Zhuang Photovoltaic Solar Power Station

Does China have a spatial map of PV power stations?

Although some researchers released several PV power station maps, most only met a medium resolution of 30 meters 9, 10. There thus still lacks a national map of China’s PV power stations with a higher spatial resolution (i.e., 10 meters) that could provide a global understanding of PV’s spatial deployment patterns.

Can photovoltaic power stations promote China's low-carbon transition?

To promote China's low-carbon transition, the construction of photovoltaic power stations is practical in various provinces of China. Since the photovoltaic power stations can maintain 25 years, the cumulative emission reduction potentials can be quantified to measure the contribution to low-carbon transition.

Where is photovoltaic power installed in China?

In addition, the total installed photovoltaic capacities in Southwest and South China are relatively low, while the competitive patterns of photovoltaic power installation in Northeast China, including Heilongjiang and Liaoning provinces are becoming increasingly obvious.

What is the regional distribution of photovoltaic power stations in China?

In general, the regional distribution of photovoltaic power stations in China is quite different, and the regional competition patterns are variable. Provinces with high installed photovoltaic power stations and high regional competition are mainly located in Northwest and North China.

Where are the cold spots of photovoltaic installation in China?

South China and Southwest China, including Guangxi, Guangdong, Fujian and Chongqing are generally the cold spots of photovoltaic installation, with relatively small installed capacities at each stage. Fig. 3. Moran scatter of China's provincial photovoltaic installation.

What is remote sensing derived dataset for large-scale photovoltaic 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.