PV capacity and total PV power generation, respectively. This study provides an efficient and robust approach for extracting WPV at a large scale. The WPV data can be a valuable supplement to official tabulate data because it contains much finer spatial information that can assist stakeholders with future WPV planning and environmental impact assessment.