Scale-dependent responses to environmental fluctuations in tropical tree species’ crown temperatures

This dataset comprises tree crown temperature and tree crown trait data for four four canopy species in Laupahoehoe forest in Hawai'i, analyzed at a "crown" and "leaf" level, as defined in the manuscript methods. Climate data were collected from the climatological station at Laupāhoehoe Forest, and here we provide the average conditions at the 5 UAV flight times.

Methods
Data here were derived from spatial orthomosaics from five UAV flights with a 20 cm2 pixel resolution were created for RGB, Thermal (°C), and lidar intensity with detailed methods described in the published manuscript.

Tree crown temperature data: 652 crowns or leaf clusters were identified to four species: 396 Metrosideros polymorpha (‘ōhi‘a lehua), 159 Acacia koa (koa), 51 Cheirodendron trigynum (ʻōlapa), and 46 Coprosma rhynchocarpa (pilo). Data were filtered to a "crown" and "leaf" level of analysis, described in detail in the manuscript, and thermal values from all remaining pixels were averaged to determine an average crown temperature at each flight time.

Tree crown trait data: For each tree crown, we extracted average height (m), calculated the coefficient of variation (CV) of crown height (the ratio of standard deviation to mean height) within each crown as a measure of leaf clumping. We used the R package “lidR” (1-3) and the function “voxel_metrics” to derive average crown densities (pts m-3) and the function “rumple_index” to calculate the rumple index (a measure of rugosity or roughness) for each crown. 

1.     R Core Team. (2023). R: A language and environment for statistical computing (Version 4.1.3). R Foundation for Statistical Computing. https://www.R-project.org/

2.     J.R. Roussel, D. Auty, N.C. Coops, P. Tompalski, T.R.H. Goodbody, A. Sanchez Meador, J.F. Bourdon, F. De Boissieu, A. Achim, lidR: An R package for analysis of Airborne Laser Scanning (ALS) data. Remote Sensing of Environment 251, 112061 (2020). Doi:10.1016/j.rse.2020.112061

3.     J.R. Roussel, D. Auty, Airborne LiDAR Data Manipulation and Visualization for Forestry Applications (2022). R package version 4.0.1. https://cran.r-project.org/package=lidR