{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T18:45:32Z","timestamp":1780512332301,"version":"3.54.1"},"reference-count":14,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,12,31]],"date-time":"2014-12-31T00:00:00Z","timestamp":1419984000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landsat 8 is the first satellite in the Landsat mission to acquire spectral imagery of the Earth using pushbroom sensor instruments. As a result, there are almost 70,000 unique detectors on the Operational Land Imager (OLI) alone to monitor. Due to minute variations in manufacturing and temporal degradation, every detector will exhibit a different behavior when exposed to uniform radiance, causing a noticeable striping artifact in collected imagery. Solar collects using the OLI\u2019s on-board solar diffuser panels are the primary method of characterizing detector level non-uniformity. This paper reports on an approach for using a side-slither maneuver to estimate relative detector gains within each individual focal plane module (FPM) in the OLI. A method to characterize cirrus band detector-level  non-uniformity using deep convective clouds (DCCs) is also presented. These approaches are discussed, and then, correction results are compared with the diffuser-based method. Detector relative gain stability is assessed using the side-slither technique. Side-slither relative gains were found to correct streaking in test imagery with quality comparable to diffuser-based gains (within 0.005% for VNIR\/PAN; 0.01% for SWIR) and identified a 0.5% temporal drift over a year. The DCC technique provided relative gains that visually decreased striping over the operational calibration in many images.<\/jats:p>","DOI":"10.3390\/rs70100430","type":"journal-article","created":{"date-parts":[[2014,12,31]],"date-time":"2014-12-31T08:49:33Z","timestamp":1420015773000},"page":"430-446","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Radiometric Non-Uniformity Characterization and Correction of Landsat 8 OLI Using Earth Imagery-Based Techniques"],"prefix":"10.3390","volume":"7","author":[{"given":"Frank","family":"Pesta","sequence":"first","affiliation":[{"name":"Image Processing Lab, Department of Electrical Engineering and Computer Science,  South Dakota State University, 315 Daktronics Hall, P.O. Box 2219 Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suman","family":"Bhatta","sequence":"additional","affiliation":[{"name":"Image Processing Lab, Department of Electrical Engineering and Computer Science,  South Dakota State University, 315 Daktronics Hall, P.O. Box 2219 Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dennis","family":"Helder","sequence":"additional","affiliation":[{"name":"Image Processing Lab, Department of Electrical Engineering and Computer Science,  South Dakota State University, 315 Daktronics Hall, P.O. Box 2219 Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nischal","family":"Mishra","sequence":"additional","affiliation":[{"name":"Image Processing Lab, Department of Electrical Engineering and Computer Science,  South Dakota State University, 315 Daktronics Hall, P.O. Box 2219 Brookings, SD 57007, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,12,31]]},"reference":[{"key":"ref_1","unstructured":"Adriansen, S., Benhadj, I., Duhoux, G., Dierckx, W., Dries, J., Heyns, W., Kleihorst, R., Livens, S., Nackaerts, K., and Reusen, I. (2010, January 10\u201312). Building a calibration and validation system for the PROBA-V satellite mission. Proceedings of the ISPRS XXXVIII International Calibration and Orientation Workshop, Castelldefels, Spain."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Anderson, C., Naughton, D., Brunn, A., and Thiele, M. (2011). Radiometric correction of RapidEye imagery using the on-orbit side-slither method. Proc. SPIE.","DOI":"10.1117\/12.898411"},{"key":"ref_3","unstructured":"Operational Land Imager (OLI) Landsat Science. Available online: http:\/\/landsat.gsfc.nasa.gov\/?p=5447."},{"key":"ref_4","unstructured":"Landsat 8 Mission Data Format Control Book, Available online: http:\/\/landsat.usgs.gov\/documents\/LDCM-DFCB-004.pdf."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Markham, B.L., Barsi, J.A., Kvaran, G., Ong, L., Kaita, E., Biggar, S., Czapla-Myers, J., Mishra, N., and Helder, D.L. (2014). Landsat-8 operational land imager radiometric calibration and stability. Remote Sens., in press.","DOI":"10.1117\/12.2063159"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Knight, E.J., and Kvaran, G. (2014). Landsat-8 operational land imager design, characterization, and performance. Remote Sens., in press.","DOI":"10.3390\/rs61110286"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Henderson, B.G., and Krause, K.S. (2004). Relative radiometric correction of QuickBird imagery using the side-slither technique on-orbit. Proc. SPIE.","DOI":"10.1117\/12.559910"},{"key":"ref_8","unstructured":"Angal, A, and Helder, D.L. (2005, January 25). Advanced land imager relative gain characterization and correction. Proceedings of Pecora 16\u2014Global Priorities in Land Remote Sensing, Sioux Falls, SD, USA."},{"key":"ref_9","unstructured":"Shrestha, A.K. (2010). Relative Gain Characterization and Correction for Pushbroom Sensors Based on Lifetime Image Statistics and Wavelet Filtering. [Master\u2019s Thesis, South Dakota State University]."},{"key":"ref_10","unstructured":"Shrestha, A.K., Helder, D.L., and Anderson, C. (2010, January 17). Relative gain characterization and correction for pushbroom sensors based on lifetime image statistics. Proceedings of the Civil Commercial Imagery Evaluation Workshop, Fairfax, VA, USA."},{"key":"ref_11","unstructured":"Landsat 8 Cal\/Val Algorithm Description Document, Available online: http:\/\/landsat.usgs.gov\/documents\/LDCM_CVT_ADD.pdf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1109\/TGRS.2012.2225066","article-title":"The characterization of deep convective clouds as an invariant calibration target and as a visible calibration technique","volume":"51","author":"Doelling","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Doelling, D.R., Nguyen, L., and Minnis, P. (2004). On the use of deep convective clouds to calibrate AVHRR data. Proc. SPIE.","DOI":"10.1117\/12.560047"},{"key":"ref_14","unstructured":"Morfitt, R., Markham, B.L., Micijevic, E., Scaramuzza, P., Barsi, J.A., Levy, R., Ong, L., and Vanderwerff, K. (2014). OLI radiometric performance on-orbit. Remote Sens., in press."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/430\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:11:55Z","timestamp":1760217115000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/430"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,31]]},"references-count":14,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,1]]}},"alternative-id":["rs70100430"],"URL":"https:\/\/doi.org\/10.3390\/rs70100430","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,31]]}}}