cross-scene hyperspectral image datasets
收藏DataCite Commons2024-12-30 更新2025-04-16 收录
下载链接:
https://ieee-dataport.org/documents/cross-scene-hyperspectral-image-datasets
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资源简介:
1) RPaviaU-DPaviaC Dataset: The RPaviaU-DPaviaC dataset is constructed by amalgamating two publicly accessible HSI datasets: the ROSIS Pavia University (RPaviaU) scene and the DAIS Pavia Center (DPaviaC) scene. The RPaviaU dataset, featuring dimensions of 610 × 340 × 103, was acquired by the ROSIS HSI sensor over the terrain of the University of Pavia, Italy. Conversely, the DPaviaC dataset, with dimensions of 400 × 400 × 72, was collected using the DAIS sensor over the central area of Pavia City, Italy. These two scenes share a common set of seven land cover classes. 2) EHangzhou-RPaviaHR Dataset: The EHangzhou-RPaviaHR dataset encompasses two distinctive scenes: the EO-1 Hangzhou (EHangzhou) scene and the ROSIS Pavia HR (RPaviaHR) scene. The EHangzhou scene, sourced from the EO-1 Hyperion hyperspectral sensor, was obtained over Hangzhou City, Zhejiang, China, and possesses dimensions of 590 × 230 × 198. In contrast, the target scene, RPaviaHR, was captured using the ROSIS HSI sensor over Pavia city, Italy, and is characterized by dimensions of 1400 × 512 × 102. These two scenes share a common subset of three land cover classes.
1) RPaviaU-DPaviaC 数据集:该数据集由两份公开可获取的高光谱(Hyperspectral Imagery, HSI)数据集融合构建而成,分别为ROSIS帕维亚大学场景(ROSIS Pavia University, RPaviaU)与DAIS帕维亚市中心场景(DAIS Pavia Center, DPaviaC)。其中RPaviaU数据集尺寸为610×340×103,由ROSIS高光谱传感器在意大利帕维亚大学校园区域采集获取;DPaviaC数据集尺寸为400×400×72,由DAIS传感器在意大利帕维亚市中心区域采集得到。这两个场景共享7类共同的土地覆盖类别。
2) EHangzhou-RPaviaHR 数据集包含两个特色场景:EO-1杭州场景(EO-1 Hangzhou, EHangzhou)与ROSIS帕维亚高分辨率场景(ROSIS Pavia HR, RPaviaHR)。其中EHangzhou场景源自EO-1 Hyperion高光谱传感器,于中国浙江省杭州市上空采集,尺寸为590×230×198;目标场景RPaviaHR由ROSIS高光谱传感器在意大利帕维亚市上空采集,尺寸为1400×512×102。这两个场景共享3类共同的土地覆盖类别。
提供机构:
IEEE DataPort创建时间:
2024-12-30
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集是一个用于跨场景高光谱图像分类的标准遥感数据集,包含两个子数据集:RPaviaU-DPaviaC和EHangzhou-RPaviaHR。每个子数据集由两个不同地理区域(如意大利帕维亚和中国杭州)采集的高光谱图像场景组成,具有不同的传感器、尺寸和光谱波段,但共享部分相同的土地覆盖类别,旨在支持跨场景的模型训练与评估研究。
以上内容由遇见数据集搜集并总结生成



