YRD_PV_2025: the spatial distribution of solar photovoltaic installation dataset across the Yangtze River Delta, China in 2025

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

Solar energy is the most common renewable energy source that is clean, safe, and inexhaustible. Photovoltaic (PV) technology utilizes solar panels to convert solar energy into electricity. The number of PV installations has rapidly increased worldwide. In this study, we employed the random forest classifier to detect potential PV areas on the Google Earth Engine (GEE) platform, and then used the SAM_LoRA method on high-resolution satellite tile images for fine-grained extraction and boundary refinement of each PV, in the study area of Yangtze River Delta (YRD) region in 2025. Validation analysis revealed that the resulting dataset achieved an overall accuracy over 98%. "YRD_PV_2025" contains the specific location as well as the size of each PV installation across the Yangtze River Delta in 2025. It includes the location, size, and perimeter of each PV installation. It also specifies the province/municipality where each PV is installed and whether it is located in urban or rural areas. The dataset is delivered in “ESRI Shapefile” formats in WGS-84 coordinate system. The attributes table of the PV polygons includes the area (km²) and perimeter (km) of each PV, the name of province this PV locates, the major_type of each PV installation, the latitude and longitude coordinates of the centre point in each PV installation, as well as whether this PV is located in urban or rural areas (indicated by the urban field, where 1 represents urban and 0 represents rural). Users can employ our YRD_PV_2025 dataset in (1) analysing the spatial patterns of PV installation across the Yangtze River Delta and in different administrative provinces; (2) analysing the spatial patterns of PV installation over different land cover and land use types; (3) collecting PV samples to train a deep learning model; (4) estimating the generated electricity and carbon mitigation effect from solar PV; (5) evaluating the environmental impact of PV on hydrology and local climate.

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