Joint Agency Commercial Imagery Evaluation (JACIE)

Fact Sheet 2024-3038
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Abstract

The Joint Agency Commercial Imagery Evaluation (JACIE) was formed to leverage resources from several Federal agencies for the characterization of remote sensing data and to share those results across the remote sensing community (U.S. Geological Survey, 2024).

Remote sensing data and the quality of that data are vital to (1) understanding the physical world and (2) supporting the science and engineering applications that strive to advance that understanding. The growing number of remotely sensed data sources offers users more choices. Understanding the characteristics and capabilities of current and new data sources, along with the quality of data they provide, is an important function of the multi-agency JACIE team. By performing data-quality analysis of civil and commercial remote sensing data and information products, the JACIE team provides the remote sensing community with awareness and independent verification of image data quality.

Joint Agency Commercial Imagery Evaluation Team

The JACIE team partnership was formed in 2001 to leverage U.S. Federal agency resources for the characterization of commercial remote sensing data. The JACIE team has grown to consist of representatives from the following Federal agencies:

  • - National Aeronautics and Space Administration (NASA)

  • - National Geospatial-Intelligence Agency (NGA)

  • - National Oceanic and Atmospheric Administration (NOAA)

  • - National Reconnaissance Office (NRO)

  • - U.S. Department of Agriculture (USDA)

  • - U.S. Geological Survey (USGS)

JACIE team partners regularly collaborate to share insights on technical topics and plan for the annual workshop.

Joint Agency Commercial Imagery Evaluation Data Quality Assessments

Experts in data-quality analysis complete independent data-quality assessments or characterizations of image and image-derived end products. Partner agencies bring their resources and strengths to this task, providing in-depth assessments of imagery and information quality. The efforts of the JACIE team members are instrumental in providing image product quality; however, the most important part of JACIE is the strong collaboration and enhanced working relationships between government and non-governmental organizations to understand remote sensing information and make it more useful to the user community.

Geo-positional, spatial, and radiometric quality are three primary areas for image characterization analysis that are completed by participating agencies using a common collection of JACIE Best Practices (Cantrell and Christopherson, 2024).

Combined, these analysis results help to describe the quality of image data and strongly affect the usability of the data for a myriad of Earth science applications and studies. The JACIE team communicates the knowledge and results of the quality and utility of the remotely sensed data available for government and private use.

Joint Agency Commercial Imagery Evaluation Annual Workshop

JACIE data-quality assessment analyses of remote sensing systems are presented each year at the JACIE Workshop. The JACIE Workshop is a week-long event where remote sensing data research and assessment results are shared with several hundred attendees from government, industry, and academia. This highly regarded and independent workshop affords the opportunity for presenters to exchange information regarding the characterization and application of commercial imagery used by the public sector. Presenters also have the opportunity to provide updates for current and future enhancements to existing sensors and promote new sensor uses and data products. Highlights of JACIE Workshops include presentations about new systems, new methods of analyzing and improving data, effects of data quality on applications, poster sessions, exhibits, focused side meetings, and networking events.

In addition to the annual JACIE Workshop, the JACIE team currently (2024) holds monthly tech team meetings. Tech team meetings usually include a guest speaker from one of the agencies or from an external group who relays technical information of interest to the group. The JACIE tech team consists of JACIE partner government and government contractor staff.

References Cited

Cantrell, S.J., and Christopherson, J.B., 2024, Joint Agency Commercial Imagery Evaluation (JACIE) best practices for remote sensing system evaluation and reporting: U.S. Geological Survey Open-File Report 2024–1023, 26 p. [Available at https://doi.org/10.3133/ofr20241023.]

U.S. Geological Survey, 2024, JACIE: U.S. Geological Survey website. [Available at https://www.usgs.gov/calval/jacie.]

JACIE activities are led and managed by the USGS Earth Resources Observation and Science (EROS) Cal/Val Center of Excellence (ECCOE) Project for the JACIE Team. For more information contact:

USGS EROS Cal/Val Center of Excellence (ECCOE) Project Team

U.S. Geological Survey, Earth Resources Observation and Science

47914 252nd Street

Sioux Falls, SD 57198

Email: eccoe@usgs.gov

https://www.usgs.gov/calval

Disclaimers

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested Citation

Clauson, J., Anderson, C., Vrabel, J., 2024, Joint Agency Commercial Imagery Evaluation (JACIE): U.S. Geological Survey Fact Sheet 2024-3038, 2 p., https://doi.org/10.3133/fs20243038.

ISSN: 2327-6932 (online)

Publication type Report
Publication Subtype USGS Numbered Series
Title Joint Agency Commercial Imagery Evaluation (JACIE)
Series title Fact Sheet
Series number 2024-3038
DOI 10.3133/fs20243038
Year Published 2024
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 2 p.
Google Analytic Metrics Metrics page
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