Abstract
Atmospheric correction is a critical pre-processing step required in quantitative remote sensing applications such as extraction of biophysical variables and multi-temporal analysis. The objective of this study was to evaluate surface reflectance of atmospheric correction methods base on scene-based empirical namely Dark Object Subtraction (DOS) and the radiative transfer methods namely the Second Simulation of Satellite Signal in the Solar Spectrum (6S). We applied these methods to Sentinel-2 images above rice fields in Cianjur and Klaten Regency, and compared surface reflectance from atmospheric correction methods with ground measured reflectance base on spectral response and vegetation indices (NDVI, EVI, SAVI and MSAVI). For that purpose, generative phase of rice growth was analysed by using statistical analysis. The result showed that the 6S method has better accuracy than DOS and varies on each bands.
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