2026-10-14T15:22:23Z https://www.scidb.cn/oai

10.57760/sciencedb.19897 2025-01-16T15:07:47Z

2025-01-16 HSR-FP-SEG doi:10.57760/sciencedb.19897 en We provide an open-access and well-annotated sample dataset for semantic segmentation of floatable plastics along Beijing-Shanghai high-speed railway of China, HSR-FP-SEG, which includes three categories of plastic mulching films, plastic greenhouses, plastic dust-proof nets.The VHR satellite imagery used is derived from Google Earth at 18-level with a spatial resolution of 1 m/pixel. Before labelling, all the VHR images are cropped into 512×512 patches. LabelImg was used for the pixel-wise annotation of all the floatable plastics. Meanwhile, the ratio of plastic mulching films, plastic greenhouses and plastic dust-proof nets is set to be 1:1:1, each with 500 samples and resulting in a total of 1,500 samples. Afterwards, the total sample dataset is split into training set, validation set and test set with a ratio of 7:1:2. Remote sensing; semantic segmentation; deep learning; high-speed railway; floatable plastics Yuan Shiying Ouyang Yu Feng Quanlong Niu Bowen Yin Gaofei Liu Jiantao Yang Jianyu PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank