Labeled SAR imagery dataset of ten geophysical phenomena from Sentinel-1 wave mode (TenGeoP-SARwv)

the tengeop-sarwv dataset is established based on the acquisitions of sentinel-1a wave mode (wv) in vv polarization. this dataset consists of more than 37,000 sar vignettes divided into ten defined geophysical categories, including both oceanic and meteorologic features. these images cover the entire open ocean and are manually selected from sentinel-1a wv acquisitions in 2016. for each image, only one prevalent geophysical phenomena with its prescribed signature and texture is selected for labeling. the sar images are processed into a quick-look image provided in the formats of png and geotiff as well as the associated labels. they are convenient for both visual inspection and machine-learning-based methods exploitation. the proposed dataset is the first one involving different oceanic or atmospheric phenomena over the open ocean. it seeks to foster the development of strategies or approaches for massive ocean sar image analysis. a key objective is to allow exploiting the full potential of sentinel-1 wv sar acquisitions, which are about 60,000 images per satellite per month and freely available. such a dataset may be of value to a wide range of users and communities in deep learning, remote sensing, oceanography, and meteorology

本数据集——Tengeop-SARWV，系基于Sentinel-1A波模式（WV）在垂直极化（VV）下的采集数据构建而成。该数据集包含超过37,000幅合成孔径雷达（SAR）图像片段，并根据十种定义明确的地球物理类别进行划分，涵盖海洋与气象特征。这些图像覆盖了整个公海区域，并从2016年Sentinel-1A WV采集数据中人工选取。对于每一幅图像，仅选取一种具有特定特征与纹理的显著地球物理现象进行标注。SAR图像经过处理，生成可供快速查看的图像，并支持PNG和GeoTIFF格式，同时提供相应的标签。这些图像既便于视觉检查，也便于基于机器学习的方法进行利用。本数据集是首个涉及公海区域不同海洋或大气现象的数据集，旨在促进大规模海洋SAR图像分析策略或方法的发展。其核心目标在于充分利用Sentinel-1 WV SAR采集数据的全潜能，该数据量约为每颗卫星每月约60,000幅图像，且资源免费。此类数据集对于深度学习、遥感、海洋学和气象学等多个领域和用户群体具有重要价值。

搜集汇总

背景与挑战

背景概述

TenGeoP-SARwv数据集是基于Sentinel-1A波模式（WV）VV极化获取的SAR图像，包含37,000多个标记图像片段，涵盖十个地球物理类别。这些图像适用于机器学习和视觉检查，旨在促进海洋SAR图像分析的发展。