Multi-satellite Burned Area Change Detection Dataset (Pre-fire Sentinel-2 and Landsat-8; Post-fire PlanetScope)

This dataset is designed for burned area change detection using multi-satellite imagery, including PlanetScope (PS), Landsat-8 (L8), and Sentinel-2 (S2). The dataset is organized into two main subsets: a patch-wise dataset and a region-wise dataset. 1) Patch-wise dataset The patch-wise dataset consists of multiple configurations:- PS_RGB_L8_RGB (Pre-fire Landsat-8, Post-fire PlanetScope)- PS_RGB_S2_RGB (Pre-fire Sentinel-2, Post-fire PlanetScope)- PS_RNG_L8_RNG (Pre-fire Landsat-8, Post-fire PlanetScope)- PS_RNG_S2_8_RNG (Pre-fire Sentinel-2, Post-fire PlanetScope)- PS_RNG_S2_8a_RREG (Pre-fire Sentinel-2, Post-fire PlanetScope) Each configuration contains three splits: train, val, and test. 2) Region-wise dataset The region-wise dataset also consists of multiple configurations:- PS_RNG_L8_RNG (Pre-fire Landsat-8, Post-fire PlanetScope)- PS_RNG_S2_8_RNG (Pre-fire Sentinel-2, Post-fire PlanetScope)- PS_RNG_S2_8a_RREG (Pre-fire Sentinel-2, Post-fire PlanetScope) Each configuration contains five regions in Korea and is divided into train, val, and test splits. Across all subsets, the data are structured as paired pre- and post-fire images with corresponding ground truth masks:- A: pre-fire images - B: post-fire images - label: corresponding ground truth masks for burned areas All images are provided as cropped samples for model training and evaluation. The dataset supports both change detection and semantic segmentation tasks. For change detection, models can utilize paired inputs (A and B) with the corresponding labels. For semantic segmentation, models can be trained using post-fire images (B) and the corresponding ground truth labels.本数据集专为利用多卫星影像开展过火区域变化检测任务设计，涵盖PlanetScope（PS）、陆地卫星8号（Landsat-8，缩写L8）以及哨兵2号（Sentinel-2，缩写S2）三类卫星影像。 数据集分为两大核心子集：切块式数据集（patch-wise dataset）与区域式数据集（region-wise dataset）。 1) 切块式数据集 该数据集包含多种配置组合： - PS_RGB_L8_RGB：火灾前陆地卫星8号影像、火灾后PlanetScope影像 - PS_RGB_S2_RGB：火灾前哨兵2号影像、火灾后PlanetScope影像 - PS_RNG_L8_RNG：火灾前陆地卫星8号影像、火灾后PlanetScope影像 - PS_RNG_S2_8_RNG：火灾前哨兵2号影像、火灾后PlanetScope影像 - PS_RNG_S2_8a_RREG：火灾前哨兵2号影像、火灾后PlanetScope影像 每种配置均划分为训练集、验证集与测试集三个子集。 2) 区域式数据集 该数据集同样涵盖多种配置组合： - PS_RNG_L8_RNG：火灾前陆地卫星8号影像、火灾后PlanetScope影像 - PS_RNG_S2_8_RNG：火灾前哨兵2号影像、火灾后PlanetScope影像 - PS_RNG_S2_8a_RREG：火灾前哨兵2号影像、火灾后PlanetScope影像 每种配置涵盖韩国境内的五个区域，并划分为训练集、验证集与测试集三个子集。 所有子集内的数据均采用配对的火灾前、火灾后影像及对应地面真值掩膜的结构组织： - A：火灾前影像 - B：火灾后影像 - label：对应过火区域的地面真值掩膜 所有影像均以裁剪样本的形式提供，用于模型训练与评估。 本数据集同时支持变化检测与语义分割两类任务。针对变化检测任务，模型可利用配对输入（A与B）及对应标签开展训练与推理；针对语义分割任务，模型可通过火灾后影像（B）及对应地面真值标签进行训练。