USGS Science⌕ Search
Home/Archive/USGS

USGS · 70035946

A national look at carbon capture and storage-National carbon sequestration database and geographical information system (NatCarb)

T.R. Carr·A. Iqbal·N. Callaghan·Dana-Adkins-Heljeson·K. Look·S. Saving·K. Nelson
View original source ↗Export metadata ↓

Abstract

The US Department of Energy's Regional Carbon Sequestration Partnerships (RCSPs) are responsible for generating geospatial data for the maps displayed in the Carbon Sequestration Atlas of the United States and Canada. Key geospatial data (carbon sources, potential storage sites, transportation, land use, etc.) are required for the Atlas, and for efficient implementation of carbon sequestration on a national and regional scale. The National Carbon Sequestration Database and Geographical Information System (NatCarb) is a relational database and geographic information system (GIS) that integrates carbon storage data generated and maintained by the RCSPs and various other sources. The purpose of NatCarb is to provide a national view of the carbon capture and storage potential in the U.S. and Canada. The digital spatial database allows users to estimate the amount of CO 2 emitted by sources (such as power plants, refineries and other fossil-fuel-consuming industries) in relation to geologic formations that can provide safe, secure storage sites over long periods of time. The NatCarb project is working to provide all stakeholders with improved online tools for the display and analysis of CO 2 carbon capture and storage data. NatCarb is organizing and enhancing the critical information about CO 2 sources and developing the technology needed to access, query, model, analyze, display, and distribute natural resource data related to carbon management. Data are generated, maintained and enhanced locally at the RCSP level, or at specialized data warehouses, and assembled, accessed, and analyzed in real-time through a single geoportal. NatCarb is a functional demonstration of distributed data-management systems that cross the boundaries between institutions and geographic areas. It forms the first step toward a functioning National Carbon Cyberinfrastructure (NCCI). NatCarb provides access to first-order information to evaluate the costs, economic potential and societal issues of CO 2 capture and storage, including public perception and regulatory aspects. NatCarb online access has been modified to address the broad needs of a spectrum of users. NatCarb includes not only GIS and database query tools for high-end user, but simplified display for the general public using readily available web tools such as Google Earth???and Google Maps???. Not only is NatCarb connected to all the RCSPs, but data are also pulled from public servers including the U.S. Geological Survey-EROS Data Center and from the Geography Network. Data for major CO 2 sources have been obtained from U.S. Environmental Protection Agency (EPA) databases, and data on major coal basins and coalbed methane wells were obtained from the Energy Information Administration (EIA). ?? 2009 Elsevier Ltd. All rights reserved.

Explore related subjects

Conference Paper

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

T.R. Carr, A. Iqbal, N. Callaghan, Dana-Adkins-Heljeson, K. Look, S. Saving, K. Nelson. 2009. A national look at carbon capture and storage-National carbon sequestration database and geographical information system (NatCarb). https://doi.org/10.1016/j.egypro.2009.02.057

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Improving building footprint extraction using NAIP and 3DEP lidar derived features with deep learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Texas↗
USGS2026

Time-to-depth conversion of seismic-reflection data from eastern Lake Superior and implications for the eastern arm of the Midcontinent Rift

Seismic-reflection data were acquired in the mid 1980s along several lines across eastern Lake Superior by industry and the Great Lakes International Multidisciplinary Program on Crustal Evolution (GLIMPCE) (Fig. 1). The lines form part of a larger network of crossing lines over the entire lake, which can be used to develop three-dimensional geologic models of the Mesoproterozoic Midcontinent Rift that lies below. To better interpret these lines, we developed velocity models to convert seismic reflections versus two-way travel time (TWTT) to reflections versus depth. In addition, the velocity models themselves provide insights into the structure of the Midcontinent Rift by recognizing common velocity ranges for certain rock types (Grauch, 2023).

eastern Lake Superior↗
USGS2026

Revisiting the utility of regional-scale, high-quality geophysical data in mineral exploration - A case study featuring the Mammoth Magnetic Anomaly, Pinal County, Arizona

Regional aeromagnetic surveys passively measure the total magnetic intensity (TMI) and are a foundational tool used in mineral exploration (Airo, 2015). With the increased global demand and the number of critical mineral resources required for manufacturing high-tech devices, developing high-quality, regional-scale geophysical surveys could aid critical mineral exploration efforts and geologic mapping. In 2019, the U. S. Geological Survey launched the Earth Mapping Resources Initiative (Earth MRI) to modernize the geologic and geophysical mapping of regions that have the potential to contain critical mineral resources within the United States. In support of planning Earth MRI geophysical surveys, Drenth and Grauch (2019) defined five aeromagnetic data quality rankings (rank 1 through rank 5) applying them to the airborne geophysical survey inventory of the United States (Johnson et al., 2021). Rank 1 aeromagnetic surveys are of the highest quality, meeting modern standards and allowing best practices for qualitative and quantitative interpretation; whereas rank 5 aeromagnetic surveys are of the lowest quality, being useful only for qualitative interpretation of broad features. Through the Earth MRI effort, 48 high-quality, regional-scale rank 1 and 2 airborne magnetic and radiometric geophysical surveys have been planned, collected, or publicly release through May 2025 (U. S. Geological Survey, 2025). Here, a portion of a rank 1 Earth MRI aeromagnetic survey in southeast Arizona is presented and compared to a legacy rank 5 aeromagnetic survey over the Mammoth Magnetic Anomaly (MMA), demonstrating how modern, high-quality aeromagnetic data improves our view of crustal geology, aiding mineral exploration.

Arizona↗