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3 results for “Tree Sway”
Video and accelerometer tree sway data for two ponderosa pine trees in the Manitou Experimental Forest, Colorado
<p>This repository includes video, accelerometer, and sway frequency data for two ponderosa pine trees (Pinus ponderosa, PIPO) in the Manitou Experimental Forest in Colorado. Video and accelerometer samples were selected from data recorded between May and September 2020. Sway frequency data for both trees was extracted from both video and accelerometer data using the methods described in Ammatelli et al. (In review).</p> <p>All times are in Mountain Daylight Time.</p> <p><strong>Video Data </strong></p> <p>The three, 30 s videos were recorded using a video camera attached to the top of a nearby tower. </p> <p>Video camera: GoPro camera, 30 fps, 1080p resolution, 155° FOV</p> <p>Approximate pixel bounding boxes (ymin, ymax, xmin, xmax):</p> <ol> <li>Tree 1: (440, 520, 395, 425)</li> <li>Tree 2: (400, 575, 690, 760)</li> </ol> <p>File naming convention: manitou-X.MP4 where X the video ID (a,b,c)</p> <p>Date and time</p> <ul> <li>manitou-a.MP4 (2020-8-15 12:05:58)</li> <li>manitou-b.MP4 (2020-8-20 17:28:9)</li> <li>manitou-c.MP4 (2020-8-31 11:50:20)</li> </ul> <p><strong>Accelerometer Data</strong></p> <p>Accelerometer data for both trees was recorded using a 3-axis accelerometer. The accelerometers were positioned ~6-8 m above the ground (total tree height ~8-10 m).</p> <p>Accelerometer: Gulf Coast Data Concepts 2g MEL-X2,16 Hz continuous sampling</p> <p>File naming convention: manitou_accelerometer_X_treeY.csv where X is the video ID (a,b,c) and Y is the tree number (1,2)</p> <p>Variables:</p> <ol> <li>datetime - time of acceleration sample (MDT)</li> <li>Ax - raw acceleration along X-axis of sensor</li> <li>Ay - raw acceleration along Y-axis of sensor</li> <li>Az - raw acceleration along Z-axis of sensor</li> </ol> <p><strong>Sway Frequency Data</strong></p> <p>For each video and tree, 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.</p> <p>File naming convention: manitou_sway_treeY.csv where Y is the tree number (1,2)</p> <p>Variables:</p> <ol> <li>name - name of video sample</li> <li>datetime - start time of video sample</li> <li>vvs_avg_hz - frequency (Hz) of tree extracted using VVS method with average spectrum aggregation</li> <li>vvs_hist_hz - frequency (Hz) of tree extracted using VVS method with peak frequency histogram aggregation</li> <li>acc_30sec_hz - frequency (Hz) of tree extracted from an accelerometer segment with the same start time and duration as the video</li> <li>acc_30min_hz - frequency (Hz) of tree extracted from a 30-minute accelerometer segment centered on the video start time</li> </ol> <p>See the below paper for more information.</p> <p>Bush, S. A. (2022). Ecohydrologic Processes in the Montane Headwaters of the Upper South<br> Platte River (Doctoral dissertation). Retrieved from ProQuest Dissertations Publishing. (cub.b12869881). Boulder, CO: University of Colorado at Boulder.</p>
Video and accelerometer tree sway data for an oak tree in Trout Lake, Wisconsin
<p>This repository includes video, accelerometer, and sway frequency data for a red oak tree (Quercus rubra) in the Trout Lake Watershed in northern Wisconsin. Video and accelerometer data were recorded on 15 August 2019. Sway frequency data was extracted from both video and accelerometer data using the methods described in Ammatelli et al. (In review).</p> <p>All times are in Central Daylight Time.</p> <p><strong>Video Data </strong></p> <p>The five, 60 s videos were recorded using a video camera fastened with straps to the base of an adjacent tree.</p> <p>Video camera: Bushnell TrophyCam, 30 fps, 1080p resolution, 45° FOV</p> <p>File naming convention: trout-X.MP4 where X (a,b,c,d,e) is the video ID</p> <p>Date and time</p> <ul> <li>trout-a.MP4 (2019-8-15 17:07:18)</li> <li>trout-b.MP4 (2019-8-15 17:30:01)</li> <li>trout-c.MP4 (2019-8-15 17:32:34)</li> <li>trout-d.MP4 (2019-8-15 18:00:01)</li> <li>trout-e.MP4 (2019-8-15 18:09:06)</li> </ul> <p><strong>Accelerometer Data</strong></p> <p>Accelerometer data for the same tree was recorded using a 3-axis accelerometer. The accelerometer was positioned beneath the main branching of the target tree at ~8 m (total tree height ~22 m). </p> <p>Accelerometer: Gulf Coast Data Concepts 2g MEL-X2,16 Hz continuous sampling</p> <p>Filename: trout_accelerometer.csv</p> <p>Variables:</p> <ol> <li>datetime index (in CDT)</li> <li>acc - single‐axis acceleration filtered through a low‐pass filter from 0.01 to 2 Hz</li> </ol> <p><strong>Sway Frequency Data</strong></p> <p>For each video, 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.</p> <p>Filename: trout_sway.csv</p> <p>Variables:</p> <ol> <li>name - name of video sample</li> <li>datetime - start time of video sample</li> <li>vvs_avg_hz - frequency (Hz) of tree extracted using VVS method with average spectrum aggregation</li> <li>vvs_hist_hz - frequency (Hz) of tree extracted using VVS method with peak frequency histogram aggregation</li> <li>mbt_avg_hz - frequency (Hz) of tree extracted using MBT method with average spectrum aggregation</li> <li>acc_60sec_hz - frequency (Hz) of tree extracted from an accelerometer segment with the same start time and duration as the video</li> <li>acc_30min_hz - frequency (Hz) of tree extracted from a 30-minute accelerometer segment centered on the video start time</li> </ol>
When the trees sway: 木が揺れるとき 作:山崎良太
This work was exhibited at the "Ueno Onshi Koen Art Walkway 2020" in Ueno Park, Tokyo, Japan.From above, there is a hole. A human figure is dug in the back. 日本の東京,上野公園で開催されている「上野恩賜公園芸術の散歩道2020」の展示作品です。上から見ると穴が空いています。背後には人型が掘られています。 Made with [Scaniverse](https://scaniverse.com). Source: Objaverse 1.0 / Sketchfab
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