Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps

Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures.     

3D Reconstrution with Rational Function Model

Rational Function Model (RFM) is the alternate sensor Model to the rigorous sensor model that allows end user to perform sensor-independent photogrammetric processing. Nowadays, commercial off-the-shelf (COTS) digital photogrammetric work stations have incorporated RFM as a method for image restitution. It is technically applicable to all types of airborne and space borne sensors. In this paper, we describe the derivations of the algorithmic procedure for third order inverse and forward RFM method for 3-D reconstruction. Model accuracy is evaluated for aerial image, TK-350 Russian image and IRS-1C PAN image. The results ensure that properly constructed RFM are accurate enough to be used in place of the original rigorous models. The test results are reported and summarised.     

Automated Target Detection and Discrimination Using Constrained Kurtosis Maximization

Exploiting hyperspectral imagery without prior information is a challenge. Under this circumstance, unsupervised target detection becomes an anomaly detection problem. We propose an effective algorithm for target detection and discrimination based on the normalized fourth central moment named kurtosis, which can measure the flatness of a distribution. Small targets in hyperspectral imagery contribute to the tail of a distribution, thus making it heavier. The Gaussian distribution is completely determined by the first two order statistics and has zero kurtosis. Consequently, kurtosis measures the deviation of a distribution from the background and is suitable for anomaly/target detection. When imposing appropriate inequality constraints on the kurtosis to be maximized, the resulting constrained kurtosis maximization (CKM) algorithm will be able to quickly detect small targets with several projections. Compared to the widely used unconstrained kurtosis maximization algorithm, i.e., fast independent component analysis, the CKM algorithm may detect small targets with fewer projections and yield a slightly higher detection rate.     

Population growth and the development of a central place system

This paper describes the spatial and functional evolution of a central place system as market conditions change with population growth. Utilizing a partial equilibrium optimization model, we examine the spatial response of two economic sectors to increases in market populations resulting from natural increase and migration. Response in both sectors is conditioned by threshold demand, with factor prices also affecting one of the sectors. As the central place system evolves it exhibits spatial and functional characteristics that are initially consistent with a Löschian landscape, then a Christallerian landscape at higher populations, while at even larger populations Krugman’s landscape emerges.     

Using a Grid-Based Filter to Solve InSAR Phase Unwrapping

This letter presents a phase-unwrapping (PU) algorithm for synthetic aperture radar interferometry based on a grid-based filter. The proposed PU algorithm, which is based on state-space techniques, simultaneously performs noise filtering and PU. The formulation of this technique provides independence from noise statistics and is not constrained by the nonlinearity of the problem. Results obtained with synthetic data show a significant improvement with respect to other conventional PU algorithms in some situations.