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Electricity generation/consumption, renewable energy, smart grid, oil/gas, carbon emissions
4,324 datasets
NOAA's Deepwater Horizon Lessons Learned Studies produced this dataset on methods to estimate oil slick coverage and thickness. The research combined satellite imagery, airborne imagery, surface characterization, and subsurface data from the chronic MC20 oil discharge site and controlled tests at Ohmsett. Data shown here are from field research at the Mississippi Canyon lease block #20 (MC20) undertaken in 2016, 2017, and 2018.
NOAA's Deepwater Horizon Lessons Learned Studies collected these photos during field research at the Mississippi Canyon lease block #20 (MC20) in the Gulf of Mexico. The data are part of a study on detecting oil slick coverage and thickness using remote sensing platforms, funded by the U.S. Department of the Interior and the Bureau of Safety and Environmental Enforcement. Research was undertaken in 2016, 2017, and 2018.
2016-2018 data collected by NOAA as part of the Deepwater Horizon Lessons Learned Studies on oil slick detection. The dataset includes synoptic satellite and airborne imagery, surface oil characterization, and water chemistry from the Mississippi Canyon lease block #20 (MC20) site. Research was funded by the U.S. Department of the Interior and the Bureau of Safety and Environmental Enforcement.
NOAA's DWH Lessons Learned Studies collected these photos as part of research on detecting oil slick coverage and thickness. The data are from the MC20 field research undertaken in 2016, 2017, and 2018 at the Mississippi Canyon lease block #20, a site with a chronic oil discharge. This research was funded by the U.S. Department of the Interior, BSEE, and the Oil Spill Preparedness Division.
NOAA's Deepwater Horizon Lessons Learned Studies collected synoptic satellite and airborne imagery, surface oil characterization, and subsurface oil slick data at the Mississippi Canyon lease block #20 (MC20). This research, funded by the U.S. Department of the Interior and BSEE, aimed to develop methods for estimating oil slick coverage and thickness. The data shown here are part of the MC20 field research undertaken in 2016, 2017, and 2018.
NOAA's Deepwater Horizon Lessons Learned Studies collected these data to develop methods for estimating oil slick coverage and thickness. The research involved synoptic collection of satellite and airborne imagery, surface characterization, and subsurface data at the MC20 site, which has experienced a chronic oil discharge since 2004. This specific dataset is part of field research undertaken in 2016, 2017, and 2018, funded by the U.S. Department of the Interior and NOAA.
2016-2018 field research data from the MC20 chronic oil discharge site in the Gulf of Mexico. The dataset was collected by NOAA as part of the Deepwater Horizon Lessons Learned Studies to develop methods for estimating oil slick coverage and thickness. It includes synoptic satellite imagery, airborne imagery, surface oil characterization, and subsurface oil slick data.
NOAA's GOM OI - TOS Oil Classification dataset contains data from a study on methods to estimate oil slick coverage and thickness. The research involved synoptic collection of satellite imagery, airborne imagery, and surface oil characterization at the MC20 site in the Gulf of Mexico. This field research was primarily funded by the U.S. Department of the Interior and the Bureau of Safety and Environmental Enforcement.
NOAA's Deepwater Horizon Lessons Learned Studies collected data on oil slick coverage and thickness using remote sensing platforms. The research, funded by the U.S. Department of the Interior and BSEE, involved synoptic collection of satellite and airborne imagery, surface characterization, and chemistry at the MC20 site, which has experienced a chronic oil discharge since 2004. Data shown here are part of the MC20 field research undertaken in 2016, 2017, and 2018.
A NOAA field research dataset from the MC20 site, part of a study on detecting oil thickness and emulsion mixtures using remote sensing platforms. The data were collected during research campaigns in 2016, 2017, and 2018, primarily funded by the U.S. Department of the Interior and the Bureau of Safety and Environmental Enforcement. It includes synoptic collections of satellite imagery, airborne imagery, surface oil characterization, and water chemistry.
NOAA's Deepwater Horizon Lessons Learned Studies collected data on oil slick coverage and thickness using satellite and airborne imagery. This dataset is part of field research at the Mississippi Canyon lease block #20 (MC20), a site of a chronic oil discharge since 2004, undertaken in 2016, 2017, and 2018. The research was funded by the U.S. Department of the Interior, Bureau of Safety and Environmental Enforcement, and NOAA.
GOM Oil On Water Sampling Photos 2016-11-15 are part of NOAA's Deepwater Horizon Lessons Learned Studies. The data were collected during field research at the Mississippi Canyon lease block #20 (MC20) in 2016, 2017, and 2018 to develop methods for estimating oil slick coverage and thickness. This research was funded by the U.S. Department of the Interior, BSEE, and the Oil Spill Preparedness Division.
NOAA's MC20 field research in the Gulf of Mexico collected aerial imagery for oil slick analysis. The data shown here are part of studies conducted in 2016, 2017, and 2018, funded by the U.S. Department of the Interior and NOAA. The research focused on methods to estimate oil slick coverage and thickness using remote sensing platforms.
Statistics Canada provides national and provincial data on crude oil supply and disposition, including production, refinery inputs, and exports. The dataset covers characteristics such as heavy crude and synthetic crude production. Data is available in XML, HTML, and CSV formats, with a last recorded update in March 2026.
Monthly data tracks electric power generation, receipts, and deliveries across Canada. Statistics Canada provides national and provincial-level figures, including trade with other provinces and the United States. The dataset was last updated in March 2026.
Monthly data on electricity generation by producer class and energy source, including hydroelectric, combustible fuels, and wind. Statistics Canada provides this dataset with national and provincial-level breakdowns, though not all combinations are available. The dataset was last updated in March 2026.
NASA's Prediction of Worldwide Energy Resources (POWER) project provides over 380 satellite-derived meteorology and solar energy parameters. The data is available at hourly, daily, monthly, and climatology temporal levels, with daily meteorological data starting from 1981 and solar data from 1984. It is updated nightly to maintain near real-time availability.
The Fate of Carbon in Alaskan Landscapes (FOCAL) project by the U.S. Geological Survey collected soil data from central Alaska. The dataset likely contains field descriptions, bulk density, particle size distribution, moisture content, carbon and nitrogen concentrations, isotopic data, and elemental concentrations from sites of varying ages and soil drainage types. The summary was provided by the USGS.
Soil microfungi data from Beaufort Island in the Ross Sea, Antarctica, detailing species composition from 23 soil samples collected in the 2004/2005 austral summer. The dataset records 20 fungal species, including 13 ascomycetes, five unidentified species, and two yeasts. It was collected by the third author of the associated study and represents the first record of soil microfungi for this isolated island.
Neodymium and Strontium isotopic data from water-soluble salts, host soils, cobbles, and surface volcanic deposits in Antarctica's Dry Valleys. Samples were provided by researchers from Boston University, Louisiana State University, and Oregon State University. Analyses were conducted via TIMS at MIT and UC Berkeley, with concentration data from ICP-MS at BU.