{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T17:23:20Z","timestamp":1772299400654,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T00:00:00Z","timestamp":1703721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"USGS","award":["G15PC00012"],"award-info":[{"award-number":["G15PC00012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landsat 9 (L9) was launched on 27 September 2021. This spacecraft contained two instruments, the Operational Land Imager-2 (OLI-2) and Thermal Infrared Sensor-2 (TIRS-2), that allow for a continuation of the Landsat program and the mission to acquire multi-spectral observations of the globe on a moderate scale. Following a period of commissioning, during which time the spacecraft and instruments were initialized and set up for operations, with the initial calibration performed, the mission moved to an operational mode This operational mode involved the same cadence and methods that were performed for the Landsat 8 (L8) spacecraft and the two instruments onboard, the Operational Land Imager-1 (OLI-1) and Thermal Infrared Sensor-1 (TIRS-1), with respect to calibration, characterization, and validation. This paper discusses the geometric operational aspects of the L9 instruments during the first year of the mission and post-commissioning, and compares these same geometric activities performed for L8 during the same time frame. During this time, optical axes of the two sensors, OLI-1 and OLI-2, were adjusted to stay aligned with the spacecraft\u2019s Attitude Control System (ACS), and the TIRS-1 and TIRS-2 instruments were adjusted to stay aligned with the OLI-1 and OLI-2 instruments, respectively. In this paper, the L9 operational adjustments are compared to the same operational aspects of L8 during this same time frame. The comparisons shown in this paper will demonstrate that both instruments aboard L8 and L9 performed very similar geometric qualities while fully meeting the expected requirements. This paper describes the geometric differences between the L9 imagery that was made available to the public prior to the reprocessing campaign that was performed using the new calibration updates to the sensor and to ACS and TIRS-to-OLI alignment parameters. This reprocessing campaign of L9 products involved data acquired from the launch of the spacecraft up to early 2023.<\/jats:p>","DOI":"10.3390\/rs16010133","type":"journal-article","created":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T09:35:21Z","timestamp":1703756121000},"page":"133","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Operational Aspects of Landsat 8 and 9 Geometry"],"prefix":"10.3390","volume":"16","author":[{"given":"Michael J.","family":"Choate","sequence":"first","affiliation":[{"name":"U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1860-7110","authenticated-orcid":false,"given":"Rajagopalan","family":"Rengarajan","sequence":"additional","affiliation":[{"name":"KBR, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]},{"given":"Md Nahid","family":"Hasan","sequence":"additional","affiliation":[{"name":"KBR, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]},{"given":"Alexander","family":"Denevan","sequence":"additional","affiliation":[{"name":"KBR, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]},{"given":"Kathryn","family":"Ruslander","sequence":"additional","affiliation":[{"name":"KBR, Contractor to the U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10286","DOI":"10.3390\/rs61110286","article-title":"Landsat-8 Operational Land Imager Design, Characterization and Performance","volume":"6","author":"Knight","year":"2014","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.3390\/rs70101135","article-title":"The Thermal Infrared Sensor (TIRS) On Landsat 8: Design Overview and Pre-launch Characterization","volume":"7","author":"Reuter","year":"2014","journal-title":"Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Choate, M.J., Rengarajan, R., Storey, J.C., and Lubke, M. (2023). Landsat 9 Geometric Commissioning Calibration Updates and System Performance Assessment. Remote Sens., 15.","DOI":"10.3390\/rs15143524"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Choate, M.J., Rengarajan, R., and Hasan, N. (2022, January 21\u201325). Early in Mission Landsat 9 Geometric Performance. Proceedings of the SPIE Optical Engineering and Applications, San Diego, CA, USA.","DOI":"10.1117\/12.2634253"},{"key":"ref_5","unstructured":"USGS (2023, February 08). Landsat Collections, Available online: https:\/\/www.usgs.gov\/landsat-missions\/landsat-collections."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"131","DOI":"10.14358\/PERS.81.2.131","article-title":"Validation of geometric accuracy of Global Land Survey (GLS) 2000 data","volume":"81","author":"Rengarajan","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Rengarajan, R., Storey, J.C., and Choate, M.J. (2020). Harmonizing the Landsat Ground Reference with the Sentinel-2 Global Reference Image Using Space-Based Bundle Adjustment. Remote Sens., 12.","DOI":"10.3390\/rs12193132"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Storey, J.C., Rengarajan, R., and Choate, M.J. (2019). Bundle Adjustment Using Space-Based Triangulation Method for Improving the Landsat Global Ground Reference. Remote Sens., 11.","DOI":"10.3390\/rs11141640"},{"key":"ref_9","unstructured":"(2023, January 07). AGRI: The Australian Geographic Reference Image. Geoscience Australia, Canberra. Available online: http:\/\/dx.doi.org\/10.4225\/25\/5524BA4A047FE."},{"key":"ref_10","unstructured":"(2023, September 24). USGS GeoData Digital Orthophoto Quadrangles, Available online: https:\/\/pubs.usgs.gov\/fs\/2001\/0057\/report.pdf."},{"key":"ref_11","unstructured":"Schowengerdt, R. (2007). Remote Sensing Models and Methods for Image Processing, Academic Press. Third Addition."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/0734-189X(86)90028-9","article-title":"Algorithms for Subpixel Registration","volume":"35","author":"Tian","year":"1986","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_13","unstructured":"USGS (2023, September 24). Landsat 8 and 9 Cal\/Val Algorithm Description Document, Available online: https:\/\/www.usgs.gov\/media\/files\/landsat-8-9-calibration-validation-algorithm-description-document."},{"key":"ref_14","unstructured":"(2023, September 24). Landsat Calibration Parameter Files, Available online: https:\/\/www.usgs.gov\/landsat-missions\/landsat-calibration-parameter-files."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"31006","DOI":"10.1051\/epjconf\/20100631006","article-title":"Digital Image Correlation: Displacement Accuracy Estimate","volume":"6","author":"Dupre","year":"2010","journal-title":"EPJ Web Conf."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1109\/TPAMI.1983.4767373","article-title":"Bounds on (Deterministic) Correlation Functions with Application to Registration","volume":"5","author":"Dvornychenko","year":"1983","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1364\/OE.24.001175","article-title":"Noise-induced bias for convolution-based interpolation in digital image correlation","volume":"24","author":"Su","year":"2016","journal-title":"Opt. Express"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dematteis, N., and Giordan, D. (2021). Comparison of Digital Image Correlation Methods and the Impact of Noise in Geoscience Applications. Remote Sens., 13.","DOI":"10.3390\/rs13020327"},{"key":"ref_19","unstructured":"Greenwalt, C.R., and Schultz, M.E. (1962). Principles and Error Theory and Cartographic Applications, USAF Aeronautical Chart and Information Center. ACIC Technical Report No. 96."},{"key":"ref_20","unstructured":"Dolloff, J., and Carr, J. (2016, January 11\u201315). Computation of scalar accuracy metrics LE, CE, and SE as both predictive and sample-based statistics. Proceedings of the ASPRS 2016 Annual Conference and Co-Located JACIE Workshop-Imaging Geospatial Technol. Forum Co-Located JACIE Work, Fort Worth, TX, USA."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Rengarajan, R., Choate, M., Storey, J., Franks, S., and Micijevic, E. (2020, January 17). Landsat Collection-2 Geometric Calibration Updates. Proceedings of the SPIE Optical Engineering and Applications, Online.","DOI":"10.1117\/12.2570429"},{"key":"ref_22","unstructured":"USGS (2023, January 08). Landsat Calibration and Validation, Available online: https:\/\/www.usgs.gov\/calval\/landsat-calibration-and-validation."},{"key":"ref_23","unstructured":"(2023, February 08). Landsat Mission Headlines, Available online: https:\/\/www.usgs.gov\/landsat-missions\/landsat-mission-headlines."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/133\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:43:31Z","timestamp":1760132611000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/1\/133"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,28]]},"references-count":23,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["rs16010133"],"URL":"https:\/\/doi.org\/10.3390\/rs16010133","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,28]]}}}