The use of remotely sensed ground based phenomena of the Earth using satellite sensors has become a standard technique for both qualitative and quantitative scientific studies. However, the data obtained is complicated due to the presence of a variable atmosphere between the satellite sensor and the target on Earth. Atmospheric phenomena like scattering and absorption play significant roles in perturbing the radiation received by sensor. Hence, there is a need to mitigate or correct for these atmospheric effects. Various forms of Radiative Transfer Code (RTC) are widely used for atmospheric correction. The remote sensing community generally uses one of the two most common forms of atmospheric correction code to correct the raw sensor data. These two are: Second Simulation of Satellite Signal in Solar Spectrum (6S) and MODerate resolution TRANsmission (MODTRAN). In the study presented here 6Sv4.1 and MODTRAN 5 are compared through predicted TOA reflectances for sets of inputs as nearly identical to one another as possible. This study included the use of true hyperspectral ground data for a maintained vegetated grass site and for a desert. The percentage difference between the two models as evaluated for different sensors and ground sites in simulated TOA reflectance relative to the 6S predicted reflectance is calculated. Using the in-band spectral responses in conjunction with the actual ground measurements for Landsat 5 TM and AWiFS bands and the simulated spectra, the difference has been estimated multispectrally for each band of these sensors. In addition to this, spectral filter shifts which affects on the in-band response of the satellite sensor are also studied. The filters on the detectors of satellite sensors can shift spectrally during its time on-orbit due to various reasons like launch condition, ageing, coating thickness etc. For this study, an assumed set of worst case shifts for the RSRs of mid-resolution sensors like Landsat 5 TM, Landsat 5 MSS, Landsat 7 ETM+ and AWiFS is simulated. Then, the absolute effect of the shift on 6S and MODTRAN predicted TOA reflectance for vegetated and desert sites is determined. The results show that the differences between 6S and MODTRAN predicted TOA reflectance is higher towards the Shortwave Infrared (SWIR) bands and lower towards the Visible Near-Infrared (VNIR) bands. The percentage difference in the VNIR bands for vegetated and desert sites are within 3% and 2%, respectively. The differences in SWIR bands for vegetated and desert site are within 6% and 4.5%, respectively. However, the absolute difference is within 0.01 reflectance units for cleaner channels (especially in visible bands). The uncertainty in reflectance due to spectral shift for all the sensors studied is within 1.3%. The difference observed in the uncertainty for the 6S and MODTRAN predicted reflectance is within 0.08% which is very small compared to the total uncertainty, so it is concluded that both 6S and MODTRAN are equally sensitive to the spectral shift effect.
","abstract_html":"<p>The use of remotely sensed ground based phenomena of the Earth using satellite sensors has become a standard technique for both qualitative and quantitative scientific studies. However, the data obtained is complicated due to the presence of a variable atmosphere between the satellite sensor and the target on Earth. Atmospheric phenomena like scattering and absorption play significant roles in perturbing the radiation received by sensor. Hence, there is a need to mitigate or correct for these atmospheric effects. Various forms of Radiative Transfer Code (RTC) are widely used for atmospheric correction. The remote sensing community generally uses one of the two most common forms of atmospheric correction code to correct the raw sensor data. These two are: Second Simulation of Satellite Signal in Solar Spectrum (6S) and MODerate resolution TRANsmission (MODTRAN). In the study presented here 6Sv4.1 and MODTRAN 5 are compared through predicted TOA reflectances for sets of inputs as nearly identical to one another as possible. This study included the use of true hyperspectral ground data for a maintained vegetated grass site and for a desert. The percentage difference between the two models as evaluated for different sensors and ground sites in simulated TOA reflectance relative to the 6S predicted reflectance is calculated. Using the in-band spectral responses in conjunction with the actual ground measurements for Landsat 5 TM and AWiFS bands and the simulated spectra, the difference has been estimated multispectrally for each band of these sensors. In addition to this, spectral filter shifts which affects on the in-band response of the satellite sensor are also studied. The filters on the detectors of satellite sensors can shift spectrally during its time on-orbit due to various reasons like launch condition, ageing, coating thickness etc. For this study, an assumed set of worst case shifts for the RSRs of mid-resolution sensors like Landsat 5 TM, Landsat 5 MSS, Landsat 7 ETM+ and AWiFS is simulated. Then, the absolute effect of the shift on 6S and MODTRAN predicted TOA reflectance for vegetated and desert sites is determined. The results show that the differences between 6S and MODTRAN predicted TOA reflectance is higher towards the Shortwave Infrared (SWIR) bands and lower towards the Visible Near-Infrared (VNIR) bands. The percentage difference in the VNIR bands for vegetated and desert sites are within 3% and 2%, respectively. The differences in SWIR bands for vegetated and desert site are within 6% and 4.5%, respectively. However, the absolute difference is within 0.01 reflectance units for cleaner channels (especially in visible bands). The uncertainty in reflectance due to spectral shift for all the sensors studied is within 1.3%. The difference observed in the uncertainty for the 6S and MODTRAN predicted reflectance is within 0.08% which is very small compared to the total uncertainty, so it is concluded that both 6S and MODTRAN are equally sensitive to the spectral shift effect.</p>","abstract_has_math":false,"creators":["Sharma, Sanjog"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis - University Access Only","degree_discipline":"Electrical Engineering and Computer Science","degree_department":null,"school":null,"contributors":["Dennis Helder","David Aaron"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-01-01T08:00:00Z","date_published":"2012-01-01T08:00:00Z","updated_at":"2026-07-24T04:29:00Z","subjects":["Electrical and Computer Engineering","Remote Sensing"],"languages":["en"],"rights":["In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/
In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/
The use of remotely sensed ground based phenomena of the Earth using satellite sensors has become a standard technique for both qualitative and quantitative scientific studies. However, the data obtained is complicated due to the presence of a variable atmosphere between the satellite sensor and the target on Earth. Atmospheric phenomena like scattering and absorption play significant roles in perturbing the radiation received by sensor. Hence, there is a need to mitigate or correct for these atmospheric effects. Various forms of Radiative Transfer Code (RTC) are widely used for atmospheric correction. The remote sensing community generally uses one of the two most common forms of atmospheric correction code to correct the raw sensor data. These two are: Second Simulation of Satellite Signal in Solar Spectrum (6S) and MODerate resolution TRANsmission (MODTRAN). In the study presented here 6Sv4.1 and MODTRAN 5 are compared through predicted TOA reflectances for sets of inputs as nearly identical to one another as possible. This study included the use of true hyperspectral ground data for a maintained vegetated grass site and for a desert. The percentage difference between the two models as evaluated for different sensors and ground sites in simulated TOA reflectance relative to the 6S predicted reflectance is calculated. Using the in-band spectral responses in conjunction with the actual ground measurements for Landsat 5 TM and AWiFS bands and the simulated spectra, the difference has been estimated multispectrally for each band of these sensors. In addition to this, spectral filter shifts which affects on the in-band response of the satellite sensor are also studied. The filters on the detectors of satellite sensors can shift spectrally during its time on-orbit due to various reasons like launch condition, ageing, coating thickness etc. For this study, an assumed set of worst case shifts for the RSRs of mid-resolution sensors like Landsat 5 TM, Landsat 5 MSS, Landsat 7 ETM+ and AWiFS is simulated. Then, the absolute effect of the shift on 6S and MODTRAN predicted TOA reflectance for vegetated and desert sites is determined. The results show that the differences between 6S and MODTRAN predicted TOA reflectance is higher towards the Shortwave Infrared (SWIR) bands and lower towards the Visible Near-Infrared (VNIR) bands. The percentage difference in the VNIR bands for vegetated and desert sites are within 3% and 2%, respectively. The differences in SWIR bands for vegetated and desert site are within 6% and 4.5%, respectively. However, the absolute difference is within 0.01 reflectance units for cleaner channels (especially in visible bands). The uncertainty in reflectance due to spectral shift for all the sensors studied is within 1.3%. The difference observed in the uncertainty for the 6S and MODTRAN predicted reflectance is within 0.08% which is very small compared to the total uncertainty, so it is concluded that both 6S and MODTRAN are equally sensitive to the spectral shift effect.
"]},{"key":"dc:title","label":"Title","values":["A Comparison of Atmospheric Models MODTRAN and 6S Based on Top of Atmosphere Reflectances of Natural Targets as Applied to Selected Mid-resolution Sensors"]}]}],"canonical_facts":{"dc:contributor":["Dennis Helder","David Aaron"],"dc:creator":["Sharma, Sanjog"],"dc:date.available":["2017-07-27T07:00:00Z"],"dc:description.abstract":["The use of remotely sensed ground based phenomena of the Earth using satellite sensors has become a standard technique for both qualitative and quantitative scientific studies. However, the data obtained is complicated due to the presence of a variable atmosphere between the satellite sensor and the target on Earth. Atmospheric phenomena like scattering and absorption play significant roles in perturbing the radiation received by sensor. Hence, there is a need to mitigate or correct for these atmospheric effects. Various forms of Radiative Transfer Code (RTC) are widely used for atmospheric correction. The remote sensing community generally uses one of the two most common forms of atmospheric correction code to correct the raw sensor data. These two are: Second Simulation of Satellite Signal in Solar Spectrum (6S) and MODerate resolution TRANsmission (MODTRAN). In the study presented here 6Sv4.1 and MODTRAN 5 are compared through predicted TOA reflectances for sets of inputs as nearly identical to one another as possible. This study included the use of true hyperspectral ground data for a maintained vegetated grass site and for a desert. The percentage difference between the two models as evaluated for different sensors and ground sites in simulated TOA reflectance relative to the 6S predicted reflectance is calculated. Using the in-band spectral responses in conjunction with the actual ground measurements for Landsat 5 TM and AWiFS bands and the simulated spectra, the difference has been estimated multispectrally for each band of these sensors. In addition to this, spectral filter shifts which affects on the in-band response of the satellite sensor are also studied. The filters on the detectors of satellite sensors can shift spectrally during its time on-orbit due to various reasons like launch condition, ageing, coating thickness etc. For this study, an assumed set of worst case shifts for the RSRs of mid-resolution sensors like Landsat 5 TM, Landsat 5 MSS, Landsat 7 ETM+ and AWiFS is simulated. Then, the absolute effect of the shift on 6S and MODTRAN predicted TOA reflectance for vegetated and desert sites is determined. The results show that the differences between 6S and MODTRAN predicted TOA reflectance is higher towards the Shortwave Infrared (SWIR) bands and lower towards the Visible Near-Infrared (VNIR) bands. The percentage difference in the VNIR bands for vegetated and desert sites are within 3% and 2%, respectively. The differences in SWIR bands for vegetated and desert site are within 6% and 4.5%, respectively. However, the absolute difference is within 0.01 reflectance units for cleaner channels (especially in visible bands). The uncertainty in reflectance due to spectral shift for all the sensors studied is within 1.3%. The difference observed in the uncertainty for the 6S and MODTRAN predicted reflectance is within 0.08% which is very small compared to the total uncertainty, so it is concluded that both 6S and MODTRAN are equally sensitive to the spectral shift effect.
"],"dc:identifier":["https://openprairie.sdstate.edu/etd/1351"],"dc:language":["en"],"dc:rights":["In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/