{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T07:06:11Z","timestamp":1773817571729,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,18]],"date-time":"2020-04-18T00:00:00Z","timestamp":1587168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hansung University, Ministry of Land, Infrastructure, and Transport, Korea","award":["14NSIP- B080144-01"],"award-info":[{"award-number":["14NSIP- B080144-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Surface reflectance data obtained by the absolute atmospheric correction of satellite images are useful for land use applications. For Landsat and Sentinel-2 images, many radiometric processing methods exist, and the images are supported by most types of commercial and open-source software. However, multispectral KOMPSAT-3A images with a resolution of 2.2 m are currently lacking tools or open-source resources for obtaining top-of-canopy (TOC) reflectance data. In this study, an atmospheric correction module for KOMPSAT-3A images was newly implemented into the optical calibration algorithm in the Orfeo Toolbox (OTB), with a sensor model and spectral response data for KOMPSAT-3A. Using this module, named OTB extension for KOMPSAT-3A, experiments on the normalized difference vegetation index (NDVI) were conducted based on TOC reflectance data with or without aerosol properties from AERONET. The NDVI results for these atmospherically corrected data were compared with those from the dark object subtraction (DOS) scheme, a relative atmospheric correction method. The NDVI results obtained using TOC reflectance with or without the AERONET data were considerably different from the results obtained from the DOS scheme and the Landsat-8 surface reflectance of the Google Earth Engine (GEE). It was found that the utilization of the aerosol parameter of the AERONET data affects the NDVI results for KOMPSAT-3A images. The TOC reflectance of high-resolution satellite imagery ensures further precise analysis and the detailed interpretation of urban forestry or complex vegetation features.<\/jats:p>","DOI":"10.3390\/ijgi9040257","type":"journal-article","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T03:23:06Z","timestamp":1587439386000},"page":"257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Determination of the Normalized Difference Vegetation Index (NDVI) with Top-of-Canopy (TOC) Reflectance from a KOMPSAT-3A Image Using Orfeo ToolBox (OTB) Extension"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8586-4750","authenticated-orcid":false,"given":"Kiwon","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Electronics and Information Engineering, Hansung University, Seoul 02876, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9136-7275","authenticated-orcid":false,"given":"Kwangseob","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electronics and Information Engineering, Hansung University, Seoul 02876, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sun-Gu","family":"Lee","sequence":"additional","affiliation":[{"name":"Korea Aerospace Research Institute, Satellite Application Division, Daejeon 34133, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongseung","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea Aerospace Research Institute, Satellite Application Division, Daejeon 34133, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2493","DOI":"10.1080\/01431161.2014.883104","article-title":"Using earth observation- based dry season NDVI trends for assessment of changes in tree cover in the Sahel","volume":"35","author":"Horion","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.isprsjprs.2016.09.008","article-title":"A global study of NDVI difference among moderate-resolution satellite sensors","volume":"121","author":"Fan","year":"2016","journal-title":"ISPRS J. Photogramm."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1016\/j.ecolind.2015.01.032","article-title":"A generalizable NDVI based wetland delineation indicator for remote monitoring of groundwater flows in the Australian Great Artesian Basin","volume":"60","author":"White","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gascon, F., Bouzinac, C., Th\u00e9paut, O., Jung, M., Francesconi, B., Louis, J., Lonjou, V., Lafrance, B., Massera, S., and Gaudel-Vacaresse, A. (2017). Copernicus Sentinel-2A Calibration and Products Validation Status. Remote Sens., 9.","DOI":"10.3390\/rs9060584"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1080\/01431161.2016.1266108","article-title":"Predicting old-growth tropical forest attributes from very high resolution (VHR)-derived surface metrics","volume":"38","author":"Meave","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"045004","DOI":"10.1117\/1.JRS.12.045004","article-title":"Assessment of cross-sensor vegetation index compatibility between VIIRS and MODIS using near-coincident observations","volume":"12","author":"Miura","year":"2018","journal-title":"J. Appl. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Vuolo, F., Zoltak, M., Pipitone, C., Zappa, L., Wenng, H., Immitzer, M., Weiss, M., Baret, F., and Atzberger, C. (2016). Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples. Remote Sens., 8.","DOI":"10.3390\/rs8110938"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.rse.2019.01.023","article-title":"Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity","volume":"224","author":"Kuhn","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_9","unstructured":"Manakos, I., Manevski, K., Kalaitzidis, C., and Edler, D. (2011, January 11\u201313). Comparison between Atmospheric Correction Modules on the Basis of Worldview-2 Imagery and In Situ Spectroradiometric Measurements. Proceedings of the 7th EARSeL SIG Imaging Spectroscopy workshop, Edinburgh, UK."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"685","DOI":"10.5721\/EuJRS20144739","article-title":"Coastline extraction using high resolution WorldView-2 satellite imagery","volume":"47","author":"Maglione","year":"2014","journal-title":"Eur. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.ufug.2018.01.021","article-title":"Mapping vegetation functional types in urban areas with WorldView-2 imagery: Integrating object-based classification with phenology","volume":"31","author":"Yan","year":"2018","journal-title":"Urban For. Urban Gree."},{"key":"ref_12","first-page":"100246","article-title":"Performances of WorldView 3, Sentinel 2, and Landsat 8 data in mapping impervious surface","volume":"15","author":"Xian","year":"2019","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_13","first-page":"101912","article-title":"A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards","volume":"83","author":"Solano","year":"2019","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"126634","DOI":"10.1016\/j.ufug.2020.126634","article-title":"Street tree health from space? An evaluation using WorldView-3 data and the Washington D.C. Street Tree Spatial Database","volume":"49","author":"Fang","year":"2020","journal-title":"Urban For. Urban Gree."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"321","DOI":"10.7780\/kjrs.2015.31.4.4","article-title":"Atmospheric Correction Problems with Multi-Temporal High Spatial Resolution Images from Different Satellite Sensors","volume":"31","author":"Lee","year":"2015","journal-title":"Korean J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1080\/2150704X.2015.1054043","article-title":"Radiometric characterization and validation for the KOMPSAT-3 sensor","volume":"6","author":"Kim","year":"2015","journal-title":"Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shin, D.Y., Ahn, H.Y., Lee, S.G., Choi, C.U., and Kim, J.S. (2016, January 12\u201319). Radiometric Cross-calibration of KOMPSAT-3A with Landsat-8. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B1, 2016, XXIII ISPRS Congress, Prague, Czech Republic.","DOI":"10.5194\/isprsarchives-XLI-B1-379-2016"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yeom, J.M., Ko, J., Hwang, J., Lee, C.S., Choi, C.U., and Jeong, S. (2018). Updating Absolute Radiometric Characteristics for KOMPSAT-3 and KOMPSAT-3A Multispectral Imaging Sensors Using Well-Characterized Pseudo-Invariant Tarps and Microtops II. Remote Sens., 10.","DOI":"10.3390\/rs10050697"},{"key":"ref_19","first-page":"1369","article-title":"Feasibility Assessment of Spectral Band Adjustment Factor of KOMPSAT-3 for Agriculture Remote Sensing","volume":"34","author":"Ahn","year":"2018","journal-title":"Korean J. Remote Sens."},{"key":"ref_20","first-page":"1327","article-title":"An Experiment for Surface Reflectance Image Generation of KOMPSAT 3A Image Data by Open Source Implementation","volume":"35","author":"Lee","year":"2019","journal-title":"Korean J. Remote Sens."},{"key":"ref_21","unstructured":"(2020, January 10). AERONET, Aerosol Robotic Network, Available online: https:\/\/aeronet.gsfc.nasa.gov\/."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"89","DOI":"10.5194\/nhess-10-89-2010","article-title":"Atmospheric correction for satellite remotely sensed data intended for agricultural applications: Impact on vegetation indices","volume":"10","author":"Hadjimitsis","year":"2010","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.rse.2015.02.004","article-title":"Evaluation of the performance of Suomi NPP VIIRS top of canopy vegetation indices over AERONET sites","volume":"162","author":"Shabanov","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kumar, L., and Mutang, O. (2018). Google Earth Engine Applications since Inception: Usage, Trends, and Potential. Remote Sens., 10.","DOI":"10.3390\/rs10101509"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"580","DOI":"10.3390\/rs6010580","article-title":"High Spatial Resolution WorldView-2 Imagery for Mapping NDVI and Its Relationship to Temporal Urban Landscape Evapotranspiration Factors","volume":"6","author":"Nouri","year":"2014","journal-title":"Remote Sens."},{"key":"ref_27","unstructured":"Jensen, J.R. (2016). Introductory Digital Image Processing A Remote Sensing Perspective, Pearson. [4th ed.]."},{"key":"ref_28","unstructured":"Bunting, P. (2020, January 10). Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI). Available online: https:\/\/arcsi.remotesensing.info\/."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Frantz, D.M., Stellmes, M., and Hostert, P. (2019). A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11030257"},{"key":"ref_30","unstructured":"Leutner, B. (2020, January 10). Package \u2018RStoolbox\u2019. Available online: https:\/\/cran.r-project.org\/web\/packages\/RStoolbox\/RStoolbox.pdf."},{"key":"ref_31","first-page":"525","article-title":"Atmospheric correction of Landsat-8\/OLI and Sentinel-2\/MSI data using iCOR algorithm: Validation for coastal and inland waters","volume":"5","author":"Sterckx","year":"2018","journal-title":"Eur. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.5194\/gmd-8-1991-2015","article-title":"System for Automated Geoscientific Analyses (SAGA) v. 2.1.4","volume":"8","author":"Conrad","year":"2015","journal-title":"Geosci. Model Dev."},{"key":"ref_33","unstructured":"(2020, January 07). DigitalGlobe Atmospheric Compensation. Available online: http:\/\/digitalglobe-marketing.s3.amazonaws.com\/files\/documents\/DataSheet_AComp_DS.pdf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s40965-017-0031-6","article-title":"Orfeo ToolBox: Open source processing of remote sensing images","volume":"2","author":"Grizonnet","year":"2017","journal-title":"Open Geospat. Data Softw. Stand."},{"key":"ref_35","unstructured":"(2020, January 10). MODIS Land Surface Reflectance. Available online: http:\/\/6s.ltdri.org\/."},{"key":"ref_36","unstructured":"Orfeo Toolbox (2020, January 10). Open Source Processing for Remote Sensing Images. Available online: https:\/\/www.orfeo-toolbox.org\/."},{"key":"ref_37","unstructured":"(2019, May 02). TOA Radiance Reflectance Conversion of KOMPSAT 1.5. Available online: http:\/\/www.si-imaging.com\/resources\/?pageid=2&uid=284&mod=document."},{"key":"ref_38","unstructured":"(2019, May 02). KOMPSAT-3A Image Data Manual v1.4. Available online: http:\/\/www.si-imaging.com\/resources\/?pageid=4&uid=234&mod=document."},{"key":"ref_39","unstructured":"(2020, March 30). OTB Cook Book. Available online: https:\/\/www.orfeo-toolbox.org\/CookBook\/CompilingOTBFromSource.html#compilingfromsource."},{"key":"ref_40","unstructured":"(2019, October 10). Reference Solar Spectral Irradiance: ASTM G-173, Available online: https:\/\/rredc.nrel.gov\/solar\/\/spectra\/am1.5\/ASTMG173\/ASTMG173.html."},{"key":"ref_41","unstructured":"(2020, January 04). NDVI, Mapping a Function over a Collection, Quality Mosaicking. Available online: https:\/\/developers.google.com\/earth-engine\/tutorial_api_06."},{"key":"ref_42","unstructured":"(2020, January 10). USGS Landsat 8 Surface Reflectance Tier 1. Available online: https:\/\/developers.google.com\/earth-engine\/datasets\/catalog\/LANDSAT_LC08_C01_T1_SR."},{"key":"ref_43","unstructured":"(2020, January 10). U.S. Landsat Analysis Ready Data: U.S. Geological Survey Fact Sheet 2018\u20133053, Available online: https:\/\/pubs.er.usgs.gov\/publication\/fs20183053."},{"key":"ref_44","unstructured":"(2020, March 30). CEOS Analysis Ready Data. Available online: http:\/\/ceos.org\/ard\/."},{"key":"ref_45","unstructured":"(2020, March 30). EarthExplorer Homepage, Available online: https:\/\/earthexplorer.usgs.gov\/."},{"key":"ref_46","unstructured":"(2020, March 30). 6 Spectral Indexes on Top of NDVI to Make Your Vegetation Analysis Complete. Available online: https:\/\/eos.com\/blog\/6-spectral-indexes-on-top-of-ndvi-to-make-your-vegetation-analysis-complete\/."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/4\/257\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:31:30Z","timestamp":1760362290000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/4\/257"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,18]]},"references-count":46,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2020,4]]}},"alternative-id":["ijgi9040257"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9040257","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,18]]}}}