Method for Landsat dense time series data format unification and surface reflectance conversion

Abstract

This paper introduces a program called landsat ecosystem disturbance adaptive processing system( LEDAPS) for the image stacks creation of the atmospherically corrected Landsat dense time series standard products from 1987 to 2011. Landsat images were first calibrated to top-of-atmosphere( TOA) reflectance by using solar zenith,Sun-Earth distance,TM or ETM+bandpass,and solar irradiance( using the MODTRAN solar output model). The interpolated aerosol optical thickness( AOT) which was interpolated spatially between the"dark dense vegetation( DDV) "using a spline algorithm,ozone,atmospheric pressure,and water vapor were supplied to the 6S radioactive transfer algorithm to convert TOA reflectance into ground surface reflectance for each30 m pixel. The algorithm was applied to the LEDAPS standard data of Landsat7 ETM+and non-standard data of Landsat5 TM to illustrate the data choice,data format unification and the algorithm implementation of the dense Landsat time series. Finally,a method for the validation of the corrected images was provided. The results show that the surface reflectance products resulting from the LEDAPS processing could effectively reduce the influence caused by ozone,water vapor,and aerosol particles in the atmosphere on the true image surface reflectance. The surface reflectivity is more precise and provides standard products for multiple scientific applications,such as land cover change or forest disturbance dynamic characterization and remote sensing based biophysical parameters retrieval,thus beneficial to formulating criteria for processing sequence image data in China.