2026-10-15T02:17:22Z https://www.scidb.cn/oai

10.57760/sciencedb.34604 2026-06-23T00:24:15Z

2026-06-23 High-Resolution Remote Sensing Dataset for Levee-Like Feature Segmentation in Arid Regions doi:10.57760/sciencedb.34604 en This dataset is a high-resolution remote sensing image dataset designed for segmentation of levee-like features in arid regions. The dataset includes 459 single-phase reference images at approximately 0.5-meter spatial resolution with corresponding pixel-level annotations, as well as multi-temporal images of the same areas captured at different times, totaling 1550 images. All annotations were manually drawn using the LabelMe tool in polygon mode and converted to YOLO-format label files (.txt). A spatial location-based data splitting strategy was adopted to prevent data leakage: the training set (~80%), validation set (~10%), and test set (~10%) were first divided based on single-phase images, and multi-temporal images were then assigned to corresponding subsets according to their spatial location. This dataset can support research on levee-like feature extraction, remote sensing change detection, and cross-region model transfer learning. The dataset is released under the CC BY 4.0 license. remote sensing; levee detection; arid region; multi-temporal dataset; deep learning; Semanttic segmentation Osman Ilniyaz Kaisar Ahmat EMBARGO https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank