Estimation of leaf area index from PROBA/CHRIS hyperspectral multi-angular data

Leaf Area Index (LAI) is a key structural and functional biophysical variable of the vegetated surfaces which is important in quantifying evapotranspiration rates and the energy exchange of terrestrial vegetation. Remote sensing offers a method of providing estimates of LAI through the analysis of the Bidirectional Reflectance Distribution Function (BRDF), an angular-dependent surface response. High-resolution, multi-angular and hyperspectral image data from PROBA/CHRIS (Project On-Board Autonomy/ Compact High Resolution Imaging Spectrometer) are used to estimate LAI. The retrieval of LAI is accomplished using the 1D turbid-medium canopy reflectance model, SAIL, coupled with the leaf reflectance model, PROSPECT REDUX. Look-up-tables are generated using scene-specific parameters required to invert the physically based model. Two experiments are performed to examine the contribution of multispectral versus hyperspectral reflectances (nadir direction) and single-look versus multi-look hyperspectral reflectances in deriving the LAI. Image data of the calibration/validation site at Chilbolton, Hampshire, UK are used for the inversion. In addition, ground measurements of LAI are compared with the retrieved LAI estimates. Retrieved LAI estimates using various spectral and directional sampling suggest that the spectro-directional reflectances from CHRIS provides more accurate results than their lower-resolution counterparts such as single-look and multispectral reflectances

The inter-comparison of AATSR dual-view aerosol optical thickness retrievals with results from various algorithms and instruments

The Advanced Along-Track Scanning Radiometer (AATSR) dual-view (ATSRDV) aerosol retrieval algorithm is evaluated for a single scene over Germany (49-53° N, 7-12° E) on 13 October 2005 by comparison of the aerosol optical thickness (AOT) at 550 nm with products from Multiangle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS), in addition to the Atmospheric Aerosol Retrieval using Dual-View Angle Reflectance Channels (AARDVARC) algorithm developed at Swansea University. The AOT was retrieved from the AATSR using the ATSR-DV algorithm, for the pixel size of 1 km × 1 km (at nadir). Then these values were meshed to be consistent with the sampling of the products from the other satellite instruments. The ATSR-DV results compare favourably with the products from orbiting optical instruments dedicated to aerosol retrieval, such as MODIS and MISR, which leads to the conclusion that AATSR is well suited for aerosol retrieval over land when the dual view is used with the ATSR-DV algorithm. © 2009 Taylor & Francis

Aerosol remote sensing over land: A comparison of satellite retrievals using different algorithms and instruments

International audienc