This materials contains a dataset of hyperspectral images captured for road pavement cracks in the ENVI format.
The crack dataset are captured in St Helens Lane north of Leeds city at post code LS16 8JJ at August 2020.
Each folder contains hyperspectral files together with the results of applying Asphalt Crack Index, ACI. described in the remote sensing paper 2020.
The files are numbered with the following abbreviations:
_ACI Asphalt Crack Index segmented image
_ACI_Overlayed ACI segmented image overlayed over original image
_VIS2 VIS2 metric segmented image
_VIS2_Overlayed VIS2 segmented regions overlayed over original image
_gt  the ground truth crack image by hand annotation.

Another set is provided with label Ax which serves the purpose of detecting fresh asphalt in roads as described in the paper.

Feel free to use the dataset for research and when using it, please cite the following papers:

Abdellatif, M , Peel, H, Cohn, AG  and Fuentes, R (2019) Hyperspectral Imaging for Autonomous Inspection of Road Pavement Defects. In: Al-Hussein, M, (ed.) Proceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC). ISARC 2019, 21-24 May 2019, Banff, AB, Canada. International Association for Automation and Robotics in Construction , pp. 384-392.
DOI: 10.22260/ISARC2019/0052
Abdellatif, M , Peel, H, Cohn, AG  and Fuentes, R (2020), Pavement Crack Detection from Hyperspectral Images Using a Novel Asphalt Crack Index, Remote Sens. 2020, 12(18), 3084; https://doi.org/10.3390/rs12183084