Particularly, in China, the number and scale of photovoltaic (PV) power stations have grown unprecedentedly in the last decade. There is an urgent need to monitor the PV power development in order to accurately estimate national renewable potentials and understand the ecological impacts.
Land used for PV power stations were mainly converted from Gobi desert, sandy land, sparse and moderate grassland. The focus of China’s PV industry is shifting from the northwest to the south and east. Many leading countries are boosting renewables, especially solar energy, as a major way to mitigate future energy crises and climate change.
The tool shows China ground mounted solar facilities occupied a surface of 2,467.7 km2 at the end of December 2020. Scientists led by the China Agricultural University have created a national-scale map and dataset of ground-mounted PV power stations in China.
We provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy.
To fill the gap, this study proposes an integrated remote sensing approach for PV power stations mapping by combining image segmentation and object-based classification (ISOC) techniques. We took five northwestern provinces of China as an illustration and produced 30-m medium-resolution PV power station distribution maps from 2007 to 2019.
According to our dataset, China has a total of 2467.7 km 2 ground-mounted PV power stations in 2020. The top three largest provinces refer to Xinjiang, Inner Mongolia and Qinghai, whose PV area ratio are 14.92%, 12.49% and 11.26%, respectively, with a total of nearly 40% of all the PV power stations of China.