Bi-quarterly, Islamic Azad University (Maybod Branch)

Document Type : Original Article


1 Instructor of electronic, Department of Information and communication technology, Imam Hossein University (IHU), Tehran, Iran

2 MSc of remote sensing, Kharazmi University, Tehran, Iran

3 MSc of physic, Institute for Advanced Studies in Basic Sciences(IASBS), Zanjan, Iran

4 M.Eng of metalogic, , Imam Hossein University, Tehran, Iran

5 M.Eng of Electronic, Microelectronic and Nanoelectronic devices, department of Information and communication technology, Imam Hossein University, Tehran, Iran


Background and objective: Absolute and Relative Models of Radiometric Corrections Due to the relative information provided from different parts of the globe, there are always errors when correcting images, which has led many researchers to develop local models or design tools to obtain information about the situation of Atmospheric of the area under study when the satellite passes. The present study aims to present a new method for radiometric correction of satellite images.
Material and methods: To apply the proposed method for correcting the calibration of satellite images, a sun-photometer was first designed and developed that can obtain atmospheric data and attenuate sunlight in the range of 400 to 950 nm in a hyperspectral mode. Sentinel-2 satellite images related to the city of Tehran were selected as a sample and in 2 days with clean and high pollution, data were obtained and the coefficients obtained were applied through a sun-photometer.
Results and conclusions: Based on made assessments, the importance of radiometric corrections based on local information for satellite images become more apparent. Evaluation of the research results shows the high capability of the designed sun-photometer in accurately assessing the attenuation of sunlight in different spectral. The amount of sunlight attenuation in the green band is more than the blue and red bands, which indicates the type of urban pollution in the region, which had the greatest impact on the green band and the least impact on the red band.


Main Subjects

Angal, A., Mishra, N., Xiong, X., & Helder, D. (2014). Cross-calibration of Landsat 5 TM and Landsat 8 OLI with Aqua MODIS using PICS. Earth Observing Systems XIX. doi:10.1117/12.2062165
Ariza, A. , Irizar, M.R. , & Bayer, S. (2018). Empirical line model for the atmospheric correction of sentinel-2A MSI images in the Caribbean Islands. European Journal of Remote Sensing , 51(1), 765–776. doi:10.1080/22797254.2018.1482732
Chen, L., Jing, Y., Zhang, P., & Hu, X. (2016). Analysis of aerosol properties derived from sun photometer and lidar over Dunhuang radiometric calibration site. Remote Sensing of the Atmosphere, Clouds, and Precipitation VI. doi:10.1117/12.2228016
Farhad, M. M., Kaewmanee, M., Leigh, L., & Helder, D. (2020). Radiometric Cross Calibration and Validation Using 4 Angle BRDF Model between Landsat 8 and Sentinel 2A. Remote Sensing, 12(5), 806. doi:10.3390/rs12050806
Gao, C., Liu, Y., Liu, J., Ma, L., Wu, Z., Qiu, S., … Wang, N. (2020). Determination of the Key Comparison Reference Value from Multiple Field Calibration of Sentinel-2B/MSI over the Baotou Site. Remote Sensing, 12(15), 2404. doi:10.3390/rs12152404
Goryl, P., Nieke, J., Dransfeld, S., Mecklenburg, S., Berruti, B., Donlon, C., … Hoersch, B. (2017). Status of copernicus Sentinel-2A and Sentinel-3A optical calibration and validation activities. 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). doi:10.1109/igarss.2017.8126957
Helder, D., Markham, B., Morfitt, R., Storey, J., Barsi, J., Gascon, F., … Pahlevan, N. (2018). Observations and Recommendations for the Calibration of Landsat 8 OLI and Sentinel 2 MSI for Improved Data Interoperability. Remote Sensing, 10(9), 1340. doi:10.3390/rs10091340
Huryna, H., Cohen, Y., Karnieli, A., Panov, N., Kustas, W. P., & Agam, N. (2019). Evaluation of TsHARP Utility for Thermal Sharpening of Sentinel-3 Satellite Images Using Sentinel-2 Visual Imagery. Remote Sensing, 11(19), 2304. doi:10.3390/rs11192304
Huseynova, R. O. (2015). Two-Wavelength Method for Calibration of High-Precision Sun Photometer. Izvestiâ Vysših Učebnyh Zavedenij. Priborostroenie, 393–396. doi:10.17586/0021-3454-2015-58-5-393-396
Isbaex, C., & Margarida Coelho, A. (2021). The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review. Forest Biomass - From Trees to Energy. doi:10.5772/intechopen.93363
Kabir, S., Leigh, L., & Helder, D. (2020). Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review. Remote Sensing, 12(24), 4029. doi:10.3390/rs12244029
Karim, Z., & van Zyl, T. (2020). Deep Learning and Transfer Learning applied to Sentinel-1 DInSAR and Sentinel-2 optical satellite imagery for change detection. 2020 International SAUPEC/RobMech/PRASA Conference. doi:10.1109/saupec/robmech/prasa48453.2020.9041139
Li, Z., Li, K., Li, D., Yang, J., Xu, H., Goloub, P., & Victori, S. (2016). Simple transfer calibration method for a Cimel Sun–Moon photometer: calculating lunar calibration coefficients from Sun calibration constants. Applied Optics, 55(27), 7624. doi:10.1364/ao.55.007624
Liu, Y.-K., Ma, L.-L., Wang, N., Qian, Y.-G., Zhao, Y.-G., Qiu, S., … Li, C.-R. (2020). On-orbit radiometric calibration of the optical sensors on-board SuperView-1 satellite using three independent methods. Optics Express, 28(8), 11085. doi:10.1364/oe.388387
Müller, R. (2014). Calibration and Verification of Remote Sensing Instruments and Observations. Remote Sensing, 6(6), 5692–5695. doi:10.3390/rs6065692
Nedkov, R. (2018). Quantitative Assessment of Forest Degradation after Fire Using Ortogonalized Satellite Images from Sentinel-2. doi:10.7546/grabs2018.1.11
Obata, K., Tsuchida, S., & Yoshioka, H. (2018). Evaluating radiometric calibration of ASTER VNIR band with Terra MODIS, Landsat 7 ETM+, and Landsat 8 OLI. Earth Observing Missions and Sensors: Development, Implementation, and Characterization V. doi:10.1117/12.2324419
Phiri, D., Simwanda, M., Salekin, S., Nyirenda, V., Murayama, Y., & Ranagalage, M. (2020). Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing, 12(14), 2291. doi:10.3390/rs12142291
Read, J. M., & Torrado, M. (2009). Remote Sensing. International Encyclopedia of Human Geography, 335–346. doi:10.1016/b978-008044910-4.00508-3
Read, J. M., Chambers, C., & Torrado, M. (2020). Remote Sensing. International Encyclopedia of Human Geography, 411–422. doi:10.1016/b978-0-08-102295-5.10589-x
Soltani, S. R., Monavari, S. M., & Mahiny, A. S. (2011). Urban land use management, based on GIS and multicriteria assessment (Case study: Tehran Province, Iran). 2011 International Conference on Multimedia Technology. doi:10.1109/icmt.2011.6001730
Szantoi, Z., & Strobl, P. (2019). Copernicus Sentinel-2 Calibration and Validation. European Journal of Remote Sensing, 52(1), 253–255. doi:10.1080/22797254.2019.1582840
Xu, Y., Feng, L., Zhao, D., & Lu, J. (2020). Assessment of Landsat atmospheric correction methods for water color applications using global AERONET-OC data. International Journal of Applied Earth Observation and Geoinformation, 93, 102192. doi:10.1016/j.jag.2020.102192
Yang, A., Zhong, B., Hu, L., Wu, S., Xu, Z., Wu, H., … Liu, Q. (2020). Radiometric Cross-Calibration of the Wide Field View Camera Onboard GaoFen-6 in Multispectral Bands. Remote Sensing, 12(6), 1037. doi:10.3390/rs12061037