System Characterization Report on the Pléiades Neo Imager

Open-File Report 2021-1030-P
By: , and 

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Executive Summary

This report addresses system characterization of the Pléiades Neo satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.

Pléiades Neo is a constellation of four identical very-high-resolution optical satellites operated by Airbus Defence and Space. The first two satellites, Pléiades Neo-3 and -4, were launched in April and August 2021, respectively. The next two satellites, launched in December 2022, did not reach orbit because of Vega-C launch vehicle failure. Pléiades Neo provides several technical improvements to previous Pléiades-HR satellites, including the addition of coastal aerosol (deep blue) and red edge spectral bands, with improved ground sample distance and swath. The Pléiades Neo satellites were designed and built by Airbus Defence and Space with the high-resolution, multispectral imager for Earth imaging and use the S950 optical satellite bus. The high-resolution sensor on Pléiades Neo collects Earth data in the visible and near-infrared region with six bands and a panchromatic band. The satellites can operate off nadir to achieve a revisit of less than 1 day. More information on Pléiades Neo satellites and sensors is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium#) and from the manufacturer (https://www.intelligence-airbusds.com/imagery/constellation/pleiades-Neo/).

The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Pléiades Neo has an interior geometric performance in the range of 0.01 meter (m; 0.008 pixel) to −0.017 m (−0.014 pixel) in band-to-band registration; an exterior geometric performance in the range of −7.015 m (−0.702 pixel) to 3.846 m (0.385 pixel) offset in comparison to Sentinel-2 using ground control points of 2.9 to 7.2 m (95-percent circular error); a radiometric performance in the range of −0.070 (minimum) to −0.053 (maximum) in offset and 1.107 (minimum) to 1.202 (maximum) in slope; and a spatial performance in the range of 1.002 to 1.226 pixels at full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.22 to 0.34 (bands 2–7).

Suggested Citation

Cantrell, S.J., Sampath, A., Vrabel, J.C., Bresnahan, P., Anderson, C., Kim, M., and Park, S., 2023, System characterization report on the Pléiades Neo Imager, chap. P of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 52 p., https://doi.org/10.3133/ofr20211030P.

ISSN: 2331-1258 (online)

Table of Contents

  • Executive Summary
  • Introduction
  • System Description
  • Procedures
  • Measurements
  • Analysis
  • Summary and Conclusions
  • Selected References
  • Appendix 1. Explanation of Ground Control Points Method and Metadata
Publication type Report
Publication Subtype USGS Numbered Series
Title System characterization report on the Pléiades Neo Imager
Series title Open-File Report
Series number 2021-1030
Chapter P
DOI 10.3133/ofr20211030P
Year Published 2023
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description vi, 52 p.
Larger Work Type Report
Larger Work Subtype USGS Numbered Series
Larger Work Title System Characterization of Earth Observation Sensors
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details