Terrestrial lidar data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã
<p>Title<br> -----</p> <p>Terrestrial lidar data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã</p> <p>Authors<br> -------</p> <p>A. Burt<br> M. Boni Vicari<br> A. C. L. da Costa<br> I. Coughlin<br> P. Meir<br> L. Rowland<br> M. Disney</p> <p>Contact<br> -------</p> <p>a.burt@ucl.ac.uk</p> <p>License<br> -------</p> <p>These data are distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC BY 4.0) - see the LICENSE file for details.</p> <p>Overview<br> --------</p> <p>Terrestrial lidar data were acquired from four large tropical rainforest trees prior to harvest (diameter range: 0.6-1.2m, height range: 30-46m) in a natural closed forest stand in Floresta Nacional de Caxiuanã, Pará, Brazil (approx. coordinates in the WGS-84 datum: -1.798, -51.435 degrees), during August/October 2018.<br> This dataset includes: i) raw lidar data, ii) tree-level point clouds, and iii) quantitative structural models.<br> A complete description of the four trees, these data, and the companion destructive harvest data can be found in our paper entitled: ‘New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar’.</p> <p>Acquisition<br> -----------</p> <p>Neighbouring vegetation surrounding each tree was removed before data collection.<br> Lidar data were acquired using a RIEGL VZ-400 terrestrial laser scanner.<br> A minimum of 16 scans (upright and tilt) were collected from 8 scan positions around each tree.<br> The angular step between sequentially fired pulses was 0.04 degrees, and the distance between scanner and tree varied.<br> This arrangement provided a 45 degree sampling arc around each tree, and a complete sample of the scene from each position.<br> The laser pulse has a wavelength of 1550nm, a beam divergence of 0.35mrad, and the diameter of the footprint at emission is 7mm.<br> The instrument was in ‘High Speed Mode’ (pulse repetition rate: 300kHZ), ‘Near Range Activation’ was off (minimum measurement range: 1.5m), and waveforms were not stored. </p> <p>Processing<br> ----------</p> <p>i) Individual scans were registered onto a common coordinate system using RIEGL RiSCAN PRO (v2.7.0, http://riegl.com).<br> ii) Tree-level point clouds were extracted from the larger-area point cloud using treeseg (v0.2.0, https://github.com/apburt/treeseg).<br> iii) Points were classified as returns from wood or leaf material using TLSeparation (v1.2.1.5, https://github.com/TLSeparation).<br> iv) Points from buttresses were manually removed using CloudCompare (v2.10.3, https://cloudcompare.org).<br> v) Quantitative structural models were constructed using TreeQSM (v2.3.2, https://github.com/InverseTampere/TreeQSM) via optqsm (v0.1.0, https://github.com/apburt/optqsm). </p> <p>File and directory naming convention<br> ------------------------------------</p> <p>The four trees are identified: CAX-H_T1, CAX-H_T2, CAX-H_T3 and CAX-H_T4.<br> The various files and directories are described as follows: </p> <p>./CAXH-H/<br> ├───CAX-H_T1/ (Directory: tree-level directories)<br> ├───CAX-H_T2/<br> ├───CAX-H_T3/<br> ├───CAX-H_T4/<br> │ ├───2018-10-06.001.riproject/<br> │ │ ├───ScanPos001/ (Directory: individual scan directories containing raw lidar data and other auxiliary files; odd: upright, even: tilt)<br> │ │ ├───ScanPos.../<br> │ │ ├───ScanPos020/<br> │ │ │ ├───181006_194253.rxp (File: measurement data stream)<br> │ │ │ ├───181006_194253.mon.rxp (File: monitoring data stream) <br> │ │ ├───matrix/ (Directory: contains the registration matrices)<br> │ │ │ ├───001.dat<br> │ │ │ ├───....dat<br> │ │ │ ├───020.dat (File: 3x4 matrix used to rotate and translate scan 20 into the coordinate system of scan 1)<br> │ │ ├───clouds/ (Directory: contains tree-level point clouds)<br> │ │ │ ├───CAXH_T4.txt (File: point cloud of CAX-H_T4 as extracted by treeseg)<br> │ │ │ ├───CAXH_T4nb.txt (File: CAXH_T4.txt with buttress points manually removed using CloudCompare)<br> │ │ │ ├───CAXH_T4w.txt (File: CAXH_T4.txt with leafy returns removed using TLSeparation)<br> │ │ │ ├───CAXH_T4l.txt (File: CAXH_T4.txt with woody returns removed using TLSeparation)<br> │ │ │ ├───CAXH_T4wnb.txt (File: CAXH_T4.txt with buttress points manually removed using CloudCompare, and leafy returns removed using TLSeparation)<br> │ │ ├───models/ (Directory: contains quantitative structural models constructed from the tree-level point clouds)<br> │ │ │ ├───CAXH_T4.mat (File: quantitative structural model of CAXH_T4.txt)<br> │ │ │ ├───CAXH_T4nb.mat<br> │ │ │ ├───CAXH_T4w.mat<br> │ │ │ ├───CAXH_T4wnb.mat<br> │ │ │ ├───CAXH_T4.models.dat (File: reports the volume (m3) and standard deviation (m3) of the QSMs)<br> │ │ │ ├───intermediate/ (Directory: contains intermediate QSMs generated by optqsm)<br> │ │ │ │ ├───CAXH_T4/<br> │ │ │ │ ├───CAXH_T4nb/<br> │ │ │ │ ├───CAXH_T4w/<br> │ │ │ │ ├───CAXH_T4wnb/<br> │ │ │ │ │ ├───CAXH_T4wnb-1.mat<br> │ │ │ │ │ ├───CAXH_T4wnb-....mat<br> │ │ │ │ │ ├───CAXH_T4wnb-10.mat</p>
ShareScore
28/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 0