Mishra, MK; Rathore, PS; Misra, A; Kumar, R (2020). Atmospheric Correction of Multispectral VNIR Remote Sensing Data: Algorithm and Inter-sensor Comparison of Aerosol and Surface Reflectance Products. EARTH AND SPACE SCIENCE, 7(9), e2019EA000710.

Optical imaging satellites, such as SPOT and Cartosat-2S, provide visible/near infrared (VNIR) multispectral data at very high spatial resolution. The applications of these data sets are associated with precise mapping, monitoring, and change detection of Earth's surface, given that the measurements can be compensated for atmospheric effects. Existing atmospheric correction (AC) algorithms use visible and shortwave infrared channels and therefore cannot be used for AC of data from VNIR sensors. This article describes an algorithm for aerosol optical depth (AOD) retrieval and AC of VNIR imaging data. The AOD algorithm relies on the fact that for vegetated surfaces there exists a visible/NIR surface reflectance relationship due to the absorption of solar radiation by photosynthetic pigments in visible bands, while high reflectance in NIR bands governed by structural discontinuities in the leaves of healthy vegetation. We then describe how retrieved AOD is used to derive surface reflectance. To test the algorithm, the aerosol and surface reflectance products generated from 106 Cartosat-2S data sets are compared with MODIS-terra products. The algorithm significantly removes the haze from the images making surface feature visible. The comparison of Cartosat-2S and MODIS-terra AOD involving >1,500 data points shows good correlation of 0.95 with a relative difference of <= 25%. Similarly, the comparison of surface reflectance involving >4,500 data points shows good correlation ranging from 0.75 to 0.86 with a relative difference ranging from 24%to 37%. The normalized difference vegetation index shows a correlation of 0.89, with a relative difference of <= 18%. Results show that the given algorithm may be useful for AC of data from VNIR sensors.