Drone Mapping Dataset – Summer 2023 – Sugarloaf Island, NC

This dataset includes georeferenced drone-based remote sensing data collected over Sugarloaf Island, North Carolina during <b>Summer 2023</b> as part of a multi-season shoreline monitoring program (2023–2025). Data were acquired using RTK-GNSS ground control and processed with Structure-from-Motion (SfM) photogrammetry to support coastal mapping, shoreline monitoring, and research on nature-based solutions.<br><br>The dataset contains two independently processed surveys (East and West island segments), each packaged as a zipped folder.<br><br>Each folder contains:<br>- Orthomosaics (0.7 cm resolution)<br>- Digital elevation models (DEMs, non-interpolated, 5 cm resolution)<br>- Dense point clouds and ground point clouds<br>- Drone imagery<br>- RTK-GNSS ground control points and checkpoint data<br>- Metadata and README files describing acquisition parameters, processing workflow, and accuracy metrics<br><br>These data support applications in coastal mapping, shoreline monitoring, nature-based solutions assessment, digital elevation model (DEM) generation, coastal geomorphology, shoreline change analysis, and barrier island restoration monitoring.<br><br>Recommended citation formats and use cases are provided in the included README files.

本数据集包含2023年夏季在北卡罗来纳州舒格洛夫岛（Sugarloaf Island）采集的地理参考无人机遥感数据，该数据为2023–2025年多季海岸线监测项目的组成部分。数据采集采用实时动态差分全球导航卫星系统（RTK-GNSS）地面控制点，并通过运动恢复结构（Structure-from-Motion, SfM）摄影测量法进行处理，可支持海岸制图、海岸线监测以及基于自然的解决方案相关研究。

本数据集包含两组独立处理的勘测数据，分别对应岛屿东段与西段，每组均打包为压缩文件夹。

每个压缩文件夹包含以下内容：
- 正射影像（Orthomosaics，分辨率0.7厘米）
- 数字高程模型（DEMs，未插值，分辨率5厘米）
- 密集点云与地面点云
- 无人机影像
- RTK-GNSS地面控制点与检查点数据
- 描述采集参数、处理流程与精度指标的元数据与README文件

此类数据可应用于海岸制图、海岸线监测、基于自然的解决方案评估、数字高程模型（DEM）生成、海岸地貌学研究、海岸线变化分析以及障壁岛（Barrier Island）修复监测等多个领域。

推荐的引用格式与使用场景详见附带的README文件。