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Papers by sandeep kumar Chittimalli

Research paper thumbnail of Sentinel-2/Landsat-8 product consistency and implications for monitoring aquatic systems

Remote Sensing of Environment, 2019

Research paper thumbnail of A reflectance-based cross calibration of the Landsat sensors

Earth Observing Systems XXII, 2017

First launched in 1972, the Landsat satellite sensors have provided the longest continuous record... more First launched in 1972, the Landsat satellite sensors have provided the longest continuous record of high quality images of the Earth’s surface that are used in both civilian and military applications. Extraction of quantitative information (e.g., surface reflectance) from the Landsat image data is only possible through an accurate absolute radiometric calibration. Typically, this calibration has been performed as a radiance-based cross-calibration between sensors. However, to convert radiance to reflectance, an accurate estimate of solar exoatmospheric irradiance is critical; and there are several solar models currently available which estimate exoatmospheric irradiance with varying levels of accuracy. Because of these inconsistencies in solar models, a TOA reflectance-based approach, independent of exoatmospheric irradiance, has been developed to provide a consistent cross-calibration of the Landsat series (from Landsat 8 OLI to Landsat 4 MSS), based on analysis of coincident and near-coincident scene pairs acquired with each sensor. The methodology uses Landsat-8 OLI reflectance measurements as the starting point (reference), as they are estimated with a 3% uncertainty (compared to the 5% uncertainty associated with radiance measurements). A set of radiometric calibration coefficients has been estimated based on the equations presented in this paper, which allows direct conversion of the digital numbers from the image data to TOA reflectance. The results obtained from application of these coefficients show significant improvement in consistency of reflectance measurements among the Landsat sensors.

Research paper thumbnail of Reflectance-based calibration and validation of the landsat satellite archive

REFLECTANCE-BASED CALIBRATION AND VALIDATION OF THE LANDSAT SATELLITE ARCHIVE SANDEEP KUMAR CHITT... more REFLECTANCE-BASED CALIBRATION AND VALIDATION OF THE LANDSAT SATELLITE ARCHIVE SANDEEP KUMAR CHITTIMALLI 2016 The primary objective of this project was to consistently calibrate the entire Landsat series to a common reflectance scale by performing cross-calibration corrections from Landsat-8 OLI to Landsat1 MSS. A consistent radiance-based calibration was already performed from Landsat-8 OLI through Landsat-1 MSS using bright targets and dark targets. The MSS radiance-based calibration results showed an uncertainty of about ±5%. Typically to convert from radiance to reflectance a solar model is used. Unfortunately, there are numerous solar models, all with various levels of accuracies. It was also seen that there is a data format inconsistency for different types of MSS data that impact the radiometric uncertainty of the products when compared to Landsat-8 OLI data. One of the advances Landsat-8 OLI has over to earlier missions is a solar model independent reflectance calibration. He...

Research paper thumbnail of Sentinel-2/Landsat-8 product consistency and implications for monitoring aquatic systems

Remote Sensing of Environment, 2019

Research paper thumbnail of A reflectance-based cross calibration of the Landsat sensors

Earth Observing Systems XXII, 2017

First launched in 1972, the Landsat satellite sensors have provided the longest continuous record... more First launched in 1972, the Landsat satellite sensors have provided the longest continuous record of high quality images of the Earth’s surface that are used in both civilian and military applications. Extraction of quantitative information (e.g., surface reflectance) from the Landsat image data is only possible through an accurate absolute radiometric calibration. Typically, this calibration has been performed as a radiance-based cross-calibration between sensors. However, to convert radiance to reflectance, an accurate estimate of solar exoatmospheric irradiance is critical; and there are several solar models currently available which estimate exoatmospheric irradiance with varying levels of accuracy. Because of these inconsistencies in solar models, a TOA reflectance-based approach, independent of exoatmospheric irradiance, has been developed to provide a consistent cross-calibration of the Landsat series (from Landsat 8 OLI to Landsat 4 MSS), based on analysis of coincident and near-coincident scene pairs acquired with each sensor. The methodology uses Landsat-8 OLI reflectance measurements as the starting point (reference), as they are estimated with a 3% uncertainty (compared to the 5% uncertainty associated with radiance measurements). A set of radiometric calibration coefficients has been estimated based on the equations presented in this paper, which allows direct conversion of the digital numbers from the image data to TOA reflectance. The results obtained from application of these coefficients show significant improvement in consistency of reflectance measurements among the Landsat sensors.

Research paper thumbnail of Reflectance-based calibration and validation of the landsat satellite archive

REFLECTANCE-BASED CALIBRATION AND VALIDATION OF THE LANDSAT SATELLITE ARCHIVE SANDEEP KUMAR CHITT... more REFLECTANCE-BASED CALIBRATION AND VALIDATION OF THE LANDSAT SATELLITE ARCHIVE SANDEEP KUMAR CHITTIMALLI 2016 The primary objective of this project was to consistently calibrate the entire Landsat series to a common reflectance scale by performing cross-calibration corrections from Landsat-8 OLI to Landsat1 MSS. A consistent radiance-based calibration was already performed from Landsat-8 OLI through Landsat-1 MSS using bright targets and dark targets. The MSS radiance-based calibration results showed an uncertainty of about ±5%. Typically to convert from radiance to reflectance a solar model is used. Unfortunately, there are numerous solar models, all with various levels of accuracies. It was also seen that there is a data format inconsistency for different types of MSS data that impact the radiometric uncertainty of the products when compared to Landsat-8 OLI data. One of the advances Landsat-8 OLI has over to earlier missions is a solar model independent reflectance calibration. He...

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