Video tree sway data for a subalpine fir tree in Niwot Ridge, Colorado

This repository includes video and sway frequency data for a subalpine fir tree (Abies lasiocarpa) near the Niwot Ridge Long-Term Ecological Research site in Colorado. Sway frequency data for the given tree was extracted from both video and accelerometer data using the methods described in Ammatelli et al. (In review). 

All times are in Mountain Standard Time.

Video Data 

The included 53-second video was recorded by hand from an AmeriFlux tower adjacent to the target tree. The camera field of view (FOV) includes the accelerometer.

Video camera: iPhone 6, 30 fps, 1080p resolution, 63.5° FOV

Approximate pixel bounding box used for analysis (ymin, ymax, xmin, xmax): (450, 1250, 570, 760)

Filename: niwot-a.mp4

Video date and time: 2015-11-21 09:50:20

Accelerometer Data

The accelerometer data accompanying the included video data is available here: https://zenodo.org/records/5149308

Sway Frequency Data

The tree's sway frequency was extracted from the video and two lengths of accelerometer data: a segment with the same start time and duration as the video and a 30-minute segment.

Filename: niwot_sway.csv

Variables:

1. name - name of video sample
2. datetime - start time of video sample
3. vvs_avg_hz - frequency (Hz) of tree extracted using VVS method with average spectrum aggregation
4. vvs_hist_hz - frequency (Hz) of tree extracted using VVS method with peak frequency histogram aggregation
5. acc_53sec_hz - frequency (Hz) of tree extracted from an accelerometer segment with the same start time and duration as the video
6. acc_30min_hz - frequency (Hz) of tree extracted from a 30-minute accelerometer segment centered on the video start time

See the below paper for more information about the accelerometer data.

Raleigh, M. S., Gutmann, E. D., Van Stan II, J. T., Burns, S. P., Blanken, P. D., & Small, E. E.
(2022). Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies with Tree Sway Monitoring. Water Resources Research, 58, e2021WR030972. https://doi.org/10.1029/2021WR030972