Video-Based Optical Flow Dataset and Python Workflow for Mapping Flow Activity on the Experimental Alluvial Fan

This archive contains the video-based optical flow dataset and processing script used to quantify flow activity on the experimental alluvial fan at one-minute temporal resolution. Each one-minute video consists of approximately 20 RGB frames captured at 3-second intervals, representing the area of the fan surface that was active during that minute. The archive includes the following components:• 01_input_OneMin_videos/Folder containing the one-minute videos used as input for the optical flow analysis. Each video captures active flow patterns across the fan surface at 3-second intervals (≈20 frames per minute).• 02_Optical_Flow_output_csv/Folder containing the resulting optical-flow magnitude rasters exported as .csv files.Each output file represents the average optical flow magnitude for a given one-minute video, computed using Farnebäck’s dense optical flow algorithm.• Opticalflow_loop.pyPython script that processes all videos in batch mode.The script:o reads each one-minute video from the input directory,o computes dense optical flow between consecutive frames,o accumulates and averages the per-pixel flow magnitude over the full minute (flow direction is ignored), ando saves the resulting magnitude field as a CSV file in the output directory.