Estimating the Influence of Spectral and Radiometric Calibration Uncertainties on EnMAP Data Products—Examples for Ground Reflectance Retrieval and Vegetation Indices

Remote Sensing

Aliaksei Makarau¹  Martin Bachmann¹  Rudolf Richter¹  Karl Segl² 

[1] Earth Observation Center (EOC), German Aerospace Center (DLR), Münchener Str. 20,Weßling 82234, Germany;Helmholtz Center Potsdam, GFZ German Research Center for Geosciences,Remote Sensing Section, Telegrafenberg A17, Potsdam 14473, Germany;

关键词: EnMAP;    imaging spectroscopy;    hyperspectral;    uncertainty;    radiometric stability;    spectral stability;    atmospheric correction;   

DOI  :  10.3390/rs70810689

来源: DOAJ

【 摘 要 】

As part of the EnMAP preparation activities this study aims at estimating the uncertainty in the EnMAP L2A ground reflectance product using the simulated scene of Barrax, Spain. This dataset is generated using the EnMAP End-to-End Simulation tool, providing a realistic scene for a well-known test area. Focus is set on the influence ofthe expected radiometric calibration stability and the spectral calibration stability. Using a Monte-Carlo approach for uncertainty analysis, a larger number of realisations for the radiometric and spectral calibration are generated. Next, the ATCOR atmospheric correction is conducted for the test scene for each realisation. The subsequent analysis of the generated ground reflectance products is carried out independently for the radiometric and the spectral case. Findings are that the uncertainty in the L2A product is wavelength-dependent, and, due to the coupling with the estimation of atmospheric parameters, also spatially variable over the scene. To further illustrate the impact on subsequent data analysis, the influence on two vegetation indices is briefly analysed. Results show that the radiometric and spectral stability both have a high impact on the uncertainty of the narrow-band Photochemical Reflectance Index (PRI), and also the broad-band Normalized Difference Vegetation Index (NDVI) is affected.

【 授权许可】

Unknown