US-LandCover-Dataset

Monitoring land cover changes is essential for understanding the environmental impact of natural processes and human activities, such as deforestation, urbanization, and agriculture. We present a comprehensive dataset covering the entire United States, spanning from 2016 to 2024. This dataset integrates multi-band imagery from the Sentinel-2 satellite with pixel-level land cover annotations from the Dynamic World dataset, providing a valuable resource for land cover change detection research. The dataset is publicly available and includes six spectral bands (Red, Green, Blue, NIR, SWIR1, SWIR2) as well as labels indicating land cover types. To address the steep learning curve associated with remote sensing, we also provide accompanying code to facilitate data loading and perform basic analyses, enabling researchers to focus on their core work without being hindered by data preprocessing challenges. This dataset facilitates research in fields such as environmental monitoring, urban planning, and climate change, offering an accessible tool for understanding landscape dynamics over time.监测土地覆被变化，是理解自然过程与人类活动（如森林砍伐、城市化与农业活动）所产生环境影响的核心前提。本研究构建了一套覆盖美国全境、时间跨度为2016年至2024年的综合数据集。该数据集整合了哨兵二号卫星（Sentinel-2）的多波段影像与Dynamic World数据集（Dynamic World）的像素级土地覆被标注信息，可为土地覆被变化检测相关研究提供宝贵的数据支撑。该数据集公开可获取，包含红、绿、蓝、近红外（NIR）、短波红外1（SWIR1）、短波红外2（SWIR2）共6个光谱波段，以及标识土地覆被类型的分类标签。针对遥感领域普遍存在的入门门槛较高问题，本数据集配套提供了辅助代码，可实现数据加载与基础分析功能，帮助研究人员摆脱数据预处理的繁琐工作，专注于核心研究任务。本数据集可为环境监测、城市规划、气候变化等多个领域的研究提供支持，为时序景观动态变化的分析提供了易用的研究工具。