{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T03:33:34Z","timestamp":1775792014650,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,11]],"date-time":"2022-08-11T00:00:00Z","timestamp":1660176000000},"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>Over the past decades, remote sensing satellite sensors have significantly increased their performance and, at the same time, differed in their characteristics. Therefore, making the data repeatable over time and uniform with respect to different platforms has become one of the most challenging issues to obtain a representation of the intrinsic characteristics of the observed target. In this context, atmospheric correction has the role of cleaning the signal from unwanted contributions and moving from the sensor radiance to a quantity more closely related to the intrinsic properties of the target, such as ground reflectance. To this end, atmospheric correction procedures must consider a number of factors, closely related to the specific scene acquired and to the characteristics of the sensor. In mountainous environments, atmospheric correction must include a topographic correction level to compensate for the topographic effects that heavily affect the remote signal. In this paper, we want to estimate the impact of topographic correction on remote sensing images based on a statistical analysis, using data acquired under different illumination conditions with different sensors. We also want to show the benefits of introducing this level of correction in second level products such as PRISMA L2C reflectance, which currently do not implement it.<\/jats:p>","DOI":"10.3390\/rs14163903","type":"journal-article","created":{"date-parts":[[2022,8,11]],"date-time":"2022-08-11T21:15:05Z","timestamp":1660252505000},"page":"3903","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Impact of Topographic Correction on PRISMA Sentinel 2 and Landsat 8 Images"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9577-0005","authenticated-orcid":false,"given":"Federico","family":"Santini","sequence":"first","affiliation":[{"name":"Institute of Methodologies for Environmental Analysis, Italian National Research Council, 85050 Potenza, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1746-0057","authenticated-orcid":false,"given":"Angelo","family":"Palombo","sequence":"additional","affiliation":[{"name":"Institute of Methodologies for Environmental Analysis, Italian National Research Council, 85050 Potenza, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1080\/01431160600815525","article-title":"A method for the atmospheric correction of ENVISAT\/MERIS data over land targets","volume":"28","author":"Guanter","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","unstructured":"Jensen, J.R. (1996). Introduction Digital Image Processing: A Remote Sensing Perspective, Prentice-Hall. [2nd ed.]."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/S0034-4257(01)00219-X","article-title":"A VNIR\/SWIR atmospheric correction algorithm for hyperspectral imagery with adjacency effect","volume":"78","author":"Sanders","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/36.581987","article-title":"Second simulation of the satellite signal in the solar spectrum, 6S: An overview","volume":"35","author":"Vermote","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","unstructured":"Vermote, E.F., and Vermeulen, A. (1999). Atmospheric Correction Algorithm: Spectral Reflectances (MOD09), Department of Geography, University of Meryland."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gao, B.-C., and Li, R.-R. (2017). Removal of Thin Cirrus Scattering Effects in Landsat 8 OLI Images Using the Cirrus Detecting Channel. Remote Sens., 9.","DOI":"10.3390\/rs9080834"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7826","DOI":"10.3390\/rs70607826","article-title":"Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_8","first-page":"691","article-title":"Evaluation of different topographic correction methods for Landsat imagery","volume":"13","author":"Hantson","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","unstructured":"Kawishwar, P. (2007). Atmospheric Correction Models for Retrievals of Calibrated Spectral Profiles from Hyperion EO-1 Data. [Master\u2019s Thesis, International Institute for Geo-Information Science and Earth Observation]."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3503","DOI":"10.1080\/01431160210154029","article-title":"Correcting satellite imagery for the variance of reflectance and illumination with topography","volume":"24","author":"Shepherd","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2259","DOI":"10.1080\/01431160802549336","article-title":"A simple empirical topographic correction method for ETM+ imagery","volume":"30","author":"Gao","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1080\/02781070500293414","article-title":"Empirical correction of low Sun angle images in steeply sloping terrain: A slope-matching technique","volume":"27","author":"Nichol","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1109\/LGRS.2005.846012","article-title":"Empirical Method for Topographic Correction in Aerial Photographs","volume":"2","author":"Svoray","year":"2005","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1080\/01431168108948349","article-title":"An examination of spectral band ratioing to reduce the topographic effect on remotely-sensed data","volume":"2","author":"Holben","year":"1981","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6296","DOI":"10.3390\/rs70506296","article-title":"An Improved Physics-Based Model for Topographic Correction of Landsat TM Images","volume":"7","author":"Li","year":"2015","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1371","DOI":"10.1080\/01431169308953963","article-title":"Improvement in Maximum Likelihood Classification performance on highly rugged terrain using Principal Component Analysis","volume":"14","author":"Conese","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","first-page":"475","article-title":"Hyperspherical direction cosine transformation for separation of spectral and illumination information in digital scanner data","volume":"56","author":"Pouch","year":"1990","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_18","unstructured":"F\u00fcreder, P. (2008, January 8\u201311). Topographic correction of satellite images for improved LULC classification in alpine areas. Proceedings of the 10th International Symposium on High Mountain Remote Sensing Cartography 2010, Kathmandu, Nepal."},{"key":"ref_19","first-page":"641","article-title":"Topographic correction for differential illumination effects on IKONOS satellite imagery","volume":"35","author":"Law","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S0034-4257(03)00002-6","article-title":"The topographic normalization of hyperspectral data: Implications for the selection of spectral end members and lithologic mapping","volume":"85","author":"Feng","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"785","DOI":"10.14358\/PERS.69.7.785","article-title":"Impact of topographic normalization on land-cover classification accuracy","volume":"69","author":"Hale","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1080\/01431160050505856","article-title":"Use of topographic correction in Landsat TM-based forest interpretation in Nepal","volume":"22","author":"Tokola","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2586","DOI":"10.1109\/TGRS.2003.817416","article-title":"Multitemporal evaluation of topographic normalization methods on deciduous forest TM data","volume":"41","author":"Vincini","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/S0034-4257(97)00177-6","article-title":"Topographic normalization of Landsat TM images of forest based on subpixel sun\u2013canopy\u2013sensor geometry","volume":"64","author":"Gu","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_25","first-page":"531","article-title":"Topographic normalization in rugged terrain","volume":"57","author":"Colby","year":"1991","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"184","DOI":"10.3390\/rs1030184","article-title":"Comparison of topographic correction methods","volume":"1","author":"Richter","year":"2009","journal-title":"Remote Sens."},{"key":"ref_27","unstructured":"McDonald, E.R., Wu, X., Caccetta, P., and Campbell, N. (2002). Illumination Correction of Landsat TM Data in South East NSW, Environment Australia."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/0924-2716(93)90028-L","article-title":"Radiometric corrections of topographically induced effects on Landsat TM data in an alpine environment","volume":"48","author":"Meyer","year":"1993","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4712","DOI":"10.1080\/01431161.2016.1222101","article-title":"Evaluating and comparing performances of topographic correction methods based on multi-source DEMs and Landsat-8 OLI data","volume":"37","author":"Wu","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1099","DOI":"10.1080\/014311697218593","article-title":"Correction of atmospheric and topographic effects for high spatial resolution satellite imagery","volume":"18","author":"Richter","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1109\/36.581991","article-title":"A physically-based model to correct atmospheric and illumination effects in optical satellite data of rugged terrain","volume":"35","author":"Sandmeier","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1080\/01431160802348101","article-title":"Simple correction of multiple reflection effects in rugged terrain","volume":"30","author":"Sirguey","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.rse.2008.09.008","article-title":"Subpixel monitoring of the seasonal snow cover with MODIS at 250 m spatial resolution in the Southern Alps of New Zealand, Methodology and accuracy assessment","volume":"113","author":"Sirguey","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4597","DOI":"10.1109\/TGRS.2017.2694483","article-title":"Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction","volume":"55","author":"Yin","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5957","DOI":"10.1080\/01431160701881889","article-title":"The integrated radiometric correction of optical remote sensing imageries","volume":"29","author":"Kobayashi","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2631","DOI":"10.1080\/01431160110115834","article-title":"Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric\/topographic correction","volume":"23","author":"Richter","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4004","DOI":"10.1364\/AO.37.004004","article-title":"Correction of satellite imagery over mountainous terrain","volume":"37","author":"Richter","year":"1998","journal-title":"Appl. Opt."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Santini, F., and Palombo, A. (2019). Physically Based Approach for Combined Atmospheric and Topographic Corrections. Remote Sens., 11.","DOI":"10.3390\/rs11101218"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Palombo, A., and Santini, F. (2020). ImaACor: A Physically Based Tool for Combined Atmospheric and Topographic Corrections of Remote Sensing Images. Remote Sens., 12.","DOI":"10.3390\/rs12132076"},{"key":"ref_40","unstructured":"Italian Space Agency (2022, May 26). PRISMA Products Specification Document Issue 2.3 Date 12 March 2020. Available online: http:\/\/prisma.asi.it\/missionselect\/docs\/PRISMA%20Product%20Specifications_Is2_3.pdf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"8830","DOI":"10.3390\/rs70708830","article-title":"The EnMAP spaceborne imaging spectroscopy mission for Earth observation","volume":"7","author":"Guanter","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_42","unstructured":"(2022, May 26). Sen2Cor Software Release Note Ref S2-PDGS-MPC-L2A-SRN-V2.10.00 Issue 01 Date 13 December 2021. Available online: https:\/\/step.esa.int\/thirdparties\/sen2cor\/2.10.0\/docs\/S2-PDGS-MPC-L2A-SRN-V2.10.0.pdf."},{"key":"ref_43","first-page":"61","article-title":"Atmospheric Correction for Short-wave Spectral Imagery Based on MODTRAN4","volume":"Volume 3753","author":"Matthew","year":"1999","journal-title":"SPIE Proceedings on Imaging Spectrometry"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/S0034-4257(98)00045-5","article-title":"MODTRAN Cloud and Multiple Scattering Upgrades with Application to AVIRIS","volume":"65","author":"Berk","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_45","unstructured":"Berk, A., Bernstein, L.S., and Robertson, D.C. (1989). MODTRAN: A Moderate Resolution Model for LOWTRAN7\u2014GL-TR-89-0122, Air Force Geophysical Laboratory Hanscom AFB."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1117\/12.410341","article-title":"Status of Atmospheric Correction Using a MODTRAN4-based Algorithm","volume":"Volume 4049","author":"Matthew","year":"2000","journal-title":"SPIE Proceedings, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1080\/01431160802438555","article-title":"On the application of the MODTRAN4 atmospheric radiative transfer code to optical remote sensing","volume":"30","author":"Guanter","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_48","unstructured":"Berk, A., Anderson, G.P., Acharya, P.K., Chetwynd, J.H., Bernstein, L.S., Shettle, E.P., Matthew, M.W., and Adler-Golden, S.M. (2000). Modtran4 User\u2019s Manual, Air Force Research Laboratory."},{"key":"ref_49","unstructured":"(2022, May 22). 6SV Second Simulation of a Satellite Signal in the Solar Spectrum Vector Code. Available online: https:\/\/github.com\/DHI-GRAS\/6SV."},{"key":"ref_50","unstructured":"Vermote, E., Tanr\u00e9, D., Deuz\u00e9, J.L., Herman, M., Morcrette, J.J., and Kotchenova, S.Y. (2022, February 15). Second Simulation of a Satellite Signal in the Solar Spectrum-Vector (6SV), Available online: https:\/\/ltdri.org\/files\/6S\/6S_Manual_Part_1.pdf."},{"key":"ref_51","unstructured":"(2022, May 26). Atmospheric Correction Module: QUAC and FLAASH User\u2019s Guide, 20AC47DOC, Version 4.7, Issue August 2009. Available online: https:\/\/www.l3harrisgeospatial.com\/portals\/0\/pdfs\/envi\/Flaash_Module.pdf."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Pignatti, S., Amodeo, A., Carfora, M.F., Casa, R., Mona, L., Palombo, A., Pascucci, S., Rosoldi, M., Santini, F., and Laneve, G. (2022). PRISMA L1 and L2 Performances within the PRISCAV Project: The Pignola Test Site in Southern Italy. Remote Sens., 14.","DOI":"10.3390\/rs14091985"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1023\/B:ASTR.0000032539.52696.82","article-title":"Astronomical Site Testing in Northwest of Argentina","volume":"290","author":"Recabarren","year":"2004","journal-title":"Astrophys. Space Sci."},{"key":"ref_54","unstructured":"Panarello, H., Sierra, J.L., and Pedro, G. (1992). Flow Patterns at the Tuzgle-Tocomar Geothermal System, Salta-Jujuy, Argentina an Isotopic and Geochemical Approach (IAEA-TECDOC--641), International Atomic Energy Agency (IAEA)."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Filipovich, R., B\u00e1ez, W., Groppelli, G., Ahumada, F., Aldega, L., Becchio, R., Berardi, G., Bigi, S., Caricchi, C., and Chiodi, A. (2020). Geological Map of the Tocomar Basin (Puna Plateau, NW Argentina). Implication for the Geothermal System Investigation. Energies, 13.","DOI":"10.3390\/en13205492"},{"key":"ref_56","unstructured":"(2022, June 07). Landsat 8\u20139 Collection 2 (C2) Level 2 Science Product (L2SP) Guide. LSDS-1619 Version 4.0. Date 24 March 2022. Available online: https:\/\/d9-wret.s3.us-west-2.amazonaws.com\/assets\/palladium\/production\/s3fs-public\/media\/files\/LSDS-1619_Landsat-8-9-C2-L2-ScienceProductGuide-v4.pdf."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/3903\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:07:26Z","timestamp":1760141246000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/3903"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,11]]},"references-count":56,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14163903"],"URL":"https:\/\/doi.org\/10.3390\/rs14163903","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,11]]}}}