2026-10-14T23:25:25Z https://www.scidb.cn/oai

10.57760/sciencedb.radars.00041 2025-03-31T17:53:10Z

2025-03-31 AIR-PolSAR-Seg-2.0: Polarimetric SAR Ground Terrain Classification Dataset for Large-scale Complex Scenes doi:10.57760/sciencedb.radars.00041 en The AIR-PolSAR-Seg-2.0 dataset aims to build a polarimetric SAR ground terrain classification dataset for large-scale complex scenes, promoting research and development in polarimetric synthetic aperture radar ground terrain classification within the field of SAR image interpretation. The dataset is composed of GF-3 L1A complex SAR images from three different regions, with a spatial resolution of 8 m and includes four polarimetric modes (HH, HV, VH, and VV), covering six typical ground terrain categories: water, vegetation, bareland, buildings, roads, and mountains. The dataset exhibits characteristics of complex scenes, large scale, diverse scattering intensities, irregular boundary distributions, varying category scales, and unbalanced sample distribution. Additionally, the complete SAR images of the three scenes have been cropped into 24,672 slices of 512×512 pixels to facilitate experimental verification within a deep learning framework. PolSAR; Deep Learning; Terrain Classification Wang Zhirui Zhao Liangjin Wang Yuelei Zeng Xuan Kang Jian Yang Jian Sun Xian PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank