A New Model-driven Correction Factor for Brdf Effects in Hrs Data

Interpretation of hyperspectral remotely sensed (HRS) imagery can be degraded by bi-directional reflectance distribution function (BRDF) effects that contribute an unknown amount of error to reflectance values. In this work we test a new empirical approach, using in-flight records concerning sensor and sun geometry at the time of acquisition, and laboratory BRDF measurements of selected land-cover classes from the new Israeli Goniometric Facility (IGF) at the remote sensing laboratory, Tel-Aviv University. BRDF datasets are then nadir-normalized (i.e. transformed to anisotropy), spectrally resampled to the required sensor and inverted to form correction vectors for the real imagery. These correction vectors are finally applied only to class-specific pixels of interest. We demonstrate this application for a non-georeferenced CASI image and four georeferenced HyMAP images and discuss results. The CASI data preliminary average anisotropy reaches ±20% and corrects down to ±5%. Its RMSE values are reduced by about 40-70%. HyMAP data Uses the same model and reduces average pre-correction ANIF by 25-50%, depending on wavelength. Since angular information about the sensor is the base for this correction, natural variability of the corrected land-cover classes is maintained. Therefore this method allows a class-specific BRDF correction that improves interpretation capability and quantitative analysis. INTRODUCTION Bi-directional reflectance distribution function (BRDF) effects in hyperspectral remotely sensed (HRS) data contribute an unknown amount of error to interpretation efforts. Accuracies of land cover classifications are affected, as well as quantitative estimates of physical parameters of landcover classes (e.g. vegetation and mineral indices, energy fluxes etc.). Previous works calibrate BRDF in HRS data by in situ measurements (i), use theoretical models for correction of these effects (ii,iii), or normalize mean column reflectance to nadir mean reflectance prior to geometric registration (iv). We suggest a new correction approach based on a set of laboratory BRDF measurements conducted at the Israel Goniometric Facility (IGF) recently built at the Remote Sensing Laboratory, at the University of Tel-Aviv (RSL-TAU). Radiometric quantities To understand the exact radiometric quantities that the IGF produces we relate to common values as starting points. With the intention of applying BRDF datasets to real imagery we normalize radiance differences between the image at the time of acquisition and the data in the laboratory. Reflectance, being the reflected energy flux divided by the incoming energy flux is a measure free of those differences. It relates to a set of reflected energy normalized to a full hemispherical set of directions. Following the standard definition of BRDF by Nicodemus (v) we have BRDF(φi,θi; φr,θr; λ)= L(φi,θi; φr,θr; λ)/ (L(φi,θi; λ)·sinθi·dw) (1) © EARSeL and Warsaw University, Warsaw 2005. Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy. New quality in environmental studies. Zagajewski B., Sobczak M., Wrzesień M., (eds)