{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Jeffery A. Steevens", "hasEmail": "mailto:jsteevens@usgs.gov"}, "description": "The data are a set of fluorescent images that were generated to support the development of a machine learning model.  The approach combines fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. The dataset is comprised of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil (NACO) and an aromatic-napthalenic crude oil (ANCO). The oil is diluted in hexane and the images represent concentrations ranging from 0 to 500 mg/L. The data are presented as JPEG files in two zip folders (one for each oil type) as well as a CSV file that describes the type and concentration of the oil photographed in each image. These images were used to train and evaluate a machine learning tool comprised of convolutional neural network architecture for feature extraction coupled with a custom regression model. Model description and code can be found at https://github.com/biplabpoudel25/Oil-spill-estimation.", "distribution": [{"@type": "dcat:Distribution", "accessURL": "https://doi.org/10.5066/P1SXVZX2", "description": "Landing page for access to the data", "format": "XML", "mediaType": "application/http", "title": "Digital Data"}, {"@type": "dcat:Distribution", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.689a01fdd4be02504d348c18.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_689a01fdd4be02504d348c18", "keyword": ["Azerbaijan", "Columbia Environmental Research Center", "Industrial pollution", "USGS:689a01fdd4be02504d348c18", "artificial intelligence", "biota", "image analysis", "machine learning", "petroleum"], "modified": "2025-08-15T00:00:00Z", "publisher": {"@type": "org:Organization", "name": "U.S. Geological Survey"}, "spatial": "46.8234, 40.1858, 51.0750, 40.5095", "theme": ["geospatial"], "title": "Images of two standard crude oils collected using a fluorescent camera device to train and optimize a machine learning model for real-time oil spill concentration assessment collected from November 7, 2023, to July 8, 2024"}