China-PMF-10: a 10-m national map of plastic-mulched farmlands in China of 2020 using deep semantic segmentation

We provide China-PMF-10, which is the first remote sensing classification dataset for national-scale plastic-mulched farmlands (PMFs) of China in 2020 derived from Sentinel-2. To produce this dataset, we firstly organized 1°×1° grids covering cropland within the national extent. We then acquired pre-processed multi-temporal Sentinel-2 imagery via Google Earth Engine (GEE) and applied a random forest model to generate initial weak labels for deep learning training. Next, we integrated the active learning strategy and deep learning model to refine weak labels, enhance model robustness, and reduce false positives. Using the trained deep learning model, we mapped the national distribution of PMFs, producing the China-PMF-10 dataset with a high resolution of 10 meters. It shows that the estimated total PMFs area of China is about 67,000 km² in 2020. Validation indicates a high overall accuracy of about 86%. As the first publicly available spatial distribution dataset of China’s plastic-mulched farmlands, China-PMF-10 provides valuable data reference for agriculture, land use, remote sensing and environmental sciences researchers.