{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T19:59:35Z","timestamp":1774641575192,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T00:00:00Z","timestamp":1562716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"USGS Contract","award":["G15PC00012"],"award-info":[{"award-number":["G15PC00012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>There is an ever-increasing interest and need for accurate georegistration of remotely sensed data products to a common global geometric reference. Although georegistration has improved substantially in the last decade, the lack of an accurate global ground reference dataset poses serious issues for data providers seeking to make geometrically stackable analysis-ready data. The existing Global Land Survey 2000 (GLS2000) dataset derived from Landsat 7 images provides global coverage and can be used as a reference dataset, but its accuracy is much lower than what can be attained using the agile and precise pointing capability of the new spacecrafts. The improved position and pointing knowledge of the new spacecrafts such as Landsat 8 can be used to improve the accuracy of the existing global ground control points using a space-based triangulation method. This paper discusses the theoretical basis, formulation, and application of the space-based triangulation method at a continental scale to improve the accuracy of the GLS-derived ground control points. Our triangulation method involves adjusting the spacecraft position, velocity, attitude, attitude rate, and ground control point locations, iteratively, by linearizing the non-linear viewing geometry, such that the residual errors in the measured image points are minimized. The complexity of the numerical inversion and processing is dealt with in our approach by processing and eliminating the ground points one at a time. This helps to reduce the size of the normal matrix significantly, thereby making the triangulation of a continent-wide scale block feasible and efficient. One of the unique characteristics of our method is the use of a correlation model linking the attitude corrections between images of the same pass, which promotes consistency in the attitude corrections. We evaluated the performance of our triangulation method over the Australian continent using the Australian Geographic Reference Image (AGRI) dataset as a reference. Both a free adjustment, using only the pointing information of the Landsat 8 spacecraft, and a constrained adjustment using the AGRI as external control were performed and the results compared. The Australian block\u2019s horizontal accuracy improved from 15.4 m to 3.6 m with the use of AGRI controls and from 15.4 m to 8.8 m without the use of AGRI controls.<\/jats:p>","DOI":"10.3390\/rs11141640","type":"journal-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T11:56:51Z","timestamp":1562759811000},"page":"1640","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Bundle Adjustment Using Space-Based Triangulation Method for Improving the Landsat Global Ground Reference"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6664-7232","authenticated-orcid":false,"given":"James C.","family":"Storey","sequence":"first","affiliation":[{"name":"KBR, Contractor to the 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":"Michael J.","family":"Choate","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD 57030, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.rse.2013.02.026","article-title":"Assessment of the NASA\u2013USGS Global Land Survey (GLS) datasets","volume":"134","author":"Gutman","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.rse.2016.08.025","article-title":"A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery","volume":"186","author":"Storey","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_3","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_4","doi-asserted-by":"crossref","first-page":"11127","DOI":"10.3390\/rs61111127","article-title":"Landsat 8 Operational Land Imager On-Orbit Geometric Calibration and Performance","volume":"6","author":"Storey","year":"2014","journal-title":"Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ravanbakhsh, M., Wang, L.W., Fraser, C., and Lewis, A. (2012). Generation of the Australian geographic reference image through long-strip ALOS PRISM orientation. ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 225\u2013229.","DOI":"10.5194\/isprsarchives-XXXIX-B1-225-2012"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1109\/LGRS.2014.2365210","article-title":"Multistrip Bundle Block Adjustment of ZY-3 Satellite Imagery by Rigorous Sensor Model Without Ground Control Point","volume":"12","author":"Zhang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4083","DOI":"10.1109\/TGRS.2009.2014366","article-title":"A Strip Adjustment Approach for Precise Georeferencing of ALOS Optical Imagery","volume":"47","author":"Rottensteiner","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"880","DOI":"10.1109\/LGRS.2016.2551739","article-title":"DEM-Aided Bundle Adjustment With Multisource Satellite Imagery: ZY-3 and GF-1 in Large Areas","volume":"13","author":"Zheng","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1109\/TGRS.2017.2750320","article-title":"Relative Geometric Refinement of Patch Images Without Use of Ground Control Points for the Geostationary Optical Satellite GaoFen4","volume":"56","author":"Yang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1109\/TGRS.2009.2033935","article-title":"DEM-Aided Block Adjustment for Satellite Images With Weak Convergence Geometry","volume":"48","author":"Teo","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","first-page":"161","article-title":"Improvement of interior and exterior orientation of the three line camera HRSC with a simultaneous adjustment","volume":"36","author":"Spiegel","year":"2007","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_12","first-page":"209","article-title":"DSM based orientation of large stereo satellite image blocks","volume":"39","author":"Reinartz","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/TGRS.2010.2054833","article-title":"Bundle Adjustment With Rational Polynomial Camera Models Based on Generic Method","volume":"49","author":"Xiong","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"983","DOI":"10.14358\/PERS.78.9.983","article-title":"Bundle Block Adjustment of Weakly Connected Aerial Imagery","volume":"78","author":"Zhang","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2096","DOI":"10.1109\/TGRS.2004.834638","article-title":"Spatiotriangulation with multisensor VIR\/SAR images","volume":"42","author":"Toutin","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","unstructured":"Rengarajan, R., Choate, M., and Storey, J. (2019, July 08). Extraction of GCP Chips from GeoCover Using Modified Moravec Interest Operator (MMIO) Algorithm, Available online: https:\/\/landsat.usgs.gov\/sites\/default\/files\/documents\/MMIO_GeoCover_Control_White_Paper.pdf."},{"key":"ref_17","unstructured":"USGS (2019, July 08). Landsat 8 (L8) Data Users Handbook, Available online: https:\/\/www.usgs.gov\/media\/files\/landsat-8-data-users-handbook."},{"key":"ref_18","unstructured":"USGS (2019, July 08). Landsat 8 (L8) Calibration and Validation (Cal\/Val) Algorithm Description Document (Add), Available online: https:\/\/landsat.usgs.gov\/sites\/default\/files\/documents\/LSDS-649-Landsat-8_CalVal_Algorithm-Description-Document.pdf."},{"key":"ref_19","first-page":"205","article-title":"Evaluation of vertical accuracy of open source Digital Elevation Model (DEM)","volume":"21","author":"Mukherjee","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"249","DOI":"10.14358\/PERS.72.3.249","article-title":"A global assessment of the SRTM performance","volume":"72","author":"Rodriguez","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_21","first-page":"96430A","article-title":"Sentinel 2 global reference image","volume":"9643","author":"Dechoz","year":"2015","journal-title":"Proc. SPIE Image Signal Proc. Remote Sens. XXI"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yan, L., Roy, D.P., Zhang, H., Li, J., and Huang, H. (2016). An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8060520"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.rse.2018.04.021","article-title":"Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology","volume":"215","author":"Yan","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2018.09.002","article-title":"The Harmonized Landsat and Sentinel-2 surface reflectance data set","volume":"219","author":"Claverie","year":"2018","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1640\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:04:18Z","timestamp":1760187858000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1640"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,10]]},"references-count":24,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["rs11141640"],"URL":"https:\/\/doi.org\/10.3390\/rs11141640","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,10]]}}}