Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land
Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2010-06-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/10/7/6421/ |
| _version_ | 1798025600656474112 |
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| author | Cristiana Bassani Rosa Maria Cavalli Stefano Pignatti |
| author_facet | Cristiana Bassani Rosa Maria Cavalli Stefano Pignatti |
| author_sort | Cristiana Bassani |
| collection | DOAJ |
| description | Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. |
| first_indexed | 2024-04-11T18:21:31Z |
| format | Article |
| id | doaj.art-e6ed1d78047144cda85fa363c1c26aeb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:21:31Z |
| publishDate | 2010-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e6ed1d78047144cda85fa363c1c26aeb2022-12-22T04:09:45ZengMDPI AGSensors1424-82202010-06-011076421643810.3390/s100706421Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over LandCristiana BassaniRosa Maria CavalliStefano PignattiQuantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness.http://www.mdpi.com/1424-8220/10/7/6421/atmospheric radiative transferaerosol optical thicknessatmospheric correctionhyperspectral remote sensingreflectanceremote sensing |
| spellingShingle | Cristiana Bassani Rosa Maria Cavalli Stefano Pignatti Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land Sensors atmospheric radiative transfer aerosol optical thickness atmospheric correction hyperspectral remote sensing reflectance remote sensing |
| title | Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land |
| title_full | Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land |
| title_fullStr | Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land |
| title_full_unstemmed | Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land |
| title_short | Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land |
| title_sort | aerosol optical retrieval and surface reflectance from airborne remote sensing data over land |
| topic | atmospheric radiative transfer aerosol optical thickness atmospheric correction hyperspectral remote sensing reflectance remote sensing |
| url | http://www.mdpi.com/1424-8220/10/7/6421/ |
| work_keys_str_mv | AT cristianabassani aerosolopticalretrievalandsurfacereflectancefromairborneremotesensingdataoverland AT rosamariacavalli aerosolopticalretrievalandsurfacereflectancefromairborneremotesensingdataoverland AT stefanopignatti aerosolopticalretrievalandsurfacereflectancefromairborneremotesensingdataoverland |