Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A fast radiometric correction method for Sentinel-2 satellite images

A fast radiometric correction method for Sentinel-2 satellite images Radiometric calibration is a method that estimates the reflection of the target from the measured input radiation. The purpose of this study is to radiometrically calibrate three spectral bands of Sentinel-2A, including green, red and infrared. For this purpose, Landsat-8 OLI data are used. Because they have bands with the same wavelength range and they have the same structure. As a result, Landsat-8 OLI is appropriate for relative radiometric calibration.Design/methodology/approachThe method used in this study is radiometric calibration uncorrected data from a sensor with corrected data from another sensor. Also, another aim of this study is a comparison between radiometric correction data and data that, in addition to radiometric correction, has been sharpened with panchromatic data. In this method, both of them have been used for radiometric calibration. Calibration coefficients have been obtained using the first-order polynomial equation.FindingsThis study showed that the corrected data has more valid answers than corrected and sharpened data. This method studied three land-cover types, including soil, water and vegetation, which it obtained the most accurate coefficients of calibration for soil class because R-square in all three bands was above 88%, and the root mean square error in all three bands was below 0.01. In the case of water and vegetation classes, only results of red and infrared bands were suitable.Originality/valueFor validating this method, the radiometric correction module of SNAP software was used. According to the results, the coefficient of radiometric calibration of the Landsat-8 sensor was very close to the coefficients obtained from the corrected data by SNAP. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aircraft Engineering and Aerospace Technology Emerald Publishing

A fast radiometric correction method for Sentinel-2 satellite images

Download PDF
6 pages

Loading next page...
 
/lp/emerald-publishing/a-fast-radiometric-correction-method-for-sentinel-2-satellite-images-WhAmjlVNPu
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1748-8842
DOI
10.1108/aeat-11-2020-0262
Publisher site
See Article on Publisher Site

Abstract

Radiometric calibration is a method that estimates the reflection of the target from the measured input radiation. The purpose of this study is to radiometrically calibrate three spectral bands of Sentinel-2A, including green, red and infrared. For this purpose, Landsat-8 OLI data are used. Because they have bands with the same wavelength range and they have the same structure. As a result, Landsat-8 OLI is appropriate for relative radiometric calibration.Design/methodology/approachThe method used in this study is radiometric calibration uncorrected data from a sensor with corrected data from another sensor. Also, another aim of this study is a comparison between radiometric correction data and data that, in addition to radiometric correction, has been sharpened with panchromatic data. In this method, both of them have been used for radiometric calibration. Calibration coefficients have been obtained using the first-order polynomial equation.FindingsThis study showed that the corrected data has more valid answers than corrected and sharpened data. This method studied three land-cover types, including soil, water and vegetation, which it obtained the most accurate coefficients of calibration for soil class because R-square in all three bands was above 88%, and the root mean square error in all three bands was below 0.01. In the case of water and vegetation classes, only results of red and infrared bands were suitable.Originality/valueFor validating this method, the radiometric correction module of SNAP software was used. According to the results, the coefficient of radiometric calibration of the Landsat-8 sensor was very close to the coefficients obtained from the corrected data by SNAP.

Journal

Aircraft Engineering and Aerospace Technology – Emerald Publishing

Published: Nov 30, 2021

Keywords: Satellite; Remote sensing; Radiometric calibration

References

  • Learning polynomials with neural networks
    Andoni, A.
  • Consideration of radiometric quantization error in satellite sensor cross-calibration
    Bhatt, R.
  • Vicarious radiometric calibration of EO-1 sensors by reference to high-reflectance ground targets
    Biggar, S.F.; Thome, K.J.; Wisniewski, W.
  • Predicting simultaneous nadir overpasses among polar-orbiting meteorological satellites for the intersatellite calibration of radiometers
    Cao, C.; Weinreb, M.; Xu, H.
  • Revised landsat-5 TM radiometrie calibration procedures and postcalibration dynamic ranges
    Chander, G.; Markham, B.
  • Empirical cross sensor comparison of Sentinel-2A and 2B MSI, landsat-8 OLI, and landsat-7 ETM+ top of atmosphere spectral characteristics over the conterminous United States
    Chastain, R.
  • Vicarious calibration of Beijing-1 multispectral imagers
    Chen, Z.
  • Remote sensing of vegetation structure using computer vision
    Dandois, J.P.; Ellis, E.C.
  • Copernicus Sentinel-2A calibration and products validation status
    Gascon, F.
  • Analyzing remote sensing data in R: the landsat package
    Goslee, S.C.
  • Remote sensing satellite’s attitude control system: rapid performance sizing for passive scan imaging mode
    Kosari, A.
  • A global analysis of Sentinel-2a, sentinel-2b and landsat-8 data revisit intervals and implications for terrestrial monitoring
    Li, J.; Roy, D.P.
  • Toward optimal closure of the earth’s top-of-atmosphere radiation budget
    Loeb, N.G.
  • Sen2Cor for sentinel-2
    Main-Knorn, M.
  • Remote sensing of riverine landscapes
    Mertes, L.A.K.
  • Application of GIS for evaluating ecotourism potential of protected area (case study: ghamishloo wildlife refuge)
    Nastaran, M.; Nia, S.H.
  • Remote sensing applications: an overview
    Navalgund, R.R.; Jayaraman, V.; Roy, P.S.
  • Inter-band radiometric comparison and calibration of ASTER visible and near-infrared bands
    Obata, K.; Tsuchida, S.; Iwao, K.
  • Sentinel-2/landsat-8 product consistency and implications for monitoring aquatic systems
    Pahlevan, N.
  • Sentinel-2A and 2B absolute calibration monitoring
    Revel, C.
  • Examination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance
    Roy, D.P.
  • Spectral and spatial quality analysis of pan-sharpening algorithms: a case study in Istanbul
    Sarp, G.
  • Remote sensing: models and methods for image processing: second edition, remote sensing: models and methods for image processing: second edition
    Schowengerdt, R.A.
  • Yield prediction with machine learning algorithms and satellite images
    Sharifi, A.
  • Application of Sentinel-1 data to estimate height and biomass of rice crop in astaneh-ye ashrafiyeh, Iran
    Sharifi, A.; Hosseingholizadeh, M.
  • A methodology for radiometric calibration of remote sensing images
    Sharifi, A.; Moradi, E.
  • Development of an allometric model to estimate above-ground biomass of forests using MLPNN algorithm, case study: hyrcanian forests of Iran
    Sharifi, A.; Amini, J.; Pourshakouri, F.
  • Multi- and hyperspectral geologic remote sensing: a review
    van der Meer, F.D.
  • Assessment of radiometric correction techniques in analyzing vegetation variability and change using time series of landsat images
    Vicente-Serrano, S.M.; Pérez-Cabello, F.; Lasanta, T.
  • Evaluation on radiometric capability of Chinese optical satellite sensors
    Yang, A.
  • Multi-source remote sensing data fusion: status and trends
    Zhang, J.
  • Cross-calibration of HJ-1/CCD over a desert site using landsat ETM + imagery and ASTER GDEM product
    Zhong, B.