CloudPatch-7 Hyperspectral Dataset

Citation Author(s):
Hua
Yan
Auburn University at Montgomery
Rachel
Zheng
Auburn University at Montgomery
Brandon
Boehm
Auburn University at Montgomery
Sameer
Shaga
Auburn University at Montgomery
Derienne
Black
Auburn University at Montgomery
Luis
Cueva Parra
High Point University
Randy
Russell
Auburn University at Montgomery
Olcay
Kursun
Auburn University at Montgomery
Submitted by:
OLCAY KURSUN
Last updated:
Sun, 09/08/2024 - 13:47
DOI:
10.21227/fgb9-qs51
Research Article Link:
License:
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Abstract 

 The "CloudPatch-7 Hyperspectral Dataset" comprises a manually curated collection of hyperspectral images, focused on pixel classification of atmospheric cloud classes. This labeled dataset features 380 patches, each a 50x50 pixel grid, derived from 28 larger, unlabeled parent images approximately 4402-by-1600 pixels in size. Captured using the Resonon PIKA XC2 camera, these images span 462 spectral bands from 400 to 1000 nm. Each patch is extracted from a parent image ensuring that its pixels fall within one of seven atmospheric conditions: Dense Dark Cumuliform Cloud, Dense Bright Cumuliform Cloud, Semi-transparent Cumuliform Cloud, Dense Cirroform Cloud, Semi-transparent Cirroform Cloud, Clear Sky - Low Aerosol Scattering (dark), and Clear Sky - Moderate to High Aerosol Scattering (bright). Incorporating contextual information from surrounding pixels enhances pixel classification into these 7 classes, making this dataset a valuable resource for spectral analysis, environmental monitoring, atmospheric science research, and testing machine learning applications that require contextual data. Parent images are very big in size, but they can be made available upon request. 

Funding Agency: 
NSF
Grant Number: 
2003740 and 2411519