Thermal infrared and hyperspectral image based transpiration rate modelling: part1

Python RGB segmentation code, R-scripts, processed and raw hyperspectral and thermal infrared image data for developing empirical transpiration rate prediction models from environmental data and images of Maize collected on an automated high-throughput phenotyping platform. The CNN RGB segmentation code can be found in the hooloovoo-master.zip and the pippa_cnn_segmentation-master.zip files. The R image preprocessing and modelling scripts are grouped in zip files that include the necessary data to run the scripts. The raw thermal data zip file also contain the RGB segmentation filters. The hyperspectral images are split up over three projects. This project contains the hyperspectral data of the DR experiment in which maize was subjected to different drought severities and the third part of the data collected during the transferability (TF) experiment. The other part of TF dataset can be found using the following DOI's: 10.5281/zenodo.8164473 and 10.5281/zenodo.8033640.