Dataset for “A Hausdorff-Guided Deep Learning Approach for Monitoring the Motion of Rotating Arctic Ice Floes”

Data for the manuscript submitted to GIScience & Remote Sensing entitled “A Hausdorff-Guided Deep Learning Approach for Monitoring the Motion of Rotating Arctic Ice Floes.”

This dataset is specifically curated to support the submission and reproducibility of the above-mentioned manuscript. It provides a comprehensive collection of data covering the full experimental pipeline, including source data, intermediate processing results, comparative experiments, and final outputs.

The dataset is organized into five folders, which systematically document the workflow of the study from raw data to experimental results:
Source Data:
This folder contains 226 multi-temporal Arctic ice floe images used as training data for the deep learning framework proposed in the manuscript.

Ice Floe Data for the Experiment:
This folder includes both the original ice floe imagery and the preprocessed data used in the experiments, reflecting the data preparation procedures applied in the study.

Extraction and Matching Results of Traditional Methods for Ice Floe Monitoring:
This folder presents the feature extraction and matching results obtained using traditional methods, including SIFT and A-KAZE. These results serve as baseline comparisons for evaluating the proposed approach.

Experimental Results:
This folder contains the motion monitoring results of ice floes between consecutive days, as well as vector maps illustrating short-term continuous motion trajectories of ice floes.

Influence of Ice Floe Rotation on Deep-Model Matching:
This folder includes partial spatial visualization results of ice floes under controlled rotations (72 rotations with a 5° interval), along with quantitative analyses demonstrating the impact of different rotation steps on matching accuracy.

The dataset supports the development, validation, and comparative analysis of the proposed Hausdorff-guided deep learning framework for detecting feature points and estimating the motion of rotating ice floes under complex Arctic marginal ice zone conditions.