Downloads provided by UsageCounts
Title ----- Terrestrial lidar data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã Authors ------- A. Burt M. Boni Vicari A. C. L. da Costa I. Coughlin P. Meir L. Rowland M. Disney Contact ------- a.burt@ucl.ac.uk License ------- 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. Overview -------- 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. This dataset includes: i) raw lidar data, ii) tree-level point clouds, and iii) quantitative structural models. 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’. Acquisition ----------- Neighbouring vegetation surrounding each tree was removed before data collection. Lidar data were acquired using a RIEGL VZ-400 terrestrial laser scanner. A minimum of 16 scans (upright and tilt) were collected from 8 scan positions around each tree. The angular step between sequentially fired pulses was 0.04 degrees, and the distance between scanner and tree varied. This arrangement provided a 45 degree sampling arc around each tree, and a complete sample of the scene from each position. The laser pulse has a wavelength of 1550nm, a beam divergence of 0.35mrad, and the diameter of the footprint at emission is 7mm. 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. Processing ---------- i) Individual scans were registered onto a common coordinate system using RIEGL RiSCAN PRO (v2.7.0, http://riegl.com). ii) Tree-level point clouds were extracted from the larger-area point cloud using treeseg (v0.2.0, https://github.com/apburt/treeseg). iii) Points were classified as returns from wood or leaf material using TLSeparation (v1.2.1.5, https://github.com/TLSeparation). iv) Points from buttresses were manually removed using CloudCompare (v2.10.3, https://cloudcompare.org). 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). File and directory naming convention ------------------------------------ The four trees are identified: CAX-H_T1, CAX-H_T2, CAX-H_T3 and CAX-H_T4. The various files and directories are described as follows: ./CAXH-H/ ├───CAX-H_T1/ (Directory: tree-level directories) ├───CAX-H_T2/ ├───CAX-H_T3/ ├───CAX-H_T4/ │ ├───2018-10-06.001.riproject/ │ │ ├───ScanPos001/ (Directory: individual scan directories containing raw lidar data and other auxiliary files; odd: upright, even: tilt) │ │ ├───ScanPos.../ │ │ ├───ScanPos020/ │ │ │ ├───181006_194253.rxp (File: measurement data stream) │ │ │ ├───181006_194253.mon.rxp (File: monitoring data stream) │ │ ├───matrix/ (Directory: contains the registration matrices) │ │ │ ├───001.dat │ │ │ ├───....dat │ │ │ ├───020.dat (File: 3x4 matrix used to rotate and translate scan 20 into the coordinate system of scan 1) │ │ ├───clouds/ (Directory: contains tree-level point clouds) │ │ │ ├───CAXH_T4.txt (File: point cloud of CAX-H_T4 as extracted by treeseg) │ │ │ ├───CAXH_T4nb.txt (File: CAXH_T4.txt with buttress points manually removed using CloudCompare) │ │ │ ├───CAXH_T4w.txt (File: CAXH_T4.txt with leafy returns removed using TLSeparation) │ │ │ ├───CAXH_T4l.txt (File: CAXH_T4.txt with woody returns removed using TLSeparation) │ │ │ ├───CAXH_T4wnb.txt (File: CAXH_T4.txt with buttress points manually removed using CloudCompare, and leafy returns removed using TLSeparation) │ │ ├───models/ (Directory: contains quantitative structural models constructed from the tree-level point clouds) │ │ │ ├───CAXH_T4.mat (File: quantitative structural model of CAXH_T4.txt) │ │ │ ├───CAXH_T4nb.mat │ │ │ ├───CAXH_T4w.mat │ │ │ ├───CAXH_T4wnb.mat │ │ │ ├───CAXH_T4.models.dat (File: reports the volume (m3) and standard deviation (m3) of the QSMs) │ │ │ ├───intermediate/ (Directory: contains intermediate QSMs generated by optqsm) │ │ │ │ ├───CAXH_T4/ │ │ │ │ ├───CAXH_T4nb/ │ │ │ │ ├───CAXH_T4w/ │ │ │ │ ├───CAXH_T4wnb/ │ │ │ │ │ ├───CAXH_T4wnb-1.mat │ │ │ │ │ ├───CAXH_T4wnb-....mat │ │ │ │ │ ├───CAXH_T4wnb-10.mat
tropical forests, terrestrial lidar, allometry, destructive harvest, tree structure, above-ground biomass
tropical forests, terrestrial lidar, allometry, destructive harvest, tree structure, above-ground biomass
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 56 | |
| downloads | 35 |

Views provided by UsageCounts
Downloads provided by UsageCounts