Hydrocarbon Spill Hyperspectral Dataset (HSHD

Hyperspectral imaging (HSI) has become a pivotal tool for environmental monitoring, particularly in identifying and analyzing hydrocarbon spills. This study presents an Internet of Things (IoT)-based framework for the collection, management, and analysis of hyperspectral data, employing a controlled experimental setup to simulate hydrocarbon contamination. Using a state-of-the-art hyperspectral camera, a dataset of 116 images was generated, encompassing temporal and spectral variations of gasoline, thinner, and motor oil spills. The data were transmitted and stored in a cloud-based repository using an IoT-enabled architecture, ensuring accessibility and scalability. This work addresses the lack of specialized hyperspectral datasets for hydrocarbon analysis, offering valuable resources for predictive modeling and decision-making. Ethical and sustainable database practices were also prioritized to enhance long-term usability for environmental research and mitigation strategies.