Willem J. Marais

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Time series derived from the first two spectral bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product can be modelled as a pair of triply (mean, phase and amplitude) modulated cosine functions. This paper proposes a meta-optimization approach for setting the parameters of the non-linear Extended Kalman Filter to(More)
This paper describes an atmospheric lidar photon-limited imaging problem in which observations are contaminated with Poisson noise. The observations are a nonlinear function of two spatially varying physical parameters. The first parameter, called the transmittance, is known to be a bounded monotonic non-increasing function. The second parameter, called the(More)
The extraction of information on land cover classes using unsupervised methods has always been of relevance to the remote sensing community. In this paper a novel criterion is proposed which extract the inherent information in an unsupervised fashion from a time series. The criterion is used to fit a parametric model to a time series and derive the(More)
In this paper the Bias Variance Search Algorithm is proposed as an algorithm to optimize a candidate set of initial parameters for an Extended Kalman filter (EKF). The search algorithm operates on a Bias Variance Equilibrium Point criterion to determine how to set the initial parameters. The candidate set is then used by the EKF to estimate state parameters(More)
Atmospheric lidar observations provide a unique capability to directly observe the vertical column of cloud and aerosol scattering properties. Detector and solar-background noise, however, hinder the ability of lidar systems to provide reliable backscatter and extinction cross-section estimates. Standard methods for solving this inverse problem are most(More)
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