Unveiling Temperature Patterns in Tree Canopies across Diverse Heights and Types

Forests are some of the major ecosystems that help in mitigating the effects of climate change. Understanding the relation between the surface temperatures of different vegetation and trees and their heights is very crucial in understanding events such as wildfires. In this work, relationships between tree canopy temperature and canopy height with respect to vegetation types were extracted. The southern part of Sardinia Island, which has dense forests and is often affected by wildfires, was selected as the region of interest. PRISMA hyperspectral imagery has been used to map all the available vegetation types in the region of interest using the support vector machine classifier with an accuracy of >80% for all classes. The Global Ecosystem Dynamics Investigation's (GEDI) L2A Raster Canopy Top Height product provides canopy height measurements in spatially discrete footprints, and to overcome this issue of discontinuous sampling, Random Forest Regression was used on Sentinel-1 SAR data, Sentinel-2 multispectral data, and the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) to estimate the canopy heights of various vegetation classes, with a root mean squared error (RMSE) value of 2.9176 m and a coefficient of determination (R-2) value of 0.791. Finally, the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and emissivity product provides ground surface temperature regardless of land use and land cover (LULC) types. LST measurements over tree canopies are considered as the tree canopy temperature. We estimated the relationship between the canopy temperature of five vegetation types (evergreen oak, olive, juniper, silicicole, riparian trees) and the corresponding canopy heights and vegetation types. The resulting scatter plots showed that lower tree canopy temperatures correspond with higher tree canopies with a correlation coefficient in the range of -0.4 to -0.5 for distinct types of vegetation.