Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness

EVALUATION OF THE AEROSOL TYPE EFFECT ON THE SURFACE REFLECTANCE RETRIEVAL USING CHRIS/PROBA IMAGES OVER LAND

Surface reflectance has a central role in the analysis of land surface for a broad variety of agricultural, geological and urban studies. An accurate atmospheric correction, obtained by an appropriate selection of aerosol type and loading, is the first requirement for a reliable surface reflectance estimation. The aerosol type is defined by its micro-physical properties, while the aerosol loading is described by optical thickness at 550 nm. The aim of this work is to evaluate the radiative impact of the aerosol model on the surface reflectance obtained from CHRIS (Compact High Resolution Imaging Spectrometer) hyperspectral data over land by using the specifically developed algorithm CHRIS@CRI (CHRIS Atmospherically Corrected Reflectance Imagery) based on the 6SV radiative transfer model. Five different aerosol models have been used: one provided by the AERONET inversion products (used as reference), three standard aerosol models in 6SV, and one obtained from the output of the GEOS-Chem global chemistry-transport model (CTM). As test case the urban site of Bruxelles and the suburban area of Rome Tor Vergata have been considered. The results obtained encourages the use of CTM in operational retrieval and provides an evaluation of the role of the aerosol model in the atmospheric correction process, considering the different microphysical properties impact

Effect of the aerosol type selection for the retrieval of shortwave ground net radiation: case study using landsat 8 data

This paper discusses the aerosol radiative effects involved in the accuracy of shortwave net radiation, Rn.sw, with sw 2 (400–900) nm, retrieved by the Operational Land Imager (OLI), the new generation sensor of the Landsat mission. Net radiation is a key parameter for the energy exchange between the land and atmosphere; thus, Rn.sw retrieval from space is under investigation by exploiting the increased spatial resolution of the visible and near-infrared OLI data. We adopted the latest version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmospheric radiative transfer model implemented in the atmospheric correction algorithm (OLI Atmospherically-Corrected Reflectance Imagery (OLI@CRI)) developed specifically for OLI data. The values of Rn.sw were obtained by varying the microphysical properties of the aerosol during the OLI@CRI retrieval of both the OLI surface reflectance, roli pxl , and the incoming solar irradiance at the surface. The analysis of the aerosol effects on the Rn.sw was carried out on a spectrally-homogeneous desert area located in the southwestern Nile Delta. The results reveal that the Rn.sw available for energy exchange between the land and atmosphere reduces the accuracy (NRMSE ' 14%) when the local aerosol microphysical properties are not considered during the processing of space data. Consequently, these findings suggest that the aerosol type should be considered for variables retrieved by satellite observations concerning the energy exchange in the natural ecosystems, such as Photosynthetically-Active Radiation (PAR). This will also improve the accuracy of land monitoring and of solar energy for power generation when space data are used

Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness