An Image Dataset for Training Deep Learning Segmentation Models to Identify Karst Sinkholes

The image dataset was prepared for training deep learning image segmentation models to identify karst sinkholes. Information about the work can be found at (https://github.com/mvrl/sink-seg/). The dataset consists of a DEM image, an aerial image, and a binary sinkhole label image in an area in central Kentucky, USA. It also includes four images derived from the DEM image. The image dataset is sourced from publicly available data from Kentucky's Elevation Data & Aerial Photography Program (https://kyfromabove.ky.gov/) and Kentucky LiDAR-derived sinkholes (https://kgs.uky.edu/geomap).

本图像数据集专为训练用于识别喀斯特塌陷坑（karst sinkholes）的深度学习图像分割模型而构建。有关该数据集的详细信息可访问链接：https://github.com/mvrl/sink-seg/。本数据集包含美国肯塔基州中部某区域的数字高程模型（Digital Elevation Model, DEM）图像、航空影像以及二值化塌陷坑标注图像，同时还包含4张由该DEM图像衍生得到的图像。本数据集的数据源来自肯塔基州高程数据与航空摄影项目（https://kyfromabove.ky.gov/）以及肯塔基州基于激光雷达（Light Detection and Ranging, LiDAR）生成的塌陷坑公开数据（https://kgs.uky.edu/geomap）。